Research on residual life prediction method of lithium ion battery for pure electric vehicle

Abstract

To overcome the complexity of the lithium-ion battery inside the chemical reaction resulting in a low battery life remaining prediction accuracy, the paper proposes a new electric vehicle lithium ion battery remaining life prediction method based on a correlation vector machine. According to the operating characteristics of lithium-ion batteries in electric vehicles, this method selects health factors that affect battery life, and selects related factors. According to the marginal likelihood function, the factor weights are integrated to obtain the health factor sequence target. Relevance vector machine is used to optimise and evaluate the characteristics of health factors, and complete the prediction of electric vehicle lithium-ion battery capacity and remaining battery life. Comparative experiments show that the prediction effect and stability of the method in this paper are better, and the minimum prediction error is only 0.013.

Study on voltage consistency characteristics of lithium-ion battery energy storage system

“…The production process is not completely parallel and the batteries' decay rate is different during working, which can easily lead to inconsistent performance of the battery [5]. The inconsistency of the battery pack is mainly evaluated by the difference in capacity, state of charge (SOC), and internal resistance between cells.…”