| Summary: | To control the combustion in an engine, an accurate estimation of the air mass flow is required. Due to strict emission legislation and high demands on fuel consumption from customers, a technology called variable valve timing is investigated. This technology controls the amount of air inducted to the engine cylinder and the amount of gases pushed out of the cylinder, via the inlet and exhaust valves. The air mass flow is usually estimated by large look-up tables but when introducing variable valve timing, the air mass flow also depends on the angles of the inlet and exhaust valves causing these look-up tables to grow with two dimensions. To avoid this, models to estimate the air mass flow have been derived. This has been done with grey-box models, using physical equations together with unknown parameters estimated by solving a linear least-squares optimization problem. To be able to implement the models in the electronic control unit in the future, only sensors implemented in a commercial vehicle are used as much as possible. The work has been done using an inline 6-cylinder diesel engine with measurements from steady-state conditions. All four models derived in this project are based on the estimation methods in use today with fix cam phasing, and are derived from the ideal gas law together with a volumetric efficiency factor. The first three models derived in this work only include sensors provided in commercial engines. The measurements needed as input signals are engine rotational speed, crank angle resolved pressure in the intake manifold, intake and exhaust valve angles and intake manifold temperature. The fourth and last model is divided into three sub-models to model different parts of the four-stroke engine cycle. This model also includes crank angle resolved exhaust manifold pressure and exhaust manifold temperature, where the temperature is the only sensor used in this project that is not provided in a commercial engine. It has been concluded how influential it is to use correctly measured values for the input signals. Since the manifold pressure and the cylinder volume vary during one four-stroke cycle, it is essential that these signal measurements are taken at the right crank angle degree. With wrong crank angle degree, the estimation is worse than if the cylinder volume is constant for all operating points and the pressure signals are taken as a mean value over the whole four-stroke cycle. Further development to reach better estimation results with lower relative error is needed. However, for the work in this thesis, the model with best model fit is estimating the air mass flow well enough to use it as a basis for further control.
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