Handling Stability Performance Research Articles

Design of Active Posture Controller for Trailing-Arm Vehicle: Improving Path-Following and Handling Stability

To address the question of which posture trailing-arm vehicles (TAVs) should be adopted while driving, this study introduces an innovative active posture controller (APC) to improve both path-following and handling stability performance. Leveraging a nonlinear tire model that considers corner load variation and wheel camber, alongside the kinematics and double-track model of TAVs, the impact of vehicle body posture on handling performance has been investigated. To fully utilize the four-wheel independent drive and posture adjustable characteristics of the TAV mechanisms, an integrated nonlinear model predictive control (NMPC) combining APC and tire forces distribution is devised. Through simulations conducted using Simulink-Multibody (2023a), the effectiveness of the proposed controller is demonstrated, particularly when compared to the scheme that does not account for the unique posture adjustment mechanisms of TAVs.

Coordinated Longitudinal and Lateral Motion Control for Distributed Drive Electric Vehicles With Mechanical Elastic Wheels

The distributed drive electric vehicle (DDEV) with active front wheel steering is an over-actuated system. For such a system, more optimization targets should be considered to make the system better in addition to meeting the driving command of drivers and keeping the vehicle stable. The slip energy generated by excessive tire slipping reduces the utilization of the output energy of the motor, resulting in a reduction of electric vehicle mileage. In order to improve the vehicle performance, a coordinated longitudinal and lateral controller is designed for DDEV with mechanical elastic wheels (MEWs). The motion control layer of the hierarchical controller adopts the integral sliding mode control (ISMC) to determine the desired longitudinal force, lateral force and yaw moment as virtual inputs of the vehicle. Then, a novel tire force distribution strategy is proposed to dynamically assign the virtual inputs among front wheels and four motors with the goal of optimizing the vehicle stability and longitudinal tire slip energy dissipation. To characterize tire slip energy more accurately, the brush model matching MEW is deduced in the combined slip conditions. The proposed controller is evaluated on the hardware-in-the-loop (HIL) test platform under different driving conditions. Simulation results demonstrate that this controller not only ensures the vehicle handling stability performance, but also improves the utilization of motor output energy and reduces tire wear.

Multi-objective optimization design of magnetorheological damper and vehicle handling stability performance research

Due to the characteristics of smart material magnetorheological (MR) fluid, such as short response time and large controllable range, semi-active suspension based on MR fluid has been widely used. In order to improve the steering stability of vehicles, a semi-active suspension with tapered flow mode MR was proposed. The magnetic circuit of the proposed structure was designed, its dynamic model was established, and the finite element simulation analysis was carried out. By establishing the optimization objectives and constraints, the MR damper was optimized by NSGA-II and MOST algorithms. The vehicle dynamics model with MR damper was established, and the vehicle dynamics simulation was carried out under the control system based on the vehicle dynamics simulation software CarSim-Simulink before and after optimization. The results show that the NSGA-II optimized MR damper can reduce vehicle roll and significantly improve vehicle handling stability. This paper provides a new idea for improving vehicle handling stability by optimizing the MR damper.

Two-level optimal torque distribution for handling stability control of a four hub-motor independent-drive electric vehicle under various adhesion conditions

In order to increase the handling stability performance of the four hub-motor independent-drive electric vehicle (4MIDEV) under various road conditions such as joint and bisectional road, this paper present an effective two-level optimal torque distribution control method. This method can calculate torque command to each hub-motor according to the desired longitudinal force and desired extra yaw moment. The first level allocation control algorithm has small calculation cost and fast response, and can achieve the maximum stability margin of vehicle under good road adhesion condition. Because the adhesion coefficients of each wheel are different, the weight coefficient of objective function is adjusted in real time in the second level allocation control strategy, so as to ensure the vehicle’s handling stability under various adhesion conditions, especially when four wheels have different road adhesion coefficients. Finally, the actual torque of the hub-motor is adjusted according to the slip rate by the sliding mode controller. The proposed distribution strategy is verified in CarSim-Matlab/Simulink joint simulation platform and hardware in the loop verification platform. Through double lane shift simulation on joint and bisectional road conditions, compared to the “general control” strategy, it is verified that the proposed distribution strategy can reduce the error of yaw rate and sideslip angle up to 47.1% and 50.3% compare to the general controller, and the calculation cost is reduced so that effectively improve the handling stability and real-time performance when facing different roads.

Multi-objective optimization design of hydropneumatic suspension with gas–oil emulsion for ride comfort and handling stability of an articulated dumper truck

This article presents the ride comfort and handling stability performance of an articulated dumper truck (ADT). Considering the influence of the hydropneumatic suspension (HPS) with gas–oil emulsion on the ADT, a comprehensive ADT dynamic model is proposed. Also, on the basis of the nonlinear programming quadratic line (NLPQL) algorithm, an integrated multi-objective optimization method regarding the HPS with gas–oil emulsion is proposed to improve the comfort and stability and ensure enough suspension working space. The body acceleration, roll angle and pitch angle of HPS are optimized to a higher degree by 17.2%, 18.4% and 23% (with no load) and 18.3%, 17.7% and 23.1% (with full load) under random excitation input. The simulation results show that the NLPQL optimization method not only increases the ride comfort and handling stability performance of ADT with reasonable suspension working space, but also helps to guide the design of the ADT’s HPS system.

Deep reinforcement learning based direct torque control strategy for distributed drive electric vehicles considering active safety and energy saving performance

Distributed drive electric vehicles are regarded as a broadly promising transportation tool owing to their convenience and maneuverability. However, reasonable and efficient allocation of torque demand to four wheels is a challenging task. In this paper, a deep reinforcement learning-based torque distribution strategy is proposed to guarantee the active safety and energy conservation. The torque distribution task is explicitly formulated as a Markov decision process, in which the vehicle dynamic characteristics can be approximated. The actor-critic networks are utilized to approximate the action value and policy functions for a better control effect. To guarantee continuous torque output and further stabilize the learning process, a twin delayed deep deterministic policy gradient algorithm is deployed. The motor efficiency is incorporated into the cumulative reward to reduce the energy consumption. The results of double lane change demonstrate that the proposed strategy results in better handling stability performance. In addition, it can improve the vehicle transient response and eliminate the static deviation in the step steering maneuver test. For typical steering maneuvers, the proposed direct torque distribution strategy significantly improves the average motor efficiency and reduces the energy loss by 5.25%–10.51%. Finally, a hardware-in-loop experiment was implemented to validate the real-time executability of the proposed torque distribution strategy. This study provides a foundation for the practical application of intelligent safety control algorithms in future vehicles.

Multi-Objective Lightweight Optimization of Parameterized Suspension Components Based on NSGA-II Algorithm Coupling with Surrogate Model

In order to reduce the negative effect of lightweighting of suspension components on vehicle dynamic performance, the control arm and torsion beam widely used in front and rear suspensions were taken as research objects for studying the lightweight design method of suspension components. Mesh morphing technology was employed to define design variables. Meanwhile, the rigid–flexible coupling vehicle model with flexible control arm and torsion beam was built for vehicle dynamic simulations. The total weight of control arm and torsion beam was taken as optimization objective, as well as ride comfort and handling stability performance indexes. In addition, the fatigue life, stiffness, and modal frequency of control arm and torsion beam were taken as the constraints. Then, Kriging model and NSGA-II were adopted to perform the multi-objective optimization of control arm and torsion beam for determining the lightweight scheme. By comparing the optimized and original design, it indicates that the weight of the optimized control arm and torsion beam are reduced 0.505 kg and 1.189 kg, respectively, while structural performance and vehicle performance satisfy the design requirement. The proposed multi-objective optimization method achieves a remarkable mass reduction, and proves to be feasible and effective for lightweight design of suspension components.

Simulation Analysis of Vehicle Handling Stability Based on Trucksim

Based on the Trucksim simulation platform and referring to the parameters of the real vehicle, the vehicle body model, tire model, powertrain model, steering system model and braking system model was constructed. After the parametric modeling of the whole vehicle, the steering wheel angle step test was selected for simulation verification referring to the standards of automobile handling stability test in China. Besides, the vehicle handling stability was analyzed with changing part of the vehicle structure parameters. The research result shows that, although the response forms of vehicle motion parameters are different, they all indicate that the faster the vehicle speed is, the more obvious the vibration of vehicle parameter curve will be, and the vehicle handling stability performance will decrease accordingly. In the steering wheel angle step test, by changing the height of the vehicle’s center of mass and the front and rear wheelbases, it can be explained that reducing the height of the vehicle’s center of mass and increasing the wheelbase can improve the handling stability of the vehicle.

Advanced Estimation Techniques for Vehicle System Dynamic State: A Survey.

In order to improve handling stability performance and active safety of a ground vehicle, a large number of advanced vehicle dynamics control systems—such as the direct yaw control system and active front steering system, and in particular the advanced driver assistance systems—towards connected and automated driving vehicles have recently been developed and applied. However, the practical effects and potential performance of vehicle active safety dynamics control systems heavily depend on real-time knowledge of fundamental vehicle state information, which is difficult to measure directly in a standard car because of both technical and economic reasons. This paper presents a comprehensive technical survey of the development and recent research advances in vehicle system dynamic state estimation. Different aspects of estimation strategies and methodologies in recent literature are classified into two main categories—the model-based estimation approach and the data-driven-based estimation approach. Each category is further divided into several sub-categories from the perspectives of estimation-oriented vehicle models, estimations, sensor configurations, and involved estimation techniques. The principal features of the most popular methodologies are summarized, and the pros and cons of these methodologies are also highlighted and discussed. Finally, future research directions in this field are provided.

Improving Handling Stability Performance of Four-Wheel Steering Vehicle Based on the H2/H∞ Robust Control

Considering the demand for vehicle stability control and the existence of uncertainties in the four-wheel steering (4WS) system, the mixed H2/H∞ robust control methodology of the 4WS system is proposed. Firstly, the linear 2DOF vehicle model, the nonlinear 8DOF vehicle model, the driver model, and the rear wheel electrohydraulic system model were constructed. Secondly, based on the yaw rate tracking strategy, the mixed H2/H∞ controller was designed with the optimized weighting functions to guarantee system performance, robustness, and the robust stability of the 4WS vehicle stability control system. The H∞ method was applied to minimize the effects of modeling uncertainties, sensor noise, and external disturbances on the system outputs, and the H2 method was used to ensure system performance. Finally, numerical simulations based on Matlab/Simulink and hardware-in-the-loop experiments were performed with the proposed control strategy to identify its performance. The simulation and experimental results indicate that the handling stability of the 4WS vehicle is improved by the H2/H∞ controller and that the 4WS system with the H2/H∞ controller has better handling stability and robustness than those of the H∞ controller and the proportional controller.

Electronic Stability Control for Improving Stability for an Eight In‐Wheel Motor‐Independent Drive Electric Vehicle

An electronic stability control (ESC) based on torque distribution is proposed for an eight in‐wheel motor‐independent drive electric vehicle (8WIDEV). The proposed ESC is extremely suitable for the independent driving vehicle to enhance its handling stability performance. The vehicle model is established based on a prototype 8WIDEV. A hierarchical control strategy, which includes a reference state generation controller, an upper‐level vehicle controller, and a lower‐level optimal control allocation controller, is utilized in the ESC. The reference state generation controller is used to obtain the ideal reference vehicle state. The upper‐level vehicle controller is structured based on sliding mode control, which obtains the generalized objective force during 8WIDEV movement, therein considering the side slip angle and yaw rate. The lower‐level optimal control allocation controller attempts to allocate the vehicle’s objective force in each motor optimally and reasonably. The model is validated by field measurement results under the step input condition and snake input condition. Simulation results from a hardware‐in‐the‐loop (HIL) simulation platform indicate that the ESC based on the optimized allocation proposed for 8WIDEV achieves better stability performance compared with direct yaw moment control (DYC).

Optimized Handling Stability Control Strategy for a Four In-Wheel Motor Independent-Drive Electric Vehicle

An optimized handling stability control strategy is put forward aiming at enhancing a four in-wheel independent-drive motors electric vehicle (4WIDEV) performance capable of handling and stability. The optimized control strategy is designed by a hierarchical control structure, which mainly includes vehicle motion controller and vehicle torque distribution controller. Lateral stability controller, in-vehicle motion controller, which yields the generalized force and generalized yaw moment required of the vehicle, is designed into two modes: an instability control mode and a continuous control mode, which mode is activated determining by stability judgment controller based on phase portraits of sideslip angle and yaw rate. When the vehicle state exceeds the stability envelope region, instability control mode based on envelope control is utilized by sliding mode control method, simultaneously controlling the two-vehicle states variables, whereas continuous control mode is performed with adaptive adjustment of the weight parameter according to pre-defined stability degree. The lateral stability controller with adaptive switching two modes exhibits excellent handling stability performance under normal driving conditions, especially under critical conditions, such as on low tire-road adhesion coefficient. The vehicle torque distribution controller assigns driving or regenerative braking torque to four wheels reasonably and efficiently to satisfy the generalized force and the generalize yaw moment acquired by the vehicle motion controller, which synchronously considers the motor output capability and tire friction ellipse constraints while maintains each wheel slip ratio within the stable range. The results in co-simulation experiments based on Carsim and MATLAB/Simulink verify the proposed control strategy, compared with other control strategies, and demonstrate the effective improvement 4WIDEV’s performance in terms of handling stability especially under critical conditions.

Nonlinear Predictive Sliding Mode Control for Active Suspension System

An active suspension system is important in meeting the requirements of the ride comfort and handling stability for vehicles. In this work, a nonlinear model of active suspension system and a corresponding nonlinear robust predictive sliding mode control are established for the control problem of active suspension. Firstly, a seven‐degree‐of‐freedom active suspension model is established considering the nonlinear effects of springs and dampers; and secondly, the dynamic model is expanded in the time domain, and the corresponding predictive sliding mode control is established. The uncertainties in the controller are approximated by the fuzzy logic system, and the adaptive controller reduces the approximation error to increase the robustness of the control system. Finally, the simulation results show that the ride comfort and handling stability performance of the active suspension system is better than that of the passive suspension system and the Skyhook active suspension. Thus, the system can obviously improve the shock absorption performance of vehicles.

Lateral stability region conservativeness estimation and torque distribution for FWIA electric vehicle steering

Estimation of the lateral stability region and torque distribution on steering is very important to improve stability in lateral handling for all wheel drive electric vehicles. Based on the built-nonlinear vehicle dynamic model, the lateral stability region of the vehicle related to steering is estimated using Lyapunov function. We obtained stable equilibrium points of non-straight driving according to the estimated lateral stability region and also reconstructed the Lyapunov function matrix, which proved that the closed-loop system composed of yaw rate and lateral velocity is satisfied with negative definite property. In addition, the designed controller dynamically allocates the drive torque in terms of the vertical load and slip rate of the four wheels. The simulation results show that the estimated lateral stability region and the designed controller are satisfactory in handling stability performance against different roads and vehicle parameters.

The Analysis of Amphibious Vehicle Handling Stability Based on ADAMS/Car

In this paper, a multi-body dynamics model of amphibious vehicle is established in terms of dynamic simulative software ADAMS/Car. The front and rear suspension system are studied and analyzed respectively. The handling stability performance of front suspension is simulated under step steering input, pulse steering input, steady turning, and meandered test in related to specifications. According to the simulation results, the handling stability of amphibious vehicle is evaluated objectively.

Handling Stability Performance Simulation and Analysis of Three Different Vehicle Models

In order to obtain accurate vehicle handling stability performance, 2 DOF nonlinear vehicle model and multi-body dynamics vehicle model are established. Selecting the same vehicle parameters, step steering angle input simulations of three vehicle model (include 2DOF linear vehicle model) are carried out under the same driving conditions, simulation results are analyzed and compared. The simulation results show that 2DOF linear model can characterize the steering states of vehicle when vehicle lateral acceleration is small, but when vehicle lateral acceleration is big, Nonlinear vehicle model and multi-body dynamics model is accurate.

The Design and Performance Analysis of Multi-Axle Dynamic Steering System

In order to improve vehicle steering performance, Multi-axle dynamic steering technology is put forward. Because of simple and low cost, the mechanical dynamic steering mechanism is suitable for heavy vehicle. In order to design ideal steering mechanism, the principle of dynamic steering mechanism was analyzed. Based on theories of multi-axle dynamic steering and vehicle dynamic, the steering angle relationships of different axles were analyzed. Taken a vehicle as an example, the corresponding steering mechanism was designed. Full vehicle model was established and handling stability performance was simulated. The results show that the mechanical dynamic steering vehicle can effectively improve vehicle agility performance at low speed and stability at high speed.