Infrastructure Planning for Electric Vehicles with Battery Swapping

Mak, Ho‐Yin; Rong, Ying; Shen, Zuo‐Jun Max

doi:10.2139/ssrn.2022651

Cited by 43 publications

(56 citation statements)

References 32 publications

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“…Until now, some alternative methods have been proposed, such as plug-in charging [16], 15 battery-swapping [19][20][21], dynamic wireless recharging [22], and charging lanes [23]. The most common charging method for BEVs is plug-in charging, which is static conductive charging via a cable and a vehicle connector when the BEV is parked.…”

Section: Literature Reviewmentioning

confidence: 99%

Multiple Types of Plug-In Charging Facilities’ Location-Routing Problem with Time Windows for Mobile Charging Vehicles

2018

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Abstract:Increasing attention is being paid to the technology of battery electric vehicles (BEVs) because of their environmental friendliness. However, their short range, extended recharging times, and insufficient charging facilities hinder the improvement in the market share of BEVs. As a remedy, this paper presents a novel approach to providing a service for the battery charge replenishment of BEVs. Instead of using traditional alternative methods by only providing a charging service in a fixed location, such as battery-swapping and charging lanes, the novel charge replenishment is provided by mobile charging vehicles (MCVs), which could offer a charging service at any time and at location requested. To consider the limited running range and the opportunity to recharge from MCVs, as well as to determine the location strategy of multiple types of plug-in charging facility locations and the routing plan of the MCVs simultaneously, the location routing problem (LRP) that can integrate two decision levels, with a strategic level (location) and tactical level (routing), is applied. Then, we present the multiple types of plug-in charging facilities' location-routing problem with time windows for mobile charging vehicles (MTPCF-LRPwTW-MCVs), and formulate the MTPCF-LRPwTW-MCVs as a mixed integer linear program for the convenience of solving. To demonstrate the model, test instances are designed and computational results are presented. Furthermore, sensitivity analyses on battery capacity, recharging rate, and so on, are also examined. The results show that with the increase of the battery capacity or the improvement of the charging rate of the charging facilities, the service efficiency of the MCVs can reasonably be improved. Therefore, the proposed method could be used in real world problems.

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Section: Literature Reviewmentioning

confidence: 99%

Multiple Types of Plug-In Charging Facilities’ Location-Routing Problem with Time Windows for Mobile Charging Vehicles

2018

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“…In the future, probably charging networks will comprise mainly slow charging stations (Gartner and Wheelock, 2009) as the widespread use of fast charging stations would increase power demand in the electrical grid (Mak et al, 2013) adding larger difficulties to grid management.…”

Section: B Electric Vehicles Charging Networkmentioning

confidence: 99%

“…On the other hand others will have to use public car parking, being important to assure that the most suitable locations are made available for charging stations or points, especially in urban areas and these identified forehand. This process could be a chicken-and-egg dilemma, when identifying what comes first: the charging network or the EV users (Mak et al, 2013). Undeniably, EV users must not be conditioned by the lack of an adequate EV charging network in their normal routes.…”

Section: Introductionmentioning

confidence: 99%

A multi-criteria decision aid methodology to design electric vehicles public charging networks

et al. 2015

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This article presents a new multi-criteria decision aid methodology, dynamic-PROMETHEE, here used to design electric vehicle charging networks. In applying this methodology to a Portuguese city, results suggest that it is effective in designing electric vehicle charging networks, generating time and policy based scenarios, considering offer and demand and the city’s urban structure. Dynamic-PROMETHE adds to the already known PROMETHEE’s characteristics other useful features, such as decision memory over time, versatility and adaptability. The case study, used here to present the dynamic-PROMETHEE, served as inspiration and base to create this new methodology. It can be used to model different problems and scenarios that may present similar requirement characteristics.

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“…Future research should incorporate the potential to improve energy efficiency in buildings (reducing both the mean and variance of electricity demand) and the potential to time-shift electricity demand in buildings, manufacturing industries, and transportation. A nascent literature addresses the dynamic optimal control of distributed devices that store, generate, and/or consume electricity; see Xi et al (2011), Kraning et al (2013), Mak et al (2013), Wu and Kapuscinski (2013), and references therein. Multidisciplinary research (spanning engineering, meteorology, finance, law, economics, political science, psychology, and OM) is needed to characterize the socially optimal investments in energy efficiency, renewable electricity generating capacity, electricity transmission infrastructure, and electric vehicles and their charging infrastructure, and then to identify policies and business models that will overcome the chicken and egg barriers to such investments.…”

Section: Questions For Om and Multidisciplinary Researchmentioning

confidence: 99%

OM Forum—Operations Management Challenges for Some “Cleantech” Firms

Plambeck

2013

M&SOM

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A "cleantech" firm is one with an innovative technology and/or business model for serving an existing market with dramatically reduced environmental impact. This paper describes operations management (OM) challenges faced by five cleantech companies, and a few questions that these raise for OM and multidisciplinary research. It aims to fuel readers' motivation to identify and pursue others. The OM community has fundamental roles to play in the creation of an environmentally sustainable economy.

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Infrastructure Planning for Electric Vehicles with Battery Swapping

Cited by 43 publications

References 32 publications

Multiple Types of Plug-In Charging Facilities’ Location-Routing Problem with Time Windows for Mobile Charging Vehicles

Multiple Types of Plug-In Charging Facilities’ Location-Routing Problem with Time Windows for Mobile Charging Vehicles

A multi-criteria decision aid methodology to design electric vehicles public charging networks

OM Forum—Operations Management Challenges for Some “Cleantech” Firms

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