A Survey on Electric Buses—Energy Storage, Power Management, and Charging Scheduling

Deng, Ruilong; Liu, Yuan; Chen, Wenzhuo; Liang, Hao

doi:10.1109/tits.2019.2956807

Cited by 49 publications

(10 citation statements)

References 111 publications

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“…Those studies on optimal charging schedules for EB transit systems directly relate to transit management of electric buses. In this regard, the survey work done by Deng et al [15] provides an excellent reference on electric buses, energy storage, power management, and charging scheduling. Indeed, this research topic on electric buses or electric vehicles, particularly for public transportation or used for public transit systems, cuts across the two important disciplines-the energy system and transportation field.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The goal is to determine aggregated maximum amounts of energy that can be loaded in a particular hour h (13), which is simply equal to all charging statuses of buses in all minutes belonging to a given hour (14). Charging statuses may not violate bus timetables (15), nor summary chargers number (16), just as in (7) and (8). New constraints introduced into this model ( 17)-( 19) are responsible for ensuring that despite the SoC level at the beginning of each hour being independent of the SoC level at the end of the previous hour (19), charging is still limited by the total amount of energy used so far plus the initial free battery capacity (17).…”

Section: Maximum Hourly Energy Requirementsmentioning

confidence: 99%

See 1 more Smart Citation

Optimal Charging Schedule Planning for Electric Buses Using Aggregated Day-Ahead Auction Bids

Żółtowska

Lin

2021

Energies

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This study aims to plan a cost-minimizing charging schedule for electric buses with fast charging stations. The paper conceptualizes the problem as a three-stage procedure, which is oriented around the participation of an electric bus aggregator in a day-ahead energy auction. First, the aggregation stage determines the bid parameters of buses. With bid parameters, aggregated cost-minimizing charging plans are obtained in the second stage conceived as the hourly day-ahead auction. The disaggregation of hourly plans into feasible minutely charging schedules is the third stage. The main contribution is the formulation of mixed-integer linear programming aggregation models to determine charging availability expressed as minimum and maximum hourly energy requirements taking into account detailed, minutely characteristics and constraints of the charging equipment and the buses. No price forecasts are required, and the plans adjust to the wholesale prices of energy. Defining only a few aggregated bids parameters used in linear programming constraints and incorporating them into the auction model is another contributing factor of this paper, allowing the scheduling of storage-based participants economically. The proposed methodology has been verified on a recently published case study of a real-world bus service operated on the Ohio State University campus. We show that the auction-based charging of all 22 buses outperforms as-soon-as-possible schedules by 7% to even 28% of daily cost savings. Thanks to the aggregated bids, buses can flexibly shift charges between high- and low-price periods while preserving constraints of the charging equipment and timetables.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Maximum Hourly Energy Requirementsmentioning

confidence: 99%

Optimal Charging Schedule Planning for Electric Buses Using Aggregated Day-Ahead Auction Bids

Żółtowska

Lin

2021

Energies

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“…Initial nodes (≤1000) are assumed to be fully charged. When discharging, the buses are not allowed to go under 10% of the total battery capacity, as specified in constraint (6).…”

Section: A Basic Constraintsmentioning

confidence: 99%

“…These new requirements have a direct impact both on the daily operation of such fleets as well as on their composition and cost. Including these properties into the existing route-scheduling systems, such as making sure that the buses have enough energy to cover their trips and enough time to recharge, is crucial for uninterruptable daily operation of electric bus fleets [5,6]. The composition and cost of one fleet is on the other hand also highly dependent on the route scheduling, since it can lead to a smaller number of necessary buses.…”

Section: Introductionmentioning

confidence: 99%

Route Scheduling for Centralized Electric Bus Depots

Jahic

Plenz

Eskander

et al. 2021

IEEE Open J. Intell. Transp. Syst.

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Route scheduling is crucial for uninterrupted operation of modern bus fleets consisting of electric buses. This paper proposes an exact route scheduling optimization model for centralized bus depots based on mixed integer linear programming. In order to adjust to the current situation at many electric bus depots, the model considers a heterogeneous fleet consisting of multiple types of electric buses with different battery capacities. With additional charging scheduling the model can minimize the number of buses charging simultaneously which directly leads to load peak reduction. This allows considering further parameters, such as for example the grid capacity limit. The model can be used to minimize the necessary number of buses, to define the optimum composition of the fleet as well as to minimize the total cost of the fleet. The results show a clear cost advantage of operating a heterogeneous fleet as well as the benefits of combined route-and charging scheduling. Timetables from five real depots from the city of Hamburg in Germany were used as examples in this paper. Analysis of the proposed model using real data can provide a valuable input to other transportation companies preparing for the electrification of their fleet.

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“…Many works based on hybrid electrical transport applications are performed essentially to face environmental issues. Most of the time, three kinds of hybridisation are pointed out: fuel cell (FC)/supercapacitors (SCs), fuel cell/battery (BT) or battery/supercapacitors [1][2][3][4][5][6][7][8][9][10][11] or more sources [12][13][14]. The connection of the power sources is subject to many power electronic topologies.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Control Based on a CAN-Bus of Hybrid Electrical Systems

2020

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Power management of a one-converter parallel structure with battery and supercapacitor is addressed in this paper. The controller is implemented on a DSP from a Microchip and uses a Controller Area Network (CAN) bus communication for data exchange. However, the low data transmission rate of the CAN bus data impacts the performances of regular power management strategies. This paper details an initial strategy with a charge sustaining mode for an application coupling a battery with supercapacitors, in which low performances have been witnessed due to the high sampling time of the CAN bus data. Therefore, a new strategy is proposed to tackle the sample time issue based on a depleting mode. Simulation and experimental results with a dsPIC33EP512MU810 DSP based on a 10 kW hybrid system proves the feasibility of the proposed approach.

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A Survey on Electric Buses—Energy Storage, Power Management, and Charging Scheduling

Cited by 49 publications

References 111 publications

Optimal Charging Schedule Planning for Electric Buses Using Aggregated Day-Ahead Auction Bids

Optimal Charging Schedule Planning for Electric Buses Using Aggregated Day-Ahead Auction Bids

Route Scheduling for Centralized Electric Bus Depots

Real-Time Control Based on a CAN-Bus of Hybrid Electrical Systems

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