Browse Topic: Vehicle performance

Items (1,362)

Tube-MPC Based Path Tracking for I Vehicle Considering Data-Driven Stable Region and External Disturbances

2025-01-8262

04/01/2025

Path tracking is a key function of intelligent vehicles, which is the basis for the development and realization of advanced autonomous driving. However, the imprecision of the control model and external disturbances such as wind and sudden road conditions will affect the path tracking effect and even lead to accidents. This paper proposes an intelligent vehicle path tracking strategy based on Tube-MPC and data-driven stable region to enhance vehicle stability and path tracking performance in the presence of external interference. Using BP-NN combined with the state-of-the-art energy valley optimization algorithm, the five eigenvalues of the stable region of the vehicle β−β̇ phase plane are obtained, which are used as constraints for the Tube-MPC controller and converted into quadratic forms for easy calculation. In the calculation of Tube invariant sets, reachable sets are used instead of robust positive invariant sets to reduce the calculation. Simulation results demonstrates that the

Zhang, Haosen, Li, Yihang, Wu, Guangqiang

Active and Passive Security Generalization Algorithm and Typical Case Analysis

2025-01-8744

04/01/2025

In order to effectively predict the vehicle safety performance and reduce the cost of enterprise safety tests, a generalized simulation model for active and passive vehicle safety was proposed. The frontal driver-side collision model under the intervention of the Autonomous Emergency Braking (AEB) was created by using the MADYMO software. The collision acceleration obtained from the sled test was taken as the original input of the model to conduct simulation for the working conditions under different sitting postures of the human body. The injury values of various parts of the Hybrid III 50th dummy were read. Based on the correlation between the two, an active and passive simulation model was established through the Back Propagation (BP) neural network. The input of the model was the inclination angle centered on the dummy's waist, and the output was the acceleration of the dummy's head. The results showed that the comprehensive prediction accuracy rate exceeded 80%. Therefore, the

Ge, Wang, fengyao, LV

Impact of Hybrid Electric Vehicles on Energy Consumption and Emission Reduction for Agricultural Applications

2025-01-8540

04/01/2025

As the agricultural industry seeks to enhance sustainability and reduce operational costs, the introduction of mild hybrid technology in tractors presents a promising solution. This paper focuses on downsizing internal combustion (IC) engine, coupled with integration of electric motor, to reduce fuel consumption and meet stringent emission regulations while maintaining power requirement for agricultural applications in India. The hybridization aims to deliver instant power boosts during peak loads and capitalizes on energy recovery during part loads and braking. Furthermore, the idle avoidance feature minimizes fuel consumption during periods of inactivity thus improving fuel efficiency. The hybridization also aims to hybridize auxiliary systems for flexible power management, enabling operation of either engine, auxiliaries, or both as needed. A newly developed hybrid supervisory control prototype efficiently manages electric power and mechanical power, enabling intelligent management

Prasad, Lakshmi P., PS, Satyanarayana, Paygude, Tejas, Gangsar, Purushottam, Thakre, Mangesh, Choudhary, Nagesh, Gitapathi, Ajinkya

Machine Learning-Based Digital Twin for Optimizing Automotive Components

2025-01-8206

04/01/2025

This paper presents a Digital Twin approach based on Machine Learning (ML), aimed at creating software-based sensors to reduce the auxiliary devices of the vehicle and enabling predictive maintenance, thus reducing carbon footprint. The solution is applied to the electric Lubrication Oil Pump (eLOP), a crucial component within a vehicle's powertrain system. The proposed eLOP Digital Twin integrates ML-based sensors to estimate critical parameters such as temperature, pressure and flow rate, reducing the reliance on physical sensors and associated hardware. This approach minimizes manufacturing complexity and cost, enhancing energy efficiency during both production and operation. Furthermore, the Digital Twin facilitates predictive maintenance by continuously monitoring the component's performance, enabling early detection of potential failures and optimizing maintenance schedules. This leads to lower energy consumption and reduced emissions throughout the component's lifecycle. The

Khan, Jalal, D'Alessandro, Stefano, Tramaglia, Federico, Fauda, Alessandro

Sensory-Driven Design Method for Personalizing Ride Comfort Tailored to Individual Vibration Perception

2025-01-8273

04/01/2025

This study aims to develop a design method that tailors the ride comfort and design variables of vehicle components according to individual differences in vibration perception. In conventional development, variations in vibration perception have been recognized; however, quantification methods remain undeveloped, preventing designs from being adapted to individual driver perceptions. The two unresolved problems include the uniformization of vibration perception in sensory performance modeling, which predicts sensory scores from vehicle vibrations, and design approaches that focus on minimizing vehicle vibrations without considering vibration perception. First, the authors’ previous study quantified the existence of individual differences in vibration perception through sensory scores obtained from ride simulator experiments involving 24 non-expert drivers using vibrations derived from a uniform vibration perception. Hierarchical clustering identified four perception groups; however

Kikuchi, Hironobu, Inaba, Kazuaki

A Comparative Study of Optimization Algorithms for 6DOF Design in Electric Vehicle Powertrain Mounting Systems

2025-01-8650

04/01/2025

Optimizing engine mounting systems is a complex task that requires balancing the isolation of vehicle vibrations with controlling powertrain movement within a limited dynamic envelope. Six Degrees of Freedom (6DOF) optimization is widely used for mounting stiffness and location optimization. This study investigates the application of various optimization algorithms for 6DOF analysis in engine mount design, where the system’s stochastic behaviour and probabilistic characteristics present additional challenges. Selecting an appropriate optimization framework is essential for achieving accurate and efficient NVH results. Recent advancements in research have introduced several 6DOF optimization algorithms to determine the optimal stiffness and location of engine mounts. The study evaluates a range of optimization methods, including Simultaneous Hybrid Exploration that is Robust, Progressive and Adaptive (SHERPA), Quadratic Programming (QP), Genetic Algorithm (GA), Particle Swarm

Hazra, Sandip, Khan, Arkadip

A Study of Tire Handling and Ride Performance Map According to Tire Tread Wear State

2025-01-8760

04/01/2025

The electric vehicle market, vehicle ECU computing power, and connected electronic vehicle control systems continue to grow in the automotive industry. The results of these advanced and expanded vehicle technologies will provide customers with increased cost savings, safety, and ride quality benefits. One of these beneficial technologies is the tire wearing prediction. The improved prediction of tire wear will advise a customer the best time to change tires. It is expected that this prediction algorithms will be essential part for both the optimization of the chassis control systems and ADAS systems to respond to changed tire performance that varies with a tire’s wear condition. This trend is growing, with many automakers interested in developing advanced technologies to improve product quality and safety. This study is aimed at analyzing the handling and ride comfort characteristics of the tire according to the depth of tire pattern wear change. The handing and ride comfort

Kim, Changsu, Kwon, Seungmin, Sung, Dae-Un, Ryu, Yonghyun, Ko, Younghee

Aerodynamic Simulation of a Parametrically Deformed Rotating Tire

2025-01-8765

04/01/2025

As the automotive industry increasingly shifts toward electrification, reducing vehicle drag becomes crucial for enhancing battery range and meeting consumer expectations. Additionally, recent regulations such as WLTP can require car manufacturers to provide reliable drag data for vehicles as they are configured, as is the case in Europe. Vehicle and tire manufacturers can assess tire impacts on vehicle performance through testing. However, to improve designs, it is essential to identify which tire features influence the flow field and overall vehicle performance. Physical tests measure tire behavior under load, but isolating contact patch and tire bulge effects is difficult, as both change together. Simulation allows independent analysis of these factors—something that physical testing alone cannot achieve. This paper investigates the aerodynamic impact of realistic tire deformation parameters—specifically, bulge and contact patch deformations—using PowerFLOW® from Dassault Systèmes

Martinez Navarro, Alejandro, Parenti, Guido, Shock, Richard

Study on Optimal Shift Schedule for Single-shaft Parallel PHEVs Considering Driver’s Performance Expectation

2025-01-8577

04/01/2025

To take into account the drivers’ performance expectations in the comprehensive performance optimization of plug-in hybrid electric vehicles (PHEVs), we proposed an optimization method for the shift schedule of single-shaft parallel PHEVs considering drivers’ demands on both dynamic and economic performance. In accordance with torque distribution strategies developed for different working modes, the modes switching logic is formulated based on the demand torque along with the engine torque characteristics and the state of charge (SOC) of power battery. And a quantification model for driver’s intention is proposed using a fuzzy inference approach, which can compute the driver's dynamic and economic performance expectations using the driver's operation characteristics and vehicle status as input. With the help of a linear weighting method using the performance expectations as weights, a comprehensive performance evaluation function is constructed as the optimization objective of shift

Yin, Xiaofeng, Li, Hong, Zhang, Jinhong, Lei, Yulong

Design and Evaluation of an Adjustable Ackermann Rate Steering System for Formula Student Racing Cars

2025-01-8000

04/01/2025

FSAE is a competition designed to maximize car performance, in which the steering system is a key subsystem, and the steering system performance directly affects the cornering performance of the car. The driver relies on the steering system for effective handling, which is also crucial for cornering and achieving faster lap times. Therefore, while improving the performance of the steering system, it is crucial to match the vehicle design to the driver's habits. Traditionally, steering systems typically use an Ackermann rate between 0% and 100% to offset the slip angle caused by tire deformation, thus achieving the purpose of reducing tire wear. Calculations have shown that a 40-60% Ackermann rate provides a similar compensation effect with little difference in tire wear. The traditional steering design method also does not consider the driver's driving habits and feedback, which is not conducive to the improvement of the overall performance of the car. In FSAE's figure-of-eight loops

Wu, Hailin, Li, Mingyuan

Path Tracking of Autonomous Vehicles with Model Predictive Control (MPC) Optimized with Particle Swarm Optimization (PSO)

2025-01-8036

04/01/2025

This paper presents a comparative study between many control techniques to investigate the efficiency of the path tracking in various driving scenarios. In this study the Model predictive control (MPC), the adaptive model predictive control (AMPC) and the Stanley controller are employed to ensure that the vehicle follows reference paths accurately and robustly under varying environmental and vehicular conditions. Two driving scenarios are utilized S-road and Curved-road with MATLAB/Simulink under three different vehicle speeds to investigate vehicle performance employing the root mean square error (RMSE) as the performance evaluation function. Particle swarm optimization (PSO) utilized for optimizing the six parameters of the MPC prediction horizon (P), Control horizon(m), manipulated variable rates, manipulated variables weights and two output variables weights. Four objective functions are employed with PSO and compared to each other in terms of the time domain regarding the RMSE of

Eldesouky, Dina M.Mustafa, Abdelaziz, Taha Helmy, Mohamed, Amr.E

Mechanical Property Analysis of Triply Periodic Minimal Surface Structure with a Novel Hybrid Structure

2025-01-8215

04/01/2025

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, Haiyuan, Xu, Dexing, Sun, Xiaowang, Wang, Xianhui, Wang, Liangmo, Wang, Tao

The Impact of GCI Engines on Long-haul Trucks in the US and China

2025-01-8396

04/01/2025

This study evaluates the impacts of the gasoline compression ignition (GCI) engine on heavy duty long-haul trucks in both the Chinese and US markets. The study examines various aspects such as vehicle performance requirements, fuel consumption, emissions, and ownerships costs, and how they influence the implementation and impact of new technologies in these markets. By considering a wide variety of drive cycles, including standard regulatory cycles and real-world cycles, the study aims to identify the impact of varying degrees of powertrain electrification using diesel and GCI engines on fuel consumption and emissions. Additionally, this paper explores the viability of powertrain electrification in long-haul trucks by analyzing factors such as levelized cost of driving (LCOD), manufacturing costs, and energy costs. These considerations play a crucial role in determining the economic feasibility and attractiveness of electrification technologies in various driving scenarios and market

Nieto Prada, Daniela, Vijayagopal, Ram, Yan, Ziming, Sari, Rafael, He, Xin

Study on an Urban Ramp Driving Cycle Using Self-Organizing Map Neural Network

2025-01-8259

04/01/2025

To tackle the issue of lacking slope information in urban driving cycles used for vehicle performance evaluation, a construction method for urban ramp driving cycle (URDC) is formulated based on self-organizing map (SOM) neural network. The fundamental data regarding vehicles driving on typical roads with urban ramp characteristics and road slopes were collected using the method of average traffic flow, which were then pre-processed and divided into short-range segments; and twenty parameters that can represent the operation characteristics of vehicle driving on urban ramp were selected as the feature parameters of short-range segments. Dimension of the selected feature parameters was then reduced by means of principal component analysis. And a SOM neural network was applied in cluster analysis to classify the short-range segments. An URDC with velocity and slope information were constructed by combination of short-range segments with highly relevant coefficients according to the

Yin, Xiaofeng, Wu, Zhimin, Liang, Yiming, Wang, Peng, Xie, Yu

Evaluation of Different Powertrain Topologies for a Premium Plug-in Hybrid Electric Vehicle

2025-01-8531

04/01/2025

Plug-in hybrid electric vehicles combine the benefits of both battery electric and internal combustion engine drivetrains. There are multiple possibilities for hybrid configurations, each with its own advantages and disadvantages. In this study, two newly developed traction electric machines were employed alongside a gasoline engine in various hybrid configurations. These configurations, ranging from P1 to P4 and their combinations, were evaluated in terms of vehicle performance, energy consumption, and emissions. The impact of battery capacity was also examined. With a larger battery providing higher discharge power, the electric acceleration time significantly decreases from around 8.6 seconds to approximately 5.2 seconds as the battery capacity increases from 20 kWh to 40 kWh in configurations featuring two traction electric machines. In hybrid mode, the reduction in acceleration time is less pronounced, with a decrease of around 0.7 seconds compared to the configuration with a 20

Nguyen, Duc-Khanh, Tokat, Alexandra, Kristoffersson, Annika, Olsson, Jan-Ola

Revolutionizing Commercial Vehicles: Integrating Software-Defined Vehicle Architecture for Enhanced Electrical and Electronic Systems

2025-01-8138

04/01/2025

Commercial Vehicle (CV) market is growing rapidly with the advancement of Software-Defined Vehicles (SDVs), which provide greater level of flexibility, efficiency and integration of AI & cutting-edge technology. This research provides an in-depth analysis of E&E architecture of CVs, focusing on the integration of SDV-based technology, which represents the transition from hardware-focused to a more dynamic, software-focused methodology. The research begins with the fundamental concepts of E&E architecture in CVs, including virtualization, centralized computing, feature based ECU, CAN and modular frameworks which are then upgraded to meet various operational and customer requirements. The capacity of SDV-based architecture designs to scale to handle heavy duty commercial vehicles is a primary focus, with an emphasis on ensuring the safety and security, to defend against potential vulnerabilities. Furthermore, the integration of real-time data processing capabilities and advanced E&E

Saini, Vaibhav, Jain, Ayushi, Meduri, Pramoda, Solutions GmbH, Verolt Technology

Performance Evaluation and Thermal Analysis of Various Electric Drives for Automotive Electric Propulsion

14-14-02-0010

03/26/2025

Electric vehicles (EVs) represent a significant stride toward environmental sustainability, offering a multitude of benefits such as the reduction of greenhouse gas emissions and air pollution. Moreover, EVs play a pivotal role in enhancing energy efficiency and mitigating reliance on fossil fuels, which has propelled their global sales to unprecedented heights over the past decade. Therefore, choosing the right electric drive becomes crucially important. The main objective of this article is to compare various conventional and non-conventional electric drives for electric propulsion in terms of electromechanical energy conversion ratio and the thermal response under continuous [at 12 A/mm2 and 6000 rpm] and peak [at 25 A/mm2 and 4000 rpm] operating conditions. The comparative analysis encompasses torque density, power density, torque pulsation, weight, peak and running efficiencies of motor, inverter and traction drive, electromechanical efficiency, and active material cost. This

Patel, Dhruvi Dhairya, Fahimi, Babak, Balsara, Poras T.

Experimental Methodology for Tire Ride Analysis Based on Outdoor Cleat Testing

10-09-03-0023

03/21/2025

Handling and ride comfort optimization are key vehicle design challenges. To analyze vehicle performance and investigate the dynamics of the vehicle and its subcomponents, we rely heavily on robust experimental data. The current article proposes an outdoor cleat test methodology to characterize tire dynamics. Compared to indoor procedures, it provides an effective tire operating environment, including the suspensions and the vehicle chassis motion influence. In addition, it overcomes the main limitation of existing outdoor procedures, the need for dedicated cleat test tracks, by using a set of removable cleats of different sizes. A passenger vehicle was equipped with sensors including an inertial measurement unit, a noncontact vehicle speed sensor, and a wheel force transducer, providing a setup suitable to perform both a handling test routine and the designed cleat procedure, aimed at ride testing and analysis. Thus, the outdoor cleat test data were compared with indoor test

Gravante, Gerardo, Napolitano Dell’Annunziata, Guido, Barbaro, Mario, Farroni, Flavio

Advancing Oil Maintenance Practices: Insights from Viscosity Analysis

2025-01-5019

03/21/2025

There is a lack of data to support the efficacy of traditional mileage and time-based criteria for oil changes in vehicles. In this study, used-oil samples from 63 vehicles were collected and analyzed. Besides dynamic viscosity, viscosity index and activation energy were evaluated as measures of thermal stability of viscosity. The results revealed that mileage and time of use are not significantly correlated with (p > 0.05) and are thus poor indicators of oil viscosity and viscosity thermal stability measures. These findings highlight the limitations of current criteria and underscore the need for new sensing and evaluation methods to reduce costs, waste, and environmental impact while ensuring vehicle performance.

Salvi, Nilesh, Tan, Jinglu

Driver Cognitive Distraction Recognition Based on Multi-Source Data from Simulated Driving Experiments

2025-01-7140

02/21/2025

Nowadays, cognitive distraction in the process of driving has become a frequent phenomenon, which has led to a certain proportion of traffic accidents, causing a lot of property losses and casualties. Since the fact that cognitive distraction is mostly reflected in the driver's reception and thinking of information unrelated to driving, it is difficult to recognize it from the driver's facial features. As a result, the accuracy of prediction is usually lower relying solely on facial performance to detect cognitive distraction. In this research, fifty participants took part in our simulated driving experiment. And each participant conducted the experiment in four different traffic scenarios using a high-fidelity driving simulator, including three cognitive distraction scenarios and one normal driving scenarios. Firstly, we identified the facial performance indicators and vehicle performance indicators that had a significant effect on cognitive distraction through one-way ANOVA. Then we

Qu, Chixiong, Bao, Qiong, Qu, Qikai, Shen, Yongjun

Deep Learning-Enhanced Direct Torque Control of BLDC Motors for Optimized Electric Vehicle Performance

12-08-04-0036

02/12/2025

Electric vehicles (EVs) represent a promising solution to reduce environmental issues and decrease dependency on fossil fuels. The main drawback associated with the direct torque control (DTC) scheme is that it is incapable of improving the efficiency and response time of the EVs. To overcome this problem, integrating deep learning (DL) techniques into DTC offers a valuable solution to enhance the performance of the drive system of EVs. This article introduces three control methods to improve the output for DTC-based BLDC motor drives: a traditional proportional–integral for speed controller (speed PI), a neural network fitting (NNF)-based speed controller (speed NNF), and a custom neural (CN) network-based speed controller (speed CN). The NNF and CN are DL techniques designed to overcome the limitations of conventional PI controllers, such as retaining the percentage overshoot, settling times, and improving the system’s efficiency. The CN controller reduced the torque ripple by 15

Patel, Sandesh, Yadav, Shekhar, Tiwari, Nitesh

Performance Analysis of Conventional Two Wheeler versus Plug in Hybrid Electric Two Wheeler for Light Goods Transportation

2025-28-0199

02/07/2025

The study investigates the performance of conventional two-wheelers versus Plug-in Hybrid Electric Vehicle (PHEV) two-wheelers in the context of light goods transportation. With growing environmental concerns and the push towards sustainable transportation solutions, the study focuses on understanding the effects of using electric or hybrid electric vehicles for small-capacity load carrying applications, in terms of parameters such as mileage, pollution, and range. A simulation model was created in MATLAB, where the various vehicle parameters can be changed and their effect on vehicle performance such as SOC, motor power, motor speed, vs input velocity can be studied. Similar tests were conducted in the real world and the results obtained were compared with simulation results. Results indicate that PHEV two-wheelers significantly reduce emissions and fuel consumption, while maintaining comparable performance in terms of speed and load capacity. However, the initial investment and

Kumar, V. Sudhir, R, Balamurugan, Pasupuleti, Thejasree, Natarajan, Manikandan

Crash Performance Study on High-Speed Electric Two-Wheeler Battery Enclosure

2025-28-0203

02/07/2025

The usage of Electric Vehicles (EVs) and the annual production rate have increased significantly over the years. This is due to the development of rechargeable electrical energy storage system (battery pack), which is the main power source for EVs. Lithium-ion batteries (LIBs) pack is predominantly used across all major vehicle categories such as 2-wheelers, 3-wheelers and light commercial vehicle. LIB is one of the high energy-dense sources of volume. However, LIBs have a challenge to pose a risk of short circuits and battery pack explosions, when exposed to damage scenarios. In the present study, the controlled crash analysis is performed for various velocities ranging from 50 kmph to 72 kmph against an obstruction directly and at an offset from the wheel, so as to mimic the real-world crash of high-speed two-wheelers. The behavior of the battery enclosure is examined through evaluating the structural integrity of the battery enclosure used in a realistic two-wheeler after crash at

Venkatesan Sr, Aiyappan, Nelson, N Rino, Hariharan Nair, Adarsh

Research on Fuel Cell Vehicle Performance Based on PEMFC Stack Degradation

2025-01-7072

01/31/2025

The degradation of vehicle performance resulting from powertrain degradation throughout the lifecycle of alternative energy vehicles (AEVs) has consistently been a focal issue among scholars and consumers. The purpose of this paper is to utilize a one-dimensional vehicle simulation model to analyze the changes in power performance and economy of fuel cell vehicles as the Proton Exchange Membrane Fuel Cell (PEMFC) stack degrades. In this study, a simulation model was developed based on the design parameters and vehicle architecture of a 45kW fuel cell vehicle. The 1D model was validated for accuracy using experimental data. The results indicate that as the stack performance degrades, the attenuation rate of the fuel cell engine is further amplified, with a degradation of up to 13.6% in the system's peak output power at the End of Life (EOL) state after 5000 hours. Furthermore, the level of economic performance degradation of the complete vehicle in the EOL state is dependent on the

Li, You, Du, Jing, Guo, Donglai, Wang, Kai, Wang, Yupeng

Rolling Optimization Shift Strategy of Heavy Truck Considering Power Interruption in Shift Process

2025-01-7036

01/31/2025

The optimization of gear shifting is a critical process in heavy-duty trucks for adjusting engine operating points, enabling a multi-objective balance between power, fuel efficiency, and comfort. However, this process is challenged by the nonlinear characteristics of engine fuel consumption, power interruptions during AMT (Automated Manual Transmission) shifts, and uncertainties in driving conditions. This study proposes a rolling optimization shift strategy for heavy trucks equipped with AMT, based on a multi-scale prediction of internal combustion engine fuel consumption on the road. Firstly, a predictive model for the energy efficiency and dynamics of heavy-duty trucks with AMT was developed, accounting for the engine’s engine’s operating condition points and power interruptions during shifting. Secondly, a future power demand, vehicle speed, and fuel consumption prediction algorithm was designed, iterating based on accelerator pedal position forecasts and dynamic modeling. Finally

Liu, Xingyi, Zhou, Quanyu, Zhang, Leibo, Lv, Dongxuan, Sun, Xiaopeng, Gao, Jinhao, Song, Kang, Xie, Hui

Experimental Study on Vibration Aging Performance of Vehicle Carbon Canisters

2025-01-7030

01/31/2025

Due to the vibration of the vehicle, the performance of the vehicle carbon canisters will be changed, which will affect its control effect on the fuel evaporation emission. In this study, a vibration test platform capable of simulating vehicle vibration characteristics was used to simulate the possible vibration effects of the vehicle carbon canisters, and to analyze the absorption and desorption performance of the carbon canisters before and after long-term operation and its influence on vehicle evaporation emissions. The results show that the carbon canisters will precipitate the carbon powder after the continuous action of the forward and backward vibration of the vehicle. As a result, the ultimate adsorption and desorption amount of fuel vapor decreased, and the adsorption amount decreased more obviously. In the 48-hour Diurnal Breathing Loss (DBL) test, fuel vapor diffusion is more difficult due to the increased flow resistance of the carbon canisters after vibration, and fuel

Yu, Xiaohong, Liu, Yiyao, Feng, Yifang, Zheng, Yushuo, Chen, Tao, Zhao, Hua

Predictive Torque Control of Open End Winding PMSM Under Single Phase Fault with Torque Ripple Suppression

2025-01-7053

01/31/2025

To enhance the operating performance of the common-bus open-winding permanent magnet synchronous motor under single-phase open-circuit faults, this paper proposes a model predictive torque control strategy with torque ripple suppression. First, the operating principles of the model predictive torque control system for both normal operation and single-phase fault conditions are analyzed. Based on this analysis, the electromagnetic torque controller in the model predictive torque control system is restructured. However, if the conventional space vector modulation strategy used during fault-free operation is continued, the required stator voltage cannot be achieved. Therefore, analyze the phase relationship of the current before and after the fault, derive a new Clark transformation matrix, and then based on the principle of torque invariance that can be generated by the fundamental magnetic flux, derive the coefficients of the Park transformation of the two-phase current. To simplify the

Zhang, Dongdong, Mo, Fushen, Lin, Xiaogang

Model Predictive Torque Control of PMSM Without Weighting Factors Based on MRAS Parameter Identification

2025-01-7057

01/31/2025

The design of weighting factors in the cost function of traditional model predictive torque control (MPTC) is relatively cumbersome, at the same time, the accuracy of the prediction model decreases obviously when the motor parameters are mismatched. Therefore, a model predictive control without weighting factors based on on-line identification of motor parameters is studied. Firstly, the control objectives transformed from torque and flux of traditional MPTC to active torque and reactive torque, since they are of the same dimension the design of weighting factors is unnecessary. Secondly, aiming at the problem of control performance degradation caused by the change of motor parameters in the prediction model, the online identification of motor parameters based on model reference adaptive system is studied, the identification results are applied to the prediction process to avoid the bad influence caused by the parameter variation. The findings from the simulation indicate that the

Zhang, Yanqing, Jia, Danyang, Yin, Zhonggang, Liu, Qi

Simulation Analysis of Seat Ventilation Performance Considering Deformation during Human Occupancy

15-18-02-0008

01/02/2025

The comfort of seats increasingly becomes a crucial factor in the overall driving experience, particularly as vehicles become increasingly integrated into people’s daily lives. Passengers often maintain a relatively fixed posture and have close contact with the seat for extended periods of time, leading to issues such as heat, humidity, and stickiness. In order to enhance the thermal comfort experienced by occupants, manufacturers are no longer satisfied with ensuring the thermal comfort performance of vehicles only through the HVAC system in the cabin, but also developed a microclimate control seat that adjusts the temperature through ventilation between the contact surface of the seat and the human body, trying to improve the thermal comfort of passengers more effectively. However, the ventilation ducts of these seats are commonly designed based on empirical or autonomous standards, and their effectiveness is subsequently assessed through test or simulation, typically under unloaded

Zhang, Tianming, Ren, Jindong, Zhang, Haonan

Impact of Replacing a 6-Speed Gearbox with a 5-Speed Gearbox on Vehicle Performance

2024-36-0125

12/20/2024

This study investigates the effects of replacing a 6-speed gearbox with a 5-speed gearbox in a sports vehicle, while keeping all other parameters constant. Through computational simulations, data is collected for comparative performance analysis. The study aims to understand the potential implications of this change on acceleration, fuel efficiency, engine response, as well as aspects such as driver comfort. The results may provide valuable insights for the automotive industry, guiding future transmission design and engineering decisions.

Marinho, Gabriel Jannuzzi, de Campos, Josué Queiroz, Lopes, Elias Dias Rossi, Rodrigues, Gustavo Simão

Assessing Road Load Predictions: A Comprehensive Review and Comparative Analysis of Real-World versus Numerical Simulation

2024-36-0157

12/20/2024

Road loads, encompassing aerodynamic drag, rolling resistance, and gravitational effects, significantly impact vehicle design and performance by influencing factors such as fuel efficiency, handling, and overall driving experience. While traditional coastdown tests are commonly used to measure road loads, they can be influenced by environmental variations and are costly. Consequently, numerical simulations play a pivotal role in predicting and optimizing vehicle performance in a cost-effective manner. This article aims to conduct a literature review on road loads and their effects on vehicle performance, leveraging experimental data from past studies from other researchers to establish correlations between measured road loads and existing mathematical models. By validating these correlations using real-world measurements, this study contributes to refining predictive models used in automotive design and analysis. The simulations in this study, utilizing five distinct empirical

Pereira, Leonardo Pedreira, Braga, Sérgio Leal

Vehicle Dynamics Using Matlab Applied to a 4x4 Vehicle

2024-36-0121

12/20/2024

Terramechanics is a pivotal field for understanding the interaction between a vehicle’s tires and the terrain. Over time, numerous models have been developed to predict the performance of wheeled vehicles across different terrains. This study aims to employ Bekker’s model, which considers the deformable ground and the rigid tire, to simulate the motion of a 4x4 off road vehicle using the Matlab Vehicle Dynamics Blockset. The methodology of this study involves the use of a MatLab Simulink blockset diagram in conjunction with Bekker’s theory to describe the tire’s interaction with the soil. This approach will enable us to obtain the vehicle’s longitudinal dynamics, including position and velocity. The primary goal of this study is to juxtapose the simulated motion with the model provided by Matlab. This comparison will serve to validate Bekker’s theory. By achieving this, we aim to contribute to the body of knowledge in the field of terramechanics and enhance the predictive accuracy of

Duque, Gabriel Leonardo, Uchôa, Lucas Etchells Riley, Lopes, Elias Dias Rossi, Rodrigues, Gustavo Simão

Research on the Pull Drift Compensation Control Algorithm based on Steer-By-Wire Systems

2024-01-7052

12/13/2024

SBW(Steer-by-wire) is a steering system that transmits the driver’s request and gives feedback to the driver through electrical signals. This system eliminates the mechanical connection of the traditional steering system, and can realize the decoupling of the steering wheel and the road wheel. In addition, this system has a perfect torque feedback system, which can accurately and delicately feedback the road surface information to the driver. However, vehicle driving deviation is one of the most common failure modes affecting vehicle performance in the automotive aftermarket, this failure mode can exacerbates tire wear, reducing their life cycle, at the same time, the driver must apply a counter torque to the steering wheel for a long time to maintain straight-line travel during driving. This increases the driver’s operational burden and poses safety hazards to the vehicle’s operation. Based on the steer-by-wire system and vehicle driving deviation characteristics, this paper proposes

Xiangfei, Xu, Qu, Yuan

Real Time Vehicle State Estimation Using Error Map Function

2024-28-0266

12/05/2024

The estimation of vehicle handling and control parameters in dynamic conditions is challenging due to errors and delays in real-time data logging with low-resolution onboard sensors. These issues significantly impact the performance of vehicle stability and control algorithms, particularly in vehicles under testing. This study presents error mapping concept parallel to statistical error method for real-time vehicle state estimation that addresses the limitations of low-resolution sensors with errors and delays in measured signal. In this study, a real-time (RT) model is developed and trained with in-house electric SUV to estimate yaw velocity and slip angle. The model leverages other measured signals available from the vehicle’s onboard sensor setup. It integrates an error and delay function with error predictive model to estimate the targeted parameter signal response in real time. The RT model introduces an error function method that enhances prediction accuracy by combining the

Kumar, Avinash, Asthana, Shivam, Rasal, Shraddhesh, M, Sudhan, Vellandi, Vikraman

An Intelligent Estimation of Dynamic Vehicle Mass for Electric Vehicle

2024-28-0229

12/05/2024

Dynamic Vehicle mass is one of the most critical parameters in automotive controls such as battery management, transmission shift scheduling, distance-to-empty predictions and most importantly, various active and passive safety systems. This work aims to find out dynamic Vehicle mass for Electric Vehicles in real time transient driving conditions. The work proposes a real-time approach in finding Dynamic vehicle mass where accumulated Energy based vehicle performance, an improvement to the vehicle dynamics equation, has been employed for consistent and accurate results. Factors affecting vehicle mass such as road grade, dynamic friction coefficient, driving pattern, wheel slip etc. have been considered for model optimization. Here recursive Bayesian state estimator has been used for finding vehicle mass as a constant state variable while time varying forgetting factors are used to nullify the impact of major losses. Algorithm is auto tuned using Machine Learning techniques to first

Pandey, Suchit, Sarkar, Prasanta, Sawhney, Chandan, Kondhare, Manish, Joshi, Pawan, CH, Sri Ram

An Analytical Method to Study Control Strategy of Torque-Vectoring Transmissions for Electric Vehicles Using MATLAB Simulink

2024-28-0210

12/05/2024

Torque vectoring offers drive flexibility and continuous individual wheel torque regulation, which is unavailable in conventional transmission systems. Electric vehicles with multiple drivetrains and torque-vectoring system can significantly enhance vehicle response and handling, and thus the active safety, efficiency, and performance of the vehicle in all driving conditions. The current methodology of predicting performance characteristics is limited through slip rate calculations and yaw rate calculations. The vehicle dynamic performance evaluations with above said methodologies holds good for dynamic cornering. But in the scenarios where the vehicle moving in straight drive with different wheel traction requirements on either side (split-μ condition) and that requires torque vectoring. These above methods do not help to evaluate the performance of vehicle. Because these methodologies are based on predicting dynamic center-of-gravity values of vehicle. In the proposed methodology

Ramakrishnan, Gowtham Raj, Baheti, Palash

An Experimental Study of Clutch Wear Profile on a Vehicle with Automated Manual Transmission and Simulating the Same on Test Bench for Future Applications

2024-28-0193

12/05/2024

Clutch wear is a significant factor affecting vehicle performance and maintenance costs, and understanding its dynamics is crucial for original equipment manufacturers (OEMs) to enhance product reliability and customer satisfaction. It is important to predict clutch wear to enable customers to understand the condition of their clutch and the remaining clutch life, to avoid sudden vehicle breakdowns. This paper explains the approach of measuring the clutch wear profile on an actual vehicle and simulating the same conditions on a powertrain test bench, with the establishment of a correlation in clutch wear profiles.

Chopra, Chandan, Kumar, Varun, Mamidigumpula, Mohan Kumar Reddy

Investigation on Thermal Performance of Battery Cooling Plate for Lithium-Ion Battery

2024-28-0259

12/05/2024

Electric vehicles are regarded to be the most effective way to lower emissions of greenhouse gases from the transportation industry. Lithium-ion batteries are rechargeable and ideally suited for vehicle electrification due to their high specific energy and energy density in comparison to other batteries. Electric vehicle performance greatly depends on the efficient operation of lithium-ion battery. Battery thermal management plays a crucial role in ensuring optimum vehicle operation. Heat dissipation from the battery should be dealt with, for safe operation and to prolong the battery life cycle. To achieve the battery’s optimal temperature, an efficient cooling system should be established. The battery cooling plate is an essential component that is necessary for heat transfer from the battery pack to the coolant. Five different battery cooling plates with linear dimple, staggered dimple, straight channel, wave channel and splitter channel are modeled for computational fluid dynamics

K, Muthukrishnan, S, Saikrishna, K, Keshavbalaje

Leveraging Welding Spot Quality Control Using Camera Vision System

2024-28-0264

12/05/2024

Spot welds are integral to automotive body construction, influencing vehicle performance and durability. Spot welding ensures structural integrity by creating strong bonds between metal sheets, crucial for maintaining vehicle safety and performance. It is highly compatible with automation, allowing for streamlined production processes and increased efficiency in automotive assembly lines. The number and distribution of spot welds directly impact the vehicle's ability to withstand various loads and stresses, including impacts, vibrations, and torsion. Manufacturers adhere to strict quality control standards to ensure the integrity of spot welds in automotive production. Monitoring spot weld count and weld quality during manufacturing processes through advanced inspection techniques such as Image processing by YOLOv8 helps identify the number of spots and quality that could compromise safety. Automating quality control processes is paramount, and machine vision offers a promising

Kadam, Shubham Narayan, Dolas, Aniket, Mishra, Jagdish

Enhancing Bumper & Headlamp Durability: Lightweight Bumper Design with Optimized Resonance Frequency

2024-28-0238

12/05/2024

In the realm of commercial vehicle design, enhancing the durability of bumpers and headlamps is paramount for ensuring safety and reducing maintenance costs. This study explores the development of a lightweight bumper design with optimized resonance frequency to improve the durability of these critical components. The research focuses on innovative design techniques to achieve a balance between weight reduction and structural integrity. The primary objective is to minimize the impact forces transmitted to the bumper and headlamp assemblies during vibrations. By employing finite element analysis (FEA) and experimental validation, the study identifies the optimal resonance frequency that mitigates the risk of resonance-induced damage. Additionally, the study examines the influence of geometric modifications on the bumper’s performance. Various design iterations are analyzed to determine the most effective configuration for enhancing durability while maintaining compliance with industry

Pandey, Sudheer, Ganesan, Balaji

Dynamic Modeling of Torque & Emissions: Digital Twin to Simulate Combustion Process and Exhaust Emissions for Diagnostics & Prognostics Applications

2024-28-0172

12/05/2024

As a journey to green initiatives, one of the focus areas for automotive industry is reducing environmental impact especially in case of internal combustion engines. Latest digital twin technology enable modelling complicated, fast and unsteady phenomena including the changes of emission gases concentration and output torque observed during diesel emission and combustion process. This paper presents research on the emission and combustion characteristics of a heavy vehicle diesel engine, elaborating an engineered architecture for prognostics/diagnostics, state monitoring, and performance trending of heavy-duty vehicle engine (HDVE) and after treatment system (ATS). The proposed architecture leverages advanced modeling methodologies to ensure precise predictions and diagnostics, using data-driven techniques, the architecture accurately model’s engine and exhaust system behaviors under various operating conditions. For exhaust system, architecture demonstrates encouraging predictive

Singh, Prabhsharn, Thakare, Ujval, Hivarkar, Umesh

Speed Control Assurance for Snowmobiles

J1222_202412 (Current)

12/05/2024

This SAE Standard provides minimum requirements and performance criteria for devices to prevent runaway snowmobiles due to malfunction of the speed control system.

Snowmobile Technical Committee

Methodology for Designing Traction Motor for an Electric Vehicle with Tandem Application of Vehicle System 1D Simulation and Electromagnetic Simulation

2024-28-0226

12/05/2024

This paper presents a comprehensive methodology for sizing an electric motor for a given vehicle performance targets and analyzing the motor performance at different operating zones of the electric vehicle. Designing the powertrain of an electric vehicle starts with understanding the on-road performance requirements of the vehicle relevant to the application such as top speed, gradient and acceleration targets. It is critical to define the operating performance boundary of the vehicle based on end user preference. This paper illustrates a comprehensive approach of implementing 1D simulation tool namely GT-SUITE to simulate the vehicle model for different on-road performance targets so as to conclude the traction motor specifications [3]. These specifications along with the other boundaries of the vehicle such as battery limitations and MCU limitations are taken as input parameters for the electromagnetic simulation assisted by Ansys Motor-CAD to design optimized motor that can meet the

Ghule, Gopal Arjun, Neelakantan, Subramoniyan

Study of Impact Forces on Wheel Rim from Pothole Impacts and Improvement of Flange Design to Eliminate Wheel Bend

2024-28-0262

12/05/2024

Typically, an automotive passenger car wheel rim can withstand gradual loading contributed from the vehicle during cornering and high-speed maneuvering and as per the standard as well as customer requirements wheel has to withstand some impact forced contributed from radial and inclined loading. But in some cased wheel rim may not withstand the impact forces generated during impact on potholes and curbs with high-speed maneuvering. This Study helps to understand the impact on wheel rim and the forces acting on the rim flanges during pothole impact and high-speed curb impact. For In this study author tends to explain about the design of the rim flanges considering the impact forces the wheel rims are exposed to during pothole impact. Also in this study, road load data for a double pothole impact in electric vehicle with lightest alloy wheel rim in the segment is acquired to understand the loads acting on the rim. Based on the simulation iterations with several design changes and

Thiyagarajan, Sriram, Jithendhar, A, Singh, Ram Krishnan, Sundaram, Raghupathi, Paua, Ketan

Complex and Nonlinear Resistance Changes of NMC/Gr Cells during Ageing

2024-01-4325

11/05/2024

Li-ion battery cell degradation has a strong impact on vehicle performance through performance degradation and deviation from original control calibration. Ageing leads to complex changes in resistance, arising from various contributions. This results in non-uniform resistance changes with temperature and state-of-charge (SoC) as well as altered time-based dynamic responses to current application. This study examines in detail the complex resistance changes with ageing and the dependencies on temperature, SoC and time. The paper evaluates data from a 9-month Nickel-Manganese-Cobalt (NMC)/Gr cell aging study at 45°C, using both frequency and time-based methods. Electrochemical Impedance Spectroscopy with Distribution of Relaxation Times is employed for frequency analysis, while time domain data is extracted from monthly Hybrid Pulse Power Characterization tests. The combination of frequency and time based data allows identification of the individual resistance features that change with

Stocker, Richard, Mumtaz, Asim, Lophitis, Neophytos

Novel Approach to Optimize the Ride Handling Performance by Reducing Vehicle Development Time and Cost

2024-28-0043

10/17/2024

The automobile industry strives to develop high-quality vehicles quickly that fulfill the buyer’s needs and stand out within the competition. Full utilization of simulation and Computer-Aided Engineering (CAE) tools can empower quick assessment of different vehicle concepts and setups without building physical models. This research focuses on optimizing vehicle ride and handling performance by utilizing a tuning specifications range. Traditional approaches to refining these aspects involve extensive physical testing, which consumes both time and resources. In contrast, our study introduces a novel methodology leveraging virtual Subjective Rating through driving simulators. This approach aims to significantly reduce tuning time and costs, consequently streamlining overall development expenditures. The core objective is to enhance vehicle ride and handling dynamics, ensuring a superior driving experience for end-users. By meticulously defining and implementing tuning specifications, we

Ganesh, Lingadalu

Artificial Intelligence in Electric Vehicle Battery Management System: A Technique for Better Energy Storage

2024-28-0089

09/19/2024

The automobile industry is currently undergoing a huge transition from IC Engine based systems to electric based mobility systems. Battery technology based on Li ion has made interesting move towards popularization of electric vehicles (EVs) in world market. battery management system (BMS) forms one of the major constituents of this technology. Battery pack as a whole is the most sought-after component of EVs which needs intensive monitoring and control. Battery parameters such as State of Health (SOH) and State of Charge (SOC) needs precise measurement and calculation. Monitoring them directly is a difficult task. In the present work methodologies and approaches for estimating the batteries parameters using Artificial Intelligent methods were investigated. Six machine learning algorithms used for state estimation were critically reviewed. The employed methods are linear, random forest, gradient boost, light gradient boosting (light-GBM), extreme gradient boosting (XGB), and support

Vashist, Devendra, Raj, Rishi, Sharma, Deepanshu

Cabin Heating Modelling and Simulation for ICE and EVs through 1D CAE

2024-28-0107

09/19/2024

India features diverse climatic zones, spanning from tropical in south to alpine in north. Since most of the regions are hot, vehicle cabin cooling analysis dominates over heating analysis, creating a notable technology gap that exists in cabin heating. Nonetheless, in colder regions of India and Europe, maintaining optimal cabin heating is crucial for human comfort. Furthermore, in climates prone to mist and frost formation, ensuring the accuracy and effectiveness of cabin heating mechanisms becomes crucial, as it directly correlates with safety considerations that comes prior to mere comfort requirements. To reduce the technology gap and physical testing in cold climatic conditions this work is proposed, which will enable us to predict cabin heating performance of vehicle on highway running as well as in stationary condition for Electric Vehicles (EV) and Internal Combustion Engine Vehicles (ICEV) in 1D Computer Aided Engineering (CAE) software. A detailed Transient Cabin Heating

Soni, Rahul, Shah, Geet, Kulkarni, Shridhar, M, Chandru, Vangala, Sai Krishna, Jaybhay, Sambhaji, Nayakawadi, Uttam

Method and System for Efficient Thermal Management in Electric Vehicles

2024-28-0060

09/19/2024

Electric Trucks offer one of the most promising alternatives to vehicles in the field of transport of goods. In battery electric trucks, heat is generated by components present in the electric truck such as battery of the electric vehicle, electric drive system, Endurance Brake System etc. which require cooling and Thermal management system to control and monitor the cooling system. The thermal management system considered here includes two coolant tanks. The first coolant tank performs thermal management for the battery and Electric-Drive(e-Drive) components which can heat up to 600C and the second coolant tank performs thermal management for HPR circuit, and it is used to break the charging circuit to protect the battery getting charged beyond 100% using regenerative braking concept. HPR (High performance resistor) is the component which can heat up to ~950C and make sure the battery is not getting charged beyond the safe limits. Since HPR is a critical component and operates at high

Pekala, Sagar Mohana, Zacharias, Nevin, Kulkarni, Krathika

Effect of Undercover Design on Vehicle Performance: An Investigation

2024-28-0062

09/19/2024

This research study investigates the influence of undercover design on three critical aspects of vehicle performance: water entering into air intake filter, Aerodynamic performance, thermal performance on vehicle engine room components (Condenser, Radiator and Air Intake System). Undercover serves the purpose of protecting Engine, underhood components and also improves aerodynamics of the vehicle. Through CFD simulations, various undercover design configurations: Full Undercover, no undercover and half undercover cases are evaluated to assess their effectiveness in mitigating the water ingress into the air intake system. Additionally, we explore the implications of these design alterations on the thermal performance and aerodynamic drag. By systematically exploring these interactions, results provided valuable insights on the effect of three undercover configurations related to vehicle performance which can help automotive engineers to develop the undercovers that strike a balance

Padakandla, Kishore Kumar, Nagendra, K. Yalla, Bisoyi, Ram Prasad

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