Objective
Electric motors (e-motors) consume more than 40% of electricity produced globally. The EU aims to save ~40Mt of CO2 emissions per year until 2030 by deploying more efficiency e-motors. E-motors are also the driving force behind EVs, currently leading the global efforts for decarbonisation of the transportation sector; their efficiency is crucial in extending EV mileage. Unfortunately, electrification plans for heavy-duty, earth-moving machines and aircrafts (accounting currently ~60% of fossil fuel consumption in transportation) have to overcome, among other limitations, the technological barrier of excess heat generated in the e-motor copper windings during power-demanding operations associated with these sectors. E-COOL promises to address this challenge via the development of a holistic e-motor cooling technology, maximising heat transfer through direct-contact, spray cooling. E-COOL aims to achieve this technological breakthrough at time-scales compatible to those required for industrial innovation to reach the market, by integrating two interdisciplinary activities: (a) development and manufacturing of novel oil-based, dilute polymer mixtures of non-Newtonian 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.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- engineering and technologymechanical engineeringvehicle engineeringaerospace engineeringaircraft
- natural scienceschemical sciencespolymer sciences
- engineering and technologyenvironmental engineeringenergy and fuels
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Keywords
Programme(s)
- HORIZON.3.1 - The European Innovation Council (EIC) Main Programme
Funding Scheme
HORIZON-EIC - HORIZON EIC GrantsCoordinator
39106 Magdeburg
Germany