Back to Search
Start Over
Computationally Efficient Tolerance Analysis of the Cogging Torque of Brushless PMSMs
- Source :
- IEEE Transactions on Industry Applications. 53:3387-3393
- Publication Year :
- 2017
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2017.
-
Abstract
- This paper investigates the impact of tolerances related to permanent magnets on the cogging torque performance of Permanent magnet synchronous machines (PMSMs). These machines usually show a considerable sensitivity regarding tolerances for geometric dimensions and material characteristics. A consistent approach is presented in order to minimize the computational effort for evaluating the sensitivity, robustness, or reliability. Thereby, design of experiments is used to minimize the required number of finite element simulations. In this work, a Box–Behnken-based approach is considered. Subsequently, a surrogate modeling technique based on a second-order equation is applied. As a consequence, a reduction of the computational cost by 96% is achieved. The obtained results are compared with outcomes solely derived by means of finite element computations and very good agreement is observed. This is illustrated by providing the probability distribution of the cogging torque for the considered machine design. In addition, the cumulative distribution is presented, which usually is applied for analyzing the reliability. Considering the analysis of the impact of tolerances as part of optimization scenarios increases the number of designs to be analyzed by at least one degree of magnitude. The obtained results look promising for achieving this at feasible computational cost.
- Subjects :
- 010302 applied physics
Engineering
Mathematical optimization
Tolerance analysis
business.industry
Design of experiments
Cumulative distribution function
020208 electrical & electronic engineering
Cogging torque
02 engineering and technology
01 natural sciences
Industrial and Manufacturing Engineering
Finite element method
Control and Systems Engineering
Robustness (computer science)
0103 physical sciences
0202 electrical engineering, electronic engineering, information engineering
Torque
Probability distribution
Electrical and Electronic Engineering
business
Subjects
Details
- ISSN :
- 19399367 and 00939994
- Volume :
- 53
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Industry Applications
- Accession number :
- edsair.doi...........c6637186957b492b024450dc7d801186