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Electric vehicles (EVs) pose significant challenges for long-distance mass evacuation during natural hazards due to their long charging time compared to traditional gasoline vehicles. This paper studies the evacuation planning for high EV ownership regions by exploring the optimization of route selection, vehicle grouping, and departure and charging scheduling. More importantly, we also consider the Mobile Charging Stations (MCS), which can be deployed temporarily to supplement the Fixed Charging Stations (FCS) for the evacuation operation, and study the optimization of their placement....

Improving battery health and safety motivates the synergy of a powerful duo: physics and machine learning. Through seamless integration of these disciplines, the efficacy of mathematical battery models can be significantly enhanced. This paper delves into the challenges and potentials of managing battery health and safety, highlighting the transformative impact of integrating physics and machine learning to address those challenges. Based on our systematic review in this context, we outline several future directions and perspectives, offering a comprehensive exploration of efficient and...

Lithium-ion batteries have found their way into myriad sectors of industry to drive electrification, decarbonization, and sustainability. A crucial aspect in ensuring their safe and optimal performance is monitoring their energy levels. In this paper, we present the first study on predicting the remaining energy of a battery cell undergoing discharge over wide current ranges from low to high C-rates. The complexity of the challenge arises from the cell’s C-rate-dependent energy availability as well as its intricate electro-thermal dynamics especially at high C-rates. To address this, we...

The reuse of second-life lithium-ion batteries (LIBs) retired from electric vehicles is critical for energy storage in underdeveloped regions, where power infrastructures are weak or absent. However, estimating the relative remaining capacity (RRC) of second-life batteries using field-accessible data stream remains challenging due to its scarcity and heterogeneity, despite efforts in battery passports and other initiatives to secure data integrity. This study proposes a deep generative transfer learning framework to address these two-fold challenges by generating voltage dynamics...