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Exhaust aftertreatment systems are essential components in modern powertrains, needed to reach the low legislated levels of NOx and soot emissions. A well designed diesel engine exhaust aftertreatment system can have NOx conversion rates above 95%. However, to achieve high conversion the aftertreatment system must be warm. Because of this, large parts of the total NOx emissions come from cold starts where the engine has been turned off long enough for the aftertreatment system to cool down and loose its capacity to reduce NOx. It is therefore important to understand how the aftertreatment cools down when the engine in turned off. Experimental data for a catalyst cool-down process is presented and analyzed. The analysis shows that it is important to capture the spatial distribution of temperatures both in axial and radial directions. The data and analysis are used to design a catalyst thermal model that can be used for model based catalyst temperature monitoring and control.

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.

New and exciting possibilities in vehicle control are revealed by the consideration of topography, for example through the combination of GPS and three dimensional road maps. How information about future road slopes can be utilized in a heavy truck is explored. The aim is set at reducing the fuel consumption over a route without increasing the total travel time. A model predictive control (MPC) scheme is used to control the longitudinal behavior of the vehicle, which entails determining accelerator and brake levels and also which gear to engage. The optimization is accomplished through discrete dynamic programming. A cost function that weighs fuel use, negative deviations from the reference velocity, velocity changes, gear shifts and brake use is used to define the optimization criterion. Computer simulations back and forth on 127 km of a typical highway route in Sweden, show that the fuel consumption in a heavy truck can be reduced with 2.5% with a negligible change in travel time.

Inverse dynamic simulation is a successful method to make fast simulations of powertrains modeled using vehicle velocity and acceleration. This method is here extended so that additional dynamics can be included, and it is compared to the standard/usual forward dynamic simulation. Simulation results show that extended inverse dynamic simulation is a good method for maintaining speed and increasing accuracy in simulations. This gives the possibility to use the inverse dynamic simulation as a tool for powertrain optimization and control strategy evaluation.

Spark ignited engines require accurate control of both air and fuel, and one important component in this system is the throttle servo. A non-linear throttle model is built and used for control design. It is shown that the non-linear model-based controller improves the performance compared to a conventional gain scheduled PI controller. Furthermore a method for estimating the load torque that the air flow produces on the throttle shaft is presented.

One important area of SI-engine diagnosis is the diagnosis of leakage in the air-intake system. This is because a leakage can cause increased emissions and drivability problems. A method for accurately detecting leaks is presented. The results are developed for a turbo-charged engine but they are also valid for a naturally aspirated SI-engine. The method is based on a physical model of the leaks and includes an estimation of leakage area. By knowing the area, it is possible to reconfigure the control algorithm such that, the effect of the leak on emissions, is suppressed. As small leaks as 2 mm in diameter can be detected and it is possible to distinguish between leakages before or after the throttle. The method is suitable for on-line implementation.

Because of legislative regulations like OBDII, on-board diagnosis has gained much interest lately. A model based approach is suggested for the diagnosis of the air intake system of an SI-engine. Important research issues are modeling concepts, residual generation and evaluation, overall performance, and limiting factors. The diagnosis system is based on a non-linear semi-physical model and uses a combination of different residual generation methods. It is capable of detecting and isolating faults in the throttle actuator, throttle sensor, air mass now sensor and manifold pressure sensor. The scheme is experimentally validated on a real production engine.