@inproceedings{adcdfe8caa4340d0a2272b0006c47d62,
title = "Optimized sizing of IPM machines for automotive traction application",
abstract = "This paper presents the implementation of an electrical machine design tool including its overall architecture. The tool is flexible and can be employed for the sizing of any permanent magnet synchronous machine. The case study considered in this work is the design of V-shaped interior permanent magnet synchronous machine for automotive applications. The preliminary design stage is considered with the aim of selecting the optimum machine pole pairs number and rotation speed. A multi-objective genetic algorithm is linked to the design tool and adopted to maximize the machine power density in terms of kW/L as well as to minimize the machine cost. The outcomes of this work are showing the variation of the above objective functions with respect to the pole-pair number and gearbox ratio as well as their effect on the machine efficiency.",
keywords = "Automotive, Genetic algorithm, High speed electrical machines, Optimization design, Permanent magnet synchronous machine",
author = "Giorgio Valente and David Gerada and Michele Degano and Christopher Gerada and John Foulsham and Daniel Beeby",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 11th IEEE International Electric Machines and Drives Conference, IEMDC 2019 ; Conference date: 12-05-2019 Through 15-05-2019",
year = "2019",
month = may,
doi = "10.1109/IEMDC.2019.8785245",
language = "English",
series = "2019 IEEE International Electric Machines and Drives Conference, IEMDC 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "970--975",
booktitle = "2019 IEEE International Electric Machines and Drives Conference, IEMDC 2019",
address = "United States",
}