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Recent development has renewed the interest in drivetrain concepts which give a higher degree of freedom by disconnecting the engine and vehicle speeds. This freedom raises the demand for active control, which especially during transients is not trivial but of which the quality is crucial for the success of the drivetrain concept. In this work the fuel optimal solution for a turbocharged diesel engine connected to a load which does not restrict the engine speed is derived, analysed and utilized for finding a suboptimal operating point trajectory. We use a Willan s efficiency model for the engine, expanded with a first order delay dependent torque reduction representing the turbocharger pressure, and study different output power transients. The analysis is made with dynamic programming, Pontryagin's maximum principle and a suboptimal strategy based on the static optimal operating points.

Hybridization and velocity management are two important techniques for energy efficiency that mainly have been treated separately. Here they are put in a common framework that from the hybridization perspective can be seen as an extension of the equivalence factor idea in the well known strategy ECMS. From the perspective of look-ahead control, the extension is that energy can be stored not only in kinetic energy, but also electrically. The key idea is to introduce more equivalence factors in a way that enables efficient computations, but also so that the equivalence factors have a physical interpretation. The latter fact makes it easy to formulate a good residual cost to be used at the end of the look-ahead horizon. The formulation has different possible uses, but it is here applied on an evaluation of the size of the electrical system. Previous such studies, for e.g.

For a fuel optimal gear shift control, when look ahead information is available, the impact of the automated manual transmission (AMT) gear-shifting process is analyzed. For a standard discrete heavy truck transmission, answers are found on when to shift gears, prior to or when in an uphill slope. The gear-shifting process of a standard AMT is modeled in order to capture the fuel and time aspects of the gear shift. A numerical optimization is performed by dynamic programming, minimizing fuel consumption and time by controlling fuel injection and gear. Since a standard AMT does not have look ahead information, it sometimes gears down unnecessarily and thus gives a significantly higher fuel consumption compared to the optimal control. However, if gearing down is inevitable, the AMT gear-shifting strategy, based on engine thresholds, is well-functioning so that the optimal control only gives marginal additional savings.