电工技术学报  2023, Vol. 38 Issue (22): 6015-6026    DOI: 10.19595/j.cnki.1000-6753.tces.230176
“电动汽车驱动电机系统”专题(特约主编:温旭辉 研究员) |
考虑等效电磁损耗电阻偏移的永磁同步电机直流信号注入在线参数辨识方法
马铱林1,2, 袁浩1,2, 尹威1,2, 杨欢1,2
1.浙江大学电气工程学院 杭州 310027;
2.浙江省电机系统智能控制与变流技术重点实验室 杭州 310027
DC-Signal-Injection-Based Online Parameters Identification for Permanent Magnet Synchronous Machine Considering Variation of Equivalent Electromagnetic Loss Resistance
Ma Yilin1,2, Yuan Hao1,2, Yin Wei1,2, Yang Huan1,2
1. College of Electrical Engineering Zhejiang University Hangzhou 310027 China;
2. Zhejiang Provincial Key Laboratory of Electrical Machine Systems Hangzhou 310027 China
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摘要 在实际运行过程中,永磁同步电机的电气参数将受到温度、磁饱和等诸多物理因素的影响而发生偏移,进而影响到效率最优控制、电流解耦控制等优化算法的运行效果。因此,为实现高性能电机控制,永磁同步电机的多电气参数在线辨识显得尤为重要。然而,现有参数辨识方法并未考虑铁磁损耗的影响,更未关注铁磁损耗随电流的偏移情况,所以在辨识精度上仍存在提升空间。对此,该文综合考虑铁磁损耗、铜损,将其集总为电磁损耗,并基于串联电磁损耗电阻模型,提出一种考虑等效电磁损耗电阻偏移的永磁同步电机直流信号注入在线参数辨识方法。该方法首先提出等效电磁损耗电阻随电流偏移的电机模型;其次由此设计同时考虑磁饱和、等效电磁损耗电阻偏移的直流信号注入在线参数辨识方法;由于待求解方程组较多,采用最小方均算法进行参数求解;最后通过实验测试所提方法的准确性,测试结果表明,与正弦信号注入法、传统直流信号注入法相比,所提方法的参数精度有所提升。
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关键词 永磁同步电机电磁损耗参数辨识直流信号注入    
Abstract:Permanent magnet synchronous machines (PMSMs) are widely used for their high operating efficiency. During the application, the parameters of PMSMs may vary a lot when considering the effect of temperature, magnetic saturation, and so on. In this case, the performance of some optimal control strategies, such as the maximum efficiency control and current decoupling control, may decay. Thus, to achieve high-performance control, online parameter identification is important. However, there are few parameter identification methods considering the ferromagnetic loss and its variation with currents, while the ferromagnetic loss occupies a great proportion of the PMSMs' loss. Therefore, this paper integrates ferromagnetic loss and copper loss as electromagnetic loss. Then, an improved DC-signal-injection-based online parameters identification is proposed considering equivalent electromagnetic loss resistance variation.
Firstly, the magnetic saturation of PMSMs and the variation of electromagnetic loss with current are discussed. Due to the magnetic saturation characteristic of ferromagnetic materials, the magnetic permanence of PMSMs may be decreased as the current rises, which, in turn, affects the inductance and flux linkage. Besides, when considering the change of current vectors, the copper loss may be variable due to the proximate effect. Meanwhile, the ferromagnetic loss may also vary with the changeable magnetic distribution. An improved series electromagnetic loss resistance model is proposed. Apparent flux linkage and incremental inductance are used to characterize the magnetic saturation, and change rates of the equivalent resistance are used to represent variations in electromagnetic loss.
Secondly, 4 groups of d-/q-axis operating currents are chosen based on the criterion of alternating changes in d-/q-axis currents. According to the analysis, if the current increment of each change is non-zero, the steady-state voltage equations of these 4 groups are linearly independent. That is, the corresponding coefficient matrix is full-rank, allowing for the full parameters identification.
Thirdly, a least mean square (LMS) algorithm is adopted to solve the 4 groups of steady-state voltage equations due to the complexity of analytical computation arising from the high-rank coefficient matrix. The LMS algorithm calculates the gradient of voltage estimation errors' mean square to each model parameter based on the measured voltages, currents, and speeds. Then, the model parameters are updated iteratively based on the corresponding gradients at each step. After iteration, the model parameters that meet the preset voltage estimation accuracy are obtained.
Finally, the accuracy of the proposed method is validated using a prototype PMSM. Experimental results show that, compared with the sinusoidal-signal-injection-based method and the traditional DC-signal-injection- based method, the proposed method is more precise in identifying electromagnetic resistance and apparent flux linkage, with an average relative error of less than 2.3%. In addition, the proposed method has high identification accuracy for torque and incremental inductance, with average relative errors less than 0.9% and 3.5%, respectively. However, there is room for improving the identification performance of the equivalent resistance change rate.
Key wordsPermanent magnet synchronous machine    electromagnetic loss    parameters identification    DC signal injection   
收稿日期: 2023-02-16     
PACS: TM341  
基金资助:国家自然科学基金(52177062)和中央高校基本科研业务费专项资金(226-2022-00011)资助项目
通讯作者: 杨 欢 男,1981年生,教授,博士生导师,研究方向为分布式发电与微电网、智能配用电、高效能电机系统等。E-mail: yanghuan@zju.edu.cn   
作者简介: 马铱林 男,1996年生,博士研究生,研究方向为高效能电机系统、数字化设计、铁磁材料性能测试等。E-mail: mayilin@zju.edu.cn
引用本文:   
马铱林, 袁浩, 尹威, 杨欢. 考虑等效电磁损耗电阻偏移的永磁同步电机直流信号注入在线参数辨识方法[J]. 电工技术学报, 2023, 38(22): 6015-6026. Ma Yilin1,2, Yuan Hao1,2, Yin Wei1,2, Yang Huan1,2. DC-Signal-Injection-Based Online Parameters Identification for Permanent Magnet Synchronous Machine Considering Variation of Equivalent Electromagnetic Loss Resistance. Transactions of China Electrotechnical Society, 2023, 38(22): 6015-6026.
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