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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.

The use of hydrogen as a possible fuel for internal combustion (IC) engines can help build a society with a clean transportation framework. Diluting the in-cylinder mixture can improve the efficiency of the engines. To prove the validity of lean burn in hydrogen IC engines, three different combustion modes are investigated in this study. The engine experiments are conducted in a spray-guided direct-injection (DI) spark-ignition engine with 10 MPa of hydrogen DI. When lean burn is applied to a hydrogen IC engine, the characteristics of pumping and heat transfer loss improve. The improvement in heat transfer loss is more significant than the reduction in negative pumping work for the indicated thermal efficiency. Among the three combustion modes, stratified charge combustion (SCC) develops the maximum indicated mean effective pressure. However, this mode deteriorates the combustion stability slightly. The nitrogen oxide emission is reduced when the excess air ratio is increased.

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.

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 spray characteristics of a swirl injector for direct-injection spark-ignition (DISI) engines were investigated for the generation of robust and well-atomized swirl spray. A highly-inclined tapered nozzle is applied as a test nozzle and the spray characteristics are compared with conventional nozzle and L-step nozzle. When the taper angle is 70°, an opened hollow cone spray is formed. This spray does not collapse with increasing fuel temperature and back pressure conditions. However, the taper angle should be optimized to avoid forming a locally rich area and to increase the spray volume. The droplet size of 70° tapered nozzle spray shows a value similar to that of the original swirl spray in the horizontal mainstream while it shows an increased value in the vertical mainstream. The deteriorated atomization characteristics of the tapered nozzle spray are improved by applying high fuel temperature injection without causing spray collapse.

In order to reduce hydrocarbon emission in gasoline engine, especially during warming-up period, it is necessary to estimate the fuel and fuel product flow rate in the emission gas. The intake airflow rate should also be estimated. A strategy was proposed to estimate air fuel ratio in a spark ignition engine. The mass of air in the cylinder was determined by filling-emptying method, and the fuel in the intake manifold and cylinder was estimated by the “wall-wetting” effect calculation. The use of graphical dynamic system control software is becoming more popular as automotive engineers strive to reduce the time to develop new control systems. The rapid prototype engine controller has been developed by using MATLAB, SIMULINK, REAL TIME WORKSHOP, xPC Target, and WATCOM C++. The sensor data from the engine will be transferred to computer, and the fuel delivery will be calculated.

To meet stringent emission standards, a considerable amount of development work is necessary to ensure suitable efficiency and durability of catalyst systems. The main challenge is to reduce the engine cold-start emissions. Close-coupled catalyst (CCC) provides fast light-off time by utilizing the energy in the exhaust gas. However, if some malfunction occurred during engine operation and the catalyst temperature exceeds 1050°C, the catalytic converter becomes deactivated and shows poor conversion efficiency. Close-coupled catalyst temperature was investigated under various engine operating conditions. All of the experiments were conducted with a 1.0L SI engine at 1500-4000 rpm. The engine was operated at no load to full load conditions. Exhaust gas temperature and catalyst temperature were measured as a function of lambda value (0.8-1.2), ignition timing (BTDC 30°-ATDC 30°) and misfire rates (0-28%).

Accurate in-cylinder air charge estimation is important for engine torque determination, controlling air-to-fuel ratio, and ensuring high after-treatment efficiency. Spark ignition (SI) engine technologies like variable valve timing (VVT) and exhaust gas recirculation (EGR) are applied to improve fuel economy and reduce pollutant emissions, but they increase the complexity of air charge estimation. Increased air-path complexity drives the need for cost effective solutions that produce high air mass prediction accuracy while minimizing sensor cost, computational effort, and calibration time. A large number of air charge estimation techniques have been developed using a range of sensors sets combined with empirical and/or physics-based models. This paper provides a technical review of research in this area, focused on SI engines.

Low-pressure cooled EGR (LP-cEGR) systems can provide significant improvements in spark-ignition engine efficiency and knock resistance. However, open-loop control of these systems is challenging due to low pressure differentials and the presence of pulsating flow at the EGR valve. This research describes a control structure for Low-pressure cooled EGR systems using closed loop feedback control along with internal model control. A Smith Predictor based PID controller is utilized in combination with an intake oxygen sensor for feedback control of EGR fraction. Gas transport delays are considered as dead-time delays and a Smith Predictor is one of the conventional methods to address stability concerns of such systems. However, this approach requires a plant model of the air-path from the EGR valve to the sensor.

A prototype of a small, spark-ignition free-piston engine combined with a linear alternator was designed to produce electric power for portable usage. It has a bore size of 25 mm and maximum stroke of 22 mm. The engine was fueled with liquefied petroleum gas consisting of 98% propane. The electric power generated by the linear alternator is a function of the piston dynamics and the electric conductance. Therefore, the purpose of current research is to investigate the effects of the basic engine controlling parameters such as the equivalence ratio of the mixture and the spark timing on the piston dynamics and study the relationship with the electric power generation performance. The equivalence ratio of the mixture was varied from 1.0 to 1.72, while the spark timing was varied at 3, 4, and 5 mm away from the maximum top dead center. Operating characteristics, namely, indicated mean effective pressure, electric power output, operating frequency and piston stroke were analyzed.

One of the major problems limiting the accuracy of piezoelectric transducers for cylinder pressure measurements in an internal-combustion (IC) engine is the thermal shock. Thermal shock is generated from the temperature variation during the cycle. This temperature variation results in contraction and expansion of the diaphragm and consequently changes the force acting on the quartz in the pressure transducer. An empirical equation for compensation of the thermal shock error was derived from consideration of the diaphragm thermal deformation and actual pressure data. The deformation and the resulting pressure difference due to thermal shock are mainly a function of the change in surface temperature and the equation includes two model constants. In order to calibrate these two constants, the pressure inside the cylinder of a diesel engine was measured simultaneously using two types of pressure transducers, in addition to instantaneous wall temperature measurement.

Adaptive valve timing control is one of the promising techniques to accomplish the optimized mixture formation and combustion depending on the load and speed, which is needed to meet the future challenges of reducing fuel consumption and exhaust emissions. The behavior and the effect of adaptive valve timing control system has been investigated by computer simulation, which simulates the gas dynamics in engines. These programs are typically one-dimensional including complex flow features as ‘special’ boundaries. A code adopting 2-step Lax-Wendroff method with artificial damping terms called FCT(Flux Corrected Transport), was developed to investigate the influence of operational and design parameters on the performance of engines. The effects of adaptive valve timing control system on volumetric efficiency or engine torque, and pumping loss were investigated. It increased low end torque by about 6%, and reduced pumping loss drastically at low load, high engine speed conditions.

The concentrations of individual exhaust hydrocarbon species were measured as a function of air-fuel ratio and EGR in a 2-liter four-cylinder engine using a gas chromatography, for natural gas and LPG. NMHC in addition to the species of HC, other emissions such as CO2, CO and NOx were at 1800rpm for two compression ratios (8.6 and 10.6) and various EGR ratios up to 7%. Fuel conversion efficiencies were also investigated together with emissions to study the effect of engine parameters on the combustion performances in gas engines especially under the lean burn conditions. It was found that CO2 emission decreased leaner mixture strength, the higher compression ratio and certainly with smaller C value of fuel. HC emissions from LPG engine consisted primarily of propane (larger 60%), ethylene and propylene, while main emissions from natural gas were methane (larger than 60%), ethane, ethylene and propane on the average.

A new concept of misfire detection in spark ignition engines using a wide-range oxygen sensor is introduced. A wide-range oxygen sensor, installed at the confluence point of the exhaust manifold, was adopted to measure the variation in oxygen concentration in case of a misfire. The signals of the wide-range oxygen sensor were characterized over the various engine-operating conditions in order to decide the monitoring parameters for the detection of the misfire and the corresponding faulty cylinder. The effect of the sensor position, the transient response characteristics of the sensor and the cyclic variation in the signal fluctuation were also investigated. Limited response time of a commercially available sensor barely allowed to observe misfire. It was found that a misfiring could be distinguished more clearly from normal combustion through the differentiation of the sensor response signal. The differentiated signal has twin peaks for a single misfiring in a cylinder.

Lean stratified combustion is a mean to dilute the fuel-air mixture leaner than stoichiometric ratio, by using stratification of fuel gradient in a spark ignition engine. Under the lean stratified combustion, differed from the stoichiometric homogeneous charge combustion, flame could propagate through extremely rich air-fuel mixture, while the global air-fuel mixture is under lean condition. The rich mixture causes considerable amount of particulate matter, but, due to large effect of efficiency improvement, the attractive point is on fuel economy compare to homogeneous charge SI combustion. The easiest way to reduce particulate matter is changing fuel to gaseous hydrocarbon, to minimize evaporating and mixing period.

Modern turbocharged spark-ignition engines are being equipped with an increasing number of control actuators to meet fuel economy, emissions, and performance targets. The response time variations between engine control actuators tend to be significant during transients and necessitate highly complex actuator scheduling routines. Model Predictive Control (MPC) has the potential to significantly reduce control calibration effort as compared to the current methodologies that are based on decentralized feedback control strategies. MPC strategies simultaneously generate all actuator responses by using a combination of current engine conditions and optimization of a control-oriented plant model. To achieve real-time control, the engine model and optimization processes must be computationally efficient without sacrificing effectiveness. Most MPC systems intended for real-time control utilize a linearized model that can be quickly evaluated using a sub-optimal optimization methodology.

As global emission standards are becoming more stringent, it is necessary to increase thermal efficiency through the high compression ratio in spark-ignited engines. Various studies are being conducted to mitigate knocking caused by an increased compression ratio, which requires an understanding of the combustion phenomena inside the combustion chamber. In particular, the in-cylinder flow is a major factor affecting the entire combustion process from the generation to the propagation of flames. In the field of spark-ignited engine research, where interest in the concept of lean combustion and the expansion of the EGR supply is increasing, flow analysis is essential to ensure a rapid flame propagation speed and stable combustion process. In this study, the flow around the spark plug was measured by the Laser Doppler Velocimetry system, and the correlation with combustion in spark-ignited engines was analyzed.

Accurate estimation of engine state(s) is vital for engine control systems to achieve their designated objectives. The fusion of sensors can significantly improve the estimation results in terms of accuracy and precision. This paper investigates using an Extended Kalman Filter (EKF) to estimate engine state(s) for Spark Ignited (SI) engines with the external EGR system. The EKF combines air path sensors with cylinder pressure feedback through a control-oriented engine cycle domain model. The model integrates air path dynamics, torque generation, exhaust gas temperature, and residual gas mass. The EKF generates a cycle-based estimation of engine state(s) for model-based control algorithms, which is not the focus of this paper. The sensor and noise dynamics are analyzed and integrated into the EKF formulation. To account for ‘non-white’ disturbances including modeling errors and sensor/actuator offset, the EKF engine state(s) observer is augmented with disturbance state(s) estimation.

Wall wetting of injected fuel onto the intake manifold and cylinder wall causes unpredictable transient behavior of air-fuel mixing which results in a significant emission of unburned hydrocarbon (HC) emission during cold start operation. Heated exhaust gas oxygen (HEGO) sensors cannot measure the air-fuel ratio (A/F) of exhaust gas during cold start condition. Precise and fast estimation of air/fuel ratio of the exhaust gas is required to elucidate the wall wetting phenomena and subsequent HC formation. Refined A/F estimation can enable the control of fuel injection minimizing HC emissions during cold start conditions so that HC emissions can be minimized. A new estimator for A/F of the exhaust gas has been developed. The A/F estimator described in this study utilizes measured exhaust gas temperature and general engine parameters such as engine speed, airflow, coolant temperature, etc.