A Machine Learning-based Digital Twin for Electric Vehicle Battery Modeling. (arXiv:2206.08080v1 [cs.LG])

The widespread adoption of Electric Vehicles (EVs) is limited by their
reliance on batteries with presently low energy and power densities compared to
liquid fuels and are subject to aging and performance deterioration over time.
For this reason, monitoring the battery State Of Charge (SOC) and State Of
Health (SOH) during the EV lifetime is a very relevant problem. This work
proposes a battery digital twin structure designed to accurately reflect
battery dynamics at the run time. To ensure a …

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