Energy impact evaluation for eco-routing and charging of autonomous electric vehicle fleet: Ambient temperature consideration

Yi, Zonggen; Smart, John; Shirk, Matthew

doi:10.1016/j.trc.2018.02.018

Cited by 87 publications

(30 citation statements)

References 49 publications

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“…This finding is interesting because it is different from our intuition and is really beneficial to promoting EVs. We compare our findings with those in other researches [3][4][5][6] which focused on travel time costs, monetary costs or operating costs. Most of them did not conduct a similar comparison and did not achieve our findings.…”

Section: Discussionmentioning

confidence: 65%

“…To the travelers, the most appealing benefit of motorization is the generalized costs, which include travel time costs, monetary costs, operating costs and environmental costs. There has been lots of research focusing on the travel time costs, monetary costs and operating costs [3][4][5][6]. This research proposed generalized costs which contain travel time costs, monetary costs and operating costs of vehicles, respectively.…”

Section: Related Studiesmentioning

confidence: 99%

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Stochastic Electric Vehicle Network Considering Environmental Costs

Cheng

et al. 2018

Sustainability

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In recent years, many countries have published their timetables to promote electric vehicles. Many researches have focused on the benefits of electric vehicles. Compared with gas vehicles, electric vehicles are more suitable for modern cities, because they are considered to be environment-friendly by the public. Hence we pay attention to the environmental costs of electric vehicles. In this paper, an electric vehicle network is established. To analyze this electric vehicle network, we define environmental costs for the network and propose a stochastic user equilibrium model to describe drivers’ route choice behavior. An algorithm is proposed to solve this model. The model and the algorithm are illustrated through a numerical example. We test the calculation feasibility of the proposed model and the computational efficiency of the proposed algorithm via this numerical example. A comparative analysis is conducted to show the benefits of introducing electric vehicles into traffic networks. With the sensitivity analysis, we also reveal the relationship between people’s environmental awareness, the quantity of electric vehicles and the environmental costs of the overall traffic network.

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Section: Discussionmentioning

confidence: 65%

Section: Related Studiesmentioning

confidence: 99%

Stochastic Electric Vehicle Network Considering Environmental Costs

Cheng

et al. 2018

Sustainability

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“…Few works have analyzed the impacts of the ACEVs' integration in power systems [144], [152], [153]. Moreover, similar to the current EVs, a large-scale implementation of ACEVs and the service provision to DSOs must still overcome many barriers related to the policies, agreements, infrastructure, and technology [146], [154].…”

Section: E Emerging Ev Technologies and Their Impact On Distributionmentioning

confidence: 99%

Distribution System Services Provided by Electric Vehicles: Recent Status, Challenges, and Future Prospects

Arias

Hashemi

Andersen

et al. 2019

IEEE Trans. Intell. Transport. Syst.

128

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Trend-setting countries have promoted or even employed an increased number of electric vehicles (EVs) and other distributed energy resources (DERs) in their power systems. This development has triggered new and increasing challenges in the distribution system planning and operation, whereby distribution systems must adapt to the increased share of DERs. However, EVs may also offer new opportunities and can be used to support the grid by providing several local and global powerand energy-based services. This paper presents a review and classification of the services potentially available from EVs for distribution systems, referred to as EV distribution system services (EV-DSS). A detailed description of recent services and approaches is given, and an assessment of the maturity of EV-DSS is provided. Moreover, challenges and prospects for future research are identified, considering key topics, such as the design of the market framework, economic assessment, battery degradation, and the impacts of the transmission system operator service provision by EVs on distribution networks. Thus, this work offers a tool for stakeholders concerning services available from EVs and provides a broad literature framework that can be used as a base for further investigations. It is aligned with the current requirements to move toward realistic implementations of EV-DSS.

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“…A UTONOMOUS driving is believed to be a disruptive technology that will transform our transportation system in the near future. Autonomous vehicles (AVs) that transport passengers or goods without human intervention will not only free human drivers from burdensome driving labor, but also promote transportation accessibility [1], cut down mobility costs [2]- [4], enhance energy efficiency, and reduce greenhouse gas emission [5]- [8]. When AVs are electrified, which we refer to as autonomous electric vehicles (AEVs), then the last two aforementioned advantages will be further enhanced, particularly if the electricity is supplied from clean energy (e.g., renewable power generation).…”

Section: Introductionmentioning

confidence: 99%

Joint Fleet Sizing and Charging System Planning for Autonomous Electric Vehicles

Zhang

Sheppard

Lipman

et al. 2020

IEEE Trans. Intell. Transport. Syst.

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This paper studies the joint fleet sizing and charging system planning problem for a company operating a fleet of autonomous electric vehicles (AEVs) for passenger and goods transportation. Most of the relevant published papers focus on intracity scenarios and adopt heuristic approaches, e.g., agent based simulation, which do not guarantee optimality. In contrast, we propose a mixed integer linear programming model for intercity scenarios. This model incorporates comprehensive considerations of 1) limited AEV driving range; 2) optimal AEV routing and relocating operations; 3) time-varying origindestination transport demands; and 4) differentiated operation cost structure of passenger and goods transportation. The proposed model can be computational expensive when the scale of the transportation network is large. We then exploit the structure of this program to expedite its solution. Numerical experiments are conducted to validate the proposed method. Our experimental results show that AEVs in passenger and goods transportation have remarkable planning and operation differences. We also demonstrate that intelligent routing and relocating operations, charging system and vehicle parameters, e.g., charging power, battery capacity, driving speed etc., can significantly affect the economic efficiency and the planning results of an AEV fleet.

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Energy impact evaluation for eco-routing and charging of autonomous electric vehicle fleet: Ambient temperature consideration

Cited by 87 publications

References 49 publications

Stochastic Electric Vehicle Network Considering Environmental Costs

Stochastic Electric Vehicle Network Considering Environmental Costs

Distribution System Services Provided by Electric Vehicles: Recent Status, Challenges, and Future Prospects

Joint Fleet Sizing and Charging System Planning for Autonomous Electric Vehicles

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