Model Order Reduction for Rotating Electrical Machines
For engineers simulating electric machines with non-symmetric features, this work provides a certified and efficient reduction technique, though it is an incremental improvement over existing methods for symmetric machines.
This paper develops an adaptive model order reduction strategy based on proper orthogonal decomposition for rotating electrical machines with non-symmetric components, such as those caused by manufacturing imperfections. The method includes an a posteriori error estimator to certify the solution, and numerical examples demonstrate its effectiveness.
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.