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带有自适应参数辨识的IPMSM MTPA控制 被引量:16

Model reference adaptive identification based MTPA control method for interior PM synchronous motor
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摘要 内置式永磁同步电机的工作点可能随着参数变化而偏离理想的最大转矩电流比(MTPA)轨迹,因而导致系统不能获得最优转矩-电流特性。针对这一问题,提出了一种在线识别定子交轴电感、转子磁链的模型参考自适应(MRAS)参数辨识方法。该方法在分析辨识模型欠秩问题和评估MTPA轨迹随参数变化偏离程度的基础上,推导了MRAS辨识模型,采用Popov超稳定性理论设计了满秩辨识器及其增益矩阵,并利用参数辨识结果计算定子电流工作点,以达到实时更新和跟踪MTPA轨迹的目的。仿真与实验结果验证了所设计方法的可行性和有效性,该方法显著提高了内置式永磁同步电机MTPA控制系统的转矩-电流特性。 In an interior PM synchronous motor(IPMSM)drive and control system,its optimal current-torque characteristics cannot be obtained under the condition of maximum-torque-per-ampere(MTPA),due to the operation point drifts with the electrical parameter variances.Aiming at this problem,a model reference adaptive system(MRAS)was presented based on adaptive parameter estimation method,in order to identify the q-axis inductance and PM flux linkage on-line.Initially,considering the problem of deficient-rank in the state space equation,the operation points’derivation degrees in reference to the ideal MTPA track were investigated with parameter changes.In the next place,a parameter adjustable model for an IPMSM was deduced,and then complying with the design method the Popov Hyper Stability Theorem,a full-rank identifier was proposed with the configuration of an appropriate gain matrix.Finally,the identified parameters were applied to refresh the torque-current working conditions real-timely,which improves significantly the system′s MTPA control properties.
作者 金宁治 周凯 Herbert Ho-Ching IU JIN Ning-zhi;ZHOU Kai;Herbert Ho-Ching IU(School of Electric and Electronic Engineering,Harbin University of Science and Technology,Harbin 150080,China;School of Electric,Electronic and Computer Engineering,University of Western Australia,Western Australia 6009,Australia)
出处 《电机与控制学报》 EI CSCD 北大核心 2020年第7期90-101,共12页 Electric Machines and Control
基金 国家留学基金(201708930003) 黑龙江省普通本科高等学校青年创新人才培养计划基金项目(UNPYSCT-2017099)。
关键词 内置式永磁同步电机 最大转矩电流比 参数辨识 模型参考自适应 欠秩问题 interior permanent magnet synchronous motor maximum torque per ampere model reference adaptive system parameter identification problem of deficient-rank
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