State Of Charge Estimation Algorithm Of Lithium Battery Based On Fractional-Order Model

Nowadays,with the increase of energy consumption and demand,battery has become an emerging research field.Battery is the main energy storage equipment for solar energy,wind energy,water energy and other new energy.Basically,in this era of big data building the energy Internet,batteries are everywhere,and the design and control of batteries to ensure energy supply is a top concern for researchers around the world.State of Charge(SOC)is a score representing the remaining charge of the battery,and is the most important indicator of the battery.The design and control of the battery cannot be separated from the accurate estimation of the SOC of the battery.And in battery research,the hottest is battery.Based on the Extended Kalman Filter(EKF)algorithm,the Fractional Order Multiple Innovation Adaptive Extended Kalman Filter(FO-MIAEFK)is proposed in this paper.The joint algorithm of FO-MIAEKF and Recursive Least Square with a variable forgetting factor(VFFRLS)is a more accurate and less likely to be disturbed battery SOC estimation algorithm with strong adaptive ability.The following is the main content of this paper:Firstly,the existing battery equivalent circuit models were enumerated and analyzed.Then,based on the second-order RC model of lithium battery,a fractional second-order RC model was established,and various parameters in the model were identified by Adaptive Genetic Algorithm(AGA).After that,AGA was used to identify the parameters of the second-order RC model with integer order,and then compared with the fractional order model to test the model accuracy.Then,Fractional Order Adaptive Extended Kalman Filter(FO-EKF)and Fractional Order Adaptive Extended Kalman Filter(FO-AEKF)were designed to estimate SOC for the fractional order second-order RC model of the battery,and the estimation accuracy was verified by pulse discharge experiments.Finally,combining the theory of many new interest and weights of ideas,the FO-AEKF algorithm on the basis of the FO-MIAEKF algorithm is proposed,and in order to continue to improve the estimation precision of SOC,the Least squares(LS)method on the basis of introducing the VFF-RLS algorithm to estimate the state of health(SOH),then estimate the result input FO-MIAEKF algorithm,establish FO-MIAEKF with VFF-RLS algorithm to estimate the SOC of the battery.The validity and precision of the joint algorithm are verified by experimental data.