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A heavy-duty diesel engine (ETH-LAV single cylinder MTU396 heavy duty research engine) was simulated by RANS and advanced reacting flow models to gain insight into its soot and NOx emissions. Due to symmetry, a section of the engine containing a single injector-hole was simulated. Dodecane was used as a surrogate to emulate the evaporation properties of diesel and a 22-step reaction mechanism for n-heptane was used to describe combustion. The Conditional Moment Closure (CMC) method was used as the combustion model in two ways. In a more conventional modelling approach, CMC was fully interfaced with the CFD and a two-equation model was employed for determining soot while the extended Zeldovich mechanism was used for NOx. In a second approach called the Imperfectly Stirred Reactor (ISR) method, the CMC equation was integrated over space and the previous RANS-CMC solution was further analysed in a post-processing step with the focus on soot.

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.

This paper investigates the energy efficiency and emissions benefits possible with connected and autonomous vehicles (CAVs). Such benefits could be instrumental in decarbonising the transport sector. The impact of CAV technology on operation, usage and specification of vehicles for optimised energy efficiency is considered. Energy consumption reductions of 55% – 66% are identified for a fully autonomous road transport system versus the present. 46% is possible for a CAV on today’s roads. Smoothing effects and reduced stoppage in the drive cycle achieve a 31% reduction in travel time if speed limits are not reduced. CAV powertrain optimised for different scenarios requires just 10 kW – 40 kW maximum power whilst the vehicle mass is reduced by up to 40% relative to current cars. Urban-optimised powertrain, with only 10 kW – 15 kW maximum power, allows energy consumption reductions of over 71%.

Engines with reduced emissions and improved efficiency are of high interest for road transport. However, achieving these two goals is challenging and various concepts such as PFI/DI/HCCI/PCCI are explored by engine manufacturers. The computational fluid dynamics is becoming an integral part of modern engine development programme because this method provides access to in-cylinder flow and thermo-chemical processes to develop a closer understanding to tailor tumble and swirling motions to construct green engines. The combustion modelling, its accuracy and robustness play a vital role in this. Out of many modelling methods proposed in the past flamelet based methods are quite attractive for SI engine application. In this study, FlaRe (Flamelets revised for physical consistencies) approach is used to simulate premixed combustion inside a gasoline PFI single-cylinder, four-stroke SI engine. This approach includes a parameter representing the effects of flame curvature on the burning rate.

The underbody of a truck is responsible for an appreciable portion of the vehicle’s aerodynamic drag, and thus its fuel consumption. A better understanding of the underbody aerodynamics could lead to designs that are more environmentally friendly. Unfortunately there are difficulties with correctly replicating the ground condition and rotating wheels when using the classical approach of a wind-tunnel for aerodynamic investigation. This in turn leads to computational modelling problems. A lack of experimental data for Computational Fluid Dynamics (CFD) validation means that the flow field in this area has seldom been investigated. There is thus very little information available for the optimisation and design of underbody aerodynamic devices. This paper investigates the use of a water-towing tank, which allows the establishment of the correct near-ground flow while permitting good optical access. Using a 1/10 scale model, Reynolds Numbers of around 0.7 million are achieved.

The underbody of a truck is responsible for an appreciable portion of the vehicle’s aerodynamic drag, and thus its fuel consumption. This paper investigates experimentally the flow around side-skirts, a common underbody aerodynamic device which is known to be effective at reducing vehicle drag. A full, 1/10 scale European truck model is used. The chassis of the model is designed to represent one that would be found on a typical trailer, and is fully reconfigurable. Testing is carried out in a water towing tank, which allows the correct establishment of the ground flow and rotating wheels. Optical access into the underbody is possible through the clear working section of the facility. Stereoscopic and planar Particle Image Velocimetry (PIV) set-ups are used to provide both qualitative images of and quantitative information on the flow field.

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.

Three-dimensional Computational Fluid Dynamics (CFD) has become an integral part in analysing engine in-cylinder processes since it provides detailed information on the flow and combustion, which helps to find design improvements during the development of modern engine concepts. The predictive capability of simulation tools depends largely on the accuracy, fidelity and robustness of the various models used, in particular concerning turbulence and combustion. In this study, a flamelet model with a physics based closure for the progress variable dissipation rate is applied for the first time to a spark ignited IC engine. The predictive capabilities of the proposed approach are studied for one operating condition of a gasoline port fuel injected single-cylinder, four-stroke spark ignited full-metal engine running at 3,500 RPM close to full load (10 bar BMEP) at stoichiometric conditions.

In recent years magnetic resonance imaging (MRI) has been shown to be an attractive method for fluid flow visualization. In this work, we show how MRI velocimetry techniques can be used to non-invasively investigate and visualize the hydrodynamics of exhaust gas in a diesel particulate filter (DPF), both when clean and after loading with diesel engine exhaust particulate matter. The measurements have been used to directly measure the gas flow in the inlet and outlet channels of the DPF, both axial profiles along the length and profiles across the channel diameter. Further, from this information we show that it is possible to indirectly ascertain the superficial wall-flow gas velocity and the soot loading profiles along the filter channel length.

The control of NOX emissions by exhaust gas recirculation (EGR) is of widespread application. However, despite dramatic improvements in all aspects of engine control, the subtle mixing processes that determine the cylinder-to-cylinder distribution of the recirculated gas often results in a mal-distribution that is still an issue for the engine designer and calibrator. In this paper we demonstrate the application of a relatively straightforward technique for the measurement of the absolute and relative dilution quantity in both steady state and transient operation. This was achieved by the use of oxygen sensors based on standard UEGO (universal exhaust gas oxygen) sensors but packaged so as to give good frequency response (∼ 10 ms time constant) and be completely insensitivity to the sample pressure and temperature. Measurements can be made at almost any location of interest, for example exhaust and inlet manifolds as well as EGR path(s), with virtually no flow disturbance.

Diesel fuel injection systems are operating at increasingly higher pressure (up to 250 MPa) with smaller clearances, making them more sensitive to diesel fuel contaminants. Most liquid particle counters have difficulty detecting particles <4 μm in diameter and are unable to distinguish between solid and semi-solid materials. The low conductivity of diesel fuel limits the use of the Coulter counter. This raises the need for a new method to characterize small (<4 μm) fuel contaminants. We propose and evaluate an aerosolization method for characterizing solid particulate matter in diesel fuel that can detect particles as small as 0.5 μm. The particle sizing and concentration performance of the method were calibrated and validated by the use of seed particles added to filtered diesel fuel. A size dependent correction method was developed to account for the preferential atomization and subsequent aerosol conditioning processes to obtain the liquid-borne particle concentration.

The European Emissions Stage 5b standard for diesel passenger cars regulates particulate matter to 0.0045 g/km and non-volatile part/km greater than 23 nm size to 6.0x10₁₁ as determined by the PMP procedure that uses a heated evaporation tube to remove semi-volatile material. Measurement artifacts associated with the evaporation tube technique prevents reliable extension of the method to a lower size range. Catalytic stripper (CS) technology removes possible sources of these artifacts by effectively removing all hydrocarbons and sulfuric acid in the gas phase in order to avoid any chemical reactions or re-nucleation that may cause measurement complications. The performance of a miniature CS was evaluated and experimental results showed solid particle penetration was 50% at 10.5 nm. The sulfate storage capacity integrated into the CS enabled it to chemically remove sulfuric acid vapor rather than rely on dilution to prevent nucleation.

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.

Transport policy research seeks to predict and substantially reduce the future transport-related greenhouse gas emissions and fuel consumption to prevent negative climate change impacts and protect the environment. However, making such predictions is made difficult due to the uncertainties associated with the anticipated developments of the technology and fuel situation in road transportation, which determine the total fuel use and emissions of the future light-duty vehicle fleet. These include uncertainties in the performance of future vehicles, fuels' emissions, availability of alternative fuels, demand, as well as market deployment of new technologies and fuels. This paper develops a methodology that quantifies the impact of uncertainty on the U.S. transport-related fuel use and emissions by introducing a stochastic technology and fleet assessment model that takes detailed technological and demand inputs.

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.

Gasoline Homogeneous Charge Compression Ignition (HCCI) combustion has been studied widely in the past decade. However, in HCCI engines using negative valve overlap (NVO), there is still uncertainty as to whether the effect of pilot injection during NVO on the start of combustion is primarily due to heat release of the pilot fuel during NVO or whether it is due to pilot fuel reformation. This paper presents data taken on a 4-cylinder gasoline direct injection, spark ignition/HCCI engine with a dual cam system, capable of recompressing residual gas. Engine in-cylinder samples are extracted at various points during the engine cycle through a high-speed sampling system and directly analysed with a gas chromatograph and flame ionisation detector. Engine parameter sweeps are performed for different pilot injection timings and quantities at a medium load point.

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.