1 citations · 1 across the 1 of their papers we have counts for
2 papers
cs.LG2024
Onboard Health Estimation using Distribution of Relaxation Times for Lithium-ion Batteries
Muhammad Aadil Khan, Sai Thatipamula, Simona Onori
Real-life batteries tend to experience a range of operating conditions, and undergo degradation due to a combination of both calendar and cycling aging. Onboard health estimation m…
cs.LG2024★ 1 cited
Domain knowledge-guided machine learning framework for state of health estimation in Lithium-ion batteries
Andrea Lanubile, Pietro Bosoni, Gabriele Pozzato +3
Accurate estimation of battery state of health is crucial for effective electric vehicle battery management. Here, we propose five health indicators that can be extracted online fr…