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A benchmark problem for fuel efficient control of a truck on a given road profile has been formulated and solved. Six different solution strategies utilizing varying degrees of off-line and on-line computations are described and compared. A vehicle model is used to benchmark the solutions on different driving missions. The vehicle model was presented at the IFAC AAC 2016 symposium and is compiled from model components validated in previous research projects. The driving scenario is provided as a road slope profile and a desired trip time. The problem to solve is a combination of engine-, driveline-and vehicle-control while fulfilling demands on emissions, driving time, legislative speed, and engine protections. The strength of this publication is the collection of all six different solutions in one paper. This paper is intended to provide a starting point for practicing engineers or researchers who work with optimal and/or model based vehicle control.

Optimizing the velocity of a vehicle over a known future route can reduce fuel consumption. This article studies the potential fuel-savings of such systems for conventional vehicles, employing an internal combustion engine, and its application to electric vehicles.A main drawback of many optimization algorithms is their computational complexity, which prevents them from being used in real-time applications. To overcome this drawback a fast algorithm is presented to optimize the velocity of a vehicle with known route slope. Using this algorithm the consumption for five real world scenarios is simulated and compared against a constant velocity policy.The results achieved for the conventional vehicle are comparable to real-world results reported in other articles and offer about 20% fuel saving using free-wheeling compared to driving with a constant velocity. For electric vehicles the consumption savings, which can be achieved using free-wheeling lie around 3.5%.