Model-Based Estimation of Lithium Concentrations and Temperature in Batteries Using Soft-Constrained Dual Unscented Kalman Filtering
Stefano Marelli, Matteo Corno
Abstract
This brief proposes an electrochemical model-based estimator of the Lithium-ion (Li-ion) concentration and temperature of a Li-ion cell. The use of the electrochemical approach allows for the estimation of the spatial distribution of lithium concentration and temperature. The estimation is based on a soft-constrained dual unscented Kalman filter (DUKF) designed on the pseudo-2-D model of a Li-ion cell. The dual structure, along with parallelization, reduces the computational complexity, whereas the soft-constraint improves convergence. A simulation analysis validates the approach showing bulk state of charge (SoC) estimation error lower than 1.5%, solid-phase lithium concentration estimation errors of less than 4%, and temperature estimation errors within 0.2 °C from the true value in any point of the cell.