Artificial intelligence-based springback compensation of EV motor component

Abstract

The hairpin is a crucial component of the drive motor of an electric vehicle, consisting of a copper coil and a very thin enamel layer. It is manufactured using successive forming processes due to its complex shape. After the forming processes, springback is inevitably observed, which causes critical issues in fabricating the drive motor. Compensating springback is a time and cost-inefficient process, and a new process is required for a cost-efficient forming process. In this research, an intelligent forming process has been proposed for springback compensation of hairpin forming by applying Artificial Intelligence to the forming process. The key parameters for the AI are the dimensions of the copper coil, including bobbin information, material property variance in a coil bobbin, punch stroke, and amount of springback. As a preliminary design, the data set has been constructed through the finite element simulation. For the springback compensation, punch stroke was optimized with the trained AI and optimization algorithm. The results show that AI could play a key role in solving the manufacturing issue.