Development of the Västra Götaland Operating Cycle for Long-Haul Heavy-Duty Vehicles

Abstract

In this paper, a complete operating cycle (OC) description is developed for heavy-duty vehicles traveling long distances in the region of Västra Götaland, Sweden. Variation amongst road transport missions is accounted for using a collection of stochastic models. These are parametrized from log data for all the influential road parameters that may affect the energy performance of heavy trucks, including topography, curvature, speed limits, and stop signs. The statistical properties of the developed OC description are investigated numerically by considering some composite variables, condensing the salient information about the road characteristics, and inspired by two existing classification systems. Two examples are adduced to illustrate the potential of the OC format, which enables ease of classification and detailed simulation of energy efficiency for individual vehicles, with application in vehicle design optimization and selection, production planning, and predictive maintenance. In particular, for the track used in the first example, a Volvo FH13 equipped with a diesel engine, simulation results indicate mean CO2 emissions of around $1700\,\,\text {g}\, \text {km}^{-1}$ , with a standard deviation of $360\,\,\text {g}\, \text {km}^{-1}$ ; in the second example, dealing with electrical fleet sizing, the optimal proportion shows a predominance of tractor-semitrailer vehicles (70%) equipping 4 motors and 11 battery packs.

Keywords

• Operating cycle
• mission classification
• road transport mission
• stochastic modeling
• autoregressive models
• Markov models