基于二分法查找-伪循环次数法的动力电池健康状态实时预测

针对纯电动汽车动力电池健康状态(SOH)预测过程中算法复杂、编程繁琐、单片机C程序开发困难的问题,以单片机作为主芯片,以电池充放电循环次数为SOH的影响转化为循环次数并将主要影响因素与SOH的非线性关系制成二维数组表,通过二分法查找得到影响程度系数,记录特性因素值及持续时间,获得伪循环次数,进而得到SOH。在国家标准试验条件下验证了该预测方法的有效性、精确性和稳定性。

Real-Time Prediction of Power Battery SOH Based on Dichotomy Searching Pseudo-Cyclic Number Method

In order to solve the problems of complex algorithm, complicated programming and difficulty in developing C program of single chip microcomputer in the process of SOH prediction of pure electric vehicle power batteries, a SOH prediction algorithm is proposed, which uses single chip as the main chip and the number of battery charging and discharging cycles as the benchmark index of SOH. The influence on battery SOH is converted into the number of cycles and the non- linear relationship between the main factors and SOH is made into a two- dimensional array table. The influence degree coefficient is obtained by the binary searching method, the value and duration of characteristic factors are recorded, and the number of pseudo-cycles and SOH are obtained. The validity, accuracy and stability of the prediction method are verified under the national standard test conditions.