Energy Consumption of Battery- Electric Buses: Review of Influential Parameters and Modelling Approaches

Abstract

The electrification of public transportation fleets worldwide can pose a challenge to multiple stakeholders, such as the fleet operator or the operator of the local electrical grid. One of the important prerequisites for the successful integration of these fleets into the existing system is the knowledge of the energy consumption of the buses during their trips. The energy consumption varies depending on multiple factors such as the vehicle or route-related parameters, operational, and environmental parameters. This paper gives an overview of the latest research regarding these influential factors. Another essential prerequisite for the implementation of intelligent management systems for electric bus fleets is the forecasting of energy consumption. Researchers take different approaches to tackle this issue. A review of the latest research considering empirical approaches, physical models, regression, and machine learning is also provided in this paper. The findings of this paper provide a quick overview of different aspects of the energy consumption of electric buses and can therefore support other researchers or decision-makers in their work.

A Trip-Based Data-Driven Model for Predicting Battery Energy Consumption of Electric City Buses

“…To potentially improve the modeling accuracy, alternative machine learning algorithms were evaluated on the aggregate dataset and compared with the quadratic regression model (11). Most of those algorithms were set to use the individual predictor variables rather than quadratic and interaction terms/features present in the model (11) (see the second column of Table 3). This is because more sophisticated machine learning algorithms should automatically detect/realize inherent interactions between individual predictor variables.…”

“…The overall e-bus regression model integrates the powertrain and HVAC system submodels given by Equation (11) and Equations ( 12) and ( 13), respectively. It is represented by the expression given in the first row of Table 7 and compared with existing models from the literature, listed in the remaining rows of Table 7.…”

“…Models of e-buses (and e-vehicles in general) can be divided into elementary, physical, and data-driven models [11]. The elementary models link electric energy consumption with basic features of driving cycles such as distance traveled [12].…”