PI: Charles Kolstad; Co-PIs: Nicolas Astier and Xavier Lambin
Even with so-called fast-charging technologies, the refueling of electric vehicles (EV) remains significantly slower than for their gasoline counterparts. However, increasing further charging speed is costly both in terms of charging infrastructure and battery degradation. A key challenge in the EV industry is thus to assess how fast DC chargers need to be to support the transition towards EVs.
Ultimately, the optimal design of fast-charging stations depends on the extent to which drivers value time in their intercity travel. This project intends to assess this value in a credible setting, leveraging revealed-preference information from choices made by the users of a large carpooling platform.
Working on a rich dataset should enable us to get values of time differentiated by route characteristics (e.g. length, rural/urban, etc.), time of the day, or even ultimately countries. Such knowledge would represent a key input to design a cost-efficient charging network across large geographical areas.