Estimating energy consumption rates for battery electric truck based on real-world data

Abstract

Battery electric trucks (BETs) have been regarded as an environmentally friendly mode of road freight transportation. However, since BETs have limited driving ranges, the freight transportation companies experience the challenge of establishing reasonable freight transport schemes, where the operators of freight transportation companies need to understand the energy consumption rate (ECR) of BETs and ensure that the transport tasks can be finished without breaking down due to energy depletion. The accurate estimation of ECR is an effective method to alleviate the negative effects of limited driving range. To this end, this study utilizes the BET operational data collected from real-world situations to investigate the estimation of ECR. A data-driven approach is adopted to establish the nonlinear regression models for estimating the ECR of BETs, accompanied by its mathematical expression. The estimated performance of the models is evaluated, and consequently, the cubic function model is selected by considering the complexity and robustness. Based on the established estimation model, the economic driving speed of BETs is investigated. The results indicate that the economic driving speed of BETs is 52.02 km/h, and the corresponding ECR is 0.53 kWh/km.