A decomposed electrode model for real-time anode potential observation of lithium-ion batteries

Abstract

The anode potential inside the lithium-ion battery is crucial for battery internal state observation in electric vehicles since it indicates the states of lithium deposition at the anode surface. Conventional equivalent circuit models (ECMs) used in the battery management system (BMS) can only predict limited battery external characteristics. Electrochemical models which can simulate the battery internal behaviors are too complex for onboard applications. In this paper, a novel decomposed electrode model (DEM) is proposed for real-time anode potential observation in real BMSs. The cathode and anode parameters can be calibrated by inserting a reference electrode inside the battery. The decomposed electrode model shows high accuracy in predicting the cell terminal voltage and the anode potential under various current conditions. This model also has predominance considering both model simplicity and computational efficiency. An online anode potential observation algorithm is developed based on the DEM and the extended Kalman filter. A lithium plating-free fast charging algorithm is formulated further by integrating the closed-loop potential observer and the closed-loop current controller. The result indicates that the proposed decomposed electrode model is suitable for online applications in the BMS. • A novel decomposed electrode model (DEM) of lithium-ion batteries is proposed. • The DEM shows advantages in model accuracy, simplicity, and computing efficiency. • A high precision anode potential observation method is proposed based on the DEM. • A lithium plating-free fast charging algorithm is formulated with a PID controller.