Adaptive Piecewise Equivalent Circuit Model With SOC/SOH Estimation Based on Extended Kalman Filter

Battery modelling plays a critical role in battery management tasks. A model that provides accurate estimations of state of charge and state of heath in varying operating conditions could significantly improve the performance of battery management systems. Departing from existing literature, this paper presents a self-adaptive Piecewise Equivalent Circuit Model (PECM) based on Extended Kalman Filter (EKF). While traditional Equivalent Circuit Models (ECM) are typically parameterized and validated for a specific range of working conditions (temperature, current and etc.), PECM is able to adapt itself to any working condition in real time. Established in the form of a combination of linear and nonlinear piecewise functions, the model parameters are continuously adjusted based on the measurement of voltage, current, and temperature. Another advantage of PECM is it does not require any prior tests in the lab, for example the Open Circuit Voltage (OCV) test which is time consuming and needs to be calibrated when aged. PECM is accurate, flexible and efficient. It has been validated for different battery chemistries, duty cycles, and temperatures. Furthermore, PECM comes with the State of Charge (SOC) and State of Health (SOH) estimation, which is shown in the model validation process and the degradation study. The results demonstrate that the piecewise parameter adaptation proposed in this paper can be applied to a range of different battery chemistries and at different aged states.