Modelling a permanent magnet synchronous motor in FEniCSx for parallel high-performance simulations

There are concerns that the extreme requirements of heavy-duty vehicles and aviation will see them left behind in the electrification of the transport sector, becoming the most significant emitters of greenhouse gases. Engineers extensively use the finite element method to analyse and improve the pe...

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Vydáno v:Finite elements in analysis and design Ročník 204; s. 103755
Hlavní autoři: McDonagh, James, Palumbo, Nunzio, Cherukunnath, Neeraj, Dimov, Nikolay, Yousif, Nada
Médium: Journal Article
Jazyk:angličtina
Vydáno: Amsterdam Elsevier B.V 01.07.2022
Elsevier BV
Témata:
Electric machine
Electric propulsion
Electrification
Emitters
FEniCS
Finite element method
Flux density
Greenhouse gases
Heavy vehicles
High-performance computing
Magnetic flux
Maxwell’s equations
Open-source software
Performance enhancement
Permanent magnets
Propulsion systems
Scale models
Subspace methods
Synchronous motors
Transportation industry
Finite element method
Open-source software
FEniCS
Electric machine
High-performance computing
Maxwell’s equations
ISSN:0168-874X, 1872-6925
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Shrnutí:There are concerns that the extreme requirements of heavy-duty vehicles and aviation will see them left behind in the electrification of the transport sector, becoming the most significant emitters of greenhouse gases. Engineers extensively use the finite element method to analyse and improve the performance of electric machines, but new highly scalable methods with a linear (or near) time complexity are required to make extreme-scale models viable. This paper introduces a three-dimensional permanent magnet synchronous motor model using FEniCSx, a finite element platform tailored for efficient computing and data handling at scale. The model demonstrates comparable magnetic flux density distributions to a verification model built in Ansys Maxwell with a maximum deviation of 7% in the motor’s static regions. Solving the largest mesh, comprising over eight million cells, displayed a speedup of 198 at 512 processes. A preconditioned Krylov subspace method was used to solve the system, requiring 92% less memory than a direct solution. It is expected that advances built on this approach will allow system-level multiphysics simulations to become feasible within electric machine development. This capability could provide the near real-world accuracy needed to bring electric propulsion systems to large vehicles. •Stable and scalable electric machine analysis is possible using iterative methods.•Open-source solvers can leverage the advantages of high-performance computing.•The parallel performance of FEniCSx exceeds an established electromagnetic code.
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ISSN:0168-874X
1872-6925
DOI:10.1016/j.finel.2022.103755