## 4 Conclusions  
This study proposes a novel battery swapping mode (BSM) for electric taxis (ETs), i.e., the so-called modular BSM, which can provide a flexible combination of battery blocks to meet different driving range requirements. Furthermore, we developed a data-driven approach to configuring and operating modular battery swapping stations (BSSs) using the taxi travel patterns extracted from the eight days of GPS trajectory data associated with 12,643 actual taxis in Beijing, China. The departure time distribution, daily mileage distribution, and percentage of travel distance per hour extracted from the trajectory data were used to define the model's rules to establish a realistic and accurate model. The trajectory data analysis indicates a strong relationship between the ET travel patterns and the dynamic battery swapping demand (_BSD_).  
We performed a real-world numerical experiment with traditional BSM as the benchmark to evaluate our model and modular BSM. It was demonstrated that the BSS with modular BSM can save 38% on the investment costs of purchasing ET battery blocks and respond to the time-of-use (ToU) price better than the benchmark. Additionally, a sensitivity analysis was conducted to measure the impact of two essential model parameters on the model output: the unit capacity costs of batteries and the ToU price. Insightful findings are obtained for BSS infrastructure planning. First, battery price fluctuations within a reasonable range will not significantly impact the configuration of BSSs. Second, when peak electricity prices (grid load) are high, increasing the number of battery blocks purchased, they can be charged early at valley electricity prices, which is a good solution.  
From the findings of this study, our future research will focus on the configuration and operation of modular BSSs featuring battery energy storage systems (BESS) that have the capability of battery-to-grid (B2G) or that cooperate with microgrids. Moreover, considering the stochastic _BSD_ for an ET driver and evaluating the performance of modular BSSs in different regions/countries are interesting future directions. Furthermore, modeling the details of the battery swapping process will increase the model scale, and designing a customized algorithm to solve the model will also be an important research direction in the future.  
Conceptualization, Z.L. and X.M.; methodology, Z.L.; software, Z.L.; validation, X.L. and G.H.d.A.C.; investigation, R.S. and W.S.; resources, X.M.; writing--original draft preparation, Z.L. and X.L.; writing--review and editing, G.H.d.A.C.; visualization, R.S.; supervision, X.M. All authors have read and agreed to the published version of the manuscript.  
This research was funded by National Natural Science Foundation of China, Award Number: 52072017.  
Not applicable.  
Figure 7: Configuration optimization results of BSS under different ToU prices. (**a**) impact of ToU prices on total annual costs, (**b**) impact of ToU prices on electricity costs.  
Data Availability Statement: The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.  
The authors declare no conflict of interest.