Design Optimization of Axial Flux Surface Mounted Permanent Magnet Brushless DC Motor For Electrical Vehicle Based on Genetic Algorithm

Authors

1 Electrical Engineering Department, Institute of Technology, Nirma University, Ahmedabad, India

2 Electrical Engineering Department, Government Engineering College, Bhuj, India

Abstract

This paper presents the design optimization of axial flux surface mounted Permanent Magnet Brushless DC motor based on genetic algorithm for an electrical vehicle application. The rating of the motor calculated form vehicle dynamics is 250 W, 150 rpm. The axial flux surface mounted Permanent Magnet Brushless DC (PMBLDC) motor was designed to fit in the rim of the wheel. There are several design variables e.g. air gap flux density, slot loading, magnet spacer width, ratio of outer to inner diameter, air gap length, current density and space factor). The main contribution in the present work is to propose the best combination of design variables obtained using genetic algorithm (GA) optimization technique and design of motor based on optimized design variables. Final validation is carried out with the help of 3-D finite element analysis (FEA) for GA based constraint and unconstraint design. The entire procedure based on GA is explained with the help of block diagram. Efficiency of the axial flux surface mounted PMBLDC motor is enhanced from 88.15 to 91.5 % using GA based design optimization. Proposed optimization technique and methodology will be useful for performance improvement of any nonlinear engineering design involving various design variables for specific application.

Keywords


1.     Afjei, E., Hashemipour, O., Saati, M. and Nezamabadi, M., "A new hybrid brushless dc motor/generator without permanent magnet", International Journal of Engineering Transactions B Applications,  Vol. 20, No. 1, (2007), 77-86.
2.     Upadhyay, P., Rajagopal, K. and Singh, B., "Computer aided design of an axial-field permanent magnet brushless dc motor for an electric vehicle", Journal of applied physics,  Vol. 93, No. 10, (2003), 8689-8691.
3.     Ilka, R., Tilaki, A.R., Alamdari, H. and Baghipour, R., "Design optimization of permanent magnet-brushless dc motor using elitist genetic algorithm with minimum loss and maximum power density", Int. J. Mecha. Elecr. Comput. Technol,  Vol. 4, No. 10, (2014), 1169-1185.
4.     Azari, M.N., Samami, M. and Pahnehkolaei, S.A., "Optimal design of a brushless dc motor, by cuckoo optimization algorithm (research note)", International Journal of Engineering-Transactions B: Applications,  Vol. 30, No. 5, (2017), 668-677.
5.     Nair, A. and Rajagopal, K., "Generic model of an electric vehicle for dynamic simulation and performance prediction", in Electrical Machines and Systems (ICEMS), 2010 International Conference on, IEEE., (2010), 753-757.
6.     Sockeel, N., Shi, J., Shahverdi, M. and Mazzola, M., "Sensitivity analysis of the battery model for model predictive control implemented into a plug-in hybrid electric vehicle", in Transportation Electrification Conference and Expo (ITEC), 2017 IEEE, (2017), 493-500.
7.     Bing, L., Huiyong, C., Hongwen, H. and Jiankun, P., "The dynamic matching calculation and simulation for dual-motor driven electric vehicle", in Transportation Electrification Asia-Pacific (ITEC Asia-Pacific), 2014 IEEE Conference and Expo, IEEE., (2014), 1-5.
8.     Hanselman, D.C., "Brushless permanent magnet motor design, New York: McGraw- Hill, (1994) in place of The Writers' Collective, (2003).
9.     Hendershot, J.R. and Miller, T.J.E., "Design of brushless permanent-magnet machines, Oxford Univ. Press, UK, (1994)  in place of Motor Design Books, (2010).
10.   Mahmoudi, A., Kahourzade, S., Rahim, N.A. and Hew, W.P., "Design, analysis, and prototyping of an axial-flux permanent magnet motor based on genetic algorithm and finite-element analysis", IEEE Transactions on Magnetics,  Vol. 49, No. 4, (2013), 1479-1492.