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Reactivity Controlled Compression Ignition (RCCI) natural gas/diesel dual-fuel combustion has been shown to achieve high thermal efficiency with low NOX and PM emissions, but has traditionally been limited to low to medium loads. High BMEP operation typically requires high substitution rates (i.e., >90% NG), which can lead to high cylinder pressure, pressure rise rates, knock, and combustion loss. In previous studies, compression ratio was decreased to achieve higher load operation, but thermal efficiency was sacrificed. For this study, a multi-cylinder heavy-duty engine that has been modified for dual-fuel operation (diesel direct-injection and natural gas (NG) fumigated into the intake stream) was used to explore RCCI and other dual-fuel combustion modes at high compression ratio, while maintaining stock lug curve capability (i.e., extending dual-fuel operation to high loads where conventional diesel combustion traditionally had to be used).

Cooled Exhaust Gas Recirculation (EGR) technology provides significant benefits such as better cycle efficiency, knock tolerance and lower NOx/PM emissions. However, EGR dilution also poses challenges in terms of combustion stability, power density and control. Conventional control schemes for EGR engines rely on a differential pressure sensor combined with an orifice flow model to estimate EGR flow rate. While EGR rate is an important quantity, intake O2 mass fraction may be a better indication of EGR, capturing quantity as well as “quality” of EGR. SwRI has successfully used intake O2 mass fraction as a controlled state to manage several types of EGR engines - dual loop EGR diesel engines, low pressure loop /dedicated EGR (D-EGR) gasoline engines as well as dual fuel engines. Several suppliers are currently developing intake O2 sensors but they typically suffer from limited accuracy, response time and reliability. Also, addition of a new sensor implies increased production costs.

The CO2 advantage coupled with the low NOX and PM potential of natural gas (NG) makes it well-suited for meeting future greenhouse gas (GHG) and NOX regulations for on-road medium and heavy-duty engines. However, because NG is mostly methane, reduced combustion efficiency associated with traditional NG fueling strategies can result in significant levels of methane emissions which offset the CO2 advantage due to reduced efficiency and the high global warming potential of methane. To address this issue, the unique co-direct injection capability of the Westport HPDI fuel system was leveraged to obtain a partially-premixed fuel charge by injecting NG during the compression stroke followed by diesel injection for ignition timing control. This combustion strategy, referred to as DI2, was found to improve thermal and combustion efficiencies over fumigated dual-fuel combustion modes.

Southwest Research Institute (SwRI) has successfully demonstrated the cooled EGR concept via the High Efficiency Dilute Gasoline Engine (HEDGE) consortium. Dilution of intake charge provides three significant benefits - (1) Better Cycle Efficiency (2) Knock Resistance and (3) Lower NOx/PM Emissions. But EGR dilution also poses challenges in terms of combustion stability, condensation and power density. The Dedicated EGR (D-EGR) concept brings back some of the stability lost due to EGR dilution by introducing reformates such as CO and H2 into the intake charge. Control of air, EGR, fuel, and ignition remains a challenge to realizing the aforementioned benefits without sacrificing performance and drivability. This paper addresses the DEGR solution from a controls standpoint. SwRI has been developing a unified framework for controlling a generic combustion engine (gasoline, diesel, dual-fuel natural gas etc.).

For the US market, an abundant supply of natural gas (NG) coupled with recent green-house gas (GHG) regulations have spurred renewed interest in dual-fuel combustion regimes. This paper explores the potential of co-direct injection to improve the efficiency and reduce the methane emissions versus equivalent fumigated dual-fuel combustion systems. Using the Westport HPDI engine as the experimental test platform, the paper reports the results obtained using both diffusion controlled (HPDI) combustion strategy as well as a partially-premixed combustion strategy (DI2). The DI2 combustion strategy shows good promise, as it has been found to improve the engine efficiency by over two brake thermal efficiency (BTE) points (% fuel energy) compared to the diffusion controlled combustion strategy (HPDI) while at the same time reducing the engine-out methane emissions by 75% compared to an equivalent fumigated dual-fuel combustion system.

An airflow-dominant control system was developed to provide precise engine and exhaust treatment control with low air fuel ratio alternative combustion. The main elements of the control logic include a real-time state observer for in-cylinder oxygen mass estimation, a simplified packaging scheme for all air-handling and fueling parameters, a finite state machine for control mode switching, combustion control models to maintain robust alternative combustion during transients, and smooth rich/lean switching during lean NOx trap (LNT) regeneration without post injection. The control logic was evaluated on a passenger car equipped with a 4-way catalyst system with LNT and was instrumental in achieving US Tier II Bin 5 emission targets with good drivability and low NVH.

This paper explores the possibility of on-board fuel classification for fuel property adaptive compression-ignition engine control system. The fuel classifier is designed to on-board classify the fuel that a diesel engine is running, including alternative and renewable fuels such as bio-diesel. Based on this classification, the key fuel properties are provided to the engine control system for optimal control of in-cylinder combustion and exhaust treatment system management with respect to the fuel. The fuel classifier employs engine input-output response characteristics measured from standard engine sensors to classify the fuel. For proof-of-concept purposes, engine input-output responses were measured for three different fuels at three different engine operating conditions. Two neural-network-based fuel classifiers were developed for different classification scenarios. Of the three engine operating conditions tested, two conditions were selected for the fuel classifier to be active.