A novel joint estimation method of state of charge and state of health based on the strong tracking-dual adaptive extended Kalman filter algorithm for the electric vehicle lithium-ion batteries.
(2021)
Journal Article
XIONG, R., WANG, S., FERNANDEZ, C., YU, C., FAN, Y., CAO, W. and JIANG, C. 2021. A novel joint estimation method of state of charge and state of health based on the strong tracking-dual adaptive extended Kalman filter algorithm for the electric vehicle lithium-ion batteries. International journal of electrochemical science [online], 16(11), article 211114. Available from: https://doi.org/10.20964/2021.11.18
In order to enhance the efficiency of electric vehicle lithium-ion batteries, accurate estimation of the battery state is essential. To solve the problems of system noise statistical uncertainty and battery model inaccuracy when using the extended Ka... Read More about A novel joint estimation method of state of charge and state of health based on the strong tracking-dual adaptive extended Kalman filter algorithm for the electric vehicle lithium-ion batteries..