To enhance the dynamic performance of distributed-drive vehicles under various driving conditions, a comprehensive vehicle stability control method based on multi-objective optimization is proposed. Initially, the phase-plane stability region is divided using the Routh-Hurwitz stability criterion, followed by the introduction of a method to calculate the stability index based on the vehicle's actual state within this region. Then, based on the dynamics model of a four-wheel hub motor-driven vehicle, a stability control strategy is proposed, and a multi-objective model predictive control (MPC) framework is established with yaw rate, side slip angle, slip ratio, and motor torque as optimization objectives. Furthermore, the stability index and slip ratio deviation are used as inputs to adaptively allocate the weight coefficients of each optimization objective in the MPC model, ultimately determining the optimal additional torque for the four hub motors. Lastly, joint simulations with CarSim and Simulink were performed under double-lane change and step-steering input scenarios. The results show that the proposed multi-objective optimization-based control strategy improves vehicle stability compared to constant-weight strategies and uncontrolled cases, verifying the effectiveness of the proposed torque vectoring controller.
Multi-objective optimization for torque vectoring control in distributed drive vehicles
Fourth International Conference on Mechatronics and Intelligent Control (MIC 2024) ; 2024 ; Nanchang, China
Proc. SPIE ; 13643
27.05.2025
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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