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Meta model-based multi-objective optimization of laser welded dissimilar material joints for battery components
University of Skövde, School of Engineering Science.
2024 (English)Independent thesis Advanced level (degree of Master (One Year)), 12 credits / 18 HE creditsStudent thesis
Abstract [en]

During the assembly process of battery packs for electric vehicles, it is crucial to ensure that the cell-to-busbar joints can be produced with high quality, good reliability, and with minimal impact on the individual battery cells. This thesis project investigates the influence of different process parameters on the joint quality for laser welded dissimilar material cell-to-busbar joints. Nickel plated copper and steel plates, joined in an overlap configuration, are used as a simplified geometry, representing a cell-to-busbar joint. By the utilization of artificial neural network-based meta models, trained on numerical results from computational fluid dynamics simulations of the laser welding process, the joint quality is predicted and evaluated. The present thesis investigates how a set of optimized process parameters can be identified for the considered laser welded dissimilar material cell-to-busbar joints, in order to simultaneously maximize the interface width for the joints, and minimize the formation of undercuts and resulting in-process temperatures. NSGA-II is used to efficiently search for trade-off solutions, in an meta model-based multi-objective optimization approach, where the meta models are used to approximate the objectives, corresponding to the joint quality obtained from computational fluid dynamics simulations. With this, the time for one objective evaluation is reduced from approximately 9 hours, when the objectives are evaluated directly from computational fluid dynamics simulations, to only tenths of a second. With the proposed optimization approach, the Pareto-optimal front of trade-off solutions is identified, leading to the selection of three optimal solutions for validation. The validity of the proposed optimization approach, and the selected optimal solutions, are confirmed by means of both physical laser welding experiments and computational fluid dynamics simulations. It is shown that the selected optimal solutions, corresponding to three parameter setups, can be used to produce joints with large interface width and low in-process temperatures, without achieving a full penetration in the lower plate of the joint.

Place, publisher, year, edition, pages
2024. , p. 95
Keywords [en]
Laser welding, cell-to-busbar joints, battery pack assembly, electric vehicles, dissimilar materials, computational fluid dynamics, artificial neural networks, meta models, multiobjective optimization, meta model-based multi-objective optimization
National Category
Mechanical Engineering
Identifiers
URN: urn:nbn:se:his:diva-23967OAI: oai:DiVA.org:his-23967DiVA, id: diva2:1872020
External cooperation
Koenigsegg Automotive AB
Subject / course
Virtual Product Realization
Educational program
Intelligent Automation - Master's Programme, 60 ECTS
Supervisors
Examiners
Available from: 2024-06-17 Created: 2024-06-17 Last updated: 2024-06-17Bibliographically approved

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