Optimal electromagnetic-thermo-mechanical integrated design for surface mount permanent magnet machines considering load profiles

Most existing design and optimization methods treat the electromagnetic, thermal and mechanical designs separately. As a result, the effects of power supply, machine control, load profile, thermal effects and materials are not fully integrated and accounted for, which often leads to over- or under- design. This paper proposes an innovative and computationally efficient approach which integrates the electromagnetic and thermo-mechanical design for Surface Mount Permanent Magnet (SMPM) machines. Particle Swarm Optimization (PSO) is part of this integrated process to efficiently find designs which optimize certain requirements, such as weight, efficiency, etc. for example. The effects of power supplies, machine controls, load profiles, thermal effects and materials can thus all be considered systematically in the proposed multi-physics design approach.

[1]  Mokhtar S. Bazaraa,et al.  Nonlinear Programming: Theory and Algorithms , 1993 .

[2]  C. Espanet,et al.  Optimal design of an high torque DC brushless in-wheel motor , 2003, IEEE International Electric Machines and Drives Conference, 2003. IEMDC'03..

[3]  Thomas G. Habetler,et al.  Multi-objective design optimization of Surface Mount Permanent Magnet machine with particle swarm intelligence , 2008, 2008 IEEE Swarm Intelligence Symposium.

[4]  Z. Zhu,et al.  Instantaneous magnetic field distribution in brushless permanent magnet DC motors. I. Open-circuit field , 1993 .

[5]  Mokhtar S. Bazaraa,et al.  Nonlinear Programming: Theory and Algorithms, 3/E. , 2019 .

[6]  Alice E. Smith,et al.  Penalty functions , 1996 .

[7]  T.G. Habetler,et al.  Method for multi-objective optimized designs of Surface Mount Permanent Magnet motors with concentrated or distributed stator windings , 2009, 2009 IEEE International Electric Machines and Drives Conference.

[8]  N. Bianchi,et al.  Design criteria of high efficiency SPM synchronous motors , 2003, IEEE International Electric Machines and Drives Conference, 2003. IEMDC'03..

[9]  Phil Mellor,et al.  The use of a genetic algorithm in the design optimisation of a brushless DC permanent magnet machine rotor , 2004 .

[10]  S. Andrew Semidey,et al.  Generic electric machine thermal model development using an automated finite difference approach , 2009, 2009 IEEE International Electric Machines and Drives Conference.

[11]  Chung-Lung Chen,et al.  Thermal management of AC induction motors using computational fluid dynamics modeling , 1999, IEEE International Electric Machines and Drives Conference. IEMDC'99. Proceedings (Cat. No.99EX272).

[12]  Y. Rahmat-Samii,et al.  Particle swarm optimization in electromagnetics , 2004, IEEE Transactions on Antennas and Propagation.

[13]  Frank P. Incropera,et al.  Fundamentals of Heat and Mass Transfer , 1981 .

[14]  Z. Zhu,et al.  Instantaneous magnetic field distribution in permanent magnet brushless DC motors. IV. Magnetic field on load , 1993 .

[15]  Nicola Bianchi,et al.  Design criteria for high-efficiency SPM synchronous motors , 2006 .

[16]  N. Bianchi,et al.  Brushless DC motor design: an optimisation procedure based on genetic algorithms , 1997 .

[17]  T.G. Habetler,et al.  A useful multi-objective optimization design method for PM motors considering nonlinear material properties , 2009, 2009 IEEE Energy Conversion Congress and Exposition.

[18]  Min Dai,et al.  Design and analysis of 42-V permanent-magnet generator for automotive applications , 2003 .