A Prediction Model for Battery Electric Bus Energy Consumption in Transit

Abstract

This study investigates the impacts of vehicular, operational, topological, and external parameters on the energy consumption (EC) 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 EC 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 EC. The regression model explained more than 96% of the variation in the EC 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).

Energy Consumption of the Urban Transport Fleet in UNESCO World Heritage Sites: A Case Study of Ávila (Spain)

“…From Figure 5, it can be observed that the values of E sup est and E rec est , according to the proposed analysis, follow a straight line with slope according to the corresponding coefficients X 1 and X 2 in Table 5. The values E sup computed according to Equation (15), are far from the estimated values E sup est (decreasing) as the altitude decreases. This is because in the intervals where the accumulated elevation gain is less than the value X 2 •d, E sup decreases (less energy needs to be supplied since the vehicle is moving on a negative slope).…”

“…As of today, manufacturers are investing numerous technical and economic resources in the development of battery electric vehicles [13]. The commercial acceptance of hybrid technology is growing, especially in the case of cars, vans and buses used in urban areas [14][15][16], while that of long-distance trucks and coaches is beginning to emerge [17,18].…”

Dynamic Surrogate Trip-Level Energy Model for Electric Bus Transit System Optimization

“…During the optimization problem, however, the algorithm requires a huge number of iterations to update the value of e ( b , r , i ) according to the change in the operation values. In every iteration, the ADVISOR model, developed and validated by Abdelaty et al ( 24 , 25 ), is used to calculate e ( b , r , i ) for every trip. If we assume that the model needs 1,000 iterations to reach the optimal design, 247 trips (in our case study), and the simulator needs only 1 s to obtain the energy consumption rate of the trip, the solution time will take up to three days (247,000 s/60/60/24 = ∼2.86).…”

“…First, ADVISOR MATLAB/Simulink environment is considered an accurate tool for simulating BEB conduct ( 25 , 26 ). ADVISOR was first developed by the National Renewable Energy Laboratory (NREL).…”

Transformation of an existing urban bus line: Milan Full Electric project

“…In this context, ATM -Azienda Trasporti Milanesi, the public company that manages the collective transport in Milan (Italy), launched in 2017 the Milan Full Electric project to equip the city by 2030 with a public transport service entirely powered by electric traction, retiring gradually the current diesel vehicles, and promoting sustainable mobility in the urban area (Wen, 2016;Wang, 2020). Several studies in the literature have addressed the issue of energy consumption by highlighting the importance of how electricity is produced (Abdelaty and Mohamed, 2021;Pietrzak and Pietrzak, 2021).…”