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Ultrasonic metal welding of Al/Cu joints with Ni coating: parametric effects on joint performance and microstructural modifications

  • Soumyajit Das , Mantra Prasad Satpathy ORCID logo EMAIL logo , Bharat Chandra Routara , Basanta Kumar Nanda and Susanta Kumar Sahoo
Published/Copyright: January 7, 2025
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Abstract

The increasing adoption of lithium-ion battery packs in electric vehicles has sparked considerable interest in choosing the appropriate busbar material and obtaining suitable mechanical, electrical, and thermal properties of the welded joints. This study comprehensively employs ultrasonic metal welding to create tab-to-busbar connections utilizing 0.3 mm nickel-coated copper and 0.5 mm aluminum sheets. Joint mechanical performance, microstructural characterization, and welding mechanism at different weld energies and clamping pressures are studied to understand the material flow, inter-atomic mixing, and newer grain formation phenomena. The correlation between the dynamic characteristics of electrical contact resistance and the resulting temperature is also revealed under various welding conditions by applying current through the joints. The micro-hardness analysis disclosed the different weld zones of distinctive values where the material has been mixed. Further, the nickel coating on the copper surfaces facilitates metallurgical bonding to a significant extent. The results revealed that the inter-atomic diffusion, wave-like bonding area, and micro-bond development on the weld cross-sectional surface are the foremost reasons for satisfactory welds.


Corresponding author: Mantra Prasad Satpathy, School of Mechanical Engineering, KIIT Deemed to be University, Bhubaneswar, 756001, Odisha, India, E-mail:

Acknowledgments

The authors are truly grateful to the organizer and convenor of ICPCM 2023.

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  5. Conflict of interest: The authors state no conflict of interest.

  6. Research funding: None declared.

  7. Data availability: Not applicable.

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Received: 2024-02-15
Accepted: 2024-06-24
Published Online: 2025-01-07
Published in Print: 2024-11-26

© 2024 Walter de Gruyter GmbH, Berlin/Boston

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