The SOC Estimation Of Lithium Battery Based On Fractional Square Root Unscented Kalman Filter

New energy electric vehicles have been welcomed and recognized by more and more consumers.Battery management system is usually used to ensure the optimal performance and normal operation of the whole vehicle system and each single battery,the state of charge(SOC)is a very important function in the battery management system,it is mainly used to quantify the remaining power of the battery.Keeping the battery SOC within a reasonable range can effectively prevent the damage to battery life caused by overcharge and overplay.At the same time,accurate battery SOC estimation can also play a good reference value for drivers to plan their journeys reasonably and predict the remaining driving mileage of vehicles.Because of the complex and interactive electrochemical reaction process,the external strong nonlinear and time-varying characteristics,and the complex and changeable vehicle operating environment,the SOC estimation is difficult.For obtaining more accurate SOC values,the following works are done:A fractional-order second-order RC equivalent circuit model based on the electrochemical impedance spectroscopy characteristic curve of lithium batteries is developed.The model uses constant phase angle element instead of ideal capacitance in traditional integer order model,which can describe the dynamic behavior of battery more accurately.Based on the discrete of fractional calculus Grunwald-Letnikov definition,the state space equation of fractional order model of lithium battery is given.A differential decreasing strategy is used to calculate the weight and applied to the parameter identification of the battery model,which greatly reduces the possibility that the standard particle swarm optimization algorithm will fall into the local optimal solution when optimizing the objective function.The simulation results show that the model has high accuracy.A SOC estimate method of the square root unscented Kalman filter based on fractional order mathematical model of lithium battery is proposed.On the one hand,this method inherits the advantages of unscented Kalman filter,and can be directly applied to nonlinear systems and ensure the positive stability of error covariance.On the other hand,it can give full play to the advantages of fractional order model of lithium battery in accurately characterizing the dynamic behavior of the system.The simulation experiments at three dynamic conditions: Federal Urban Driving Schedule,US06 Highway Driving Schedule and Beijing dynamic stress test,and at three temperatures(25℃,0℃ and 45℃),show that the proposed method has high estimation accuracy.The quality of process noise and measurement noise is the key factor affecting the estimation accuracy of Kalman filter,an adaptive noise covariance matrix strategy is proposed.This strategy combined with fractional square root unscented Kalman filter to estimate the SOC of lithium ion batteries,which effectively overcomes the problem that noise covariance is set as constant value in general filtering method and leads to inaccurate filtering result,and prevents the problem that inaccurate noise covariance matrix leads to filter divergence.Simulation experiments at three different temperatures and three different dynamic conditions show that the SOC estimation of lithium batteries based on this method can obtain higher estimation accuracy.