A low-order homogeneous charge compression ignition (HCCI) combustion model to support model-based control development for spark ignition (SI)/HCCI mode transitions is presented. Emphasis is placed on mode transition strategies wherein SI combustion is abruptly switched to recompression HCCI combustion through a change of the cam lift and opening of the throttle, as is often employed in studies utilizing two-stage cam switching devices. The model is parameterized to a steady-state dataset which considers throttled operation and significant air-fuel ratio variation, which are pertinent conditions to two-stage cam switching mode transition strategies. Inspection and simulation of transient SI to HCCI (SI-HCCI) mode transition data shows that the extreme conditions present when switching from SI to HCCI can cause significant prediction error in the combustion performance outputs even with the model’s adequate steady-state fit. When a correction factor related to residual gas temperature is introduced to account for these extreme conditions, it is shown that the model reproduces transient performance output time histories in SI-HCCI mode transition data. The model is thus able to capture steady-state data as well as transient SI-HCCI mode transition data while maintaining a low-order cycle to cycle structure, making it tractable for model-based control of SI-HCCI mode transitions.
- Dynamic Systems and Control Division
A Low-Order HCCI Model Extended to Capture SI-HCCI Mode Transition Data With Two-Stage Cam Switching Available to Purchase
Gorzelic, P, Shingne, P, Martz, J, Stefanopoulou, A, Sterniak, J, & Jiang, L. "A Low-Order HCCI Model Extended to Capture SI-HCCI Mode Transition Data With Two-Stage Cam Switching." Proceedings of the ASME 2014 Dynamic Systems and Control Conference. Volume 2: Dynamic Modeling and Diagnostics in Biomedical Systems; Dynamics and Control of Wind Energy Systems; Vehicle Energy Management Optimization; Energy Storage, Optimization; Transportation and Grid Applications; Estimation and Identification Methods, Tracking, Detection, Alternative Propulsion Systems; Ground and Space Vehicle Dynamics; Intelligent Transportation Systems and Control; Energy Harvesting; Modeling and Control for Thermo-Fluid Applications, IC Engines, Manufacturing. San Antonio, Texas, USA. October 22–24, 2014. V002T34A005. ASME. https://doi.org/10.1115/DSCC2014-6275
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