Multi-Objective System Optimization by Means of Evolutionary Algorithms for Electric Powertrain Development: Magna-OPED

Authors

Dipl.-Ing. K. Huber, Magna Powertrain GmbH & Co KG, Lannach; Dr. A. Sorgdrager, Dipl.-Ing. P. Laaber, Magna Powertrain GmbH & Co KG ECS, St. Valentin; Dipl.-Ing. D. Lechleitner, Dipl.-Ing. M. Hofstetter, Graz University of Technology:

Year

2022

Print Info

Production/Publication ÖVK

Summary

In addition to the fulfillment of requirements, a central target during the development of electric drive units is a short development time. To investigate a large solution space within a short time, an automated system optimization method is required. “Magna-OPED" represents such a method and is described in the present work. By consideration of the complex interactions between inverter, electric machine, gearbox and cooling system, optimal electric powertrain systems are generated by means of evolutionary algorithms. The applied multi-objective optimization creates a large number of design variants, which are evaluated by analysis models and rated according to defined design objectives. These objectives in general represent a complex area of conflict in terms of costs, energy efficiency and package integration. The result is a Pareto front, which provides optimal and tailor-made system designs for the specific customer requirements in the early development phase. The proposed method is applied to a case study and a vehicle-integrated prototype based on the optimization results is presented.

ISBN

1920-2323-23-1

Number of pages

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