Currently, the adoption rate of pure electric buses is continuously increasing
across cities nationwide, and their energy consumption costs have become an
important component of urban bus operating expenses. The aim of this study is to
explore significant factors related to energy savings for a bus route, which can
help bus operators improve route energy efficiency and make resource allocation
more reasonable.
This study selects per capita energy consumption per thousand kilometers (PKEK)
as the energy efficiency indicator and constructs a regression model with robust
standard errors and a hierarchical clustering model using GPS operation data,
total daily energy consumption data, and card swiping data from electric buses
on eight routes in the same operational area of Nanjing from April 1 to June 10,
2021.
The research results confirm the existence of significant variables affecting
energy efficiency, primarily including: average speed, proportion of high-speed
intervals, vehicle age, number of turns, whether it is a weekend, minimum
distance between stations, average temperature, distance from the first station
to the charging station, and number of seats. Based on these variables, the
eight routes are classified into four types, i.e., Type I to Type IV routes,
with significant differences in their energy efficiency distribution and a
gradual decrease in performance. For Type III and Type IV routes with lower
energy efficiency, this study offers targeted improvement suggestions in areas
such as driver behavior, vehicle updates, charging station placement and vehicle
scheduling. These suggestions point to some feasible directions at the route
level for bus companies to reduce operating costs and promote green
development.