RSM-DE-ANN method for sensitivity analysis of active material cost in PM motors

Alireza Fatemi, Dan M. Ionel, Nabeel A.O. Demerdash, Steven J. Stretz, Thomas M. Jahns

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations

Abstract

In this paper, a numerical technique is developed for sensitivity analysis of active material cost (AMC) in PM motors with distributed and fractional slot concentrated windings. A comprehensive analysis is carried out to identify how the optimal design rules and proportions of IPM motors with sintered NdFeB magnets vary with respect to the changes in the commodity prices of permanent magnet material, copper, and steel. The sensitivities of the correlations between the design parameters and the AMC with respect to the commodity price ranges are investigated based on response surface methodology (RSM) and large-scale design optimization practice using differential evolution (DE) optimizer. An innovative application of artificial neural network (ANN)-based design optimization is introduced. Multi-objective minimization of cost and losses is pursued for an overall of 200,000 design candidates in 30 different optimization instances subjected to different cost scenarios according to a systematic design of experiments (DOE) procedure. An interesting finding is that, despite common expectations, the average mass of steel in the optimized designs is more sensitive to changes in the commodity prices than the masses of copper and rotor PMs.

Original languageEnglish
Title of host publicationECCE 2016 - IEEE Energy Conversion Congress and Exposition, Proceedings
ISBN (Electronic)9781509007370
DOIs
StatePublished - 2016
Event2016 IEEE Energy Conversion Congress and Exposition, ECCE 2016 - Milwaukee, United States
Duration: Sep 18 2016Sep 22 2016

Publication series

NameECCE 2016 - IEEE Energy Conversion Congress and Exposition, Proceedings

Conference

Conference2016 IEEE Energy Conversion Congress and Exposition, ECCE 2016
Country/TerritoryUnited States
CityMilwaukee
Period9/18/169/22/16

Keywords

  • Active material cost (AMC)
  • artificial neural network (ANN)
  • design optimization
  • permanent magnet (PM) motors
  • response surface methodology (RSM)
  • sensitivity analysis

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Energy Engineering and Power Technology
  • Control and Optimization

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