Novel reduced-order modeling method combined with three-particle nonlinear transform unscented Kalman filtering for the battery state-of-charge estimation.
(2020)
Journal Article
XU, W., WANG, S., FERNANDEZ, C., YU, C., FAN, Y. and CAO, W. 2020. Novel reduced-order modeling method combined with three-particle nonlinear transform unscented Kalman filtering for the battery state-of-charge estimation. Journal of power electronics [online], 20(6), pages 1541-1549. Available from: https://doi.org/10.1007/s43236-020-00146-z
Accurate estimation of the lithium-ion battery state of charge plays an important role in the real-time monitoring and safety control of batteries. In order to solve the problems that the real-time estimation of the lithium-ion battery is difficult a... Read More about Novel reduced-order modeling method combined with three-particle nonlinear transform unscented Kalman filtering for the battery state-of-charge estimation..