Browse Topic: Analysis methodologies

Items (9,310)
In order to manage the serious global environmental problems, the automobile industry is rapidly shifting to electric vehicles (EVs) which have a heavier weight and a more rearward weight distribution. To secure the handling and stability of such vehicles, understanding of the fundamental principles of vehicle dynamics is inevitable for designing their performance. Although vehicle dynamics primarily concerns planar motion, the accompanying roll motion also influences this planar motion as well as the driver's subjective evaluation. This roll motion has long been discussed through various parameter studies, and so on. However, there is very few research that treats vehicle sprung mass behavior as “vibration modes”, and this perspective has long been an unexplored area of vehicle dynamics. In this report, we propose a method to analytically extract the vibration modes of the sprung mass by applying modal analysis techniques to the governing equations of vehicle handling and stability
Kusaka, KaoruYuhara, Takahiro
Vehicles with SAE J3016TM Level 3 systems are exposed to road infrastructure, Vulnerable Road Users (VRUs), traffic and other actors on roadways. Hence safe deployment of Level 3 systems is of paramount importance. One aspect of safe deployment of SAE Level 3 systems is the application of functional safety (ISO 26262) to their design, development, integration, and testing. This ensures freedom from unreasonable risk, in the event of a system failure and sufficient provisions to maintain Dynamic Driving Task (DDT) and to initiate Minimum Risk Maneuver (MRM), in the presence of random hardware and systematic failures. This paper explores leveraging ISO 26262 standard to develop architectural requirements for enabling SAE Level 3 systems to maintain DDT and MRM during fault conditions and outlines the importance of fail-operability for Level 3 systems, from a functional safety perspective. At a high-level, UN Regulation No. 157 – Automated Lane Keeping Systems (ALKS) is used as a baseline
Mudunuri, Venkateswara RajuJayakumar, Namitha
Based on the harmonic current injection method used to suppress the torsional vibration of the electric drive system, the selection of the phase and amplitude of the harmonic current based on vibration and noise has been explored in this paper. Through the adoption of the active harmonic current injection method, additional torque fluctuations are generated by actively injecting harmonic currents of specific amplitudes and phases, and closed-loop control is carried out to counteract the torque fluctuations of the motor body. The selection of the magnitude of the injected harmonic current is crucial and plays a vital role in the reduction of torque ripple. Incorrect harmonic currents may not achieve the optimal torque ripple suppression effect or even increase the motor torque ripple. Since the actively injected harmonic current is used to counteract the torque ripple caused by the magnetic flux linkage harmonics of the motor body, the target harmonic current command is very important
Jing, JunchaoZhang, JunzhiLiu, YiqiangHuang, WeishanDai, Zhengxing
In recent years, energy scarcity and environmental pollution have intensified globally, prompting increased research and development in new energy vehicles as countries prioritize environmental protection and energy conservation. Compared to fuel-powered vehicles, new energy vehicles have relatively larger battery volumes and weights, which can increase damage and the risk of fires and explosions in collisions. To analyze and optimize the safety performance of a specific vehicle model's battery pack, we constructed a finite element model using existing software and performed pre-processing, simulation, and analysis of modal, random vibration, and extrusion characteristics. This revealed specific damage scenarios and enabled reliability analysis under working conditions. To enhance safety and reduce mass, we parametrically modeled power pack components and optimized parameters via multi-objective genetic algorithms under three road conditions. Results indicate reduced mass and improved
Wang, Zhi
Automotive chassis components are considered as safety critical components and must meet the durability and strength requirements of customer usage. The cases such as the vehicle driving through a pothole or sliding into a curb make the design (mass efficient chassis components) challenging in terms of the physical testing and virtual simulation. Due to the cost and short vehicle development time requirement, it is impractical to conduct physical tests during the early stages of development. Therefore, virtual simulation plays the critical role in the vehicle development process. This paper focuses on virtual co-simulation of vehicle chassis components. Traditional virtual simulation of the chassis components is performed by applying the loads that are recovered from multi-body simulation (MBD) to the Finite Element (FE) models at some of the attachment locations and then apply constraints at other selected attachment locations. In this approach, the chassis components are assessed
Behera, DhirenLi, FanTasci, MineSeo, Young-JinSchulze, MartinKochucheruvil, Binu JoseYanni, TamerBhosale, KiranAluru, Phani
Vehicle restraint systems, such as seat belts and airbags, play a crucial role in managing crash energy and protecting occupants during vehicle crashes. Designing an effective restraint system for a diverse population is a complex task. This study demonstrates the practical implementation of state-of-the-art Machine Learning (ML) techniques to optimize vehicle restraint systems and improve occupant safety. An ML-based surrogate model was developed using a small Design of Experiments (DOE) dataset from finite element human body model simulations and was employed to optimize a vehicle restraint system. The performance of the ML-optimized restraint system was compared to the baseline design in a real-world crash scenario. The ML-based optimization showed potential for further enhancement in occupant safety over the baseline design, specifically for small-female occupant. The optimized design reduced the joint injury probability for small female passenger from 0.274 to 0.224 in the US NCAP
Lalwala, MiteshLin, Chin-HsuDesai, MeghaRao, Shishir
Both automotive aftermarket vehicle modifications and Advanced Driver Assistance Systems (ADAS) are growing. However, there is very little information available in the public domain about the effect of aftermarket modifications on ADAS functionality. To address this deficiency, a research study was previously performed in which a 2022 Chevrolet Silverado 1500 light truck was tested in four different hardware configurations. These included stock as well as three typical aftermarket configurations comprised of increased tire diameters, a suspension level kit, and two different suspension lift kits. Physical tests were carried out to investigate ADAS performance of lane keeping, crash imminent braking, traffic jam assist, blind spot detection, and rear cross traffic alert systems. The results of the Silverado study showed that the ADAS functionality of that vehicle was not significantly altered by aftermarket modifications. To determine if the results of the Silverado study were
Bastiaan, JenniferMuller, MikeMorales, Luis
The integrated vehicle crash safety design provides longer pre-crash preparation time and design space for the in-crash occupant protection. However, the occupant’s out-of-position displacement caused by vehicle’s pre-crash emergency braking also poses challenges to the conventional restraint system. Despite the long-term promotion of integrated restraint patterns by the vehicle manufacturers, safety regulations and assessment protocols still basically focus on traditional standard crash scenarios. More integrated crash safety test scenarios and testing methods need to be developed. In this study, a sled test scenario representing a moderate rear-end collision in subsequence of emergency braking was designed and conducted. The bio-fidelity of the BioRID II ATD during the emergency braking phase is preliminarily discussed and validated through comparison with a volunteer test. The final forward out-of-position displacement of the BioRID II ATD falls within the range of volunteer
Fei, JingWang, PeifengQiu, HangLiu, YuShen, JiajieCheng, James ChihZhou, QingTan, Puyuan
Trajectory tracking control is a key component of vehicle autonomous driving technology. Compared with traditional vehicles, Distributed Driven Electric Vehicle (DDEV) is an ideal vehicle for trajectory tracking control because of its high space utilization, redundant control freedom and fast system response. However, the chassis execution system of DDEV has a relatively large number of sensors, which significantly increases its probability of failure. In this paper, we propose a trajectory tracking fault-tolerant control method for DDEV considering steering actuator faults. Firstly, we establish the dynamic model of the steering actuator and the trajectory tracking model of DDEV. The model is linearized and discretized by using Taylor series expansion and forward Euler method. Next, considering multi-objective constraints such as motion comfort, actuator saturation and road adhesion boundary, the trajectory tracking control strategy of DDEV is designed by using model predictive
Wang, DepingLi, LunTeng, YuhanZhu, BingChen, Zhicheng
Electric vehicles (EVs) have experienced significant growth, and the battery safety of EVs has drawn increased attention. However, the mechanical responses of battery during crashes have rarely been studied. Hence, the objective of this study was to understand EV battery package mechanics during side-pole crashes at different impact locations and speeds beyond regulated side-pole test with one specific speed and one location. An EV finite element (FE) model with a battery package was used. Side-pole impact simulations were conducted at four impact locations, including the baseline impact location according to side-pole impact regulation, plus three positions by moving the rigid pole 400 mm toward the back of the EV and moving the pole 400 and 800 mm toward the front of the EV. In addition, the impact velocities at 32, 50, and 80 km/h were simulated. Based on simulations, the peak relative displacement, the maximum change in gap between batteries, the maximum change in gap between the
Chen, JianBian, KeweiMao, Haojie
Neck injury is one of the most common injuries in traffic accidents, and its severity is closely related to the posture of the occupant at the time of impact. In the current era of smart vehicle, the triggered AEB and the occupant's active muscle force will cause the head and neck to be out of position which has significant affections on the occurrence and severity of neck injury responses. Therefore, it is very important to study the influences of active muscle force on neck injury responses in in frontal impact with Automatic Emergency Braking conditions. Based on the geometric characteristics of human neck muscles in the Zygote Body database, the reasonable neck muscle physical parameters were obtained firstly. Then a neck finite element model (FEM) with active muscles was developed and verified its biofidelity under various impact conditions, such as frontal, side and rear-end impacts. Finally, using the neck FEM with or without active muscle force, a comparative study was
Junpeng, XuGan, QiuyuJiang, BinhuiZhu, Feng
Deliberate modifications to infrastructure can significantly enhance machine vision recognition of road sections designed for Vulnerable Road Users, such as green bike lanes. This study evaluates how green bike lanes, compared to unpainted lanes, enhance machine vision recognition and vulnerable road users safety by keeping vehicles at a safe distance and preventing encroachment into designated bike lanes. Conducted at the American Center for Mobility, this study utilizes a vehicle equipped with a front-facing camera to assess green bike lane recognition capabilities across various environmental conditions including dry daytime, dry nighttime, rain, fog, and snow. Data collection involved gathering a comprehensive dataset under diverse conditions and generating masks for lane markings to perform comparative analysis for training Advanced Driver Assistance Systems. Quality measurement and statistical analysis are used to evaluate the effectiveness of machine vision recognition using
Ponnuru, Venkata Naga RithikaDas, SushantaGrant, JosephNaber, JeffreyBahramgiri, Mojtaba
Triply Periodic Minimal Surface (TPMS) structures have gained significant attention in recent years due to their excellent mechanical properties, lightweight characteristics, and potential for energy absorption in various engineering applications, particularly in automotive safety. This study explores the design, manufacturing, and mechanical performance of both general and hybrid TPMS structures for energy absorption. Three types of fundamental TPMS unit cells—Primitive, Gyroid, and IWP—were modeled using implicit functions and combined to form hybrid structures. The hybrid designs were optimized by employing Sigmoid functions to achieve smooth transitions between different unit cells. The TPMS structures were fabricated using Selective Laser Melting (SLM) technology with 316L stainless steel and subjected to quasi-static compression tests. Numerical simulations were conducted using finite element methods to verify the experimental results. The findings indicate that hybrid TPMS
Liu, ZheWang, MingJieGuo, PengboLi, YouguangLian, YuehuiZhong, Gaoshuo
Several challenges remain in deploying Machine Learning (ML) into safety critical applications. We introduce a safe machine learning approach tailored for safety-critical industries including automotive, autonomous vehicles, defense and security, healthcare, pharmaceuticals, manufacturing and industrial robotics, warehouse distribution, and aerospace. Aiming to fill a perceived gap within Artificial Intelligence and ML standards, the described approach integrates ML best practices with the proven Process Failure Mode & Effects Analysis (PFMEA) approach to create a robust ML pipeline. The solution views ML development holistically as a value-add, feedback process rather than the resulting model itself. By applying PFMEA, the approach systematically identifies, prioritizes, and mitigates risks throughout the ML development pipeline. The paper outlines each step of a typical pipeline, highlighting potential failure points and tailoring known best practices to minimize identified risks. As
Schmitt, PaulSeifert, Heinz BodoBijelic, MarioPennar, KrzysztofLopez, JerryHeide, Felix
In this work, design optimization for the lightweight of the body frame of a commercial electric bus with the requirements of stiffness, strength and crashworthiness is presented. The technique for order preference by similarity to ideal solution (TOPSIS) is applied to calculate the components that have a great impact on the output response of the static modal model and the rear-end collision model. The thickness of the five components with the highest contribution in the two models is determined as the final design variable. Design of experiment (DOE) is carried out based on the Latin Hypercube sampling method, and then the surrogate models are fitted by the least squares regression (LSR) method based on the DOE sampling data. The error analysis of the surrogate model is carried out to determine whether it can replace the finite element (FE) model for optimization, then the optimization scheme for lightweight optimization of electric bus frame is implemented based on the algorithm of
Yang, XiujianTian, DekuanLiu, JiaqiCui, YanLin, Qiang
Automated driving is an important development direction of the current automotive industry. Level 3 automated driving allows the driver to perform non-driving related tasks (NDRTs) during automated driving, however, once the operating conditions exceed the designed operating domain, the driver is still required to take over. Therefore, it is important to rationally design takeover requests (TORs) in Level 3 conditional automated driving. This paper investigates the effect of directional tactile guidance on driver takeover performance in emergency obstacle avoidance scenarios during the transfer of control from automated driving mode to manual driving. 18 participants drove a Level 3 conditional automated driving vehicle in a driving simulator on a two-way four-lane urban road, performed a takeover, and avoided obstacles while performing non-driving related tasks. The driver's takeover performance during the takeover process was measured and subjective driver evaluation data was
Liang, XinyingLiang, YunhanMa, XiaoyuanWang, LuyaoChen, GuoyingHu, Hongyu
The electric motor is a significant source of noise in electric vehicles (EVs). Traditional hardware-based NVH optimization techniques can prove insufficient, often resulting in trade-offs between motor torque or efficiency performance. The implementation of motor control-based torque ripple cancellation (TRC) technology provides an effective and flexible solution to reduce the targeted orders. This paper presents an explanation of the mathematical theory underlying the TRC method, with a particular focus on the various current injection methods, including those that allow up to 4DOFs (degrees-of-freedom). In the case study, the injection of controlled fifth or seventh order current harmonics into a three-phase AC motor is shown to be an effective method for cancelling the most dominant sixth order torque ripple. A dedicated feedforward harmonic current generation module is developed the allows the application of harmonic current commands to a motor control system with adjustable
He, SongGong, ChengChang, LePeddi, VinodZhang, PengGSJ, Gautam
Automotive audio components must meet high quality expectations with ever-decreasing development costs. Predictive methods for the performance of sound systems in view of the optimal locations of loudspeakers in a car can help to overcome this challenge. Use of simulation methods would enable this process to be brought up front and get integrated in the vehicle design process. The main objective of this work is to develop a virtual auralization model of a vehicle interior with audio system. The application of inverse numerical acoustics [INA] to source detection in a speaker is discussed. The method is based on truncated singular value decomposition and acoustic transfer vectors The arrays of transfer functions between the acoustic pressure and surface normal velocity at response sites are known as acoustic transfer vectors. In addition to traditional nearfield pressure measurements, the approach can also include velocity data on the boundary surface to improve the confidence of the
Baladhandapani, DhanasekarThaduturu, Sai RavikiranDu, Isaac
To provide an affordable and practical platform for evaluating driving safety, this project developed and assessed 2 enhancements to an Unreal-based driving simulator to improve realism. The current setup uses a 6x6 military truck from the Epic Games store, driving through a pre-designed virtual world. To improve auditory realism, sound cues such as engine RPM, braking, and collision sounds were implemented through Unreal Engine's Blueprint system. Engine sounds were dynamically created by blending 3 distinct RPM-based sound clips, which increased in volume and complexity as vehicle speed rose. For haptic feedback, the road surface beneath each tire was detected, and Unreal Engine Blueprints generated steering wheel feedback signals proportional to road roughness. These modifications were straightforward to implement. They are described in detail so that others can implement them readily. A pilot study was conducted with 3 subjects, each driving a specific route composed of a straight
Duan, LingboXu, BoyuGreen, Paul
In future spark-ignition internal combustion engines, characterized by high compression ratios, issues such as knocking and super-knocking have increasingly emerged as major factors limiting thermal efficiency improvements. Ion current detection technology, with its advantages of not altering engine structure, low cost, and maintenance-free operation, is considered as one of the most promising methods for in-cylinder combustion detection. However, the mechanism of ion current formation under end gas auto-ignition conditions remains unclear, and the matching law between the ion current signal and the combustion state can only be obtained by experimental and statistical methods so far, posing challenges for abnormal combustion diagnostics and control based on ion current detection technology. To analyze the signal characteristics of ion current under abnormal combustion from a more intrinsic perspective, this paper develops a one-dimensional flame ionization model using MATLAB. The model
Zhou, YanxiongDong, GuangyuNi, XiaociXu, JieLi, XianLi, Liguang
Opening a tailgate can cause rain that has settled on its surfaces to run off onto the customer or into the rear loadspace, causing annoyance. Relatively small adjustments to tailgate seals and encapsulation can effectively mitigate these effects. However, these failure modes tend to be discovered relatively late in the design process as they, to date, need a representative physical system to test – including ensuring that any materials used on the surface flow paths elicit the same liquid flow behaviours (i.e. contact angles and velocity) as would be seen on the production vehicle surfaces. In this work we describe the development and validation of an early-stage simulation approach using a Smoothed Particle Hydrodynamics code (PreonLab). This includes its calibration against fundamental experiments to provide models for the flow of water over automotive surfaces and their subsequent application to a tailgate system simulation which includes fully detailed surrounding vehicle geometry
Gaylard, Adrian PhilipWeatherhead, Duncan
The mechanical properties of materials play a crucial role in real life. However, methods to measure these properties are usually time-consuming and labour intensive. Small Punch Through (SPT) has non-destructive characteristics and can obtain load-displacement curves of specimens, but it cannot visually extract the mechanical properties of materials. Therefore, we designed a proprietary SPT experiment and fixture, built a finite element method (FEM) model and developed a multi-fidelity model capable of predicting the mechanical properties of steel and aluminium alloys. It makes use of multi-fidelity datasets obtained from SPT and FEM simulation experiments, and this integration allows us to support and optimize the predictive accuracy of the study, thus ensuring a comprehensive and reliable characterization of the mechanical properties of the materials. The model also takes into account variations in material thickness and can effectively predict the mechanical properties of materials
Zou, JieChen, YechaoLi, ShanshanHuayang, Xiang
The proliferation of the electric vehicle (EVs) in the US market led to an increase in the average vehicle weight due to the assembly of the larger high-voltage (HV) batteries. To comply with this weight increase and to meet stringent US regulations and Consumer Ratings requirements, Vehicle front-end rigidity (stiffness) has increased substantially. This increased stiffness in the larger vehicles (Large EV pickups/SUVs) may have a significant impact during collision with smaller vehicles. To address this issue, it is necessary to consider adopting a vehicle compatibility test like Euro NCAP MPDB (European New Car Assessment Program Moving Progressive Deformable Barrier) for the North American market as well. This study examines the influence of mass across vehicle classes and compares the structural variations for each impact class. The Euro NCAP MPDB (European New Car Assessment Program Moving Progressive Deformable Barrier) protocol referenced for this analysis. Our evaluation
Kusnoorkar, HarshaKoraddi, BasavarajGuerrero, MichaelSripada, Venu VinodTangirala, Ravi
Image-based machine learning (ML) methods are increasingly transforming the field of materials science, offering powerful tools for automatic analysis of microstructures and failure mechanisms. This paper provides an overview of the latest advancements in ML techniques applied to materials microstructure and failure analysis, with a particular focus on the automatic detection of porosity and oxide defects and microstructure features such as dendritic arms and eutectic phase in aluminum casting. By leveraging image-based data, such as metallographic and fractographic images, ML models can identify patterns that are difficult to detect through conventional methods. The integration of convolutional neural networks (CNNs) and advanced image processing algorithms not only accelerates the analysis process but also improves accuracy by reducing subjectivity in interpretation. Key studies and applications are further reviewed to highlight the benefits, challenges, and future directions of
Akbari, MeysamWang, AndyWang, QiguiYan, Cuifen
This study numerically analyzed the gas diffusion layer (GDL) in proton exchange membrane fuel cells (PEMFCs). The GDL, composed of carbon fibers and binder, plays a critical role in facilitating electron, heat, gas, and water transport while cushioning under cell compression. Its microstructure significantly influences these properties, requiring precise design. Using simulations, this study explored GDL designs by varying fiber and binder parameters and calculated gas diffusivity under wet conditions. Unlike previous studies, a novel model treated carbon fibers as beam elements with elastic binder connections, closely replicating structural changes under compression. Key properties analyzed include permeability, electrical conductivity, and gas diffusion efficiency under wet conditions. The optimized designs enhanced these properties while balancing trade-offs between electrical conductivity and mass transport. These findings provide valuable guidelines for advancing PEMFC technology
Ota, YukiDobashi, ToshiyukiNomura, KumikoHattori, TakuyaMaekawa, Ryosuke
The linear region of the side-slip mechanical properties of tires is often used in the simulation of linear monorail models for vehicles, especially in the design of active control systems. Side-slip stiffness is a key parameter in tire side-slip, and is significantly influenced by camber and load. In response to the tire industry's need for efficient acquisition of tire mechanical properties and the development of virtual prototyping technology, this paper proposes a method to address the influence mechanism of camber on side-slip in the study of tire camber side-slip prediction models. This paper analyzes the impact of camber on the linear region of tire side-slip mechanical properties at the microscopic level. It then examines the effect of camber on the side-slip condition from the perspective of tire external characteristics, combined with the tire theoretical model, to map the local characteristics of camber onto the external characteristics of tire side-slip. First, a finite
Yin, HengfengSuo, YanruWu, HaidongMin, HaitaoLiu, Dekuan
As the utilization of lithium-ion batteries in electric vehicles becomes increasingly prevalent, there has been a growing focus on the mechanical properties of lithium-ion battery cores. The current collector significantly impacts the tensile properties of the electrode and the internal fracture of the battery cell. The stripping process tends to cause additional damage to the current collector, so tensile testing is not able to obtain in-situ mechanical properties of the current collector. Therefore, nanoindentation tests are required to acquire the in situ mechanical properties of the current collector. Nanoindentation testing represents the primary methodology for the determination of the mechanical properties of thin films. The Oliver-Pharr method is the standard approach used by commercial indentation instruments for the evaluation of mechanical properties in materials. Nevertheless, this approach is constrained by the limitations imposed by the sample boundary conditions. To
Dai, RuiSun, ZhiweiPark, JeongjinXia, YongZhou, Qing
The advancement of high-performance electrification for electric vehicle (EV) development is continuously pushing the boundaries of electric motor technology. The axial flux motor (AFM) represents a promising application for high-performance EVs, offering potential advantages including up to twice the torque density and a 50% reduction in weight compared to regular IPM radial flux motors. The distinctive "pancake" configuration and high axial forces inherent to AFMs present notable NVH challenges, yet there is a lack of research exploring NVH analysis and risk assessment. In this paper, a 10-pole and 12-slot AFM motor is designed, prototyped, and tested, demonstrating the capability to deliver 320 Nm of peak torque and 140 kW of peak power. A comprehensive finite-element model is constructed, and the orthotropic stator material properties are evaluated using modal test data. The dominant axial stator modes are identified as the source of resonances in the system responses. A three
He, SongJensen, WilliamForsyth, AlexanderChang, LeZhang, PengGong, ChengYao, JianZou, YushengFedida, VincentDuan, ChengwuGSJ, Gautam
High-efficiency manufacturing involves the transmission of copious amounts of data, exemplified both by trends in the automotive industry and advances in technology. In the automotive industry, products have been growing increasingly complex, owing to multiple SKUs, global supply chains and the involvement of many tier 2 / Just-In Time (JIT) suppliers. On top of that, recalls and incidents in recent years have made it important for OEMs to be able to track down affected vehicles based on their components. All of this has increased the need for OEMs to be able to collect and analyze component data. The advent of Industry 4.0 and IoT has provided manufacturing with the ability to efficiently collect and store large amounts of data, lining up with the needs of manufacturing-based industries. However, while the needs to collect data have been met, corporations now find themselves facing the need to make sense of the data to provide the insights they need, and the data is often unstructured
Jan, JonathanPreston, JoshuaJuncker, John
Virtual prototyping enables tires to be involved in automotive research and development (R&D) at an early stage, eliminating the trial-and-error process of physical tire samples and effectively reducing time and costs. Semi-empirical/empirical tire models are commonly used to evaluate vehicle-tire virtual mating. To parameterize these models, finite element (FE) simulations are necessary, involving combinations of sideslip, camber, and longitudinal slip under various loads. This paper identifies that when multiple inputs are combined, the FE simulation conditions become complex and numerous, presenting a significant challenge in virtual prototyping applications. Through an extensive analysis of more than ten tire prediction modeling methods and models in detail, this paper demonstrates the significant potential of tire prediction modeling in addressing this challenge. We begin with an overview of the current state of research in tire virtual prototyping, reviewing its application
Yin, HengfengSuo, YanruLu, DangXia, DanhuaMin, Haitao
In cold and snowy areas, low-friction and non-uniform road surfaces make vehicle control complex. Manually driving a car becomes a labor-intensive process with higher risks. To explore the upper limits of vehicle motion on snow and ice, we use an existing aggressive autonomous algorithm as a testing tool. We built our 1:5 scaled test platform and proposed an RGBA-based cost map generation method to generate cost maps from either recorded GPS waypoints or manually designed waypoints. From the test results, the AutoRally software can be used on our test platform, which has the same wheelbase but different weights and actuators. Due to the different platforms, the maximum speed that the vehicle can reach is reduced by 1.38% and 2.26% at 6.0 m/s and 8.5 m/s target speeds. When tested on snow and ice surfaces, compared to the max speed on dirt (7.51 m/s), the maximum speed decreased by 48% and 53.9%, respectively. In addition to the significant performance degradation on snow and ice, the
Yang, YimingBos, Jeremy P.
With the widespread application of the Automatic Emergency Braking System (AEB) in vehicles, its impact on pedestrian safety has received increasing attention. However, after the intervention of AEB, the kinematic characteristics of pedestrian leg collisions and their corresponding biological injury responses also change. At the same time, in order to accurately evaluate the pedestrian protection performance of vehicles, the current assessment regulations generally use advanced pedestrian protection leg impactors (aPLI) and rigid leg impactors (TRL) to simulate the movement and injury conditions of pedestrian legs. Based on this, in order to explore the collision boundary conditions and changes in injury between vehicles and APLI and TRL leg impactors under the action of AEB, this paper first analyzes the current passive and active assessment conditions. Secondly, the simulation software LS-DYNA is used to build a finite element model of APLI and TRL impactor-vehicle collisions to
Ye, BinHong, ChengWan, XinmingLiu, YuCheng, JamesLong, YongchenHao, Haizhou
Novel experimental and analytical methods were developed with the objective of improving the reliability and repeatability of coast-down test results. The methods were applied to coast-down tests of a SUV and a tractor-trailer combination, for which aerodynamic wind-tunnel data were available for comparison. The rationale was to minimize the number of unknowns in the equation of motion by measuring rolling and mechanical resistances and wheel-axle moments of inertia, which was achieved using novel experimental techniques and conventional rotating-drum tests. This led to new modelling functions for the rolling and mechanical resistances in the equation of motion, which was solved by regression analysis. The resulting aerodynamic drag coefficient was closer to its wind-tunnel counterpart, and the predicted low-speed road load was closer to direct measurements, than the results obtained using conventional methods. It is anticipated that applying the novel techniques to characterize the
Tanguay, Bernardde Souza, Fenella
This paper focuses on the design optimization of a commercial electric bus body frame with steel-aluminum heterogeneous material orienting the performances of strength, crashworthiness and body lightweight. First, the finite element (FE) model of the body frame is established for static and side impact analysis, and the body frame is partitioned into several regions according to the thickness distribution of the components. The thicknesses of each region are regarded as the variables for the sensitivity analysis by combining the relative sensitivity method and the Sobol index method, and nine variables to which the performance indexes are more sensitive are selected as the final design variables for design optimization. Then the surrogate models are developed, and in order to improve the accuracy of the surrogate models, a model-constructing method called the particle swarm optimization BP neural network (PSO-BP) data regression prediction is proposed and formulated. In this method
Yang, XiujianTian, DekuanCui, YanLin, QiangSong, Yi
Parts in automotive exhaust assembly are joined to each other using welding process. When the exhaust is subjected to dynamic loads, most of these weld joints experience high stresses. Hence it should be ensured that the exhaust assembly is designed to meet the requirements of exhaust durability for the estimated life of the vehicle. We also know that all parts used in manufacturing of exhaust system have inherent variations with respect to sheet metal thickness, dimensions and shape. Some parts like flex coupling and isolators have high variations in their stiffness based on their material and manufacturing processes. This all leads to a big challenge to ensure that the exhaust system meets the durability targets on a vehicle manufactured with all these variations. This works aims to evaluate the statistical spread in weld life of an exhaust with respect to inherent variations of its components. For the purpose of variational analysis, a Design of Experiments (DOE) is done where
Ramamoorthy, RajapandianBazzi, Ramzi
Automotive industry is growing rapidly with innovations leading to increase in new features and improving the Quality of vehicles. These new components are developed with the available design standards across global OEMs. This Quality research paper aims to address the need of revision of design standards due to environmental factors prevailing in India. With the increase towards autonomous mobility, the number of electronics is also increasing, and this involves hardware & software evaluation. The hardware testing is a point of concern due to increase in the failure rate from the markets. Environment changes are very much evident with the growing economies and OEMs are developing the components with innovation, but if the basic design standards are not revised in parallel with the changing environment, the issues will continue to trouble the end customers. The failed cases data received from across the country was analyzed and observed that the cases are majorly reported from urban
Marwah, RamnikPyasi, PraveenBindra, RiteshGarg, Vipin
Shear Thickening Fluid (STF) exhibits tunable stiffness under varying loading velocities, making it an ideal candidate for energy absorption in transportation systems subjected to complex loading conditions, such as crash scenarios. Recent research highlights that integrating STF with conventional structures can significantly enhance overall energy absorption performance. In this study, we developed a novel sandwich plate by combining a newly designed bio-inspired 3D periodic structure with STF, aiming to create an advanced energy absorber. A finite element model of this system was developed to simulate the crush tests. Using this numerical model, we conducted additional impact simulations to investigate the effects of impact velocity on key structural responses, including force-displacement curve, as well as energy absorption. The contributions of both the fluid and solid components were analyzed. Our findings indicate that the integrated structure demonstrates superior performance
Zhu, FengDeb, Anindya
This study investigates the impact of various notch geometries on the outer surface of the rotor of an interior permanent magnet synchronous motor intended for traction applications, focusing on improving both its thermal and electromagnetic performances. Traditional motor cooling methods, such as water jackets or oil spray/impingement, typically target the stator and/or end windings, neglecting rotor cooling. As a result, the dissipation of the heat from the rotor is dependent on the heat transfer across the air gap surrounding the rotor, despite air’s poor thermal conductivity, which causes it to act as an insulator. Rotor notches are used to limit the higher order harmonics from air gap flux density which results in decreased torque ripple, cogging torque, noise, and vibration of the machine. While the effect of rotor notches on electromagnetic performance is analyzed, their impact on the thermal management of the motor, particularly the heat transfer coefficient in the air gap
Zajac, ArthurDe Silva, BuddhikaLee, SunMistry, JigarNasirizarandi, RezaJianu, OfeliaKar, Narayan
Triply periodic minimal surface (TPMS) structure, demonstrates significant advantages in vehicle design due to its excellent lightweight characteristics and mechanical properties. To enhance the mechanical properties of TPMS structures, this study proposes a novel hybrid TPMS structure by combining Primitive and Gyroid structures using level set equations. Following this, samples were fabricated using selective laser sintering (SLS). Finite element models for compression simulation were constructed by employing different meshing strategies to compare the accuracy and simulation efficiency. Subsequently, the mechanical properties of different configurations were comprehensively investigated through uniaxial compression testing and finite element analysis (FEA). The findings indicate a good agreement between the experimental and simulation results, demonstrating the validity and accuracy of the simulation model. For TPMS structures with a relative density of 30%, meshing with S3R
Tang, HaiyuanXu, DexingSun, XiaowangWang, XianhuiWang, LiangmoWang, Tao
This paper investigates the development of a Finite Element model of a Mixed Service Drive truck tire sized 315/80R22.5 equipped with thermal simulating properties. The physical experiments were performed at a high-speed track in Hällered, Sweden for the truck combination travelling at a constant speed of 80 km/h. For this investigation, the Gross Combination Weight is approximately 42 metric tons. In the Finite Element Analysis environment, ESI Virtual Performance Solutions, the truck tire is designed with hyperelastic Ogden solid rubber definitions. The Ogden material definition is used in this application as it is more suitable to perform thermal and wear analysis within the Finite Element environment. The Finite Element truck tire model is simulated to increase in two different temperature rates. The truck tire model simulates the thermal build-up over time for select tires on a High-Capacity transport truck combination, particularly a driven tire on the tractor. Finite element
Ly, AlfonseCollings, WilliamEl-Sayegh, ZeinabEl-Gindy, MoustafaJohansson, IngeOijer, Fredrik
Wind tunnel calibration is necessary for repeatable and reproducible data for all industries interested in their output. Quantities such as wind speed, pressure gradients, static operating conditions, ground effects, force and moment measurements, as well as flow uniformity and angularity are all integral in an automotive wind tunnel’s data quality and can be controlled through appropriate calibration, maintenance, and statistical process control programs. The purpose of this technical paper is to (1) provide a basis of commonality for automotive wind tunnel calibration, (2) help customers and operators to determine the calibration standards best suited for their unique automotive wind tunnel and, (3) complement the American Institute of Aeronautics and Astronautics recommended practice R-093-2003(2018) Calibration of Subsonic and Transonic Wind Tunnels as specifically applied to the automotive industry. This document compiles information from various automotive wind tunnel customers
Bringhurst, KatlynnBest, ScottNasr Esfahani, VahidSenft, VictorStevenson, StuartWittmeier, Felix
This paper presents Matchit, a novel method for expediting issue investigation and generating actionable insights from textual data. Recognizing the challenges of extracting relevant information from large, unstructured datasets, we propose a domain-adaptable approach by integrating expert domain knowledge to guide Large Language models (LLMs) to automatically identify and categorize key information into distinct topics. This process offers two key functionalities: fully automatic topic extraction based solely on input data, providing a concise overview of the problem and potential solutions, and user-guided extraction, where domain experts can specify the type of information or pre-defined categories to target specific insights. This flexibility allows for both broad exploration and focused analysis of the data. Matchit's efficacy is demonstrated through its application in the automotive industry, where it successfully extracts repair diagnostics from diverse textual sources like
Wang, LijunArora, Karunesh
This paper seeks to define an analytical approach to ergonomic cockpit design for SAE formula style vehicles. The proposed approach uses a data driven driver model based on RAMSIS ergonomic FEA that considers the discomfort, fatigue, and force availability to evaluate cockpit designs that are generated considering defined constraint inputs, such as driver gender and size. The multifunctional model is applicable to various settings of vehicle design and is tuned toward proving performance in operation tasks, as well as setting the groundwork for a multi-variable optimization to determine the preferred driver controls positions for minimum effort and fatigue. In this initial research, RAMSIS ergonomic software is used to generate fatigue and joint discomfort data related to individual joint angles. Anthropometric data is used to calculate the proportional limb lengths from an individual’s gender and height percentile. The optimization function works by selecting a range of driver
Mayor, J.RhettBezaitis, MeganOromi, NegarWinters, EmilyRepp, Alex
Real-world data show that abdominal loading due to a poor pelvis-belt restraint interaction is one of the primary causes of injury in belted rear-seat occupants, highlighting the importance of being able to assess it in crash tests. This study analyzes the phenomenon of submarining using video, time histories, and statistical analysis of data from a Hybrid III 5th female dummy seated in the rear seat of passenger vehicles in moderate overlap frontal crash tests. This study also proposes different metrics that can be used for detecting submarining in full-scale crash tests. The results show that apart from the high-speed videos, when comparing time-series graphs of various metrics, using a combination of iliac and lap belt loads was the most reliable method for detecting submarining. Five metrics from the dynamic sensors (the maximum iliac moment, maximum iliac force drop in 1 ms, time for 80% drop from peak iliac force, maximum pelvis rotation, and lumbar shear force) were all
Jagtap, Sushant RJermakian, Jessica SEdwards, Marcy A
Battery safety is a paramount concern in the development of electric vehicles (EVs), as failures can lead to catastrophic consequences, including fires and explosions. With the rapid global adoption of EVs, understanding how battery cells perform under extreme conditions such as mechanical or thermal abuse is crucial for ensuring vehicle safety. This study investigates the abuse response of lithium-ion batteries under high-speed mechanical loading. Our research systematically examines the response of these cells at different states of charge (SOC) through controlled dynamic tests. These tests offer insights into the failure response of the cells. By analyzing the data, we gain a deeper understanding of the conditions that could trigger thermal runaway under mechanical abuse loadings, representative of EV crashes, a critical safety concern in EV battery systems. The experimental setup and methodologies are presented in this paper, alongside key findings that highlight the importance of
Patanwala, HuzefaKong, KevinChalla, VidyuDarvish, KuroshSahraei, Elham
Over the last two decades many improvements have been made in stock car racing driver safety. One of these is the head surround, which is rigidly secured to and an integral part of the NASCAR (National Association for Stock Car Auto Racing, LLC) seating environment and serves as an effective restraint for head protection during lateral and rear impacts. However, previous head impact material specifications were optimized for moderate to severe impacts and did not address low severity impacts that occur frequently during typical driving, such as race restart vehicle nose-to-tail contact. This study focused on developing a test methodology for comprehensive evaluation of rear head surround materials for low, moderate and severe impacts. Specifically, this study aimed to formulate a specification that maintains previous material performance during high speed impacts, while decreasing head accelerations at low speed impacts. Quasi-static and dynamic drop tower testing of sample materials
Gray, Alexandra N.Harper, Matthew G.Mukherjee, SayakPatalak, John P.Gaewsky, James
This paper is a continuation of a previous effort to evaluate the post-impact motion of vehicles with high rotational velocity within various vehicle dynamic simulation softwares. To complete this goal, this paper utilizes a design of experiments (DOE) method. The previous papers analyzed four vehicle dynamic simulation software programs; HVE (SIMON and EDSMAC4), PC-Crash and VCRware, and applied the DOE to determine the most sensitive factors present in each simulation software. This paper will include Virtual Crash into this methodology to better understand the significant variables present within this simulation model. This paper will follow a similar DOE to that which was conducted in the previous paper. A total of 32 trials were conducted which analyzed ten factors. Aerodynamics, a factor included in the previous DOE, was not included within this DOE because it does not exist within Virtual Crash. The same three response variables from the previous DOE were measured to determine
Roberts, JuliusCivitanova, NicholasStegemann, JacobBuzdygon, DavidThobe, Keith
Continuing prior work, which established a simulation workflow for fatigue performance of elastomeric suspension bushings operating under a schedule of 6-channel (3 forces + 3 moments) road load histories, the present work validates Endurica-predicted fatigue performance against test bench results for a set of multi-channel, time-domain loading histories. The experimental fatigue testing program was conducted on a servo-hydraulic 3 axis test rig. The rig provided radial (cross-car), axial (for-aft), and torsional load inputs controlled via remote parameter control (rpc) playback of road load data acquisition signals from 11 different test track events. Bushings were tested and removed for inspection at intervals ranging from 1x to 5x of the test-equivalent vehicle life. Parts were sectioned and checked for cracks, for point of initiation and for crack length. No failure was observed for bushings operated to 1 nominal bushing lifetime. After 3 nominal bushing lifetimes, cracks were
Mars, WillBarbash, KevinWieczorek, MatthewPham, LiemBraddock, ScottSteiner, EthanStrumpfer, Scott
As a kind of off-road racing car, the driving condition of Baja is extremely bad. In order to allow the driver to control the vehicle well in complex working conditions, it is particularly important to provide a comfortable and convenient driving space and handling space for the driver. In this paper, firstly, RAMSIS is used to carry out the ergonomics verification of the racing car from the comfort analysis, reachable area analysis and visual field analysis, and optimize the design of the cockpit layout of the Baja racing car. Then the NVH characteristics of the Baja racing car frame are studied, and the 12-order modal results are obtained by finite element analysis and simulation. Then the natural frequency of the frame is measured by experiments, and the experimental results are verified to match the theoretical values. The research shows that the above steps can design a comfortable driving posture and operating space for the racer and provide experience for the future layout of
Liu, Silang
The modern luxurious electric vehicle (EV) demands high torque and high-speed requirements with increased range. Fulfilling these requirements, arises the need for increased electric current supply to motors. Increased amperage through the stator causes higher losses resulting in elevated temperature across the motor components and its housing. In most of the cases, stator is mounted on the housing through interference fit to avoid any slippage during operation conditions. High temperature across the stator and housing causes significant thermal expansions of the components which is uneven in nature due to the differences in corresponding coefficient of thermal expansion (CTE) values. Housings are generally made of aluminium and tends to expand more having higher value of CTE than that of steel core of stator which may give rise to a failure mode related to stator slippage. To address this slippage if the amount of interference fit is increased, that’ll result in another failure mode
Karmakar, NilankanPrasad, Praveen
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