Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
184 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
45 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Optimal Design of Electric Machine with Efficient Handling of Constraints and Surrogate Assistance (2206.01695v1)

Published 3 Jun 2022 in cs.NE

Abstract: Electric machine design optimization is a computationally expensive multi-objective optimization problem. While the objectives require time-consuming finite element analysis, optimization constraints can often be based on mathematical expressions, such as geometric constraints. This article investigates this optimization problem of mixed computationally expensive nature by proposing an optimization method incorporated into a popularly-used evolutionary multi-objective optimization algorithm - NSGA-II. The proposed method exploits the inexpensiveness of geometric constraints to generate feasible designs by using a custom repair operator. The proposed method also addresses the time-consuming objective functions by incorporating surrogate models for predicting machine performance. The article successfully establishes the superiority of the proposed method over the conventional optimization approach. This study clearly demonstrates how a complex engineering design can be optimized for multiple objectives and constraints requiring heterogeneous evaluation times and optimal solutions can be analyzed to select a single preferred solution and importantly harnessed to reveal vital design features common to optimal solutions as design principles.

Citations (3)

Summary

We haven't generated a summary for this paper yet.