A General Framework for Automated Physics-Based Reduced-Order Modeling of Electromechanical Systems

摘要

Physics-based models of electromechanical systems,rnsuch as finite element-based models and/or high-fidelityrnmagnetic equivalent circuits, accurately representrnunderlying magnetic devices. However, these modelsrnusually introduce hundreds to thousands of state variablesrnand are computationally intensive. Moreover, includingrnrelative motion in the physics-based dynamic modeling ofrnelectromechanical systems is not a trivial task. In this paper,rnrelative motion is incorporated in highly accurate full-orderrnmodels that are based on geometrical and material data.rnAutomated linear and nonlinear order-reduction techniquesrnare introduced to mathematically extract the essentialrnsystem dynamics in the desired bandwidth, thus preservingrnboth accuracy and computational efficiency. The resultingrnreduced-order systems are verified using finite elementbasedrnmodels and magnetic equivalent circuits in both timernand frequency domains.