Browse Topic: Design Engineering and Styling

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Autonomous Racing Control Using Reinforcement Learning with Racing Line Guidance2026-01-0031To be published on 04/07/2026
In recent years, with the emergence of autonomous racing competitions such as Roborace, autonomous racing cars have become a prominent research focus and have undergone rapid development. This paper establishes a reinforcement learning-based decision-making and control framework for autonomous racing cars, achieving cooperative optimization between high-speed racing and safety control under extreme operating conditions. By integrating a Control Barrier Function constrained reward function for dynamic stability and a racing line-guided path optimization, the proposed framework achieves a synergistic balance between minimum lap time and operational safety. Dynamic stability domain constraints based on a two-degree-of-freedom single-mass rigid-body model and racing line optimization based on track geometric modeling are established. The phase plane stability boundary is constructed using the yaw rate method and double-line method, upon which Control Barrier Function constraints are
peng, tao, Zhang, Weiqi, Li, Zengwen, sudong, jiang
Modified Hybrid A* Collision-Free Path-Planning for Parking a Vehicle in Tight Spaces2026-01-0046To be published on 04/07/2026
Parking a vehicle in tight spaces is a challenging task to perform due to the scarcity of feasible paths that are also collision-free. This paper presents a strategy to tackle this kind of maneuver with a modified Hybrid-A* path-planning algorithm that combines the feasibility guarantee inherent in the standard Hybrid A* algorithm with the addition of static obstacle collision avoidance. A kinematic single-track model is derived to describe the low-speed motion of the vehicle, which is subsequently used as the motion model in the Hybrid A* path-planning algorithm to generate feasible motion primitive branches. The model states are also used to reconstruct the vehicle centerline, which, in conjunction with an inflated binary occupancy map, facilitates static obstacle collision avoidance functions. Simulation study and animation are set up to test the efficacy of the approach, and the proposed algorithm proves to consistently provide kinematically feasible trajectories that are also
Cao, Xincheng, Chen, Haochong, Aksun Guvenc, Bilin, Guvenc, Levent
Research on Reliability Test Methods for Electric Drive Axle Differentials2026-01-0007To be published on 04/07/2026
With the rapid socio-economic development, global issues such as the energy crisis and environmental pollution have become increasingly severe. Electric vehicles have garnered growing attention due to their environmental friendliness, simple structure, and high energy efficiency. Electric drive technology is regarded as the most ideal universal driving solution for pure electric vehicles, hybrid electric vehicles, and fuel cell vehicles. The electric drive axle, as a new type of integrated mechatronic transmission system, is being increasingly adopted owing to its advantages such as high drive efficiency, flexible spatial arrangement, and facilitation of digital and automated chassis control. This study focuses on reliability testing methods for the differential in electric drive axles, mainly including the extraction of reliability test conditions and feasibility analysis of the test scheme. The main research contents are as follows: First, based on specific parameters of an electric
Zheng, Hongyu, Li, Ziyu, Wang, Dajiang, tian, kai
A Proposed Methodology for Human Operator Modeling and Development of a Virtual Operator Model for Control of a Simulated Compact Track Loader2026-01-0146To be published on 04/07/2026
A methodology for performing Human Operator Modeling (HOM) using a Caterpillar Model 299D3 XE Compact Track Loader (CTL) is presented. The proposed method uses task analysis techniques to decompose a material excavation and moving task into smaller, individual tasks presented in a task list. A method for verifying and refining the task list is presented, along with a procedure for identifying relevant human operator sensory information and analyzing human decision making in the context of CTL operation. This methodology is then partially verified through the analysis of a non-expert human operator in Vortex Studio, a realistic construction equipment simulator. A modified test course is executed by a non-expert human operator in the simulation environment, and the recorded data is used to create a quantitative Human Operator Model. From this, a Virtual Operator Model (VOM) feedback controller simulating the performance of the human operator is developed. The VOM is implemented using a
Wang, Orson R., Norris, William R., Patterson, Albert E., Soylemezoglu, Ahmet, Nottage, Dustin S.
Simulink DevOps Evolution: Bridging Interactive Platforms for Accelerated Model-Based Workflows2026-01-0080To be published on 04/07/2026
This paper builds on last year’s paper presenting DevOps automation in the context of model-based development. Following that paper, we interviewed Simulink users in passenger automotive, motorsports, commercial vehicles, aviation, rocketry, and industrial automation. We discovered that much of the benefit of DevOps platforms to reduce product development cycle time relies on their interactive features. We prototyped new tools to bridge interactive DevOps Git-based platforms with model-based development workflows, and then gathered reactions from another round of interviews. Here we present these interactive DevOps workflows with the feedback from these interviews to contextualize how engineering teams could adopt them to accelerate their own model-based workflows.
Mathews, Jon, Ferrero, Sergio, Tamrawi, Ahmed, Sauceda, Jeremias
A decision-making framework for field manufacturability of vehicle parts in expeditionary environments2026-01-0143To be published on 04/07/2026
Expeditionary environments (such as remote exploration missions, forward military operations, and disaster response zones) demand adaptive manufacturing solutions to support vehicle sustainment in the absence of traditional supply chains. This work introduces a conceptual mathematical framework for modeling the constraints and trade-offs inherent to expeditionary manufacturing, with a focus on vehicle repair and spare parts fabrication using low-energy and simple automated systems including desktop-scale 3D printers and CNC machines. The model integrates key variables such as energy availability, material transport cost, fabrication time, and environmental limitations to support rapid decision-making on part manufacturability and in-field feasibility. A case study involving the on-demand production of some common wear and failure parts on a vehicle, including suspension components and the water pump, is used to demonstrate how this framework can guide the selection of suitable
Mollan, Calahan, Pandey, Vijitashwa, Patterson, Albert E.
Benchmarking Driver Responses in Head-On Conflicts: Toward an Objective Protocol for Human and AV Evaluation2026-01-0534To be published on 04/07/2026
Head-on emergency conflicts present a unique challenge for evaluating driver and automated vehicle (AV) performance. Unlike most emergency scenarios that follow a direct stimulus–response sequence, head-on encounters are characterized by a stimulus–wait–response pattern in which time to contact (TTC) strongly shapes driver behavior. Drawing on naturalistic and simulator data, this study quantified human responses to head-on conflicts. When the opposing vehicle crossed the centerline with more than 2 seconds of TTC, drivers delayed braking until an average of 1.3 seconds (SD = 0.8) before impact, regardless of the timing of the intrusion. By contrast, when TTC was less than 2 seconds, braking was initiated only 0 to 1.0 second before impact. As a result, many drivers applied the brakes less than half a second before collision. These findings provide a meta-analytically grounded benchmark for comparing human behavior to AV decision-making processes and demonstrate the need for conflict
Muttart, Jeffrey, Dinakar, Swaroop, Maloney, Tim, Adikhari, Bikram, Gernhard-Macha, Suntasty
The Characterization of Lumbar Acceleration in Rear-End Impacts Across Different Surrogate Occupant Types2026-01-0552To be published on 04/07/2026
Longitudinal lumbar acceleration is often overlooked as a key variable when biomechanically assessing lumbar response in rear-end collisions. Previous studies have assessed lumbar accelerations for occupant types individually, but comparative analyses between surrogate occupant types have been limited. Human volunteers best reflect kinematics in real crash scenarios but are limited to low-severity impacts due to ethical limitations. Post-mortem human subjects (PMHS) can be employed in higher speed impacts, however their lack of muscular input may not extensively capture occupant kinematics. Anthropomorphic test devices (ATDs) offer trial consistency and repeatability, however the widely used Hybrid III ATD's relatively simple lumbar spine may not fully emulate the human lumbar vertebrae. Based on these physiological differences between occupant types, there may be corresponding differences in lumbar spine acceleration that have not been objectively quantified. The aim of this study was
Zambare, Keya, Ogbu Felix, Jordan, Arana Barcala, Emily, Westrom, Clyde, Caraan, John, Adanty, Kevin, Shimada, Sean
Bias and uncertainty in the time, position, and speed data of consumer-grade GPS devices2026-01-0544To be published on 04/07/2026
The goal of this study is to quantify the accuracy and uncertainty of position and speed measurements acquired by a wide range of consumer-grade GPS-enabled devices while road cycling. We acquired position and speed data simultaneously from 13 consumer devices (e.g., phones, watches, bicycle computers) at their maximum sampling rate (typically 1 Hz) during 10 hours (thirty 20 minute sessions) and 150 km of road cycling in a suburban environment. The position data from these devices were compared to real-time kinematic (RTK) data acquired using a differential GPS system and the speed data from these devices were compared to speed data acquired with high-resolution wheel rotation sensors (23,040 pulses per revolution) synchronized with the RTK data. Based on these comparisons, we generated probability distributions for the errors in the position and speed measured by each of the consumer devices. This study provides foundational data needed to quantify the accuracy and uncertainty across
Booth, Gabrielle R., Mitchell, Alan L., Siegmund, Gunter P.
Effect of housing design on oil splash lubrication in an E-drive Unit through Computational Fluid Dynamics Simulation2026-01-0116To be published on 04/07/2026
Proper lubrication of gears and supporting bearings is crucial for the optimal functioning of an e-drive unit, particularly under high-speed and high-load conditions. Understanding the causes of bearing failure requires an analysis of the oil splash pattern in a testbed with a transparent casing. Additionally, modifying the gearbox and housing designs can be both time-consuming and costly to achieve performance goals. As an alternative, Computational Fluid Dynamics (CFD) modeling provides a virtual testing environment that allows for quicker design evaluations and reduces product development time. This study focuses on using CFD to assess a housing design aimed at enhancing lubrication for the rear and front drive units (RDU/FDU) in electric vehicles. Multiphase flow simulations were conducted using the volume of fluid (VOF) method in the commercial CFD software Simerics-MP+. This software generates an unstructured Cartesian mesh and manages complex mesh movements through a volume
Kumar, P. Madhan, Motin, Abdul, Pasunurthi, Shyam Sundar, Ganamet, Alain, Maiti, Dipak, Taghizadeh, Salar, Mohapatra, Chinmoy K.
Experimental Validation of a Multi-Row Tapered Roller Bearing Analytical Model for Relating Preload to Frequency Response Characteristics2026-01-0008To be published on 04/07/2026
Roller bearings are used in many rotating power transmission systems in the automotive industry. During the assembly process of the power transmission system, some types of roller bearings (e.g., tapered roller bearings) require a compressive preload force. Those bearings' rolling resistance and lifespan strongly depend on the preload set during the installation process. Therefore, accurate setting of the preload can improve bearing efficiency, increase bearing lifespan and reduce maintenance costs over the life of the vehicle. A new method for bearing preload measurement has shown potential for both high accuracy and fast cycle time using the frequency response characteristics of the power transmission system. An open problem is experimental validation of the multi-row tapered roller bearing analytical model. After validation, the analytical model can be used to predict the assembled system damped natural frequency for a desired bearing preload. This work presents the experimental
Gruzwalski, David, Mynderse, James
Determining Video Frame Capture Rate through Reverse Engineering2026-01-0543To be published on 04/07/2026
The timing of video recordings, along with the spatial positioning of objects, is a fundamental parameter for calculating the speed time history. If the task involves determining an object’s average speed over several to a dozen frames, the average inter-frame interval can be used as the basic time unit. However, if the objective is to compute speed from individual frames, the reliability of the timing becomes crucial. Without access to DVR hardware documentation, proprietary algorithms, or software – and considering the frequent hardware modifications and software updates - the most effective way to solve the problem is through a reverse-engineering approach. This study discusses several aspects of timing analysis, including: (1) making a test recording of a calibrated LED lightboard; (2) analyzing the relationship between the lightboard time and the presentation time stamp (pts) extracted from the file metadata; (3) investigating frequency interference occurring when recordings are
Wach, Wojciech
Mathematical Modeling of Trust Calibration for Human–Automation Safety2026-01-0530To be published on 04/07/2026
Trust between humans and automated vehicles is increasingly recognized as a pivotal factor in achieving safety in advanced vehicles and mobility environments. Poorly calibrated trust—either over-trust leading to complacency or under-trust leading to disengagement—has been identified in numerous incidents involving advanced driver assistance systems and autonomous functions. Yet, most current approaches to managing trust rely on surveys, heuristics, or qualitative assessments, providing little predictive capability for safety engineers and system designers. This paper presents a formal mathematical framework for trust calibration, modeling trust as a dynamic, evolving construct grounded in probabilistic reasoning. We represent trust as a Beta-distributed belief that updates over time through Bayesian inference, with parameters adjusted by observed successes and failures, contextual cues, and system feedback signals. The model also incorporates forgetting and drift functions, allowing
Wen, He, Mounir, Adil
OFEODM: An Onboard Fast and Efficient Object Detection and Distance Prediction Model2026-01-0017To be published on 04/07/2026
Object detection and distance prediction have advanced significantly in recent years. The YOLO series has released its 11th version, along with numerous variants that have been applied across various fields. Meanwhile, the Detection Transformer (DETR) has repeatedly set new state-of-the-art (SOTA) records in the field of object detection. Depth Anything also released its second version last year, further pushing the boundaries of distance detection. Although these models achieve impressive performance, they often require substantial computational resources. However, for algorithms intended for real-world applications and deployment on onboard devices, computational resources are limited and valuable. Inference time per frame is a critical factor in ensuring an algorithm's reliability and feasibility. Designing a model that operates in real time without sacrificing accuracy remains an extremely challenging problem, and extensive research is ongoing in this area. To address this
Li, Taozhe, Wang, Hanchen, Hajnorouzali, Yasaman, Xu, Bin
Embedded Coding Agent: Natural-Language Driven Generation of AUTOSAR & Non-AUTOSAR Embedded C/C++ code2026-01-0105To be published on 04/07/2026
Embedded software development in the automotive sector is becoming more demanding as engineers balance performance, safety, and certification requirements. Traditional approaches such as manual coding or model-based workflows require significant effort in writing boilerplate code, ensuring AUTOSAR compliance, and preparing verification artifacts for audits. Commercial tools like MathWorks Simulink Embedded Coder already provide model-to-code generation capabilities, but these solutions are often costly and may not be viable for budget-sensitive domains such as two-wheelers and three-wheelers. This creates a strong need for alternative, more accessible approaches that can deliver efficiency without compromising on quality. This paper introduces an embedded coding agent designed to address this gap. The agent accepts natural language or structured prompts and generates AUTOSAR-compatible ARXML as well as embedded C and C++ implementations. Unlike general-purpose coding assistants, it is
Daware, Kartik
Model-Based Development of the “Big 5” in Fuel Cell Systems2026-01-0072To be published on 04/07/2026
Fuel cell systems are gaining traction across heavy-duty applications, driven by global decarbonization targets. Managing their inherent complexity and diverse architectural requirements, commonly organized into the “Big 5” fuel cell subsystems (stack, thermal, electric, anode, and cathode), necessitates advanced Model-Based Development (MBD) approaches. This paper presents and validates a constraint-graph-based, equation-oriented, acausal MBD methodology for fuel cell system (FCS) development, implemented in an industrial modeling environment. This methodology supports scalable functional and software development from 75 kW single-stack systems to twin-stack configurations exceeding 250 kW. It facilitates robust parameterization and reuse of consistently formulated, subsystem-level physical models across Model-in-the-Loop (MiL) to Hardware-in-the-Loop (HiL) environments, ensuring numerically robust software architectures and improved embedded control quality. Industrial application
Bandi, Rajendra Prasad, Bleile, Thomas
Data-Driven Objective Road-Driving Classification For Durable Design Of Vehicles2026-01-0181To be published on 04/07/2026
Durability development in the automotive industry depends on a clear understanding of how road surfaces and driving characteristics affect structural road loads and fatigue. Traditionally, road surface classification has been subjective (e.g., city, highway, rural), and done through driving instrumented vehicles over a small selection of roads. The variations in driving characteristics that are often consequent to the road surface quality is rarely accounted for in designing vehicle level durability tests. This makes it difficult to establish targets for the durability testing that accurately match the wide variations in real-world roads and driving across the market of vehicles. This paper presents a data-driven approach to objectively classify road surface and driving characteristics using metrics derived from existing vehicle and road response metrics like Vibration Dose Value (VDV), International Roughness Index (IRI) and statistical estimates of vehicle speed and acceleration
Shaurya, Shubham, Ramakrishnan, Sankaran, Demiri, Albion, Khapane, Prashant
Quantifying Accuracy and Robustness to Guide Fidelity Selection for Multi-fidelity Vehicle Dynamics Models2026-01-0149To be published on 04/07/2026
Accurate and reliable simulation models are essential for design, development, and performance evaluation during virtual vehicle testing. However, fidelity assessment and validation remain a challenge. While error metrics are used to evaluate simulations, they alone do not capture how reliable predictions are, or how robust models are to varying driving scenarios and modeling assumptions. This work develops a systematic quantitative approach for evaluating vehicle dynamics model fidelity, moving beyond traditional visual or qualitative comparisons. A dimensionless fidelity metric is proposed that integrates error and uncertainty into a single measure, enabling objective accuracy assessment of variable-fidelity simulations. This framework supports fidelity selection in vehicle dynamics, providing clearer insight into tradeoffs between computational cost and achievable accuracy, and advancing the goal of reliable virtual testing. This approach is demonstrated on an open-loop vehicle
Emara, Mariam, Balchanos, Michael, Mavris, Dimitri
A Study on Fatigue Life Prediction Method for Point-Based Joints Considering Multiple Fracture Modes – FDS, Blind Rivet, and Blind Nut Focus2026-01-0180To be published on 04/07/2026
The application of light weight alloys for vehicle bodies such as aluminum alloys and composite materials are rapidly advancing to support the construction of multi-material vehicle bodies. These materials play a crucial role in reducing overall vehicle weight, enhancing fuel efficiency, and complying with increasingly strict environmental regulations. As the automotive industry continues to evolve toward electrification and sustainability, the integration of lightweight and high-performance materials has become a key design strategy. However, the use of multiple materials introduces new challenges in manufacturing, particularly in joining technologies. Since different materials have varying mechanical properties, thermal behaviors, and surface characteristics, selecting appropriate joining methods is essential to ensure structural integrity and durability. Depending on the material types, thicknesses, production processes, and cost constraints, various joining techniques—such as
Takuno, Sougo, Isono, Toshiyuki, Urakawa, Kazushi, Goto, Suguru, Kawamura, Hiroaki, Niisato, Eita, Ishigami, Yuta
Multi-Objective Reinforcement Learning Framework for Transmission Shift Schedule Optimization2026-01-0162To be published on 04/07/2026
Building upon previous work that successfully employed a Reinforcement Learning (RL) agent for the autonomous optimization of transmission shift programs to enhance fuel efficiency , this paper addresses a critical limitation of that approach: the neglect of human-centric factors. While the prior methodology achieved substantial fuel consumption reductions by training an RL agent in a Software-in-the-Loop (SiL) environment, it did not explicitly account for aspects such as driver comfort and preferences, which are paramount for realworld user acceptance and drivability. This work presents a multi-objective optimization framework extending the artificial calibrator to simultaneously maximize fuel efficiency and enhance driver comfort. The method introduces a modified RL reward function that penalizes undesirable shift behavior to ensure a smooth driving experience (drivability). This new methodology also incorporates a mechanism to capture and integrate driver preferences, moving beyond
Kengne Dzegou, Thierry Junior, Schober, Florian, Rebesberger, Ron, Henze, Roman, Sturm, Axel
Analysis of the biofidelity of aPLI under low-speed collision conditions2026-01-0551To be published on 04/07/2026
Abstract: With the increasing popularity of automotive active safety systems, the probability of collisions between vehicles and pedestrians has gradually decreased. Among them, the AEB system, as an important part of active safety systems, can actively intervene to avoid collisions in advance. However, in actual road traffic conditions, there are still situations where the AEB system cannot completely avoid collision accidents, and the impact speed between pedestrians and vehicles may drop to below 40 kph. However, the aPLI legform impactor, which is widely used in pedestrian protection evaluations in various regions, has a standard impact speed of 40 kph in the test procedure. The response of the aPLI to low-speed collisions and the resulting pedestrian leg injuries is still unclear. Based on finite element simulation, this study compared the kinematic responses and injury responses of the aPLI impactor with human body models (THUMS and GHBMC) under 5 different speeds (20kph, 25kph
Sun, Bowen, YE, BIN, LONG, YONGCHENG, Zhan, Zhenfei, shi, Xinxin, jun, yin
AI-Enhanced Functional Safety in ADAS Controllers: Predictive Fault Management under ISO 262622026-01-0036To be published on 04/07/2026
Ensuring ISO 26262 functional safety in advanced driver assistance systems (ADAS) is increasingly complex as these platforms adopt artificial intelligence for perception and control. Traditional safety mechanisms are deterministic, but AI introduces non-determinism that challenges verification and validation. This paper presents a predictive fault management framework that enhances functional safety in ADAS controllers using AI-driven models. Real-time vehicle and sensor data are processed through machine learning algorithms that forecast hardware and software faults before they escalate into hazardous conditions. These predictive insights are coupled with ISO 26262 safety mechanisms to enable adaptive diagnostics, fault isolation, and recovery strategies. Hardware-in-the-loop (HIL) validation demonstrates up to a 25% improvement in diagnostic coverage compared to conventional monitoring, while maintaining ASIL-D compliance and real-time performance. By showing how AI can complement
Abdul Karim, Abdul Salam
Simulation verification and design guide for P1+P2 hybrid built-in damper system2026-01-0006To be published on 04/07/2026
Among the hybrid system methods, the TMED (Transmission mounted electric device) method is divided into the TMED-1 system driven by the existing mass-produced P0+P2 motor and the TMED-2 system driven by the P1+P2 motor. It is known that the TMED-2 method improves power and fuel efficiency by about 10% or more compared to the TMED-1 due to the intervention of the P1 motor, and that carbon emissions can be reduced due to the improvement of engine thermal efficiency. However, the TMED-2 system is a structure that replaces the P0 motor with the P1 motor to improve power performance and transmission efficiency. The P1 motor is disadvantageous in terms of mountability due to its longer overall length compared to the P0. To solve this problem, the existing external damper system was designed and shaped to be assembled into the inner space between the P1 and P2 motors (built-in damper system), thereby securing mountability. The main development item that our company is currently researching is
Sun, Hyang Sun, GANESAN, KARTHIKEYAN
Optimizing Weld Placement in Automotive Structures Using Topology and Multi-Disciplinary Approaches2026-01-0514To be published on 04/07/2026
This work presents two approaches for weld optimization aimed at reducing manufacturing cost and process time, while meeting structural performance requirements in automotive structures. The first approach uses topology optimization to identify the most efficient weld layouts. A design space is generated along mating flanges, joints, and panel interfaces, where potential weld locations are defined. Welds are treated as discrete design variables, and the topology optimization systematically evaluates their contribution to global stiffness and load path integrity. Non-critical welds, those with minimal impact on stiffness, durability, or crashworthiness, are eliminated, resulting in a minimized weld pattern that maintains structural performance. The second approach applies Multi-Disciplinary Optimization (MDO) to balance weld reduction with performance targets across multiple domains, including linear and non-linear stiffness, crashworthiness, and fatigue. Using a preprocessing tool
Koppaka, Vinaya, Yoo, Dong Yeon, Chavare, Sudeep
Operational Feasibility of Battery Swapping in U.S. Transit: A Case Study of King County Metro2026-01-0402To be published on 04/07/2026
Battery swapping technology has emerged as a promising alternative to conventional plug-in charging for electric bus fleets, offering rapid turnaround times and improved vehicle availability. This paper investigates whether battery swapping can be integrated into U.S. public transit bus operations without disrupting existing timetables. A Seattle based public transit agency- King County Metro is taken as a case study in this paper. Using General Transit Feed Specification data from King County Metro, a MATLAB model was built that reconstructs blocks and layovers, extracts dwell-time opportunities, and performs block distance and block time analyses to understand operational rhythms. A mathematical energy model was developed that maps route mileage, efficiency, and layover availability to swap decisions, using a look-ahead rule that defers exchanges whenever the next feasible layover can still be reached while respecting a minimum state-of-charge. The workflow estimates how many swaps
Vadlapatla, Taraka Rishi, Jankord, Gregory, D'Arpino, Matilde
Development and Validation of a Self-Propelled Trailer: A Standards-Based Approach to Enhancing Compact Vehicle Towing2026-01-0055To be published on 04/07/2026
This paper presents a structured test plan for the development and validation of a Self-Propelled Trailer, an emerging concept designed to enhance the towing capacity of compact, fuel-efficient vehicles. Unlike conventional trailers, the proposed system integrates a drivetrain in the trailer, which could consist of either electric propulsion or some other type of power source. It also includes sensing capabilities in the trailer hitch to determine what the effort provided by the towing vehicle is, along with a control system to use this data to appropriately modulate the power provided by the trailer. This autonomous system will actively assist the towing vehicle, reducing engine load and improving fuel economy. Safety, however, is a critical factor in a successful design for such a system, and appropriate testing needs to be planned and carried out as the system is developed. The methodology to do so employs a Design Failure Mode and Effects Analysis (DFMEA) to systematically identify
Reilly, Carter, Peters, Diane, Zadeh, Mehrdad
Impedance Characterization of an Automotive Battery Pack2026-01-0381To be published on 04/07/2026
Parasitic inductance and capacitance of the battery pack can affect the performance of the electric powertrains. Characterizing these parasitic phenomena in an automotive battery pack is therefore crucial to ensuring performance and reliability. In this work, geometric models of a production automotive battery pack are developed to simulate the parasitic inductance of the busbar system, the parasitic inductance of individual modules, and other critical components. For these simulations, several assumptions and simplifications are introduced to reduce model complexity, while preserving the main electromagnetic behavior of the system. The impact of the different components on the battery pack impedance is investigated to evaluate parasitic capacitances, thereby simulating the worst-case scenario. Laboratory procedures are developed to accurately measure parasitic impedance, providing a reliable comparison between experimental data and analytical models and supporting the overall validity
Misley, Marco, D'Arpino, Matilde, ZHU, Di, Zhang, Liwen
Attention and Intrinsic Curiosity-Enhanced Deep Reinforcement Learning for Path Planning in Dynamic Environments2026-01-0044To be published on 04/07/2026
Efficient and reliable path planning remains a core challenge for autonomous vehicles operating in dynamic and crowded environments. Although Deep Reinforcement Learning (DRL) has shown considerable potential in autonomous decision-making, it still faces challenges such as insufficient feature extraction, sparse rewards, and low obstacle avoidance efficiency in complex scenarios. To address these issues, this paper proposes an end-to-end path planning framework, PPO-ICM-Attn. Built upon the Proximal Policy Optimization (PPO) algorithm, the framework incorporates a dual-channel attention convolutional neural network module (Attention-CNN) to enhance spatial and semantic understanding of dynamic obstacles, and introduces an Intrinsic Curiosity Module (ICM) to promote active exploration in sparse reward settings. Furthermore, a reactive avoidance reward function based on velocity obstacle theory is designed and embedded to achieve real-time proactive collision avoidance in highly dynamic
Shen, Shiquan, Liu, Jiahao, Chen, Zheng, Li, Zongdian, Zhao, Yuting, Wu, Minggong, Zhao, Jie, Qin, Zongquan, Wang, Yanfeng
Numerical Analysis of Operating Parameters Coupled Effects on Flow Instability Mechanisms at Supercritical Pressure2026-01-0134To be published on 04/07/2026
Supercritical fluids (SCFs) are widely utilized in advanced energy systems due to their exceptional heat transfer characteristics. However, flow instability, particularly near pseudo-critical conditions, poses a significant challenge to their effective applications. Despite extensive research, the coupled effects of thermal and fluid dynamic mechanisms on flow instability remain insufficiently understood, particularly in supercritical water (SCW) systems. This study identifies the onset of flow instability (OFI) in the negative slope region of pressure drop curve during steady-state conditions, analyzing the relationship between pressure drop and mass flow rate. Transient analyses were then conducted to investigate the influence of operating parameters on oscillatory phenomena such as pressure drop oscillations (PDO), density wave oscillations (DWO), and thermal oscillations (ThO). The results show that higher mass flow rates and heat fluxes, reduce pressure oscillations by up to 20
Rehman, Attiq, Ahmad, Hassaan, Du, Xiaocheng, kanwal, Lubna
Advancing Electric Drive Unit Design with Smoothed Particle Hydrodynamics (SPH).2026-01-0413To be published on 04/07/2026
The performance of Electric Drive Units (EDUs) in electrified powertrains heavily depends on efficient thermal and lubrication management. Accurate assessment of lubrication flow, particularly in terms of wettability and churning losses, is essential for optimizing EDU performance across various driving conditions. This paper presents a comprehensive numerical investigation of lubrication flow behavior within an EDU using an advanced Smoothed Particle Hydrodynamics (SPH) method. The mesh-free SPH approach provides significant advantages in modeling intricate oil dynamics, such as oil splashing, and the behavior of oil in contact with rotating components. The primary focus of this study is to investigate the phenomena of splashing, wettability, and churning losses under various operating conditions within the gearbox environment. Key flow characteristics such as oil distribution, particle trajectories, torque resistance due to fluid drag, and oil volume fraction are analyzed under
Chintala, Paramesh, Inada, Jorge, Flores Solano, Cesar Alfonso, Gingade, Suresh
Investigation of In-Cylinder Cycle-to-Cycle Variation Using PIV, LIF and RANS Simulation2026-01-0299To be published on 04/07/2026
To elucidate the cycle-to-cycle variations (CCV) in gas flow and combustion within gasoline engine cylinders, simultaneous two-section PIV and LIF measurements were performed using an optical engine, coupled with RANS simulations. The results revealed the following: The variation in the equivalence ratio per cycle has little effect on initial combustion but does influence IMEP. Evaluating the laminar combustion velocity (SL) and turbulent combustion velocity (ST) as factors determining initial combustion revealed almost no correlation with SL, while moderate correlations were observed between ST and CA10. The position of the tumble vortex center at ignition timing was found to be critical; the vortex center position most favorable for advancing combustion timing was located to the right and below the spark plug. Under nitrogen-enriched conditions with a dilution ratio of approximately 40%, cycle fluctuations increased. Concentration characteristics of THC and CO, obtained from high
Hokimoto, Satoshi, Moriyoshi, Yasuo, Kuboyama, Tatsuya
CFD-Guided DoE-ML Optimization Methods in a Heavy-Duty Hydrogen Engine2026-01-0326To be published on 04/07/2026
This study introduces a CFD-guided Design of Experiments (DoE) and Machine Learning (ML) framework for the co-optimization of piston and pre-chamber geometries in a passive pre-chamber heavy-duty hydrogen engine operating at medium and low loads. Starting from a reference configuration—an omega-type piston and a methane-optimized pre-chamber—the design space was parameterized using seven geometric variables. A Sobol sequence was employed to generate 96 randomized design variants in the DoE, each evaluated through high-fidelity 3D-CFD simulations to capture key combustion and performance metrics. The resulting dataset served as the foundation for developing and evaluating several ML regression models. A rigorous ML workflow was adopted, featuring 5-fold cross-validation and hyperparameter tuning via Bayesian optimization to ensure generalization and robustness. Model selection was based on multi-metric performance criteria including prediction accuracy, error stability, and sensitivity
Menaca, Rafael, Shakeel, Mohammad Raghib, Liu, Xinlei, Mohan, Balaji, AlRamadan, Abdullah, Cenker, Emre, Silva, Mickael, Zhang, Anqi, Pei, Yuanjiang, Im, Hong
Multi-Objective Topology Optimization for Cost and Time Minimization in Fiber Reinforced Additive Manufacturing2026-01-0257To be published on 04/07/2026
Fiber Reinforced Additive Manufacturing (FRAM) combines the geometric freedom of additive manufacturing with the high strength-to-weight ratio of composite materials, enabling the production of lightweight, high-performance automotive components. The anisotropic nature of fiber-reinforced composites makes their mechanical performance highly dependent on fiber orientation relative to applied loads. Leveraging this directional behavior through optimization provides opportunities to enhance structural efficiency while reducing vehicle weight. Conventional FRAM research has largely focused on structural objectives such as compliance minimization, often overlooking manufacturability challenges. In particular, support structures - temporary features required for overhang fabrication - can significantly increase print time, material usage, and production cost, limiting industrial adoption. To address this gap, this research introduces a novel multi-objective topology optimization framework
Wotten, Erik, Kim, Il Yong
Numerical Study of Gasoline Direct Injection Sprays across Different Operating Conditions using a Machine-Learning-Based Rate of Injection2026-01-0338To be published on 04/07/2026
Gasoline Direct Injection (GDI) is a key technology for increasing engine efficiency and reducing criteria pollutants, often in combination with boosted operation and engine downsizing. The development of advanced GDI injection systems is increasingly focused on refining the in-cylinder spray process, encompassing spray formation, mixing, and combustion, to achieve both homogeneous and stratified combustion. Given the broad spectrum of operating conditions, from cold-start to early and late injections at different engine loads, accurately modeling the spray formation and its evolution presents significant challenges. This study reports on a computational fluid dynamics investigation of spray morphology across different injection pressures under both cold-start and late-injection conditions. Due to a lack of information regarding the rate of injection (ROI) for the targeted injectors, a recently developed machine-learning-based model is used to extract the ROI from optical data of
Lien, Hao-Pin (Paul), Torelli, Roberto, Zhao, Le, Park, Ji-Woong, Zhang, Anqi, Pei, Yuanjiang, Hwang, Joonsik, Lee, Kyungwon
Analyzing Fastened Joints in Hydraulic Dampers using Simulation and Experimental Methods2026-01-0585To be published on 04/07/2026
The main purpose of this study is to develop and validate an accurate calculation model for an unorthodox hydraulic damper piston joint, enabling reliable torque specification and clamp behavior without full prototype iteration. The joint features a bolted interface with a laminated shim stack of many thin disks with varying outer diameters. Analysis of such unorthodox joints are uncommon in literature, making the effects of load distribution truncation in the member stack due to varying outer diameters and surface contact effects between thin members during compression and torquing difficult to quantify. The model discussed in this paper is based on frustum load distribution combined with annular-plate bending and elastic-foundation effects to capture the effects of washer cupping. Concrete outputs of the calculator include member load distribution, bolt and member stiffnesses, torque-to-preload relationships, including friction factors and a variable effective-bearing-diameter, and
Dresen, Gabriel S., Vollmar, Race, Roy Chowdhury, Sourav
Risk analysis of occupant injuries with different lower limb postures during vehicle frontal impact2026-01-0572To be published on 04/07/2026
To investigate the biomechanical characteristics of injuries sustained by occupants with different lower limb postures during frontal impact, the human body finite element models- THUMS AM50 under standard sitting posture and sitting posutres with 100° calf bend, 90° calf bend, and crossed legs were analyzed in the frontal impact at 56 km/h. Injury biomechanical analysis demonstrates that the occupant under the sitting posture with crossed legs has the highest overall injure risk, e.g, the highest HIC (Head Injury Critirion) value, peak value of head accerelation, VC (Viscous Crterion) values, strain of the thracic organs, stress of pelvic cortical bone and knee ligments, and so on. In summary, different lower limb postures can affect the overall risk of occupant injury: the smaller the calf flexion angle and the more complex the leg posture, the higher the risk of overall injury. In the future study it is necessary to strengthen the protection of occupants in non-standard seating
Li, Dongqiang, jiang, Yejie, Tan, Chun, Li, Yanyan, HeQuan, Wu, Jiang, Binhui, Zhu, Feng
Generative Agents for High-Fidelity Simulation of Community-Scale Mobility and Energy Behavior2026-01-0465To be published on 04/07/2026
The transition to sustainable mobility and energy systems is a complex socio-technical challenge, where the success of new technologies and policies hinges on their interaction with human behavior. Traditional models often fail to capture the nuanced, heterogeneous, and adaptive nature of occupant decision-making, particularly in terms of mobility choices and energy use, creating a critical uncertainty gap for system design and policy evaluation. This paper presents a new paradigm to address this gap: a scalable, high-fidelity simulation framework based on Generative Agents. The framework's core innovations are twofold: 1) It leverages Large Language Models (LLMs) to autonomously generate agents with intrinsic personality traits autonomously, enabling a realistic simulation of diverse, human-like responses to environmental, social, and transportation-related cues. 2) It introduces a hierarchical "Prototype-Individual" architecture that makes large-scale simulation of entire communities
Chen, Yongjian, Yang, Zhifeng, Ou, Shiqi(Shawn)
Accurate simulation of Sealing process using a GPU-accelerated Lagrangian differencing dynamics method2026-01-0492To be published on 04/07/2026
A vehicle body consists of many parts, between which there are seams and gaps that water, dust, and noise can enter. To prevent corrosion and reduce noise, these gaps are sealed with a paste featuring complex non-Newtonian properties. Sealing also serves a cosmetic function for visible areas, which demands high quality for better customer satisfaction. Usually, seam length can reach several meters with a height of 0.5-5 mm and a width of 5-40 mm. In this situation, optimizing the robotic paths and sealant flow can speed up production and reduce costs. Accurate and fast CFD modeling helps with planning the sealing process, shortening vehicle development cycles and minimizing costs. Due to the complexity of vehicle body geometry, arbitrary robotic movements, sealing seam length, free surface, and the complex rheological material properties, traditional CFD simulations have difficulties in modelling this process. This paper presents a new framework for modelling the sealing processes
Panov, Dmitrii Olegovich, Zhu, Huaxiang, Basic, Josip, Zhang, Lingran, Kotian, Akhilesh, Menon, Muraleekrishnan, Borra, Ravi Kanth, Ando, Yuya
ML FMEA in Action: Lessons from Applications of Machine Learning Safety2026-01-0079To be published on 04/07/2026
Introducing machine learning (ML) into safety-critical systems presents a fundamental challenge, as traditional safety analysis techniques often struggle to capture the dynamic, data-driven, and non-deterministic behavior of learning-enabled components. To address this gap, the Machine Learning Failure Mode and Effects Analysis (ML FMEA) methodology was developed as an open-source framework tailored to ML-specific risks. This paper reports on the maturation of ML FMEA from an initial conceptual framework to a proven, practice-driven methodology. We make four primary contributions. First, we extend the ML FMEA pipeline with two new stages: a “Step Zero” for problem definition and system-level hazard analysis, and a “Step 5” for constructing ground truth or reward signals. Autonomous vehicle and humanoid robot applications are presented to illustrate the practical application and safety benefits of these additions. Second, we introduce tailored Severity, Occurrence, and Detection
Schmitt, Paul, Ward, David, Shinde, Chaitanya, Chalana, Akshay, Pennar, Krzysztof, Wagner, Michael, Poh, Justin, Seifert, Bodo, Mohammed, Majed, Lopez, Jerry, Wadhvana, Neil, Mannan, Fahim, Diemert, Simon
Machine Learning-Based Prediction of Wind-Induced Interior Noise in Ground Vehicles2026-01-0599To be published on 04/07/2026
In response to increasing customer demand for enhanced passenger comfort and perceived vehicle quality, OEMs in automotive and commercial vehicles are placing significant emphasis on reducing the interior cabin noise. At highway speeds, wind noise is a primary contributor to the overall noise within the vehicle cabin. Conventional approaches to predict vehicle wind noise rely on physical testing, which can only be conducted in the later stages of the design process once a physical prototype is available. Increased adoption of established computational fluid dynamics (CFD) methods has enabled earlier assessment. However, such simulations require several hours to complete, posing a challenge in the context of rapid design iteration cycles. With the growing adoption of artificial intelligence in engineering, machine learning (ML) approaches have been proposed to predict a vehicle’s aerodynamics performance. Nevertheless, development of ML techniques in the context of aeroacoustics
Higgins, John, Fougere, Nicolas, Sondak, David, Senthooran, Sivapalan, Moron, Philippe, Jantzen, Andreas, Bi, Jing, Oancea, Victor
Introduction to Catesby Aero Research Facility, CARF, the coast-down tunnel proving ground.2026-01-0611To be published on 04/07/2026
This paper reports on the Catesby Aero Research Facility (CARF), which began commercial use in 2019, and provides an overview of the facility and related technologies, particularly details on the vehicle-mounted component force measurement devices. CARF is a proving ground that was renovated from a former railway tunnel approximately 2.74km long and is now covered with high-quality tarmac. The road surface quality was designed to be at least as good as that of SUBARU's proving ground, and the standards were achieved using British construction technology. The course is almost straight, but there is a slight incline. The course specifications are: blockage 40m2, road width 6m (maximum 8.4m), flatness σ<0.5mm, and gradient 0.57%.In particular, compared to outdoor coastdown trucks, its overall length allows for continuous measurement right up to the stop, giving it a significant advantage in repeatability.At the same time, Subaru's newly developed six-component force sensor built into the
Shimoyama, Hiroshi
26M-00552026-01-0603To be published on 04/07/2026
Since air drag is proportional to the square of the speed, it is expected that reducing air drag will significantly improve fuel efficiency for long-distance trucks and buses, which are often driven at high speeds. Therefore, the purpose of this study is to propose a conceptual shape that will dramatically improve the aerodynamic performance of heavy-duty vehicles, assuming that restrictions on overall length will be relaxed in the future. Using NSGA-II, a genetic algorithm, the overall vehicle shape was optimized with the objective functions CD and CL values and design variables as parameters in a total of 13 locations. Among the Pareto solutions, CD = 0.08 was obtained when the CD value was the lowest. Since the CL value remains low with this shape, it can be seen that driving stability does not deteriorate. Among the design variables in optimization, it was confirmed that the corner radius of the vehicle side was particularly effective in reducing the CD value. In addition, when
Kawano, Daisuke
Comparing the Dynamic Response of a Rolling Tire using Data Collected using a 3D Scanning Laser Doppler Vibrometer2026-01-0592To be published on 04/07/2026
Detailed tire response data is necessary to advance vehicle safety, and monitor real time tire health. This study presents a non-contact experimental method to measure the vibratory characteristics of a tire subject to shaker excitation and road rolling forces. A Global Electric Motorcars (GEM) E4 electric vehicle was mounted on a chassis dynamometer to simulate loading conditions in a controlled environment. Scanning laser vibrometry (SLDV) was employed to capture out of plane velocity responses across the tire surface using a three independent laser configuration. This technique enables visualization of mode shapes under static and dynamic excitation. The results from SLDV identified the tire’s dominant resonant frequencies and corresponding operating deflection shapes under both static and dynamic conditions at different velocities. The dynamic measurements revealed that the harmonics of rotational frequency dominated higher order structural responses. Incorporating a reference
Gower, Adam, Baqersad, Javad, Gupta, Arjun
AI-Driven Data Consistency and Relationship Inference System for Agile Component Library Management2026-01-0109To be published on 04/07/2026
Reliable component libraries are the foundation of the engineering process and the starting point for all intelligence within CAD tools. In practice, however, libraries created and maintained by librarians often contain incomplete, inconsistent, or outdated data. This paper introduces the component data consistency and relationship inference AI system, developed within Amoeba software, which addresses these challenges by improving component library quality. The system uses AI to infer component attributes such as component type, gender, color, material, etc. Moreover, it can identify relationships such as the family a connector is associated with based on its attributes and geometry. The system improves data consistency in areas such as resolving mismatched wire size constraints imposed by the connector and cavity components. It also utilizes computer vision to identify common connector footprints, cavity sizes, and 2D symbol geometries. Deployed within Amoeba software, the system has
Phan, Dung, Horvat, Bryan
Model-Based Design and dSPACE/MathWorks Environment Enable Innovative Engineering Education2026-01-0073To be published on 04/07/2026
The exponentially growing complexity of engineering systems, such as a robotic system, an autonomous vehicle, and an unmanned aerial vehicle, requires sophisticated control strategies that can efficiently coordinate the system’s operation in various environments. The traditional control design approaches present significant challenges for control engineers to keep up with the increasing complexity and changing requirements. To advance embedded control system design, a paradigm shift from traditional development approaches toward more structured, systematic methodologies that can manage the multi-domain nature of control systems is critically needed. Model-based design approach is emerging as a solution for this demand. Model-based design approach uses a system model for control system development, from requirements capture to control system design, implementation, and testing. It provides an integrated environment for design, implementation, automatic code generation, and validation
Repaka, Sindhura, Chen, Bo
A Real-Time Repositioning Strategy for SAEV Fleets Using a Simulation-Informed Deep Learning Model2026-01-0035To be published on 04/07/2026
Shared Autonomous Electric Vehicles (SAEVs) can enhance urban mobility and efficiency. However, their operational performance is often hindered by the spatio-temporal imbalance between vehicle supply and passenger demand, leading to long wait times. This paper develops a novel repositioning framework where a lightweight CNN, informed by computationally intensive multi-agent simulations, enables real-time strategy deployment. The results show that: (1) An optimized repositioning policy, calibrated via multi-agent simulation, effectively cuts the mean passenger waiting time from 12.0 to 3.0 minutes (a 75% reduction). (2) A lightweight CNN surrogate model enables real-time deployment, reducing the policy computation time from ~4 hours to ~5 minutes (>98% faster). (3) The deep learning surrogate achieves this speed with a negligible performance trade-off, increasing the waiting time by only 0.156 minutes (4.9%) compared to the full optimization.
Shang, Kai, Wang, Ning
The Impact of Extreme Ambient Temperatures on Electric Vehicle Performance in the Kingdom of Saudi Arabia2026-01-0133To be published on 04/07/2026
The rapid expansion of Saudi Arabia’s electric vehicle sector driven by manufacturers such as CEER Lucid Tesla and BYD necessitates evaluating vehicle performance under extreme thermal conditions. This study investigates the impact of high ambient temperatures on electric vehicle operation by analyzing a 60 kWh NMC battery pack under representative Riyadh summer conditions of up to 47 °C using MATLAB Simulink simulations. The results show that elevated temperatures accelerate state of charge (SOC) depletion and increase battery internal resistance. To maintain safe operating limits the BTMS must operate continuously consuming up to 20 percent of the available energy. Cooling demand increases nonlinearly with temperature exceeding 40 kW at 50 °C which leads to significant parasitic losses and a 15 to 20 percent reduction in driving range. At the system level this increased energy demand raises charging frequency and intensifies electricity load during peak summer periods thereby
Bedywi, Lama Mohammed A, AlJuhani, Haneen, Duan, Chen, AbdulNour, Bashar
Simulation of Conjugate Heat Transfer using the Lattice Boltzmann Method2026-01-0135To be published on 04/07/2026
Flow simulation with conjugate heat transfer, which involves fluid flow, conduction, and radiation in solid components, is a critical capability that helps engineers design and evaluate cooling systems for heat-generating components such as brakes, powertrains, batteries, and power electronics for both gasoline and electric vehicles. For this study, we utilize PowerFLOW™, featuring its novel native thermal solver, which models both fluid and solid domains within a single model. For the flow domain, we use the Lattice Boltzmann Method with VLES turbulence modeling based on the RNG k-epsilon method. And for the solid domain, the finite volume method with second-order accuracy for thermal conduction and a surface-to-surface radiation for the surfaces. This approach not only leads to a more integrated and streamlined workflow but also enables an accurate modeling of conduction and radiation. In this study, we demonstrate the accuracy of the conjugate heat transfer simulation methodology
Mukutmoni, Devadatta, Shock, Richard, Li, Han, Wanderer, John
Ultra-Low Latency Video Pipeline Optimization for Perception-Centric Autonomous Systems2026-01-0022To be published on 04/07/2026
Autonomous platforms such as self-driving vehicles, advanced driver-assistance systems (ADAS), and intelligent aerial drones demand real-time video perception systems capable of delivering actionable visual information at ultra-low latency. High-resolution vision pipelines are often hindered by delays introduced at multiple stages-sensor acquisition, video encoding, data transmission, decoding, and display-undermining the responsiveness required for safety-critical decision making. This study introduces a holistic system-level optimization framework that systematically reduces end-to-end video latency while maintaining image fidelity and perception accuracy. The proposed approach integrates hardware-accelerated encoding, zero-copy direct memory access (DMA), lightweight UDP-based RTP transport, and GPU-accelerated decoding into a unified pipeline. By minimizing redundant memory copies and software bottlenecks, the system achieves seamless data flow across hardware and software
Indrakanti, Rama Kiran Kumar
Integrated Design and Validation of a Robust Lane Centering Controller for Automated Driving.2026-01-0037To be published on 04/07/2026
Lane centering is a critical active safety feature whose effectiveness depends on robust design and validation across diverse driving conditions. This paper presents the development of a Lane Centering Controller (LCC) using a structured model-based design workflow in MATLAB and Simulink. A kinematic bicycle model was employed to simulate vehicle dynamics and evaluate an angle based steering controller integrating both feedforward and feedback control paths. The controller was tested across multiple road geometries and speeds up to 65 mph to ensure tracking consistency and stability under nominal and perturbed conditions. Perception noise models for lane curvature and curvature rate were extracted from onboard camera data under controlled conditions, revealing Gaussian characteristics. No filtering was applied, allowing direct evaluation of the controller’s inherent robustness to raw signal variability. The LCC maintained a peak lateral offset within ±0.35 m and lateral jerk within ±9
Bijinepalli, Ravi Teja, Tambolkar, Pooja, Midlam-Mohler, Shawn
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