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Optimization design of brushless DC motor based on improved JAYA algorithm.

Yuan Cheng¹, Xueli Lyu², Shasha Mao¹

¹School of Control Engineering, Wuxi Institute of Technology, Wuxi, 214121, China.

Scientific Reports

|March 5, 2024

Summary

This summary is machine-generated.

An improved JAYA algorithm optimizes brushless DC motor parameters, boosting average efficiency to 95.3% and enhancing industrial application value. This method ensures faster convergence and superior performance over existing algorithms.

Keywords:

Brushless DC motor JAYA algorithm Mathematical model Optimization problems Parameter optimization

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Area of Science:

Electrical Engineering
Optimization Algorithms
Industrial Automation

Background:

Brushless DC motors are crucial in industrial production due to their efficiency and low noise.
Optimizing these motors is key to reducing costs and improving performance.
Existing optimization methods may lack efficiency or convergence speed.

Purpose of the Study:

To enhance the operational efficiency and reduce the cost of brushless DC motors.
To introduce and validate an improved JAYA algorithm for motor parameter optimization.
To achieve optimal electromagnetic structure parameters and efficiency calculations.

Main Methods:

Introduction of the JAYA algorithm for brushless DC motor parameter optimization.
Improvement of JAYA algorithm's population diversity using an empirical learning strategy.
Integration of an adaptive strategy to balance development and search capabilities for enhanced convergence.
Validation through unimodal and multimodal function operations and comparison with other algorithms.

Main Results:

The optimized brushless DC motor achieved an average efficiency of 94.48%, with a maximum of 95.3%.
The adaptive JAYA algorithm demonstrated faster convergence, reaching global optimum in ~40 iterations.
Achieved 5-12 percentage points higher efficiency compared to three other algorithms.
Optimal motor parameters closely matched theoretical values, satisfying all constraints.

Conclusions:

The adaptive JAYA algorithm effectively optimizes brushless DC motor parameters, significantly improving efficiency.
This optimization enhances the economic value of brushless DC motors in industrial production and applications.
The method provides a stable, accurate, and efficient approach for complex motor design optimization.