Abstract

Ultrasonic welding can realize the high-strength connection between wire harnesses, and has the technical characteristics of energy conservation and environmental protection, so it has a broad application prospect in the field of new energy vehicles. However, the influence of welding parameters on joint strength is complex, which is not easy to reveal, limiting its application in industry. In this study, ultrasonic welding experiment between aluminum alloy and copper wire is carried out, and the artificial neural network model optimized by genetic algorithm (GA-ANN) analysis is conducted to investigate the influences of welding parameters on joint strength. Designed and conducted a 3-factor, 3-level comprehensive test. According to experimental research, the maximum strength of ultrasonic welding of copper wire and aluminum alloy can reach 719 N. The influence weight of welding parameters and interaction between parameters on joint strength is obtained. Ultrasonic connection between aluminum alloy and copper wire is realized through diffusion layer at the interface. The main component of the diffusion layer is Cu, with a small amount of Al and Al2Cu. According to the GA-ANN model, the detailed influence of welding parameters on joint strength is obtained. The optimal parameter range under different clamping force is optimized. Within this range, the joint strength can exceed 680 N. With the increase of clamping force, the optimal parameter range gradually transfers from the combination of high vibration amplitude and high welding time to the combination of high vibration amplitude and low welding time.

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