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Journal articles on the topic 'Battery swapping'

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Author: Grafiati

Published: 9 March 2023

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1

Chudy, Aleksander. "BATTERY SWAPPING STATIONS FOR ELECTRIC VEHICLES." Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska 11, no. 2 (June 30, 2021): 36–39. http://dx.doi.org/10.35784/iapgos.2654.

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Battery swapping is a promising technology when compared with the traditional electric vehicle charging stations. The time spent at a battery swapping station might be similar to the time spent at a filling station. The article presents information on attempts to implement this solution, methods of battery swapping, infrastructure and operation of battery swapping stations, as well as the benefits and key challenges of the battery swapping technology.

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2

Zu, Shengdong, and Lijiang Sun. "Optimization Model of Pure Electric Vehicle Battery-Swapping Dispatch Based on Transportation Problems." E3S Web of Conferences 185 (2020): 01026. http://dx.doi.org/10.1051/e3sconf/202018501026.

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The optimization object of pure electric vehicle battery-swapping service dispatch is making the total cost to be minimum under the condition of meeting the battery-swapping demand. The battery-swapping service requires each charging station to scientifically transport the supplementary batteries of the electricity exchange station. It is a multi-objective optimization decision-making process. With the object of minimizing the total cost of one-time transportation, applying the transportation problems theory, an optimization model of the battery-swapping service between the charging station and the exchange station was established, and a typical example was analyzed. The results show that the battery-swapping service transportation line is one of the main factors affecting the cost of pure electric vehicle battery-swapping service dispatch.

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3

Wang, Xin, Jing Wang, and Yan Zhang. "Research on a Current Electric Bus Battery Swapping System Based on the Cartesian Coordinate Robot." Applied Mechanics and Materials 713-715 (January 2015): 715–18. http://dx.doi.org/10.4028/www.scientific.net/amm.713-715.715.

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Electric vehicle is a prominent representative domain in the exploitation of new energy resources, which will be the trend of automotive industry in the future. The purpose of the scheme is to provide a current electric bus battery swapping system based on the Cartesian coordinate robot to solve the pressure of petroleum resources and air pollution. In this paper, the battery swapping robot and battery pack lifting robot are the key of the battery swapping system, which will be discussed in detail. Experiments show that the positioning precision during the swapping process is high, the position is accuracy, and the swapping speed is moderate.

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4

Qiang, Hao, Yanchun Hu, Wenqi Tang, and Xiaohua Zhang. "Research on Optimization Strategy of Battery Swapping for Electric Taxis." Energies 16, no. 5 (February 27, 2023): 2296. http://dx.doi.org/10.3390/en16052296.

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Nowadays, sustainability-related issues have attracted growing attention due to fossil fuel depletion and environmental concerns. Considering many cities have gradually replaced taxis with electric vehicles (EVs), to reduce greenhouse gas emissions and traditional energy consumption, this paper studies the optimization strategy of battery swapping for electric taxis (ETs), and it is not only to ease congestion in the battery swapping station (BSS) but also for electric taxis to address their range anxiety and maximize their benefits. Firstly, based on the road network, the Dijkstra algorithm is adopted to provide the optimal path for ETs to BSSs with the minimum energy consumption. Then, this paper proposes the optimization objective function with minimum cost, which contains the battery service cost based on the battery’s state of charge, waiting cost caused by waiting for swapping battery in BSSs and the carbon emission reduction benefit generated during ETs driving to BSSs, and uses a mixed-integer linear programming (MILP) algorithm to solve this function. Finally, taking the Leisure Park of Laoshan City in Beijing as an example, the numerical simulation is carried out and the proposed battery swapping strategy is efficient to alleviate the congestion of BSSs and maximize the total benefit of ETs, and the cost based on the proposed strategy is 14.21% less than that of disorderly swapping.

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5

Wu, Xiaoyuan, Pengyu Liu, and Xinbao Lu. "Study on Operating Cost Economy of Battery-Swapping Heavy-Duty Truck in China." World Electric Vehicle Journal 12, no. 3 (September 4, 2021): 144. http://dx.doi.org/10.3390/wevj12030144.

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In recent years, battery-swapping heavy-duty trucks have seen rapid growth in China. Summarizing from the practical experiences gained in this development, and starting from market research and analysis of the most typical city of application case, Beijing, we aim to achieve the following: (ⅰ) Establish an operating cost model for battery-swapping heavy-duty trucks throughout a full operation cycle from the perspective of a heavy-duty truck freight transport capacity operator, based on four key cost dimensions, including transportation equipment, operation and maintenance, environmental protection compensation, and battery recycling compensation. (ⅱ) Calculate and compare the operating cost economy of battery-swapping heavy-duty trucks and other types of heavy-duty truck under different energy supplement modes, including charging, hydrogenation, and diesel. (ⅲ) Propose suggestions for faster and more successful heavy-duty truck electrification. The results indicate that battery-swapping heavy-duty trucks have good cost economy in a full operation cycle under specific scenario, and their economy will be improved with the popularization of battery-swapping stations.

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6

Wu, Yongzhong, Siyi Zhuge, Guoxin Han, and Wei Xie. "Economics of Battery Swapping for Electric Vehicles—Simulation-Based Analysis." Energies 15, no. 5 (February 25, 2022): 1714. http://dx.doi.org/10.3390/en15051714.

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As electric vehicles have become increasingly popular in recent years, battery swapping technology has been promoted as an alternative to the time-consuming battery charging process. Nevertheless, battery swapping is held back by the trade-off between the additional battery investment and the short service time for users. In this paper, we developed simulation models to analyze the economics of battery swapping systems. In particular, we collected real data from eight battery swapping stations Guangzhou, China for the analysis. The results show that the service levels of the stations are reduced significantly as the number of users increases. On the other hand, economies of scale exists when implementing the battery swapping system. As the number of users increases, to maintain the same level of service level, the cost of the batteries shared by each user decreases. The analysis also suggests that, given the scale of potential users for an area, the marginal utility of increasing the number of stations will diminish. Finally, to maximize the utility and economic return of the service, we identified that there is a trade-off between the number of stations and the amount of batteries equipped in each station.

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7

Bhumarkar, Prafull. "Optimal Cost Analysis of Battery Swapping Station for EV Using PSO." International Journal for Research in Applied Science and Engineering Technology 9, no. 11 (November 30, 2021): 2060–67. http://dx.doi.org/10.22214/ijraset.2021.39162.

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Abstract: Electric vehicles are the demand of the current scenario to fight with the increasing levels of pollution. Electric vehicles operate by getting power from the battery which needs to be charged after a particular duration. Battery swapping stations are used for providing the optimal power for charging these batteries. An algorithm known as Particle swarm optimization can be used to find the optimal cost of these battery swapping stations. The project presents an expository study about ParticleSwarm Optimization and thus various factors related to it. Keywords: Battery Swapping Station, Battery Charging Station, Load flow Analysis, Particle Swarm Optimization

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8

Wang, Xin, and Jing Wang. "Research on Electric Vehicle Charging & Battery Swapping Robot System." Applied Mechanics and Materials 494-495 (February 2014): 20–23. http://dx.doi.org/10.4028/www.scientific.net/amm.494-495.20.

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Electric Vehicle will be the main trend of automotive industry in the future. The purpose of the scheme is to provide electric vehicle charging & battery swapping robot system based on palletizing robot for solving the double pressure of resources and environment problems. In this paper, the battery swapping robot is the key of the system, and will be mainly discussed from the mechanical body and electrical control part in detail. Experiments show that the positioning precision during the battery swapping process is high, the relative displacement is small, the position is accuracy, and the swapping speed is moderate.

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9

Purnamasari, B. D., T. A. A. Jamaluddin, H. Halidah, and F. Armansyah. "Cost and benefit battery swapping business model for indonesian electric two-wheeler." IOP Conference Series: Earth and Environmental Science 1108, no. 1 (November 1, 2022): 012010. http://dx.doi.org/10.1088/1755-1315/1108/1/012010.

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Abstract Government of Indonesia (GoI) plan to achieve Net Zero Carbon by 2060. One of implementation through Electric Vehicle in the transportation sector where it will drive the reduction of emission and accelerate the demand of global battery. Indonesia has strong position in terms of integrated battery industry. In order to support Electric Vehicle ecosystem, one of value chain related to charging station infrastructures. Nowadays, the charging method for electric vehicles commonly used are battery swapping, conductive and inductive charging. In this paper, we will consider battery charging of electric vehicles, especially electric two-wheeler. In this case, the problem of excessive battery charge time is the main consideration of the users. The development of Battery Swapping Station (BSS) may be an alternative to solving these problems. In the meantime, Battery Swapping Station (BSS) needs a high-level view from stakeholders to understand the cost-benefit ratio of this alternative technology. The objectives of this research are to identify, analyze, and evaluate the current Battery Swapping Station (BSS) technology in market. In this research, it is necessary to have results to establish the policy for manufacture considers large capacity batteries and the standards such as types and specification of batteries as well as swapping stations.

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10

Liu, Zhengke, Xiaolei Ma, Xiaohan Liu, Gonçalo Homem de Almeida Correia, Ruifeng Shi, and Wenlong Shang. "Optimizing Electric Taxi Battery Swapping Stations Featuring Modular Battery Swapping: A Data-Driven Approach." Applied Sciences 13, no. 3 (February 3, 2023): 1984. http://dx.doi.org/10.3390/app13031984.

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Optimizing battery swapping station (BSS) configuration is essential to enhance BSS’s energy savings and economic feasibility, thereby facilitating energy refueling efficiency of electric taxis (ETs). This study proposes a novel modular battery swapping mode (BSM) that allows ET drivers to choose the number of battery blocks to rent according to their driving range requirements and habits, improving BSS’s economic profitability and operational flexibility. We further develop a data-driven approach to optimizing the configuration of modular BSS considering the scheduling of battery charging at the operating stage under a scenario of time-of-use (ToU) price. We use the travel patterns of taxis extracted from the GPS trajectory data on 12,643 actual taxis in Beijing, China. Finally, we test the effectiveness and performance of our data-driven model and modular BSM in a numerical experiment with traditional BSM as the benchmark. Results show that the BSS with modular BSM can save 38% on the investment cost of purchasing ET battery blocks and is better able to respond to the ToU price than to the benchmark. The results of the sensitivity analysis suggest that when the peak electricity price is too high, additional battery blocks must be purchased to avoid charging during those peak periods.

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11

Shao, Sujie, Shaoyong Guo, and Xuesong Qiu. "A Mobile Battery Swapping Service for Electric Vehicles Based on a Battery Swapping Van." Energies 10, no. 10 (October 20, 2017): 1667. http://dx.doi.org/10.3390/en10101667.

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12

Zhang, Yusheng. "Analysis of Battery Swapping Technology for Electric Vehicles – Using NIO’s Battery Swapping Technology as an Example." SHS Web of Conferences 144 (2022): 02015. http://dx.doi.org/10.1051/shsconf/202214402015.

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The electric vehicle (EV) industry is growing rapidly at the moment. However, refueling an electric vehicle could be a time-consuming process. This was the case until the emergence of battery swapping technology. Using the battery swapping technology developed by EV manufacturer NIO as an example, this paper aims to analyze the history, current state, and future of the technology. In order to conduct the analysis, data provided by the EV industry is closely examined, as data from NIO is compared with data from other aspects of the EV industry. Through the analysis, it is found that the battery swapping technology provides efficiency and convenience, but is of high cost and lacks adequate infrastructure on a larger scale. Battery swapping technology has a promising future, but in order to effectively compete with conventional technologies such as charging stations, it would be beneficial for the technology to cut down on cost and expand its infrastructure.

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13

Wang, Ning, and Yun Li. "The Economic Benefit of Electric Taxi Based on Total Ownership Cost Model." Advanced Materials Research 724-725 (August 2013): 1379–82. http://dx.doi.org/10.4028/www.scientific.net/amr.724-725.1379.

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To analyze the economic benefit of electric taxi in two different models: battery charging model (ETC) and swapping model (ETS), this paper built total ownership cost model based on purchase and used cost, and equaled the total ownership cost of electric and conventional taxi in the nominal lifetime to get the maximum affordable battery charging price and battery swapping price respectively, which is 1.1 RMB yuan/kWh and 0.54 RMB yuan/km. The results show that ETS has economic advantage over ETC. Adjust the charging and swapping price to 0 RMB yuan, the equilibrium year of ETS is only 0.8 years, compared to ETCs 2.8 years.

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14

Alharbi, Walied, Abdullah S. Bin Humayd, Praveen R. P., Ahmed Bilal Awan, and Anees V. P. "Optimal Scheduling of Battery-Swapping Station Loads for Capacity Enhancement of a Distribution System." Energies 16, no. 1 (December 24, 2022): 186. http://dx.doi.org/10.3390/en16010186.

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A battery-swapping station (BSS) can serve as a flexible source in distribution systems, since electric vehicle (EV) batteries can be charged at different time periods prior to their swapping at a BSS. This paper presents an EV battery service transformation from charging to swapping batteries for EVs for the capacity enhancement of a distribution system. A novel mathematical model is proposed to optimally quantify and maximize the flexibility of BSS loads in providing demand response for the utility operator while considering technical operations in the distribution grid. Case studies and numerical findings that consider data from the National Household Travel Survey and a 32-bus distribution system are reported and discussed to demonstrate the effectiveness of the proposed model. Offering battery-swapping services helps reduce not only the peak load, but also the station operation cost.

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15

Zhang, Xu, Yue Cao, Linyu Peng, Naveed Ahmad, and Lexi Xu. "Towards Efficient Battery Swapping Service Operation Under Battery Heterogeneity." IEEE Transactions on Vehicular Technology 69, no. 6 (June 2020): 6107–18. http://dx.doi.org/10.1109/tvt.2020.2989195.

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16

Vallera, A. M., P. M. Nunes, and M. C. Brito. "Why we need battery swapping technology." Energy Policy 157 (October 2021): 112481. http://dx.doi.org/10.1016/j.enpol.2021.112481.

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17

You, Pengcheng, Youxian Sun, John Pang, Steven Low, and Minghua Chen. "Battery Swapping Assignment for Electric Vehicles." ACM SIGMETRICS Performance Evaluation Review 45, no. 2 (October 11, 2017): 85–87. http://dx.doi.org/10.1145/3152042.3152068.

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18

Ning, Guobao, Zijian Zhen, Peng Wang, Yang Li, and Huaixian Yin. "Economic Analysis on Value Chain of Taxi Fleet with Battery-Swapping Mode Using Multiobjective Genetic Algorithm." Mathematical Problems in Engineering 2012 (2012): 1–15. http://dx.doi.org/10.1155/2012/175912.

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This paper presents an economic analysis model on value chain of taxi fleet with battery-swapping mode in a pilot city. In the model, economic benefits of charging-swapping station group, taxi company, and taxi driver in the region have been taken into consideration. Thus, the model is a multiobjective function and multiobjective genetic algorithm is used to solve this problem. According to the real data collected from the pilot city, the multiobjective genetic algorithm is tested as an effective method to solve this problem. Furthermore, the effects of price of electricity, price of battery package, life cycle of battery package, cost of battery-swapping devices and infrastructure, and driving mileage per day on the benefits of value holders are analyzed, which provide theoretical and practical reference for the deployment of electric vehicles, for the national subsidy criteria adjusment, technological innovation instruction, commercial mode selection, and infrastructure construction.

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19

-Guarin, J. Garcia, W. Infante, J. Ma, D. Alvarez, and S. Rivera. "Optimal scheduling of smart microgrids considering electric vehicle battery swapping stations." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 5 (October 1, 2020): 5093. http://dx.doi.org/10.11591/ijece.v10i5.pp5093-5107.

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Smart microgrids belong to a set of networks that operate independently. These networks have technologies such as electric vehicle battery swapping stations that aim to economic welfare with own resources of smart microgrids. These resources should support other services, for example, the supply of energy at peak hours. This study addresses the formulation of a decision matrix based on operating conditions of electric vehicles and examines economically viable alternatives for a battery swapping station. The decision matrix is implemented to manage the swapping, charging, and discharging of electric vehicles. Furthermore, this study integrates a smart microgrid model to assess the operational strategies of the aggregator, which can act like a prosumer by managing both electric vehicle battery swapping stations and energy storage systems. The smart microgrid model proposed includes elements used for demand response and generators with renewable energies. This model investigates the effect of the wholesale, local and electric-vehicle markets. Additionally, the model includes uncertainty issues related to the planning for the infrastructure of the electric vehicle battery swapping station, variability of electricity prices, weather conditions, and load forecasting. This article also analyzes how both the user and the providers maximize their economic benefits with the hybrid optimization algorithm called variable neighborhood search - differential evolutionary particle swarm optimization. The strategy to organize the infrastructure of these charging stations reaches a reduction of 72% in the overall cost. This reduction percentage is obtained calculating the random solution with respect to the suboptimal solution.

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20

Mitici, Mihaela, Madalena Pereira, and Fabrizio Oliviero. "Electric flight scheduling with battery-charging and battery-swapping opportunities." EURO Journal on Transportation and Logistics 11 (2022): 100074. http://dx.doi.org/10.1016/j.ejtl.2022.100074.

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21

Huang, A. Q., Y. Q. Zhang, Z. F. He, G. W. Hua, and X. L. Shi. "Recharging and transportation scheduling for electric vehicle battery under the swapping mode." Advances in Production Engineering & Management 16, no. 3 (September 30, 2021): 359–71. http://dx.doi.org/10.14743/apem2021.3.406.

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Electric vehicle battery recharging on the swapping mode has grown up as an important option other than the plug-in recharging mode in China, given that several auto giants have been dedicated in constructing their battery swapping systems. However, the lack of effective operational methods on battery recharging and transportation scheduling has aroused a big challenge on the practical application of the swapping mode, which enables the necessity of our work. This study proposes a joint optimization model of recharging and scheduling of electric vehicle batteries with a dynamic electricity price system which is able to identify the optimal charging arrangement (the recharging time and the quantity of recharging batteries) as well as the optimal transportation arrangement (the transportation time and the quantity of transporting batteries). For the validation purpose, a numerical study is implemented based on dynamic electricity prices in Beijing. A sensitivity analysis of parameters is carried out to increase the robustness and provide more managerial insights of the model.

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22

Wu, Shangchen. "A New Design of Battery Swapping Station." Journal of Physics: Conference Series 1996, no. 1 (August 1, 2021): 012008. http://dx.doi.org/10.1088/1742-6596/1996/1/012008.

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Abstract Electric vehicles have developed rapidly in recent years, and have made tremendous contributions to energy conservation, emission reduction, and green travel. However, the long charging time limits the further promotion of electric vehicles. Based on the idea of power exchange instead of charging, this paper puts forward the design plan of the power station and the battery design program suitable for the power exchange mode. A verification analysis was conducted.

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23

Jia, Jun Guo, Jian Xu Xing, Jin Hai Song, Chao Yun Xiao, Jun Jia, Hai Feng Liu, and Song Song Zheng. "Technical requirements and economic benefit evaluation of interaction between vessel charging and battery swapping stations and power Grid." E3S Web of Conferences 256 (2021): 01011. http://dx.doi.org/10.1051/e3sconf/202125601011.

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Electric vessels have developed rapidly with the advancement of transportation electrification in recent years. The power battery capacity of large vessels usually reaches several MWhs, in which case battery change technology is more applicable. A vessel charging and battery swapping station has the dual attributes of power utilization and energy storage and can realize Vessel to Grid through charging and discharging facilities. Aiming at the scenarios of interaction between vessel charging and battery swapping stations and the power grid, this paper studied technical requirements of several participants, established an input-output analysis model and analyzed multiple influencing factors. The results show that revenues cannot be increased effectively with the increase of the number of spare batteries alone; the interactive service can achieve a balance of payments when the battery cost is higher than 1.4 ¥/ Wh, and; benefits may not be gained when the battery life is less than 5 years.

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24

Feng, Yu, and Xiaochun Lu. "Deployment and Operation of Battery Swapping Stations for Electric Two-Wheelers Based on Machine Learning." Journal of Advanced Transportation 2022 (December 29, 2022): 1–21. http://dx.doi.org/10.1155/2022/8351412.

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Battery swapping stations effectively address the challenges of long charging times, lack of charging stations, and safety hazards for electric two-wheelers. With the rapid development of shared electric bicycles and takeaways, the scale of electric two-wheeler users is expanding while generating a huge demand for battery swapping. The research on the planning and operation of battery swapping stations (BSSs) for electric two-wheelers has yet to be widely discussed. This study developed a data-driven optimization model based on machine learning algorithms using Beijing’s battery swapping stations and point of interest (POI) dataset. First, through the spatial features of BSS analyzed by ArcGIS, we found that the coverage of BSSs was mainly concentrated within the fifth ring road, and the utilization rate was unbalanced. Then, on a 3000 m grid scale, a prediction model of BSS quantity with random forest, support vector regression, and gradient-boosting decision tree algorithm was built. The final stacking model was constructed by strengthening three single models with an accuracy of 86.21%. Compared with the original BSSs layout, the machine-learning algorithm proposed in this study can cover more factors and avoid the subjectivity of site selection. Finally, the queuing model for BSSs based on the Monte Carlo simulation was proposed. Through two scenarios, we found that the key parameters m (the number of charging slots) and λ (the user arrival rate) were influential to the outputs of service capability.

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25

Li, Guohao, and Tao Wang. "Long-Term Leases vs. One-Off Purchases: Game Analysis on Battery Swapping Mode Considering Cascade Utilization and Power Structure." Sustainability 14, no. 24 (December 17, 2022): 16957. http://dx.doi.org/10.3390/su142416957.

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The electric vehicle industry faces intense competition and the sustainability problem. In order to obtain a differential competitive advantage, enterprises actively promote the battery swapping mode (BSM) to respond to cost pressures caused by the mismatch between demand and supply. Considering cascade utilization, the Stackelberg game models of electric vehicle supply chain under three different scenarios, in the secondary supply chain consisting of a battery manufacturer (BM) and a vehicle manufacturer (VM), were constructed, respectively. Additionally, then, through the contrastive analysis of differential power structures, the influence of power structures and related parameters on the optimal pricing strategy and enterprise profits of both parties in the supply chain were studied and compared. The conclusions show that the dominance of the supply chain determines the profit level of enterprises in BSM. Compared with VMs, the adoption of the BSM has provided BM greater profit growth. Secondly, the number of reserve batteries in the battery swapping stations and the revenue of cascade utilization are essential factors affecting the profits of battery swapping service (BSS), especially for VMs. In addition, setting a reasonable range for the pricing of BSS can achieve a win–win situation for both manufacturers.

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26

Li, Congbo, Ningbo Wang, Wei Li, Qian Yi, and Dongfeng Qi. "A battery centralized scheduling strategy for battery swapping of electric vehicles." Journal of Energy Storage 51 (July 2022): 104327. http://dx.doi.org/10.1016/j.est.2022.104327.

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27

Shangguan, Zizhuo, and Dongfeng Qi. "Charging Station Planning of Electric Vehicle in Battery Swapping Scene." Journal of Physics: Conference Series 2354, no. 1 (October 1, 2022): 012004. http://dx.doi.org/10.1088/1742-6596/2354/1/012004.

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Abstract In response to the national green development concept, the electric vehicles quantity continues to surge. However, the cost of electric vehicle charging facilities is hindering the development of electric vehicles. Considering charging facility cost and fuel consumption cost of logistics vehicles, we propose the charging planning for electric vehicle batteries. First, according to the user’s mileage, we simulate the maximum demand for electric vehicle batteries in each time. Then, based on the electric vehicle battery charging planning, we establish an optimization model for the number of battery charging equipment and the fuel consumption cost of logistics vehicles. Finally, through specific examples we show the optimal number of delivery is 4 from the battery charging station to the battery swapping station. The battery charging equipment are 368 units and the fuel consumption cost of the logistics vehicle is 8040 RMB per day. In addition, the number of logistics vehicle departures is reduced by 3 compared to the same amount of delivery, which significantly improves the stability and efficiency of the battery swapping scene.

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Adegbohun, Feyijimi, Annette von Jouanne, and Kwang Lee. "Autonomous Battery Swapping System and Methodologies of Electric Vehicles." Energies 12, no. 4 (February 19, 2019): 667. http://dx.doi.org/10.3390/en12040667.

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The transportation industry contributes a significant amount of carbon emissions and pollutants to the environment globally. The adoption of electric vehicles (EVs) has a significant potential to not only reduce carbon emissions, but also to provide needed energy storage to contribute to the adoption of distributed renewable generation. This paper focuses on a design model and methodology for increasing EV adoption through automated swapping of battery packs at battery sharing stations (BShS) as a part of a battery sharing network (BShN), which would become integral to the smart grid. Current battery swapping methodologies are reviewed and a new practical approach is proposed considering both the technical and socio-economic impacts. The proposed BShS/BShN provides novel solutions to some of the most preeminent challenges that EV adoption faces today such as range anxiety, grid reliability, and cost. Challenges and advancements specific to this solution are also discussed.

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Li, Wenxiang, Ye Li, Haopeng Deng, and Lei Bao. "Planning of Electric Public Transport System under Battery Swap Mode." Sustainability 10, no. 7 (July 19, 2018): 2528. http://dx.doi.org/10.3390/su10072528.

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Applying battery electric buses (BEBs) in the city is a good means to reduce the increasing greenhouse gas emissions and crude oil dependence. Limited by the driving range and charging time, battery swap station seems to be the best option for battery electric buses to replenish energy currently. This paper presents a novel method to plan and design an electric public transport system under battery swap mode, which comprised of battery electric buses, routes, scheduling, battery swap station, etc. Thus, new routing and scheduling strategies are proposed for the battery electric bus fleets. Based on swapping and charging demand analysis, this paper establishes an algorithm to calculate the optimal scales of battery swap station, including scales of battery swapping system, battery charging system and battery packs, and power capacity of output. Regarding the case of Xuejiadao battery swap station serving 6 BEB routes in Qingdao, China, a numerical simulation program is established to evaluate the validity of our methods. The results reflect that our methods can optimize the system scales meeting an equivalent state of operation demand. In addition, sensitivity analyses are made to the scales under different values of battery capacity and charging current. It suggests that the scales and cost of battery swap station can be effectively reduced with the development of power battery manufacture and charging technology in future.

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30

Shu, Liu, Fang Liu, and Xiu Yang. "Micro-Grid Energy Optimization Include Battery-Swapping-Station." Applied Mechanics and Materials 672-674 (October 2014): 1358–63. http://dx.doi.org/10.4028/www.scientific.net/amm.672-674.1358.

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Accessing electric vehicle (EV) into micro-grid (MG) by battery-swapping station (BSS) will not only reduce the negative impact brought by EVs which are directly accessed into MG, but also improve the capacity of MG to absorb more renewable energy. That BSS is regarded as schedulable load is guided to avoid peak and fill valley according to TOU. As a result, the gap between peak and valley of MG is decreased and the operation efficiency of MG is elevated. A specific MG is taken as the studying object and the minimum operating cost is regarded as the optimizing goal, then the genetic algorithm is used to optimize the outputting of each micro-source and the charging power of BSS so that the optimal operation is realized.

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31

Revankar, Swapnil R., and Vaiju N. Kalkhambkar. "Grid integration of battery swapping station: A review." Journal of Energy Storage 41 (September 2021): 102937. http://dx.doi.org/10.1016/j.est.2021.102937.

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32

Ban, Mingfei, Jilai Yu, Zhiyi Li, Danyang Guo, and Jing Ge. "Battery Swapping: An aggressive approach to transportation electrification." IEEE Electrification Magazine 7, no. 3 (September 2019): 44–54. http://dx.doi.org/10.1109/mele.2019.2925762.

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Liu, Xiaochuan, Tianyang Zhao, Shuhan Yao, Cheong Boon Soh, and Peng Wang. "Distributed Operation Management of Battery Swapping-Charging Systems." IEEE Transactions on Smart Grid 10, no. 5 (September 2019): 5320–33. http://dx.doi.org/10.1109/tsg.2018.2880449.

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Zeng, Ming, Yifei Pan, Danyang Zhang, Ziyang Lu, and Yong Li. "Data-Driven Location Selection for Battery Swapping Stations." IEEE Access 7 (2019): 133760–71. http://dx.doi.org/10.1109/access.2019.2941901.

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Mak, Ho-Yin, Ying Rong, and Zuo-Jun Max Shen. "Infrastructure Planning for Electric Vehicles with Battery Swapping." Management Science 59, no. 7 (July 2013): 1557–75. http://dx.doi.org/10.1287/mnsc.1120.1672.

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Moon, Joon, Young Joo Kim, Taesu Cheong, and Sang Hwa Song. "Locating Battery Swapping Stations for a Smart e-Bus System." Sustainability 12, no. 3 (February 5, 2020): 1142. http://dx.doi.org/10.3390/su12031142.

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With the growing interest and popularity of electric vehicles (EVs), the electrification of buses has been progressing recently. To achieve the seamless operation of electric buses (e-Buses) for public transportation, some bus stations should play the role of battery swapping station due to the limited travel range of e-Buses. In this study, we consider the problem of locating battery swapping stations for e-Buses on a passenger bus traffic network. For this purpose, we propose three integer programming models (set-covering-based model, flow-based model and path-based model) to model the problem of minimizing the number of stations needed. The models are applied and tested on the current bus routes in the Seoul metropolitan area of South Korea.

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Kanthavel, R. "Ethereum and IOTA based Battery Management System with Internet of Vehicles." September 2021 3, no. 3 (November 1, 2021): 229–40. http://dx.doi.org/10.36548/jucct.2021.3.006.

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The era of Electric Vehicles (EVs) has influenced the very make and manufacture of vehicles resulting in low pollution and advanced battery life. On the other hand, the internet of things has also expanded allowing a number of devices to stay connected using the internet. Massive drawbacks faced by EVs today are the limitation in battery swapping and charging stations and limitation in the range of batteries used. This proposed paper aims to efficiently manage the best battery system apart from building the essential infrastructure. In some cases battery swapping option is also provided through other EV drivers or at registered stations. Hence a complete database of the EV network is required so that it is possible to swap and charge batteries successfully. An EV management using two blockchains as a data layer and network of the application is implemented in this work. The first step involves the development of a blockchain framework using Ethereum and the next step entails a direct acyclic graph. When integrated, these two methodologies prove to be an efficient platform that offers a viable solution for battery management in Electric Vehicles.

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De Silva, Sudam Chamikara, Maroay Phlernjai, Suchada Rianmora, and Photchara Ratsamee. "Inverted Docking Station: A Conceptual Design for a Battery-Swapping Platform for Quadrotor UAVs." Drones 6, no. 3 (February 23, 2022): 56. http://dx.doi.org/10.3390/drones6030056.

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“Flight Time” and the “Scope of the mission” play major roles in using UAVs as they affect most industrial activities. Once the battery has depleted, the UAV has to land on the ground and human interaction is needed to change the battery with a fully charged one. Nowadays, several automatic battery swapping systems are catching interest in research. This research presents the novel concept of an Inverted Docking Station that allows a quadrotor UAV to attach to the ceiling during the automatic battery-swapping process. The proposed design consist of a docking station, a positioning system and gripper mechanisms. The proposed design allows the quadrotor to carry the load under the quadrotor and remain attached throughout the servicing period. A mathematical model and design guideline have been proposed, and a Finite Element Analysis (FEA) was performed to check that the developed platform is strong enough to withstand the above task. A ‘DJI TELLO’ small-scale quadrotor was chosen as a case study to demonstrate the proposed research. Finally the advantages and the limitations of the system are discussed.

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Wu, Shengjun, Qingshan Xu, Qun Li, Xiaodong Yuan, and Bing Chen. "An Optimal Charging Strategy for PV-Based Battery Swapping Stations in a DC Distribution System." International Journal of Photoenergy 2017 (2017): 1–11. http://dx.doi.org/10.1155/2017/1504857.

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Photovoltaic- (PV-) based battery swapping stations (BSSs) utilize a typical integration of consumable renewable resources to supply power for electric vehicles (EVs). The charging strategy of PV-based BSSs directly influences the availability, cost, and carbon emissions of the swapping service. This paper proposes an optimal charging strategy to improve the self-consumption of PV-generated power and service availability while considering forecast errors. First, we introduce the typical structure and operation model of PV-based BSSs. Second, three indexes are presented to evaluate operational performance. Then, a particle swarm optimization (PSO) algorithm is developed to calculate the optimal charging power and to minimize the charging cost for each time slot. The proposed charging strategy helps decrease the impact of forecast uncertainties on the availability of the battery swapping service. Finally, a day-ahead operation schedule, a real-time decision-making strategy, and the proposed PSO charging strategy for PV-based BSSs are simulated in a case study. The simulation results show that the proposed strategy can effectively improve the self-consumption of PV-generated power and reduce charging cost.

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Florea, Bogdan Cristian, and Dragos Daniel Taralunga. "Blockchain IoT for Smart Electric Vehicles Battery Management." Sustainability 12, no. 10 (May 13, 2020): 3984. http://dx.doi.org/10.3390/su12103984.

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Electric Vehicles (EVs) have generated a lot of interest in recent years, due to the advances in battery life and low pollution. Similarly, the expansion of the Internet of Things (IoT) allowed more and more devices to be interconnected. One major problem EVs face today is the limited range of the battery and the limited number of charging or battery swapping stations. A solution is to not only build the necessary infrastructure, but also to be able to correctly estimate the remaining power using an efficient battery management system (BMS). For some EVs, battery swapping can also be an option, either at registered stations, or even directly from other EV drivers. Thus, a network of EV information is required, so that a successful battery charge or swap can be made available for drivers. In this paper two blockchain implementations for an EV BMS are presented, using blockchain as the network and data layer of the application. The first implementation uses Ethereum as the blockchain framework for developing smart contracts, while the second uses a directed acyclic graph (DAG), on top of the IOTA tangle. The two approaches are implemented and compared, demonstrating that both platforms can provide a viable solution for an efficient, semi-decentralized, data-driven BMS.

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Wu, Hao, Grantham Kwok Hung Pang, King Lun Choy, and Hoi Yan Lam. "An Optimization Model for Electric Vehicle Battery Charging at a Battery Swapping Station." IEEE Transactions on Vehicular Technology 67, no. 2 (February 2018): 881–95. http://dx.doi.org/10.1109/tvt.2017.2758404.

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Tan, Xiaoqi, Guannan Qu, Bo Sun, Na Li, and Danny H. K. Tsang. "Optimal Scheduling of Battery Charging Station Serving Electric Vehicles Based on Battery Swapping." IEEE Transactions on Smart Grid 10, no. 2 (March 2019): 1372–84. http://dx.doi.org/10.1109/tsg.2017.2764484.

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Cokyasar, Taner. "Delivery drone route planning over a battery swapping network." Procedia Computer Science 184 (2021): 10–16. http://dx.doi.org/10.1016/j.procs.2021.03.013.

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Ahmad, Furkan, Mohammad Saad Alam, Ibrahim Saad Alsaidan, and Samir M. Shariff. "Battery swapping station for electric vehicles: opportunities and challenges." IET Smart Grid 3, no. 3 (May 19, 2020): 280–86. http://dx.doi.org/10.1049/iet-stg.2019.0059.

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You, Pengcheng, Steven H. Low, Wayes Tushar, Guangchao Geng, Chau Yuen, Zaiyue Yang, and Youxian Sun. "Scheduling of EV Battery Swapping—Part I: Centralized Solution." IEEE Transactions on Control of Network Systems 5, no. 4 (December 2018): 1887–97. http://dx.doi.org/10.1109/tcns.2017.2773025.

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You, Pengcheng, Steven H. Low, Liang Zhang, Ruilong Deng, Georgios B. Giannakis, Youxian Sun, and Zaiyue Yang. "Scheduling of EV Battery Swapping–Part II: Distributed Solutions." IEEE Transactions on Control of Network Systems 5, no. 4 (December 2018): 1920–30. http://dx.doi.org/10.1109/tcns.2017.2774012.

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Infante, William, Jin Ma, and Ariel Liebman. "Operational strategy analysis of electric vehicle battery swapping stations." IET Electrical Systems in Transportation 8, no. 2 (June 2018): 130–35. http://dx.doi.org/10.1049/iet-est.2017.0075.

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Feng, Yu, and Xiaochun Lu. "Construction Planning and Operation of Battery Swapping Stations for Electric Vehicles: A Literature Review." Energies 14, no. 24 (December 7, 2021): 8202. http://dx.doi.org/10.3390/en14248202.

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The popularity of electric vehicles has been limited by factors such as range, long charging times and fast power failure in winter. In order to overcome these challenges, battery swapping stations (BSS) have been constructed and greatly promoted in recent years. In this paper, the related literature on electric vehicle service is reviewed and the co-occurrence of keywords is analyzed using CiteSpace. The literature is classified according to clustering results and recurring themes, such as the location of BSS, inventory decisions, charging strategies and BSS assignment. In each topic, typical optimization models and algorithms proposed in previous studies are summarized. Then, this paper gives a case about the business model and revenue capacity calculation of BSS. Finally, it points out the future research direction of battery swapping stations for electric vehicles.

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Li, Jin, Feng Wang, and Yu He. "Electric Vehicle Routing Problem with Battery Swapping Considering Energy Consumption and Carbon Emissions." Sustainability 12, no. 24 (December 16, 2020): 10537. http://dx.doi.org/10.3390/su122410537.

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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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Jain, Aarav, and Aayan Jain. "BATTERY TECHNOLOGY AND FUTURE OF BATTERY SWAPPING SYSTEM FOR ELECTRIC VEHICLES - OPPORTUNITIES AND CHALLENGES." International Journal of Advanced Research 10, no. 10 (October 31, 2022): 553–67. http://dx.doi.org/10.21474/ijar01/15523.

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