EURO 2025 Leeds
Abstract Submission

2877. Optimal charging infrastructure size and location to support electric taxi fleets using real trajectory data: a case study in a Portuguese city

Invited abstract in session WB-30: Shared Mobility Optimization III, stream Shared Mobility Optimization.

Wednesday, 10:30-12:00
Room: Maurice Keyworth 1.05

Authors (first author is the speaker)

1. Ana Loureiro
Faculdade de Engenharia da Universidade do Porto
2. Beatriz Brito Oliveira
INESC TEC, Faculty of Engineering, University of Porto
3. Vera Miguéis
DEGI, Faculdade de Engenharia da Universidade do Porto
4. João Neves
Faculdae de Ciências, Universidade do Porto
5. Álvaro Costa
Faculdade de Engenharia, Universidade do Porto
6. Michel Ferreira
Faculdade de Ciências, Universidade do Porto

Abstract

Despite the rise of electric mobility, taxi fleets lag behind. Accelerating their transition requires demonstrating the feasibility and cost-effectiveness of electric taxis with adequate charging, while highlighting their environmental benefits. This work addresses this issue by seeking, for a charging infrastructure (CP), both the best location within a taxi stand network and the minimum number of chargers required to maximize the number of taxis transitioning to electric vehicles while keeping the current service level. For this purpose, we formulated a bi-objective optimization model and validated it using real data collected by an entire taxi fleet over 4 weeks of operation. We applied the Epsilon-constraint method to solve the model and obtain the Pareto fronts, allowing to quantify efficient and feasible trade-offs. We determined that the configuration of the CP and the number of electric taxis it could support greatly depended on the activity level. In each week, an average of 20 chargers was consistently allocated to a subgroup of stands. For the whole 4 weeks period, we showed that the operation of nearly a third of the fleet could be perfectly adapted to electric mobility. For this scenario, the deployment of 22 chargers would be needed. We believe that the proposed model can aid authorities and managers in promoting the use of electric vehicles for taxi services, by providing a tool that allows to define a customized CP that meets the needs of the operating fleet.

Keywords

Status: accepted

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