Integrated energy-oriented lateral stability control of a four-wheel-independent-drive electric vehicle

• Published in: Science China. Technological sciences Vol. 62; no. 12; pp. 2170 - 2183
• Main Authors: Liu, JingXing, Zhuang, WeiChao, Zhong, Hong, Wang, LiangMo, Chen, HeJuan, Tan, Chin-An
• Format: Journal Article
• Language: English
• Published: Beijing Science China Press 01.12.2019; Springer Nature B.V
• Subjects: Computer simulation; Control stability; Controllers; Cornering; Decision making; Electric vehicles; Energy consumption; Engineering; Lane changing; Lateral stability; Linear quadratic regulator; Maneuvers; Multiple objective analysis; Optimization; Proportional integral; Stability analysis; Torque; Yaw; four-wheel-independent-drive electric vehicle; energy-oriented; lateral stability; torque allocation
• ISSN: 1674-7321; 1869-1900
• DOI: 10.1007/s11431-019-9672-5

Improving the energy efficiency of an electric vehicle (EV) is an effective approach to extend its driving range. This paper proposes an integrated energy-oriented lateral stability controller (IESC) for a four-wheel independent-drive EV (4WID-EV) to optimize its energy consumption while maintaining vehicular stability during cornering. The IESC is a hierarchical controller with two levels. The high-level decision-making controller determines the virtual control inputs, i.e., the desired additional yaw moment and total wheel torque, while the low-level controller allocates the motor torques according to the virtual control inputs. In the high-level controller, the desired additional yaw moment is first calculated using a linear quadratic regulator (LQR) to minimize the control expenditure. Meanwhile, a stability weighting factor (SWF) based on phase plane analysis is proposed to adjust the additional yaw moment, which can reduce the additional energy consumption caused by the mismatch between the reference model and the actual vehicle. In addition to the yaw moment, the desired total wheel torque is calculated using a proportional-integral (PI) controller to track the desired longitudinal velocity. In the low-level controller, a multi-objective convex-optimization problem is established to optimize the motor torque by minimizing the energy consumption and considering the tire-road frictional limit and motor saturation. A globally optimal solution is obtained by using an active-set method. Finally, double-lane change (DLC) simulations are conducted using CarSim and MATLAB/Simulink. The simulation results demonstrate that the proposed controller achieves great lateral stability control performance and reduces the energy consumption by 5.23% and 2.95% compared with the rule-based control strategy for high- and low-friction DLC maneuvers, respectively.