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Gasoline Controlled Auto Ignition offers a high CO2 emission reduction potential, which is comparable to state-of-the-art, lean stratified operated gasoline engines. Contrary to the latter, GCAI low temperature combustion avoids NOX emissions, thereby trying to avoid extensive exhaust aftertreatment. The challenges remain in a restricted operation range due to combustion instabilities and a high sensitivity towards changing boundary conditions like ambient temperature, intake pressure or fuel properties. Once combustion shows instability, cyclic fluctuations are observed. These appear to have near-chaotic behavior but are characterized by a superposition of clearly deterministic and stochastic effects. Previous works show that the fluctuations can be predicted precisely when taking cycle-tocycle correlations into account. This work extends current approaches by focusing on additional dependencies within one single combustion cycle.

The technological development in the field of automotive electronics is proceeding at almost break-neck speed. The functions being developed and integrated into cars are growing in complexity and volume. With the increasing number and variety of sensors and actuators, electronics have to handle a greater amount of data, and the acquisition and generation of I/O signals is also growing in complexity, for example, in engine management applications. Moreover, intelligent and complex algorithms need to be processed in a minimum of time. This all intensifies the need for Rapid Control Prototyping (RCP), a proven method of decisively speeding up the model-based software development process of automotive electronic control units (ECUs) [1],[2]. All these demanding tasks, including connecting sensors and actuators to the RCP system, need to be performed within a standard prototyping environment.