Online Self-Seeking Optimal Traction Control for Dual-Mode Coupling Drive Electric Vehicles on Bisectional Slopes

Considering the power requiment of electric vehicles on bisectional slopes and reducing the demand for drive motors performance, a study on online self-seeking traction control is conducted based on the dual-mode coupling drive system (DMCS) with both centralized and distributed drive functions. At first, the traction control mechanism of the DMCS on a bisectional road was analyzed, and the configuration superiority to improve vehicle trafficability was proved. Then, a new online self-seeking optimal traction control strategy with variable-
$\beta $
sliding mode extreme value search algorithm (
$\beta $
_SES) was proposed. At last, the feasibility and superiority of the DMCS on improving the vehicle dynamics performance under the proposed control strategy are verified by the simulation and test. The results also show that, without considering the influence of tire parameters, the proposed traction control strategy can effectively suppress the steady-state fluctuations of the sliding mode extreme value search algorithm (SES) and improve the search speed. The study provides a theoretical basis for better traction control based on the DMCS.