基于无迹卡尔曼滤波水下WPT系统副边关键参数在线辨识  

Online Identification of Key Parameters of Secondary Edges in Underwater WPT System Based on Unscented Kalman Filtering Algorithm

作　　者：程志远 张智超 眭清洋 纪天睿 李东东 CHENG Zhiyuan;ZHANG Zhichao;SUI Qingyang;JI Tianrui;LI Dongdong(College of Electrical Engineering,Shanghai University of Electric Power,Yangpu District,Shanghai 200090,China)

机构地区：[1]上海电力大学电气工程学院,上海市杨浦区200090

出　　处：《中国电机工程学报》2024年第11期4470-4479,I0025,共11页Proceedings of the CSEE

基　　金：国家自然科学基金项目(51877129)。

摘　　要：为提升无线电能传输(wireless power transfer,WPT)系统传输性能,需在控制过程中实时获取负载与耦合系数等关键信息,而该信息的获取目前普遍采用无线通讯模块或增加额外通信线圈等方式,增加了系统复杂度,尤其面临复杂水下工况及高频电磁环境,在通讯过程中极易造成通讯异常而导致系统瘫痪。为此,文中提出一种新型基于无迹卡尔曼滤波的WPT系统互感及负载关键参数在线识别方法,该方法仅需采样原边侧电压瞬时值,即可实时获取互感与负载等关键参数信息。同时为提升辨识精度与收敛速度,采用离线式神经网络指导粒子群优化算法建立系统噪声协方差矩阵。实验结果表明,该算法具有模型简单、计算精度较高等特点,在变负载、变移相控制角及偏移情况下,所提出的在线辨识方法对负载与互感的最大识别误差分别为6.19%和1.7%,且2 ms左右即可完成负载的动态识别,具有一定的工程应用价值。In order to improve the transmission performance of wireless power transfer(WPT)system,it is necessary to obtain key information such as load and coupling coefficient in real time during the control process.Currently,acquiring this information typically involves using wireless communication modules or adding additional communication coils,which adds complexity to the system.This complexity is further exacerbated in complex aquatic conditions and high-frequency electromagnetic environments,where abnormal communication during the process is highly likely to cause system paralysis.For this purpose,this paper proposes a novel Unscented Kalman filter(UKF)based online identification method for the critical parameters of the WPT system's transients and loads.This method only samples the instantaneous value of the voltage at the edge of origin,and can acquire the information of critical parameters such as transients and loads in real time.At the same time,to improve the discrimination accuracy and convergence speed,the offline neural network guided particle swarm optimization(PSO-NN)algorithm is used to establish a systematic noise covariance matrix.The experimental results show that the proposed online discrimination method achieves the maximum identification errors of 6.19%and 1.7%for load and mutual inductance,respectively,in the case of varying load,varying phase control angle and offset.The dynamic identification of load can be completed in about 2 ms,which has some engineering applications.

关 键 词：无线电能传输 无迹卡尔曼滤波 在线辨识 互感识别 负载识别 

分 类 号：TM46[电气工程—电器]