At present,one of the important factors affecting the development of pure electric vehicles is battery,and an important indicator to consider batteries is the state of charge(SOC)of lithium batteries.If the SOC of lithium batteries can be accurately estimated,which can provide corresponding data support for its remaining mileage prediction and battery energy management.As a common charging device,lithium battery's SOC is difficult to estimate,which restricts the development of new energy vehicles.Aiming at the problem of estimating the state of charge of lithium battery,the working principle is analyzed,and the model of lithium iron phosphate battery is established.By identifying the internal parameters of lithium battery,based on Extended Kalman Filter(EKF)and Unscented Kalman Filter(UKF),the SOC of lithium iron phosphate battery is estimated by using the above algorithms in MATLAB.The errors of the two algorithms are obtained by simulation,which further shows that UKF has high accuracy,and its estimation error can be kept within 4%,which can meet the requirements of the state of charge of lithium-ion batteries.
关键词
电动汽车/锂电池/戴维宁模型/Matlab
Key words
electric vehicle/lithium battery/Davining model/Matlab
维普
万方数据