Electrochemical Model and Sigma Point Kalman Filter Based Online Oriented Battery Model

Abstract

This paper presents a reduced-order electrochemical battery model designed for online implementation of battery control systems. This model is based on porous-electrode and concentratedsolution theory frameworks and is able to predict voltage as well as the internal electrochemical variables of a battery. The reduction of the model leads to a physics-based one-dimensional discrete-time state-space reduced-order model (ROM) especially beneficial for online systems. Models optimized around different operational setpoints are combined in order to predict the cell variables over a wide range of temperature and state of charge (SOC) using the output-blending method. A sigma-point Kalman filter is further used in order to cope with inaccuracies generated by the reduction process and experimental-related issues such as measurement error (noise) on the current and voltage sensors. The state-estimation accuracies are measured against a full-order model (FOM) developed in COMSOL. The whole system is able to track the internal variables of the cell as well as the cell voltage and SOC with very high accuracy, demonstrating its suitability for an online battery control system.