考虑参数误差的无速度传感器异步电机低速发电工况稳定性提升策略

doi:10.19595/j.cnki.1000-6753.tces.221140

摘要
图/表
参考文献
相关文章 (15)

全文: PDF (1491 KB)
输出: BibTeX | EndNote (RIS)

摘要对于无速度传感器异步电机控制系统,反馈矩阵理论上可以减小系统发电运行不稳定区域,改善低速发电工况下的转速观测性能。然而,由于电机参数误差,现有控制策略无法在低定子电流频率下实现理想的稳定性目标。针对这个问题,本文提出了一种基于多误差项协同的反馈矩阵设计方法,提高系统对电机参数误差的鲁棒性,并提升转速观测的稳定性。首先,本文提出了一种基于多误差项解耦的磁链误差在线观测方法,分析并设计了磁链误差权重系数。其次,在观测器反馈矩阵设计中引入电流误差项,实现电流误差项与磁链误差项的协同设计。在此基础上,将误差矢量系数矩阵行列式重构为抛物线函数,通过引入常数项满足系统稳定的必要条件,解决传统反馈矩阵设计方法对电机参数变化敏感的缺陷,提高观测器对参数误差的鲁棒性。在低定子电流频率下,本文所提出的方法可以在低速发电区域实现稳定的转速观测。最后,在2.2 kW异步电机平台上验证了所提方法的有效性。

	服务

	把本文推荐给朋友
	加入我的书架
	加入引用管理器
	E-mail Alert
	RSS
	作者相关文章
	杨凯
	李孺涵
	罗成
	徐智杰
	郑逸飞

关键词 ：异步电机, 无速度传感器控制, 参数误差, 自适应全阶观测器

Abstract：The speed-sensorless induction motor drives (SSIMD) technique possesses high reliability, easy maintenance, low cost, and is adopted broadly. High performance of the SSIMD system relies on the precise rotor speed information. Recently, several papers have been reported to realize speed estimation as accurate as possible. For the SSIMD control system, the feedback matrix of the adaptive full-order observer (AFO) can theoretically reduce the unstable regenerating region, and improve the speed estimation performance in low-speed regenerating mode. However, the desired performance of existing methods deteriorates at low stator frequencies due to parameter uncertainties. The boundaries of the unstable region cannot coincidence with the inevitable parameter uncertainties.
Actually, most of existing methods ignore the flux error, which is unable to be observed directly by instruments. Then the necessary conditions of the SSIMD control system cannot be satisfied at the low-speed regenerating mode. To solve the problem above, this paper proposes a feedback matrix design method. To design and select the robust feedback in Section Ⅲ, a flux error online estimate method is introduced in Section Ⅱ based on decoupling error terms. Existing literature points out that both the stator current error and the rotor flux error are composed of stator resistance error, rotor resistance error, and rotor speed error. Hence, the expression of the flux error can be obtained by the decoupling analysis. To determine the weight coefficients, variations of ratios N1 and N3 against different synchronous speeds and torque currents are presented. Then the weight coefficients can be selected appropriately.
Introducing the flux error into the feedback matrix design, the mathematical model and the block diagram of the control system with the proposed feedback matrix design are given in Section Ⅲ. To realize the necessary conditions of the SSIMD, the stability function of the AFO is reconstructed as a parabola. The function maximums and the robustness improvement design are discussed based on the vertex movement. With a constant term from the flux error, the stability of the SSIMD in the low-speed regenerating region can be guaranteed even if there are parameter uncertainties. The proposed method overcomes the sensitivity against parameter variation and enhances the robustness of AFO.
Finally, the effectiveness of the proposed method is verified on a 2.2 kW IM experimental setup. Two identical machines are set to provide desired load torque and test the proposed method, respectively. In the load step experiment, the SSIMD control system operates stably with the proposed feedback design, when the stator frequency is 0.4 Hz. The conventional method fails to provide stable speed estimation at 0.6 Hz. The comparison experiments validate the superiority of the proposed method. To test the operation performance in the whole low-speed ranges, the speed reversal experiments are carried out. With the proposed feedback gains, the induction motor crosses the zero-stator-frequency line successfully with great speed observability.
Furthermore, this paper shows the excellent speed tracking performance of the SSIMD control system using the loaded speed step experiments. The parameter robustness, as the core innovation in this paper, is validated by stator and rotor mismatches experiments. Although there are little observation errors, the control system works well.
As conclusion, This paper has provided an alternative solution to enhance the stability of AFO, and also to realize the robustness of feedback gains against parameter uncertainties. The flux error has been estimated with the weight values derived according to IM operating conditions. On this basis, the current and the flux error are adopted as state variables of feedback gains term to design the multiple error-based feedback gains. The effectiveness has been confirmed by experiments in low-speed regenerating region. The stable operations have been realized against parameter uncertainties.

Key words： Induction motor (IM) speed-sensorless control parameter uncertainties adaptive full-order observer

收稿日期: 2022-06-14

PACS:

TM346

基金资助:国家自然科学基金资助项目（52237002,52207055）

通讯作者: 罗成男,1991年生,博士,助理研究员,研究方向为交流电机控制技术。E-mail：luoxcheng@126.com

作者简介: 杨凯男,1976年生,教授,博士生导师,研究方向为交流电机设计及其智能控制技术。E-mail：yk@hust.edu.cn

引用本文:

杨凯, 李孺涵, 罗成, 徐智杰, 郑逸飞. 考虑参数误差的无速度传感器异步电机低速发电工况稳定性提升策略[J]. 电工技术学报, 0, (): 36-36. Yang Kai, Li Ruhan, Luo Cheng, Xu Zhijie, Zheng Yifei. Enhanced Stability for Speed-Sensorless Induction Motor Drives in Low-Speed Regenerating Region Considering Parameter Uncertainties. Transactions of China Electrotechnical Society, 0, (): 36-36.

链接本文:

https://dgjsxb.ces-transaction.com/CN/10.19595/j.cnki.1000-6753.tces.221140 https://dgjsxb.ces-transaction.com/CN/Y0/V/I/36

[1] 王勃, 王天擎, 于泳, 等. 感应电机电流环非线性积分滑模控制策略[J]. 电工技术学报, 2021, 36(10): 2039-2048.
Wang Bo, Wang Tianqing, Yu Yong, et al.Nonlinear integral sliding mode control strategy for current loop of induction motor drives[J]. Transactions of China Electrotechnical Society, 2021, 36(10): 2039-2048.
[2] 肖雄, 王浩丞, 武玉娟, 等. 基于双滑模估计的主从结构共轴双电机模型预测直接转矩控制无速度传感器控制策略[J]. 电工技术学报, 2021, 36(5): 1014-1026.
Xiao Xiong, Wang Haocheng, Wu Yujuan, et al.Coaxial dual motor with master-slave structure model-predictive direct torque control speed sensorless control strategy based on double sliding mode estimation[J]. Transactions of China Electrotechnical Society, 2021, 36(5): 1014-1026.
[3] 张学广, 张雅阁, 方冉, 等. 弱电网下双馈风电机组电网电压扰动补偿控制策略[J]. 电力系统自动化, 2020, 44(6): 146-154.
Zhang Xueguang, Zhang Yage, Fang Ran, et al.Control strategy of disturbance compensation for grid voltage of DFIG based wind turbine in weak grid[J]. Automation of Electric Power Systems, 2020, 44(6): 146-154.
[4] 王震宇, 孙伟, 蒋栋. 基于虚拟电压注入的闭环磁链观测器的感应电机无速度传感器矢量控制系统[J]. 电工技术学报, 2022, 37(2): 332-343.
Wang Zhenyu, Sun Wei, Jiang Dong.Induction motor speed sensorless vector control system based on closed-loop flux observer with virtual voltage injection[J]. Transactions of China Electrotechnical Society, 2022, 37(2): 332-343.
[5] Sun Wei, Gao Jie, Yu Yong, et al.Robustness improvement of speed estimation in speed-sensorless induction motor drives[J]. IEEE Transactions on Industry Applications, 2016, 52(3): 2525-2536.
[6] Suwankawin S, Sangwongwanich S.Design strategy of an adaptive full-order observer for speed-sensorless induction-motor Drives-tracking performance and stabilization[J]. IEEE Transactions on Industrial Electronics, 2006, 53(1): 96-119.
[7] Qu Zengcai, Hinkkanen M, Harnefors L.Gain scheduling of a full-order observer for sensorless induction motor drives[J]. IEEE Transactions on Industry Applications, 2014, 50(6): 3834-3845.
[8] 张康, 王丽梅. 基于反馈线性化的永磁直线同步电机自适应动态滑模控制[J]. 电工技术学报, 2021, 36(19): 4016-4024.
Zhang Kang, Wang Limei.Adaptive dynamic sliding mode control of permanent magnet linear synchronous motor based on feedback linearization[J]. Transactions of China Electrotechnical Society, 2021, 36(19): 4016-4024.
[9] 宋文祥, 周杰, 朱洪志, 等. 基于自适应全阶观测器的感应电机低速发电运行稳定性[J]. 电工技术学报, 2014, 29(3): 196-205.
Song Wenxiang, Zhou Jie, Zhu Hongzhi, et al.Regenerating-mode stabilization of induction motors based on adaptive full-order observer[J]. Transactions of China Electrotechnical Society, 2014, 29(3): 196-205.
[10] Zaky M S, Metwaly M K.Sensorless torque/speed control of induction motor drives at zero and low frequencies with stator and rotor resistance estimations[J]. IEEE Journal of Emerging and Selected Topics in Power Electronics, 2016, 4(4): 1416-1429.
[11] Kim J H, Choi J W, Sul S K.Novel rotor-flux observer using observer characteristic function in complex vector space for field-oriented induction motor drives[J]. IEEE Transactions on Industry Applications, 2002, 38(5): 1334-1343.
[12] Luo Cheng, Wang Bo, Yu Yong, et al.Operating-point tracking method for sensorless induction motor stability enhancement in low-speed regenerating mode[J]. IEEE Transactions on Industrial Electronics, 2020, 67(5): 3386-3397.
[13] Cao Pengpeng, Zhang Xing, Yang Shuying.A unified-model-based analysis of MRAS for online rotor time constant estimation in an induction motor drive[J]. IEEE Transactions on Industrial Electronics, 2017, 64(6): 4361-4371.
[14] Yin Shaobo, Huang Yingwei, Xue Yaru, et al.Improved full-order adaptive observer for sensorless induction motor control in railway traction systems under low-switching frequency[J]. IEEE Journal of Emerging and Selected Topics in Power Electronics, 2019, 7(4): 2333-2345.
[15] Etien E, Chaigne C, Bensiali N.On the stability of full adaptive observer for induction motor in regenerating mode[J]. IEEE Transactions on Industrial Electronics, 2010, 57(5): 1599-1608.
[16] Luo Cheng, Wang Bo, Yu Yong, et al.A speed adaptive scheme-based full-order observer for sensorless induction motor drives in low-speed regenerating operation range[C]//2018 21st International Conference on Electrical Machines and Systems (ICEMS), Jeju, Korea (South), 2018: 1301-1306.
[17] 徐伟, 陈俊杰, 刘毅, 等. 无刷双馈独立发电系统的改进无参数预测电流控制[J]. 电工技术学报, 2021, 36(19): 4002-4015.
Xu Wei, Chen Junjie, Liu Yi, et al.Improved nonparametric predictive current control for standalone brushless doubly-fed induction generators[J]. Transactions of China Electrotechnical Society, 2021, 36(19): 4002-4015.