Fuel consumption for heavy trucks depends on many factors like roads, weather, and driver behavior that are hard for a manufacturer to influence. However, one design possibility is the powertrain configuration. Here a new simulation program for heavy trucks is created to find the configuration of the powertrain that gives the lowest fuel consumption for each transport task.

For efficient simulations the model uses production code for speed and gear control, and it uses exchangeable data sets to allow simulation of the whole pro­ duction range of engine types, on recorded road profiles from all over the world. Combined with a graphical user interface this application is called STARS (Scania Truck And Road Simulation).

The forces of rolling resistance and air resistance in the model are validated through an experiment where the propeller shaft torque of a heavy truck is measured. It is found that the coefficient of rolling resistance is strongly dependent on tire temperature, not only on vehicle speed as expected. This led to the development of a new model for rolling resistance. The model includes the dynamic behavior of the tires and relates rolling resistance to tire temperature and vehicle speed.

In another experiment the fuel consumption of a test truck in highway driving is measured. The altitude of the road is recorded with a barometer and used in the corresponding simulations. Despite of the limited accuracy of this equipment the simulation program manage to predict a level of fuel consumption only 2% lower than the real measurements.

It is concluded that STARS is a good tool for predicting fuel consumption for trucks in highway driving and for comparing different powertrain configurations.