Fuzzy control of electric vehicle compound braking system based on multi-obiective optimization NSGA-II algorithm

In order to improve the braking effect of electric vehicles, multi-objective optimization, and fuzzy control decision-making are used to distribute the braking torque. The Pareto solution set is constructed by multi-objective optimization to distribute the compound braking torque. After determining the optimal solution of the Pareto solution set, the optimal output result is obtained through the ideal solution, and the data is transmitted to the motor and braking structure, so as to ensure that the torque distribution mode meets the actual braking requirements. The results show that adding vehicle braking factors in the decision analysis stage can fully meet the requirements of torque distribution, and realize the transformation from a multi-objective optimization process to a single objective analysis process of optimizing braking stability. Through the simulation test, the control strategy can achieve a higher recovery rate of braking energy, promote the obvious improvement of braking recovery ability under the condition of low-intensity braking, obtain better performance than the single fuzzy control strategy, and achieve the expected braking force distribution effect.