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The upcoming European legislation for heavy duty vehicles, EuVI, includes rules on monitoring of urea consumption and urea tank volume. These new rules put new demands on the level sensing system monitoring the urea tank. The normal vehicle mounted liquid level sensing system today consists of a single, more or less vertically placed, sensor. When the vehicle is tilted the level of the fluid at the sensor position normally changes. This results in a measurement error in the calculated volume, as the volume is calculated based only on the information from the level sensor. The presented modeling studies investigate the feasibility of using sensor fusion to improve the accuracy of liquid volume estimation on a heavy duty truck. In the first study, the signals from multiple level sensors located in various liquid containing tanks on the truck are fused.

An investigation of the need of engine model complexity for use in powertrain control applications is presented in this paper. The engine studied is an SI-engine, but the analysis methods could easily be adapted to a CI-engine. The different engine models investigated are a cylinder-by-cylinder engine model and a mean value engine model. The way to evaluate the engine models is to compare the dynamical behavior and how the engine affects the driveline. The analysis is made by studying the engine in the frequency and time domain. The investigation shows that the mean value engine model is sufficient for use in powertrain simulations and for powertrain control design. The dynamical behavior for the two models coincide, and the combustion pulses are well damped in the driveline (powertrain without engine). A less complex structure is preferable when designing a control system.