Browse Topic: Vehicle dynamics

Items (8,590)
This study investigates the gradeability performance of an L7e-class electric micro truck from both vehicle dynamics and thermal perspectives. A 1D simulation model (Amesim) was developed and validated with multiple test results. Using inputs such as motor characteristics, drivetrain configuration, and vehicle mass, the model analyzed vehicle performance on a 20% gradient, calculating the required torque, achievable motor speed, and corresponding vehicle speed. Furthermore, gradeability limits were evaluated, and the effects of gear ratio and airflow rate around the air-cooled motor on both gradeability and thermal behavior were examined. The findings provide practical insights for improving the powertrain and cooling system design of lightweight electric vehicles. The results showed that selecting an appropriate gear ratio can enable the motor to operate more efficiently under demanding driving conditions. A 20% increase in the gear ratio was found to delay motor heating by up to 10
Turan, AzimKantaroğlu, Hasan HüseyinAkbaba, MahirKasım, Recep FarukYarar, Göktuğ
The effect of tire tread depth on the deceleration performance of anti-lock brake systems (ABS) in newer vehicles is not well studied. A single sport-utility vehicle (SUV) was used to perform a series of 216 ABS-engaged braking tests on dry and wet asphalt and concrete surfaces using six sets of four tires with tread depths varying from 0.8 mm (1/32″) to 7.1 mm (9/32″). Vehicle speed and deceleration as a function of time were calculated from 5th-wheel displacement data sampled at 200 Hz. Braking tests were initially conducted on a dry surface, after which a water truck distributed water onto the road to create a wet condition and additional tests of each tire set were conducted. Overall, average deceleration levels did not vary significantly across the tires sets with tread depths from 7.1 mm (9/32″) down to 2.4 mm (3/32″) for both road surfaces in both dry and wet conditions. Compared to the deceleration levels at these larger tread depths, dry deceleration levels were greater for
Miller, IanKing, DavidSiegmund, Gunter P.
Software-defined vehicles offer customers a greater degree of customization of vehicle controls and driving experience. One such feature is user-adjustable tuning of vehicle ride and handling, where customers can vary ride height, damper stiffness, front-rear torque balance, and other aspects of vehicle dynamics. While promising a great customer experience, such a feature can expose the vehicle to a wider range of structural loads than those in the nominal design condition, particularly when such tuning is extended to cover spirited “sport” mode driving, off-road driving, etc. In this paper we present a novel methodology combining Road Load Data Acquisition (RLDA) data and real-world telemetry data to estimate the impact of user-adjustable vehicle-dynamics tuning on structural durability. In doing so, the method combines the physics of damage accumulation (from RLDA data) with user behavior (from telemetry data) to present an accurate assessment of the impact on durability, moving
Demiri, AlbionRamakrishnan, SankaranWhite, DylanKhapane, PrashantBorton, Zackery
Pedestrian fatalities in traffic accidents continue to rise, with severe injuries often resulting from both vehicle impact and subsequent ground contact, frequently occurring outside the field of view of vehicle-mounted cameras. This study presents a proof-of-concept (PoC) approach for reconstructing three-dimensional pedestrian motion—including occluded regions—using dashcam video. The method integrates 2D human pose estimation (MMPose) and monocular depth estimation (Depth Anything V2),the latter was fine-tuned on a custom dataset, to generate 3D skeletal coordinates.To evaluate motion matching, the reconstructed pedestrian poses were quantitatively compared with a database of vehicle collision simulations using the THUMS human body model and skeletal data representing real-world crash scenarios generated in PC-Crash. Composite similarity indices based on thoracic center of gravity trajectory and torso orientation vectors were employed for this comparison. Preliminary results
Onishi, KojiWang, KewangUno, ErikoIchikawa, KojiTanase, NoboruAndo, Takahiro
Federal Motor Vehicle Safety Standards (FMVSS) 126 and 136 are standards imposed on four of the eight recognized road vehicle classes in The United States. These standards make it mandatory for Electronic Stability Control modules (ESC) to be mounted to Class 1,2,7, and 8 vehicles. These modules strategically activate the vehicle brakes via the Antilock Brake System (ABS) to limit the recorded yaw rate and lateral displacement of a vehicle during an extreme cornering maneuver such as a sudden swerve to avoid an obstacle on the road. The two aforementioned FMVSS mandates also specify three different driving maneuvers that are conducted to profile and analyze ESC module performance. There is now an interest in creating a new FMVSS that makes ESC modules mandatory for Class 5 vehicles. The purpose of this paper is to analyze how one specific Class 5 vehicle’s ESC module performed when subjected to the two test procedures that correspond to FMVSS 126 and 136. As will be seen, the vehicle’s
Cazares, Richard IsaacGuenther, DennisHeydinger, Gary
In a few extreme customer abuse load cases such as curb impact and potholes, automotive structures see non-linear (plastic) deformations as well as large rigid body motion. The load cases can be simulated by a few tools: crash analysis tools such as LS-Dyna, non-linear structure analysis tools, or multi-body dynamics (MBD) analysis tools like Ansys Motion. The three simulation tools have pros and cons, respectively. In this study, a curb impact simulation was performed using the multi-body dynamic approach with nonlinear structural analysis capabilities included in Ansys Motion. The tool demonstrated the simulation was completed faster than other MBD tools due to smartly recycling the system Jacobian matrix when structural deformation was not significant. The results were compared with structural analysis and correlated reasonably well. The post-impact suspension alignment changes can also be simulated for reviewing design requirements. This approach proposes a new way to simulate
Hong, Hyung-JooKim, Wangoo
Oscillations in understeering vehicles are occasionally described in the literature, primarily in terms of the poles of the yaw rate response, but perhaps not completely appreciated in their complexity. This work shows that as speed of an understeering vehicle increases, the increasingly underdamped poles of the yaw rate transfer function combine with the effects of a low frequency zero and a reduced steady-state response to result in oscillations greater than would be expected from eigenvalues alone. A speed range for acceptable yaw rate response is suggested, and it is shown that a typical understeering passenger car operates within this range. As the understeering vehicle’s speed increases beyond this range, the high-speed limit of the oscillation frequency is found.
Williams, Daniel
The phenomenon of bicycle pitch-over is simple in concept, yet determining threshold criteria for pitch-over has yet to be well established, particularly with respect to determining whether or not a bicycle’s front wheel will roll over a particular obstacle or not. Two prior SAE papers have laid out two different analytical approaches to predict this threshold – the Moment-Inversion and Brach Pitch-Over Threshold models - and this paper proposes a modification to the Moment-Inversion model to account for tire deflection. Testing began by measuring the center of gravity locations and moments of inertia for a bicycle with weights and training wheels and for a test rider on a bicycle and tricycle. These physical measurements were used to calculate the predicted pitch-over height for each system for each model. The test systems were then ridden over a series of progressively taller square edge obstacles until they transitioned from rolling over to stopping or pitching over. From this
Sweet, David MichaelO'Brien, NathanBretting, Gerald
The Formula SAE (FSAE) race track is characterized by a large number of corners, making cornering performance a key factor affecting lap time. Based on the proportional control strategy for rear-wheel steering angles, this paper proposes a steering angle optimization method using a Temporal Convolutional Network (TCN). The TCN model features a faster training speed than traditional sequential neural networks. In addition, dilated convolutions enable an exponential expansion of the receptive field without increasing computational costs, making it particularly suitable for capturing the temporal dependencies of vehicle states. By processing vehicle dynamic parameters including front-wheel steering angle, vehicle speed, yaw rate and sideslip angle, the model calculates the correction value of the rear-wheel steering angle. This correction value is then superimposed with the reference value of the rear-wheel steering angle derived from the proportional control strategy, which serves as the
Liu, Xiyuan
This study presents the vehicle control optimization of a Formula SAE (FSAE) electric vehicle developed by National Taiwan University Racing Team (NTU Racing), utilizing a dual-axle dynamometer and a real-time Hardware-in-the-Loop platform from Chroma. The novelty of this work lies in the comprehensive system-level validation of independent torque control strategies, namely Torque Vectoring (TV) and Traction Control (TC), implemented directly within the vehicle control unit (VCU), and the high-fidelity simulation of dynamic driving scenarios based on the FSAE circuit. The vehicle features an independently controlled rear-axle, two-wheel drive (2WD) configuration, consisting of two in-wheel motors, self-developed inverters, and planetary gearboxes. During testing, a pre-built CarSim driver model provides throttle, brake, and steering inputs to the VCU via Controller Area Network (CAN) interface. The VCU, in turn, computes the independent torque commands according to the TV and TC
Hsiao, Tsung-YuChen, Zhi-RenJian, Rong-WeiChen, Tai-HsiangWang, Tai-JieHu, Wei-ZheHo, Hui-TingWu, Ting-YuLin, Ting-HeChiu, Joseph
Ensuring safe operation and reliable control of mobility systems remains a significant challenge, particularly for nonlinear and high-dimensional applications subject to external disturbances with hard constraints and limited computational resources in real-time implementations. A reference governor (RG) can enforce constraints using an add-on scheme that preserves the pre-stabilizing controller while balancing the need to satisfy other requirements, including reference tracking and disturbance rejection. Thus, in this paper, we exploit RG-based strategies focusing on nonlinear mobility systems. While the method is generalizable to other applications, such as waypoint following for autonomous driving, the flight dynamics of a quadrotor system with twelve states are used as an example. We implement a disturbance rejection RG to satisfy safety constraints and track set points. To handle nonlinearity, we propose an optimal strategy to quantify the maximum deviation between the nonlinear
Dong, YilongLi, Huayi
Toyota vehicles equipped with Toyota Safety Sense (TSS) can record detailed information surrounding various driving events. Often, this data is employed in accident reconstruction to better understand the dynamics of a collision. TSS data is comprised of three main categories: Vehicle Control History (VCH), Freeze Frame Data (FFD), and image records. During an event, it is possible that a vehicle undergoes a catastrophic power loss from the damage sustained during the event. In this paper, the effects of sudden power loss on the VCH, FFD, and images are studied. Events are triggered on a TSS 3.0 equipped vehicle by driving toward a stationary target. After system activation, a total power loss is induced, triggered on the instrument cluster “BRAKE” alert message, at various delays after activation. This testing studies various signals recorded across VCH, FFD and image data including vehicle speed and time and date. Results show that there is a minimum time to record after system
Getz, CharlesYeakley, AdamDiSogra, Matthew
The tire model is a crucial component in the design of the K-characteristic of FSAE racing car suspensions, and directly influences the achievement of maximum cornering lateral force. Not only do the slip angle, vertical load, tire pressure, and camber angle affect the mechanical characteristics of the tire, but temperature is also an important influencing factor when FSAE vehicle tires operate at high speeds. However, the modeling process of traditional tire models based on temperature characteristics is often very complex. The FSAE tire test code (FSAE TTC) already has a large amount of official sample data, which provides a basis for data-driven neural network models. This study implemented a hybrid modeling methodology, constructing two cascaded feedforward neural networks that combine the physical interpretability of the Magic Formula tire model with the nonlinear approximation capabilities of neural networks. The first network model uses slip angle, vertical load, tire pressure
Liu, XiyuanWang, ShenyaoLi, MingyuanHuang, Jiayu
Despite remarkable advances in vehicle technology - enhancing comfort, safety, and automation – productivity of transportation over the road continues to decline. Stop-and-go driving remains one of the most persistent inefficiencies in modern mobility systems, leading to greater travel delays, energy waste, emissions, and accident risk. As vehicle volumes rise, these effects compound into systemic challenges, including driver frustration, unstable flow dynamics, and elevated greenhouse gas (GHG) emissions. To address these issues, an extensive data-driven evaluation was performed characterizing the underlying causes of traffic instability and uncovering hidden behavioral parameters influencing traffic flow. This research led to the identification of a previously unrecognized metric - the Driver Comfort Index (DCI) - which quantifies an inter-vehicle spacing behavior that reflects intrinsic human driving behavior. Building on this discovery, mixed traffic is explored to identify its
Schlueter, Georg J.
The demand for improved energy efficiency in real-world vehicle operations continues to grow with technology enhancement. When transporting large cargo loads with passenger pickup trucks and rental trailers, the interaction between vehicle payload, towing configuration, and fuel consumption becomes a key factor in overall system efficiency. Understanding how towing configurations and trailer loading influence fuel consumption and vehicle performance is critical for both consumer guidance and vehicle system design. This study investigates the energy efficiency of U-Haul truck and trailer systems, with a particular focus on the influence of trailer tongue weight. U-Haul truck and trailer simulation models were developed using AVL Vehicle Simulation Model (VSM) software, with an F-350 engine brake-specific fuel consumption (BSFC) map integrated to represent realistic engine performance. Two configurations with equal payload were evaluated: (1) a U-Haul truck alone, and (2) a U-Haul truck
Wang, GangKathadi, MohammadYang, WilliamChen, Yan
Drivers obtain road information through head and neck rotation. In order to study the influences of head and neck rotation posture on occupant injury in frontal impact scenario, the THUMS (Total Human Model for Safety) AM50 human body model with five different head and neck rotation postures but without active muscles was adopted to study the biomechanical injury responses of occupant under the frontal impact scenario at 56 km/h in this study. Firstly, the kinematic responses of total body and head acceleration curves at the center of gravity predicted by PMHS (Post Mortem Human Subject) and THUMS AM50 human model under the sled test conditions were compared to verify the simulation model for subsequent study. Then, the THUMS AM50 human model with standard occupant seating posture was adjusted to have five different head and neck rotation postures with 0°, ±20°, and ±40° rotation angle, respectively. Finally, a series of frontal impact sled with or without airbag simulations were
Li, Dongqiangjiang, YejieTan, ChunLi, YanyanGong, ChuangyeWu, HequanJiang, Binhui
During the initial design phase, automotive Original Equipment Manufacturers (OEMs) require the adaptability to examine various suspension system architectures while maintaining focus on the specific performance objectives. Those requirements are expressed by Kinematics and Compliance (K&C) look-up tables and represent the footprint of what the suspension should look like in real-world applications. However, translating those requirements into the full geometric hardpoint layout is not straightforward. This process often relies on trial-and-error approaches, making it time consuming and requiring significant expertise. This challenge, known as ”target cascading,” remains a major hurdle for many engineers. The main objective of this paper is to cascade the suspension requirements from K&C look-up tables to hardpoint locations by adopting an automatic workflow and ensuring respect for constructive and feasibility constraints. Design space exploration was conducted using a robust
Brigida, PieroDi Carlo, PaoloDi Gioia, NiccolòGeluk, TheoTong, SonAlirand, MarcGorgoretti, DavideOcchineri, MarcoTassini, NicolaBerzi, Lorenzo
Heavy-duty Class 8 battery electric trucks not only offer the potential to significantly reduce greenhouse gas (GHG) emissions compared to conventional diesel trucks but can also provide significant savings in fuel costs. To further enhance energy and freight efficiency, Predictive Cruise Control (PCC) algorithms can be developed that generate optimal acceleration profiles for the vehicle by minimizing a cost function which combines both energy consumption and deviation from the desired velocity. A critical component of the cost function is the penalty factor, which governs the tradeoff between energy use and travel time, which are two conflicting objectives in freight logistics. Selecting an appropriate penalty factor is essential, as freight deliveries are time sensitive, but minimizing energy consumption remains a priority. Moreover, variations in payload significantly affect vehicle dynamics and energy usage, making it critical to adapt the penalty factor to different payload
Safder, Ahmad HussainVillani, ManfrediWang, EricKhuntia, SatvikNelson, JamesMeijer, MaartenAhmed, Qadeer
Wake effects modify the aerodynamic performance of a road vehicle when driving in traffic. Analysis of wind-tunnel measurements conducted in flows with wake characteristics, using a traffic-wake-simulation system, suggests that conventional uniform-wind performance coefficients can be scaled, using wake-flow-field information, to predict the influence of wake effects. This paper presents a flow-field-averaging method that estimates a dynamic-pressure correction and yaw-angle correction for application to uniform-wind data, to account for changes in performance due to wake effects. This first-order method is shown to provide reasonably-good accuracy when reverse correcting the wind-tunnel wake-effects measurements. Drag-coefficient data for light-duty-vehicle models, which showed wake effects exceeding 20%, were corrected to within 5% of uniform-wind values, while data for heavy-duty-vehicle models, which showed wake effects exceeding 15%, were corrected to within 2% of uniform-wind
McAuliffe, Brian
When a vehicle performs planar motion, the tire side force induces a jacking-up effect determined by the suspension roll center height governed by suspension geometry. These jacking forces also excite pitching motion. In this study, the pitching degree of freedom, along with roll degree of freedom, was incorporated in the bicycle model of the vehicle motion, hence it becomes four-degree-of-freedom model, and a new analytical method that applies modal analysis method to the model decomposes the motion of the sprung mass of the vehicle into mutually independent vibration modes. Since the superposition of these vibration modes can reproduce vehicle motion, these vibration modes are the fundamental factors governing sprung-mass behavior. Therefore, understanding how these vibration modes respond to design parameters provides a theoretical foundation to design desired vehicle dynamics from the early stage of car development. This report presents, by conducting modal analysis of the four
Kusaka, KaoruYuhara, TakahiroKoakutsu, Shingo
In this paper, the effects of aerodynamic interactions on the drag of a longitudinally-arranged two-vehicle system are examined by considering the influence of separation distance, cross winds, vehicle size and shape. Testing was undertaken at 30% scale in a large wind tunnel with road-representative freestream turbulence. Separation distances of 0.5, 1.0, and 2.0 vehicle lengths (L) were examined over a range of yaw angles between ±15°. A highlight of the current study is the characterization of platoon drag-reduction benefits for different sizes and shapes of the lead and follower models, by using a DrivAer model and an Aero-SUV model, each with slant-back (Notchback or Fastback) and square-back (Estateback) variants, providing four distinct model pairings. Drag reduction for the lead model appears to be affected mainly by the size of the follower model, while the follower model shows a much greater sensitivity to shape of the lead model. Larger drag reductions were observed at most
McAuliffe, BrianGhorbanishohrat, Faegheh
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 static conditions, revealing both Gaussian and non-Gaussian characteristics. No filtering was applied, allowing direct evaluation of the controller’s inherent robustness to raw-signal variability. The LCC maintained a mean lateral offset within ±0.35
Bijinepalli, Ravi TejaTambolkar, PoojaMidlam-Mohler, Shawn
Design for durability 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 are rarely accounted for in designing vehicle level durability tests. This makes it difficult to establish targets for durability testing that accurately match the wide variations in real-world roads and driving. This paper presents a data-driven approach to objectively classify road surface and driving characteristics using metrics derived from existing road response metrics like Vibration Dose Value (VDV) and statistical estimates of vehicle speed and acceleration. Data collected at the proving grounds on gravel roads, smooth roads, city-like roads
Shaurya, ShubhamRamakrishnan, SankaranDemiri, AlbionKhapane, Prashant
This study presents a torque distribution control strategy for EVs with e4WD powertrain to overcome the trade-off between ensuring vehicle acceleration and deceleration responsiveness and mitigating backlash shock in the driving system. The deterioration of the drivability which occurs from the intrinsic hardware characteristics of the drivetrain is prevented by designing a response-priority drive mode in which neither front or rear motor torque is allowed to change its sign. Instead, in such drive mode, the front motor torque is only allowed to perform regenerative braking while the rear motor torque is only allowed to produce positive acceleration torque. In order to avoid sacrificing the maximum acceleration by applying such strategy, the mode transition function is implemented as well. In addition, in order to prevent backlash impact due to drivetrain compliance, variable offset torque based on drivetrain compliance model is evaluated in real time and applied to each motor command
Oh, JIWONLee, Ho Wook
The Electro-Mechanical Brake (EMB) system is a novel type of brake by wire systems with independently controllable characteristics. This system aids in the decoupling analysis of the vehicle and actuator dynamics, thereby improving the accuracy of parameter identification. Therefore, this paper proposes an innovative parameter identification method for vehicle parameters and longitudinal tire model parameters, based on the characteristics of the EMB system and onboard sensors. First, based on the wind resistance and rolling resistance coefficients obtained from the vehicle coasting conditions, a decoupled constant clamping force sequence braking condition for the front and rear axles is designed by integrating the characteristics of the EMB actuator and vehicle dynamics. This approach enables the identification of vehicle and nonlinear longitudinal tire model parameters, significantly improving the accuracy of parameter identification. Next, considering the nonlinear characteristics of
Huang, JiayiCheng, YulinZhuo, GuirongLe, QiaoWei, WeiShu, Qiang
Vehicles may enter highly unstable dynamic states due to lateral collisions, sudden loss of grip, or extreme steering disturbances. When such instability arises in congested road sections where obstacle avoidance is required, the safety risk to both the ego vehicle and surrounding traffic escalates significantly. In such scenarios, the vehicle must not only regain stability but also navigate the roadway in the shortest feasible time to prevent secondary collisions. This paper investigates the minimum-time maneuver of a vehicle starting from an unstable dynamic condition and constrained to travel within prescribed road boundaries. A single-track vehicle model with combined-slip nonlinear tire model is employed to capture the vehicle dynamics under high slip conditions. Phase-plane analysis is conducted to reveal how control inputs reshape the system’s vector field and influence the possibility and speed of stability recovery. An optimal control problem is formulated to compute the
Leng, JiatongYu, LiangyaoWang, YongxinYou, WeijieLi, ZiangJin, Zhipeng
Tires are critical to vehicle dynamics, transmitting traction, braking, and cornering forces to the road. A tire blowout, the sudden and rapid loss of inflation pressure due to puncture or structural failure, can cause severe instability, rollover, or collisions. Understanding vehicle response during blowout events is essential for developing robust safety systems and control strategies. Earlier developed simulation models are used to study and understand vehicle behavior during blowouts, but there is a lack of on-road testing platforms to validate these models experimentally. In this paper, an experimental platform integrating a tire blowout device and an instrumentation system has been developed to address this gap. The blowout device consists of multiple solenoid valves mounted on the wheel surface and powered by a 12V power supply. All valves can be triggered at the same time using an RF remote, producing rapid and synchronized deflation. As an extension of this implementation, an
Kanthala, Maha Vishnu Vardhan ReddyKrishnakumar, AshwinLin, Wen-ChiaoChen, Yan
Advances in Connected and Automated Vehicles (CAVs) have developed a level in which high-definition maps can be used to improve road safety. Data compactness and robustness on road characterization is essential for the proper handling of vehicles under curves. In this paper, an optimization scheme that relates highway-design road curvature and optimal speed of travel is defined to safely navigate through a given road. The scheme is divided in two main steps. First a nonlinear optimization problem, in which curvature profiles are fitted from a model that based on street design standards as per the American Association of State Highway and Transportation Officials (AASHTO). Secondly, the optimized curvature profile is subject to a secondary optimization problem that uses vehicle dynamics for both constraints and objective function derivation. Guidance reference parameters such as curvature and velocity, at different levels of friction are analyzed. Results show that, even in sparse
Jacome, Ricardo OsmarStolle, CodyGrispos, George
The multi-body dynamics (MBD) model and the MATLAB Simulink model can be integrated to create a control-integration model. Using a high-fidelity MBD model to represent the vehicle as the plant, this integrated model can be used to analyze vehicle system physics and develop control strategies. For hybrid vehicles, this process is more complex because the powertrain and other vehicle systems are often built as separate MBD models. This paper describes a method for integrating a powertrain model developed in AMESIM, a vehicle model developed in SIMPACK, and a control model developed in MATLAB Simulink. The resulting integrated model was then used to perform frequency sweep analysis to identify driveline system properties. In particular, the driveline frequency and the amplitude of the transfer function between motor speed and motor torque are critical parameters. By applying active damping control to the driveline system, the peak amplitude and driveline vibrations can be reduced. The
Xing, XingMathew, Vino
As automotive aerodynamic testing facilities evolve to capture more real-world behavior, updating the correlation between old and new technologies is essential. Recently, the three-member consortium of the United States Council for Automotive Research (USCAR) - General Motors, Ford Motor Company, and FCA US LLC - transitioned from full-size static ground plane facilities to 5-belt moving ground plane wind tunnel facilities. The primary objective of this study was to update the correlation data sets to maintain consistent and robust data sharing among companies, which is the cornerstone of USCAR efforts. To achieve this, a set of updated correlation data sets were calculated to replace the original correlation study results from 2008. Additionally, the methodology for applying correlation equations was revised from using averaged wind tunnel data to employing direct wind tunnel-to-wind tunnel correlation equations. In a two-phase correlation effort conducted in 2022 and 2025, the three
Nastov, AlexanderLounsberry, ToddMadin, TrevorLangmeyer, GregoryFadler, GregorySkinner, ShaunHorton, Damien
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, MariamBalchanos, MichaelMavris, Dimitri
This paper presents an approach utilizing Nonlinear Model Predictive Control (NMPC) and Unscented Kalman Filter (UKF) to predict system state and control the trajectory of the vehicle with dual trailers in an intersection turn scenario. The UKF estimates vehicle and trailers’ lateral traversal velocity states and the NMPC controls the vehicle acceleration and steering to maintain the vehicle’s desired heading through the turn. The vehicle’s lateral traversal velocity function is formulated using Lyapunov based method which is used as a propagation function in the UKF to improve the estimation accuracy. The lateral traversal velocity is then used as one of the constraints in the NMPC problem. The overall estimation and the control scheme are formulated and assessed in the simulation environment. The simulation results show good tracking and curb avoidance performance.
Malla, Rijan
To enhance the lateral stability and torque optimization of four-wheel hub motor distributed-drive vehicles under complex road conditions, a hierarchical control strategy for yaw stability is proposed. The upper-layer controller designs a yaw moment controller based on sliding mode control theory, establishing both a two-degree-of-freedom vehicle model and a seven-degree-of-freedom vehicle model to track the vehicle's desired yaw rate, desired sideslip angle, actual yaw rate, and actual sideslip angle. This enables the derivation of the corresponding additional yaw moment. The vehicle's operational state is analyzed using the phase plane method based on the sideslip angle and yaw rate, and the total additional yaw moment is computed through weighted calculations according to the identified state. Simultaneously, an unscented Kalman filter observer is implemented to improve the tracking accuracy of the actual yaw rate and actual sideslip angle in the seven-degree-of-freedom model. The
Shi, Cheng'aoLiu, BingsenZou, XiaojunWang, TaoZhang, Ming
Longitudinal lumbar acceleration is often overlooked as a key variable when biomechanically assessing lumbar response in rear-end collisions. The objective of this study is twofold: (1) to conduct a comprehensive literature review of peak longitudinal lumbar acceleration to statistically evaluate differences between three surrogate occupant types: human volunteers, post-mortem human subjects (PMHS), and anthropomorphic test devices (ATDs) and (2) to construct a mathematical predictive model of longitudinal lumbar acceleration using peak longitudinal vehicle or sled change in velocity (delta-V) and vehicle acceleration in rear-end impacts. Peak longitudinal lumbar acceleration was obtained from peer-reviewed literature and the Insurance Institute for Highway Safety database. Tests included belted human volunteers, PMHS, and ATD occupants seated upright in unmodified, conventional driver seats. Compared to human volunteers instrumented at L5-S1, BioRID ATDs instrumented at L1 displayed
Zambare, KeyaOgbu Felix, JordanArana Barcala, EmilyWestrom, ClydeCaraan, JohnAdanty, KevinShimada, Sean
Drivers often interact with partial automation (SAE Level 2) systems, initiating transfer of control (TOC) either by handing control over to the automation or by taking it back. Accurately predicting these interactions may inform the design of future automation systems that adapt proactively to the operating context, enhance comfort, and ultimately may improve safety. We present a context-aware framework that generates a unified driver–vehicle–environment representation by fusing data from in-cabin video of the driver and of the forward roadway with vehicle kinematics, driver glance, and hands-on-wheel behaviors. This representation was encoded in a hierarchical Graph Neural Network that classified driver-initiated TOCs to: (i) Manual-to-automation and (ii) Automation-to-manual transitions and predicted time-to-TOC. Shapley-based explainable AI was used to quantify how the importance of behavioral, contextual, and kinematic cues evolved in the seconds preceding a TOC. Analysis of a
Zhao, ZhouqiaoGershon, Pnina
The push for vehicle development through virtual prototyping and testing in motorsports highlights the critical challenge of tire model selection and calibration, especially when vehicle dynamics must be accurately captured. The calibration process for tire models such as the Pacejka Magic Formula (MF) relies on parameter identification and experimental data fitting. While optimization algorithms have been implemented to calibrate tire models, few studies explore the effects of parameter selection on overall vehicle performance, complicating prioritization for the vehicle’s modeling and simulation strategy. To bridge this gap, this paper leverages optimal control methods to quantify how the variability of MF tire model parameters propagates to the overall vehicle model and impacts lap time prediction accuracy. To achieve this, a subset of parameters critical to combined slip of the MF tire model are varied through a Design of Experiments (DOE). These variations are executed on a flat
Zarate Villazon, Angel M.Brown, IanBalchanos, MichaelMavris, Dimitri
Vehicle pull under acceleration is a phenomenon commonly observed in high-performance vehicles and electric vehicles (EVs), primarily arising asymmetric driveshaft angles, drivetrain architecture, and suspension geometry. In addition to these mechanical factors, tire characteristics, particularly the tire lateral force generated at the contact patch, significantly influence this effect. The lateral force is intricately tied to the dynamics of the contact patch and the geometric design of the tire tread pattern. This study investigates the relationship between tread pattern geometry and vehicle pull under acceleration, emphasizing the role of tire lateral force variations. By employing finite element (FE) simulation, lateral force response variations (dfy/dfx) resulting from tread block deformation were analyzed. Based on these simulation, a robust analytical methodology for tread pattern evaluation and optimization was established. The developed tread pattern characteristic parameter
Yoon, YoungsamJang, DongjinKim, HyungjooLee, Jaekil
Industries are following a tedious product development cycle for developing their product. In product development major steps includes design ideas, Drawings, CAD, CAE, Testing and design improvement cycle. This is a monotonous process and takes time which impacts on its time to deliver product and cost on development. Now a days industries are fast growing and targeting to reduce development cycle time and cost. AI&ML is impacting almost all areas in the industry and significantly reducing efforts time and cost. To make use of AI&ML in CAE, Altair Physics AI is an effective tool. To ensure the design of product traditional way is to develop a CAD of the product, develop, perform CAE and analyze performance. If we consider CAE procedure it is time consuming process which includes FEA model build, applying boundary conditions, running simulation and analyzing results which could take minutes to hours. By using ML with Physics AI we can make predictions on new design of the product in
Dangare, Anand ManoharKulkarni, Mandar
To enhance the lateral stability of four-wheel-drive intelligent electric vehicles (FWDIEV) under extreme operating conditions, this paper proposes a cooperative control strategy integrating active front steering (AFS) and direct yaw moment control (DYC) based on dissipative energy method. A nonlinear three-degree-of-freedom vehicle model is established to analyze the evolution of the vehicle state phase trajectory. A quantitative lateral stability index is constructed using dissipative energy to accurately evaluate the vehicle’s lateral dynamics. Utilizing dissipative energy and its gradient information, a time-varying stability boundary is defined under dynamic constraints, and adaptive weighting coordination between the AFS and DYC systems is designed to achieve coordinated control of front steering angle and additional yaw moment. A feedforward–model predictive control (FF-MPC) framework is developed, in which a feedforward module generates compensation based on driver intent to
Zhao, KunZhao, ZhiguoWang, YutaoXia, XueChen, XiHu, Yingjia
Integrated active and passive safety protection systems have made substantial contributions to reducing traffic accidents and mitigating human injuries. However, assessing such systems through vehicle collision tests is limited, as this approach cannot cover the wide range of accident scenarios. To address this gap, identifying and generating representative pre-crash scenarios from real-world accidents provides key boundary conditions for the setup of virtual test scenarios. In this study, we used the Future Mobile Traffic Accident Scenario Study (FASS) dataset to reconstruct 112 two-wheeler accidents. For each case, we extracted pre-crash dynamic information, static attributes, and environmental context. An autoencoder was employed to encode high-dimensional features of scenarios, and K-means clustering was applied to categorize the accidents into eight representative pre-crash scenarios. For each scenario, we examined the motion states of participants and further compared the
Wang, GuojieGao, XinLiu, SiyuanLiu, JiaxinLi, QuanShi, LiangliangNie, Bingbing
At the U.S. Environmental Protection Agency’s National Vehicle and Fuel Emissions Laboratory, a development project was implemented to compare various test methods for benchmarking the operation of vehicle electric drive units (EDUs). In earlier research, several test methods were identified, of which two were used to test a Chevrolet Bolt EDU: (a) in-vehicle testing of the complete EDU on a chassis hub dynamometer and (b) stand-alone testing of the EDU’s electric motor and inverter in a dedicated test cell after removal from the vehicle. The resulting data sets were compared with each other and with similar data previously published by GM. In this paper, additional EDU test methods are explored. First, the stand-alone testing of the EDU and its subcomponents is expanded to include testing both with and without the EDU gearing. This testing allows the electric motor, inverter, and gearbox to be characterized separately and the EDU to be characterized as a complete unit. Second, in
Moskalik, AndrewSchauer, EthanBarba, Daniel
Vehicle testing for fuel economy and emissions is typically performed indoors over standard dynamometer drive schedules to minimize variability and maximize repeatability of the results. In contrast, during on-road operation, operational parameters such as vehicle speed and acceleration and environmental factors such as temperature and wind will change unpredictably. These factors influence vehicle fuel economy and emissions, making on-road operation much more variable than dynamometer results. However, even though on-road conditions may be unpredictable, the on-road operational data can still be used to characterize vehicle performance. This paper describes the development of an on-road vehicle test methodology, with a focus on accounting for on-road factors with a high degree of accuracy while requiring only an achievable and reasonable amount of data. To develop this methodology, a 2016 Honda Civic was instrumented and driven multiple times over a route covering urban, rural, and
Moskalik, AndrewBarba, Daniel
High-precision estimation of key vehicle–road state parameters is crucial for ensuring the accurate and safe control of mining trucks (MT), as well as for reliable trajectory tracking. Among these parameters, the vehicle sideslip angle is particularly critical for assessing and predicting lateral stability. However, its direct measurement is challenging, and its estimation typically depends on an accurate characterization of tire cornering stiffness. For MT, large variations in loading conditions (from empty to fully loaded) pose significant challenges to sideslip angle estimation due to the resulting nonlinearity and variability of tire cornering stiffness. To address this issue, a novel joint estimation framework integrating the Moving Horizon Estimation (MHE) and Square-Root Cubature Kalman Filter (SCKF) is proposed to simultaneously achieve high-precision estimation of both tire cornering stiffness for each tire and vehicle sideslip angle. In this framework, the cornering stiffness
Xia, XueShen, PeihongJiao, LeqiLi, TaoChen, HuiyongZhao, KunJiao, LeqiZhao, Zhiguo
Topology optimization (TO) of dynamic structures has traditionally been constrained to single-body components and simplified harmonic load assumptions. Extending TO to multibody dynamic systems (MBS) remains challenging due to complex coupling between inertia, mass distribution, and joint constraints. This paper presents an inertia-aware topology optimization framework that integrates mass moment of inertia (MMI) constraints within an enhanced Equivalent Static Displacement (ESD) methodology. Building upon the authors’ previously developed ESD framework, the proposed approach — termed Inertia-Augmented Equivalent Static Displacement (IA-ESD) — explicitly incorporates inertial effects arising from accelerations and joint interactions. The approach enables dynamically consistent optimization by coupling design-dependent inertia tensors with equivalent static displacements derived from nonlinear multibody dynamics. Case studies involving an MBB beam and a piston–connecting rod assembly
Gupta, AakashTovar, Andres
Detailed kinetics simulations coupled with 3D CFD offer a powerful analysis tool for combustion and emissions. Such methods allow consistent modeling of multi-component fuels from evaporation to combustion and correctly capture the effects of local inhomogeneities created by preferential evaporation on the performance and emissions of modern powertrains. Such computations are extremely computationally demanding, prompting interest in the development of calculation acceleration techniques that can effectively balance the speed and accuracy of the chemical source calculation terms. Chemical kinetics clustering methods are widely used for that effect. However, such techniques must be not only effective but also robust with respect to the engine conditions and fuel composition changes, to reduce the computational demands introduced by the need to calibrate the parameters of the acceleration method itself. In this paper, an extended chemical kinetics clustering approach is proposed. A
Hernandez, IgnacioTurquand d Auzay, CharlesShapiro, EvgeniyShala, MehmetBorg, AndersSeidel, LarsMauss, Fabian
This study estimates the impact on driving energy of differences in aerodynamic characteristics for yaw angle from natural wind during North American Highway mode driving. A previous study [1] clarified the potential to estimate the fuel consumption impact of natural wind by integrating the drag coefficient yaw characteristics and yaw angle occurrence probability. The natural wind was measured on a vehicle while driving a representative North American Highway test course [2]. Driving energy is predicted from the obtained yaw probability and the drag coefficient yaw sweep data in a wind tunnel. Measurements were conducted every weekday for 8 hours in 2023, covering 70% of the traffic volume. The validity of the measurement period was evaluated by the deviation from the annual average of wind direction and speed. Since yaw probability varies depending on the road environment, it is necessary to weigh the road environment type probability when calculating the driving energy. The
Onishi, YasuyukiNucera, FortunatoNichols, LarryMetka, Matt
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