Experimental investigation on end winding thermal management with oil spray in electric vehicles

Wang, Xuehui; Li, Bo; Huang, Kuo; Yan, Yuying; Stone, Ian; Worrall, Sean

Abstract

To achieve a carbon-neutral sustainable future, the transportation sector is experiencing quick electrification, as more and more vehicles are driven by electric motors. Electric motors are designing more and more powerful and thus pose a great increasing challenge for thermal management. In this paper, an innovative experimental study on oil spray for end winding thermal management were presented. The experimental results indicated that the oil spray cooling significantly decrease the temperature of the winding. With higher oil temperature and flow rate, better cooling performance and better temperature uniformity were achieved both for teeth and slot winding. Meanwhile, a heat transfer performance prediction model based on a fully connected artificial neural network (ANN) was developed to correlate oil spray. The model used Reynolds number and Prandtl number as inputs, and the number of neurons in hidden layer was optimized to 8. The model accurately predicts the heat transfer performance of oil spray with a correlation coefficient of 0.93. The paper is expected to be a good reference for the oil spray engineering application in e-motor cooling.

• Journal Article Type: Article
• Acceptance Date: Apr 29, 2022
• Online Publication Date: May 6, 2022
• Publication Date: 2022-07
• Deposit Date: Jun 20, 2022
• Publicly Available Date: Jun 21, 2022
• Journal: Case Studies in Thermal Engineering
• Publisher: Elsevier BV
• Peer Reviewed: Peer Reviewed
• Volume: 35
• Article Number: 102082
• DOI: https://doi.org/10.1016/j.csite.2022.102082
• Keywords: Fluid Flow and Transfer Processes; Engineering (miscellaneous)
• Public URL: https://nottingham-repository.worktribe.com/output/7957224
• Publisher URL: https://www.sciencedirect.com/science/article/pii/S2214157X22003288?via%3Dihub