基于RLS法的锂离子电池离线参数辨识

提出一种基于递推型最小二乘法(RLS)算法改进的离线参数识别方法,采用RLS法作为离线参数辨识的初值,以解决离线辨识初值选择的限制,并能保证辨识结果的精度。采用RLS算法辨识参数,获取模型参数,仿真电压和实验电压最大误差达100 mV,但耗时仅120 s。采用Simscape模型的离线参数辨识方法,最大误差58 mV,耗时1.8 h;利用RLS算法获取初值,用离线参数辨识方法,最大误差为31 mV,平均误差15 mV,耗时0.5 h。辨识精度与辨识速度都有明显的提升。

Offline parameter identification of Li-ion battery based on RLS method

An improved offline parameter identification method based on recursive least square(RLS)algorithm was proposed.An improved off-line parameter identification method based on RLS algorithm was proposed,which used the RLS method as the initial value of off-line parameter identification,which not only solved the limitation of the initial value selection of off-line identification,but also ensured the accuracy of the identification results.RLS algorithm was used to identify parameters.After obtaining model parameters,the maximum error of simulation voltage and experimental voltage was up to 100 mV,but the time was only 120 s.The offline parameter identification method of Simscape model was adopted,with a maximum error of 58 mV and a time of 1.8 h.After the initial value was obtained by RLS algorithm,the offline parameter identification method was adopted.The maximum error was 31 mV,the average error was 15 mV,the time was 0.5 h.The identification accuracy and speed were significantly improved.