Laser welding of dissimilar materials - simulation driven optimization of process parameters

Abstract

Laser welding can be used to join dissimilar materials to produce lightweight structures, and electric vehicle battery systems, which are important means of limiting the carbon emissions in the transport industry. Due to the differences in melting temperatures, thermal conductivities, and mutual solubility of dissimilar materials, it is still challenging to create defect-free joints with high mechanical strength, or low contact electrical resistance. In this work, we present a state-of-the-art numerical model of laser welding, developed within the Computational Fluids Dynamics (CFD) paradigm. The multi-physics model simulates melting, flow, and solidification of the alloys and accounts for the laser-material interactions, phase change, temperature and alloy-dependent thermophysical properties, recoil pressure, buoyancy force, and Marangoni effect. The simulation predicts weld penetration depth and width, alloy mixing, as well as the temperature gradient and cooling rate during the solidification that can be further fed into a micro-structure prediction model. The model is coupled with an optimization tool, which iterates over different process parameters to optimize the joint. The methodology is presented for steel to aluminium welding in lap configuration, but it can be used for other materials such as steel-copper, aluminium-copper, or steel-nickel, and in arbitrary geometrical configuration.