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Keywords = battery swapping van

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19 pages, 5236 KiB  
Article
Optimal Scheduling for Hybrid Battery Swapping System of Electric Vehicles
by Ziqi Wang and Sizu Hou
Processes 2023, 11(6), 1604; https://doi.org/10.3390/pr11061604 - 24 May 2023
Cited by 1 | Viewed by 1602
Abstract
Range anxiety seriously restricts the development of electric vehicles (EVs). To address the above issue, a hybrid battery swapping system (HBSS) is developed in this paper. In the system, EVs can swap their battery at battery swapping stations or by the roadside via [...] Read more.
Range anxiety seriously restricts the development of electric vehicles (EVs). To address the above issue, a hybrid battery swapping system (HBSS) is developed in this paper. In the system, EVs can swap their battery at battery swapping stations or by the roadside via battery swapping vans. The proposed scheduling strategy aims to achieve the best service quality for the HBSS by controlling the mobile swapping service fee. In the model, the uncertainty of EV selection is managed by leveraging the Sigmoid function. Based on proving the uniqueness of the solution, the particle swarm optimization algorithm is used to solve the problem. Simulations validate the effectiveness of the proposed strategy in alleviating range anxiety. Moreover, the impacts of maximum service capacity and the operating rule have been analyzed. Full article
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Figure 1

Figure 1
<p>HBSS structure.</p>
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<p>Schematic diagram of Battery swapping process.</p>
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<p>Probability of selecting the SS mode generated by the Sigmoid function. (<b>a</b>) The influence of swapping cost on the probability of selecting the SS mode; (<b>b</b>) The influence of parameter <span class="html-italic">γ</span> on the probability of selecting the SS mode.</p>
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<p>The flowchart of the HBSS optimal scheduling strategy.</p>
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<p>Traffic network in Beijing.</p>
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<p>Battery swapping demand.</p>
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<p>Simulation results based on the optimal and constant service fee. (<b>a</b>) Case 2; (<b>b</b>) Case 5.</p>
Full article ">Figure 7 Cont.
<p>Simulation results based on the optimal and constant service fee. (<b>a</b>) Case 2; (<b>b</b>) Case 5.</p>
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<p>Time sequence of battery swapping generated by MCS.</p>
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<p>Convergence process.</p>
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<p>Optimization process. (<b>a</b>) Sigmoid functions of EVs selecting actively; (<b>b</b>) Deviation from <span class="html-italic">k</span> with different <math display="inline"><semantics> <mrow> <msub> <mi>l</mi> <mi>t</mi> </msub> </mrow> </semantics></math>.</p>
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<p>Simulation results based on different <span class="html-italic">k</span> and <math display="inline"><semantics> <mrow> <msubsup> <mover accent="true"> <mi>d</mi> <mo>¯</mo> </mover> <mi>i</mi> <mrow> <mi>D</mi> <mi>E</mi> <mi>T</mi> </mrow> </msubsup> </mrow> </semantics></math>. (<b>a</b>) Case 1; (<b>b</b>) Case 2; (<b>c</b>) Case 3; (<b>d</b>) Case 4.</p>
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<p>MS service fees in case 1 to case 4.</p>
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2724 KiB  
Article
A Mobile Battery Swapping Service for Electric Vehicles Based on a Battery Swapping Van
by Sujie Shao, Shaoyong Guo and Xuesong Qiu
Energies 2017, 10(10), 1667; https://doi.org/10.3390/en10101667 - 20 Oct 2017
Cited by 56 | Viewed by 11291
Abstract
This paper presents a novel approach for providing a mobile battery swapping service for electric vehicles (EVs) that is provided by a mobile battery swapping van. This battery swapping van can carry many fully charged batteries and drive up to an EV to [...] Read more.
This paper presents a novel approach for providing a mobile battery swapping service for electric vehicles (EVs) that is provided by a mobile battery swapping van. This battery swapping van can carry many fully charged batteries and drive up to an EV to swap a battery within a few minutes. First, a reasonable EV battery swapping architecture based on a battery swapping van is established in this paper. The function and role of each participant and the relationships between each participant are determined, especially their changes compared with the battery charging service. Second, the battery swapping service is described, including the service request priority and service request queuing model. To provide the battery swapping service efficiently and effectively, the battery swapping service request scheduling is analyzed well, and a minimum waiting time based on priority and satisfaction scheduling strategy (MWT-PS) is proposed. Finally, the battery swapping service is simulated, and the performance of MWT-PS is evaluated in simulation scenarios. The simulation results show that this novel approach can be used as a reference for a future system that provides reasonable and satisfying battery swapping service for EVs. Full article
(This article belongs to the Special Issue Battery Energy Storage Applications in Smart Grid)
Show Figures

Figure 1

Figure 1
<p>EV battery swapping structure based on battery swapping van.</p>
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<p>The general battery swapping service request queuing model.</p>
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<p>General queuing model for a single service area.</p>
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<p>New queuing model for a single service area.</p>
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<p>Scheduling model for the single battery swapping van.</p>
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<p>MWT-PS scheduling strategy.</p>
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<p>performance evaluation with respect to the number of battery swapping vans and fully charged battery capacity (<b>a</b>) miss ratio; (<b>b</b>) average response time.</p>
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<p>Performance evaluation with respect to the number of requests (<b>a</b>) miss ratio; (<b>b</b>) average response time; (<b>c</b>) satisfaction ratio with priority 1 and 2.</p>
Full article ">
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