Layout Optimization of Static Wireless Charging Facilities for Electric Buses by Considering Battery Degradation Characteristics

被引:0
作者
Wang, Yongxing [1 ]
Bi, Jun [1 ,2 ]
Xie, Dongfan [1 ]
Sai, Qiuyue [3 ]
机构
[1] School of Traffic and Transportation, Beijing Jiaotong University, Beijing
[2] Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong University, Beijing
[3] Institute of Scientific and Technical Information of China, Beijing
来源
Huanan Ligong Daxue Xuebao/Journal of South China University of Technology (Natural Science) | 2024年 / 52卷 / 06期
基金
中国国家自然科学基金;
关键词
battery degradation; electric bus; layout optimization; static wireless charging;
D O I
10.12141/j.issn.1000-565X.230359
中图分类号
学科分类号
摘要
As the existing layout schemes of static wireless charging (SWC) facilities often neglect battery degradation costs, this paper proposes a layout optimization method of SWC facilities for electric buses by considering battery degradation characteristics. Firstly, by considering the operation characteristics of electric buses under opportunity charging mode, a layout optimization method of SWC facilities is developed with simultaneous consideration of charger deployment costs and battery degradation costs, with the function mechanism of battery state of charge (SOC) variety ranges on battery degradation rate being integrated into the model, and with the accumulated energy consumption constraints being introduced in the model to ensure that the SWC layout scheme can satisfy the bus route operation demands. Then, an improved TS (Tabu Search) algorithm is presented to solve the model by overcoming its computational complexity, and the initial solution and neighborhood structure of the algorithm are constructed according to the model characteristics. Finally, a numerical example is designed to verify the model and algorithm. The results indicate that the layout of SWC facilities has significant effects on battery degradation; that the proposed model can reduce 3. 8% of the total annualized cost, as compared with the conventional model that neglects the battery degradation characteristics; that the battery degradation cost accounts for up to 72. 3% of the total annualized cost under current battery technology and cost conditions; and that the improved TS algorithm is better than the original one because it significantly improves the solution efficiency. Moreover, a sensitive analysis is conducted to explore the impacts of multiple critical factors on optimal results, finding that both the upper bound of battery SOC and the SWC facility charging power have significant negative correlation with the total annualized cost, while the battery’s unit capacity cost, the SWC facility layout cost and the vehicle energy consumption rate all have positive correlation with the total annualized cost in various degrees. © 2024 South China University of Technology. All rights reserved.
引用
收藏
页码:45 / 55
页数:10
相关论文
共 33 条
  • [1] QU Xiaobo, LIU Yajun, CHEN Yuwei, Urban electric bus operation management: review and outlook [J], Journal of Automotive Safety and Energy, 13, 3, pp. 407-420, (2022)
  • [2] LAJUNEN A., Lifecycle costs and charging requirements of electric buses with different charging methods, Journal of Cleaner Production, 172, pp. 56-67, (2018)
  • [3] WANG J,, KANG L, LIU Y., Optimal scheduling for electric bus fleets based on dynamic programming approach by considering battery capacity fade [J], Renewable and Sustainable Energy Reviews, 130, pp. 1099781-13, (2020)
  • [4] XU Guizhi, LI Chenxi, ZHAO Jun, Electromag⁃ netic environment safety study of wireless electric vehicle charging [J], Transactions of China Electrotechnical Society, 32, 22, pp. 152-157, (2017)
  • [5] BI Z,, KLEINE R,, KEOLEIAN G., Integrated life cycle assessment and life cycle cost model for comparing plug-in versus wireless charging for an electric bus system [J], Journal of Industrial Ecology, 21, 2, pp. 344-355, (2017)
  • [6] ZHANG Y,, ZHAO Z., Frequency splitting analysis of two-coil resonant wireless power transfer [J], IEEE An⁃ tennas and Wireless Propagation Letters, 13, pp. 400-402, (2014)
  • [7] CHEN G,, HU D,, CHIEN S., Optimizing battery-electric-feeder service and wireless charging locations with nested genetic algorithm [J].IEEE Access, 8, pp. 67166-67178, (2020)
  • [8] CHEN G, HU D, CHIEN S, Optimizing wire⁃ less charging locations for battery electric bus transit with a genetic algorithm, Sustainability, 12, 21, pp. 89711-89720, (2020)
  • [9] LIU Z,, SONG Z,, HE Y., Optimal deployment of dy⁃ namic wireless charging facilities for an electric bus sys⁃ tem [J], Transportation Research Record, 2647, 1, pp. 100-108, (2017)
  • [10] ALWESABI Y, LIU Z, KWON S., A novel integration of scheduling and dynamic wireless charging planning models of battery electric buses, Energy, 230, (2021)