摘要
制动能量回收系统能够将动能转化为电能存储到电池中,从而有效提高电动汽车的续驶里程,然而频繁的制动会引起电池的频繁充电.电池寿命与其工作的外部环境有直接关系,如充放电倍率,电池剩余电量及工作温度.单纯的制动能量回收并没有考虑回馈制动的时间点,时间长度和制动强度给电池寿命带来的影响,而这些都是影响电池老化的不可忽略的因素.电动汽车制动过程具有电机制动和液压制动两种制动模式,本文针对制动工况,对四轮轮毂电动汽车建立了制动模式下的能耗模型和电池寿命模型,设计了电机/液压制动模式协调优化控制器,旨在同时兼顾电动汽车的能量回收与电池寿命的损耗.基于AMESim/Simulink联合仿真平台对制动能量回收给电池寿命带来的影响进行了仿真分析,并对所提出的控制策略进行了仿真验证,与未考虑电池寿命的策略进行了对比,最后对不同的初始电池荷电状态和不同的制动强度对优化的影响进行了分析.
The braking energy recovery system can convert kinetic energy into electrical energy and store it in the battery, which effectively improves the driving range of the electric vehicle. However, the frequent braking will cause the frequent charging of the battery. The external work environment of the battery, such as the charge and discharge rates, the battery state of charge(SOC), and the work temperature are directly related to the battery life. The simple braking energy recovery system does not consider the impact of the regenerative braking time point and length and the braking strength on the battery aging, which shouldn’t be ignored. There are two braking modes in electric vehicle braking process: motor braking mode and hydraulic braking mode. In this paper, the energy consumption and recovery model and battery life depletion model of the braking process are established for the four in-wheel motors electric vehicle, a coordination and optimization controller of the two braking modes is designed to take into account both the energy recovery and the battery life. Based on AMESim/Simulink co-simulation platform, the simulations are carried out to analyse the impact of braking energy recovery on battery life first, then the proposed control method is verified compared with the strategy without considering battery life, finally the effects of the initial battery SOC and different braking strengths for the optimization are simulated and analyzed.
作者
徐薇
陈虹
赵海艳
XU Wei;CHEN Hong;ZHAO Hai-yan(State Key Laboratory of Automotive Simulation and Control,Jilin University,Changchun Jilin 130025,China;College of Communication Engineering,Jilin University,Changchun Jilin 130025,China;Clean Energy Automotive Engineering Center,Tongji University,Shanghai 201804,China)
出处
《控制理论与应用》
EI
CAS
CSCD
北大核心
2019年第11期1942-1951,共10页
Control Theory & Applications
基金
国家自然科学基金项目(61790564,U1664257,U1564207)
省校共建项目(SXGJSF2017–2–1–1)资助~~
关键词
电动汽车
制动能量优化
电池寿命
力矩分配
electric vehicles
braking energy optimization
battery life
torque distribution
