Improving switched reluctance motor drive excitation with a gaussian inductance profile in electric vehicles

• Dynamic turn-on/off angle calculation with minimum boundary conditions. • Simultaneously reducing copper losses and torque ripple using Gaussian inductance. • Notable reductions in copper losses and torque ripple without complex algorithms. In this study, an improved Switched Reluctance Motor (SRM) drive excitation based on the Gaussian inductance model is proposed for electric vehicles. Most electric vehicles operate in a transient mode and their electric motor speed is changing instantaneously. In this proposed method, optimal excitation of each motor phase at different speeds is performed by a Gaussian profile in such a way that, in addition to preventing negative torque generation, copper losses in the constant inductance region are avoided. Determining the SRM excitation position in the magnetization and demagnetization region depends on the speed, current and back-EMF. In this method, using the Gaussian method, the angle of turning on and off the phases is adjusted online over a wide range of speeds and at different currents. To evaluate the proposed method, a 12/8 pole SRM was simulated in the MATLAB™/SIMULINK® environment for different speeds. In addition, the proposed method was practically implemented by DSP-board controller TMS320F28335. The simulation and experiment results show that the proposed method is effective in the optimal excitation of each phase and prevents the production of negative torque and undesired vibration at different speeds. Also, in the constant slope inductance region where torque is not produced, current injection is prevented, which leads to a reduction in unwanted copper losses.

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Publication Details

Journal
Electric Power Systems Research
Published
2025-12-02
DOI
https://doi.org/10.1016/j.epsr.2025.112560
Primary Topic
Electric Motor Design and Analysis
Type
article
Field-Weighted Citation Impact
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article

Improving switched reluctance motor drive excitation with a gaussian inductance profile in electric vehicles

M. Divandari, Amangaldi Koochaki, Mostafa Gohari
Electric Power Systems Research
Electric Motor Design and Analysis
article

Improving switched reluctance motor drive excitation with a gaussian inductance profile in electric vehicles

M. Divandari, Amangaldi Koochaki, Mostafa Gohari
article en

Abstract

• Dynamic turn-on/off angle calculation with minimum boundary conditions. • Simultaneously reducing copper losses and torque ripple using Gaussian inductance. • Notable reductions in copper losses and torque ripple without complex algorithms. In this study, an improved Switched Reluctance Motor (SRM) drive excitation based on the Gaussian inductance model is proposed for electric vehicles. Most electric vehicles operate in a transient mode and their electric motor speed is changing instantaneously. In this proposed method, optimal excitation of each motor phase at different speeds is performed by a Gaussian profile in such a way that, in addition to preventing negative torque generation, copper losses in the constant inductance region are avoided. Determining the SRM excitation position in the magnetization and demagnetization region depends on the speed, current and back-EMF. In this method, using the Gaussian method, the angle of turning on and off the phases is adjusted online over a wide range of speeds and at different currents. To evaluate the proposed method, a 12/8 pole SRM was simulated in the MATLAB™/SIMULINK® environment for different speeds. In addition, the proposed method was practically implemented by DSP-board controller TMS320F28335. The simulation and experiment results show that the proposed method is effective in the optimal excitation of each phase and prevents the production of negative torque and undesired vibration at different speeds. Also, in the constant slope inductance region where torque is not produced, current injection is prevented, which leads to a reduction in unwanted copper losses.

Electric Power Systems ResearchVol. 253
Islamic Azad University, Aliabad Katoul (IR)
Openalex Percentile: Top 62%
Electric Motor Design and Analysis
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