Component integrated multidisciplinary design automation of electric machines - a systematic approach

This dissertation presents a systematic framework for the component integrated multidisci- plinary design automation (MDDA) of electric machines. It addresses the challenges in the design process of electric motors, which are increasingly complex due to multidisciplinary interac- tions and stringent performance requirements.The study emphasizes the necessity of integrating various engineering domains in the design process, such as electromagnetic, thermal, structural, and manufacturing considerations, to enhance the efficiency and effectiveness of electric machine design. The research commences with an exploration of existing MDDA approaches and their limited application in electric machine design using a systematic literature review. The review identifies gaps in the literature concerning a cohesive methodological framework that embraces the multidisciplinarity inherent in electric machine development. Based on these findings, a structured framework is introduced that facilitates the adoption of MDDA practices by pro- viding tools for systematic workflow creation, knowledge formalization, and model reuse. The framework is oriented along a model-based product line engineering approach (MBPLE), allow- ing the configuration of engineering assets for the MDDA workflows based on a feature catalog. The framework guides the engineer to create a workflow specification based on the previously collected information and to select suitable models for the application. In addition, a Component Deep Dive methodology is also proposed, allowing for detailed analysis and design automation of specific components within the electric machine. The proposed approach is accompanied by a specially developed software tool that supports and partially automates the proposed steps for creating an MDDA. The framework is initially validated through a case study involving the design of a truck motor with additively manufactured hairpin windings, demonstrating its practical applicability and effectiveness in specifying and creating MDDA workflows to create and evaluate different motor designs. The proposed framework aims to bridge the gap between existing knowledge and practical implementation, ultimately enhancing the design process of electric machines and contributing to the advancement of digital engineering practices in this field. Future work will focus on refining the framework and exploring its versatility across diverse electric machine applications.