Researchers from the University of Illinois at Urbana-Champaign and the University of Indonesia have delved into the challenges of managing electric vehicle (EV) fleets, particularly focusing on electric taxis. Their study, published in the journal Nature Energy, aims to balance the often-conflicting goals of fleet profitability, battery longevity, and grid stability.
Operating large-scale EV fleets presents unique challenges for both fleet operators and the power grid. Fleet operators may prioritize rapid charging to meet service demands, but this can lead to increased grid stress and potential instability. Moreover, frequent high-rate charging can accelerate battery degradation, reducing the overall lifespan of the fleet. The researchers developed an EV fleet simulator to evaluate the impact of different charging policies on battery degradation and grid stress using real-world travel data from New York City taxis.
The study compared a baseline charging policy, where 80% of the fleet charges at a high rate and 20% at a lower rate, with a reinforcement learning-based policy designed to prolong battery life and reduce grid stress. Over a five-year simulation period, the researchers monitored grid stress, battery degradation, and profitability. They found that the learned policy outperformed the baseline in all three areas.
For the energy sector, this research offers practical insights into optimizing charging strategies for EV fleets. By adopting intelligent charging policies, fleet operators can extend battery life, reduce maintenance costs, and minimize the impact on the power grid. This can contribute to more stable and efficient grid operations, particularly as the number of EVs on the road continues to grow. The simulator developed by the researchers can serve as a valuable tool for fleet operators to assess the impact of different charging policies and make informed decisions.
This article is based on research available at arXiv.