东南大学学报（自然科学版）Issue(1)：49-54,6.DOI:10.3969/j.issn.1001-0505.2016.01.009
基于双 STF-UKF 算法的永磁同步电机参数联合估计
PMSM parameters estimation based on dual STF-UKF algorithm
摘要
Abstract
To solve the parameter identification problem of the permanent magnet synchronous mo-tor, the identification model of PMSM( permanent magnet synchronous motor) was analyzed.Re-garding the parameters as slow varied states along with time and considering the presence of the sys-tem noise and measure noise, an improved unscented Kalman filter( UKF) algorithm was proposed based on the strong tracking filter( STF) .This improved filter algorithm is able to estimate the pa-rameters of PMSM including stator resistance, permanent magnet flux linkage and q-axis and d-axis inductance.The stability of the proposed algorithm was discussed.In order to reduce the calculation consumption of the algorithm, the four parameters were divided into two parts and estimated by dual STF-UKF, respectively.Simulation results show that the improved UKF algorithm can estimate the parameters accurately under different PMSM operations.关键词
永磁同步电机/参数辨识/强跟踪滤波器/无迹卡尔曼滤波/稳定性Key words
permanent magnet synchronous motor/parameters estimation/strong tracking filter/unscented Kalman filter/stability分类
信息技术与安全科学引用本文复制引用
林辉,吕帅帅..基于双 STF-UKF 算法的永磁同步电机参数联合估计[J].东南大学学报（自然科学版）,2016,(1):49-54,6.基金项目
国家自然科学基金资助项目（51407143）、高等学校博士学科点专项科研基金资助项目（20136102120049）、中央高校基本科研业务费专项资助项目（3102014JCQ01066）、陕西省自然科学基础研究计划资助项目（2014JQ7264，2015JM5227）、陕西省微特电机及驱动技术重点实验室开放基金资助项目（2013SSJ1002）． （）
