Electric vehicle charging infrastructure planning in a road network

Micari, Salvatore; Polimeni, Antonio; Napoli, G.; Andaloro, L.; Antonucci, V.

doi:10.1016/j.rser.2017.05.022

Cited by 110 publications

(30 citation statements)

References 38 publications

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“…In short, the zero-dimensional (0D) model calculates the time-dependent heat generation (2), incorporating the internal resistances and the OCV, as shown in the Equations (1) and (2). Moreover, as the study investigated high-current profiles, the "reversible" or entropic heat was not considered in this study [43].…”

Section: Thermal Modelingmentioning

confidence: 99%

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Combining an Electrothermal and Impedance Aging Model to Investigate Thermal Degradation Caused by Fast Charging

et al. 2018

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Fast charging is an exciting topic in the field of electric and hybrid electric vehicles (EVs/HEVs). In order to achieve faster charging times, fast-charging applications involve high-current profiles which can lead to high cell temperature increase, and in some cases thermal runaways. There has been some research on the impact caused by fast-charging profiles. This research is mostly focused on the electrical, thermal and aging aspects of the cell individually, but these factors are never treated together. In this paper, the thermal progression of the lithium-ion battery under specific fast-charging profiles is investigated and modeled. The cell is a Lithium Nickel Manganese Cobalt Oxide/graphite-based cell (NMC) rated at 20 Ah, and thermal images during fast-charging have been taken at four degradation states: 100%, 90%, 85%, and 80% State-of-Health (SoH). A semi-empirical resistance aging model is developed using gathered data from extensive cycling and calendar aging tests, which is coupled to an electrothermal model. This novel combined model achieves good agreement with the measurements, with simulation results always within 2°C of the measured values. This study presents a modeling methodology that is usable to predict the potential temperature distribution for lithium-ion batteries (LiBs) during fast-charging profiles at different aging states, which would be of benefit for Battery Management Systems (BMS) in future thermal strategies.

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Section: Thermal Modelingmentioning

confidence: 99%

“…Nonetheless, some significant obstacles exist with respect to the transition from the use of conventional vehicles to EVs, for example charging infrastructure [2], recycling issues [3,4], total cost [5,6], and safety issues [7]. Another issue is the charging time.…”

Section: Introductionmentioning

confidence: 99%

Combining an Electrothermal and Impedance Aging Model to Investigate Thermal Degradation Caused by Fast Charging

et al. 2018

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“…In the literature, Micari et al [18] describe a planning strategy for positioning EV charging points for calculating the number and position of EV charging points in a road network is outlined. The methodology is taking into account EV features, charging times and vehicles flow.…”

Section: Introductionmentioning

confidence: 99%

A Framework for Analysis and Expansion of Public Charging Infrastructure under Fast Penetration of Electric Vehicles

Pallonetto

Galvani

Torti

et al. 2020

WEVJ

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The improvement commercial competitiveness of private electric vehicles supported by the European policy for the decarbonisation of transport and with the consumers awareness-raising about CO 2 emissions and climate change, are driving the increase of electric vehicles on the roads. Therefore, public charging networks are facing the challenge of supply electricity to a fast increasing number of electric cars. The objective of this paper is to establish an assessment framework for analysis and monitor of existing charging networks. The developed methodology comprises modelling the charging infrastructure electricity profile, analysing the data by using machine learning models such as functional k-means clustering and defining a novel congestion metric. The described framework has been tested against Irish public charging network historical datasets. The analyses reveal a lack of reliability of the communication network infrastructure, frequent congestion events for commercial and shopping areas in specific clusters of charge points and the presence of power peaks caused by the high number of simultaneous charging events. Several recommendations for future network expansion have been highlighted.

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“…An extensive review of the literature available in this field can be found in [1]. A common aim is to find the optimal locations for charging stations in a road network under different constraints (see, e.g., [2][3][4][5]). The flow-refueling location model (FRLM), which maximises the number of covered long-distance trips with several refueling stops, is one of the possible ways to formulate this problem [6].…”

Section: Introductionmentioning

confidence: 99%

A Corridor-Based Approach to Estimating the Costs of Electric Vehicle Charging Infrastructure on Highways

Suomalainen

Colet

2019

WEVJ

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One of the barriers holding back the large-scale development of electric vehicles is underdeveloped charging infrastructure. The optimal location of charging stations has received much attention, whereas the development of charging infrastructure over time and its economic implications remain a less explored topic, especially in the context of dynamic inductive charging. This work compares the infrastructure costs for two electric vehicle charging solutions deployed on highways: fast-charging stations and a dynamic charging lane based on wireless inductive charging technology. The deployment costs are estimated using a simplified infrastructure model for a highway corridor. The model first defines the required charging capacity based on projected future demand, sizes the charging infrastructure, and then determines the related costs, revenues, and net present value. A numerical example based on the French highway context is also presented. The results show that the payback period is much longer for dynamic charging lanes that for charging stations. In addition, the charging lane infrastructure cannot be installed gradually over time but requires a major investment from the start while bringing in little revenue early on.

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Electric vehicle charging infrastructure planning in a road network

Cited by 110 publications

References 38 publications

Combining an Electrothermal and Impedance Aging Model to Investigate Thermal Degradation Caused by Fast Charging

Combining an Electrothermal and Impedance Aging Model to Investigate Thermal Degradation Caused by Fast Charging

A Framework for Analysis and Expansion of Public Charging Infrastructure under Fast Penetration of Electric Vehicles

A Corridor-Based Approach to Estimating the Costs of Electric Vehicle Charging Infrastructure on Highways

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