Experimental data for E-ASHA manuscript 核心 · 已核验

mxdsr40psgd2em25

"Current sensor inaccuracies and system delays (collectively termed hybrid errors) degrade the performance of finite control set model predictive current control (FCS-MPCC) in surface-mounted permanent magnet synchronous motor (SPMSM) drives, leading to increased torque ripple, speed fluctuations, and reduced efficiency. This paper proposes an enhanced adaptive selective harmonic annulation (E-ASHA) algorithm integrated within the FCS-MPCC framework to simultaneously compensate for both sensor-induced errors and delay-induced harmonics. The proposed method employs an LMS-based adaptive learning mechanism to selectively estimate and cancel targeted harmonic components in both q-axis and d-axis currents without requiring additional sensors, motor parameter identification, or observer-based structures. By exploiting the coupling between dq-axis currents and motor speed dynamics, the strategy effectively mitigates torque and speed ripple while preserving the predictive nature of FCS-MPCC. Experimental validation on a 1-kW SPMSM platform demonstrates up to 80.5% reduction in current total harmonic distortion at low speed and more than 46% torque ripple suppression under high-speed heavy-load conditions while maintaining computational efficiency."

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落地页

https://ieee-dataport.org/documents/experimental-data-e-asha-manuscript

国内可访问性

国内直连:可达 (2026-07-11 检测) 非直连:可达 (2026-07-11 检测)
「直连超时」表示检测窗口内未完成,系慢或不稳定证据,不构成封锁证据。

发布年份

2026

发布方

IEEE DataPort

设备类型

synchronous_motor

故障工况

传感器

运行工况