A Review of Friction Stir Welding and Machine Learning for Dissimilar Aluminium Alloy Joints in EV

The development in the electric vehicles (EVs) is tremendous in the modern-day transportation sector. The developments in this cutting-edge technology have resulted in modern vehicles in both transportation and logistics sector.  The fast-growing electric vehicles have raised the demand of light-weight battery-tray structures made of high-performance aluminium alloys. Aluminium alloys play a vital role in automobile applications for its superior inherent properties. The combination of alloys such as AA5083/AA6082 and AA6061/AA7075 provide possibilities to achieve a balance between strength, corrosion resistance, formability and cost. Friction Stir Welding (FSW) has become a favored solid-state joining method for these alloys, as it decreases fusion-related defects and results in refined microstructures. At the same time, machine learning methods are increasingly applied to predict weld quality and optimize process parameters. This review focuses on recent progress in FSW of dissimilar aluminum alloys for EV battery trays, covering process parameters, mechanical properties, microstructural changes, and machine-learning-based modelling.