A New Method to Plan the Capacity and Location of Battery Swapping Station for Electric Vehicle Considering Demand Side Management

Liu, Wenxia; Niu, Shuya; Xu, Huiting; Li, Xiaoying

doi:10.3390/su8060557

Cited by 25 publications

(4 citation statements)

References 17 publications

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“…Electric buses provide an attractive solution for reducing greenhouse gas emissions. Existing studies on electric buses mainly focus on the planning of charging infrastructure (16)(17)(18)(19)(20), the evaluation of lifecycle costs (21,22), and the fleet transition problem (23). As far as the VSP of electric buses is concerned, studies have mainly looked at vehicle scheduling and charging strategies (24)(25)(26)(27).…”

Section: Literature Reviewmentioning

confidence: 99%

Optimization of Electric Bus Scheduling Considering Charging Station Resource Constraints

Zhang,

Yang,

et al. 2023

Transportation Research Record: Journal of the Transportation R

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The electrification of bus systems is an inevitable trend in sustainable urban development because electric buses do not use fossil fuels and, therefore, do not exacerbate energy shortages. However, because of their limited driving range and the restricted charging station resources, it is crucial to optimize the scheduling and charging plan for electric buses jointly to ensure operational efficiency. This paper studies the electric bus scheduling problem considering charging station resource constraints, including the limited number of chargers and total power output, which are generally simplified in the relevant literature. We first formulate a nonlinear model to optimize vehicle scheduling, charging time, and charging power, to minimize the total system costs, including the usage costs of electric buses and charging costs. Then, a genetic algorithm is developed to solve this model. Finally, the proposed method is demonstrated by using the example of a transit network in Nanjing. Compared with the existing scheme based on an uncontrolled charging strategy, the proposed solution reduces the total system costs and charging costs by 7.34% and 36.51%, respectively. The findings in this paper can provide practical guidance on electric bus scheduling and promote the sustainable development of bus systems.

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Section: Literature Reviewmentioning

confidence: 99%

Optimization of Electric Bus Scheduling Considering Charging Station Resource Constraints

Zhang,

Yang,

et al. 2023

Transportation Research Record: Journal of the Transportation R

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“…In addition, each cell has a specific operational nation due to the distinction in temperature, state of health, and country of price. erefore, for a green and safe operation, each battery cell wishes to be monitored independently [26].…”

Section: Why the Bms Is Required In Evmentioning

confidence: 99%

Review on Li-Ion Battery with Battery Management System in Electrical Vehicle

Ramkumar

Reddy²,

Ramakrishnan

et al. 2022

Advances in Materials Science and Engineering

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In this paper, functions of BMS in elections vehicles are explained. The BMS consists of number of electronics components for monitoring and controlling the functions of batteries in electrical vehicles (EVs). Nowadays, the EV has more concentrations because it has number of merits like compact in size, does not require fossil fuel so it is environment friendly, and cost-saving. The main components in EV are batteries because batteries decide the performance and efficiency of EV. So, we should give more importance to batteries. Battery is controlled and monitored with the help of BMS. The BMS protects the battery and increases life time and efficiency due to charging discharging process.

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“…Due to the limited travel range of e-buses, the deployment of a switching station network is very important. Liu et al (2016) present a new method to determine the capacity and location of a battery swapping station (BSS), respectively [38]. By minimizing the net losses of a distribution system, they propose a model for optimal locations of BSSs.…”

Section: Location Optimization Of Battery Swapping Stationsmentioning

confidence: 99%

Electric Vehicle Routing Problem with Battery Swapping Considering Energy Consumption and Carbon Emissions

2020

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In this paper, we study an electric vehicle routing problem while considering the constraints on battery life and battery swapping stations. We first introduce a comprehensive model consisting of speed, load and distance to measure the energy consumption and carbon emissions of electric vehicles. Second, we propose a mixed integer programming model to minimize the total costs related to electric vehicle energy consumption and travel time. To solve this model efficiently, we develop an adaptive genetic algorithm based on hill climbing optimization and neighborhood search. The crossover and mutation probabilities are designed to adaptively adjust with the change of population fitness. The hill climbing search is used to enhance the local search ability of the algorithm. In order to satisfy the constraints of battery life and battery swapping stations, the neighborhood search strategy is applied to obtain the final optimal feasible solution. Finally, we conduct numerical experiments to test the performance of the algorithm. Computational results illustrate that a routing arrangement that accounts for power consumption and travel time can reduce carbon emissions and total logistics delivery costs. Moreover, we demonstrate the effect of adaptive crossover and mutation probabilities on the optimal solution.

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A New Method to Plan the Capacity and Location of Battery Swapping Station for Electric Vehicle Considering Demand Side Management

Cited by 25 publications

References 17 publications

Optimization of Electric Bus Scheduling Considering Charging Station Resource Constraints

Optimization of Electric Bus Scheduling Considering Charging Station Resource Constraints

Review on Li-Ion Battery with Battery Management System in Electrical Vehicle

Electric Vehicle Routing Problem with Battery Swapping Considering Energy Consumption and Carbon Emissions

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