A novel charged state prediction method of the lithium ion battery packs based on the composite equivalent modeling and improved splice Kalman filtering algorithm.
(2020)
Journal Article
WANG, S., FERNANDEZ, C., YU, C., FAN, Y., CAO, W. and STROE, D.-I. 2020. A novel charged state prediction method of the lithium ion battery packs based on the composite equivalent modeling and improved splice Kalman filtering algorithm. Journal of power sources [online], 471, article ID 228450. Available from: https://doi.org/10.1016/j.jpowsour.2020.228450
As the unscented Kalman filtering algorithm is sensitive to the battery model and susceptible to the uncertain noise interference, an improved iterate calculation method is proposed to improve the charged state prediction accuracy of the lithium ion... Read More about A novel charged state prediction method of the lithium ion battery packs based on the composite equivalent modeling and improved splice Kalman filtering algorithm..