Accurate State of Charge Estimation for Lithium Iron Phosphate Battery Cell Using Equivalent Circuit Model, Parameter Tuning and Unscented Kalman Filter

For an Electric Vehicle (EV), knowing the range capability before the next recharge session is dependent on the accuracy of the State of Charge (SOC) estimation. SOC is simply a measure of the amount of extractable charge from a battery cell or pack. Being a hidden state of a nonlinear dynamic system, SOC cannot be directly measured but must be accurately and precisely estimated. Many literatures have been synthesized to understand the methods for estimating battery state of charge in various use cases. However, there are scarcely any thorough reports. Hence, in this paper, we comprehensively investigate the employment of the unscented Kalman filter with a realistic battery equivalent circuit model. A battery model is designed, and the parameters are estimated by model correlation with experimental data. The results showed convergence of the simulated SOC estimate to the real SOC. We therefore make understandable, the state-of-the art technique that should be employed by Battery Management System (BMS) developers in performing an important battery management functionality – SOC estimation.