A Direct Yaw Moment Control Framework Through Robust T-S Fuzzy Approach Considering Vehicle Stability Margin

The direct yaw moment control system of distributed drive electric vehicles provides a flexible control scheme to enhance the vehicle stability through four independently driven in-wheel motors. However, the vehicle nonlinearities may lead to the invalidation of control. To this end, a Takagi–Sugeno (T-S) fuzzy-based robust H∞ control method is proposed to ensure the vehicle performance while addressing the nonlinear challenge. First, thanks to the T-S fuzzy modeling technology, the tire nonlinear characteristics are described by fuzzy rules, based on which the vehicle lateral dynamics model is established. Next, the safety region represented by the tire slip angles phase plane is presented to evaluate the vehicle stability performance. Considering the control priority of vehicle handling performance and stability control with different stability margins, a multiobjective optimization function is transformed into a standard robust performance optimization problem with dynamic weight coefficients. A T-S fuzzy-based robust H∞ state feedback controller is then designed to ensure the system stability and H∞ performance. Finally, the hardware-in-the-loop tests are conducted to validate the proposed controller. Comparative results show the effectiveness to improve the vehicle handling performance while ensuring the stability.

I. Introduction

The electric vehicle has attracted more attention due to its advantages of reducing the energy consumption and traffic noise [1], [2], [3]. Distributed drive electric vehicles (DDEVs) with four independent in-wheel motor torque inputs provide an effective approach to enhance the vehicle stability through the direct yaw moment control (DYC), and are regarded as a promising chassis architecture in the future [4], [5]. The studies and experiments in [6] proved that the DYC can modulate the vehicle steering characteristics, thereby improving the stability in extreme driving conditions. In recent years, combining DYC with other vehicle active safety systems [e.g., active front-wheel steering (AFS)] is also a hot topic to pursue better performance [7], [8], [9], [10], such as driving comfort and stability during collision avoidance [11]. However, the vehicle enters an unstable state and behaves with nonlinear characteristics when the tire force approaches the saturation value. It poses a great challenge to vehicle dynamics modeling and control.