Estimation of Oil Spray Cooling Heat Transfer Coefficients on Hairpin Windings with Reduced-Parameter Models

Chuan Liu, David Gerada, Zeyuan Xu, Yew Chuan Chong, Melanie Michon, James Goss, Jing Li, Chris Gerada, He Zhang

Research output: Journal PublicationArticlepeer-review

8 Citations (Scopus)

Abstract

Hairpin windings and spray cooling are becoming an increasingly popular combination in the field of high-performance electrical machine design. Machines adopting hairpin windings can achieve higher torque and power densities while enabling them to be manufactured automatically on a large scale to meet the rapid market growth of electric transport. Spray cooling is an effective way for high heat flux removal, which has shown great potentials in electrical machine applications. Although spray cooling has been studied for decades in different engineering applications, the focus had been on investigating its performance on regular surfaces using low-viscosity liquids, such as water. In addition, many existing models for spray cooling heat transfer were built on spray parameters that are difficult to obtain without specialist equipment. Thus, most results from previous studies are difficult to be interpreted and directly applied to electrical machine applications. Practical and economical approaches for estimating the heat transfer coefficients (HTCs) of spray cooling on hairpin windings are needed. This article proposes and validates an experimental approach based on reduced-parameter models that can be applied to predict the HTC of spray cooling setups on hairpin windings.

Original languageEnglish
Article number9224936
Pages (from-to)793-803
Number of pages11
JournalIEEE Transactions on Transportation Electrification
Volume7
Issue number2
DOIs
Publication statusPublished - Jun 2021

Keywords

  • Cooling
  • electric machines
  • spraying

ASJC Scopus subject areas

  • Automotive Engineering
  • Transportation
  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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