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.

Items (11,245)
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
Xia, XinanXia, YanzheZhao, Tina
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
Elshenawy, MohamedAboudina, AyaAbdelmotaleb, AnharAmr, MariamEl-darieby, Mohamed
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
Shiledar, AnkurVillani, ManfrediLucero, Joseph N. E.Sun, RuixiaoSujan, Vivek A.Onori, SimonaRizzoni, Giorgio
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
Viswanathan, Aravindh BabuZhang, YuMerritt, Brock
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, MohsenLi, Jamy
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
Li, JialinLu, JianweiWei, HengAo, Di
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
Chowdhury, RohanShukla, Dhwanil
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
Fischer, MarcusPischinger, Stefan
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
Chen, GuoyingWang, XinyuWang, JiaqiZhan, XinwangBi, ChenxiaoCong, ShiqiHua, MinSun, TianjunGao, Zhenhai
Thoracic injuries are common for belted occupants in frontal motor vehicle crashes. However, there remains a lack of female post-mortem human subject (PMHS) data in the literature to generate female-specific biomechanical response corridors and evaluate engineering tools such as anthropomorphic test devices (ATDs) and computational human body models (HBMs). Additionally, the effect of breast tissue on thoracic response has not been directly investigated despite female ATDs and HBMs having features representing breasts. As such, this study sought to utilize simplified frontal hub impacts to (1) generate female PMHS thoracic response corridors both with breasts positioned with a bra and without breasts (no bra) and (2) preliminarily explore the influence of breasts on the thoracic responses of female PMHS. Twelve female PMHS (9 small and 3 midsize) were subjected to frontal impacts at mid-sternum with a 14.0 kg circular impactor at 4.3 m/s in conditions with and without breasts. Force
Baker, Gretchen H.Kang, Yun-SeokMarcallini, AngeloLang, RyanHutter, ErinMoorhouse, KevinAgnew, Amanda M.
Stochastic preignition (SPI) or low-speed preignition (LSPI) is an abnormal combustion phenomenon observed in downsized turbocharged direct-injection spark-ignition engines at highly boosted conditions. SPI results from the ignition of the air-fuel mixture from a fuel or oil droplet or a detached deposit before the spark discharge, and its occurrence can lead to extremely high peak pressures and severe knock, which can cause physical damage to the engine. This phenomenon limits the downsizing and boosting potential of direct-injection spark-ignition engines, thereby constraining the efficiency benefits that can be achieved. The propensity for SPI to occur is impacted by engine operating conditions as well as the properties of the fuel, fuel additives, lubricant, and lubricant additives. To mitigate its occurrence, it is important to understand the factors that impact the frequency of SPI events. As this abnormal combustion phenomenon is relatively recent, there was a lack of a standard
Gopujkar, SiddharthDavis, RichardWorm, JeremyTuma, NicShukla, PrajwalReilly, VeronicaChapman, ElanaCiaravino, JosephSeyfried, Philipp
This study focuses on a hydrogen ejector for a proton exchange membrane fuel cell (PEMFC) with a maximum power of 150 kW. Experimental tests were conducted to obtain the operating parameters of the stack under 100 kW and 150 kW conditions, which were used as simulation boundary conditions. A three-dimensional numerical model of the ejector was established and validated. Based on this model, the effects of key structural parameters—including nozzle throat radius (Rnt ), nozzle position (NXP), mixing chamber radius (Rm ), diffuser outlet radius (Rde ), secondary flow inlet radius (Rs ), suction chamber radius (Rf ), and constant-pressure mixing chamber length (Lpm )—on ejector performance were systematically analyzed. The results indicate that Rnt and Rf are negatively correlated with ejector performance, while Rs and Lpm are positively correlated. In contrast, NXP, Rm , and Rde exhibit an optimal range, leading to a single-peak characteristic in ejector performance. This research
Liu, GuoqingTai, ShupengXi, FuqiangLi, ZongjiJi, ShaoboWang, XiuyuWei, Hui
During idling tests of a newly developed sport utility vehicle (SUV) under tropical high-temperature conditions, the condenser surface temperature exceeded the allowable range, degrading the air-conditioning system’s cooling performance. In this study, a three-dimensional computational fluid dynamics (CFD) model of the engine compartment flow field was established using STAR-CCM+. The results reveal that under idling conditions, the kinetic energy of hot air passing through the cooling module was insufficient to overcome the pressure difference between the front and rear sections, thus inducing hot air recirculation (HAR) and increasing the overall compartment temperature. To address the unfavorable flow field characteristics, four structural improvements were proposed and simulated for both flow and temperature fields. Through comparative analysis, the optimal scheme was determined: installing a flow guide baffle above the engine. Simulation results show that the airflow velocity
Shi, HuojieRao, R.H.Chen, J.Zheng, Z.L.
This article presents a novel finite element modeling approach to predict the mechanical response of jellyrolls in large-scale explicit crash simulations up to the experimental occurrence of internal short-circuit. The proposed simplified layered model embeds membrane elements within a solid element mesh to improve the prediction in load cases dominated by the buckling and sliding of the jellyroll’s layered structure. The model was validated against experimental results from in-plane, out-of-plane, and bending tests on jellyroll samples extracted from prismatic lithium-ion cells. The experimental results confirmed the jellyroll’s high compressibility under out-of-plane loads and its behavior as a collection of unconnected layers under in-plane and bending loading. Compared to the widely used crushable foam model, the simplified layered model offered additional flexibility, especially for in-plane and bending load cases. Additionally, it meets critical time increment requirements for
Cioni, DanieleMorin, DavidStrating, ArjanKizio, StephanCostas, Miguel
Investigating high-speed aerodynamics and aerothermodynamics presents a significant challenge for manned re-entry missions. The thermal effects on the surface of the re-entry vehicle and atmospheric stresses are primarily influenced by re-entry type and flight trajectory. This study investigates the monostability characteristics and aerothermodynamics of the Orion re-entry vehicle by incorporating static fins onto the aft fuselage of the vehicle, ensuring the lift-to-drag ratio remains unaffected throughout the numerical simulations. The study evaluated two different Mach numbers of 7 and 9 at various altitudes. The models were analyzed at different angles of attack from 0° to 90° in increments of 15°. The model with static fins exhibits a displacement in the monostable trim point, a reduction in the heat-shield pressure coefficient, and enhanced heat transfer throughout the re-entry vehicle.
Sabapathy, Santhosh
To estimate risk of concussion, risk functions based on injuries occurring in sports are often used. A range of datasets have been used to develop injury risk functions for concussion based on either global kinematics or tissue-level predictors. Two such datasets are one from American football, and another one from Australian football and rugby. These two datasets constitute the largest published collections of video-verified concussive cases in sports with known kinematics suitable for constructing risk functions. The objective of this study was to analyze the differences between two datasets of concussion for injury predictions to better understand the influence on injury risk functions. The kinematics were applied to the KTH head model and risk functions for different kinematic- and tissue-based predictors were developed and compared. The accuracy, sensitivity, specificity, and AUC were also compared. The two datasets evaluated in this study generated different risk curves. The
Fahlstedt, MadelenMeng, ShiyangPatton, DeclanMcIntosh, Andrew S.Kleiven, Svein
This study developed a new multibody model that accurately represents the collision behavior of crash test dummies using PC-Crash. The model replicates the shape and weight of an actual dummy. To investigate the influence of joint structures on collision behavior, an additional multibody model was developed to reproduce the joint structure of the actual dummy. These models were applied to analyze occupant behavior in a full-frontal rigid barrier and pedestrian behavior in a vehicle-to-pedestrian impact experiments. A comparison of the multibody model simulations with actual dummy impact experiments revealed that the behavior of the multibody model, which simulates the joint structure of the dummy, closely matched that of the actual dummy. The results indicate that joint structure significantly influences collision behavior, and accurately recreating it improves the precision of crash test dummy collision behavior analysis using PC-Crash.
Usui, MasatoshiMatsui, YasuhiroHosokawa, NaruyukiTanaka, Yoshinori
Passenger vehicles experience severe packaging constraints around the instrument panel, rendering glove-box operation a critical yet ergonomically underexplored interaction. Although glove-box interaction occurs frequently during routine vehicle use, its potential implications for ergonomic risk remain largely unexamined in existing automotive research. To isolate the influence of driver-side packaging constraints from component-level design effects, this study adopts a comparative evaluation of driver and co-driver glove-box interaction as a built-in control condition. This study introduces a discomfort-based evaluation framework that integrates Digital Human Modeling with India-specific anthropometric datasets. A composite loss-function scoring model is developed to quantify functional usability differences across four glove-box configurations, defined by variations in latch placement (center or side) and storage-bin mechanisms (fixed or rotating). Indians are utilized to assess
Jujjavarapu, SreeramRajakumaran, SriramKota, SrinivasKotkunde, NitinJasti, Naga Vamsi Krishna
Agricultural vehicles operating in rough environments experience increased fatigue damage accumulation, which may decrease machine safety and reliability. Autonomous agricultural machines offer an opportunity to incorporate fatigue damage considerations into path planning. This work investigates whether machine learning can predict fatigue damage to a tractor chassis using light detection and ranging (LiDAR)-based terrain features, vehicle speed, and rotational vehicle state data (e.g., triaxial angle, angular velocity, and angular acceleration). Fatigue damage was estimated using the Rupp filter and the Durability Transfer Concept. Following poor predictive performance of the machine learning models, an exploratory analysis of damage histograms, dominant frequency, and acceleration magnitude was performed. Results indicated that most estimated fatigue damage occurred in the 0–2 Hz band, which coincides with the frequency range of terrain-induced acceleration. On-road driving led to
Govers, Megan EmilyHamilton-Wright, AndrewHassan, MarwanOliver, Michele L.
Knowing a detailed operating cycle is critical for developing and testing equipment. Operating cycles can be separated by two clear distinctions: (1) regulatory or non-regulatory and (2) application at the engine-only or full machine level. The Environmental Protection Agency’s (EPA) Nonroad Transient Cycle (NRTC) may be a good representation of engine use in many types of equipment, but there is a gap in standardized and validated drive cycles specifically for nonroad material handlers. Lacking a standardized drive cycle makes it difficult to accurately benchmark machine performance and validate new powertrain technologies. The objective of this investigation is to illustrate the development of a custom drive cycle augmented with real-world customer use data that serves multiple purposes: (1) understand the range of operation and utilization that formulated inputs for electrified architecture analysis and (2) develop a repetitive and consistent maneuver to establish baseline energy
Czarnecki, AlexanderGoodenough, BryantWorm, JeremyRobinette, DarrellLaTendresse, PhilWestman, John
The present review evaluates recent advances in the development of Welding-Based Additive Manufacturing (WBAM) technologies using arc, high-energy density, solid-state, and hybrid welding systems by providing an interdisciplinary assessment of technological aspects, sensing, process optimization, and multi-process strategies. It is concluded that, in spite of considerable progress in process optimization and control, there exist numerous paradoxes associated with relationships among process conditions, structure, and properties, especially those related to heat input effects on material microstructure and performance. An important finding is the fragmentation of predictive modeling approaches, where physics-based and data-driven methods remain inadequately integrated, limiting generalizability and accuracy. Another important conclusion is related to the dominance of the effect of thermal history and multi-physical phenomena on the mechanical performance of the material produced by WBAM
Santhana Babu, A.V.John Rajan, A.Mishra, AishwaryChakravarthy, P.Jayabalakrishnan, D.
Occupant protection has been at the forefront of risk evaluation regarding vehicle crashworthiness design. However, the vehicle is a member of a larger transportation system with varied stakeholders. This article identifies an opportunity for assessing risk in a crash event through emerging safety science paradigms. Conventional Safety I and Safety II frameworks handle well-defined hazards but falter with uncertainty, variability, and emergent behaviors in real crashes. A comprehensive literature review was performed on peer-reviewed research to situate automotive crash safety risk within the Safety III paradigms. The review addresses two questions: (1) How is “risk” defined across the crash safety literature and adjacent safety science domains? and (2) What limitations arise from these definitions in practice? Findings show a dominant probabilistic framing alongside a minority of system-oriented interpretations. Current crash safety practice lacks a coherent, system-level definition
Rye, Patrick J.
Large language models (LLMs) have shown remarkable capabilities for perceiving driving environments and making interpretable, logical decisions for autonomous driving. However, their potential for more comprehensive driving strategies, especially concerning energy efficiency, remains underexplored. Most existing studies primarily focus on driving safety, which may inadvertently increase energy consumption. To address this issue, this study explores the use of LLMs as high-level controllers to jointly optimize driving safety and energy efficiency. A textual prompt is designed for the LLM, incorporating few-shot examples that describe scenarios, states, and actions. The LLM processes the scenario and state prompts describing the surrounding traffic environment. It generates a high-level control signal, which is then translated into low-level vehicle motion commands in a high-fidelity traffic simulator with realistic physics, vehicle dynamics, road slopes, and network topology
Wang, HaoyuLi, ZhenningWang, SiyingZhou, ZijingZhang, XiangYang, ZhifengOu, Shiqi (Shawn)Qi, Hao
A novel looped-freezing mean approach based on Detached Eddy Simulation (DES) approach is developed in context of assessing underhood cooling performance in heavy-duty vehicles. The method involves computing a temporally averaged flow field from DES simulations, which is then frozen and used by the energy solver to predict temperature distributions. This process is iteratively repeated until a statistically steady-state temperature field is achieved. It is demonstrated that traditional DES approach demonstrates superior accuracy in capturing forced convection heat transfer compared to the Reynolds-Averaged Navier–Stokes (RANS) method. The validation against experimental data for flow over a heated sphere at a Reynolds number of 105 shows that DES yields Nusselt numbers with better correlation than RANS. However, it is observed that DES approach captures unsteady flow features that introduce temporal fluctuations in heat transfer. In the context of underhood cooling evaluations where
Holay, SarangSankar, HariDixit, PritishSingh, Ramanand
1Systems level and integration testing are an integral part of the design and development of Automated Vehicles (AVs). Measurement science plays a pivotal role in testing to ensure the safe and efficient operation of AVs. This science establishes a common understanding of the units of measurement, crucial in linking human activities. This article describes the significance of measurement in studying interactions between key system technologies in AVs, including AI for perception, sensing, communications, and cybersecurity. To address the complexities of these interactions, a novel, adaptable, and interactive framework called the System Technology Interaction Model (STIM) is introduced. STIM considers both designed and emergent interactions between these system technologies, allowing AV developers to explore tailored experiments with the flexibility of filtering for focused testing. The framework currently models system interactions statically, not in real-time, to define potential
Griffor, Edward R.Arora, MahimaKootbally, ZeidNguyen, Vinh
In the present study, research was conducted to increase the combustion efficiency in a diesel engine by adding 100 and 200 ppm aluminum powder to diesel and biodiesel (produced from 10% spent coffee ground oil and 90% waste cooking oil) blends. Aluminum powder is a flammable metal. Due to this feature, it has been used as an additive to liquid fuels in many studies in the literature. In general, it has been reported that thermal efficiency increases with the addition of aluminum particles. However, the high explosion sensitivity of aluminum can affect its stable combustion. In addition, Al is a metal that can be easily oxidized. Therefore, coating aluminum is considered a good solution. Stearic acid has been suggested in the literature as a suitable material for coating aluminum. In this study, stearic acid, a saturated fatty acid, was used to coat aluminum particles. Stearic acid is a good surfactant, hydrophobic substance, and plasticizer. It is also a more environmentally friendly
Kül, Volkan SabriAkansu, Selahaddin OrhanSarıtaş, Mehmet
Over the last few years, there has been an uptick in the exploration and implementation of aluminum high-pressure die casting (HPDC) mega-castings as replacements for conventional stamped steel parts in vehicles. This trend is expected to increase with common justifications, including claims of reduced costs and lower environmental impacts associated with the replacement of dozens of individual parts with a single casted piece, along with reduced demands on associated tooling and machinery. However, the data and literature to support these claims are limited and at times contradictory, with some studies showing increased costs and energy demands for mega-casting technologies. This study presents the results of a literature review and a gate-to-gate life cycle inventory (LCI) adapted from conventional HPDC aluminum casting unit processes that may be used to quantify potential life cycle global warming potential (GWP), cumulative energy demand (CED), and other environmental impacts of
Sebastian, BrandieBalzer, Russ
Distributed drive electric vehicles (DDEVs) provide enhanced maneuverability through independent wheel torque control, but coordinating precise path tracking with lateral stability remains challenging under aggressive driving conditions. This paper presents a coordinated control strategy that integrates model predictive control (MPC) for path tracking with a proportional gain controller for stability regulation. The proposed framework adopts a hierarchical design. The path tracking control leverages MPC to compute front steering commands while accounting for vehicle dynamics and preview errors. The stability adjustment uses dual proportional gain controllers to generate an additional yaw moment, which is adaptively balanced through a phase plane coordination mechanism, enhancing yaw stability during path tracking. The generated yaw moment is subsequently distributed to individual in-wheel motors with an optimization torque allocation method, respecting tire force limitations. The
He, YangZhu, YuzhengGuo, RuixinZhu, YueyingXing, ChaoLiu, ShuangxiLin, Yier
Decarbonization efforts achieved through electrification in nonroad mobile machinery can realize a reduction in fuel consumption of more than 20%, thanks to concepts familiar to light-duty passenger vehicles. This case study compares the results of a hybrid-electric material handler to its conventional counterpart, utilizing machine-specific drive cycles presented in part one of this paper series. The hybrid prototype features an extended-range electric vehicle (EREV) powertrain that demonstrated substantial energy efficiency improvements. Specifically, there was a reduction in equivalent fuel consumption of 75% when operating in electric-only mode, and 33% when maintaining the battery by charging with an on-board generator. Together, the efficiency improvements can be extrapolated over a low-intensity, 8-h shift characterized by significant idle time and highly dynamic engine load for a 47% reduction in net energy consumption. Key technologies that led to this improvement included
Czarnecki, AlexanderGoodenough, BryantWorm, JeremyRobinette, DarrellLaTendresse, PhilWestman, JohnSubert, DavidHeath, MatthewKiefer, DylanBlack, Andrew
Abstract This study investigates and evaluates systematically the combustion, performance, and emissions characteristics of heavy-duty diesel engines fueled by diesel–ammonia–compressed natural gas triple blends. While dual-fuel systems are well-documented, the interactive effects of ammonia and CNG within a single compression ignition (CI) engine remain largely unexplored. Experiments were conducted on a 300 Nm, 660 rpm diesel engine by testing pure diesel, diesel–ammonia blends (10–20 wt.% aqueous ammonia), and triple-fuel mixtures containing 10% of the total energy from compressed natural gas. Pure diesel was first tested to provide baseline data, and subsequently blends were tested for a comparative study. The primary contribution of this work is the identification of a synergistic effect of the fuel triple blends on engine performance and emissions. Results indicate that all fuel blends improve thermal efficiency and reduce fuel consumption compared to conventional diesel. The
Sinkala, HappySarıtaş, MehmetKül, Volkan SabriAkansu, Selahaddin OrhanÜnalan, Sebahattin
As automated vehicle technologies enable increased seat recline angles during travel, understanding the biomechanics of injury under these novel occupant postures becomes imperative. This study evaluated the pelvis injury response and associated kinematics of reclined small female post-mortem human surrogates (PMHS) subjected to frontal sled tests across three restraint configurations. Each configuration varied in seat stiffness and the presence of a knee bolster to assess their influence on pelvic dynamics and submarining risk. Nine PMHS tests were conducted using a consistent reclined posture (38° thorax, 75–80° pelvis angle) and production restraint systems. Submarining probability was estimated using a validated logistic regression referenced from previous study. Distinct pelvic kinematics, fracture patterns, and associated injury mechanisms emerged across the test configurations in the current dataset. Configuration 1, featuring a stiffer seat without a knee bolster, exhibited
Somasundaram, KarthikDriesslein, KlausPintar, Frank A.
Road traffic crashes are a major cause of traumatic brain injury (TBI), particularly among vulnerable road users (VRUs). However, current injury prevention strategies often overlook the heterogeneity of TBI—which include various injury types and severities—leading to an oversimplified approach to evaluating helmets and safety systems in regulations and ratings. To identify priority TBI types and severities in VRUs and to inform targeted prevention strategies, the German In-Depth Accident Study database was analyzed and a pathoanatomic classification system, i.e., Abbreviated Injury Scale, was employed. AIS 2 (moderate) TBIs account for 70-80% of all brain injuries across VRU groups, nearly half of which are concussions. For helmeted cyclists, milder TBIs are at a greater percentage than for unhelmeted cyclists. These findings highlight the need for expanding prevention efforts to include AIS 2+ injuries. Key injury types observed include concussion (with and without loss of
Meng, ShiyangSchindler, RonKleiven, SveinLubbe, Nils
Since 2019, sex equity in traffic crashes has been a highly debated topic in vehicle safety, especially following the 2019 study by Forman et al. (1) claiming that female occupants face a 73 percent greater risk of serious injury in frontal crashes compared to male occupants. This was soon followed by a Consumer Reports Article by Keith Barry (2), which attempted to identify underlying factors contributing to the higher risk. These have been embraced by several parties since 2019. Firstly, it was alleged that vehicle design practice over the last four decades considered safety for the male population only and ignored that of the female as evidenced by the exclusive use of the mid-sized male Anthropomorphic Test Devices (ATDs) in Regulatory and Safety Ratings tests and not with an average sized female ATD. The absence of such an ATD for testing of vehicles “set the course for four decades’ worth of car safety design, with deadly consequences” (2). Secondly, although there is a
Prasad, PriyaDalmotas, Dainius J.
Trajectory tracking control is a core technology in intelligent vehicle autonomous driving systems, directly influencing both driving safety and control accuracy. To overcome the limitations of traditional model predictive control (MPC) in real-time performance under complex operating conditions, as well as the limited robustness of linear quadratic regulators (LQR) against system uncertainties, this article proposes a hybrid iterative LQR–MPC (ILQR-MPC) control strategy. First, a dynamic model of the intelligent vehicle is developed to capture its behavior during high-speed driving and cornering. Next, an ILQR-MPC hybrid framework is designed. By exploiting the rapid iterative optimization capabilities of the ILQR algorithm, an initial control sequence is generated for the MPC, thereby reducing the computational load during MPC’s online rolling-horizon optimization. This approach preserves MPC’s advantages in handling constraints and maintaining robustness against parameter variations
Lai, FeiSun, JunhaoHuang, Chaoqun
This study presents a torque distribution strategy for dual-motor electric vehicles utilizing a Deep Deterministic Policy Gradient reinforcement learning algorithm designed to optimize energy consumption. By using a simplified architecture and replicable reward functions, the proposed agents rely exclusively on standard CAN bus signals, commanded longitudinal force, and the motors’ velocities, eliminating the need for specialized sensors or complex plant models. Two reinforcement agents are trained using two different reward functions: power-based and State of Charge-based. These agents are validated through high-fidelity CarSim–Simulink co-simulations across soft, medium, and severe acceleration scenarios, in which they demonstrate superior performance to traditional adaptive methods. In the most demanding scenario, a typical adaptive strategy achieves an additional 7.8% of power consumption and 85% of optimal energy recovery, while the proposed reinforcement learning strategies reach
Meléndez-Useros, MiguelViadero-Monasterio, FernandoLópez-Boada, María JesúsLópez-Boada, Beatriz
Autonomous Vehicles (AVs) offer unprecedented opportunities to design control strategies that could be able to simultaneously enhance safety, performance, user experience, time efficiency, and the environmental impact of mobility. However, as automation levels increase, a paradigm shift becomes not only necessary but imperative: the integration of human needs into mobility objectives. This includes not only traditional comfort considerations but also minimizing Motion Sickness (MS), a largely under-explored challenge in control strategy design. In recent literature, several methodologies for modeling and mitigating MS have been proposed, yet their integration into vehicle control logics remains limited, often restricted to isolated and specific case studies, with the research area largely unexplored, particularly with respect to the generalization of the proposed methods. This work introduces a theoretically grounded multi-objective Nonlinear Model Predictive Control (NMPC) framework
Ponticelli, LorenzoBottiglione, FrancescoRini, GabrieleTimpone, FrancescoSakhnevych, Aleksandr
The decarbonization of heavy-duty trucks (HDTs) is a crucial path for China to achieve its “dual-carbon” goals and transition to decarbonized freight transport. Zero-carbon fuels are key alternatives to fossil fuels for these high-emission vehicles. This study develops an integrated scenario analysis framework to quantify the theoretical CO₂e emission trajectories of China’s long-haul HDT fleet from 2020 to 2060. Functioning as a macro-level stress test, the model derives theoretical equivalent stock from anticipated logistics turnover demand, integrating them with well-to-wheel (WTW) emission factors under six distinct policy stringencies (Projects 1 through 6), representing varying paces of fossil fuel vehicle phase-out. The results demonstrate that policy stringency primarily governs the timing and depth of emission reductions, while fuel technology defines the minimum achievable emission level. Three-dimensional visualization analysis reveals a nonlinear “emission cliff” under
Wu, YunmeiHuang, HuaLi, RuiHe, GuijiaLiu, BoLiu, RuoweiXie, Yongliang
This article describes multi-body dynamics simulation to investigate door jitter issues caused by the limiter during door operations. A simulation model integrating a rigid limiter and a flexible door-body system was developed to replicate the dynamic process of wide-angle door opening/closing. Through iterative refinements—including correlation of simulation results with test data, optimization of internal door connection methods, and solid-element hinge modeling—simulation accuracy was improved to over 89.7%. Using the validated model, quantitative metrics were established to evaluate door jitter severity. Key parameters that influence the door operation smoothness were identified, and an optimization scheme was proposed for a specific vehicle model, incorporating slope-holding performance requirements under hill-parking conditions. Finally, prototype testing validated the approach’s effectiveness. The developed simulation method provides a technical foundation for virtually
Xiao, YongfuDeng, JianjiaoLi, JingtanYang, TaoHou, HangshenHan, ChaoGao, MengWang, YiqiLiu, Yihong
An accurate air spring model is essential for the design and optimization of air suspension systems to achieve superior performance. This article presents a novel stiffness model for a rolling lobe air spring (RLAS), formulated using stiffness characteristic parameters. Prediction models for these parameters, including effective area and its change rate, as well as effective volume and its change rate, are derived through geometric analysis, based on polynomial fitting of the irregular piston contour. The local contour cone angle of the piston is determined by differentiating the polynomial function, capturing the geometry-dependent variation across the profile. Additionally, a nonlinear hysteresis model for the rubber bellows is integrated, combining a Berg friction component and a Kelvin-Voigt fractional derivative viscoelastic model to represent the amplitude- and frequency-dependent behavior of the RLAS. The proposed model is parameterized through quasi-static and dynamic bench
Xia, XiaojunZhang, HongZou, YiYe, LeiLu, YiChen, RuiZou, HantongWang, Yang
In this article, the aerodynamic features of two configurations of Lotus EMEYA are introduced. The first configuration includes a fixed air dam and an active rear spoiler (ARS) assembly, which has two active blades in order to obtain the aerodynamic drag and lift performance required. The second configuration includes an Active Air Dam (AAD) assembly and a gurney flap mounted on the ARS in order to achieve more aggressive aerodynamic performance. The aerodynamic bandwidths and the lift balances of both configurations are demonstrated, and the strategies of active aero components of the two configurations are also introduced. Through active aerodynamics and control strategies, the two configurations of Lotus EMEYA can meet the performance requirements of users in different scenarios.
Yuan, QingpengYang, LeiLi, BoNi, LiTo, Chi HinXiong, Zhenfeng
Corner module vehicles (CMVs) achieve the decoupling of driving, braking, steering, and suspension, significantly enhancing vehicle handling potential, but under extreme operating conditions, the interactions between actuators severely constrain the improvement of vehicle handling performance. In order to mitigate conflicts between subsystems and enhance vehicle handling stability, a hierarchical hybrid game–based limit stability control method for CMVs is proposed in this article. Taking into account the handling potential of subsystems under limit conditions, a Stackelberg leader–follower game is designed by first designating Direct Yaw moment Control (DYC) as the leader and Active Rear Steering (ARS) as the follower. Subsequently, the DYC–ARS and Active Suspension System (ASS) were constructed into a non-cooperative game system, and the Nash equilibrium solution was solved through iteration. The lower-level controllers, respectively, established a tire force distribution model that
Peng, JinxinXiao, FengKe, YuanJin, Liqiang
The reliability of welded joints is a vital factor in modern manufacturing, directly affecting product performance and durability. This study investigates methods to enhance the mechanical and metallurgical quality of butt joints in AISI 304L stainless steel welded by the gas tungsten arc (GTA) process. A systematic experimental design was implemented using the Taguchi method with an L9 orthogonal array, considering welding current, gas flow rate, and travel speed as the main parameters. To determine overall weld performance, the joints were characterized by measuring ultimate tensile strength (UTS), yield strength, percentage elongation, and examining their microstructural morphology. An experimental strategy based on the Taguchi approach has been implemented. The welding performance of the material was investigated, and the process parameters were optimized using multiresponse optimization through principal component analysis (PCA), incorporating an orthogonal array design, signal-to
Ghosh, NabenduRoy, Angshuman
Accurate prediction of load distribution in multi-bolt metal–composite joints relies heavily on high-fidelity modeling of single-bolt joint stiffness. Current models, however, inadequately capture the complex effects of bolt–hole clearance, including delayed load take-up and reduced bearing chord stiffness, as well as multi-interface friction interactions. To overcome these limitations, quasi-static tests were conducted on single-bolt, single-lap aluminum–CFRP joints with varying clearances. By integrating experimental findings with an analysis of the load-transfer mechanisms, we identified five distinct loading states and formulated corresponding analytical load-deformation equations along with explicit transition criteria, culminating in a novel piecewise-linear stiffness model. Enhancements over traditional tri-linear models encompass: (a) subdivision of the transition region into separate local and global slip phases, facilitating an accurate representation of asynchronous slip
Liu, HaolongSun, QingpingLiu, YangZhao, QiLiu, Yue
Letter from the Editor-in-Chief
Hardy, Warren N.
Letter from the Guest Editor
Tylko, Suzanne
A full lithium-ion battery (LIB) pack has hundreds to thousands of cells, coolant flow lines and channels, and channel bends to control cell temperature within its operating window and minimize cell internal resistance, aging, and fire risk. A 75 kWh LIB pack has four modules, and each has 23–25 bricks. Two challenges in battery state predictions for hot and subzero temperatures are battery temperature (Tbatt ) and coolant flow within the whole pack. In this work, a 1D 75 kWh full-pack model with its thermal management system is developed using a holistic reverse-engineering method, which can predict Tbatt at any bricks/modules and inlet/outlet coolant flow characteristics. A Tesla Model Y equipped with dual e-motors is tested on an in-house state-of-the-art chassis dynamometer. The test data at V = 60–80 km/h, 100–150 A constant discharge, and Tbatt = −10°C to 40°C are used to develop the model. The 75 kWh pack model features 4000+ cylindrical cells (96S46P, Panasonic 21700-format
Sok, RatnakKusaka, Jin
Autonomous vehicles exhibit extremely strong nonlinearity during drift. However, existing autonomous drift algorithms often neglect previewed path curvature and offer only limited consideration of road surface uncertainty because of the influence of vehicle nonlinear dynamics, which can affect tracking accuracy and robustness of drift control. To solve these problems, this study proposes a robust optimal drift control framework based on curvature preview. First, a preview vehicle kinematic model is constructed, and a preview model predictive control path-tracking controller that considers the forthcoming curvature is designed. Through the analysis of equilibrium points with additional yaw moment, a robust optimal drift controller is developed, which employs a three-degrees-of-freedom vehicle model with an additional yaw moment. This controller adopts integral sliding mode control with a super-twisting algorithm (STA) and exhibits good stability, which is verified through Lyapunov
Gan, YurunSong, ZiyuGu, TongtongDing, HaitaoXu, NanZhang, Jianwei
Diesel engines used for the main power supplier of submarine normally run in high back pressure and low intake pressure, causing unstable performances. Furthermore, when a submarine runs under the sea the exhaust pipe of the diesel engine is under the seawater. Once the lowest pressure in the exhaust pipe is not sufficient to push all the water out, the water will flow into the exhaust pipe and damage the diesel engine. Modeling can provide a useful guide for designing diesel engines, intake and exhaust pipes, and turbocharging systems to avoid water flowing into diesel engine. However, existing simulation methods cannot well simulate the exhaust system of an underwater diesel engine, in which the interface between the liquid water and the exhaust gas is variable. To overcome the drawbacks of existing simulation methods in handling the variable interface between the two phases, a variable interface finite volume method (FVM) is proposed, and a corresponding model is developed in this
Guo, DongshaoZhang, LichengYang, ShiyouSun, YongAbidin, ZainalLin, Shujun
Traffic collision reconstruction traditionally relies on human expertise and, when performed properly, can be incredibly accurate. However, attempting to perform pre-crash reconstruction, i.e., reconstructing the driver and vehicle behaviors that preceded the actual crash, poses significantly more challenges. This study develops a multi-agent artificial intelligence (AI) framework that reconstructs pre-crash scenarios and infers vehicle behaviors from fragmented collision data. We present a two-phase collaborative framework combining reconstruction and reasoning phases. The system processes 277 rear-end lead vehicle deceleration (LVD) collisions from the Crash Investigation Sampling System (CISS; 2017–2022), integrating textual crash reports, structured tabular data, and visual scene diagrams. Phase I generates natural language crash reconstructions from multimodal inputs. Phase II performs in-depth crash reasoning by combining these reconstructions with the temporal event data
Xu, GeruiChen, BoyouGuo, HuizhongLeBlanc, DaveKusari, ArpanYarbasi, EfeAhmed, AnannaSun, ZhaonanBao, Shan
To reduce traffic fatalities through vehicle safety measures, particular attention must be given to cyclist-related fatalities. Clarifying the characteristics of hazardous events leading to cyclist fatalities, not only by vehicle speed range but also by vehicle type, is essential and should be based on analyses of real-world accident data. Accordingly, this study aimed to characterize fatal cyclist accidents involving vehicles traveling at low and high speeds in Japan. We used macro accident data from the Japanese Institute for Traffic Accident Research and Data Analysis covering the period from 2013 to 2022. Based on nine vehicle types, we investigated the effects of road type, vehicle behavior, and accident type on cyclist fatalities. Additionally, we identified the five most frequent accident scenarios separately for each low- and high-speed category. At signalized intersections, the proportions of cyclist fatalities involving vehicles traveling at low speeds were higher than those
Matsui, YasuhiroOikawa, Shoko
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