The impact of electromobility in public transport: An estimation of energy consumption using disaggregated data in Santiago, Chile

Electromobility in public transport has become a promising way to reduce environmental pollution. Several contributions have sought to estimate the energy consumption of buses in public transport. However, most of these efforts use measurements collected from controlled or simulated experiments, or that do not characterize the entire bus network. Unlike these studies, this article estimates the energy consumption of all the electric buses that circulate in the city of Santiago, Chile, during the studied period using full disaggregated GPS data and empirical measurements on some sensorized electric buses. The methodology considers a feature selection phase and the development of energy consumption prediction models using physics based and machine learning approaches. The performances of both models are compared with each other, and then, the best one is used to measure the impact of electromobility in the city. This analysis allows decision-makers to target investment by determining the buses with higher energy consumption savings in the face of budget constraints.