A Prediction Model for Battery Electric Bus Energy Consumption in Transit

This study investigates the impacts of vehicular, operational, topological, and external parameters on the energy consumption (E-C) of battery-electric buses (BEBs) in transit operation. Furthermore, the study develops a data-driven prediction model for BEB energy consumption in transit operation that considers these four parameters. A Simulink energy model is developed to estimate the E-C rates and validated using the Altoona's test real-world data. A full-factorial experiment is used to generate 907,199 scenarios for BEB operation informed by 120 real-world drive cycles. A multivariate multiple regression model was developed to predict BEB's E-C. The regression model explained more than 96% of the variation in the E-C of the BEBs. The results show the significant impacts of road grade, the initial state of charge, road condition, passenger loading, driver aggressiveness, average speed, HVAC, and stop density on BEB's energy consumption, each with a different magnitude. The study concluded that the optimal transit profile for BEB operation is associated with rolling grade and relatively lower stop density (one to two stops/km).

Automated summary

This study investigates the impacts of various parameters on the energy consumption of battery-electric buses in transit operation, and develops a data-driven prediction model to optimize the operation configuration for BEBs.