Geospatial Analysis of Electric Vehicle Battery Re-Use Pathways for Urban Resilience and Disaster Preparedness

Authors: Elizabeth Moore*, Rochester Institute of Technology, Callie W Babbitt, Rochester Institute of Technology, Brian Tomaszewski, Rochester Institute of Technology
Topics: Spatial Analysis & Modeling, Sustainability Science, Energy
Keywords: urban resilience, disaster, electric vehicles, waste management
Session Type: Paper
Day: 4/5/2019
Start / End Time: 9:55 AM / 11:35 AM
Room: Balcony B, Marriott, Mezzanine Level
Presentation File: No File Uploaded


As electric vehicle (EV) adoption increases worldwide, the production of lithium-ion batteries will subsequently increase. Sustainable management of EV batteries through various re-use pathways at their end-of-vehicle life can enable energy resilience in urban areas while also minimizing emissions and costs from producing additional batteries for stationary or portable charging applications. To demonstrate the utility of urban reuse pathways, geospatial analysis was performed to determine (a) where EV battery packs could be optimally located to aid in building the energy resilience of cities and (b) how the batteries could be transported efficiently and effectively during the time of a disaster (to provide electrical supplements). In this study, two urban reuse pathways are analyzed to determine the critical infrastructure benefits of integrating battery packs into secondary life applications. A strategy scenario enabling distributed energy in net zero buildings was analyzed for Berlin, Germany to determine the potential for EV batteries to aid in the day to day operations of intermittent renewable grid support. In the second scenario, the European blackout of 2006 was simulated to determine how batteries could be temporarily routed to provide power resources for critical locations of the city. In both scenarios, sustainable reuse pathway strategies can help to 1) avoid disposal or recycling of functional EV batteries and 2) support each city’s resilience framework.

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