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

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.

Keywords:

Lithium-ion battery , capacity loss , lifetime prediction , cycle-life , operational time