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.

有人担心重型车辆和航空的极端要求将使它们在运输部门的电气化中被抛在后面，成为最重要的温室气体排放者。工程师广泛使用有限元方法来分析和改进电机的性能，但需要具有线性（或接近）时间复杂度的新的高度可扩展的方法来使极端规模模型可行。本文介绍了使用 FEniCSx 的 3D 永磁同步电机模型，FEniCSx 是一种专为大规模高效计算和数据处理而设计的有限元平台。该模型展示了与 Ansys Maxwell 中构建的验证模型相当的磁通密度分布，电机静态区域的最大偏差为 7%。求解最大的网格，包含超过 800 万个单元，在 512 个进程中显示了 198 个加速。使用预条件 Krylov 子空间方法求解系统，所需内存比直接求解少 92%。预计基于这种方法的进步将使系统级多物理场仿真在电机开发中变得可行。这种能力可以提供将电力推进系统带入大型车辆所需的接近现实世界的精度。