Search Results

Increasing emissions regulations, diagnostics capability, and other demands in vehicle refinement, have led to the need for increasingly complex engine control systems. These demands have led to in-cylinder combustion control, especially for the diesel engine. Diesel engine combustion relies heavily on the auto-ignition process. Therefore accurate control of this process is important and will become even more important for HCCI-engines. This paper discusses the configuration of a diesel engine for in-cylinder combustion control. It describes the digital evaluation of the cylinder pressure signal and the computation of the physical parameters necessary for proper combustion analysis, along with methods for using the calculated combustion parameter for engine control. The paper demonstrates the advantages of electronic engine control combined with in-cylinder pressure information. The paper also addresses some of the future challenges of engine control.

The use of design of experiment (DoE) and data-driven simulation has become state-of-the-art in engine development and base calibration to cope with the drastically increased complexity of today's engine ECUs (electronic control units). Based on the representation of the engine behavior with a virtual plant model, offline optimizers can be used to find the optimal calibration settings for the engine controller, e.g. with respect to fuel consumption and exhaust gas emissions. This increases the efficiency of the calibration process and reduces the need for expensive test stand runs. The present paper describes the application of Gaussian process regression, a statistical modeling approach with practical benefits in terms of achievable model accuracy and usability. The implementation of the algorithm in a commercial tool framework enables a broad use in series engine calibration.