Bai Xiyue, Huang Weiguang, Gao Chuang, Wu Yingna
Center for Adaptive System Engineering, ShanghaiTech University, Shanghai 201210, China.
Shanghai Advanced Research Insititute, Chinese Academy of Sciences, Shanghai 201210, China.
Sensors (Basel). 2025 Feb 20;25(5):1290. doi: 10.3390/s25051290.
To improve the precision of the position and speed estimation in ultra-high-speed (UHS) permanent magnet synchronous motors (PMSM) without position sensors, multiple refinements to the traditional extended electromotive force (EEMF) estimation algorithm are proposed in this paper. The key improvements include discretization compensation, high-frequency harmonic filtering, and the real-time adjustment of the phase-locked loop (PLL) bandwidth. Firstly, a discrete model is introduced to address EMF cross-coupling issues. Secondly, an improved proportional resonant (IPR) controller eliminating static errors is utilized in place of the conventional proportional-integral (PI) controller and low-pass filter (LPF) to enable precise electromotive force extraction, effectively filtering high-frequency harmonics that arise in low carrier ratio conditions. Based on a standard PR design, the IPR controller offers a streamlined calculation for target leading angles in delay compensation schemes to effectively mitigate discretization and delay errors. Additionally, an adaptive phase-locked loop (AQPLL) dynamically adjusts its bandwidth during acceleration to balance noise rejection and phase delay, reducing position estimation errors and optimizing torque. Simulations and experimental analyses on a motor (90,000 rpm, 30 kW) validate the effectiveness of the proposed sensorless driving techniques and demonstrate enhanced performance in position and velocity estimation, compared to the conventional EEMF approach.
为了提高无位置传感器的超高速（UHS）永磁同步电机（PMSM）中位置和速度估计的精度，本文对传统的扩展电动势（EEMF）估计算法提出了多项改进。关键改进包括离散化补偿、高频谐波滤波以及锁相环（PLL）带宽的实时调整。首先，引入离散模型来解决电动势交叉耦合问题。其次，采用改进的比例谐振（IPR）控制器消除静态误差，取代传统的比例积分（PI）控制器和低通滤波器（LPF），以实现精确的电动势提取，有效滤除低载波比条件下出现的高频谐波。基于标准PR设计，IPR控制器为延迟补偿方案中的目标超前角提供了简化计算，以有效减轻离散化和延迟误差。此外，自适应锁相环（AQPLL）在加速过程中动态调整其带宽，以平衡噪声抑制和相位延迟，减少位置估计误差并优化转矩。对一台电机（90,000转/分，30千瓦）进行的仿真和实验分析验证了所提出的无传感器驱动技术的有效性，并表明与传统的EEMF方法相比，在位置和速度估计方面具有更高的性能。
