Optimizing Electric Taxi Battery Swapping Stations Featuring Modular Battery Swapping: A Data-Driven Approach
Source abstract
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.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Electric Vehicles and Infrastructure · Transportation and Mobility Innovations · Energy, Environment, and Transportation Policies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Transportation Science and Engineering, Beihang University, Beijing 100191, China
Department of Transport and Planning, Faculty of Civil Engineering and Geosciences, Delft University of Technology, 2628 CN Delft, The Netherlands
School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China
Beijing Key Laboratory of Traffic Engineering, College of Metropolitan Transportation, Beijing University of Technology, Beijing 100124, China
Funding
National Natural Science Foundation of China
References (28)
Show source-provided references
1. Taxi Trajectory Data Based Fast-Charging Facility Planning for Urban Electric Taxi Systems10.1016/j.apenergy.2021.116515 ↗
2. A Mip Model for Locating Slow-Charging Stations for Electric Vehicles in Urban Areas Accounting for Driver Tours10.1016/j.tre.2014.11.005 ↗
3. Netherlands Enterprise Agency (2022, February 11). Electric Transport in The Netherlands. Available online: https://english.rvo.nl/information/electric-transport.
4. U.S. Department of Transportation (2022, February 02). Electric Vehicle Charging Speeds, Available online: https://www.transportation.gov/rural/ev/toolkit/ev-basics/charging-speeds.
5. Non-Myopic Dynamic Routing of Electric Taxis with Battery Swapping Stations10.1016/j.scs.2020.102113 ↗
6. An Intelligent Method for Dynamic Distribution of Electric Taxi Batteries between Charging and Swapping Stations10.1016/j.scs.2020.102605 ↗
7. Infrastructure Planning for Electric Vehicles with Battery Swapping
8. Dynamic Planning for Simultaneous Recharging and Relocation of Shared Electric Taxies: A Sequential Milp Approach10.1016/j.trc.2020.102933 ↗
9. Assessing the Impact of an Ev Battery Swapping Station on the Reliability of Distribution Systems10.3390/app10228023 ↗
10. A Two-Echelon Electric Vehicle Routing Problem with Time Windows and Battery Swapping Stations10.3390/app112210779 ↗
11. Battery Swap Pricing and Charging Strategy for Electric Taxis in China10.1016/j.energy.2018.01.082 ↗
12. Construction Planning and Operation of Battery Swapping Stations for Electric Vehicles: A Literature Review10.3390/en14248202 ↗
13. A Review of Siting, Sizing, Optimal Scheduling, and Cost-Benefit Analysis for Battery Swapping Stations10.1016/j.energy.2022.124723 ↗
14. Sulfuric Acid Leaching of Metals from Waste Li-Ion Batteries without Using Reducing Agent10.1016/j.mineng.2022.107597 ↗
15. Electric Car Battery: An Overview on Global Demand, Recycling and Future Approaches Towards Sustainability10.1016/j.jenvman.2021.113091 ↗
16. Configuration and System Operation for Battery Swapping Stations in Beijing10.1016/j.energy.2020.118883 ↗
17. Concept Review of a Cloud-Based Smart Battery Management System for Lithium-Ion Batteries: Feasibility, Logistics, and Functionality10.3390/batteries8020019 ↗
18. Forecasting Transportation Network Speed Using Deep Capsule Networks with Nested Lstm Models10.1109/TITS.2020.2984813 ↗
19. Impacts of Free-Floating Bikesharing System on Public Transit Ridership10.1016/j.trd.2019.09.014 ↗
20. A Unified Configurational Optimization Framework for Battery Swapping and Charging Stations Considering Electric Vehicle Uncertainty10.1016/j.energy.2020.119536 ↗
21. Deploying Battery Swap Stations for Electric Freight Vehicles Based on Trajectory Data Analysis10.1109/TTE.2022.3160445 ↗
22. Deploying Battery Swap Stations for Shared Electric Vehicles Using Trajectory Data10.1016/j.trd.2021.102943 ↗
23. Trajectory-Driven Planning of Electric Taxi Charging Stations Based on Cumulative Prospect Theory10.1016/j.scs.2022.104125 ↗
24. Tsang. Optimal Charging Operation of Battery Swapping and Charging Stations with Qos Guarantee10.1109/TSG.2017.2666815 ↗
25. Tsang. Optimal Scheduling of Battery Charging Station Serving Electric Vehicles Based on Battery Swapping10.1109/TSG.2017.2764484 ↗
26. An Optimization Model for Electric Vehicle Battery Charging at a Battery Swapping Station10.1109/TVT.2017.2758404 ↗
27. Investigation of Individual Cells Replacement Concept in Lithium-Ion Battery Packs with Analysis on Economic Feasibility and Pack Design Requirements10.3390/pr9122263 ↗
28. Gas, P., and Company, E. (2022, November 24). Tariffs-Business Electric Vehicle. Available online: https://www.pge.com/tariffs/index.page.