Shared automated vehicles are expected to be part of the supply of transportation systems in the future. Parallel to this evolution, there is the rapid penetration of battery electric vehicles (BEVs). The limitations in battery capacity and charging speed of BEVs can influence the planning and operation of shared automated electric vehicle (SAEV) systems. The design of such systems needs to include these limitations so that their viability is properly estimated. In this paper, we develop a space–time-energy flow-based integer programming (IP) model in support of the strategic design of a regional SAEV system. The proposed approach optimizes the fleet (size and composition) and charging facilities (number and location), while explicitly accounting for vehicle operations in aggregated terms (including movements with users, relocations, and charging times). The model is used to assess the impact of vehicle range and different types of chargers in the optimal design of an interurban SAEV transport system in the center of Portugal. Results show a reduction in profit as the vehicle range increases. In regards to energy, it is observed that the adoption of long-range vehicles reduces the energy spent in relocations, and increases the amount of energy charged at a lower price. Additionally, it is found that a system with long-range vehicles does not take advantage of having fast chargers. Concerning the chargers’ optimal location, systems using short-range vehicles have more chargers close to the main commuter trips attracting cities, while systems with long-range vehicles have the chargers nearby the homes of users.

(2023). A space–time-energy flow-based integer programming model to design and operate a regional shared automated electric vehicle (SAEV) system and corresponding charging network [journal article - articolo]. In TRANSPORTATION RESEARCH. PART C, EMERGING TECHNOLOGIES. Retrieved from https://hdl.handle.net/10446/235750

A space–time-energy flow-based integer programming model to design and operate a regional shared automated electric vehicle (SAEV) system and corresponding charging network

Birolini, Sebastian;
2023-01-01

Abstract

Shared automated vehicles are expected to be part of the supply of transportation systems in the future. Parallel to this evolution, there is the rapid penetration of battery electric vehicles (BEVs). The limitations in battery capacity and charging speed of BEVs can influence the planning and operation of shared automated electric vehicle (SAEV) systems. The design of such systems needs to include these limitations so that their viability is properly estimated. In this paper, we develop a space–time-energy flow-based integer programming (IP) model in support of the strategic design of a regional SAEV system. The proposed approach optimizes the fleet (size and composition) and charging facilities (number and location), while explicitly accounting for vehicle operations in aggregated terms (including movements with users, relocations, and charging times). The model is used to assess the impact of vehicle range and different types of chargers in the optimal design of an interurban SAEV transport system in the center of Portugal. Results show a reduction in profit as the vehicle range increases. In regards to energy, it is observed that the adoption of long-range vehicles reduces the energy spent in relocations, and increases the amount of energy charged at a lower price. Additionally, it is found that a system with long-range vehicles does not take advantage of having fast chargers. Concerning the chargers’ optimal location, systems using short-range vehicles have more chargers close to the main commuter trips attracting cities, while systems with long-range vehicles have the chargers nearby the homes of users.
articolo
Gonçalves Duarte Santos, Gonçalo; Birolini, Sebastian; Homem de Almeida Correia, Gonçalo
(2023). A space–time-energy flow-based integer programming model to design and operate a regional shared automated electric vehicle (SAEV) system and corresponding charging network [journal article - articolo]. In TRANSPORTATION RESEARCH. PART C, EMERGING TECHNOLOGIES. Retrieved from https://hdl.handle.net/10446/235750
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10446/235750
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