The report describes a sensitivity study of an optimal controller for a hybrid truck, i.e. how sensitive is the controller to the difference between the estimated vehicle mass and the actual mass. The controller uses predictive information about road slope to optimize energy buffers (dissipated energy and battery state of charge) and thus minimize fuel consumption.

The simulations show that variation in the vehicle mass significantly influences the average vehicle speed, which results from the speed profile that the controller computes. There is no clear observable trend in the fuel consumption as a function of ratio between estimated mass and actual mass that persists after the variations in average vehicle speed are taken into account. The main finding is instead that it is the variations in average speed that is what mainly effects the variations in fuel consumption, and that this is not a direct result of the variations in estimated mass.