基于模糊算法的纯电动汽车制动能量回收

为提高纯电动汽车再生制动能量回收率,采用以总制动力需求、车速以及电池SOC为输入,以电机制动力系数为输出的mamdani型模糊控制器,确定电机制动力与机械制动力之间的比例分配;同时考虑汽车制动的安全性和稳定性,提出了采用理想制动力分配方法对前、后轮制动力进行分配.在ADVISOR上建立了模糊控制算法的仿真模型,并结合典型道路工况CYC_UDDS进行仿真,通过与ADVISOR自带的策略以及文献7]提出的模糊控制策略的仿真结果进行对比,结果表明：采用改进的模糊控制算法后,电池SOC提高了2%,制动能量回收效率提高了33.7%,整车系统的效率提高了3.1%,表明文中提出的改进的模糊控制算法能提高纯电动汽车制动能量回收的效果,有效延长纯电动汽车的续航里程.

Pure electric vehicle braking energy recovery based on fuzzy algorithm

In order to improve the braking energy recovery effect of pure electric vehicle, the paper used a mamdani＇s fuzzy logic controller which has four inputs including requirement of braking force, vehicle speed, batteries SOC and one output which was the electric braking force coefficient, to determine the proportion distribution between electric braking force and mechanical braking force. Meanwhile, based on the safety of vehicle braking and stability, we used the ideal brake force distribution method to distribute the front and rear wheel braking force in the paper. The model based on fuzzy logic control strategy was established on the ADVISOR, and combined with the typical driving cycle CYC_UDDS to simulate. By comparing the simulation results of the ADVISOR own strategy and the seventh literature proposed fuzzy control strategy, the results showed that： with fuzzy logic control strategy, the battery SOC increased by 2%, the regenerative braking efficiency raised by 33.7%, and the overall vehicle system efficiency raised by 3.1%, which indicated that the fuzzy control strategy can improve the pure electric vehicle braking energy recovery effect and prolong the pure electric vehicle mileage.