FSEC电动赛车锂离子动力电池状态估计及均衡控制

发布时间：2018-01-16 07:27

本文关键词：FSEC电动赛车锂离子动力电池状态估计及均衡控制　出处：《哈尔滨工业大学》2016年硕士论文　论文类型：学位论文

【摘要】：随着国家新能源产业的长足进步,中国大学生电动方程式大赛的参与度日益提升,对电动赛车的整体性能要求也不断提升。而电池管理系统的发展滞后一直是电动汽车性能提升的瓶颈。通过对CSG-HRT15E用钴酸锂电池的综合性能开展研究,设计一套适用于钴酸锂电池的管理系统,实现对电池状态实时监测并在必要情况下介入电池组进行均衡管理,使电池组在实际工况中的可靠性得到有效提升。本文选用钴酸锂电池作为探究对象,围绕电池外特性进行一定的研究,通过多次实验以获得电池开路电压特性,在不同SOC(State of charge)阶段下的回弹电压的研究,辨识出了电池在不同SOC阶段下的二阶戴维南电池模型参数。并通过MATLAB仿真模拟电池在模拟实际工况下的电压变化情况,验证了拟合参数的可靠性。将无迹卡尔曼滤波与电池模型相匹配对电池SOC实施在线估算,为解决无迹卡尔曼滤波在运行过程中出现的协方差非正定问题,引入平方根无迹卡尔曼滤波以增强滤波器的强健性。在复杂工况下对电池SOC进行估算,结果表明,基于较高精度的电池模型,平方根无迹卡尔曼滤波的拟合精度较为理想,估算精度误差小于1.5%。将反激式变压器作为均衡拓扑核心结构,通过Or CAD软件对均衡电路进行调试验证。将电池SOC值确定为均衡判据,根据电池实际工况制定电池组充放电后期均衡策略,利用MATLAB/Simulink对均衡系统及均衡策略进行仿真调试。对于多种均衡环境,以反激式变压器为核心的均衡结构结合基于电池确定的均衡判据能够有效预防电池过度充放,提高电池工作效率。设计电池管理系统的软硬件,选用HRT14YL01作为电池管理系统的主控模块,该模块主要完成对电池组总电压、总电流的检测,对电池SOC的估算以及各模块的CAN通信。设计包含电池组温度、单体电压实时监测以及电池组内单体间均衡的从控模块,同时完成对系统的软件设计。
[Abstract]:With the rapid progress of the national new energy industry, the participation of Chinese university students in the electric equation competition is increasing day by day. The development of battery management system has been the bottleneck of the performance improvement of electric vehicles. Through the comprehensive performance of lithium cobalt battery used in CSG-HRT15E. Exhibition research. A management system suitable for lithium cobalt battery is designed to realize the real-time monitoring of the battery status and the balanced management of the battery pack if necessary. In order to improve the reliability of battery pack in actual working conditions, this paper selects lithium cobalt battery as the research object, carries on certain research around the battery external characteristic, obtains the battery open circuit voltage characteristic through many experiments. The study of springback voltage under different SOC(State of charge stages. The parameters of the second-order Davinan battery model under different SOC stages were identified, and the voltage variation of the battery under simulated conditions was simulated by MATLAB simulation. The reliability of fitting parameters is verified. The unscented Kalman filter is matched with the battery model to estimate the battery SOC online to solve the problem of non-positive covariance of unscented Kalman filter. Square root unscented Kalman filter is introduced to enhance the robustness of the filter. The battery SOC is estimated under complex conditions. The results show that the battery model is based on high accuracy. The square root unscented Kalman filter has an ideal fitting accuracy, and the error of estimation accuracy is less than 1.5. The flyback transformer is regarded as the core structure of the equalization topology. The equalization circuit is debugged and verified by or CAD software. The SOC value of the battery is determined as the equalization criterion. According to the actual condition of the battery, the later equalization strategy of the battery pack charge and discharge is worked out. The equalization system and strategy are simulated and debugged by MATLAB/Simulink. The equalization structure based on flyback transformer combined with the equalization criterion determined by battery can effectively prevent battery overcharging and improve battery working efficiency and design the hardware and software of battery management system. HRT14YL01 is selected as the main control module of the battery management system, which mainly completes the detection of the total voltage and current of the battery pack. The design includes battery temperature, cell voltage real-time monitoring and slave control module with equalization between the cells. At the same time, the software design of the system is completed.
【学位授予单位】：哈尔滨工业大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：U469.72

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