大数据技术在动力电池异常监控中的应用

新能源电动汽车其安全性一直困扰着行业与市场的发展,传统电池管理系统(BMS)储及计算能力不足,难以实 现动力电池的异常状态预测,基于车联网数据,搭建了大数据监控与管理平台,提出了动力电池热失控关键算法,并实现 了算法的平台集成与应用。应用结果表明,此系统应用能够有效评估和预测动力电池潜在安全风险,并能及时有效地指 导安全处置,从而降低整车安全事故发生概率。

Application of Big Data in Abnormal Monitoring of Power Battery

The safety of new energy electric vehicles has always plagued the development of the industry and the market. The traditional battery management system ( BMS) has insufficient storage and computing capabilities, and it is difficult to predict the abnormal state of the power battery. This paper builds big data platform based on the data of the Internet of Vehicles. The management platform puts forward key algorithms for thermal runaway and health of power batteries, and realizes platform integration and application of algorithms. The application results show that the application of this system can effectively evaluate and predict the potential safety risks of power batteries, and can effectively guide safe disposal in time, thereby reducing the probability of vehicle safety accidents.