Kevin Cardinale
Design and Development of a cosimulation framework to evaluate SOH in electric vehicles.
Rel. Edoardo Patti, Alessandro Aliberti, Lorenzo Bottaccioli. Politecnico di Torino, Master of science program in Computer Engineering, 2024
Abstract
The increasingly pressing need to combat environmental issues, in particular greenhouse gas emissions, requires a transition towards more sustainable transport solutions. Electric vehicles (EVs) are identified as a key pillar in this process. However, maximising their efficiency also depends on an accurate assessment of battery health (SOH). A detailed knowledge of SOH is essential to optimise the performance of EVs, predict their remaining life and ensure their safe operation. In parallel, recent advances in the field of artificial intelligence show a real advantage in the use of such tools in various application areas. Therefore, the use of such technologies to estimate the SOH of electric vehicles appears to be a solution to this problem.
Unfortunately, such tools require large amounts of data to make reliable predictions, and considering that the technology behind EVs is still recent, the availability of data to train neural networks is insufficient
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