With air resistance being one of the two major energy losses in on-road vehicles
(the other one being tire losses) and therefore heavily contributing to the
range of battery electric and fuel cell electric vehicles, it is necessary to
account for realistic air resistance in a priori assessments like vehicle range
estimations, component dimensioning, and system simulations.
However, lack of input data tempts analysts to instead assume unrealistic
“nominal conditions” throughout—a simplification which usually underestimates
the amount of energy actually required to overcome air resistance and completely
ignores the fact that varying environmental conditions will lead to significant
variances in energy consumption and therefore vehicle range. Using “nominal
conditions,” it is thus impossible to assess the robustness of these measures
and, therefore, difficult to design robust systems and to perform meaningful
trade-off studies.
In this study, we show how publicly available data from weather observations can
be used to assess the long-term variation of air resistance of a truck with a
semitrailer. Realistic distributions of energy losses due to air resistance,
covering multiple years, are derived—showing not only average values but the
complete envelope in which the energy losses vary.
This, in turn, enables to follow up with probabilistic calculations of vehicle
performance in order to assess robustness and trade-offs on various system
levels of interest. As a consequence, consumption and range predictions of EVs
and ICE vehicles can be performed with higher accuracy and confidence.
