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In decade years, Spark Ignition-Controlled Auto Ignition (SI-CAI) hybrid combustion, also called Spark Assisted Compression Ignition (SACI) has shown its high-efficiency and low emissions advantages. However, high dilution causes the problem of unstable initial ignition and flame propagation, which leads to high cyclic variation of heat release and IMEP. The instability of SI-CAI hybrid combustion limits its dilution degree and its ability to improve the thermal efficiency. In order to solve instability problems and expand the dilution boundary of hybrid combustion, micro flame ignition (MFI) strategy is applied in gasoline hybrid combustion engines. Small amount of Dimethyl Ether (DME) chosen as the ignition fuel is injected into cylinder to form micro flame kernel, which can stabilize the ignition combustion process.

Modeling techniques matter a lot in many fields of engine engineering. Models are requested not only for control design but also for dynamic prediction. However, problems might be encountered during modeling process either because of the system complexity or the unaffordable modeling cost. As a result, a new modeling technique based on disturbance estimation is proposed in this paper. By employing the proposed modeling technique, models are set up in real time with the online information from input and output. The uncertainties of system dynamics are handled as internal disturbance of the system, while the perturbation from outside are taken as the external disturbance, and the combination of the two can be estimated online by a kind of active observer called extended state observer (ESO).

The increasingly stringent requirements in relation to emission reduction and onboard diagnostics are pushing the Chinese automotive industry toward more innovative solutions and a rapid increase in electronic control performance. To manage the system complexity the architecture will require being well structure on hardware and software level. The paper introduces GEMS-K1 (Gasoline Engine Management System - Kit 1). GEMS-K1 is a platform being compliant with Euro IV emission regulation for gasoline engines. The application software is developed using modeling language, the code is automatically generated from the model. The driver software has a well defined structure including microcontroller abstraction layer and ECU abstraction layer. The hardware is following design rules to be robust, 100% testable and easy to manufacture. The electronic components use the latest innovation in terms of architecture and technologies.