The Shortest Path Problems in Battery-Electric Vehicle Dispatching with Battery Renewal

Huang, Minfang; Li, Jingquan

doi:10.3390/su8070607

Cited by 9 publications

(8 citation statements)

References 28 publications

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“…Constraint (14) calculates the total power injection of each node after the charging stations connect to the grid. Constraint (15) indicates that the total loads cannot be greater than the grid's capacity. Constraint (16) suggests the fluctuation range of the voltage.…”

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confidence: 99%

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Charging Network Planning for Electric Bus Cities: A Case Study of Shenzhen, China

et al. 2019

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In 2017, Shenzhen replaced all its buses with battery e-buses (electric buses) and has become the first all-e-bus city in the world. Systematic planning of the supporting charging infrastructure for the electrified bus transportation system is required. Considering the number of city e-buses and the land scarcity, large-scale bus charging stations were preferred and adopted by the city. Compared with other EVs (electric vehicles), e-buses have operational tasks and different charging behavior. Since large-scale electricity-consuming stations will result in an intense burden on the power grid, it is necessary to consider both the transportation network and the power grid when planning the charging infrastructure. A cost-minimization model to jointly determine the deployment of bus charging stations and a grid connection scheme was put forward, which is essentially a three-fold assignment model. The problem was formulated as a mixed-integer second-order cone programming model, and a “No R” algorithm was proposed to improve the computational speed further. Computational studies, including a case study of Shenzhen, were implemented and the impacts of EV technology advancements on the cost and the infrastructure layout were also investigated.

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confidence: 99%

“…In this study, the charging stations which are planned are plug-in charging stations. Currently, there are three charging technologies: battery swapping [14,15], plug-in charging [16,17], and wireless charging [18]. Each has its advantages and disadvantages.…”

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confidence: 99%

Charging Network Planning for Electric Bus Cities: A Case Study of Shenzhen, China

et al. 2019

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“…Batteries (BTs) devices are generally characterized by their higher specific energy compared to UCs. In fact, BTs can provide additional power for a long time [9]. However, UCs are inserted to control transient power compared to BTs due to their high power, higher efficiency and longer charging/discharging cycles [10].…”

Section: Introductionmentioning

confidence: 99%

Hybrid Electric Vehicle: Design and Control of a Hybrid System (Fuel Cell/Battery/Ultra-Capacitor) Supplied by Hydrogen

Gherairi

2019

Energies

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Due to its high efficiency and reduced emissions, new zero-emission hybrid electric vehicles have been selected as an attractive challenge for future transport applications. New zero -emission hybrid electric, on the other hand, has some major drawbacks from the complicated charging process. The hybrid electrical fuel cell system is introduced as the main source to intelligently control multi-source activities. An ultra-capacitor system is selected as the energy recovery assistance to monitor the fuel cell’s fast transient and peak power during critical periods. To regulate energy demand and supply, an intelligent energy management system is proposed and tested through several constraints. The proposed approach system aims to act quickly against sudden circumstances related to hydrogen depletion in the prediction of the required fuel consumption basis. The proposed strategy tends to define the proper operating system according to energy demand and supply. The obtained results show that the designed system meets the targets set for the energy management unit by referring to an experimental velocity database.

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“…Huang et al studied the shortest path problems in electric transit bus scheduling and electric truck routing with time windows and developed a label-correcting algorithm with state space relaxation to find optimal solutions. The computational experiments resulted show that the label-correcting algorithm performed very well [27]. Han et al confronted the problem of an aggregator coordinating charging schedules of electric vehicles with the objective of minimizing the total charging cost, using the assumption that the maximum charging power could vary according to the current state of charge.…”

Section: Introductionmentioning

confidence: 99%

Combinational Scheduling Model Considering Multiple Vehicle Sizes

Gong

2019

Sustainability

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Urban public transport is an effective way to solve urban traffic problems and promote sustainable development of urban traffic. A scientific operation scheduling system has an important guiding significance for optimizing the configuration of urban public transport capacity resources, improving the level of operation organization and management, and providing for the sustainability of the transportation system. According to the inhomogeneous distribution of passenger flow along transit lines, this study develops a combinational scheduling model in which the enterprise supplies zonal service based on regular service. The objective function minimizes the sum of passenger travel cost and operation cost, and the simulated annealing algorithm is designed to solve the optimization model. This paper abstracts an ideal example by taking a real-world case of Bus Line 131 in Lanzhou, China. The numerical example is used to verify the validity of the model and algorithm. Results show that the combinational operation scheme can effectively satisfy passengers’ demand and reduce the total cost by 7.03% in comparison with the regular operation system. The optimal combinational system with the lowest total cost can increase the vehicle load factor and improve the utilization ratio.

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The Shortest Path Problems in Battery-Electric Vehicle Dispatching with Battery Renewal

Cited by 9 publications

References 28 publications

Charging Network Planning for Electric Bus Cities: A Case Study of Shenzhen, China

Charging Network Planning for Electric Bus Cities: A Case Study of Shenzhen, China

Hybrid Electric Vehicle: Design and Control of a Hybrid System (Fuel Cell/Battery/Ultra-Capacitor) Supplied by Hydrogen

Combinational Scheduling Model Considering Multiple Vehicle Sizes

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