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2023 | OriginalPaper | Chapter

AI-Based Performance Prediction and Its Application on the Design and Simulation of Cooling Plates for Battery Electric Vehicles

Authors : Niklas Klinke, Stefan Buchkremer, Lutz-Eike Elend, Maksym Kalaidov, Thomas von Tschammer

Published in: Future Automotive Production Conference 2022

Publisher: Springer Fachmedien Wiesbaden

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Abstract

With the increasing focus on the electrification of personal mobility, shortened development cycles with high cost pressure have to be managed quicker than ever in the Automotive Industry at minimal development cost. As a global automotive supplier, Mubea develops novel manufacturing technologies for new products in the electric powertrain. One example in the battery case of battery electric vehicles is the thermal management system of the traction batteries - a key factor in the battery case. As a new production technology for this product, the Mubea Rollbonding Process of aluminum offers several advantages, such as a high design freedom of the channel structure. For the product development – even though Mubea consequently makes use of automated simulation workflows – the turn-around time of a single CFD performance evaluation is still high. Therefore, our goal is to use all the historic simulation results from past projects to build a predictive model that allows the prediction of simulation results in real-time. However, given the high freedom in the design space allowed by the Rollbonding process, standard Machine Learning approaches, based on parameters, are not suitable. Hence, there is the need to directly process 3D geometries as such. Using historical engineering data, the unique deep learning approach of Neural Concept is able to predict unseen designs in seconds rather than hours, directly from the raw CAD file. This innovative approach allows Mubea to iterate faster and shorten the response time on customer enquiries. In conjunction with other design disciplines and manufacturing data, we look forward to have not only an AI-based design evaluation but also a tolerance-aware design optimization. In this paper we present an innovative strategy to utilize historic simulation results, and the corresponding 3D geometries, to predict the performance of new designs instantaneously. After explaining the underlying approach, first results are discussed. It can be shown that with as little as 100 training samples, this approach is able to deliver predictions with sufficient accuracy and over 90 % of lead-time reduction. Finally, we explain how Neural Concept and Mubea are collaborating to embed this approach in the Mubea design and simulation environment.

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Literature
1.
go back to reference Bralla, J.G.: Handbook of manufacturing processes. Industrial Press Inc., U.S. (ISBN: 978-0-8311-3179-1) Bralla, J.G.: Handbook of manufacturing processes. Industrial Press Inc., U.S. (ISBN: 978-0-8311-3179-1)
2.
go back to reference Bay, N., Clemensen, C., Juelstorp, O., Wanheim, T.: Bond strength in cold roll bonding. CIRP Ann. 34(1), 221–224 (1985)CrossRef Bay, N., Clemensen, C., Juelstorp, O., Wanheim, T.: Bond strength in cold roll bonding. CIRP Ann. 34(1), 221–224 (1985)CrossRef
3.
go back to reference Klinke, N.: The use of HPC in optimal design of TRB lightweight vehicle components. In: 8th european altair technology conference, Paris, France, 29 Sept.–1 Oct. 2015 Klinke, N.: The use of HPC in optimal design of TRB lightweight vehicle components. In: 8th european altair technology conference, Paris, France, 29 Sept.–1 Oct. 2015
4.
go back to reference Ryberg, A.-B.: Metamodel-based design optimization—a multidisciplinary approach. Dissertation, Linköping University (2013) Ryberg, A.-B.: Metamodel-based design optimization—a multidisciplinary approach. Dissertation, Linköping University (2013)
5.
go back to reference Kayvantash, K., Thiam, A.-T., Ryckelynck, D., Chaabane, S. B., Touzeau, J., Ravier, P.: Model reduction techniques for LS-Dyna ALE and crash applications. In: 10th LS-Dyna conference, Würzburg, Germany, 15–17 June 2015 Kayvantash, K., Thiam, A.-T., Ryckelynck, D., Chaabane, S. B., Touzeau, J., Ravier, P.: Model reduction techniques for LS-Dyna ALE and crash applications. In: 10th LS-Dyna conference, Würzburg, Germany, 15–17 June 2015
6.
go back to reference Astrid, P.: Reduction of process simulation models: a proper orthogonal decomposition approach. Dissertation, Eindhoven University of Technology (2004) Astrid, P.: Reduction of process simulation models: a proper orthogonal decomposition approach. Dissertation, Eindhoven University of Technology (2004)
7.
go back to reference Frenzel, M., Ollar, J., Büttner, C., Finotto, V. C., Fliesser, M.: Automotive crashworthiness optimisation using machine learning to emulate engineering expertise. In: 14th World congress of structural and multidisciplinary optimization, Boulder, USA, 13–18 June 2021 Frenzel, M., Ollar, J., Büttner, C., Finotto, V. C., Fliesser, M.: Automotive crashworthiness optimisation using machine learning to emulate engineering expertise. In: 14th World congress of structural and multidisciplinary optimization, Boulder, USA, 13–18 June 2021
8.
go back to reference Baque, P., Remelli, E., Fleuret, F., Fau, P.: Geodesic convolutional shape optimization. In: Proceedings of the 35th international conference on machine learning. Stockholm, Schweden (2018) Baque, P., Remelli, E., Fleuret, F., Fau, P.: Geodesic convolutional shape optimization. In: Proceedings of the 35th international conference on machine learning. Stockholm, Schweden (2018)
Metadata
Title
AI-Based Performance Prediction and Its Application on the Design and Simulation of Cooling Plates for Battery Electric Vehicles
Authors
Niklas Klinke
Stefan Buchkremer
Lutz-Eike Elend
Maksym Kalaidov
Thomas von Tschammer
Copyright Year
2023
DOI
https://doi.org/10.1007/978-3-658-39928-3_15

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