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动力电池管理系统设计及SOC实时在线估计方法 被引量:9

Design of power battery management system and real-time SOC online estimation method
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摘要 针对电动汽车动力电池组的管理需求,设计了一款基于MC9S12XEP100和LTC6804的锂电池管理系统,实现对单体电池电压、电流和温度实时监控、电压均衡管理、热管理、充放电管理、数据存储和上位机显示功能。针对电池荷电状态(state of charge,SOC)估算精度和实时性方面的问题,提出了一种新颖的开路电压和安时积分融合型SOC估算方法,有效减小了开路电压处于平台期造成的误差影响。采用Arbin电池测试设备对上述功能和SOC估计方法进行了测试验证。结果显示,电池电压误差小于0.07 V,温度误差小于1℃,SOC估算误差小于1.2%,因此,设计系统可用于实际电动汽车动力电池组管理,实现电池SOC实时在线准确估计。 Aiming at the power battery management requirements of electric vehicle,a lithium battery management system was designed based on MC9S12XEP100 and LTC6804.The system can realize the functions of real-time monitoring of the voltage,current and temperature of the cells,voltage balance management,heat management,charge and discharge management,data storage and host computer display.At the same time,to solve the problems in the estimation accuracy and real-time performance,an innovative SOC real-time estimation method was proposed based on the integration of open-circuit voltage and ampere hour counting method.With the innovative method,the error influence caused by the open circuit voltage in the plateau period decreases effectively.Arbin battery test equipment was used to test and verify the above functions and the SOC estimation method.The results show that the voltage measurement error is less than 0.07 V,the temperature error is less than 1℃,and the SOC estimation error is less than 1.2%.Therefore,the designed system can be applied to the management of electric vehicle battery pack and the accurate online estimation of battery SOC in real time.
作者 刘耿峰 张向文 LIU Gengfeng;ZHANG Xiangwen(School of Electronic Engineering and Automation,Guilin University of Electronic Technology,Guilin Guangxi 541004,China;Guangxi Key Laboratory of Automatic Detecting Technology and Instruments,Guilin University of Electronic Technology,Guilin Guangxi 541004,China)
出处 《电源技术》 CAS 北大核心 2022年第3期329-334,共6页 Chinese Journal of Power Sources
基金 国家自然科学基金项目(51465011) 广西自然科学基金项目(2018GXNSFAA281282) 广西自动检测技术与仪器重点实验室主任基金项目(YQ17110) 桂林电子科技大学研究生教育创新计划资助项目(2021YCXS120)。
关键词 电动汽车 动力电池 电池管理系统 LTC6804-2 SOC估计 electric vehicle power battery battery management system LTC6804-2 SOC estimation
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