Interactive Multi-fractional Order Model Approach Of SOC Estimation For Lithium-ion Batteries

With the intensification of global environmental pollution and energy crisis,new energy vehicles have become the main direction of automobile transformation.Lithium-ion batteries are the main energy supply units of new energy vehicles,it is necessary to monitor the working status of the batteries.State of Charge(SOC)estimation is the basis for lithium-ion battery energy management,and battery aging will cause complex changes in battery parameters to a large extent,thus affecting the estimation accuracy of SOC.Aiming at the problem of battery parameter change caused by battery aging,this paper aims to achieve accurate SOC estimation of the battery life cycle.Based on the analysis of the life decay principle of lithium-ion battery,an interactive multi-fractional order model(IMFOM)is proposed to estimate SOC.Specifically,according to the influence of battery aging on model parameters,a number of fractional order models are established to characterize the parameter drift of different life segments of the battery.Combined with the GrünwaldLetnikov definition,the state space equation in continuous time is discretized.And the model parameters are identified by recursive least square method with forgetting factor.According to the law of battery capacity attenuation and user habits,the initial probability of the model is set up,the state transfer mode of the adaptive Markov matrix improvement sub-models is proposed,and the IM-FOM is established.Interactive multi-model Extended Kalman Filter(IMM-EKF)is used to solve the nonlinear estimation problem in IM-FOM framework,and interactive multi-model Quadrature Kalman Filter(IMM-QKF)algorithm is proposed.The results show that the IM-FOM based SOC estimation method is superior to the traditional method based on single model,and its estimation accuracy is improved by more than 2 times.Among them,IMM-QKF has better accuracy and anti-interference ability than IMM-EKF,and has stronger convergence and stability in the whole life cycle.The IMM-QKF based on the IM-FOM provides an effective method for accurate SOC estimation in the whole life cycle of lithium-ion battery.