This study investigated optimal welding conditions for copper hairpin windings using a multi-mode Adjustable Mode Beam (AMB) laser with independently controlled center and peripheral beams. Tensile strength tests and cross-sectional analyses were conducted to evaluate welding quality under various conditions. Improper settings led to weak welding or over-welding, with weak welding reducing cross-sectional area and increasing heat generation, while over-welding caused bead misalignment and raised the risk of short-circuit defects. Optimal conditions achieved tensile strengths exceeding 140 kgf and eliminated porosity, attributed to the multi-mode laser's ability to expand the molten region and the use of shielding gas to remove metal vapor. A plasma measurement system was employed to monitor plasma intensity, power, and temperature, facilitating the development of a welding classification algorithm. Short-Time Fourier Transform (STFT) identified weak welding via RMS thresholds, while Fast Fourier Transform (FFT) with a Moving Average Filter (MAF) classified over-welding. Case studies validated the algorithm’s effectiveness in real-time monitoring. Despite identifying optimal conditions, real-world factors may cause defects, necessitating further tests under diverse conditions. Limited data points were a constraint; expanding datasets would improve accuracy and reliability. Future research aims to enhance the algorithm and adapt it for industrial use, ensuring reliable, eco-friendly electric powertrain systems.
