<p>Combustion supervision by evaluating flywheel speed variations is a common approach in the automotive industry. This often involves preliminary measurements. An adequate model for simulating flywheel speed can assist to avoid some of these preliminary measurements. </p><p>A physical nonlinear model for simulating flywheel speed based on cylinder pressure information is investigated in this work. Measurements were conducted at Scania in a test bed and on a chassis dynamometer. The model was implemented in MATLAB/Simulink and simulations are compared to measured data. The first model can not explain all dynamics for the measurements in the test bed so extended models are examined. A model using a dynamically equivalent model of the crank-slider mechanism shows no difference from the simple model, whereas a model including a driveline can explain more from the test-bed measurements. When simulating the setups used at the chassis dynamometer, the simplest model works best. Yet, it is not very accurate and it is proposed that optimization of parameter values might improve the model further. A sensitivity analysis shows that the model is fairly robust to parameter changes.</p><p>A continuation of this work might include optimization to estimate parameter values in the model. Investigating methods for combustion supervision may also be a future issue.</p>

Combustion supervision by evaluating flywheel speed variations is a common approach in the automotive industry. This often involves preliminary measurements. An adequate model for simulating flywheel speed can assist to avoid some of these preliminary measurements. A physical nonlinear model for simulating flywheel speed based on cylinder pressure information is investigated in this work. Measurements were conducted at Scania in a test bed and on a chassis dynamometer. The model was implemented in MATLAB/Simulink and simulations are compared to measured data. The first model can not explain all dynamics for the measurements in the test bed so extended models are examined. A model using a dynamically equivalent model of the crank-slider mechanism shows no difference from the simple model, whereas a model including a driveline can explain more from the test-bed measurements. When simulating the setups used at the chassis dynamometer, the simplest model works best. Yet, it is not very accurate and it is proposed that optimization of parameter values might improve the model further. A sensitivity analysis shows that the model is fairly robust to parameter changes. A continuation of this work might include optimization to estimate parameter values in the model. Investigating methods for combustion supervision may also be a future issue.