# Model Order Reduction for Rotating Electrical Machines

## TL;DR

This paper develops an adaptive model order reduction method using proper orthogonal decomposition for simulating non-symmetric rotating electrical machines efficiently, with error certification and demonstrated effectiveness.

## Contribution

It introduces an adaptive reduction technique specifically tailored for non-symmetric machines, addressing challenges not covered by existing symmetric models.

## Key findings

- Effective reduction of simulation costs for non-symmetric machines
- Error estimator certifies solution accuracy
- Numerical examples validate the method's efficiency

## Abstract

The simulation of electric rotating machines is both computationally expensive and memory intensive. To overcome these costs, model order reduction techniques can be applied. The focus of this contribution is especially on machines that contain non-symmetric components. These are usually introduced during the mass production process and are modeled by small perturbations in the geometry (e.g., eccentricity) or the material parameters. While model order reduction for symmetric machines is clear and does not need special treatment, the non-symmetric setting adds additional challenges. An adaptive strategy based on proper orthogonal decomposition is developed to overcome these difficulties. Equipped with an a posteriori error estimator the obtained solution is certified. Numerical examples are presented to demonstrate the effectiveness of the proposed method.