A comparative study of the influence of different open circuit voltage tests on model‐based state of charge estimation for lithium‐ion batteries. (30th March 2021) - Ren, Zhong; Du, Changqing; Wu, Zhongyi; Shao, Jianbo; Deng, Wenjun
Summary: A predetermined relationship between open circuit voltage (OCV) and state of charge (SoC) is the premise of model‐based SoC estimation algorithms. Commonly used OCV tests to obtain the offline OCV‐SoC curves include the low current OCV test and the incremental OCV test. In this paper, in addition to comparing the low current OCV test with the incremental OCV test which applies 0.5 C current‐rate, the incremental OCV tests which apply 0.2, 0.3, and 1 C current‐rates are compared as well. Moreover, from the perspective of test accuracy and test duration, the optimal relaxation time for incremental OCV test is investigated. The recursive least squares method with a forgetting factor (FFRLS) is used to identify the parameters of the battery model, and the adaptive extended Kalman filter (AEKF) is employed to estimate SoC. The results indicate that the SoC estimator which applies the OCV‐SoC curve obtained from the 0.5 C incremental OCV test performs better than other estimators at 25°C and 45°C. But at 0°C, the SoC estimator which applies the OCV‐SoC curve obtained from the 0.2 C incremental OCV test has the best estimation performance. In addition, 3 h relaxation time is the optimal choice at 25°C and 45°C, while 4 h relaxation time is recommended at 0°C. Abstract : The impact of various OCV tests, namely low current OCV test and different current‐rate incremental OCV tests, on SoC estimation performance is comprehensively studied under three ambient temperatures and entire SoC range. The optimal choice of relaxation time for incremental OCV tests is investigated from the perspective of test accuracy and test duration. An FFRLS‐AEKF joint SoC estimation algorithm is proposed to update parameters and estimate SoC online.