Due to Germany’s ambitious climate protection goals, the increasing greenhouse gas
(GHG) emissions from the transport sector – especially from heavy duty vehicles
which are currently and in the foreseeable future almost exclusively powered by diesel
engines – are increasingly at the centre of political and scientific discussion. Consequently,
not only technical measures (i. e. higher energy efficiency and alternative
drive technologies) but also changes in driving behaviour that can be implemented
immediately, such as driving at reduced maximum velocity on motorways, should be
taken into account and investigated by both policy makers and the actors directly involved
in road freight transport (i. e. transport and logistics service providers).
In order to analyse the real effects in a holistic and anticipatory manner on both the
vehicle‘s physical-technical level and the transport service provider‘s logistic-economic
level, this thesis links a physically-based fuel consumption model with a trip chain
model. Firstly, the average values of both fuel consumption (in l/100 km) and velocity
(in km/h) resulting from a reduction measure are determined by simulation experiments
with a fuel consumption model based on MATLAB/Simulink. Secondly, these
two variables are described as payload-dependent functions for each vehicle. A reduced
maximum velocity is represented by correspondingly adapted driving cycles,
which originate from HBEFA and are modified in this work with the help of an analytical
procedure (programme). Each vehicle represents all vehicles in one of a total of
15 vehicle classes, which together account for around 91 % of diesel consumption and
GHG emissions, respectively, of all heavy duty vehicles in Germany in 2010. Accordingly,
the simulation results of one vehicle can be projected for all vehicles in each
class with the given stock.
Afterwards, the effects of a decreased average velocity to the temporal sequence of
different trips, which have to be carried out by one vehicle within a year, are analysed
with the trip chain model (discrete-event simulation model based on Excel-VBA). Due
to constant frame conditions for both the vehicle (i. a. driving ban periods) and the
driver (i. a. driving and rest periods), which are always fulfilled in the model, the results
are not only increasing trip times, which behave inversely proportional to the
velocity, but also some trips which have to be shifted to the next day or even the next
week. The corresponding delay time is calculated and recorded with respect to the
baseline situation (i. e. without reduced velocity). By recording and evaluating the increasing
total personnel expenditure (i. e. working time on each vehicle), the corresponding
costs can be offset against the total amount of saved fuel costs. Thereby, the
economic efficiency of a reduction measure is finally determined on the basis of the
anually increased or decreased total costs. The corresponding amount of potentially
reduced GHG emissions from all heavy duty vehicles is specified, too.
Aktualisiert: 2023-03-22
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