A Variable Gain Nonlinear Current Controller for Torque Ripple Minimization in Switched Reluctance Motor Drives

In switched reluctance motor (SRM) drives, conventional current controllers often struggle to cope with the highly time-varying phase inductance and nonlinear back electromotive force (EMF). This article proposes a discrete-time adaptive sliding mode controller (ASMC) to reduce torque ripple and improve current tracking performance. Unlike conventional continuous-time designs, the proposed controller is formulated entirely in the discrete domain, making it suitable for digital implementation. An adaptive law based on the sliding mode surface dynamics mitigates current overshoot caused by time-varying phase inductance during commutation. To enhance robustness, a high-frequency switching term is incorporated to compensate for system uncertainties and nonlinear back EMF effects. The closed-loop stability of the system is rigorously proven using discrete Lyapunov theory. Experimental results demonstrate that the proposed ASMC significantly reduces torque ripple, lowers torque root mean square error (RMSE), and increases average torque compared to traditional controllers, validating its effectiveness for practical SRM applications.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Transportation Electrification
Published
2025-08-12
DOI
https://doi.org/10.1109/tte.2025.3598196
Primary Topic
Electric Motor Design and Analysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Variable Gain Nonlinear Current Controller for Torque Ripple Minimization in Switched Reluctance Motor Drives

S. F. Zhang, Xijian Lin, Rodrigo Padilha Vieira, Lefei Ge et al.
IEEE Transactions on Transportation Electrification
Electric Motor Design and Analysis
article

A Variable Gain Nonlinear Current Controller for Torque Ripple Minimization in Switched Reluctance Motor Drives

S. F. Zhang, Xijian Lin, Rodrigo Padilha Vieira, Lefei Ge, Dianxun Xiao, Zifeng Chen
article en

Abstract

In switched reluctance motor (SRM) drives, conventional current controllers often struggle to cope with the highly time-varying phase inductance and nonlinear back electromotive force (EMF). This article proposes a discrete-time adaptive sliding mode controller (ASMC) to reduce torque ripple and improve current tracking performance. Unlike conventional continuous-time designs, the proposed controller is formulated entirely in the discrete domain, making it suitable for digital implementation. An adaptive law based on the sliding mode surface dynamics mitigates current overshoot caused by time-varying phase inductance during commutation. To enhance robustness, a high-frequency switching term is incorporated to compensate for system uncertainties and nonlinear back EMF effects. The closed-loop stability of the system is rigorously proven using discrete Lyapunov theory. Experimental results demonstrate that the proposed ASMC significantly reduces torque ripple, lowers torque root mean square error (RMSE), and increases average torque compared to traditional controllers, validating its effectiveness for practical SRM applications.

IEEE Transactions on Transportation ElectrificationVol. 11(6)
Northwestern Polytechnical University (CN), Universidade Federal de Santa Maria (BR)
Affordable and clean energy
Openalex Percentile: Top 81%
Electric Motor Design and Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

A Variable Gain Nonlinear Current Controller for Torque Ripple Minimization in Switched Reluctance Motor Drives — S. F. Zhang, Xijian Lin, et al. · IEEE Transactions on Transportation Electrification (2025) | TGRS Research Map | TGRS