Academic literature on the topic 'Battery swapping'
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Journal articles on the topic "Battery swapping"
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.
Full textZu, 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.
Full textWang, 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.
Full textQiang, 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.
Full textWu, 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.
Full textWu, 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.
Full textBhumarkar, 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.
Full textWang, 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.
Full textPurnamasari, 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.
Full textLiu, 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.
Full textDissertations / Theses on the topic "Battery swapping"
Pedron, Alessandro <1988>. "Possibilità di sviluppo del mercato delle auto elettriche tramite il battery swapping." Master's Degree Thesis, Università Ca' Foscari Venezia, 2014. http://hdl.handle.net/10579/4187.
Full textInfante, William Ferrer. "Stochastic Approaches in Developing Business Models and Strategies for Electric Vehicle Battery Swapping Stations." Thesis, The University of Sydney, 2019. https://hdl.handle.net/2123/21341.
Full textCARFAGNA, GIUSEPPE. "Integrated energy interchange platform between green system of smart housing and smart mobility." Doctoral thesis, Università degli Studi di Camerino, 2018. http://hdl.handle.net/11581/408083.
Full textFU, SHU-YUAN, and 傅淑媛. "The Satisfaction of Battery Swapping Station for Electric Motorcycle." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/f3tdq5.
Full text逢甲大學
工業工程與系統管理學系
106
The theme of this research is based on satisfaction survey of battery exchange stations for electric-motorcycle. Starting with overviews of current electric motorcycle market in Taiwan. Using the SERVQUAL scale, it analyzes how the consumer is evaluating business model of the battery exchanges. Research methods are questionnaires involving how to satisfy the costumer, upon using battery exchange station and most important, the cost of running the station.Then using SPSS to conduct statistical analysis and hypothesis verification, and empirically analyze consumer usage behavior and influences on the purchase intention. By gathering relevant datas, this research hopes draw specific conclusion on the customer's consumption factors, and to make ways for the government to raise electric motorcycle's visibility, at the same time for the manufactures gain edges on competitors by creating products that can improve customer satisfaction and gain customer loyalty.
Lou, Si-Yan, and 樓熹妍. "A Location Problem of Battery-Swapping Stations for Electric Scooters." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/ns4u9r.
Full text國立臺灣大學
土木工程學研究所
105
Because of the global warming, governments in many countries replace fossil fuel with green energy. In Taiwan, greenhouse emission from transportation industry accounts for twenty-two percent of total air pollution. In order to reduce pollution, some country (city) governments will compensate for those users who switch from gasoline-fueled scooter to electric scooter. Therefore, there are more and more electric scooter users in Taiwan for recent years. The charging systems of electric scooter can be generally divided into two; one is charging batteries and the other is swapping batteries. The former means that users charge their own batteries and the latter users swap the low power battery with high one. Batteries swapping system can be defined as a process that users exchange a lower power battery for higher one at the specific location, swapping batteries station. Due to the special design swapping batteries station, electric vehicle system can extend the battery Life-cycle and collect the Driving Behavior data. Thus, batteries swapping system has become the main service for electric scooter users to charge energy. The topic of this research is to decide the location of batteries swapping stations which considering batteries activity (charging or staying full capacity) at swapping station and batteries activity at user side (consuming or waiting for battery). The problem is formulated as a stochastic programming problem. The objective of this paper is to minimize the total expected cost of station installation cost and the user swapping inconvenience.
TONG, CHIA-YUN, and 董家昀. "An Optimization of Electric Scooter Battery swapping station Operation Cost." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/e536x7.
Full text逢甲大學
工業工程與系統管理學系
106
In this study, we used a particle swarm optimization algorithm to solve the minimize cost of an electric scooter battery swapping and used Matlab 2015b to assist in the composition of the PSO. In order to analyze the problems commonly faced by battery swapping stations, that is, sometimes no full battery can be swap, so we have built a mathematical model to solve the following problems. How many batteries should be prepare and how much battery inventory is needed, and considering the cost of damage to the charge, these issues need to be balanced. Expect to help domestic electric mobility companies, while setting up battery exchange stations and expanding the power grid, can help assess the number of batteries that need to be set up.
劉昭吟. "Application of Erlang’s Loss Model to Capacity Decision in Battery Swapping Station." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/bp82gz.
Full text國立中正大學
企業管理系研究所
106
In a battery swapping station (BBS), blocking occurs when an arriving customer finds no fully-charged batteries available for swapping. Service level of BSS depends on how often blocking occurs, and the probability of blocking in turn is determined by the capacity of BSS, battery characteristics, swapping policies, etc. This thesis aims at investigating the impact of capacity, charging ability, swapping policies and replacement conditions on the blocking probability of a single BSS. Based on Erlang’s Loss Model, we develop in this thesis different queueing models that take into consideration of the effect of broken batteries in BSS. The objective is to analyze, through the developed queueing models, how the blocking probability is affected by the station capacity, the maximal broken batteries allowed, battery charging ability, and swapping policies and replacement conditions. Detailed sensitivity analysis of numerical examples is conducted, which may provide useful information for capacity decision making of BSS for electric vehicle suppliers.
Chen, Yun-Ju, and 陳韻如. "Location Optimization of Battery Swapping Stations for Electric Scooters using Stochastic Discrete-event Simulation." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/x6cug3.
Full text國立臺灣大學
土木工程學研究所
107
In recent years, along with raising environmental consciousness, an innovative transportation mode—electric vehicles have gotten many attentions. Because the power source of electric vehicles is electric power, a renewable and environmentally friendly energy, worldwide countries have been devoted to the popularization of electric vehicles and Taiwan is no exception. However, there are two principal challenges for the penetration of electric vehicles: the limited endurance of the mode and its expensive batteries. The limited endurance lets the user has to refuel the energy during a certain using period and the problem of range anxiety comes out. Hence, an auxiliary equipment—the refueling facility is necessary for electric vehicles and it is essential to locate the charger appropriately. Actually, there already are many types of refueling methods and one of the innovative and promising ways is the swapping system. The swapping system reduces the entire refueling time from original several hours to a few minutes or even seconds. This user-friendly advantage lets the user conducts the refueling on the road become much more possible but on the other side, this benefit also increases the need for spare batteries. Therefore, not only the location but also the capacity of swapping stations has to be cautiously determined by the operator. Nevertheless, it is thorny to decide where and how big the swapping station should be directly, so the purpose of this research is to develop a model for deploying the refueling facilities of the swapping system. In addition, because the most popularized transportation mode in Taiwan is scooters, the research object of this study is electric scooters. In order to enhance the applicability of the model and depict the usage behavior conveniently, the methodology adopted in this study combines the genetic algorithm and the discrete-event simulation forming a two-stage planning. In addition, considering the usage habits of the swapping system, the notion of flow interception is adopted in the model. After the sensitivity analysis of experiments, it is found that different parameters have diverse impacts on different shapes of demand spatial distribution. Regular spatial distribution is much more sensitive to the budget and the irregular one is sensitive to the power consumption rate of batteries. Noteworthily, a factor significantly influencing both the shape of demand distribution is the driving endurance. With the case study in the reality, some setting instructions for such a location problem have been obtained. The operator who is going to plan a layout for swapping stations should adopt the entire traffic “flow” rather than the traffic “zone”. Besides, the operator should give a locating priority to the station where is near heavy traffic flows regardless of the shape of demand distributions. Further, considering the user’s maximum tolerable driving distance for swapping, the operator should radially deploy the station taking origins and destinations as the center. Many important factors are considered in the model such as the demand uncertainty, driving endurance, the tolerance of the user, usage behavior and the varied charging power levels by charging time. This is the first time that a model takes these significant factors into account at the same time. What’s more, after the experiments and the case study, the utility and validity of the model are exhibited and these results also show the importance of considering usage behavior. Thus, this model can be a useful tool to help the operator to decide a proper deployment of swapping stations for electric scooters.
Book chapters on the topic "Battery swapping"
Zhang, Yuqing. "Electric Vehicle Battery Charging Scheduling Under the Battery Swapping Mode." In Lecture Notes in Operations Research, 269–78. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-90275-9_22.
Full textHuang, Fei-Hui. "Measuring User Experience of Using Battery Swapping Station." In Advances in Intelligent Systems and Computing, 656–64. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-60492-3_62.
Full textHuang, Fei-Hui. "Measuring User Experience of Seniors in Battery Swapping Interactions." In Intelligent Human Systems Integration, 508–14. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-73888-8_79.
Full textHuang, Fei-Hui. "Exploring Information Needs of Using Battery Swapping System for Riders." In Human Interface and the Management of Information: Applications and Services, 531–41. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-40397-7_51.
Full textRaj, Neha, Manikanta Suri, and K. Deepa. "Integration of Battery Charging and Swapping Using Metaheuristics: A Review." In Lecture Notes in Electrical Engineering, 247–58. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-2354-7_23.
Full textKumar, Mukesh, and Sarita Baghel. "Solar Energy Production Onsite for Battery Swapping Stations in Delhi." In Lecture Notes in Mechanical Engineering, 149–56. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9613-8_14.
Full textHussain, Md Muzakkir, Mohammad Saad Alam, and M. M. Sufyan Beg. "A FOG Computing Based Battery Swapping Model for Next Generation Transport." In Proceedings of 2nd International Conference on Communication, Computing and Networking, 957–68. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1217-5_94.
Full textJatschka, Thomas, Fabio F. Oberweger, Tobias Rodemann, and Gunther R. Raidl. "Distributing Battery Swapping Stations for Electric Scooters in an Urban Area." In Optimization and Applications, 150–65. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-62867-3_12.
Full textHuang, Fei-Hui. "System Acceptability Evaluation of Battery Swapping System for Electric Two Wheelers." In Advances in Ergonomics Modeling, Usability & Special Populations, 325–37. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-41685-4_29.
Full textJatschka, Thomas, Matthias Rauscher, Bernhard Kreutzer, Yusuke Okamoto, Hiroaki Kataoka, Tobias Rodemann, and Günther R. Raidl. "A Large Neighborhood Search for Battery Swapping Station Location Planning for Electric Scooters." In Computer Aided Systems Theory – EUROCAST 2022, 121–29. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-25312-6_14.
Full textConference papers on the topic "Battery swapping"
Jain, Shubham, Zaurez Ahmad, Mohammad Saad Alam, and Yasser Rafat. "Battery Swapping Technology." In 2020 5th IEEE International Conference on Recent Advances and Innovations in Engineering (ICRAIE). IEEE, 2020. http://dx.doi.org/10.1109/icraie51050.2020.9358366.
Full textLee, Danny, Joe Zhou, and Wong Tze Lin. "Autonomous battery swapping system for quadcopter." In 2015 International Conference on Unmanned Aircraft Systems (ICUAS). IEEE, 2015. http://dx.doi.org/10.1109/icuas.2015.7152282.
Full textLu, Honghao. "Electric Vehicle Battery Swapping Station Design." In PRIS 2020: 2020 International Conference on Pattern Recognition and Intelligent Systems. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3415048.3416105.
Full textMurali, Vidhya, Abhik Banerjee, and Vijendran Gopalan Venkoparao. "Optimal Battery Swapping Operations Using Reinforcement Learning." In 2019 Fifteenth International Conference on Information Processing (ICINPRO). IEEE, 2019. http://dx.doi.org/10.1109/icinpro47689.2019.9092262.
Full textPradhan, Rohan, Shaswat Saxena, Akarsh Kumar Singh, and Jabir Ali. "Battery Swapping System for the Electric Vehicles." In 2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS). IEEE, 2022. http://dx.doi.org/10.1109/icccis56430.2022.10037225.
Full textDreyfuss, Michael, and Yahel Giat. "Optimizing Spare Battery Allocation in an Electric Vehicle Battery Swapping System." In 6th International Conference on Operations Research and Enterprise Systems. SCITEPRESS - Science and Technology Publications, 2017. http://dx.doi.org/10.5220/0006115000380046.
Full textYou, Pengcheng, Zaiyue Yang, and Yongmin Zhang. "Efficient battery charging schedule of battery-swapping station for electric buses." In 2015 European Control Conference (ECC). IEEE, 2015. http://dx.doi.org/10.1109/ecc.2015.7330563.
Full textYou, Pengcheng, Peng Cheng, John Z. F. Pang, and Steven H. Low. "Efficient Online Station Assignment for EV Battery Swapping." In e-Energy '18: The Ninth International Conference on Future Energy Systems. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3208903.3212032.
Full textHui, Qi, and Wang Xin. "Electric bus battery-swapping system based on robots." In 2012 2nd International Conference on Consumer Electronics, Communications and Networks (CECNet). IEEE, 2012. http://dx.doi.org/10.1109/cecnet.2012.6202178.
Full textWang, Yang, Liusheng Huang, Hao Wei, Wei Zheng, Tianbo Gu, and Hengchang Liu. "Planning Battery Swapping Stations for Urban Electrical Taxis." In 2015 IEEE 35th International Conference on Distributed Computing Systems (ICDCS). IEEE, 2015. http://dx.doi.org/10.1109/icdcs.2015.87.
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