轮毂电动机驱动车辆并联式复合制动策略  

Parallel compound braking strategy of vehicle driven by wheel motor

作　　者：付翔[1] 肖帅 徐超 FU Xiang;XIAO Shuai;XU Chao(School of Automotive Engineering,Wuhan University of Technology,Wuhan,Hubei 430070,China)

机构地区：[1]武汉理工大学汽车工程学院,湖北武汉430070

出　　处：《江苏大学学报（自然科学版）》2025年第1期9-17,共9页Journal of Jiangsu University：Natural Science Edition

基　　金：国家重点研发计划项目(2022YFC3006005)。

摘　　要：基于并联式轮毂电动机驱动实车构型,分析影响制动能量回收效率的主要因素,采用联邦卡尔曼滤波纵向车速估计算法,提出了三层式复合制动控制策略.该策略中的制动决策层根据踏板输入信号和行驶状态来识别制动工况,并进入相应的制动模式.制动控制层根据制动决策层的指令,在常规制动工况下通过粒子群优化(PSO)算法优化前、后轮电制动力矩分配,实现电池有效回收效率最大化;紧急制动工况下,通过模糊自整定PID算法实现车辆在不同附着路面上各轮滑移率的安全有效控制,优化了制动防抱死控制的鲁棒性,提高制动安全性.制动执行层响应制动控制层的指令,设计了电制动补偿机制,以迅速补偿调节各轮轮缸的压力误差,提高车辆制动稳定性.最后实车验证了该复合控制策略的有效性.Based on the real vehicle configuration driven by parallel hub motor,the main factors affecting the braking energy recovery efficiency were analyzed,and the Federal Kalman filter longitudinal speed estimation algorithm was used to propose the three-layer compound braking control strategy.By the braking decision-making layer,the braking conditions were identified and entered into the corresponding braking mode according to the pedal input and driving state.According to the decision,by the braking control layer,the electric braking torque distribution of the front and rear wheels was optimized through particle swarm optimization(PSO)under conventional braking conditions to maximize the effective battery recovery efficiency.Under emergency braking conditions,the fuzzy self-tuning PID algorithm was used to realize the safe and effective control of the slip rate of each wheel on different adhesion roads,and the robustness of the anti lock braking control was optimized with improved braking safety.The command of the control layer was responded by the braking executive layer,and the electric braking compensation mechanism was designed to quickly compensate and adjust the pressure error of each wheel cylinder for improving the braking stability of the vehicle.The control strategy was verified by the real vehicle.

关 键 词：轮毂电动机驱动车辆 并联式复合制动 粒子群优化 制动能量回收 模糊自整定PID 

分 类 号：U461.3[机械工程—车辆工程]