Least squares support vector machine based lithium battery capacity prediction

The capacity character of lithium-ion battery is one of the most important performance parameters, which need to be accurate measurement for the safety and efficiency usage. In this paper, the regularity that battery capacity parameter changes with working temperature and charge or discharge rate has been analyzed, and the least squares support vector machine based battery capacity prediction method has been proposed for LiFePO₄ battery. Furthermore, the lithium-ion battery capacity estimation experiments are carried out for both charging and discharging process, and the related results illustrate that the proposed method is able to give an accurate and efficient estimation of the corresponding battery capacity parameter in the presumed range of working temperature and charge or discharge rate.