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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.

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.

Results from a large set of HCCI experiments performed on a single-cylinder research engine fueled with different mixtures of iso-octane and n-heptane are presented and discussed in this paper. The experiments are designed to scrutinize fuel reactivity effects on the operating range of an HCCI engine. The fuel effects on upper and lower operating limits are measured respectively by the maximum pressure rise rate inside the cylinder and the stability of engine operation as determined by cycle-to-cycle variations in IMEP. Another set of experiments that examine the intake air heating effects on HCCI engine performance, exhaust emissions and operating envelopes is also presented. The effects of fuel reactivity and intake air heating on the HCCI ranges are demonstrated by constructing the operating envelopes for the different test fuels and intake temperatures.

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.

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.

Employing detailed chemistry into modern engine simulation technologies has potential to enhance the robustness and predictive power of such tools. Specifically this means significant advancements in the ability to compute the onset of ignition, low and high temperature heat release, local extinction, knocking, exhaust gas emissions formation etc. resulting in a set of tools which can be employed to carry out virtual engineering studies and add additional insight into common IC engine development activities such as computing IMEP, identifying safe/feasible operating ranges, minimizing exhaust gas emissions and optimizing operating strategy. However the adoption of detailed chemistry comes at a greater computational cost, this paper investigates the means to retain computational robustness and ease of use whist reducing computational timescales.

Regulations on emissions from diesel and gasoline fuelled engines are becoming more stringent in all parts of the world. Hence there is a great deal of interest in developing advanced combustion systems that offer the efficiency of a diesel engine, but with low PM and NOx. One promising approach is that of Partially-Premixed Compression Ignition (PPCI) or Low Temperature Combustion (LTC). Using this approach, PM can be reduced in compression ignition engines by promoting the mixing of fuel and air prior to combustion. This paper describes the application of an advanced combustion simulator for fuels, combustion and emissions to analyze the key processes which occur in PPCI combustion mode. A detailed chemical kinetic model with advanced PM population balance sub-model is employed in a PPCI engine context to examine the impact of ignition resistance on combustion, mixing, ignition and emissions.

In recent decades, “physics-based” gas-dynamics simulation tools have been employed to reduce development timescales of IC engines by enabling engineers to carry out parametric examinations and optimisation of alternative engine geometry and operating strategy configurations using desktop PCs. However to date, these models have proved inadequate for optimisation of in-cylinder combustion and emissions characteristics thus extending development timescales through additional experimental development efforts. This research paper describes how a Stochastic Reactor Model (SRM) with reduced chemistry can be employed to successfully determine in-cylinder pressure, heat release and emissions trends from a diesel fuelled engine operated in compression ignition direct injection mode using computations which are completed in 147 seconds per cycle.

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 HCCI engines, the Air/Fuel Ratio (AFR) and Residual Gas Fraction (RGF) are difficult to control during the SI-HCCI-SI transition, and this may result in incomplete combustion and/or high pressure raise rates. As a result, there may be undesirably high engine load fluctuations. The objectives of this work are to further understand this process and develop control methods to minimize these load fluctuations. This paper presents data on instantaneous AFR and RGF measurements, both taken by novel experimental techniques. The data provides an insight into the cyclic AFR and RGF fluctuations during the switch. These results suggest that the relatively slow change in the intake Manifold Air Pressure (MAP) and actuation time of the Variable Valve Timing (VVT) are the main causes of undesired AFR and RGF fluctuations, and hence an unacceptable Net IMEP (NIMEP) fluctuation. We also found large cylinder-to-cylinder AFR variations during the transition.

A Stochastic Reactor Model (SRM) has been used to simulate the transition from Spark Ignition (SI) mode to Homogeneous Charge Compression Ignition (HCCI) mode in a four cylinder in-line four-stroke naturally aspirated direct injection SI engine with cam profile switching. The SRM is coupled with GT-Power, a one-dimensional engine simulation tool used for modelling engine breathing during the open valve portion of the engine cycle, enabling multi-cycle simulations. The model is initially calibrated in both modes using steady state data from SI and HCCI operation. The mode change is achieved by switching the cam profiles and phasing, resulting in a Negative Valve Overlap (NVO), opening the throttle, advancing the spark timing and reducing the fuel mass as well as utilising a pilot injection. Experimental data is presented along with the simulation results.

This research describes the potential to adopt detailed chemical kinetics for practical and potential future fuels using tri-component surrogate mixtures capable of simulating fuel octane “sensitivity” . Since the combustion characteristics of modern fuels are routinely measured using the RON and MON of the fuel, a methodology to generate detailed chemical kinetic mechanisms for these fuels based on these data is presented. Firstly, a novel correlation between various tri-component blends (comprised of i-octane, n-heptane and toluene) and fuel RON and MON was obtained by carrying out standard octane tests. Secondly, a chemical kinetic mechanism for tri-component fuels was validated using a Stochastic Reactor Model (SRM) suite, an in-cylinder engine combustion simulator, and a series of engine experiments conducted in HCCI operating mode.

An established Stochastic Reactor Model (SRM) is used to simulate the transition from Spark Ignition (SI) to Homogeneous Charge Compression Ignition (HCCI) combustion mode in a four-cylinder in-line four-stroke naturally aspirated direct injection SI engine with cam profile switching. The SRM is coupled with GT-Power, a one-dimensional engine simulation tool used for modeling engine breathing during the open valve portion of the engine cycle, enabling multi-cycle simulations. The mode change is achieved by switching the cam profiles and phasing, resulting in a Negative Valve Overlap (NVO), opening the throttle, advancing the spark timing and reducing the fuel mass as well as using a pilot injection. A proven technique for tabulating the model is used to create look-up tables in both SI and HCCI modes. In HCCI mode several tables are required, including tables for the first NVO, transient valve timing NVO, transient valve timing HCCI and steady valve timing HCCI and NVO.

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.

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 previously developed Stochastic Reactor Model (SRM) is used to simulate combustion in a four cylinder in-line four-stroke naturally aspirated direct injection Spark Ignition (SI) engine modified to run in Homogeneous Charge Compression Ignition (HCCI) mode with a Negative Valve Overlap (NVO). A portion of the fuel is injected during NVO to increase the cylinder temperature and enable HCCI combustion at a compression ratio of 12:1. The model is coupled with GT-Power, a one-dimensional engine simulation tool used for the open valve portion of the engine cycle. The SRM is used to model in-cylinder mixing, heat transfer and chemistry during the NVO and main combustion. Direct injection is simulated during NVO in order to predict heat release and internal Exhaust Gas Recycle (EGR) composition and mass. The NOx emissions and simulated pressure profiles match experimental data well, including the cyclic fluctuations.

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.

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.

Two-stage fuel direct injection (DI) has the potential to expand the operating region and control the auto-ignition timing in a Diesel fuelled homogeneous charge compression ignition (HCCI) engine. In this work, to investigate the dual-injection HCCI combustion, a stochastic reactor model, based on a probability density function (PDF) approach, is utilized. A new wall-impingement sub-model is incorporated into the stochastic spray model for direct injection. The model is then validated against measurements for combustion parameters and emissions carried out on a four stroke HCCI engine. The initial results of our numerical simulation reveal that the two-stage injection is capable of triggering the charge ignition on account of locally rich fuel parcels under certain operating conditions, and consequently extending the HCCI operating range.