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Real-Time Closed-Loop Control of a Light-Duty RCCI Engine During Transient Operations
Technical Paper
2017-01-0767
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
Real-time control of Reactivity Controlled Compression Ignition (RCCI) during engine load and speed transient operation is challenging, since RCCI combustion phasing depends on nonlinear thermo-kinetic reactions that are controlled by dual-fuel reactivity gradients. This paper discusses the design and implementation of a real-time closed-loop combustion controller to maintain optimum combustion phasing during RCCI transient operations. New algorithms for real-time in-cylinder pressure analysis and combustion phasing calculations are developed and embedded on a Field Programmable Gate Array (FPGA) to compute RCCI combustion and performance metrics on cycle-by-cycle basis. This cycle-by-cycle data is then used as a feedback to the combustion controller, which is implemented on a real-time processor.
A computationally efficient algorithm is introduced for detecting Start of Combustion (SOC) for the High Temperature Heat Release (HTHR) or main-stage heat release. This identified SOC and HTHR are then utilized to calculate the main-stage CA50 (i.e., crank angle of 50% cumulative heat release). The designed RCCI controller simultaneously adjusts CA50 and Indicated Mean Effective Pressure (IMEP) during engine transient operations. For controlling CA50, either Premixed Ratio (PR) or Start of Injection (SOI) timing of high reactive fuel is utilized. The selection between PR and SOI is done based on the experimental sensitivity analysis. For controlling IMEP, total fuel quantity is controlled to obtain the desired engine load. The experimental validation results show that the designed RCCI controller can maintain desired CA50 during engine load transients and also reach to a desired IMEP within 2-4 engine cycles.
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Arora, J. and Shahbakhti, M., "Real-Time Closed-Loop Control of a Light-Duty RCCI Engine During Transient Operations," SAE Technical Paper 2017-01-0767, 2017, https://doi.org/10.4271/2017-01-0767.Data Sets - Support Documents
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