Torque Enhancement of BLDC Motor Considering Iron Loss: Modeling and Compensation Approach

This paper explores the effects of iron loss on Permanent Magnet Brushless DC motor (BLDCM) performance and compares two of the most popular compensation techniques to improve torque. Iron loss significantly impacts the efficiency and performance of BLDC motors, particularly in high-speed applications. By incorporating iron loss into a detailed motor model, the study aims to accurately predict performance and develop effective compensation strategies. Simulation results validate the comparison of the proposed methods namely Model Predictive Control (MPC) and Field Oriented Control (FOC) based on improvements in torque output. The findings demonstrate the robustness and accuracy of the Model Predictive Control (MPC) system over conventional Field Oriented Control (FOC) under varying load and speed conditions. This research underscores the importance of considering iron losses for optimizing BLDC motor efficiency, especially in electric vehicle applications.

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Publication Details

Published
2024-12-18
DOI
https://doi.org/10.1109/pedes61459.2024.10961329
Citations
6
Primary Topic
Electric Motor Design and Analysis
Type
article
Field-Weighted Citation Impact
1.25
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article

Torque Enhancement of BLDC Motor Considering Iron Loss: Modeling and Compensation Approach

Utkal Ranjan Muduli, Amitesh Prakash, Devara Vijaya Bhaskar, Alok Ranjan
6 citations
Electric Motor Design and Analysis
1.25
article

Torque Enhancement of BLDC Motor Considering Iron Loss: Modeling and Compensation Approach

Utkal Ranjan Muduli, Amitesh Prakash, Devara Vijaya Bhaskar, Alok Ranjan
article en
6 citations

Abstract

This paper explores the effects of iron loss on Permanent Magnet Brushless DC motor (BLDCM) performance and compares two of the most popular compensation techniques to improve torque. Iron loss significantly impacts the efficiency and performance of BLDC motors, particularly in high-speed applications. By incorporating iron loss into a detailed motor model, the study aims to accurately predict performance and develop effective compensation strategies. Simulation results validate the comparison of the proposed methods namely Model Predictive Control (MPC) and Field Oriented Control (FOC) based on improvements in torque output. The findings demonstrate the robustness and accuracy of the Model Predictive Control (MPC) system over conventional Field Oriented Control (FOC) under varying load and speed conditions. This research underscores the importance of considering iron losses for optimizing BLDC motor efficiency, especially in electric vehicle applications.

Khalifa University of Science and Technology (AE), Indian Institute of Technology Dhanbad (IN)
Affordable and clean energy
Openalex Percentile: Top 19%
Electric Motor Design and Analysis
1.25
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