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Improving efficiency and reducing emissions are the principal challenges in developing new generations of internal combustion engines. Different strategies such as downsizing or sophisticated after-treatment of exhaust gases are pursued. Another approach aims at optimizing the parameterization of the engine. Correct adjustments of ignition timings, waste gate position and other factors have significant influence on the combustion process. A multitude of application data is generated during the development process to predefine appropriate settings for most situations. Improvements in regards to the application effort and the quality of the settings can be achieved by measuring the combustion process and optimizing the parametrization in a closed loop. However, cylinder pressure sensors that are used during the development process are too expensive for series applications.

Modern methods of engine development use complex mathematical models. Adding advanced components such as variable valve trains or direct injection systems to the model increases the degrees of freedom resulting in a high number of measurements for validation. Steadily rising costs for development, time and staff make it crucial for industry to improve the quality of measurements with advanced analysis techniques. Often, such models consider the simulated system as stationary, implying that system variables no longer change with time. This paper presents an internal combustion engine measurement system utilizing algorithms for the real-time evaluation of the state of the engine or its components. Several approaches have been reviewed and tested regarding their applicability. The most straightforward algorithms compare the gradient of a sensor signal to a pre-defined threshold.