Stochastic driving cycle synthesis for analyzing the energy consumption of a battery electric bus

Previous driving cycle generation studies have focused on constructing a single cycle from a large data set. This paper takes the opposite approach by presenting a novel driving cycle synthetization method that can generate a large number of varying cycles and passenger numbers for a chosen bus route based on only a handful of measured cycles. The validity of the method was confirmed by comparing the statistical properties of synthesized cycles to those of measured cycles on a selected route. The method was applied to analyze the impact of driving cycle and passenger load variations on energy consumption variations of a battery electric bus on a suburban route in Espoo, Finland. Ten-thousand synthetic cycles were run with a validated electric bus simulation model, and the energy consumption during each cycle was recorded. The mean consumption was 0.914 kWh/km, the standard deviation was 0.043 kWh/km, and the range of the consumption variation was 0.331 kWh/km. The new cycle synthetization and consumption distribution forecasting methods are useful tools for public transport authority, route operators, and bus manufacturers, as they could be used in optimizing bus powertrain dimensions as well as bus line schedules.Peer reviewe