Optimal coordinated control of active steering and direct yaw moment for distributed-driven electric vehicles. (May 2023)

• Record Type: Journal Article
• Authors: Dong, Jiachen; Li, Jianqiu; Gao, Qinhe; Hu, Jiayi; Liu, Zhihao
• Is Part Of: Control engineering practice. Volume 134(2023)
• Publication Date: 2023-05
• Subjects: Distributed-driven vehicle -- Over-actuated system -- Coordinated control -- Optimal allocation; Automatic control -- Periodicals; 629.89
• DOI: 10.1016/j.conengprac.2023.105486
• Languages: English
• ISSNs: 0967-0661

Abstract

Abstract: This paper considers the problem of optimal coordination of active steering and direct yaw moment for general electric vehicles equipped with in-wheel motors and steer-by-wire devices. As a typical over-actuated system, vehicle planar motion shows flexible control performance under different wheel actuations, thus achieving the optimal integration among them is of critical significance. Based on the modeling from wheel actuations of motor torques and wheel angles to vehicle planar motion states, this paper proposes an optimal hierarchical control framework composed of a reference state generator, a linear time-varying model predictive controller (LTV-MPC), and an optimal control allocator. Motor torques and wheel angles are decoupled as equivalent distributed variables by linearization technique. Then an optimal allocation framework is formed towards the trade-off between driving security and power saving, and a compensation module based on the back-propagation neural network (BPNN) is designed to guarantee the control allocation accuracy. Holistic multi-objective optimization is demonstrated through Co-simulations with Matlab/Simulink and TruckSim. Results verify the effectiveness of the proposed control strategy. Highlights: LTV-MPC based hierarchical control framework is proposed for an n -axle distributed-driven electric vehicle. Active steering and direct yaw moment are integrated through the optimal coordination of distributed wheel actuations. Multi-objective optimization towards the tradeoff between tire force utilization and motor power consumption is realized.