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Premixed Charge Compression Ignition (PCCI), a Low Temperature Combustion (LTC) strategy for diesel engines is of increasing interest due to its potential to simultaneously reduce soot and NOx emissions. However, the influence of mixture preparation on combustion phasing and heat release rate in LTC is not fully understood. In the present study, the influence of injection timing on mixture preparation, combustion and emissions in PCCI mode is investigated by experimental and computational methods. A sequential coupling approach of 3D CFD with a Stochastic Reactor Model (SRM) is used to simulate the PCCI engine. The SRM accounts for detailed chemical kinetics, convective heat transfer and turbulent micro-mixing. In this integrated approach, the temperature-equivalence ratio statistics obtained using KIVA 3V are mapped onto the stochastic particle ensemble used in the SRM.

A powerful and efficient turbocharger turbine benefits the engine in many aspects, such as better transient response, lower NOx emissions and better fuel economy. The turbine performance can be further improved by employing secondary flow injection through an injector over the shroud section. A secondary flow injection system can be integrated with a conventional turbine without affecting its original design parameters, including the rotor, volute, and back disk. In this study, a secondary flow injection system has been developed to fit for an asymmetric twin-scroll turbocharger turbine, which was designed for a 6-cylinder heavy-duty diesel engine, aiming at improving the vehicle’s performance at 1100 rpm under full-loading conditions. The shape of the flow injector is similar to a single-entry volute but can produce the flow angle in both circumferential and meridional directions when the flow leaves the injector and enters the shroud cavity.

A detailed chemical model was implemented in the KIVA-3V two dimensional CFD code to investigate the effects of the spray cone angle and injection timing on the PCCI combustion process and emissions in an optical research diesel engine. A detailed chemical model for Primary Reference Fuel (PRF) consisting of 157 species and 1552 reactions was used to simulate diesel fuel chemistry. The model validation shows good agreement between the predicted and measured pressure and emissions data in the selected cases with various spray angles and injection timings. If the injection is retarded to -50° ATDC, the spray impingement at the edge of the piston corner with 100° injection angle was shown to enhance the mixing of air and fuel. The minimum fuel loss and more widely distributed fuel vapor contribute to improving combustion efficiency and lowering uHC and CO emissions in the engine idle condition.

A novel modeling approach is applied to investigate the use of hydrogen-rich gas (HRG) for controlling the combustion process in a Homogenous-Charge Compression-Ignition (HCCI) engine. A detailed-chemistry stochastic reactor model is coupled with a one-dimensional gas dynamics model to account for the full engine cycle. The integrated model simulates the steady-state and transient operation of a single-cylinder HCCI engine. A previously developed tabulation scheme is utilized to speed up the detailed-chemistry simulations, which, though computationally cheap compared to many other approaches, are impractical for simulations involving a large number of cycles. A control strategy based on HRG addition is implemented using a closed-loop controller built within the gas dynamics model. Simulations conducted at different speeds and with varying loads indicate that the HRG can be effectively used to control the combustion phasing, and hence expand the operating range of the HCCI engine.

Analyzing the combustion characteristics, engine performance, and emissions pathways of the internal combustion (IC) engine requires management of complex and an increasing quantity of data. With this in mind, effective management to deliver increased knowledge from these data over shorter timescales is a priority for development engineers. This paper describes how this can be achieved by combining conventional engine research methods with the latest developments in process informatics and statistical analysis. Process informatics enables engineers to combine data, instrumental and application models to carry out automated model development including optimization and validation against large data repositories of experimental data.

This paper describes the development of a novel data model for storing and sharing data obtained from engine experiments, it then outlines a methodology for automatic model development and applies it to a state-of-the-art engine combustion model (including chemical kinetics) to reduce corresponding model parameter uncertainties with respect engine experiments. These challenges are met by adopting the latest developments in the semantic web to create a shared data model resource for the IC engine development community. The relevant data can be extracted and then used to set-up simulations for parameter estimation by passing it to the relevant application models. A methodology for incorporating experimental and model uncertainties into the model optimization procedure is presented.

A dual-fuel approach to control combustion in HCCI engine is investigated in this work. This approach involves controlling the combustion heat release rate by adjusting fuel reactivity according to the conditions inside the cylinder. Experiments were performed on a single-cylinder research engine fueled with different ratios of primary reference fuels and operated at different speed and load conditions, and results from these experiments showed a clear potential for the approach to expand the HCCI engine operation window. Such potential is further demonstrated dynamically using an optimized stochastic reactor model integrated within a MATLAB code that simulates HCCI multi-cycle operation and closed-loop control of fuel ratio. The model, which utilizes a reduced PRF mechanism, was optimized using a multi-objective genetic algorithm and then compared to a wide range of engine data.

A multi-objective optimization scheme based on stochastic global search is developed and used to examine the performance of an HCCI model containing a reduced chemical kinetic mechanism, and to study interrelations among different model responses. A stochastic reactor model of an HCCI engine is used in this study, and dedicated HCCI engine experiments are performed to provide reference for the optimization. The results revealed conflicting trends among objectives normally used in mechanism optimization, such as ignition delay and engine cylinder pressure history, indicating that a single best combination of optimization variables for these objectives did not exist. This implies that optimizing chemical mechanisms to maintain universal predictivity across such conflicting responses will only yield a predictivity tradeoff. It also implies that careful selection of optimization objectives increases the likelihood of better predictivity for these objectives.

Regulations concerning emissions from diesel- and gasoline-fuelled engines are becoming ever more stringent in all parts of the world. Historically these targets have been achieved through on-going technological development using an iterative process of computational modeling, design, build and test. Computational modeling is certainly the cheapest aspect within this process and if employed to meet more of the challenges associated with development, has the potential to significantly reduce developmental cost and time scales. Furthermore, computational models are an effective means to retain and apply often highly focused technical knowledge of complex processes within development teams thus delivering greater insight into processes.

In this study, the internal nozzle flow and macroscopic spray characteristics of a kind of wide distillation fuel (WDF) - kerosene were investigated both with numerical and experimental approaches. Simulation results indicate that compared with diesel fuel, kerosene cavitates more due to higher turbulent kinetic energy as a result of lower viscosity. The results from experiment indicate that under lower charge density, the spray penetration for kerosene is obviously shorter than that for diesel, especially for the lower injection pressure. This is because lower fuel viscosity results in a reduction in the size of the spray droplets, leading to lower momentum. However the spray angle of kerosene is larger compared with diesel due to stronger turbulence in the nozzle flow caused by increased cavitation for kerosene, which also accords well with the simulation results.