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The original Table 2 includes incorrect data under the "Primary Energy" column for "multi-strike", "continuous" and "plasma" system types.

Hydrogen is widely considered a promising fuel for future transportation applications for both, internal combustion engines and fuel cells. Due to their advanced stage of development and immediate availability hydrogen combustion engines could act as a bridging technology towards a wide-spread hydrogen infrastructure. Although fuel cell vehicles are expected to surpass hydrogen combustion engine vehicles in terms of efficiency, the difference in efficiency might not be as significant as widely anticipated [1]. Hydrogen combustion engines have been shown capable of achieving efficiencies of up to 45 % [2]. One of the remaining challenges is the reduction of nitric oxide emissions while achieving peak engine efficiencies. This paper summarizes research work performed on a single-cylinder hydrogen direct injection engine at Argonne National Laboratory.

The highly transient operational nature of passenger car engines makes cylinder pressure based feedback control of combustion phasing difficult. The problem is further complicated by cycle-to-cycle combustion variation. A method for fast and accurate differentiation of normal combustion variations and true changes in combustion phasing is addressed in this research. The proposed method combines the results of a feed forward combustion phasing prediction model and “noisy” measurements from cylinder pressure using an iterative estimation technique. A modified version of an Extended Kalman Filter (EKF) is applied to calculate optimal estimation gain according to the stochastic properties of the combustion phasing measurement at the corresponding engine operating condition. Methods to improve steady state CA50 estimation performance and adaptation to errors are further discussed in this research.

Autoignition delay times of two full blend gasoline fuels (high and low RON) were explored in a rapid compression machine. CO2 dilution by mass was introduced at 0%, 15%, and 30% levels with the O2:N2 mole ratio fixed at 1:3.76. This dilution strategy is used to represent exhaust gas recirculation (EGR) substitution in spark ignition (SI) engines by using CO2 as a surrogate for major EGR constituents(N2, CO2, H2O). Experiments were conducted over the temperature range of 650K-900K and at 10 bar and 20 bar compressed pressure conditions for equivalence ratios of (Φ =) 0.6-1.3. The full blend fuels were admitted directly into the combustion chamber for mixture preparation using the direct test chamber (DTC) approach. CO2 addition retarded the autoignition times for the fuels studied here. The retarding effect of the CO2 dilution was more pronounced in the NTC region when compared to the lower and higher temperature range.

This paper presents a combined numerical and experimental investigation of the characteristics of spark discharge in a spark-ignition engine. The main objective of this work is to gain insights into the spark discharge process and early flame kernel development. Experiments were conducted in an inert medium within an optically accessible constant-volume combustion vessel. The cross-flow motion in the vessel was generated using a previously developed shrouded fan. Numerical modeling was based on an existing discharge model in the literature developed by Kim and Anderson. However, this model is applicable to a limited range of gas pressures and flow fields. Therefore, the original model was evaluated and improved to predict the behavior of spark discharge at pressurized conditions up to 45 bar and high-speed cross-flows up to 32 m/s. To accomplish this goal, a parametric study on the spark channel resistance was conducted.

As engines are equipped with an increased number of control actuators to meet fuel economy targets, they become more difficult to control and calibrate. The additional complexity created by a larger number of control actuators motivates the use of physics-based control strategies to reduce calibration time and complexity. Combustion phasing, as one of the most important engine combustion metrics, has a significant influence on engine efficiency, emissions, vibration and durability. To realize physics-based engine combustion phasing control, an accurate prediction model is required. This research introduces physics-based control-oriented laminar flame speed and turbulence intensity models that can be used in a quasi-dimensional turbulent entrainment combustion model. The influence of laminar flame speed and turbulence intensity on predicted mass fraction burned (MFB) profile during combustion is analyzed.

This research proposes a control system for Spark Ignition (SI) engines with external Exhaust Gas Recirculation (EGR) based on model predictive control and a disturbance observer. The proposed Economic Nonlinear Model Predictive Controller (E-NMPC) tries to minimize fuel consumption for a number of engine cycles into the future given an Indicated Mean Effective Pressure (IMEP) tracking reference and abnormal combustion constraints like knock and combustion variability. A nonlinear optimization problem is formulated and solved in real time using Sequential Quadratic Programming (SQP) to obtain the desired control actuator set-points. An Extended Kalman Filter (EKF) based observer is applied to estimate engine states, combining both air path and cylinder dynamics. The EKF engine state(s) observer is augmented with disturbance estimation to account for modeling errors and/or sensor/actuator offset.

Computational fluid dynamics of gas-fueled large-bore spark ignition engines with pre-chamber ignition can speed up the design process of these engines provided that 1) the reliability of the results is not affected by poor meshing and 2) the time cost of the meshing process does not negatively compensate for the advantages of running a computer simulation. In this work a flame propagation model that runs with arbitrary hybrid meshes was developed and coupled with the KIVA4-MHI CFD solver, in order to address these aims. The solver follows the G-Equation level-set method for turbulent flame propagation by Tan and Reitz, and employs improved numerics to handle meshes featuring different cell types such as hexahedra, tetrahedra, square pyramids and triangular prisms. Detailed reaction kinetics from the SpeedCHEM solver are used to compute the non-equilibrium composition evolution downstream and upstream of the flame surface, where chemical equilibrium is instead assumed.

Fuel lean combustion and exhaust gas dilution are known to increase the thermal efficiency and reduce NOx emissions. In this study, experiments are performed to understand the effect of equivalence ratio on flame kernel formation and flame propagation around the spark plug for different low turbulent velocities. A series of experiments are carried out for propane-air mixtures to simulate engine-like conditions. For these experiments, equivalence ratios of 0.7 and 0.9 are tested with 20 percent mass-based exhaust gas recirculation (EGR). Turbulence is generated by a shrouded fan design in the vicinity of J-spark plug. A closed loop feedback control system is used for the fan to generate a consistent flow field. The flow profile is characterized by using Particle Image Velocimetry (PIV) technique. High-speed Schlieren visualization is used for the spark formation and flame propagation.

As engines are equipped with an increased number of control actuators to meet fuel economy targets they become more difficult to control and calibrate. The large number of control actuators encourages the investigation of physics-based control strategies to reduce calibration time and complexity. Of particular interest is spark timing control and calibration since it has a significant influence on engine efficiency, emissions, vibration and durability. Spark timing determination to achieve a desired combustion phasing is currently an empirical process that occurs during the calibration phase of engine development. This process utilizes a large number of stored surfaces and corrections to account for the wide range of operating environments and conditions that a given engine will experience. An obstacle to realizing feedforward physics-based combustion phasing control is the requirement for an accurate and fast combustion model.

The influence of spark plug orientation on early flame kernel development is investigated in an optically accessible gasoline direct injection homogeneous charged spark ignition engine. This investigation provides visual understanding and statistical characterization of how spark plug orientation impacts the early flame kernel and thus combustion phasing and engine performance. The projected images of flame kernel were captured through natural flame chemiluminescence with a high-speed camera at 10,000 frames per second, and the ignition secondary discharge voltage and current were measured with a 10 MHz DAQ system. The combustion metrics were determined using measurement from a piezo-electric in-cylinder pressure transducer and real-time engine combustion analyzer. Three spark plug orientations with two different electrode designs were studied. The captured images of the flame were processed to yield 2D and 1D probability distributions.

Low Temperature Combustion (LTC) engines are promising to improve powertrain fuel economy and reduce NOx and soot emissions by improving the in-cylinder combustion process. However, the narrow operating range of LTC engines limits the use of these engines in conventional powertrains. The engine’s limited operating range can be improved by taking advantage of electrification in the powertrain. In this study, a multi-mode LTC-SI engine is integrated with a parallel hybrid electric configuration, where the engine operation modes include Homogeneous Charge Compression Ignition (HCCI), Reactivity Controlled Compression Ignition (RCCI), and conventional Spark Ignition (SI). The powertrain controller is designed to enable switching among different modes, with minimum fuel penalty for transient engine operations.

In order to extend the operability limit of the gasoline compression ignition (GCI) engine, as an avenue for low temperature combustion (LTC) regime, the effects of parametric variations of engine operating conditions on the performance of six-stroke GCI (6S-GCI) engine cycle are numerically investigated, using an in-house 3D CFD code coupled with high-fidelity physical sub-models along with the Chemkin library. The combustion and emissions were calculated using a skeletal chemical kinetics mechanism for a 14-component gasoline surrogate fuel. Authors’ previous study highlighted the effects of the variation of injection timing and split ratio on the overall performance of 6S-GCI engine and the unique mixing-controlled burning mode of the charge mixtures during the two additional strokes. As a continuing effort, the present study details the parametric studies of initial gas temperature, boost pressure, fuel injection pressure, compression ratio, and EGR ratio.

Past experimental studies conducted by the current authors on a 13 liter 16.7:1 compression ratio heavy-duty diesel engine have shown that diesel-Compressed Natural Gas (CNG) Reactivity Controlled Compression Ignition (RCCI) combustion targeting low NOx emissions becomes progressively difficult to control as the engine load is increased. This is mainly due to difficulty in controlling reactivity levels at higher loads. For the current study, CFD investigations were conducted in CONVERGE using the SAGE combustion solver with the application of the Rahimi mechanism. Studies were conducted at a load of 5 bar BMEP to validate the simulation results against RCCI experimental data. In the low load study, it was found that the Rahimi mechanism was not able to predict the RCCI combustion behavior for diesel injection timings advanced beyond 30 degCA bTDC. This poor prediction was found at multiple engine speed and load points.

Every passing year automotive engineers are challenged to attain higher fuel economy and improved emission targets. One widely used approach is to use Cooled Exhaust Gas Recirculation (CEGR) to meet these objectives. Apart from reducing emissions and improving fuel economy, CEGR also plays a significant role in knock mitigation in spark ignited gasoline engines. Generally, CEGR is introduced into the intake manifold in SI gasoline engine. Even though the benefits of using CEGR are significant, they can be easily negated by the uneven CEGR flow distribution between the cylinders, which can result in combustion instability. This paper describes the application of co-simulation between one and three dimensional tools to accurately predict the distribution of CEGR to the cylinders and the effect of its distribution on engine performance.

Gasoline compression ignition (GCI) technology shows the potential to obtain high thermal efficiencies while maintaining low soot and NOx emissions in light-duty engine applications. Recent experimental studies and numerical simulations have indicated that high reactivity gasoline-like fuels can further enable the benefits of GCI combustion. However, there is limited empirical data in the literature studying the gasoline compression ignition process at relevant in-cylinder conditions, which are required for further optimizing combustion system designs. This study investigates the temporal and spatial evolution of the compression ignition process of various high reactivity gasoline fuels with research octane numbers (RON) of 71, 74 and 82, as well as a conventional RON 97 E10 gasoline fuel. A ten-hole prototype gasoline injector specifically designed for GCI applications capable of injection pressures up to 450 bar was used.

As automotive emissions become more stringent, accurate control of three-way catalyst temperature is increasingly important for maintaining high levels of conversion efficiency as well as preventing damage to the catalyst. A real-time catalyst temperature model provides critical information to the engine control system. In order to improve emissions and ensure regulatory compliance over a wide range of speed-load conditions, it is desirable to use modelled catalyst temperature as the primary input to catalyst efficiency control strategies. This requirement creates a challenge for traditional empirical models designed for component protection at high speed-load conditions. Simulation results show that a physics aligned model can estimate temperature in all operating conditions, including: cold-start, extended idle, engine shutdown, stop-start events, deceleration fuel shut-off, as well as traditional high load and part load points.

In-cylinder ion sensing is a subject of interest due to its application in spark-ignited (SI) engines for feedback control and diagnostics including: combustion knock detection, rate and phasing of combustion, and mis-fire On Board Diagnostics (OBD). Further advancement and application is likely to continue as the result of the availability of ignition coils with integrated ion sensing circuitry making ion sensing more versatile and cost effective. In SI engines, combustion knock is controlled through closed loop feedback from sensor metrics to maintain knock near the borderline, below engine damage and NVH thresholds. Combustion knock is one of the critical applications for ion sensing in SI engines and improvement in knock detection offers the potential for increased thermal efficiency. This work analyzes and characterizes the ionization signal in reference to the cylinder pressure signal under knocking and non-knocking conditions.

In this paper, a model-based linear estimator and a non-linear control law for an Fe-zeolite urea-selective catalytic reduction (SCR) catalyst for heavy duty diesel engine applications is presented. The novel aspect of this work is that the relevant species, NO, NO2 and NH3 are estimated and controlled independently. The ability to target NH3 slip is important not only to minimize urea consumption, but also to reduce this unregulated emission. Being able to discriminate between NO and NO2 is important for two reasons. First, recent Fe-zeolite catalyst studies suggest that NOx reduction is highly favored by the NO 2 based reactions. Second, NO2 is more toxic than NO to both the environment and human health. The estimator and control law are based on a 4-state model of the urea-SCR plant. A linearized version of the model is used for state estimation while the full nonlinear model is used for control design.

The application of hydrogen (H2) as an internal combustion (IC) engine fuel has been under investigation for several decades. The favorable physical properties of hydrogen make it an excellent alternative fuel for fuel cells as well as IC engines and hence it is widely regarded as the energy carrier of the future. The potential of hydrogen as an IC engine fuel can be optimized by direct injection (DI) as it provides multiple degrees of freedom to influence the in-cylinder combustion processes and consequently the engine efficiency and exhaust emissions. This paper studies a single-hole nozzle and examines the effects of injection strategy on engine efficiency, combustion behavior and NOx emissions. The experiments for this study are done on a 0.5 liter single-cylinder research engine which is specifically designed for combustion studies and equipped with a cylinder head that allows side as well as central injector location.