Diagnostic Analysis and Research on Battery Health Status of Electric Vehicles

Abstract

With the rapid development of electric vehicles, the attenuation problem of high-specific energy lithium-ion batteries has been paid more and more attention. Its health state is the core parameter of durability management, which is crucial to prolong battery life and improve system reliability. Aiming at the safety and power performance of power battery in the operation of electric vehicles, the kalman filter method was combined with battery charge-discharge curve identification, and the battery health (SOH) diagnosis method based on online testing platform was proposed. The results show that the battery health state can be estimated by the change of internal resistance of the battery model, and the absolute error is not more than 3%, and with the improvement of the model accuracy, the estimation of the battery health state becomes more accurate.