Development of Lifetime Prediction Model of Lithium-Ion Battery Based on Minimizing Prediction Errors of Cycling and Operational Time Degradation Using Genetic Algorithm

Abstract

Accurate lifetime prediction of lithium-ion batteries is a great challenge for the researchers and engineers involved in battery applications in electric vehicles and satellites. In this study, a semi-empirical model is introduced to predict the capacity loss of lithium-ion batteries as a function of charge and discharge cycles, operational time, and temperature. The model parameters are obtained by minimizing the prediction errors of experimental capacity loss for each charge/discharge cycle at 25 ^oC, 35 ^oC, and 45 ^oC.The optimum values of the model parameters are obtained using genetic algorithm, one of the optimization tools in Matlab software. The model accurately predicts the capacity loss of lithium-ion battery for more charge and discharge cycles at 25 °C with an average error of 4 %. The mentioned cycles are used only to validate the prediction.