Bi-Objective Optimization for Battery Electric Bus Deployment Considering Cost and Environmental Equity

Zhou, Yirong; Liu, Cathy; Wei, Ran; Golub, Aaron

doi:10.1109/tits.2020.3043687

Cited by 41 publications

(19 citation statements)

References 40 publications

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“…This research results show that the charging method has a central role in the implementation of electric vehicle, especially city buses [34]. As the initial cost of the charging stations are much high, the user to evaluate the electric buses performance, to optimize battery sizing and options for charging infrastructure, and identify opportunities and gaps associated with vehicle electrification in real world city bus transit service, needs to take into account the charging station use the different operating routs as well as many other analysis [35,36].…”

Section: Discussionmentioning

confidence: 70%

Performances of the Electric Vehicles With Different Charging Methods

Jakimovska¹,

Vasileva²,

Bartłomiejczyk³

2021

MESJ

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Since the world pollution has been increased, the need for eco-solutions is alarming. One solution is electric vehicles, which have been rapidly developed in recent years. Those vehicles are energy efficient and emission free, but the initial costs can be much higher in comparison to other vehicles. This paper would focus on the methods of charging power and battery requirements as well as energy consumption. Analyzing the methods of charging for achieving environmentally friendly cities, as well as comparisons between the methods will greatly support the development of strategies for achieving zero emissions.

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Section: Discussionmentioning

confidence: 70%

Performances of the Electric Vehicles With Different Charging Methods

Jakimovska¹,

Vasileva²,

Bartłomiejczyk³

2021

MESJ

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“…Similarly, [26] studies the traditional charging location problem with a unified objective function taking into consideration the cost of installing the facilities, transportation costs derived from completing the trips, and the electricity price at different times of the day. In a similar context, [27] proposed a slightly simpler objective for the model to balance the "environment equity and the capital investment". That model extends [28] aiming at developing a system for a partial replacement of the entire diesel-engine fleet for a mixedone.…”

Section: Related Workmentioning

confidence: 99%

“…First, it is important to have a consistent charging schedule, which prevents the occupation of chargers already in use. Although [28] and [27] allow simultaneous charges in the same location by installing multiple chargers in a single charging station, in some circumstances, making the buses wait could be more cost-effective. Therefore, our model includes a group of non-overlapping constraints, which essentially prevents two buses from charging simultaneously in the same charger.…”

Section: Related Workmentioning

confidence: 99%

“…Then, if a charger is occupied (for primary/backup route), the other buses (in the other type of route) must wait until it is released. The new non-overlapping constraints between primary and backup routes are defined in Constraints [26][27][28][29][30][31]. Note that we use the double apostrophe for the variables z and Z because the single apostrophe was already used for the overlapping constraints related only to the backup route, while these constraints represent a mixture between primary and backup.…”

Section: F Non-overlapping Between Primary and Backup Routesmentioning

confidence: 99%

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Robust eBuses Charging Location Problem

Quintana

Arbeláez²,

Climent³

2022

IEEE Open J. Intell. Transp. Syst.

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The implementation of a sustainable and efficient electric bus (eBus) transportation network requires addressing multiple concerns, such as limited driving range and battery charging/discharging time. Currently, eBuses can travel between 200 to 300 km on a single charge, and fast charging stations can fully recharge a battery in a matter of minutes. However, a failure in a charging station might negatively impact the operation of the system with unnecessary delays for the users. Taking this into account, we propose and implement a model for the Robust eBuses Charging Location problem that takes into account potential vulnerabilities of the transportation system. Our model incorporates a protection mechanism that allows eBuses to reach a backup charging station in case the regular one is down. We propose a MIP model to tackle this problem with minimal disruptions in the regular operation of the eBuses. Furthermore, we also present a Large Neighbourhood Search framework to efficiently tackle the problem. Our empirical evaluation suggests that our framework can operate a robust service with a small number of charging stations for three Irish cities and our Large Neighbourhood Search approach largely outperforms a popular commercial MIP solver.

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“…More recent CLP publications introduced models that allow charging location planning for entire bus networks including multiple bus lines (cf. Kunith et al 2016, Kunith et al 2017, Sebastiani et al 2016, Xylia et al 2017b, Xylia et al 2017a, Lotfi et al 2020, Zhou et al 2020. When accounting for multiple bus lines, synergies between several bus lines can be leveraged to identify better solutions compared to considering bus lines separately, as buses that operate on different bus lines can use the same charging stations.…”

Section: Charging Location Problemsmentioning

confidence: 99%

A Concise Guide on the Integration of Battery Electric Buses into Urban Bus Networks

Dirks,

Wagner,

Schiffer

et al. 2021

Preprint

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With the increasing market penetration of battery-electric buses into urban bus networks, practitioners face many novel planning problems. As a result, the interest in optimizationbased decision-making for these planning problems increases but practitioners' requirements on planning solutions and current academic approaches often diverge. Against this background, this survey aims to provide a concise guide on optimization-based planning approaches for integrating battery-electric buses into urban bus networks for both practitioners and academics. First, we derive practitioners' requirements for integrating battery-electric buses from state-of-the-art specifications, project reports, and expert knowledge. Second, we analyze whether existing optimization-based planning models fulfill these practitioners' requirements. Based on this analysis, we carve out the existing gap between practice and research and discuss how to address these in future research.

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Bi-Objective Optimization for Battery Electric Bus Deployment Considering Cost and Environmental Equity

Cited by 41 publications

References 40 publications

Performances of the Electric Vehicles With Different Charging Methods

Performances of the Electric Vehicles With Different Charging Methods

Robust eBuses Charging Location Problem

A Concise Guide on the Integration of Battery Electric Buses into Urban Bus Networks

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