A turbulent jet ignition system of a spark ignited (SI) engine consists of pre-combustion and main-combustion chambers, where the combustion in the main-combustion chamber is initiated by turbulent jets of reacting products from the pre-combustion chamber. If the gas exchange and combustion processes are accurately controlled, the highly distributed ignition will enable very fast combustion and improve combustion stability under lean operations, which leads to high thermal efficiency, knock limit extension, and near zero NOx emissions. For model-based control, a precise combustion model is a necessity. This paper presents a control-oriented jet ignition combustion model, which is developed based on simplified fluid dynamics and thermodynamics, and implemented into a dSPACE based real-time hardware-in-the-loop (HIL) simulation environment. The two-zone combustion model is developed to simulate the combustion process in two combustion chambers. Correspondingly, the gas flowing through the orifices between two combustion chambers is divided into burned and unburned gases during the combustion process. The pressure traces measured from a rapid compression machine (RCM), equipped with a jet igniter, are used for initial model validation. The HIL simulation results show a good agreement with the experimental data.
- Dynamic Systems and Control Division
A Control-Oriented Jet Ignition Combustion Model for an SI Engine
Song, R, Gentz, G, Zhu, G, Toulson, E, & Schock, H. "A Control-Oriented Jet Ignition Combustion Model for an SI Engine." Proceedings of the ASME 2015 Dynamic Systems and Control Conference. Volume 1: Adaptive and Intelligent Systems Control; Advances in Control Design Methods; Advances in Non-Linear and Optimal Control; Advances in Robotics; Advances in Wind Energy Systems; Aerospace Applications; Aerospace Power Optimization; Assistive Robotics; Automotive 2: Hybrid Electric Vehicles; Automotive 3: Internal Combustion Engines; Automotive Engine Control; Battery Management; Bio Engineering Applications; Biomed and Neural Systems; Connected Vehicles; Control of Robotic Systems. Columbus, Ohio, USA. October 28–30, 2015. V001T11A001. ASME. https://doi.org/10.1115/DSCC2015-9687
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