A novel estimation of state of charge for the lithium-ion battery in electric vehicle without open circuit voltage experiment

The estimation of the state-of-charge(SOC) based on equivalent circuit model(ECMs) for the lithium-ion battery has been widely adopted. The relationship between the open-circuit voltage(OCV) and the SOC is essential for the ECMs, which is commonly obtained through the incremental OCV(IO) test or the low-current OCV(LO) test and requires a long experimental time. Meanwhile, the SOC is usually defined as the ratio of the remaining capacity to the nominal capacity, which reduces the accuracy of SOC estimation owing to the change of the available capacity under actual conditions. In this paper, the recursive least square with forgetting factor(FFRLS) is applied to identify the parameters including the OCV values based on the Thevenin model. Afterwards, the differential equations of the OCV and available capacity with respect to time are established, respectively. And then an adaptive extended Kalman filter(AEKF) is used to identify the OCV and available capacity. The estimated OCV and available capacity are input to a second AEKF for SOC estimation, and neither IO nor LO test is required. The proposed method is verified by experiments. The results indicate that the estimated SOC presents high accuracy and good robustness to the noises and different initial SOC values at different temperatures.