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Data · dataset · 2026

Experimental data and Simulink models for knowledge-guided DNN-based PMSM harmonic compensation

Listed in Teesside University Research Data Repository

This dataset provides the experimental data, simulation models, and source codes associated with the study on a knowledge-guided deep neural network (KG-DNN) with an enhanced adaptive notch filter (EANF) for harmonic compensation in permanent magnet synchronous motor (PMSM) drives.

Description

Experimental data were collected on a 1.5 kW surface-mounted PMSM testbench controlled by a dSPACE DS1202 real-time system. The control algorithm was executed at a 10 kHz interrupt rate, and signals were recorded at 8192 Hz.

The dataset includes two CSV files. experimental_sample.csv contains time-series measurements for six control configurations (A–F), with columns for timestamp (s), reference speed (rpm), measured speed (rpm), d/q-axis currents (A), d/q-axis voltages (V), electromagnetic torque (N·m), average torque error (N·m), total harmonic distortion (%), and configuration label. sensitivity_scan.csv reports the parameter sensitivity scan results, including parameter name, value, average torque error, THD, convergence epochs, and stability status.

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Reproduction instructions are provided in the Supplementary Material of the associated paper.

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Where it is published

Catalogue records · 1

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Simulation 75%
Provenance · 1 source records, 12 field assertions
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