Vehicle Handling Performance Research Articles

Bionic Optimization Design and Fatigue Life Prediction of a Honeycomb-Structured Wheel Hub.

The wheel hub is an important component of the wheel, and a good hub design can significantly improve vehicle handling, stability, and braking performance, ensuring safe driving. This article optimized the hub structure through morphological aspects, where reducing the hub weight contributed to enhanced fuel efficiency and overall vehicle performance. By referencing honeycombed structures, a bionic hub design is numerically simulated using finite element analysis and response surface optimization. The results showed that under the optimization of the response surface analytical model, the maximum stress of the optimized bionic hub was 109.34 MPa, compared to 119.77 MPa for the standard hub, representing an 8.7% reduction in maximum stress. The standard hub weighs 34.02 kg, while the optimized hub weight was reduced to 29.89 kg, a decrease of 12.13%. A fatigue analysis on the optimized hub indicated that at a stress of 109.34 MPa, the minimum load cycles were 4.217 × 105 at the connection point with the half-shaft, meeting the fatigue life requirements for commercial vehicle hubs outlined in the national standard GB/T 5334-2021.

Design and optimization of two-stage controller for three-phase multi-converter/multi-machine electric vehicle

Abstract Electric vehicles (EVs) cut greenhouse gas emissions and our use of non-renewable resources, making them more attractive. EVs have lower fuel and maintenance expenses than internal combustion engine automobiles. This study proposes a multi-converter/Multi‒Machine system with two induction motors (IM) that drive a pure EV’s rear wheels. EV two-stage controllers using a simple Adaline neural network (NN) regulate Field-Oriented regulate of a three-phase IM. To control IM speed, the first controller level is a hybrid proportional–integral (PI) with a robust integral sign of error (RISE) controller. Injection torque is controlled by PI‒adaline NN in the second controller step. The simple Adaline NN improves two-stage controller performance. The Multi-Verse Optimization algorithm found the ideal RISE parameter to improve EV drive system performance. A plug-in EV’s linear speed is controlled by the Electronic Differential Controller (EDC). It uses the driver’s reference speed and steering angle to set each driving wheel’s reference speed. EDC adjusts wheel speeds to enhance traction and stability during cornering, accelerating, and decelerating. Utilizing this information, the EDC can effectively distribute power and torque to the wheels, thereby enhancing vehicle handling and overall performance. Three distinct road scenarios and the designated driving route topology have been used to act and demonstrate the resistive forces that affected the EV while it was traveling down the road. By using Matlab (Simulink), EV’s roadworthiness and efficiency will be evaluated.

Path-tracking control at the limits of handling of a prototype over-actuated autonomous vehicle

Considering the vehicle dynamics at the limits of handling is vital to improve the performance and safety of autonomous vehicles especially in extreme situations. This paper presents the development of a path-tracking controller for an over-actuated autonomous vehicle. The vehicle is an electric prototype equipped with torque vectoring and four-wheel steering, which enable enhanced control of vehicle dynamics. A model predictive controller is proposed taking into account the nonlinearities in vehicle dynamics at the limits of handling as well as the crucial actuator constraints. The controller is examined in both high-fidelity simulation and practical testing to validate the vehicle's handling performance. Both the simulation and testing results illustrate that the over-actuation topology can enhance the handling performance as well as vehicle stability at conditions close to the limits of handling. With additional references such as side slip angle, the vehicle's attitude under such extreme condition can also be manipulated. The testing also demonstrates the real-time capability of the controller. Further testing has been done to confirm that side slip angle reference plays an important role in path-tracking control at the limits of handling, and to push the vehicle to the friction limits.

Multiobjective optimization framework for designing a steering system considering structural features and full vehicle dynamics

Vehicle handling and stability performance and ride comfort is normally assessed through standard field test procedures, which are time consuming and expensive. However, the rapid development of digital technologies in the automotive industry have enabled to properly model and simulate the full-vehicle dynamics, thus drastically reducing design and manufacturing times and costs while enhancing the performance, safety, and longevity of vehicle systems. This paper focus on a computationally efficient multi-objective optimization framework for developing an optimal design of a vehicle steering system, which is carried out by coupling certain computer-aided design tools (CAD) and computer-aided engineering (CAE) software. The 3D CAD model of the steering system is made using SolidWorks, the Finite Element Analysis (FEA) is modelled using Ansys Workbench, while the multibody kinematic and dynamic is analysed using Adams/Car. They are embedded in a multidisciplinary optimization design framework (modeFrontier) with the aim of determining the optimal hardpoint locations of the suspension and steering systems. This is achieved by minimizing the Ackermann error and toe angle deviations, together with the volume, mass, and maximum stresses of the rack-and-pinion steering mechanism. This enhances the vehicle stability, safety, manoeuvrability, and passengers’ comfort, extends the vehicle systems reliability and fatigue life, while reducing the tire wear. The method has been successfully applied to different driving scenarios and vehicle maneuvers to find the optimal Pareto front and analyse the performance and behaviour of the steering system. Results show that the design of the steering system can be significantly improved using this approach.

Aerodynamics and Drag of a Car

According to Chinese economic development and human life improvement, the vehicle, as the most important transportation, goes into common people’s life gradually. The following problems of energy are highlighted day by day. In Chinese Manufacturing 2025, the idea of energy-saving and new energy vehicle was pointed out as an important development area, and energy-saving and emission reduction had already been the core work content for Original Equipment Manufacturers. Aerodynamic performance has great influence to vehicle handling performance, power performance, fuel and economy. The external flow filed character better or not will all impact vehicle comfort performance directly. Therefore, OEMs paid more and more attention to vehicle aerodynamic simulation analysis. Reasonable aerodynamic performance plays an important role in improving the performance of vehicle dynamics, economy and so on. Therefore, how to meet the requirements of modeling, engineering at the same time, but also to improve aerodynamic characteristics is particularly important for design a car. This paper discusses the factors that affect the air resistance of the car.

Assessment of Vehicle Handling Performance of Drivers Using Machine Learning Algorithms

Reliable assessment of an individual’s driving skills is very important. The growing population of unskilled drivers will result in disastrous and fatal road accidents. Current situation demands better and accurate automated assessment technique for driver performance. This research aims to development a portable independent assessment system which can be installed in any vehicle. This system will monitor and understand the driver’s skills based on the data from sensors and access their performance using machine learning algorithm. Machine learning based classifiers with more than 90% accuracy are developed for classifying the driver skills. This proposed system will ensure one from possibilities of beaching the formal process and getting the license without qualification, it is a suggestion to the conventional method of assessment. This system could help in building better-skilled driver on the road for a healthy road environment.

A Supervisory Control Strategy of Distributed Drive Electric Vehicles for Coordinating Handling, Lateral Stability, and Energy Efficiency

A supervisory control strategy, including dynamic control supervisor, handling-stability controller, energy efficiency controller, and coordinated torque allocator, is proposed for distributed drive electric vehicles to coordinate vehicle handling, lateral stability, and energy economy performance. In the dynamic control supervisor, first, the phase plane analysis is implemented to accurately define the vehicle stability boundary so that the lookup table of bounds can be established for online applications. Subsequently, based on the feedback drive conditions and vehicle states, the identified boundary is dynamically quantified by the designed varying weight factor (VWF) in real time. In the handling-stability controller, a unified yaw rate reference of VWF is developed to simultaneously guarantee vehicle maneuverability and lateral stabilization. Then, a novel integral triple-step method is proposed to calculate the proper direct yaw moment for the desired vehicle motion. In the energy efficiency controller, the interaxle torque distribution map is optimized for optimal vehicle energy economy. In the coordinated torque allocator, a torque increment allocation problem is formulated and optimized to realize the desired forces, meanwhile, based on VWF to minimize energy consumption and tire workload usage. The validations of the proposed strategy are conducted under various maneuvers, yielding comprehensive improvements in terms of vehicle handling, lateral stability, and energy performance.

DESIGN AND ASSESSMENT OF A SPEED-BASED INTEGRATED ACTIVE VEHICLE CONTROLLER FOR LATERAL STABILITY

An integrated active vehicle control system implementing fuzzy-logic control (FLC) is introduced. The system integrates three commercially- available active vehicle control systems, namely, Active Front Steering (AFS), Electronic Stability Control (ESC) and Torque Vectoring System (TVS) aiming at enhancing vehicle handling and cornering stability and rollover prevention. Two different vehicle models were constructed to simulate the dynamic behavior of the system with and without the proposed integration controller, namely, a 14-DOF vehicle dynamic model with nonlinear tire characteristics and a 2DOF bicycle reference model. Last model was utilized to generate controller’s reference values of vehicle’s yaw rate and body side slip angle at a given forward speed and driver’s steering input. Simulation was carried out in the MATLAB/SIMULINK software environment. The effectiveness of the system was investigated applying five different standard cornering test maneuvers at different vehicle forward speeds of 10, 20 and 30m/s. Simulated test maneuvers are: step, J-turn, single lane change (SLC), sine with dwell, (SWD) and fishhook.Results reveal that, for stability enhancement, AFS is most effective at low vehicle speeds with declining efficacy as speed goes up. Both ESC and TVS have been found to be equally effective at moderate to high speeds. In conclusion, an integrated chassis control (ICC) strategy has been proposed that improves vehicle handling and cornering performance across the entire operating range of speed using a forward-speed-based stability criterion to allocate stability control authority and ensure smooth transition of control between the three AFS, ESC, and TVS systems.

Rear-Wheel Steering Control for Enhanced Steady-State and Transient Vehicle Handling Characteristics

This paper presents a rear-wheel steering (RWS) control algorithm to enhance the vehicle handling performance without prior knowledge of tire characteristics. A RWS system is a chassis control module that can effectively improve vehicle maneuverability and stability. Since the tire-road friction coefficient is difficult to obtain in real world application, the proposed RWS control algorithm is designed so that it can be implemented without any tire-road information. The proposed RWS control algorithm consists of steady-state and transient control inputs. The steady-state control input is proportional to the driver's steering input for achieving the desired yaw rate gain. The desired yaw rate gain is obtained through an offline optimization that is aimed to minimize the vehicle lateral velocity. The transient control input consists of feedforward and feedback control inputs. The feedforward input is designed to improve transient responses of the yaw rate. Computer simulation studies have shown that a trade-off relationship between overshoot and response time exists when the RWS control input is a sum of the steady-state and feedforward inputs. To compromise this conflict, a feedback input has been designed. The overshoot can be significantly reduced while the response time is slightly changed via the feedback input. The proposed algorithm has been investigated via computer simulations. The simulation has been conducted for step steer and sine with dwell scenarios under various road friction conditions. The performance of a RWS vehicle was evaluated using objective indices. Simulation results show that the proposed algorithm enhances vehicle handling performance.

Effect of compliant linkages on suspension under load

Abstract. A numerical investigation is performed into the effects of rigid and compliant suspension linkages, respectively, on: the kinematics and handling performance of a lightweight electric vehicle (EV). CAE models of the front and rear suspension systems are first established based on the measured parameters of the target vehicle. The validity of the CAE models is confirmed by comparing the results obtained for the camber angle and kingpin inclination angle with those obtained mathematically using the vector loop method. CAE models are then performed using half-vehicle and whole-vehicle models. Quarter-vehicle simulations are then performed to compare the solutions obtained from the compliance and rigid-body models for the forces acting on the hardpoints of the two suspension systems under pothole impact conditions. Finally, whole-vehicle simulations are conducted using both the rigid-body model and the compliance model to evaluate the handling performance of the EV in impulse steering tests conducted at vehicle speeds of 40, 60 and 80 km h−1, respectively. In general, the results show that the choice of a rigid-body model or a compliance model has a significant effect on the forces computed at some of the hardpoints in the front and rear suspension systems. Furthermore, the rigid-body model predicts a better vehicle body stability following high-speed turns than the compliance model.

Analysis and Prediction of Performance of MR Damper at Different Currents and Control Strategies for Quarter Suspension System of a Roadway Vehicle

Ride comfort and vehicle handling are the two major issues to be dealt in the design of suspension systems of automobiles. With passive systems offering contrariety on these two parameters, the alternative systems are being in study. Magnetorheological (MR) damper, a most feasible semi-active device, is one such alternative, which will offer the advantage of dealing with both these issues overcoming contrariety. In this study, the suspension system of a car using MR damper is analysed at 5 different currents viz., 0A, 0.25A, 0.5A, 0.75A, 1A, using 2DOF quarter car model and 4DOF half car models for ride comfort and handling and the comparisons of these are done with same suspension system equipped with regular passive damper. A MR damper is built-up using MR fluid consisting of carbonyl iron powder and silicone oil added with additive. Further, the characteristic of this damper is established by conducting experiments, which in turn is used to identify the parameters of Spencer model for MR damper. Using Spencer model of MR damper, at 5 different currents, the quarter car and half car models of vehicle suspension system are simulated by implementing a semi-active suspension system for analysing the resulting displacement and acceleration in the car body. The ride comfort and vehicle handling performance of each specific vehicle model with passive suspension system are compared with corresponding skyhook, ground hook and hybrid based semi-active suspension systems. The simulation and analysis are carried out using Matlab/Simulink.

Variable steering ratio control of steer-by-wire vehicle to improve handling performance

To improve vehicle handling performance, a variable steering ratio characteristic for steer-by-wire system is designed. The steering ratio is adjusted by a compensating coefficient according to vehicle longitudinal speed and steering wheel angle. To evaluate the performance of vehicle with variable steering ratio, simulations are conducted based on an objective evaluation index, which consists of quadratic cost functions of vehicle lateral deviation, steering angular speed, vehicle lateral acceleration and roll angle. By using the optimized data from the simulation results, a Takagi-Sugeno fuzzy neural network is designed for the steering ratio control. In order to test and validate the proposed controller, a series of comparison experiments are conducted on a closed-loop driver-vehicle system, including lemniscate curve test and double lane-change test. The results demonstrate that compared with a conventional steering system with fixed steering ratio, the proposed system can not only improve steering agility at low speed and steering stability at high speed, but also reduce driver’s workload in critical driving conditions.

Identification of Tire Force and Moment (F&M) Characteristics That Improve Combined Slip Handling Performance

ABSTRACT Since tires generate the control forces required for the operation of a vehicle, the tire force and moment (F&M) characteristics have to be designed such that the vehicle can easily be kept under driver control under many driving conditions. However, the relationship between F&M characteristics and vehicle handling performance is not well understood for many driving maneuvers. A better understanding of this relationship would thus provide insight into how to improve the matching between tires and vehicles for increased vehicle stability. Building a large number of tires with different characteristics would be too expensive and time consuming, so an investigation using simulations is preferred. However, one problem with simulations is that handling performance cannot be evaluated by a professional driver (subjective metrics), unlike in outdoor tests. A way of evaluating handling performance in simulation through objective metrics is therefore necessary. In this study, the focus is on vehicle handling performance during simultaneous cornering and braking. Desirable F&M metrics were identified using the following process: Handling simulations were validated using instrumented vehicle measurements of handling behavior at outdoor test facilities. An objective handling metric (peak body slip angle) was identified that has high correlation with professional driver ratings (subjective metric) of combined slip handling performance. The objective metric could therefore be used with simulations to predict the professional driver rating. Many virtual tires were generated by changing F&M characteristics of Pacejka tire models. These virtual tires were used in simulations of combined slip handling maneuvers and evaluated for performance using the objective handling metric. By identifying which changes to F&M metrics had high correlation to changes in handling performance, the primary influencing characteristics were determined. These results were also confirmed by looking at the correlation between F&M metrics of actual tires and their subjective ratings.

Integrated Vehicle Dynamics Control Via Torque Vectoring Differential and Electronic Stability Control to Improve Vehicle Handling and Stability Performance

This paper proposed a full vehicle state estimation and developed an integrated chassis control by coordinating electronic stability control (ESC) and torque vectoring differential (TVD) systems to improve vehicle handling and stability in all conditions without any interference. For this purpose, an integrated TVD/ESC chassis system has been modeled in Matlab/Simulink and applied into the vehicle dynamics model of the 2003 Ford Expedition in carsim software. TVD is used to improve handling in routine and steady-state driving conditions and ESC is mainly used as the stability controller for emergency maneuvers or when the TVD cannot improve vehicle handling. By the β−β˙ phase plane, vehicle stable region is determined. Inside the reference region, the handling performance and outside the region the vehicle stability has been in question. In order to control the integrated chassis system, a unified controller with three control layers based on fuzzy control strategy, β−β˙ phase plane, longitudinal slip, and road friction coefficient of each tire is designed in Matlab/Simulink. To detect the control parameters, a state estimator is developed based on unscented Kalman filter (UKF). Bees algorithm (BA) is employed to optimize the fuzzy controller. The performance and robustness of the integrated chassis system and designed controller were conformed through routine and extensive simulations. The simulation results via a co-simulation of MATLAB/Simulink and CarSim indicated that the designed integrated ESC/TVD chassis control system could effectively improve handling and stability in all conditions without any interference between subsystems.

Study of YSC used for all Electric Independent Driving and Braking Electric Vehicle based on Fuzzy PI Control

Vehicle handling and stability performance is the premise of giving full play to the performance advantages of all electric independent driving and braking electric vehicle (abbr. AIDBEV). This paper presents the working principle of yaw stability control (abbr. YSC) used for AIDBEV. The YSC adopts fuzzy PI control algorithm. For verifying the control effect of YSC, a simulation platform based on fifteen degrees of freedom vehicle model is built. The sinusoidal steering with amplitude and period increasing is used for simulation. According to the simulation results, the yaw rate can be controlled near the target value when YSC works, but the vehicle is unstable when YSC does not work. Take front left wheel as an example, the maximum braking torque of EMB is reduced by 372.9Nm, accounting for 58% of the total braking torque, and the working time of EMB is reduced by 0.265s, accounting for 49.53% of total working time. This can provide potentiality to optimize EMB. By coupled brake, IWM can recover energy 18.77kJ. It has certain energy saving effect, too.

NMPC-Based Yaw Stability Control by Active Front Wheel Steering

This paper proposes a nonlinear model predictive control (NMPC) method for active front steering (AFS) system to improve vehicle handling and stability performance at handling limits. Nonlinear vehicle and tire models are adopted in this proposed NMPC controller to describe the nonlinear dynamics of vehicle and tire. In addition, the nonlinear optimal problem is solved by nonlinear solver in MATLAB optimization toolbox. Finally, this study explores the effectiveness of the NMPC system through sine and double lane change maneuver. Results corroborate that the proposed NMPC system can enhance the yaw stability at the handling limits.

Integrated Dynamics Control and Energy Efficiency Optimization for Overactuated Electric Vehicles

AbstractA large number of studies have been conducted on the dynamics control of electric vehicles or on the optimization of their energy efficiency but few studies have looked at both of these together. In this study, an integrated dynamics control and energy efficiency optimization strategy is proposed for overactuated electric vehicles, where the control of both longitudinal and lateral dynamics is dealt with while the energy efficiency is optimized. First, considering the trade‐off between control performance and energy efficiency, criteria are defined to categorize the vehicle motion status as linear pure longitudinal motion and non‐linear motion or turning motion. Then different optimization targets are developed for different motion status. For the pure linear longitudinal motion and cornering motion, the energy efficiency and vehicle dynamics performance are equally important and a trade‐off control performance between them needs to be achieved. For the non‐linear turning motion, vehicle handling and stability performance are the primary concerns, and energy efficiency is a secondary target. Based on the defined targets, the desired longitudinal and lateral tyre forces and yaw moment are then optimally distributed to the wheel driving and steering torques. Finally numerical simulations are used to verify the effectiveness of the proposed strategies. The simulation results show that the proposed strategies can provide good dynamics control performance with less energy consumption.

A dynamic stability control for electric narrow tilting three wheeled vehicle using integrated multivariable controller

Narrow tilting three wheeled (NTTW) vehicle is an upcoming smart transportation system which is a viable alternative to four and two wheelers for personal mobility. It combines positive aspects of a car and a motorcycle. It outperforms conventional cars on the aspects of consumption of less space in traffic and in parking. However, its realization offers certain challenges in order to make it safe, comfortable and acceptable to the consumers.In this paper, a detailed nonlinear seven degrees of freedom mathematical model for an electric NTTW vehicle has been developed. The NTTW vehicle model captures the chassis dynamics of NTTW vehicle along longitudinal, lateral and tilt motions. The NTTW vehicle is considered to have two driven front wheels housed with in-wheel hub motors and one non-driven rear wheel. The vehicle is assumed to be equipped with a tilting actuator to lean the vehicle body and steer-by-wire mechanism to steer the front wheels. Two integrated controllers each consisting of two separate control schemes, first for lateral-tilt dynamics and the second for longitudinal dynamics are designed. The prime objective is to achieve the desired trajectory of the driver while maintaining vehicle stability. A baseline controller strategy is first designed with PID control technique. Thereafter, a multi variable controller strategy using a state feedback approach is implemented. A comparison is made on their respective performances by means of simulating the vehicle model in various operating conditions. These studies and simulations show improved vehicle handling and stability performances with proposed novel strategy.

Analysis of MR Damper for Quarter and Half Car Suspension Systems of a Roadway Vehicle

Magnetorheological (MR) dampers are evolving as one of the most promising devices for semi-active vibration control of various dynamic systems. In this paper, the suspension system of a car using MR damper is analysed for 2DOF quarter car and 4DOF half car models and then compared with corresponding suspension system using passive damper for ride comfort and handling. Magnetorheological damper is fabricated using a MR fluid of Carbonyl iron powder and Silicone oil added with additive. Experiments are conducted to establish the behaviour of the MR damper and are used to validate Spencer model for MR damper. Further, using the validated Spencer model of MR damper, the quarter car and half car models of Vehicle Suspension system are simulated by implementing a semi-active suspension system for analysing the resulting displacement and acceleration in the car body. The ride comfort and vehicle handling performance of each specific vehicle model with passive suspension system are compared with corresponding semi-active suspension system. The simulation and analysis are carried out using MATLAB/SIMULINK.

Adaptive optimal control for integrated active front steering and direct yaw moment based on approximate dynamic programming

In this paper, a novel adaptive optimal control algorithm based on approximate dynamic programming (ADP) approach is proposed for integrated active front steering (AFS) and direct yaw moment control (DYC). The corrective yaw moment and active steering angle are generated online without knowing system dynamics, which is realised by using a neural network (NN) identifier to identify the unknown system dynamics and a critic NN to calculate the optimal control action, respectively. Control commands are executed via active steering angle on front wheels and proper brake torque distribution on the effective wheels. Computer simulations under three different driving manoeuvres, i.e., lane change manoeuvre, step steer manoeuvre and sine with dwell manoeuvre, are carried out to evaluate the proposed control method. Simulation results show that the proposed ADP-based control method demonstrates improved tracking performance in terms of enhancing vehicle handling and stability performance when encountering the varying longitudinal velocity, the uncertain cornering stiffness and the different road/tyre friction coefficients. Model-free and self-adaptive properties of the proposed method provide a new solution to vehicle stability controller design instead of the commonly used model-based methods.