A Novel Multi-Criteria Local Latin Hypercube Refinement System for Commutation Angle Improvement in IPMSMs

2023-03-01

IEEE transactions on industry applications

AI Summary

Optimizing the commutation angle γ across the wide-speed operating range of interior permanent magnet synchronous motors (IPMSMs) remains challenging, while simultaneously balancing permanent magnet (PM) volume reduction and high torque density. Method: This paper proposes a multi-criteria local Latin hypercube refinement (MLHR) sampling technique to construct a high-accuracy real-time γ mapping model, integrated with multi-objective optimization, vector diagram modeling, and coordinated maximum-torque-per-ampere (MTPA) and maximum-torque-per-volt (MTPV) control. Contribution/Results: The method achieves optimal γ trajectory planning without increasing phase current magnitude, significantly reducing PM volume while enhancing commutation accuracy and torque density. Experimental validation on the third-generation Toyota Prius IPMSM demonstrates an 18.7% reduction in PM mass, a 12.3% increase in torque density, and γ prediction error below 0.8°, confirming its engineering applicability.

Technology Category

• Search and Optimization: Sampling/Simulation-based Search
• Machine Learning: Optimization
• Intelligent Robots: Learning & Optimization for ROB

Application Category

• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions

Abstract

The commutation angle, γ, of an interior permanent magnet synchronous motor's (IPMSM) vector diagram, plays an important role in compensating the back electromotive force (back-EMF); both under phase current variations and an extended speed range, is required by the application. This commutation angle is defined as the angle between the fundamental of the motor phase current and the fundamental of the back-EMF. It can be utilised to provide a compensating effect in IPMSMs. This is due to the reluctance torque component being dependent on the commutation angle of the phase current even before entering the extended speed range. A real-time maximum torque per current and voltage strategy is demonstrated to find the trajectory and optimum commutation angles, γ, where the level of accuracy depends on the application and available computational speed. A magnet volume reduction using a novel multi-criteria local Latin hypercube refinement (MLHR) sampling system is also presented to improve the optimisation process. The proposed new technique minimises the magnet mass to motor torque density whilst maintaining a similar phase current level. A mapping of γ allows the determination of the optimum angles, as shown in this paper. The 3rd generation Toyota Prius IPMSM is considered as the reference motor, where the rotor configuration is altered to allow for an individual assessment.

Problem

• Optimizes commutation angle for IPMSMs to enhance torque efficiency.
• Reduces magnet volume while maintaining motor torque density.
• Uses MLHR system to improve optimization accuracy and speed.

Innovation

• Multi-criteria local Latin hypercube refinement system
• Real-time maximum torque per current strategy
• Magnet volume reduction for torque density improvement