| | | The electric vehicle is envisioned as a solution to low-carbon dioxide transportation. However, the low power density of battery still exists and causes the short range of electric vehicles. This problem is even more significant to taxis as the daily distances travelled by taxis usually exceed their ranges. Therefore, during the day, electric taxis need to charge at least once which might influence their revenue or services provided. Under this background, this project aims at designing a charging strategy for taxi drivers. Given a complete trajectory dataset with indicators of passengers on board, the project tries to minimize the services missed by electric vehicles when deciding when, where and how much to charge. During this decision process, several factors can be considered, such as the nonlinear speed of battery charging, uncertainties of future taxi demand, etc. The project will begin with incorporating the aforementioned factors into one existed mathematical programming, then the corresponding problem needs to be solved with an efficient algorithm. |