| 引用本文: | 张元星,李 斌,颜湘武,等.基于电池模型的电动汽车充电故障监测与预警方法[J].电力系统保护与控制,2021,49(10):143-154.[点击复制] |
| ZHANG Yuanxing,LI Bin,YAN Xiangwu,et al.Monitoring and early warning method of EV charging failure based on a battery model[J].Power System Protection and Control,2021,49(10):143-154[点击复制] |
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| 摘要: |
| 随着我国电动汽车的规模化发展，电动汽车充电过程中的故障监测与预警得到业内人士的重视。针对这些问题，提出了一种基于电池模型的电动汽车充电故障监测与预警方法。通过动力电池模型荷电状态和电池电动势在线估计，实时调节电池荷电状态和电压以及温度等参数以模拟动力电池充电响应，可以模拟不同类型、规格以及参数的动力电池。在充电过程中，利用CAN总线监听技术，接收并解析充电机与电池的充电信息，将电池模型模拟的充电响应信息与电池的充电状态信息进行对比，同时将充电机的充电状态信息与电池充电需求信息进行对比，来判断充电过程是否正常。当判断出现充电异常或故障时，及时发出故障预警信号。该方法可以识别包括BMS功能失效在内的10余种故障类型。实际充电数据验证了充电正常和异常情况下故障监测方法的可行性。 |
| 关键词: 电池模型 电动汽车 CAN总线监听 充电故障 监测与预警 |
| DOI：DOI: 10.19783/j.cnki.pspc.200684 |
| 投稿时间：2020-06-15修订日期：2020-09-06 |
| 基金项目:国家电网有限公司科技项目资助“电动汽车充放电故障智能诊断与安全预警关键技术及运维服务体系研究”(5418-201918159A-0-0-00) |
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| Monitoring and early warning method of EV charging failure based on a battery model |
| ZHANG Yuanxing1,LI Bin1,YAN Xiangwu2,WANG Ling2,JIANG Linru1,DIAO Xiaohong1,LI Taoyong1 |
| (1. Beijing Electric Vehicle Charging/Battery Swap Engineering and Technology Research Center, China Electric Power Research
Institute Co., Ltd., Beijing 100192, China; 2. North China Electric Power University (Baoding), Baoding 071003, China) |
| Abstract: |
| With the large-scale development of electric vehicles in China, fault monitoring and early warning of electric vehicles during the charging process have received attention. This paper proposes a method for monitoring and early warning of electric vehicle charging faults based on a battery model. Through online estimation of the state of charge of the power battery model and battery electromotive force, parameters such as battery state of charge, voltage, and temperature can be adjusted in real time to simulate the charging response of the power battery, and can simulate power batteries of different types, specifications, and parameters. During the charging process, CAN bus monitoring technology is used to receive and analyze the charging information of the charger and battery. The charging response information simulated by the battery model is compared with the battery charging state information, and the charging state information of the charger is compared with the battery charging demand information to determine whether the charging process is normal. When it is judged that there is an abnormal charging or fault, a fault early warning signal is sent in good time. This method can identify more than 10 types of fault, including the failure of the BMS function. The actual charging data is used to verify the feasibility of the fault monitoring method under normal and abnormal charging conditions.
This work is supported by the Science and Technology of State Grid Corporation of China “Research on Key Technologies and Operation Maintenance Service System of EV Charging/Discharging Fault Intelligent Diagnosis and Safety Warning” (No. 5418-201918159A-0-0-00). |
| Key words: battery model electric vehicle CAN bus monitoring charging failure monitoring and early warning |
