Abstract

Abstract The demand for lithium-ion (Li-ion) batteries is on the rise because of the increase in usage of electric vehicles (EVs) and other electrified applications. The battery management system (BMS) plays an important role in ensuring the safe and reliable operation of the battery. In order for the BMS to function and manage the battery pack effectively, a battery model is needed to monitor and predict the behavior of the battery. The equivalent circuit model (ECM) is widely used in online battery applications such as EVs, due to its simplicity and accuracy. There has been evidence suggesting that the addition of the hysteresis effect to the ECM would improve its accuracy. This paper presents an investigation into the effect of integrating hysteresis into the ECM, for both non-dynamic and dynamic applications. Two models are introduced, the first-order ECM and the first-order ECM with hysteresis (ECMwH). The model parameters are estimated using the Levenberg–Marquardt algorithm and training datasets. The models are then compared in terms of accuracy and computing time, using two driving cycles and a characterization cycle. The results show that the addition of the hysteresis effect to the first-order ECM improves the accuracy of the model in non-dynamic applications more significantly than in dynamic applications. The computing time increases, as expected, for the ECMwH, suggesting that it might not be beneficial to integrate hysteresis to battery models for online applications such as EVs.

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