【目的】针对内置式永磁同步电机零低速高频方波注入位置观测中,d、q轴电感随运行工况变化导致解调系数失配,进而降低位置观测精度的问题,提出一种基于在线电感辨识的解调系数自适应补偿方法。【方法】首先建立高频方波注入解调模型,通过差分法提取高频电流,推导电感变化对解调系数及位置观测误差的传递机理;在此基础上,引入模糊逻辑的级联模型参考自适应系统(FLC-MRAS)在线辨识Ld、Lq,利用辨识结果实时重构解调系数,对两相解调信号进行补偿,再将相位误差信号输入锁相环,实现转子位置与速度的闭环估计,减弱参数变化对系统的影响。【结果】基于Matlab/Simulink平台进行了仿真分析。结果表明,在转速阶跃工况下FLC-MRAS的Ld、Lq辨识最大误差较传统MRAS分别减小了94.1%、97.1%。与传统高频方波注入相比,补偿后速度误差负峰值和正向反冲峰值分别减小43.9%和42.4%,位置误差峰值减小30.6%。在负载阶跃工况下,Ld、Lq辨识最大误差分别减小85.7%、95.7%,速度跌落幅值和误差峰值分别减小70.8%和64.8%,角度误差幅值减小60.0%。【结论】本文所提方法基于FLC-MRAS在线辨识电感实时修正高频解调模型,减弱电感变化引起的系数失配,提高转速和转子位置观测精度,并增强系统在不同工况下的鲁棒性。

[Objective] To address the issue of demodulation coefficient mismatch caused by variations in d-axis and q-axis inductances due to changing operating conditions, which degrades position observation accuracy in zero- and low-speed interior permanent magnet synchronous motor drives using high-frequency square-wave signal injection, an adaptive demodulation coefficient compensation method based on online inductance identification is proposed. [Methods] Firstly, a high-frequency square-wave injection demodulation model was established. The difference method was used to extract the high-frequency current, and the transfer mechanism of how inductance variation affects the demodulation coefficient and position observation error was derived. On this basis, a fuzzy logic cascade model reference adaptive system (FLC-MRAS) was employed to identify Ld and Lq online. The identification results were then used to reconstruct the demodulation coefficients in real time, compensating the two-phase demodulation signals. Finally, the phase error signal was fed into a phase-locked loop to achieve closed-loop estimation of rotor position and speed, thereby mitigating the impact of parameter variations on the system. [Results] Simulations were conducted on the Matlab/Simulink platform. The results indicated that under the speed step condition, the maximum identification errors of Ld and Lq using FLC-MRAS were reduced by 94.1% and 97.1%, respectively, compared to the traditional MRAS. Compared with conventional high-frequency square-wave injection, the negative peak and positive overshoot of the speed error were decreased by 43.9% and 42.4% after compensation, and the peak position error was reduced by 30.6%. Under the load step condition, the maximum identification errors of Ld and Lq were lowered by 85.7% and 95.7%, respectively; the speed drop amplitude and error peak were decreased by 70.8% and 64.8%; and the amplitude of the angular error was reduced by 60.0%. [Conclusion] The proposed method is based on FLC-MRAS online inductance identification to correct the high-frequency demodulation model in real time, which mitigates coefficient mismatch caused by inductance variations, improves the observation accuracy of speed and rotor position, and enhances system robustness under different operating conditions.

国家自然科学基金(U22A20246)