Print Email Facebook Twitter Optimizing Electric Taxi Battery Swapping Stations Featuring Modular Battery Swapping Title Optimizing Electric Taxi Battery Swapping Stations Featuring Modular Battery Swapping: A Data-Driven Approach Author Liu, Zhengke (Beihang University) Ma, Xiaolei (Beihang University) Liu, Xiaohan (Beihang University) Correia, Gonçalo (TU Delft Transport and Planning) Shi, Ruifeng (North China Electric Power University) Shang, Wenlong (Beijing University of Technology) Date 2023 Abstract 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. Subject battery swapping station configurationdata-driven approachelectric taximodular battery swapping modetrajectory data To reference this document use: http://resolver.tudelft.nl/uuid:bc80454d-7e87-4bb7-b946-2ff7ba0894c7 DOI https://doi.org/10.3390/app13031984 ISSN 2076-3417 Source Applied Sciences, 13 (3) Part of collection Institutional Repository Document type journal article Rights © 2023 Zhengke Liu, Xiaolei Ma, Xiaohan Liu, Gonçalo Correia , Ruifeng Shi, Wenlong Shang Files PDF applsci_13_01984.pdf 2.59 MB Close viewer /islandora/object/uuid:bc80454d-7e87-4bb7-b946-2ff7ba0894c7/datastream/OBJ/view