Novel framework for optimising battery-cooling microchannel heat exchangers

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Thermal overheating can affect the capacity, safety and life expectancy of batteries for renewable energy storage and electric vehicles. Microscale heat exchangers are a potential high-efficiency, low-bulk solution. This project aims to develop a novel computational methodology to optimise the design of those heat exchangers in which viscoelastic fluids are used to control flow instabilities and enhance heat transfer at the microscale. A new microscopic fluid physics model will provide data for an innovative neural network framework to optimise the working fluid conditions and microscale design, which could contribute to increased adoption of renewable energy technologies that are supported by microscale heat exchangers.