SOURCE-LINKED INTELLIGENCE

A HOLISTIC APPROACH OF ELECTRIC MOTOR COOLING

CORDIS · observation · Publication date unknown

nature, which, when employed in spray-cooling thermal management systems, will be a game-changer; (b) implementation of a universal design methodology for spray cooling, optimised with the aid of new Machine Learning (ML) algorithms. Training datasets for the ML tool will be obtained by ‘ground-truth’ experimental and numerical investigations also to be conducted for the first time in E-COOL. The envisioned cooling system aims to provide unprecedented cooling rates at local temperature hot spots, which can contribute to an average 20% increase in e-motor’s efficiency compared to today’s state-of-the-art. This will allow next-generation e-motor utilisation over the whole range of transportation sectors, thus, facilitating significant additional energy and CO2 savings relative to the existing EU plans. Spray cooling, viscoelastic fluid, CFD spray simulations, machine learning, electric motor, laser diagnostics

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recordType

award

status

SIGNED

region

EU

value

2165477.5

unit

EUR