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Design optimisation of Permanent Magnet Synchronous Motor for electric vehicles traction using the Bees Algorithm

Braiwish, N. Y., Anayi, F. J., Fahmy, Ashraf and Eldukhri, E. E. 2014. Design optimisation of Permanent Magnet Synchronous Motor for electric vehicles traction using the Bees Algorithm. Presented at: 49th International Universities Power Engineering Conference (UPEC), Cluj-Napoca, Romania, 2-5 September 2014. Power Engineering Conference (UPEC), 2014 49th International Universities. IEEE, pp. 1-5. 10.1109/UPEC.2014.6934742

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Abstract

Electric machines designs for traction application are concerned with paying particular attention to power density and efficiency. Therefore, this paper is focused on applying Bees algorithm (BA) for optimal design of Brushless Permanent Magnet Synchronous Motor (BLPMSM) for propulsion application. The analytical approach for the motor magnetic circuit is performed using the radial instantaneous magnetic field distribution in the airgap under specified loading condition; taking into account the magnetic core saturation and motor overall performance. The design aims to maximize the power density. Therefore, the optimisation objective function is formed to minimise motor weight and maximise efficiency. While the Bees Algorithm (BA) is applied to search for the optimum design parameters; the optimised design is then verified using Finite Element Method (FEM). Comparing with an existing machine, called here basic motor; the obtained results show that motor weight can be reduced by approximately 20%, while motor output power is kept constant. As the motor is designed for traction applications, the characteristics of the developed torque and speed were investigated under different gearing levels using magnetic gearing technique, the efficiency shows improvements in comparison to the basic motor.

Item Type: Conference or Workshop Item (Paper)
Date Type: Publication
Status: Published
Schools: Centre for Advanced Manufacturing Systems At Cardiff (CAMSAC)
Business (Including Economics)
Engineering
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Publisher: IEEE
ISBN: 9781479965564
Last Modified: 09 Oct 2019 13:59
URI: http://orca-mwe.cf.ac.uk/id/eprint/69251

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