Multi-Variable Multi-Objective Optimization Algorithm for Optimal Design of PMa-SynRM for Electric Bicycle Traction Motor
| Autor: | Kyung-Pyo Yi, Dong-Kuk Lim, Ji-Chang Son |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Electric machine
Optimal design business.product_category Optimization problem Computer science Chemical technology Process Chemistry and Technology Crossover Bioengineering TP1-1185 design optimization finite element analysis Pattern search Finite element method Traction motor Chemistry Control theory heuristic algorithms Genetic algorithm Chemical Engineering (miscellaneous) business QD1-999 permanent magnet motors |
| Zdroj: | Processes Volume 9 Issue 11 Processes, Vol 9, Iss 1901, p 1901 (2021) |
| ISSN: | 2227-9717 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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