A Hybrid Algorithm for PMLSM Force Ripple Suppression Based on Mechanism Model and Data Model

Yunlong Yi (), Sheng Ma, Bo Zhang and Wei Feng
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Yunlong Yi: School of Computer Science and Technology, Shenyang Institute of Engineering, Shenyang 110136, China
Sheng Ma: School of Computer Science and Technology, Shenyang Institute of Engineering, Shenyang 110136, China
Bo Zhang: School of Electrical Engineering, Shenyang University of Technology, Shenyang 110178, China
Wei Feng: School of Electrical Engineering, Shenyang University of Technology, Shenyang 110178, China

Energies, 2025, vol. 18, issue 15, 1-16

Abstract: The force ripple of a permanent magnet synchronous linear motor (PMSLM) caused by multi-source disturbances in practical applications seriously restricts its high-precision motion control performance. The traditional single-mechanism model has difficulty fully characterizing the nonlinear disturbance factors, while the data-driven method has real-time limitations. Therefore, this paper proposes a hybrid modeling framework that integrates the physical mechanism and measured data and realizes the dynamic compensation of the force ripple by constructing a collaborative suppression algorithm. At the mechanistic level, based on electromagnetic field theory and the virtual displacement principle, an analytical model of the core disturbance terms such as the cogging effect and the end effect is established. At the data level, the acceleration sensor is used to collect the dynamic response signal in real time, and the data-driven ripple residual model is constructed by combining frequency domain analysis and parameter fitting. In order to verify the effectiveness of the algorithm, a hardware and software experimental platform including a multi-core processor, high-precision current loop controller, real-time data acquisition module, and motion control unit is built to realize the online calculation and closed-loop injection of the hybrid compensation current. Experiments show that the hybrid framework effectively compensates the unmodeled disturbance through the data model while maintaining the physical interpretability of the mechanistic model, which provides a new idea for motor performance optimization under complex working conditions.

Keywords: permanent magnet synchronous linear motor; force ripple; data model; mechanism model; force ripple suppression algorithm (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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