Effects of energy consumption on cost optimal recharging station locations for e-scooters

E-scooters are getting widespread within micromobility vehicles that ensure short-term access to transportation modes in order to deal with the urban mobility problem. Considering the development in battery and recharging technology, locating the number of recharging stations optimally, is a significant challenge in order to increase the usage of e-scooters. In this study, we have focused on the decision on the location of the cost-optimal recharging stations for e-scooters by highlighting the significance of calculating the energy consumption as accurate as possible. In this context, a mixed-integer linear programming formulation referred as the Recharging Station Locating Problem with Energy Consumption (RSLP-EC) is presented where vehicle motion dynamics based energy consumption model is incorporated with a location model, in order to determine the remaining battery load considering the 3-Dimensional road geometry, as well as e-scooter and road surface characteristics. We have discussed on the results of RSLP-EC with 30 trips on a real-world instance where the slope varies up to 8.5%. Results show that the distance-based energy consumption approach for e-scooters in literature over or underestimates the recharging station requirement, and, hence the locations of the recharging stations, although network-specific energy consumption rates are considered, which results in an excessive amount of RS investment or few e-scooters to run out of the battery without completing their trips. We have also discussed the influence of the allowable charging time on recharging station siting decision, and the decision on the node-based recharging station e-scooter capacity in order to provide a cost-optimal solution to serve for a set of e-scooter O-D flows.