电测与仪表
電測與儀錶
전측여의표
ELECTRICAL MEASUREMENT & INSTRUMENTATION
2014年
2期
58-62
,共5页
电池模型%荷电状态(SOC)%EKF%UKF
電池模型%荷電狀態(SOC)%EKF%UKF
전지모형%하전상태(SOC)%EKF%UKF
battery model%SOC%EKF%UKF
针对实际运行中电池参数的变化，建立了基于Thevenin模型的锂离子动力电池状态空间模型，采用递推最小二乘法进行模型参数在线辨识，对参数做出实时修正，同时克服广义卡尔曼滤波（EKF）估算的不足，提出了基于无色卡尔曼滤波（UKF）估算锂电池SOC估算的新方法。实验结果验证了在同等条件下，UKF比EKF具有更好的滤波估算精度，提高了系统的适应性。
針對實際運行中電池參數的變化，建立瞭基于Thevenin模型的鋰離子動力電池狀態空間模型，採用遞推最小二乘法進行模型參數在線辨識，對參數做齣實時脩正，同時剋服廣義卡爾曼濾波（EKF）估算的不足，提齣瞭基于無色卡爾曼濾波（UKF）估算鋰電池SOC估算的新方法。實驗結果驗證瞭在同等條件下，UKF比EKF具有更好的濾波估算精度，提高瞭繫統的適應性。
침대실제운행중전지삼수적변화，건립료기우Thevenin모형적리리자동력전지상태공간모형，채용체추최소이승법진행모형삼수재선변식，대삼수주출실시수정，동시극복엄의잡이만려파（EKF）고산적불족，제출료기우무색잡이만려파（UKF）고산리전지SOC고산적신방법。실험결과험증료재동등조건하，UKF비EKF구유경호적려파고산정도，제고료계통적괄응성。
A state space model of a Li cell is proposed based on Thevenin model. The battery parameters always change in the actual operation, so the recursive least square method is chosen to identify the parameters on-line so as to make real-time correction and enhance the adaptability of the system. To overcome the weaknesses of EKF, a new estimation method is put forward based on UKF (Unscented Kalman Filtering) to estimate SOC of Li-ion battery. Experiments are made to compare the performance with the new filter to that with EKF. The result demonstrates that UKF achieve higher filtering accuracy under the same conditions.
