Optimization of an Electric Motor Across Multiple Physics Domains

When considering optimization of a new electric motor design, designers will often work within a single physics domain, the effects of changes primarily aimed at improving a single variety of result, thermal, electromagnetic, etc. In reality, when a change is made to a design it can affect performance in many different ways but it can be difficult to take into account all these effects in a single simulation. Yet, these different domains interact in the real world, for instance as an electric motor heats up, it’s performance characteristics change as the material properties of its components change.

The goal of this presentation will be to demonstrate how we can construct automated multi-physics simulations appropriate for the optimization of an electric motor. By coupling electromagnetic results to thermal simulations, a better understanding of the motor performance vs temperature profile can be established. By applying an optimization loop to coupled simulation a designer can ensure maximum performance is maintained both from a electromagnetic and thermal standpoint. Attendees will be introduced to the coupled electromagnetic-thermal workflow, and to running optimization for performance in both physics’ domains.

The approach: A base model for the new motor design will be built and the geometry parameterized in anticipation of the application of optimization later. Initially an electromagnetic simulation can be run to determine the performance characteristics of the motor without thermal effects. Using a basic coupled electromagnetic-thermal solution without cooling effects we can quickly identify areas in need of cooling and design a parameterized cooling solution to match. Running the coupled simulation again with active cooling will allow observation of how thermal changes affect the performance of the motor. With the geometry parameterized and electromagnetic-thermal coupling established we can close the loop with an optimization tool to automate design changes.

The benefit: By being able to easily couple electromagnetic results to a thermal solution, a designer can quickly predict thermal and performance concerns early in the design process. By applying intelligent optimization, the detailed design adjustment can be offloaded, keeping the designer’s attention on making design decisions rather than adjusting simulations, and accelerating the development cycle. Optimization can also be used in conjunction with costing. In high volume environment management usually asks for a lower cost, medium cost, and higher cost product. With optimization we can add constraints that are tied to costing and it can be as simple as prices of material from an excel spreadsheet tied as part of the optimization process.



Anthony Lowther

Electromagnetics Specialist
Maya HTT