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Multi-Variable Multi-Objective Optimization Algorithm for Optimal Design of PMa-SynRM for Electric Bicycle Traction Motor

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Abstract
In this paper, internal division point genetic algorithm (IDP-GA) was proposed to lessen the computational burden of multi-variable multi-objective optimization problem using finite element analysis such as optimal design of electric bicycles. The IDP-GA could consider various objectives with normalized weighted sum method and could reduce the number of function calls with novel crossover strategy and vector-based pattern search method. The superiority of the proposed algorithm was verified by comparing performances with conventional optimization method at two mathematical test functions. Finally, the applicability of the IDP-GA in practical electric machine design was verified by successfully deriving an improved design of electric bicycle propulsion motor.
Author(s)
손지창이경표임동국
Issued Date
2021
Type
Article
Keyword
design optimizationfinite element analysisheuristic algorithmspermanentmagnet motors
DOI
10.3390/pr9111901
URI
https://oak.ulsan.ac.kr/handle/2021.oak/8826
https://ulsan-primo.hosted.exlibrisgroup.com/primo-explore/fulldisplay?docid=TN_cdi_doaj_primary_oai_doaj_org_article_1c0bb077b4b044e9a561f6679d5990fc&context=PC&vid=ULSAN&lang=ko_KR&search_scope=default_scope&adaptor=primo_central_multiple_fe&tab=default_tab&query=any,contains,Multi-Variable%20Multi-Objective%20Optimization%20Algorithm%20for%20Optimal%20Design%20of%20PMa-SynRM%20for%20Electric%20Bicycle%20Traction%20Motor&offset=0&pcAvailability=true
Publisher
PROCESSES
Location
스위스
Language
영어
ISSN
2227-9717
Citation Volume
9
Citation Number
11
Citation Start Page
1901
Citation End Page
1901
Appears in Collections:
Engineering > Aerospace Engineering
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