Electrical conductivity of additively manufactured copper and silver for electrical winding applications
Munagala, Sai Priya
Govindaraman, Loganathan T
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AbstractEfficient and power-dense electrical machines are critical in driving the next generation of green energy technologies for many industries including automotive, aerospace and energy. However, one of the primary requirements to enable this is the fabrication of compact custom windings with optimised materials and geometries. Electrical machine windings rely on highly electrically conductive materials, and therefore, the Additive Manufacturing (AM) of custom copper (Cu) and silver (Ag) windings offers opportunities to simultaneously improve efficiency through optimised materials, custom geometries and topology and thermal management through integrated cooling strategies. Laser Powder Bed Fusion (L-PBF) is the most mature AM technology for metals, however, laser processing highly reflective and conductive metals such as Cu and Ag is highly challenging due to insufficient energy absorption. In this regard, this study details the 400 W L-PBF processing of high-purity Cu, Ag and Cu–Ag alloys and the resultant electrical conductivity performance. Six Cu and Ag material variants are investigated in four comparative studies characterising the influence of material composition, powder recoating, laser exposure and electropolishing. The highest density and electrical conductivity achieved was 88% and 73% IACS, respectively. To aid in the application of electrical insulation coatings, electropolishing parameters are established to improve surface roughness. Finally, proof-of-concept electrical machine coils are fabricated, highlighting the potential for 400 W L-PBF processing of Cu and Ag, extending the current state of the art.
CitationRobinson J, Munagala SP, Arjunan A, Simpson N, Jones R, Baroutaji A, Govindaraman LT, Lyall I. (2022) Electrical Conductivity of Additively Manufactured Copper and Silver for Electrical Winding Applications. Materials, 15(21):7563. https://doi.org/10.3390/ma15217563
Description© 2022 The Authors. Published by MDPI. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.3390/ma15217563
SponsorsThis research was conducted with support from Innovate UK Knowledge Transfer Partnership KTP013117 (University of Wolverhampton/AceOn).
Except where otherwise noted, this item's license is described as https://creativecommons.org/licenses/by/4.0/