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Journal ArticleDOI

Modeling and Parametric Design of Permanent-Magnet AC Machines Using Computationally Efficient Finite-Element Analysis

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TLDR
The CE-FEA method is presented and applied to a parametric design study for an interior-permanent-magnet machine and significant reduction of simulation times is achieved, permitting a comprehensive search of large design spaces for optimization purposes.
Abstract
Computationally efficient finite-element analysis (FEA) (CE-FEA) fully exploits the symmetries of electric and magnetic circuits of sine-wave current-regulated synchronous machines and yields substantial savings of computational efforts. Motor performance is evaluated through Fourier analysis and a minimum number of magnetostatic solutions. The major steady-state performance indices (average torque, ripple and cogging torque, back-electromotive-force waveforms, and core losses) are satisfactorily estimated as compared with the results of detailed time-stepping (transient) FEA. In this paper, the CE-FEA method is presented and applied to a parametric design study for an interior-permanent-magnet machine. Significant reduction of simulation times is achieved (approximately two orders of magnitude), permitting a comprehensive search of large design spaces for optimization purposes. In this case study, the influence of three design variables, namely, stator tooth width, pole arc, and slot opening, on three performance indices, namely, average torque, efficiency, and full-load torque ripple, is examined, and design trends are derived. One hundred candidate designs are simulated in less than 20 minutes on a state-of-the-art workstation.

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Citations
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Journal ArticleDOI

A Review of Recent Developments in Electrical Machine Design Optimization Methods With a Permanent-Magnet Synchronous Motor Benchmark Study

TL;DR: In this article, the authors systematically cover the significant developments of the last decade, including surrogate modeling of electrical machines and direct and stochastic search algorithms for both single and multi-objective design optimization problems.
Journal ArticleDOI

Novel High-Performance SynRM Design Method: An Easy Approach for A Complicated Rotor Topology

TL;DR: A novel, simple, fast, and systematic design procedure for a SynRM rotor with specific stator structure is developed and presented and can be competitively optimized with respect to an induction machine (IM) by a limited number of finite-element-method sensitivity analysis studies of the macroscopic design parameters.
Journal ArticleDOI

Direct-Driven Interior Magnet Permanent-Magnet Synchronous Motors for a Full Electric Sports Car

TL;DR: The design process of direct-driven permanent-magnet (PM) synchronous machines (PMSMs) for a full electric 4 × 4 sports car is presented and an integer slot stator winding was selected to fully take advantage of the additional reluctance torque.
Journal ArticleDOI

Particle Swarm Optimization Algorithm With Intelligent Particle Number Control for Optimal Design of Electric Machines

TL;DR: A modified particle swarm optimization (PSO) algorithm is proposed, which is an improved version of the conventional PSO algorithm, aiming at minimizing the total harmonic distortion of the back electromotive force (back EMF).
Journal ArticleDOI

Calculation of Magnet Losses in Concentrated-Winding Permanent-Magnet Synchronous Machines Using a Computationally Efficient Finite-Element Method

TL;DR: The proposed hybrid method combines computationally efficient finite-element analysis (CE-FEA) with a new analytical formulation for eddy-current losses in the permanent magnets (PMs) of sine-wave current-regulated brushless synchronous motors.
References
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Book

Multi-Objective Optimization Using Evolutionary Algorithms

TL;DR: This text provides an excellent introduction to the use of evolutionary algorithms in multi-objective optimization, allowing use as a graduate course text or for self-study.
Book

Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series)

TL;DR: This volume explores the differential evolution (DE) algorithm in both principle and practice and is a valuable resource for professionals needing a proven optimizer and for students wanting an evolutionary perspective on global numerical optimization.
Book

Differential Evolution: A Practical Approach to Global Optimization

TL;DR: The differential evolution (DE) algorithm is a practical approach to global numerical optimization which is easy to understand, simple to implement, reliable, and fast as discussed by the authors, which is a valuable resource for professionals needing a proven optimizer and for students wanting an evolutionary perspective on global numerical optimisation.
Journal ArticleDOI

Evolution and Modern Approaches for Thermal Analysis of Electrical Machines

TL;DR: The improvements and the new techniques proposed in the last decade are analyzed in depth and compared in order to highlight the qualities and defects of each.
BookDOI

Finite element analysis of electrical machines

S. J. Salon
TL;DR: The aim of this chapter is to clarify the role of magnetism in the design of Induction Machines and to provide a procedure for integrating magnetism into the model of the motor.
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