Reliability-Based Design Optimization of a Permanent Magnet Motor Under Manufacturing Tolerance and Temperature Fluctuation

A reliability-based design optimization (RBDO) method is proposed to ensure a given confidence level of output performances of a permanent magnet motor in the presence of operating temperature fluctuation and manufacturing tolerance. To achieve the goal, first, probabilistic distributions of materia...

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Bibliographic Details
Published inIEEE transactions on magnetics Vol. 57; no. 6; pp. 1 - 4
Main Authors Mun, Jaegyeong, Lim, Jongsu, Kwak, Yejin, Kang, Byungsu, Choi, K. K., Kim, Dong-Hun
Format Journal Article
LanguageEnglish
Published New York IEEE 01.06.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Confidence intervals
Design optimization
Design parameters
Electromagnetics (EMs)
Fluctuations
Magnetism
Material properties
Mathematical model
Monte Carlo simulation
Operating temperature
optimization
Optimization techniques
Permanent magnet motors
Permanent magnets
Random variables
Reliability
Reliability engineering
reliability theory
robustness
Safety
Safety factors
Statistical analysis
Synchronous motors
Temperature distribution
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Summary:A reliability-based design optimization (RBDO) method is proposed to ensure a given confidence level of output performances of a permanent magnet motor in the presence of operating temperature fluctuation and manufacturing tolerance. To achieve the goal, first, probabilistic distributions of material properties of motor components are investigated in accordance with the variation in operational temperature. Then, random material parameters and random design variables due to both uncertainties are incorporated into a mathematical formulation of the RBDO, and an optimal design is sought out using the Monte Carlo simulation combined with a highly accurate surrogate model. An interior-type permanent magnet synchronous motor is provided to demonstrate the validity of the proposed method by comparison with the conventional method, which adopts a deterministic optimization technique in conjunction with a safety factor.
ISSN:0018-9464
1941-0069
DOI:10.1109/TMAG.2021.3063161