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This study focuses on the combustion visualization of spark ignition combustion in an optical single cylinder engine using natural gas and propane at several air to fuel ratios and speed-load operating points. Propane and natural gas fuels were compared as they are the most promising gaseous alternative fuels for reciprocating powertrains, with both fuels beginning to find wide market penetration on the fleet level across many regions of the world. Additionally, when compared to gasoline, these gaseous fuels are affordable, have high knock resistance and relatively low carbon content and they do not suffer from the complex re-fueling and storage problems associated with hydrogen.

Natural gas is a promising alternative fuel as it is affordable, available worldwide, has high knock resistance and low carbon content. This study focuses on the combustion visualization of spark ignition combustion in an optical single cylinder engine using natural gas at several air to fuel ratios and speed-load operating points. In addition, Turbulent Jet Ignition optical images are compared to the baseline spark ignition images at the world-wide mapping point (1500 rev/min, 3.3 bar IMEPn) in order to provide insight into the relatively unknown phenomenon of Turbulent Jet Ignition combustion. Turbulent Jet Ignition is an advanced spark initiated pre-chamber combustion system for otherwise standard spark ignition engines found in current passenger vehicles. This next generation pre-chamber design simply replaces the spark plug in a conventional spark ignition engine.

Electro-pneumatic valve actuators are used to eliminate the cam shaft of a traditional internal combustion engine. They are used to control the opening timing, duration, and lift of both intake and exhaust valves. A physics based nonlinear mathematical model called the level one model was built using Newton's law, mass conservation and thermodynamic principles. A control oriented model, the level two model, was created by partially linearizing the level one model for model reference parameter identification. This model reduces computational throughput and enables real-time implementation. A model reference adaptive control system was used to identify the nonlinear parameters that were needed for generating a feedforward control signal. The closed-loop valve lift tracking, valve opening and closing timing control strategies were proposed.

A direct-injection and spark-ignition single-cylinder engine with optical access to the cylinder was used for the combustion visualization study. Gasoline and ethanol-gasoline blended fuels were used in this investigation. Experiments were conducted to investigate the effects of fuel injection pressure, injection timing and the number of injections on the in-cylinder combustion process. Two types of direct fuel injectors were used; (i) high-pressure production injector with fuel pressures of 5 and 10 MPa, and (ii) low-pressure production-intent injector with fuel pressure of 3 MPa. Experiments were performed at 1500 rpm engine speed with partial load. In-cylinder pressure signals were recorded for the combustion analyses and synchronized with the high-speed combustion imaging recording. Visualization results show that the flame growth is faster with the increment of fuel injection pressure.

The automotive industry is subject to stringent regulations in emissions and growing customer demands for better fuel consumption and vehicle performance. Engine calibration, a process that optimizes engine performance by tuning engine controls (actuators), becomes challenging nowadays due to significant increase of complexity of modern engines. The traditional sweep-based engine calibration method is no longer sustainable. To tackle the challenge, this work considers two powerful global optimization methods: genetic algorithm (GA) and Bayesian optimization for steady-state engine calibration for single speed-load point. GA is a branch of meta-heuristic methods that has shown a great potential on solving difficult problems in automotive engineering. Bayesian optimization is an efficient global optimization method that solves problems with computationally expensive testing such as hyperparameter tuning in deep neural network (DNN), engine testing, etc.

The requirement of reduced emissions and improved fuel economy led the introduction of direct-injection (DI) spark-ignited (SI) engines. Dual-fuel injection system (direct-injection and port-fuel-injection (PFI)) was also used to improve engine performance at high load and speed. Ethanol is one of the several alternative transportation fuels considered for replacing fossil fuels such as gasoline and diesel. Ethanol offers high octane quality but with lower energy density than fossil fuels. This paper presents the combustion characteristics of a single cylinder dual-fuel injection SI engine with the following fueling cases: a) gasoline for PFI and DI, b) PFI gasoline and DI ethanol, and c) PFI ethanol and DI gasoline. For this study, the DI fueling portion varied from 0 to 100 percentage of the total fueling over different engine operational conditions while the engine air-to-fuel ratio remained at a constant level.