This paper presents a robust fuzzy $H_{\infty }$ control strategy for improving vehicle lateral stability and handling performance through integration of direct yaw moment control system (DYC) and active front steering. Since vehicle lateral dynamics possesses inherent nonlinearities, the main objective is dedicated to deal with the nonlinear challenge in vehicle lateral dynamics by applying Takagi-Sugeno (T-S) fuzzy modeling approach. First, the nonlinear Brush tire dynamics and the nonlinear functions of longitudinal velocity are represented via a T-S fuzzy modeling technique, and vehicle parametric uncertainties are handled by the norm-bounded uncertainties. An uncertain nonlinear vehicle lateral dynamic T-S fuzzy model is then obtained with multi-fuzzy-rules. The resulting robust fuzzy $H_{\infty }$ state-feedback controller is designed with the parallel-distributed compensation strategy and premise variables, and solved via a set of linear matrix inequalities derived from Lyapunov asymptotic stability and quadratic $H_{\infty }$ performance. Simulations for two different maneuvers are implemented with a high-fidelity, CarSimⓇ, full-vehicle model to verify the effectiveness of the developed approach. It is confirmed from the results that the proposed controller can effectively preserve vehicle lateral stability and enhance yaw handling performance.

Improving Vehicle Handling Stability Based on Combined AFS and DYC System via Robust Takagi-Sugeno Fuzzy Control

This study presents an integrated multi-objective controller for electric vehicles ( EVs) to achieve four main control objectives concurrently, i.e. slip control in traction and braking, lateral st...

Model Predictive Control for integrated lateral stability, traction/braking control, and rollover prevention of electric vehicles

For four wheel independent motor-drive electric vehicle, the vehicle longitudinal and lateral motion can be controlled by distributing the driving and regenerative braking torques of four wheel motors. To meet the driving command of driver and keep the vehicle lateral stability, a hierarchical control system is proposed in this paper. In the upper layer, a nonlinear model predictive control is implemented to solve the nonlinear multiinput multioutput, over-actuated problem. The controller is based on a nonlinear three degree-of-freedom model with nonlinear tire model, considering wheel slips as virtual control input. In the lower layer, the wheel slips are manipulated by a PID controller for generating driving and regenerative braking torques of the independent motors. This proposed controller is tested in a hardware-in-the-loop system with four typical maneuvers, which are constant velocity, accelerating, decelerating, and low road adhesion coefficient situations to show different driver command. The results show that the driver command of longitudinal and lateral motion control are both satisfied.

Coordinated Longitudinal and Lateral Motion Control for Four Wheel Independent Motor-Drive Electric Vehicle

Torque optimization control for electric vehicles with four in-wheel motors equipped with regenerative braking system

Four wheel independently driven (4WID) electric vehicles are promising vehicle architectures. However, the complex coordination control of the four driving motors and the operation reliability of the vehicle are challenges. In this paper, to address the multimotor coordinate operation against the actuator faults in the 4WID system, combining the adaptive sliding mode (ASM) control and the fault-tolerant (FT) control allocation, an adaptive sliding mode fault-tolerant coordination (ASM-FTC) control is proposed. First, a new vehicle dynamic model with a driving motor fault is set up. In the control layer, an adaptive variable exponential reaching law is used in the ASM to alleviate the chattering and improve the reaching speed, precision, and robustness. Then, the FTC allocation based on the quadratic programming is designed to properly coordinate the four in-wheel motors at the presentation of the motor fault. To verify the proposed control method, a 4WID electric vehicle platform is set up. Simulation and experimental results demonstrate the effectiveness of the ASM-FTC control.

Adaptive Sliding Mode Fault-Tolerant Coordination Control for Four-Wheel Independently Driven Electric Vehicles

MPC-based yaw stability control in in-wheel-motored EV via active front steering and motor torque distribution

Nonlinear MPC-based slip control for electric vehicles with vehicle safety constraints

To improve the vehicle stability of an electric vehicle with four in-wheel motors, an integrated control scheme with active front wheel steering and direct yaw moment is proposed using a triple-step nonlinear method. The method handles the nonlinear tire characteristics explicitly and actualizes a decoupling control for the considered two-input two-output nonlinear system, in the sense that the closed-loop error dynamics evolve independently. The design procedure is formalized as a triple-step deduction, and the derived controller consists of three parts: steady-state-like control, feedforward control considering reference variations, and state-dependent error feedback control. Finally, the designed controller is evaluated in a realistic seven DOF vehicle model and results are satisfying.

Integrated control of in-wheel motor electric vehicles using a triple-step nonlinear method

To improve the vehicle stability of an electric vehicle (EV) with four in-wheel motors, the authors investigate the use of a non-linear control allocation scheme based on model predictive control (MPC) for EVs. Such a strategy is useful in yaw stabilisation of the vehicle. The proposed allocation strategy allows a modularisation of the control task, such that an upper level control system specifies a desired yaw moment to work on the EVs, while the control allocation is used to determine control inputs for four driving motors by commanding appropriate wheel slips. To avoid unintended side effects, skidding or discomforting the driver in critical driving condition, the MPC method, which permits us to consider constraints of actuating motors and slip ratio, is proposed to deal with this challenging problem. An analytical approach for the proposed controller is given and applied to evaluate the handing and stability of EVs. The experimental results show that the designed MPC allocation algorithm for motor torque has better performance in real time, and the control performance can be guaranteed in the real-time environment.

https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/iet-cta.2015.0437

Bingtao Ren

Papers

MPC-based yaw stability control in in-wheel-motored EV via active front steering and motor torque distribution

Torque optimization control for electric vehicles with four in-wheel motors equipped with regenerative braking system

Nonlinear MPC-based slip control for electric vehicles with vehicle safety constraints

Integrated control of in-wheel motor electric vehicles using a triple-step nonlinear method

Model predictive control allocation for stability improvement of four-wheel drive electric vehicles in critical driving condition