Advances in Electrochemical Models for Predicting the Cycling Performance of Traction Batteries: Experimental Study on Ni-MH and Simulation

Abstract

Rigorous electrochemical models to simulate the cycling performance of batteries have been successfully developed and reported in the literature. They constitute a very promising approach for State-of-Charge (SoC) estimation based on the physics of the cell with regards to other methods since SoC is an internal parameter of these physical models. However, the computational time needed to solve electrochemical battery models for online applications requires to develop a simplified physics-based battery model. In this work, our goal is to present and validate an advanced 0D-electrochemical model of a Ni-MH cell, as an example. This lumped-parameter model will be used to design an extended Kalman filter to predict the SoC of a Ni-MH pack. It is presented, followed by an extensive experimental study conducted on Ni-MH cells to better understand the mechanisms of physico-chemical phenomena occurring at both electrodes and support the model development. The last part of the paper focuses on the evaluation of the model with regards to experimental results obtained on Ni-MH sealed cells but also on the related commercial HEV battery pack.