A spatial-temporal estimation model of residual energy for pure electric buses based on traffic performance index

Abstract

The relationship between the energy consumption of buses and traffic conditions has gradually garnered research attention with the expansion of the green transportation concept and the promotion of new energy buses. In line with these developments, this study develops a spatial–temporal estimation model of residual energy for pure electric buses with fuzzy clustering and time-series algorithms. These algorithms are based on the traffic performance index of the road sections between the nearest bus stops. Furthermore, they are established according to the positions of floating vehicles and the bus routes in combination with the energy consumption data derived from the battery management system of pure electric buses. Test results show that these estimation algorithms can accurately describe the spatial–temporal relationship between traffic performance index and the residual energy in pure electric buses. Thus, they can be applied as significant references in the analysis of traffic conditions, energy conservation, and emission reduction for buses.

Keywords

• fuzzy clustering
• fuzzy time series
• pure electric bus
• residual energy
• traffic index