Journal Articles - SAE Mobilus

SAE journals provide rigorously peer-reviewed, archival research by subject matter experts--basic and applied research that is valuable to both academia and industry.

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Comparison of Two Distinct Automatic Emergency Braking Control Strategies for Heavy Vehicles02-20-01-00049/2/2026
Research on automatic emergency braking (AEB) control algorithms for heavy vehicles is relatively limited. Compared with passenger cars, heavy vehicle AEB algorithms must accommodate both unloaded and fully loaded conditions, with the latter posing higher demands. This study compares two distinct AEB control strategies: the time-to-collision (TTC) algorithm and the professional driver fitted (PDF) algorithm. Using simulation analyses under three regulatory-recommended scenarios—stationary lead vehicle, slow-moving lead vehicle, and decelerating lead vehicle—the results indicate that the PDF-based control system better adapts to both unloaded and fully loaded conditions. It demonstrates significant improvements in braking performance and robustness compared to the TTC-based system. For an unloaded vehicle equipped with the PDF–AEB control system (5500 kg), the final gap to the lead vehicle is the longest (11.5 m) under the scenario of a stationary lead vehicle with an initial ego vehicle speed of 80 km/h and the shortest (3.1 m) under the scenario of a lead vehicle with an initial speed of 50 km/h braking at 0.4 g. For a fully loaded vehicle (12,500 kg), the corresponding final gaps to the lead vehicle are 11.2 m and 2.5 m, respectively.
Lai, Fei, Huang, Chaoqun
An Effective Pathway for Off-Road Tier 5 Emission Compliance03-19-08-00418/31/2026
Proposed Tier 5 off-highway emission regulations for the 19–56 kW engine class pose significant technical and economic challenges. Unlike larger platforms, where selective catalytic reduction (SCR) is the standard nitrogen oxide (NOX) control strategy, engines in this class face cost and packaging constraints that limit complex aftertreatment adoption. This article investigates whether a production Tier 4 diesel engine and its existing aftertreatment can meet proposed Tier 5 limits through calibration and minor hardware changes alone, without major redesign or SCR. The approach combined a cooled exhaust gas recirculation (EGR) strategy with start of injection (SOI) timing optimization to manage the NOX–particulate matter (PM) trade-off, using the stock diesel oxidation catalyst (DOC) and diesel particulate filter (DPF) system for particulate control. An EGR/SOI design-of-experiments (DOE) sweep identified an optimal calibration, validated over both the ramped modal cycle (RMC) and non-road transient cycle (NRTC) per Title 13 California Code of Regulations (CCR) Section 2423 for certification of variable-speed engines in this power category. Results indicate that the system can be a viable pathway of meeting upcoming Tier 5 final emission standards.
Patil, Shubham Vishwanath, Michlberger, Alexander, Bachu, Pruthvi R., Amaral Garcia, Herbert, Smith, Edward M.
Shimmy Dynamics Analysis of a Dual-Wheel Main Landing Gear Considering Side Stay Angular Coupling01-19-02-00078/31/2026
Main landing gear shimmy is jointly affected by tire forces, structural elasticity, damping, and geometric coupling. To investigate the influence of side stay angular coupling on shimmy stability, this article establishes a shimmy dynamic model of a dual-wheel main landing gear considering side stay angular coupling. Numerical continuation bifurcation analysis, Hopf bifurcation frequency mapping, and local sensitivity analysis are then employed to study its influence mechanism on stability boundaries, dominant modes, and multistable behavior. The results show that the horizontal inclination angle of the side stay introduces additional structural coupling between strut torsion and longitudinal bending, causing the longitudinal motion to evolve from a passive response into an important mode participating in shimmy instability. A small horizontal inclination angle can induce the coexistence of multiple stable periodic responses, whereas a larger inclination angle changes the connectivity of Hopf bifurcation curves and forms a new instability branch involving longitudinal motion. Further analysis indicates that adjusting the orientation angle to make the local horizontal inclination angle approach zero can weaken the direct structural coupling between torsion and longitudinal motion and reduce the sensitivity of the longitudinal response to variations in the horizontal inclination angle. These results indicate that the angular design of the side stay should comprehensively consider the coupling effect between the horizontal inclination angle and the orientation angle, so as to avoid multistability and mode transition induced by the side stay angular arrangement.
Wei, Jian, He, Jipeng, Zhang, Jiahao, Zhu, Shixing, Li, Shuangbao, Zhu, Hengjia
Objective Quantification of Harmonic Impulsive Sounds and Interval Prediction of Sound Quality in Hybrid Vehicle Engines10-11-01-00038/28/2026
Steady advancement is observed in global research on eco-friendly and sustainable transportation. Rapid technological evolution of hybrid electric vehicles (HEVs) is documented. Lower overall noise output and more compact structures are achieved in HEV engines relative to conventional internal combustion engines. The perceptibility of harmonic impulsive sounds is significantly enhanced by these design characteristics. A close correlation is observed between these acoustic phenomena and negative human auditory perceptions. These events are treated as a core focus for HEV noise, vibration, and harshness optimization. Accurate quantification of harmonic impulsive sounds is not achieved by conventional objective indicators. A favorable balance between reliability and accuracy is not established by existing subjective prediction models. Practical engineering applications of these methods are severely restricted. A novel objective quantification method for harmonic impulsive sounds is proposed in this study. The method is established based on time–frequency masking theory and tonal strength. Bench tests in a semi-anechoic chamber and subjective evaluation experiments with standardized rating scales are performed for data collection. Collected sound signals are decomposed through an integrated approach of wavelet transform and variational mode decomposition. Targeted feature extraction is completed for harmonic impulsive sounds. A quantitative index incorporating human auditory temporal and frequency masking effects is developed. The proposed index exhibits a significantly stronger correlation with subjective evaluation results than traditional objective metrics, confirming its superior ability to reflect actual perceived sound quality. An interval prediction model for sound quality evaluation is established based on support vector machines and kernel density estimation. Traditional objective metrics and the proposed index are introduced as key input parameters. Effective and reliable prediction of HEV engine noise subjective satisfaction is achieved by the model.
Lin, Xu, Liang, Xingyu, Shi, Zhiyuan
Design, Simulation, and Experimental Evaluation of an R290-Based Dual Secondary Loop Thermal Management System for Electric Vehicles14-15-03-00188/28/2026
The transition toward low global warming potential (GWP) refrigerants, driven by increasingly stringent environmental regulations and carbon reduction targets, has imposed new requirements on thermal management systems (TMSs) for electric vehicles (EVs). These systems must ensure efficient operation across a wide range of ambient conditions while maintaining high energy efficiency and environmental compatibility. Among potential alternatives, R290 (propane) has emerged as a promising natural refrigerant due to its favorable thermophysical properties and low environmental impact. In this study, an R290-based dual secondary loop TMS is proposed and evaluated for wide-temperature-range EV applications. A one-dimensional system model was developed using Dymola and validated through experimental testing on a dedicated performance test bench. TMS performance was investigated under multiple steady-state operating conditions, including high-load cooling, battery fast charging, and low-temperature heating, and benchmarked against a conventional R1234yf-based direct TMS. The results demonstrate that the R290-based dual secondary loop system achieves improved performance compared to a conventional R1234yf direct system, with a coefficient of performance (COP) increase of 4.29% under high-load cooling conditions at 43°C and up to 27.27% under high-load heating conditions at −10°C. Furthermore, under extreme low-temperature conditions (−18°C), the system delivers a heating capacity of 7 kW with a COP of 1.8, demonstrating strong low-temperature adaptability without the need for auxiliary heating. The results confirm that the proposed R290-based dual secondary loop system provides significant advantages in energy efficiency and wide-temperature adaptability, offering a promising solution for next-generation EVTMSs.
Zhang, Yunpeng, Mohammed, Mustafa Mudassir, Gu, Yiliang, Zhou, Guoliang
Development of Remote Cab Controller for Construction Machinery14-15-03-00178/27/2026
This article focuses on the research and development of a remote cab controller for pure electric loaders, aiming to address the threats posed by traditional loaders operating in harsh and hazardous environments to drivers’ health and safety. First, the functional requirements of the controller were analyzed, based on which the hardware design with a multicore microprocessor as the core was completed, featuring functions such as signal acquisition, controller area network (CAN) communication, and H-bridge driving. On this basis, a control algorithm framework for remote driving was developed, including modules for signal input, analysis and processing, and signal output. Detailed control strategies were formulated for key components: For the pedal sensor, algorithms for opening degree calculation, automatic zero-position calibration, and dual-signal redundant fault diagnosis were proposed; for the steering module, precise angle calculation and force feedback feel simulation were achieved; and for the electric control handle, a hysteresis control algorithm was developed to suppress shocks caused by overly fast operations. In addition, a hierarchical fault diagnosis mechanism was established to ensure system safety. To verify the controller performance, a complete remote driving system was built. Field test results show that the system exhibits good signal following and control responsiveness in terms of traveling and working functions. Efficiency tests indicate that the remote driving efficiency can reach 80% of that of in-person operation under short-term test conditions, demonstrating the technical feasibility and control effectiveness of the developed controller. While the prototype exhibits promising performance for pilot deployment, long-term reliability metrics such as mean time between failures (MTBF) remain to be validated through extended field operation.
Lu, Yueqi, Ji, Shaobo, Yu, Qiuye, Li, Meng, Xu, Haozhi, An, Meng
Study of Port Fuel Injection Engine Cold Start Unburned Hydrocarbons Reduction Using Computational Fluid Dynamics with a Reduced Iso-Octane Mechanism Considering Various Isomers and Thermal Decompositions03-19-04-00218/27/2026
A modeling study was performed to find solutions to reduce the unburned hydrocarbons during cold start of a PFI (port fuel injection) SI (spark ignition) engine. Through modeling, the root cause for the high unburned hydrocarbons of the baseline engine during cold start was found. The slow combustion, which is due to the high amount of exhaust gas flowing back into the intake port and then becoming trapped inside the cylinder, is the root cause. A new valve lift, which can reduce the internal residual by 26%, was designed. Along with a fuel amount decrease of 35%, the UHC (unburned hydrocarbons) before the three-way catalyst can be reduced by 40%. The exhaust temperature using the new valve lift design increases by 400°C, which improves the performance of the three-way catalyst for further reducing UHC. In addition to the adoption of the new valve lift, an active SAI (secondary air injection) strategy was also investigated. Modeling results show that SAI can promote secondary combustion in the exhaust pipes to increase exhaust temperature and thus is beneficial for further oxidizing unburned hydrocarbons. The amount of active SAI mass flow rate should be controlled to less than 25% of the intake air flow rate to avoid the cooling effect dominating over the oxidation process. The duration of SAI should be from EVO (exhaust valve opening) to IVO (intake valve opening). For combustion modeling, a newly reduced iso-octane chemical kinetic mechanism was developed using carbon flux analysis to extract major reaction pathways for a wide range of practical engine temperature conditions. In the new reduced mechanism, a skeletal sub-mechanism for species starting from iso-octane to C4 is coupled with a recently updated H2/O2/CO/C1–C4 detailed sub-mechanism. Including a reduced NOx (oxides of nitrogen) sub-mechanism, the final mechanism has 681 species and 3332 reactions. Before the new reduced iso-octane mechanism was used, it had been validated with available experimental data of ignition delay times, laminar flame speeds, and important species profiles in the literature. Both the investigation of PFI engine unburned hydrocarbons reduction under cold start operating conditions and the development of a reduced chemical mechanism are the objectives of this work.
Guo, Dongshao, Zhang, Licheng, Yang, Shiyou, Bourg, Cyrus, Sun, Yong, Abidin, Zainal, Lin, Shujun
Evaluation of the Isolation Efficiency of Quasi–Zero Stiffness Structure in Improving Seat Comfort of Different Commercial Vehicles02-20-01-00038/26/2026
Different commercial vehicles, such as the sunflower harvester, tracked vehicle, and vibratory roller, operate across off-road and on-road environments, often encountering rough and poorly maintained surface conditions. Thus, their comfort and working efficiency are very low. To solve this problem, a quasi–zero stiffness structure (QZSS) is investigated and added to traditional seat suspensions in the sunflower harvester, tracked vehicle, and vibratory roller to improve their comfort and working efficiency. From their established dynamic models, the isolating efficiencies and stabilities of QZSS are then analyzed in detail under different conditions of speed and seat mass. Reducing the root-mean-square values of the seat acceleration (aw) and displacement (zw) is used to evaluate the results. The research shows that the comfort of the sunflower harvester and vibratory roller is very poor compared with the tracked vehicle under the same simulation conditions. By adding QZSS to their seat suspension system, the values of {aw and zw} in the sunflower harvester, tracked vehicle, and vibratory roller are strongly reduced by {67.9% and 38.8%}, {54.7% and 23.9%}, and {65.4% and 34.3%} in comparison without QZSS. Therefore, the comfort of the three vehicle models is greatly improved in comparison without QZSS. Besides, QZSS improves the vibratory roller’s comfort better than the tracked vehicle, while QZSS improves the sunflower harvester’s comfort to be the best. These study results further strengthen the isolation efficiency of QZSS on different commercial vehicles. This contributes to providing more applicability of QZSS in real vehicle conditions.
Nguyen, Vanliem, Zhang, Li, Liu, Yaxi
Resilient Trajectory Tracking Static Output-Feedback Control for Automated Vehicles under Denial-of-Service Attacks10-11-01-00028/24/2026
The safety and reliability of autonomous vehicles are critically linked to network communication quality. Consequently, threats such as Denial-of-Service attacks pose significant risks by disrupting communication between essential components and jeopardizing driving safety. This article presents a robust trajectory tracking control method resilient to such attacks. Utilizing a Linear Parameter–Varying control framework, the method effectively addresses time-varying vehicle speeds and incorporates a norm-bounded strategy to manage tire behavior uncertainties. By employing a Static Output-Feedback scheme, it avoids the need of costly sensors while maintaining a straightforward control structure suitable for real-time implementation. Using Lyapunov’s method, we analyze the system stability under attack conditions, ensuring the controller remains robust against disturbances. The design of the resilient controller is formulated as a convex optimization problem with Linear Matrix Inequalities constraints. The effectiveness of the proposed controller is validated through co-simulation in MATLAB/CarSim®, where it outperforms several state-of-the-art controllers across different driving scenarios, maintaining consistent tracking performance despite varying attack severity levels.
Meléndez-Useros, Miguel, Viadero-Monasterio, Fernando, Nguyen, Anh-Tu, López-Boada, María Jesús
Performance and Emission Control Enhancement Using Green-Synthesized Additives in Diesel Engine03-19-04-00208/24/2026
Cashew nut shell oil–based biodiesel (BD) is an environmentally friendly and sustainable alternative energy source that can help decrease the depletion of fossil fuels and reduce environmental pollution. In this research, the BD extracted from cashew nut shell was enriched with green-synthesized nanoparticles with various blends and evaluated for its performance. The BD20A blend recorded the best thermal efficiency of the brake, 29.5%, which was a boost of about 20.4% over diesel when using a medium load of 2.7 kW. Furthermore, the decrease in brake-specific fuel consumption was 36.2%, and exhaust gas temperature improved by 26.1% due to enhanced combustion, indicating better combustion and utilization of heat. The BD10A and BD20A recorded a considerable decrease in emissions compared to diesel under full-load conditions, with carbon monoxide and hydrocarbons reducing by 35.7% and 33.3%, respectively, and a moderate increase of nitrogen oxides. Among the multi-objective optimization approaches, the Jaya algorithm exhibited the fastest convergence rate and identified the optimum operating condition that achieved the best trade-off between engine performance and exhaust emissions. BD blends, particularly BD20A, provide greater thermal performance and better combustion behavior as well as lower exhaust emissions, making them viable as green alternatives to the traditional diesel fuel.
Victor Soosai Irudayaraj, S., Thanigaivelan, V., Brucely, Y., Lenin, N.
Hierarchical Yaw–Roll Stability Control of Semi-Trailers Based on Joint Estimation of Equivalent Parameters02-20-01-00018/19/2026
Semi-trailers are widely used in highway freight transportation because of their large payload capacity and high transport efficiency. However, structural characteristics such as a high center of gravity (CG), heavy loads, and the dynamic coupling between the tractor and trailer make them prone to yaw instability and rollover under complex conditions. To solve these problems, this article proposes a hierarchical stability control architecture for semi-trailers based on the joint estimation of equivalent parameters. First, a six-degree-of-freedom (6-DOF) theoretical dynamic model is established. This model includes the lateral, yaw, and roll motions of both the tractor and trailer to provide desired reference states. Second, a parameter estimation method combining a genetic algorithm (GA) with a forgetting-factor recursive least squares (RLS) algorithm is designed. It dynamically identifies eight unknown equivalent parameters, specifically the tire cornering stiffness and suspension damping. Next, a hierarchical controller is developed. The upper layer uses model predictive control (MPC) to calculate the required additional yaw moments, while the lower layer allocates these moments through quadratic programming (QP) based on vehicle steering characteristics. Co-simulation results, evaluated using error metrics that compare control outputs directly against TruckSim reference outputs, show that the fusion GA-RLS method offers better accuracy and adaptability than a standalone GA. Furthermore, the stability controller prevents rollover in high-speed maneuvers and reduces peak state indicators by over 41.2% in low-speed scenarios. Robustness tests also confirm its effectiveness under low-adhesion road conditions and heavy payloads. Compared with a conventional fixed-parameter MPC, the proposed adaptive architecture improves key stability indicators by 19% to 25%, effectively enhancing the dynamic safety of semi-trailers.
Song, Dafeng, Ni, Lixin, Duan, Chaosheng, Zeng, Xiaohua
A Comprehensive Analysis of a Truck–Semi-Trailer Performance Based on Hierarchical Controller Design to Enhance Driver Comfort and Dynamic Stability02-20-01-00028/18/2026
This study presents an integrated suspension system to improve the ride quality and stability of semi-trailer truck vehicles. The system consists of both an Air/MR-controlled suspension on the driver’s seat and on the truck cab, and an active air main suspension for the truck to improve vehicle stability. All components are connected to the truck and semi-trailer via a series of coupled connections. An analysis of dynamic stability reveals how the truck’s motions affect slosh forces within the semi-trailer during operation. An experimental validation of the new Air/MR suspension damper, developed using ANSYS 2023 R1 Computational Fluid Dynamics (CFD) software, yielded results consistent with prior experimental evidence. The control strategy uses a hierarchical architecture in which an inverse LSTM network controls the MR damper, accurately following the damping forces generated by a higher-level RNN controller implemented in MATLAB. The RNN system adaptively adjusts the stiffness of the cab and driver seat suspension, isolating the cab from vibrations caused by uneven roads. The truck and trailer’s main air suspension uses LQR control, using state inputs to counteract vertical motions caused by road roughness and sloshing. An integrated nonlinear co-simulation model of the truck and semi-trailer—including the truck, sloshing trailer, nonlinear air springs, and CFD-based MR damper demonstrates the control system’s effectiveness. Simulation results compared with a passive suspension system show that the proposed integrated controlled suspension system significantly reduces the truck chassis bending moment, improves ride comfort (49.98%), reduces cab body displacement (63.60%), and increases dynamic stability (57.78%). Maximizing dynamic tire load due to slosh dynamics in both half-loaded and full-loaded tanks does not affect the effective dynamic stability of tire hopping at high frequencies because the stiffness coefficient is adaptively adjusted, thereby synchronizing disturbance rejection and long-term riding comfort in frequency-based control under different road conditions.
Gad, Ahmed Shehata
Evaluating the Applicability of Advanced Physical Vapor Deposition Coatings through Characterization and Dry Machining05-19-04-00318/18/2026
This study investigates the characterization and dry machining performance of advanced physical vapor deposition (PVD) aluminum titanium nitride (AlTiN) and aluminum chromium titanium nitride (AlCrTiN) coatings deposited using three techniques: cathodic arc evaporation (CAE), high-power impulse magnetron sputtering (HiPIMS), and scalable pulse power plasma (S3p). The coatings were evaluated for thickness, microstructure, surface roughness, coefficient of friction (CoF), adhesion strength, and microhardness. Among the tested coatings, the S3p-deposited AlCrTiN showed the best performance, exhibiting the highest microhardness (40 GPa), the strongest adhesion (108 N), and the lowest CoF (0.25), along with a defect-free microstructure. Under the selected dry turning condition of 150 m/min cutting speed, 0.15 mm/rev feed rate, and 0.7 mm depth of cut, the S3p-deposited AlCrTiN coating achieved a maximum tool life of 10,800 mm, nearly three times higher than the CAE-deposited AlTiN coating. In contrast, CAE coatings showed comparatively lower hardness and weaker adhesion, with minimum values of 25 GPa and 68 N for C1, along with higher CoF values of 0.58–0.60. Furthermore, AlCrTiN coatings produced by HiPIMS and S3p provided 20–30% longer tool life than AlTiN coatings under identical cutting conditions, highlighting the importance of deposition technique.
Sonawane, Gaurav Dinkar
Pelvis Lap Belt Engagement of Small-Sized Females in Frontal Impacts Using Seat-Integrated Restraints and Vehicle Seats for Alternative Seating Positions2026-22-00088/14/2026
Non-traditional vehicle seating postures challenge traditional occupant protection paradigms that promote pelvis lap belt engagement. Seat-integrated restraints may promote pelvis lap belt engagement in alternative seating postures but have not been evaluated with post-mortem human subjects (PMHS) in vehicle seats. The goal of this research was to perform three 38.8 g, 56 km/h frontal impact sled tests with small-sized female PMHS in a crash environment with a vehicle seat designed for alternative seating positions. PMHS pelvis kinematics, lap belt engagement, and submarining response were compared to that of the Hybrid III 5th female (HIII-5F) in the same environment. The seat was in the rearmost seat track position, reclined 40° from vertical, and incorporated a leg rest, which elevated the feet off the floor. A seat cushion airbag (SCAB), large passenger airbag (PAB), shoulder belt pretensioner (SB P/T), and seat-integrated belt (BIS) were incorporated into the testing environment. The SCAB restricted initial downward translation of the pelvis and induced 7.7°–11.8°of initial pelvis rearward rotation. Lap belt loading of the abdominal soft tissue occurred in each test via three distinct interactions: (1) initial pelvis lap belt engagement followed by pelvis fracture and subsequent submarining; (2) lack of initial pelvis engagement and direct abdominal loading; (3) initial pelvis lap belt engagement followed by submarining. In a matched test environment, the HIII-5F did not submarine nor reproduce the entire lap belt pelvis interactions observed by the PMHS. Future research must develop better tools for predicting lap belt engagement in alternative seating positions.
Newman, Rachel, Shin, Jeesoo, Sochor, Sara, Morgan, Neal R., Gepner, Bronislaw D., Kerrigan, Jason R., Kim, Yongtae, Kim, Sung Rae
Relevant vehicle front-end components for pedestrian laboratory testing to address real-world pedestrian injuries when struck by passenger vehicles with high hood heights2026-22-00098/14/2026
In the United States, pedestrian deaths account for 18% of roadway fatalities and have increased 78% since their lowest point in 2009. U.S. consumers are increasingly purchasing larger vehicles that are responsible for a disproportionate number of pedestrian injuries. This study examined a dataset of pedestrians struck by passenger vehicles in Michigan from 2015 to 2024 to identify the unique characteristics of the tallest vehicles, large SUVs and pickups, which are contributing to increased injury. Vehicle height was categorized as the hood leading edge (HLE) height compared with the estimated pedestrian hip and waist heights from anthropometric measures. Maximum abbreviated injury scale and injury sources by body region were tabulated for three vehicle height categories. Typical kinematic patterns were observed for each relative height category and the corresponding injury frequency and impact locations. For vehicles with high hood heights, head and torso injuries were commonly from the front of the vehicle —the grille, headlights, and HLE. In contrast, head injuries sustained when pedestrians were struck by medium-height and short vehicles were primarily from the vehicle hood and windshields. Even among the tallest vehicles where the bumper was much higher than the pedestrian’s knee, leg injuries from the vehicle bumper and valance were frequent, suggesting that evaluating these vehicle components is also necessary to address lower extremity injuries. This study identified the unique pedestrian impact locations associated with the tallest vehicles, which can help guide vehicle designers when considering impact attenuation strategies to reduce injury in crashes with pedestrians.
Mueller, Becky, Jermakian, Jessica
Review of Semi-Active Shock Absorption Mechanisms in Landing Systems01-19-02-00068/13/2026
Effective shock absorption is essential for maintaining stability during landing events. Aerospace systems traditionally rely on oleo-pneumatic struts, while robotic platforms utilize lightweight compliant joints for impact mitigation. Recent advances have shifted attention toward adaptive solutions, including magnetorheological and electrorheological dampers, which can adjust their damping characteristics in real time through sensor feedback and control algorithms. By integrating established mechanical design principles with advanced materials and intelligent control strategies, modern landing systems can achieve improved energy dissipation and enhanced performance under variable and unpredictable conditions. This work evaluates the transition from passive to adaptive shock absorption technologies by examining landing dynamics, the mechanical architectures of conventional and semi-active systems, and the control strategies that enable adaptive damping. The findings indicate that, although passive systems offer reliability and simplicity, they lack the adaptability required for highly variable environments, while semi-active systems provide enhanced performance through real-time modulation enabled by advanced control algorithms. However, challenges related to power requirements, system complexity, material durability, and long-term reliability continue to limit widespread implementation of adaptive technologies. Overall, this review highlights the limitations of passive designs, evaluates the tradeoffs between MR and ER damping technologies, examines the evolution of semi-active control strategies, and identifies the key technical barriers that must be addressed before adaptive shock absorption systems achieve broader operational adoption.
Shah, Rajesh, Patel, Parth, Mittal, Vikram
Experimental Study on the Combined Effects of Swirl and Inlet Offset on the Flow through an Automotive Catalyst Monolith Substrate03-19-04-00198/7/2026
Maldistributed flow within an automotive catalyst can cause reduced conversion efficiency, high pressure loss, and premature deactivation. However, packaging constraints often result in uneven flow distribution between the monolith channels, thus compromising design and, inevitably, performance of the device. Flow uniformity may be improved by the introduction of swirl upstream of the catalyst assembly, and in turbocharged applications the residual swirl from the turbine can serve that purpose. Indeed, low swirl has been shown to provide favorable flow uniformity in the monolith substrate in an axisymmetric flow setup. However, the automotive exhaust aftertreatment setups are seldom axisymmetric, and the combined effects of inlet swirl and offset on the flow profile through a monolith substrate are unknown. To address this gap, this study provides the first systematic experimental characterization of the coupled influence of inlet swirl and packaging-relevant inlet offset on flow development and uniformity in a sudden expansion catalyst assembly. Particle image velocimetry (PIV), wall pressure measurements, and hot-wire anemometry (HWA) are combined to link the upstream separation and recirculation structures to the velocity distribution downstream of the monolith. The results reveal a previously unreported swirl-dependent sensitivity to geometric asymmetry: under no-swirl and moderate-swirl conditions, flow uniformity is robust to inlet offset, varying by no more than 1.4%, whereas at low swirl the offset reduces uniformity by up to 8% at high mass flow rate. Increasing mass flow rate reduces uniformity by up to 15%, while swirl improves uniformity by up to 19% relative to axial flow. These findings demonstrate that improvements observed for swirl in axisymmetric assemblies cannot be assumed to transfer directly to offset geometries. Swirl intensity and inlet alignment must instead be considered as coupled design variables. The measurements also provide a benchmark dataset for validating computational fluid dynamics simulations before their application to production-type systems.
Rusli, Ijhar, Aleksandrova, Svetlana, Medina, Humberto, Benjamin, Stephen F.
Delay-Compensated Active Anti-Roll Bar of Tractor-Trailers Using Two-Dimensional Piston Pump Electro-Hydrostatic Actuators02-19-04-00278/5/2026
As tractor-trailers are essential to global logistics, their roll stability during emergency maneuvers is a critical safety concern. This paper presents a novel delay-compensated active roll control strategy for tractor-trailers using a two-dimensional piston pump electro-hydrostatic actuator (EHA). Unlike existing advanced strategies that assume ideal actuator behavior, this approach specifically targets the inherent response delay in high-tonnage applications. A detailed EHA model, including pump flow characteristics and hydraulic mechanics, was developed and validated through step response experiments. A seven-degree-of-freedom vehicle dynamics model and a model predictive controller were also constructed to compute the required anti-roll moment under emergency driving conditions. In order to address the EHA actuator’s response delay, a delay feedforward controller (DFC) was designed, integrating acceleration feedforward, feedback regulation, and delay disturbance estimation. TruckSim–Simulink co-simulations under double lane-change (DLC) maneuvers at 40 km/h, 60 km/h, and 80 km/h show that DFC improves displacement tracking and reduces peak trailer roll angle by up to 15% compared to a velocity-feedforward proportional-integral-derivative (VFPID) controller. It also enhances control efficiency, as evidenced by lower average motor speeds and pressure response of EHA. The system demonstrates high power-to-weight ratio and efficient tracking capabilities under dynamic conditions. Although active control provides limited benefit at low speeds, the proposed strategy effectively improves roll stability and driving safety under dynamic conditions.
Chen, Lijie, Yin, Yuming, Zeng, Yuhang, Ruan, Jian, Li, Hangqi, Sun, Peng
Machine Learning Approach for Bidirectional Modeling and Optimization of Inconel 625 Deposition in Wire Arc Additive Manufacturing05-19-04-00307/30/2026
Machine learning (ML) techniques are increasingly being applied to establish correlations between input parameters and key process responses in the wire arc additive manufacturing (WAAM) process. Despite their potential, there remains limited understanding of how to develop an integrated ML framework that simultaneously considers both the dataset characteristics and the modeling approach to ensure accurate and reliable predictions. The present study addresses this gap by developing an integrated ML framework to predict the deposition behavior of Inconel 625 in WAAM. To capture nonlinear system behavior, three ML methods, namely artificial neural network (ANN), support vector machine (SVM), and adaptive neuro-fuzzy inference system (ANFIS), were developed and systematically evaluated for predictive modeling and process optimization, considering deposited geometry, area, and efficiency as the key output characteristics. The input parameters, i.e., voltage, wire feed rate, torch travel speed, and shielding gas flow rate, were identified as critical factors influencing the deposition process. The datasets were preprocessed to remove noise and analyzed to extract relevant features that captured the intrinsic physical behavior of the process. Performances of the ML models were evaluated using a separate test dataset, and predictions were assessed through mean absolute percentage deviation (MAPD). Results demonstrated that integrated ML framework could accurately represent intricate interdependencies among process parameters on deposition outcomes, providing a robust method of predictive modeling and parametric process optimization for Inconel 625 deposition by WAAM process. The ANN model demonstrated satisfactory performance for forward modeling with MAPD values of 12.24, 14.87, and 11.91 for deposition geometry, deposition area, and deposition efficiency, respectively. For inverse modeling, the ANN accurately predicted key inputs from outputs, with MAPD values of 1.39, 18.91, 12.25, and 19.36 for voltage, wire feed rate, torch speed, and shielding gas flow rate, respectively. Bidirectional predictive modeling keeps to set operating conditions to achieve desired depositions and process automations.
Samanta, Avishek, Maji, Kuntal
Co-optimization of Energy Efficiency and Drivability for Dual-Motor Electric Commercial Vehicles: A Topology-Aware Hierarchical Approach02-19-04-00267/29/2026
Dual-motor architectures provide additional operating degrees of freedom for electric commercial vehicles (ECVs), but the integration of automated manual transmissions (AMTs) introduces torque discontinuities during gear-related mode transitions. Existing energy management strategies usually focus on steady-state efficiency optimization, while the mechanical feasibility of mode transitions is often considered separately or neglected. To address this issue, this study proposes a topology-aware hierarchical control framework for dual-motor ECVs. The framework combines an offline global efficiency map with an online transition-feasibility arbitration mechanism. In the offline layer, the energy-oriented operating mode and torque split are extracted over the vehicle-speed and wheel-torque domain. In the online layer, a topology-based transition matrix is used to identify mechanically singular mode transitions, and potentially torque-interrupting commands are re-routed through feasible bridge modes. The proposed method embeds powertrain topology constraints into the real-time implementation of an offline optimal map, thereby complementing conventional global optimization methods with transition-feasibility arbitration. Simulation results under the CHTC driving cycle show that the proposed strategy improves torque continuity during mode transitions while retaining most of the energy-saving benefit of the unconstrained efficiency-oriented strategy. Compared with the rule-based strategy, the proposed method reduces SOC-equivalent energy consumption by 10.7%, and recovers 65.5% of the DP-achievable energy-saving potential. Hardware-in-the-Loop (HIL) results further demonstrate that the proposed online arbitration logic can be executed within the controller sampling period.
Song, Dafeng, Chen, Lexin, Zeng, Xiaohua, Ni, Lixin
Simulation and Experimental Evaluation of a Vehicle–Road Cooperative Positioning Method in Global Navigation Satellite Systems (GNSS)-Denied Environments12-09-04-00297/29/2026
In complex urban environments, vehicle positioning based on Global Navigation Satellite Systems (GNSS) is prone to failure or accuracy degradation due to signal blockage and multipath effects. To address this issue, this article proposes a vehicle–road cooperative positioning method based on factor graph optimization for GNSS-denied environments and evaluates its performance through both simulation and real-vehicle experiments. In the proposed approach, road codes deployed on the road surface serve as absolute position references on the road surface, and high-precision vehicle position estimates are obtained in real time by fusing roadside positioning information with onboard sensor measurements using factor graph optimization. Furthermore, to reduce the experimental cost and development cycle of the vehicle–road cooperative positioning method, a performance simulation platform is developed based on the CARLA simulator, RoadRunner, and the CARLA-ROS (Robot Operating System) bridge for real-time communication between simulation and positioning modules. The platform supports road code generation and deployment, customized scenario construction, and positioning performance simulation, and a multi-objective optimization approach is employed to obtain an optimal deployment scheme for road code spacing. Finally, the effectiveness of the proposed vehicle–road cooperative positioning method is validated through both simulation and real-vehicle experiments. Real-vehicle experiments show that the proposed method reduces the average RMSE (Root Mean Square Error) by 26.6% compared with the ESKF (Error State Kalman Filter) baseline, achieving an RMSE of 0.25 m and a maximum error of 0.95 m at a vehicle speed of 60 km/h and a 10 m code spacing, thereby confirming decimeter-level continuous accuracy in GNSS-denied environments.
Shen, Chuanfu, Zhao, Zhiguo, Yan, Danshu, Ling, Yubin
Systematic Assessment of State-of-the-Art Approaches Available for Variable Camber Morphing01-19-01-00057/29/2026
Aerodynamicists around the globe are developing mechanisms and structures inspired by nature that enable variable camber morphing (VCM) for aerodynamic surfaces. The implementation of the VCM mechanism in an airplane wing enhances the performance and stability during various flight segments. The present review article is focused mainly on the up-to-date VCM methods in a qualitative as well as quantitative approach that are specific to Aircraft/unmanned aerial vehicle (UAV) wing configurations. Initial literature discussions are confined to the conventional mechanisms that enable VCM in different aircraft configurations and the added aerodynamic advantages such as lift enhancement, drag reduction, boundary layer separation, and flow control. However, those designs need either external shape optimization or internal structural refinements to ensure the factor of safety (FoS). The modern aviation industry is also focused on bioinspired technology because of the adaptive flying capabilities and stall-delay characteristics. Therefore, a review of bioinspired VCM methods that are assessed based on the aerodynamic potentials is sequentially organized in the article. Additionally, considerations are motivated by the application of various compliant structural patterns for VCM in the aircraft industry. The discussion indicates the prospective benefits of morphing toward the future of the Green Aviation industry.
Manjunath, S. V., Jini Raj, R.
Comparison of Female and Male Post Mortem Human Subject Kinematic Responses and Injuries in Rear-Facing Seat Configurations in High-Speed Frontal Impacts2026-22-00077/28/2026
This study investigates female post-mortem human subject (PMHS) responses and injuries, comparing them to previously published data from male PMHS tested at a change in velocity (delta-V) of 56 kph in high-speed rear-facing frontal- impact (HSRFFI) scenarios. Twelve small female PMHS were subjected to the same HSRFFI pulse. The subjects were positioned in reinforced production seats, identical to those from the previous male PMHS studies, and set to recline angles of either 25 or 45 degrees. Instrumentation was used to measure kinematics of the head, spine, pelvis, and ribs. Whole-body kinematics were recorded using motion capture. Female PMHS consistently showed lower head restraint, seatback, and lap belt loads compared to males across all test conditions (Bio Rank System [BRS] scores >1.0), with BRS scores for head restraint forces as high as 4.0. While head and T1 kinematics were consistent with males in all-belt-to-seat (ABTS) conditions (BRS < 1.0), significant differences were found in other body regions (BRS>1.0). Female PMHS had larger head forward rotation and smaller pelvis Z-axis displacement (less ramping) than males in the fixed D-ring (FDR) conditions, leading to major discrepancies (BRS>2.0). In addition, female chest deflection was smaller in one FDR condition (BRS=1.98), and tibia acceleration onset was earlier. Female PMHS sustained severe to critical rib fractures (Abbreviated Injury Scale [AIS]3-5) similar to males. However, five females in the FDR conditions and one in the ABTS condition sustained sacral fractures, an injury not seen in males. Females also had a higher frequency of lower extremity fractures (7 of 12) and vertebral body fractures (7 of 12) compared to males. These findings suggest that existing male PMHS data may not adequately predict responses and injury risks for female PMHS, emphasizing the need for female-specific biomechanical data to enhance safety tools and models in HSRFFI scenarios.
Kang, Yun-Seok, Baker, Gretchen H., Ramachandra, Rakshit, Marcallini, Angelo, Kwon, Hyunjung, Foster, Craig D., Moorhouse, Kevin, Agnew, Amanda M., Bolte, John H.
Model-Based Optimization and Evaluation of Hybrid Powertrains for Commercial Heavy-Duty Class 8 Truck Applications02-19-04-00257/27/2026
In an ever-evolving landscape of emission regulations, charging infrastructure, customer demands, fuel/energy costs and decarbonization goals, heavy-duty on-road vehicle manufacturers continue to evaluate alternative powertrain technologies. While most heavy-duty vehicle manufacturers now have battery electric vehicles (BEVs) in their portfolio, significant challenges of charging infrastructure, range anxiety, payload capacity reduction and upfront costs have contributed to their lower adoption rates. Plug-in hybrid electric vehicles (PHEVs) have significant potential of leveraging upcoming BEV infrastructure and component supply chains to reduce operating costs while still maintaining longer range and payload capacity benefits of conventional ICE powertrains. This article applies a model-based approach to evaluate multiple Class 7–8 heavy-duty powertrain configurations. A system-level (1D) model of the conventional diesel ICE-based truck was developed in GT-Suite and validated against on-road test data. Using the diesel ICE model as a baseline, system-level models for different hybrid configurations were adapted, and their powertrain architecture was optimized at the system level. Additionally, an equivalent consumption minimization strategy (ECMS) for energy management was also optimized for each of the hybrid powertrain configurations to maximize fuel efficiency and emission benefits. All the hybrid configurations were then compared against the conventional diesel ICE Class 8 truck in terms of performance (acceleration, top speed, gradeability and startability), fuel economy (real-world cycles and certification cycles), emissions, and range for long-haul applications. Unique to this approach is the simultaneous co-optimization of powertrain component sizing and supervisory control logic by utilizing a Genetic Algorithm–based optimization approach. Results indicate that all parallel hybrid architectures (P2, P2–P3, and P4) achieve performance (acceleration, top speed, gradeability, and startability) parity or improvement compared to baseline diesel architecture. P2-based architectures demonstrated a 12–14% improvement in fuel economy on representative real-world cycles when operating in a blended charge-depleting–charge-sustaining mode of operation, and a 4–6% improvement in fuel economy when operating in charge-sustaining mode alone. By quantifying these results across diverse topologies, this work addresses a significant research gap in the holistic evaluation of Class 8 hybrids, specifically, the trade-off between multi-speed electric drives, system-level mass increases, and real-world fuel economy, that remains underexplored in current literature.
Baburaj, Adithya, Paul, Sumit, Dhanraj, Fnu, Joshi, Satyum, Franke, Michael
Efficiency Modeling, Experimental Validation, and Machine Learning-Assisted Model Calibration of a Two-Speed E-Drive Transmission for Construction Equipment02-19-03-00197/27/2026
This study details the development and experimental validation of a high-fidelity one-dimensional (1D) simulation model for a two-speed transmission designed for off-road vehicles, such as tractors and backhoe loaders used in agricultural and civil engineering applications. The model, implemented in the AMESim platform from Siemens, integrates physics-based loss sub-models for all major components, including gears, bearings, seals, and fluid drag (churning) losses. After development, the model was rigorously validated against test bench data, with efficiency measurements taken across various speed, torque, and oil level combinations, demonstrating a strong correlation with experimental results. A detailed analysis enabled the quantification of the contribution of each loss mechanism, identifying the countershaft gears and input shaft bearings as the primary contributors. Furthermore, a Machine Learning (ML)–based calibration framework, employing Bayesian Optimization, was implemented to reduce discrepancies between simulation and experiment and to generate a synthetic dataset for the creation of fast-executing surrogate models. The study concludes that the proposed methodology constitutes an effective tool for efficiency analysis and optimization during early design stages, establishing a foundation for future integration with ML techniques and the development of digital twins.
Ferreira, Tiago Simao, Fallahi, Farzad, Kedziora, Slawomir, Hichri, Bassem, Kiefer, Jean-Daniel
Geometric Deep Learning–Based AI Framework for Nonlinear Crash Behavior of Extruded Rails15-19-03-00127/27/2026
Extruded Rails are critical energy-absorbing components in automotive structures designed to mitigate impact loads during the frontal collisions. Traditional crashworthiness design relies heavily on computationally expensive finite element simulations and iterative design exploration. This work proposes a machine learning–driven framework for rapid front extruded rails design using a trained geometric deep surrogate model. A design-of-experiments (DoE) was conducted by varying geometric parameters including width, height, and wall thickness of a thin-walled extruded rail structure. For each design variant, LS-DYNA simulations were performed to obtain performance metrics such as mean crush force and peak crush force. These simulation results were used to train an AI surrogate model capable of predicting crash responses directly from geometric parameters. The proposed approach significantly reduces computational cost by replacing repeated high-fidelity crash simulations with machine learning surrogate predictions. By enabling fast and accurate evaluation of crash response metrics, the workflow shortens design cycles and supports sustainability-driven crashworthiness assessment by reducing simulation resource usage. The framework establishes a scalable, simulation-driven engineering pathway across vehicle platforms and provides a foundation for future closed-loop, AI-assisted crash design workflows.
Kumar, Manik, Srinivasan, Sriram
3D Computational Fluid Dynamics Analysis of the Performance and Emissions of an Off-Highway Port Fuel Injection Hydrogen Engine03-19-04-00187/27/2026
To fulfil the global aspiration of achieving net-zero emissions, hydrogen as a fuel seems to be one of the promising candidates. High energy density per unit mass and zero carbonaceous emissions are the two salient advantages that hydrogen offers. In the present study, a set of detailed chemistry-based 3D CFD combustion simulation has been carried on a 3-cylinder turbocharged, water-cooled port fuel injection SI Hydrogen engine to understand its optimum air–fuel ratio, compression ratio, spark timing and combustion chamber geometry. The simulations have been conducted at the full load of the rated power and maximum torque engine rpms. During simulation, the λ zone for study is restricted between 2.1 and 2.7. Two different bowl geometries (spherical and cylindrical), with two compression ratio options (12 and 14) are explored in the simulations. While the spherical bowl seems to accommodate flame front better than the cylindrical bowl, the compression ratio of 12 is a safer choice to control the maximum rate of pressure rise (dp/dθ). At full load and rated speed, the indicated thermal efficiency drops by 7.7% as the λ swings from 2.1 to 2.7, whereas the indicated specific NOx and dp/dθ drop by 99% and 81%, respectively. Similarly, at full load and maximum torque RPM, the indicated thermal efficiency drops by 6.4% with λ swing from 2.1 to 2.7, whereas the indicated specific NOx and dp/dθ drop by 99% and 91%, respectively. Beyond λ = 2.4 NOx reaches almost to zero, however, at a compromise of the thermal efficiency. The dp/dθ remains well within the acceptable limit under this scenario. To account this trade-off between the performance and emission parameters, optimum λ zone has been found out to be between 2.3 and 2.5.
Satre, Santosh Dadasaheb, Mukherjee, Nalini Kanta, Kumar, Sanjeev, Nene, Devendra
An Updated Data-Driven Greenhouse Gas Emission Rate Analysis for Vehicle Comparisons Applied to Europe14-15-03-00167/25/2026
This study presents a data-driven lifecycle assessment (LCA) framework for evaluating greenhouse gas (GHG) emissions from passenger vehicles across European electricity systems. The analysis compares battery electric vehicles (BEVs), full hybrid electric vehicles (FHEVs), and internal combustion engine vehicles (ICEVs) using both conventional average electricity emissions factors and time-resolved marginal emissions, referred to as real charging emissions (RCE). Hourly generation and interconnector/cross-border flow data for 2023 from 29 European countries are processed to estimate consumption-based marginal emissions rates that account for grid dispatch behavior and cross-border electricity flows. The approach is applied to two vehicles where multiple powertrains are available on the same platform, the 2024 Hyundai Kona (available as a BEV, FHEV, and ICEV) and Peugeot 2008 (available as a BEV and ICEV), to isolate drivetrain-related lifecycle differences. Results show substantial divergence between average and marginal emissions estimates, with a mean absolute difference in BEV–FHEV lifecycle emissions of 31–36 g CO2 eq/km across Europe. In several countries with carbon-intensive marginal generation, including Poland and Cyprus, BEVs may exhibit higher lifecycle emissions than comparable hybrids, while low-carbon grids such as Norway, Sweden, and France provide large BEV advantages. Sensitivity analyses demonstrate the importance of transmission losses, temperature effects, electricity imports, and charging timing. These findings highlight the limitations of average grid emissions factors in vehicle LCAs and underscore the importance of geographically and temporally resolved data-driven electricity emissions when assessing electrified vehicle climate impacts.
Drew, Alfred, Burton, Tristan, Senecal, Kelly, Davy, Martin, Leach, Felix
Coupled Lateral–Longitudinal Trajectory Tracking Control for Autonomous Vehicles Based on Multi-Agent Reinforcement Learning12-09-03-00247/23/2026
Trajectory tracking control serves as the core operational component of autonomous vehicles, directly determining driving safety and passenger comfort by ensuring control precision and stability. To enhance the tracking accuracy and stability for autonomous vehicles, this study proposes a coupled lateral–longitudinal trajectory tracking controller based on multi-agent reinforcement learning. The framework first establishes a Model predictive controller (MPC) derived from vehicle dynamics, formulating the lateral control process as a Markov decision process. A reward function incorporating lateral error, heading error, and steering angle is designed, followed by the construction of a Deep Q-Network (DQN) Agent to optimize the prediction horizon of the MPC. Subsequently, a position–velocity dual-loop PID controller is developed for longitudinal control, with its parameter optimization strategy learned through a Deep Deterministic Policy Gradient (DDPG) Agent. The Extended State Observer (ESO) is incorporated to perform steering angle compensation for internal modeling errors and external disturbances. Co-simulation experiments are conducted in CarSim and MATLAB/Simulink, and the results demonstrate that the coupled controller achieves superior tracking accuracy and stability in both overtaking and lane-changing scenarios compared with the decoupled controller.
Kun, Feng, Jinxiang, Zhai, Li, Wenli
A Review of Physical and Digital Infrastructure Standards and Guidelines to Support Deployment of Automated Vehicles in Rural Environments12-09-04-00307/23/2026
Connected and Automated Vehicles (CAVs) represent a transformative innovation poised to revolutionize roadway transportation by leveraging automated driving systems equipped with advanced sensors, high-performance computing, and communication technologies. While urban areas are the primary focus of current CAV developments, rural transportation systems risk being left behind despite the significant benefits that CAVs can bring to these regions. This article, therefore, explores the physical and digital infrastructure requirements for the safe deployment of CAVs in rural areas, drawing insights from standards, recommendations, and guidelines developed by leading standard organizations. The study highlights the specific design of physical infrastructure, including traffic signs, traffic signals, and pavement markings, and digital infrastructure, including communication, sensing, and mapping, to ensure rural communities are effectively prepared to benefit from the potential of CAVs. As its primary contribution, this article provides a comprehensive review of existing standards and guidelines relevant to rural CAV deployment. By synthesizing guidance across multiple standard-setting organizations, this review delivers a structured analytical assessment of existing standards, revealing their limitations and misalignment with rural transportation contexts while highlighting emerging good practices. The article clarifies the applicability of current guidance to rural infrastructure, identifies systemic infrastructure-related failure modes, and informs context-aware planning considerations for efficient and scalable CAV deployment in rural areas.
Zakaria, Mohammed, Getahun, Tesfamichael, Tavasoli, Mahsa, Pandey, Venktesh, Sarrafzadeh, Abdolhossein, Karimoddini, Ali
Effect of Aftermarket Suspension Modifications on ADAS Functionality of Five Light Vehicles12-09-04-00317/15/2026
Advanced Driver Assistance Systems (ADAS) are increasingly prevalent in light vehicles, both in the United States and worldwide. Moreover, ADAS are steadily being incorporated into regulatory requirements globally. Like ADAS, the automotive aftermarket is also increasing in size and significance. As both ADAS and the aftermarket industry are growing, the effect of aftermarket modifications on ADAS functionality should be examined. However, there is very little information available in the public domain about the effect of aftermarket modifications on original equipment ADAS. This work is centered on a considerable research project that was conducted to address the knowledge gap at the intersection of ADAS and the aftermarket. The project investigates five light vehicles that are important to the aftermarket, including four pickup trucks and one sport-utility vehicle. It focuses solely on the effect of popular aftermarket suspension modifications, and it does not evaluate aftermarket ADAS equipment. Typical suspension modifications were applied to the test vehicles in five modification categories, including stock, lower kits, level kits, 3–4 in. lift kits, and 6 in. lift kits. Six ADAS test procedures were performed for the test vehicles, comprised of blind spot detection, crash imminent braking, lane departure warning, pedestrian automatic emergency braking, rear cross traffic alert, and traffic jam assist. The physical tests were developed based on National Highway Traffic Safety Administration (NHTSA) New Car Assessment Program (NCAP) written experimental procedures. Statistical hypothesis testing was performed for the purpose of determining if average measured dynamic responses varied in the modified vehicles compared to stock. The results show that vehicles modified with typical aftermarket modifications will likely retain their ADAS functionality, given the limitations of the small sample size of five vehicles. Vehicles with 6 in. lift kits are expected to exhibit greater variability in their dynamic responses compared to stock. Plans for future work and unanswered research questions are outlined, with the goal of advancing aftermarket ADAS integration and ensuring the safety and performance of modified vehicles.
Bastiaan, Jennifer M., Morales, Luis, Muller, Mike
ERRATUM: Ergonomic Assessment of Glove-Box Design in Passenger Vehicles for the Indian Scenario15-19-02-0009.17/15/2026
ERRATUM
Jujjavarapu, Sreeram, Rajakumaran, Sriram, Kota, Srinivas, Kotkunde, Nitin, Jasti, Naga Vamsi Krishna
Numerical Investigation of Inverted Airfoils in Ground Effect for Motorsport Applications01-19-01-00047/15/2026
Ground effect plays a critical role in enhancing the aerodynamic performance of race cars by increasing downforce without a proportional rise in drag. Despite its importance, the influence of airfoil geometry on inverted airfoils operating in ground proximity remains underexplored in open literature. This study addresses this gap through a detailed numerical investigation of chord-dominated ground effect using two-dimensional Reynolds-Averaged Navier–Stokes (RANS) simulations. A range of NACA four-digit airfoils is systematically analyzed to isolate the effects of camber, thickness, and camber location on aerodynamic performance in ground proximity. Results show that increased camber enhances downforce and efficiency both in and out of ground effect; thinner airfoils yield higher downforce and efficiency in ground effect; and forward camber locations outperform rearward ones in maximizing downforce contrary to out-of-ground-effect trends. Detailed pressure distribution and flow separation analyses explain the underlying mechanisms, offering actionable guidelines for optimizing ground effect airfoil design in motorsport.
Chowdhury, Rohan, Shukla, Dhwanil
On Disturbance-Aware Minimum-Time Trajectory Planning: Evidence from Tests on a Dynamic Driving Simulator10-10-03-00267/13/2026
This work aims to investigate how disturbance-aware, robustness-embedding reference trajectories translate into actual driving performance when executed by professional drivers in a dynamic driving simulator. The study compares three planned reference trajectories against a free-driving baseline (NO-REF) to assess the trade-offs between lap time (LT) performance and steering effort: NOM, the nominal time-optimal trajectory; TLC, a track-limit-robust, time-optimal trajectory obtained by tightening margins to the track edges; and FLC, a friction-limit-robust, time-optimal trajectory obtained by tightening against axle/tire saturation. All reference trajectories share the same minimum LT objective with a small steering-smoothness regularizer, and are evaluated with two professional drivers driving a high-performance car on a virtual track. The reference trajectories stem from a disturbance-aware minimum-LT framework recently proposed by some of the authors, where worst-case disturbance growth is propagated over a finite horizon and used to tighten tire-friction and track-limit constraints, preserving performance while delivering probabilistic safety margins. LT and steering energy (SE) are evaluated as indicators of driving performance and steering effort, respectively, while RMS values of lateral deviation, speed error, and drift angle are used to characterize driving style. The results reveal a Pareto-like trade-off between LT and SE: NOM achieves the shortest LT, but with the highest SE, TLC minimizes SE at the expense of longer LT, while FLC lies near the efficient frontier, markedly reducing SE relative to NOM with only a minor LT increase. Removing reference trajectories (NO-REF) leads to both higher SE and longer LT, confirming that trajectory guidance improves pace and control efficiency. Overall, the findings highlight reference-based and disturbance-aware planning, particularly the FLC variant, as effective tools for training and for achieving fast yet stable trajectories.
Masoni, Matteo, Palermo, Vincenzo, Gabiccini, Marco, Gulisano, Martino, Previati, Giorgio, Gobbi, Massimiliano, Comolli, Francesco, Mastinu, Gianpiero, Guiggiani, Massimo
Fuel Savings from Predictive Charge Control Based on Short-Trip Duration in Series Hybrid Electric Vehicles14-15-03-00157/10/2026
Series hybrid electric vehicles (HEVs) employ an electric motor for propulsion, while the internal combustion engine operates solely as a generator under energy-efficient speed and load conditions. Owing to this architecture, series HEVs can achieve high fuel efficiency with a relatively simple control structure. However, conventional energy management systems (EMSs) often prioritize battery state-of-charge (SOC) stabilization, which can lead to frequent engine start–stop operations and unnecessary fuel consumption, particularly in short-trip driving. This study aims to enhance energy management performance in series HEVs by optimizing engine power generation timing based on predicted short-trip duration. A computationally efficient, rule-based prediction model is developed using real-world driving data, in which short-trip duration is estimated from vehicle speed and acceleration. Due to its low computational load, the proposed model is suitable for implementation in an onboard electronic control unit (ECU). The proposed control strategy initiates engine power generation when the battery SOC is low and the predicted trip duration is long, and suppresses generation when the SOC is sufficiently high or the predicted trip is short. A detailed vehicle model incorporating an engine, generator, electric motor, inverter, and battery is developed in Modelica to evaluate the proposed strategy. Simulation results demonstrate that the proposed EMS significantly reduces the frequency of engine start–stop events, leading to fuel economy improvements of 3.6% under the WLTC (excluding the extra-high phase) and 13.4% in a real-world urban–rural driving cycle, compared with a commercialized baseline vehicle. These results confirm the effectiveness and practical applicability of the proposed EMS for passenger vehicle applications.
Mizushima, Norifumi, Sato, Akira, Kuboyama, Tatsuya, Moriyoshi, Yasuo
Steering System Fault Diagnosis and Fault-Tolerant Control of Active Wheel-Corner Electric Vehicles10-10-04-00367/9/2026
The Active Wheel-Corner (AWC) integrates driving, braking, steering, and suspension systems into the wheel end, forming a fully drive-by-wire, four-wheel independent steering and four-wheel independent driving (4WIS&4WID) vehicle platform. While improving vehicle control performance, the full by-wire architecture also places higher demands on system reliability and fault tolerance. The steer-by-wire system has electrical, communication, and software failure risks, which may cause the vehicle to lose steering capability and trigger severe traffic accidents. This article proposes a hierarchical active fault-tolerant control strategy based on fault information reconstruction (FAST-FTC), enabling fault diagnosis and active fault-tolerant control when the steer-by-wire system fails, effectively ensuring the steering maneuverability and lateral stability of the vehicle under fault conditions. First, the strategy designs an adaptive observer combined with the Dugoff tire model to estimate nonlinear tire forces, while introducing a fault factor to achieve quantitative grading of steering system faults. Second, a hierarchical controller is designed for steering system faults. The upper-level controller, based on Adaptive Super-Twisting Sliding Mode Control (AST-SMC), determines the generalized forces required to track the desired trajectory under different fault conditions. The lower-level controller, based on the Fault-Aware Model Predictive Control (FA-MPC) strategy, dynamically adjusts weight matrices according to the fault factor and tire reconstructed stiffness, coordinating the allocation of four-wheel driving and the steering of healthy wheels to ensure lateral stability. Finally, the effectiveness of the proposed active fault-tolerant control strategy is validated through Hardware-in-the-Loop (HIL) simulation and real-vehicle tests.
Xiao, Feng, Jiang, Yueyong, Cheng, Rui, Xu, Changhe, Tang, Xiangjiao, Gao, Fengling, Li, Jianhua
Crashworthiness of WC19 Wheelchairs in Vertical Dynamic Aircraft Seating Tests09-14-02-00047/9/2026
Currently, people who use wheelchairs are not permitted to use their own wheelchairs as seats on commercial aircraft. To advance equitable aircraft travel for these passengers, we need to determine whether wheelchairs would be safe seating for their occupants and not pose a safety hazard for other passengers in case of emergency landing. We hypothesized that wheelchairs meeting the voluntary standards for vehicle crashworthiness (Rehabilitation Engineering Society of North America [RESNA] Section 19 Wheelchairs Used as Seats in Motor Vehicles [WC19]) would be able to pass the Federal Aviation Administration (FAA) vertical crashworthiness standards for aircraft seating. Wheelchairs were secured using surrogate 4-point strap tiedowns using the geometry specified by WC19. The FAA Hybrid III anthropomorphic test device (FH3 ATD) was restrained by both the wheelchair-attached lap belt and a vehicle-mounted lap belt identified as necessary to pass FAA dynamic horizontal test requirements. For the dynamic vertical testing with the wheelchairs oriented 60 degrees relative to horizontal, modeling demonstrated the suitability of using the trapezoidal pulse achieved with the UMTRI sled produced rather than the typical triangular shaped FAA pulse. Of the five manual and three power wheelchairs tested, four had broken components that would not impede emergency exit, four did not have visible damage, and the FH3 remained within the seat in all tests. The three power wheelchairs did not meet lumbar compression requirements. Based on these results, it may be feasible for people to use their own WC19-compliant wheelchairs on aircraft when secured to the aircraft with 4-point strap tiedown systems, supplemented by an occupant lap belt anchored to the aircraft, notwithstanding the lumbar force requirement.
Manary, Miriam A., Orton, Nichole Ritchie, Vallier, Tyler, Boyle, Kyle J., Klinich, Kathleen DeSantis
A Framework for Precautionary Safety for Automated Driving Systems—Toward Tactical Decisions Fulfilling Quantitative Risk Acceptance Criteria12-09-04-00287/8/2026
Safety of Automated Driving Systems (ADSs) is arguably one of the main remaining barriers before widespread market deployment. While there exists a plethora of methods for planning a trajectory that fulfils certain constraints, what those constraints should look like, to enable effective planning of safe trajectories, is still being discussed. In this article, we generalize the concept of Precautionary Safety (PCS) and present a framework providing constraints on the tactical and operational decisions of the ADS. Such constraints consider the ADS’ capabilities, the external conditions, knowledge of statistically relevant events and behaviors of other traffic actors, as well as the controllability of these events. The proposed framework enables assessment of the statistical fulfilment of quantitative risk acceptance criteria (QRACs), including requirements on accident, injury, and fatality rates. The framework further provides a means to dynamically adapt the constraints used for trajectory planning, i.e., to adapt the driving to the situation at hand. A case study, considering a possible collision scenario with a jaywalking pedestrian and a rear-end collision with a trailing vehicle, is provided to showcase the applicability and usefulness of the presented framework. The simulation-based case study displays the safety benefits from considering QRACs with multiple injury risk levels and further shows how the proposed PCS framework can be applied in practice.
Gyllenhammar, Magnus, de Campos, Gabriel Rodrigues, Sandblom, Fredrik, Törngren, Martin, Fredriksson, Jonas
Average-Differential-Coordinates-Based Variable Slip Ratio Control of Electrified Vehicles with Torque Vectoring Differential10-10-04-00357/7/2026
These days, the vehicle dynamics control of electric vehicles (EVs) with multi-actuated architectures has been widely investigated. Such EVs have a torque vectoring differential (TVD), which can generate a torque difference between the left and right wheels. As one of TVDs, a two-motor-torque difference amplification mechanism (TDA-TVD), has been proposed. The TDA-TVD can generate a greater torque difference compared to an individual-wheel-drive (IWD) system. However, it has controllability difficulties due to its two resonance modes. Previous studies first proposed a frequency response model of the TDA-TVD and anti-vibration feedforward torque controllers based on an average-differential coordinates (ADC) transformation. Subsequently, wheel speed control (WSC) and slip ratio control (SRC) based in the ADC were presented. However, only the WSC was designed with frequency domain analysis, and the SRC was designed with manual tuning. In this study, the closed loop of the SRC of the TDA-TVD is modeled in the frequency domain, and a parameter determination method based on Nyquist plot and sensitivity function analysis of the SRC, which is the outer loop of the WSC, is suggested. Next, several SRC strategies are proposed, depending on the driver’s preference. Lastly, experimental results using a real vehicle with the TDA-TVD on slippery surfaces are shown. Newly proposed and conventional SRCs are compared. The effectiveness of the proposed strategies is analyzed and presented.
Fuse, Hiroyuki, Fujimoto, Hiroshi, Sawase, Kaoru, Takahashi, Naoki, Takahashi, Ryota, Hayashi, Takayuki
A Multiphysics Approach to Mitigate Pulse-Width-Modulation-Induced Acoustic Noise in Permanent Magnet Synchronous Motor Drives for Electric Vehicles14-15-03-00147/3/2026
This article investigates high-frequency noise in permanent magnet synchronous motors (PMSMs) for electric vehicles, originating from pulse width modulation (PWM). A theoretical model is developed to formulate the phase voltage under space vector PWM (SVPWM), explicitly accounting for the additional harmonic components generated by the discrete-time voltage update in digital control systems. This derived voltage waveform serves as the excitation source in an electromagnetic finite-element model, from which the PWM current harmonics and their resulting high-frequency electromagnetic forces are computed. Critical components of the electromagnetic force are then extracted through two-dimensional Fourier transform. A structural model of the motor, incorporating practical assembly constraints, is established and validated by experimental modal tests on a fully assembled motor unit. To enable rapid noise prediction over the wide speed range, vibro-acoustic transfer functions are introduced. The predicted noise shows good agreement with experimental data. Leveraging this multiphysics model, the influence of switching frequency on noise characteristics is analyzed. The study identifies that avoiding excitation of the motor’s zero-order mode is critical for noise suppression. Accordingly, an optimal frequency-hopping strategy is proposed. Experimental validation confirms the strategy’s effectiveness in reducing noise over the wide speed range.
Lin, Fu, Chen, Yihui
The Influence of Spatial and Aspatial Factors on the Safety Driving Behavior of Motorcycle Couriers in the Gig-Economy Era: A Case Study of East Jakarta, Indonesia09-14-02-00057/3/2026
This study aims to analyze the impact of spatial and aspatial factors on the safety driving behavior of motorcycle couriers in East Jakarta within the context of the gig economy. Both factors are integrated to clarify how spatial conditions and individual characteristics jointly shape couriers’ safety driving behavior. The Partial Least Squares Structural Equation Modeling (PLS-SEM) method was employed to examine the relationship between spatial and aspatial factors on safety driving behavior. Data were collected through questionnaires from 253 motorcycle couriers operating in three subdistricts in East Jakarta, namely Cakung, Pasar Rebo, and Pulo Gadung. The results show that safety driving behavior is significantly influenced by aspatial factors, particularly socioeconomic characteristics and personality traits. In contrast, spatial factors such as road conditions and daily activity patterns do not directly influence safety driving behavior, but exert indirect effects through the couriers’ personality traits.
Wahyuddin, Yasser, Sitorus, Paldibo Alfriramson, Putri, Kharunia, Maharani, Garnierita
A Methodology for the Conversion from Physics-Based to Ultrafast-Running Data-Driven Powertrain Models for Real-Time Applications03-19-04-00177/3/2026
The virtualization of powertrain systems is a key enabler for modern powertrain development. While physics-based 0D/1D simulation models provide accuracy and interpretability, these models are typically computationally demanding, prolonging the development process and usage throughout the V-cycle. Moreover, achieving real-time-capable simulation models through model simplifications remains challenging, as it often leads to significant losses in accuracy. In contrast, data-driven approaches can achieve high computational efficiency without significantly compromising model accuracy. This opens the possibility for not only online control applications, such as model predictive control or reinforcement learning, but also for computational expensive offline control prototyping using ultrafast-running data-driven digital twins. This work focuses on the elaboration of a scalable methodology for the development of ultrafast-running powertrain models for stationary and transient engine operation. This includes the efficient generation of training data with great variance, data analysis, and preparation, an optimized partitioning method using the Jensen–Shannon distance, feature engineering, model training of a multilayer perceptron (MLP), a long short-term memory (LSTM), and gated recurrent unit (GRU) network, followed by the model evaluation using test data and the concluding model deployment. In order to demonstrate the concept, a calibrated 0D/1D model of a dual-fuel marine main engine provided by WinGD Ltd. for a pure car and truck carrier is utilized as the reference physics-based model. The case study provides a comprehensive examination of the development of ultrafast-running data-driven fuel consumption models in both stationary and transient engine operation. The results show that the proposed methodology yields robust results and minimizes the loss of accuracy to 1.80%–2.14% for the MLP predicting the steady-state fuel consumption and to 0.67%–0.96% (GRU) and 1.52%–1.68% (LSTM) for predicting the transient fuel consumption, while achieving a multiple 104-fold reduction of the real-time factor (RTF) on an identical CPU.
Weller, Louis, Zanelli, Alessandro, Yang, Qirui, Brutsche, Martin, Grill, Michael, Kulzer, André Casal
A Transition Curve-Based Design Method for the Recirculation Channel in Internal Recirculating Ball Screws15-19-03-00117/1/2026
Internal recirculating ball screws are widely used as linear motion components in automotive active safety systems, owing to their simple structure and compact size. The recirculation (or deflection) channel is a key feature that distinguishes this type from other ball screw designs. The objective of this article is to investigate this key feature that has been rarely addressed in existing research on internal ball screw. The conventional design method for the recirculation channel involves sweeping the cross-section along the center curve. The center curve is typically defined by various classical equations. These equations are applied in different application scenarios. In automotive braking systems, high loads and strict size constraints place critical demands on both the recirculation channel and its center curve. As a representative best-practice example, the machined channel in the screw is typically employed in this application. This article compares several classical center curve equations and proposes a new general approach based on a family of transition curves. The mechanical analysis identifies the inherent structural characteristics of recirculation channel and develops corresponding design guideline. Furthermore, parameter optimization is performed using MSC ADAMS Multibody Dynamics (MBD) software.
Xia, Xinan, Xia, Yanzhe, Zhao, Tina
Assessing Geographical and Seasonal Influences on Energy Consumption and Driving Range for Electric Drayage Trucks14-15-03-00136/29/2026
The electrification of heavy-duty vehicles is a critical pathway toward improved energy efficiency in the freight sector. The current battery electric truck technology poses several challenges to commercial vehicle operations, such as limited driving range, sensitivity to climate conditions, and long recharging times. Estimating the energy consumption of heavy-duty electric trucks is crucial to assessing the feasibility of fleet electrification and its impact on the electric grid. This article focuses on developing a model-based simulation approach to predict and analyze the energy consumption of electric trucks by considering the impact of weather and geographical conditions on vehicle road load and auxiliary components power consumption, as well as the impact these factors have on driving range. Specifically, drayage trucks employed in logistics around maritime ports are used as a case study, with consideration of seasonal climate variations and geographical characteristics at different locations. The article includes results for three major container ports within the United States, providing region-specific insights into the energy requirements and driving range of the electric drayage trucks in these regions, which will inform decision-makers in integrating electric trucks into the existing drayage operations and plan investments for electric grid development.
Shiledar, Ankur, Villani, Manfredi, Lucero, Joseph N. E., Sun, Ruixiao, Sujan, Vivek A., Onori, Simona, Rizzoni, Giorgio
Model-Guided Scenario Expansion for Data-Driven Autonomous-Vehicle Safety Testing: A Feasibility Demonstration12-09-04-00326/29/2026
This article presents a data-driven pipeline for autonomous-vehicle (AV) safety testing. The pipeline integrates real-world traffic observations with model-guided scenario expansion and safety-metric evaluation to enable an end-to-end AV safety testing framework, demonstrated on a canonical highway scenario. The framework enhances test diversity, realism, and coverage by generating statistically informed variants of observed driving behaviors. Key parameters such as vehicle speed, trajectories, and headways are extracted from naturalistic data and used to train a probabilistic model of traffic dynamics. Scenario variants are sampled from this model and encoded as behavior trees (BTs) for modular, simulation-ready execution. Each scenario is simulated using a consistent AV control configuration, and safety metrics such as minimum safe distance violation, minimum safe distance factor, time to collision, and aggressive driving are applied to evaluate safety outcomes independently of system-specific tuning. A case study based on the highD dataset (110,000+ trajectories) demonstrates the framework’s ability to generate realistic and safety-relevant scenarios, providing an initial demonstration of pipeline feasibility and metric-based evaluation. This initial study is intentionally scoped to a single scenario class and a simplified parametric model to isolate and validate the end-to-end integration of the pipeline.
Elshenawy, Mohamed, Aboudina, Aya, Abdelmotaleb, Anhar, Amr, Mariam, El-darieby, Mohamed
Experimental Investigation of Fuel Cutout Strategies in a Heavy-Duty Gasoline Compression Ignition Engine03-19-03-00156/26/2026
This study investigates Gasoline Compression Ignition (GCI), a family of advanced combustion strategies that can be used to achieve low engine-out criteria pollutant emissions in the heavy-duty transportation sector. In particular, high fuel stratification GCI (HFS-GCI) has been shown to have high thermal efficiencies while maintaining a highly controllable and responsive mixing-controlled combustion event. However, stable combustion at low loads has been shown to be the principal challenge to the implementation of HFS-GCI in production applications. It has also been observed that several strategies that achieve stable combustion at low loads result either in increased emissions or efficiency penalties. While the achievement and maintenance of high enough exhaust temperatures for efficient aftertreatment operation is a significant challenge at low loads even for traditional diesel engine operation, this challenge is exacerbated by the low reactivity and colder flame temperature of gasoline. In recent single-cylinder and 1D simulation studies, fuel cutout strategies have been proposed as an enabling strategy to simultaneously improve combustion stability at low loads and increase exhaust temperatures. In this study, fuel cutout strategies are studied in a prototype multicylinder heavy-duty GCI engine based on a Cummins ISX15 diesel engine. Steady-state engine studies are conducted at warm and cold idle conditions to identify combinations of cylinders that provide the most benefit. NOx and soot limits are set and the performance of cutout strategies are compared to a pre-optimized baseline. The most optimal strategies from steady-state testing are then implemented under transient test cycle conditions similar to those required under United States regulatory testing. The strategies were found to offer simultaneous improvements in stability, fuel consumption, criteria pollutants, and turbine outlet temperature. The choice of cylinders whose fuel supply was cut was seen to be important in realizing the observed benefits. The use of fuel cutout strategies offered optimal performance at all the conditions considered, offering an additional lever to improve the performance of HFS-GCI and highlighting a promising pathway to the use of gasoline-like fuels as alternatives to diesel in heavy-duty engines.
Viswanathan, Aravindh Babu, Zhang, Yu, Merritt, Brock
Automosphere: Exploring Vehicle Heads-Up Display with Weather-Related Windshield Cues for Passive Fatigue Management12-09-03-00256/26/2026
Passive fatigue can cause accidents with automated and regular vehicles. A proof-of-concept prototype [made with light-emitting diode (LED) matrices and white LED (WLED)] and a preliminary comparative usability test (N = 7) are used to study whether the active manipulation of simulated weather cues can be a potential countermeasure to passive fatigue. Participants rated system suitability, system impression, and their fatigue level similarly when they viewed a weather windshield heads-up display (HUD) versus a speedometer windshield HUD [no significant differences found and relatively small 95% confidence interval (CI) ranges around 0]. Qualitative analysis of interviews found that participants saw the potential value of the weather display and that display placement, dynamic graphics, and user activation were commonly mentioned themes. These results suggest the concept is theoretically possible, though further work is needed to prove the concept in practice.
Ensafjoo, Mohsen, Li, Jamy
Spray–Wall Interaction at Thermal Swing Coatings in SI Engines03-19-03-00146/25/2026
As a contribution to the reduction of greenhouse gas emissions in the transportation sector, the indicated efficiency of SI engines can be increased via thermal swing coatings. Thereby, a decrease in greenhouse gas emissions can be achieved, although not at all operating conditions. Here, the often-observed increased hydrocarbon emission partially overcompensates the reduced wall heat losses. The main root cause is always attributed to the increased surface roughness and porosity, leading to an increased crevice volume. Further investigations were performed at a single-cylinder engine equipped with a FTIR for species analysis of hydrocarbon emissions. A comparison of direct injection and port fuel injection were performed for RON95 E10 and methanol to assess the influence of mixture preparation. 3D CFD was used to additionally investigate the in-cylinder processes. The comparison of port fuel injection and direct injection showed a significant influence on the fuel hydrocarbon emissions for the direct injection when the thermal swing coating was applied. The effect is more pronounced for methanol. For port fuel injection nearly the same or reduced fuel hydrocarbon emissions can be observed. This is mainly attributed to an increased wall film agglomeration at the piston for the thermal swing coating in case of direct injection, which can be observed in 3D CFD. Due to the low thermal effusivity of the coating, the droplet impingement leads to a notable decrease in the surface temperature. This results in lower evaporation of the fuel and a longer droplet lifetime. Consequently, a fuel wall film is still present at top dead center after ignition leading to additional hydrocarbon emissions.
Fischer, Marcus, Pischinger, Stefan
Impact of Network-Induced Delays on Autonomous Vehicle Steering Stability10-10-03-00246/25/2026
This article presents a cross-layer framework that integrates realistic vehicle-to-network-to-vehicle (V2N2V) delay characterization with a rigorous stability analysis of automated vehicle steering control. Both constant and network-induced time-varying delays modeled via deterministic bounds are addressed. For constant delays, delay-independent stability regions within the controller gain space are analytically derived. For time-varying delays with stochastic network origins, modeled using deterministic bounds, a refined Lyapunov–Krasovskii functional (LKF) incorporating augmented single- and double-integral terms is constructed. To establish delay-dependent linear matrix inequality (LMI) conditions, a reciprocally convex combination approach is employed to handle the delay interval partitioning, and the second-order Bessel–Legendre inequality is applied to tighten the integral quadratic bounds. The resulting LMI conditions explicitly capture the coupled effects of delay magnitude, delay variation rate, and control gains on closed-loop stability. Simulations of a lane-keeping scenario confirm that the predicted stability boundaries accurately match the closed-loop system behavior. Notably, incorporating a realistic time-varying V2N2V delay profile into the controller design reduces the lateral-state root-mean-square error (RMSE) by over 54% and decreases the settling time by a factor of 10 compared to designs relying on an average-delay assumption. However, high packet loss rates are shown to still induce residual oscillations due to information scarcity. Ultimately, these results elucidate delay-induced instability mechanisms and provide practical guidelines for designing delay-robust steering controllers for connected and automated vehicles.
Li, Jialin, Lu, Jianwei, Wei, Heng, Ao, Di
BO-NRPPO: A Bayesian Optimization–Tuned Proximal Policy Optimization Framework for Semi-Active Suspension Control10-10-03-00256/25/2026
Semi-active suspension systems enhance ride comfort and handling performance by adaptively modulating damping characteristics. However, conventional model-based controllers often fail to maintain optimal performance under uncertain and time-varying vehicle conditions. This article proposes Bayesian Optimization–Tuned Proximal Policy Optimization with Non-Parametric Rewards (BO-NRPPO), a novel reinforcement learning (RL) framework that integrates Bayesian Optimization (BO) with Proximal Policy Optimization (PPO) and a non-parametric reward function (NRF). The proposed approach enables adaptive self-tuning, data-driven reward shaping, and uncertainty-aware policy learning. Moreover, a Trapezoidal Simple Moving Average (TSMA)–based reward normalization scheme is introduced to accelerate convergence and stabilize training. Simulation results across diverse driving scenarios demonstrate that BO-NRPPO outperforms the passive suspension, the classical Linear Quadratic Regulator (LQR), and PPO with parametric rewards. Specifically, compared to the passive suspension and the LQR baseline, BO-NRPPO achieves up to 6.63% and 5.14% improvements in handling stability, respectively. Concurrently, it delivers maximum enhancements of 46.96% and 42.55% in ride comfort over these two baselines. For real-world vehicle applications, this adaptive self-tuning capability significantly reduces the time-consuming manual calibration efforts typically required in chassis development. Furthermore, Hardware-in-the-loop (HiL) validation confirms its real-time applicability and robustness under uncertain driving conditions, highlighting its immense potential as a scalable intelligent suspension control solution.
Chen, Guoying, Wang, Xinyu, Wang, Jiaqi, Zhan, Xinwang, Bi, Chenxiao, Cong, Shiqi, Hua, Min, Sun, Tianjun, Gao, Zhenhai
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