BLACK BOX EFFICIENCY MODELLING OF AN ELECTRIC DRIVE UNIT UTILIZING METHODS OF MACHINE LEARNING
Lukas BAUER
lukas.bauer@hs-aalen.deAalen University, Institute for Drive Technology (Germany)
Leon STÜTZ
Aalen University, Institute for Drive Technology (Germany)
Markus KLEY
Aalen University, Institute for Drive Technolog (Germany)
Abstract
The increasing electrification of powertrains leads to increased demands for the test technology to ensure the required functions. For conventional test rigs in particular, it is necessary to have knowledge of the test technology's capabilities that can be applied in practical testing. Modelling enables early knowledge of the test rigs dynamic capabilities and the feasibility of planned testing scenarios. This paper describes the modelling of complex subsystems by experimental modelling with artificial neural networks taking transmission efficiency as an example. For data generation, the experimental design and execution is described. The generated data is pre-processed with suitable methods and optimized for the neural networks. Modelling is executed with different variants of the inputs as well as different algorithms. The variants compare and compete with each other. The most suitable variant is validated using statistical methods and other adequate techniques. The result represents reality well and enables the performance investigation of the test systems in a realistic manner.
Keywords:
electromobility, powertrain, electric drives, artificial neural network, efficiency modellingReferences
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Authors
Lukas BAUERlukas.bauer@hs-aalen.de
Aalen University, Institute for Drive Technology Germany
Authors
Leon STÜTZAalen University, Institute for Drive Technology Germany
Authors
Markus KLEYAalen University, Institute for Drive Technolog Germany
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