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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.

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%.

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 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.

The information provided by the in-cylinder pressure signal is of great importance for modern engine management systems. The obtained information is implemented to improve the control and diagnostics of the combustion process in order to meet the stringent emission regulations and to improve vehicle reliability and drivability. The work presented in this paper covers the experimental study and proposes a comprehensive and practical solution for the estimation of the in-cylinder pressure from the crankshaft speed fluctuation. Also, the paper emphasizes the feasibility and practicality aspects of the estimation techniques, for the real-time online application. In this study an engine dynamics model based estimation method is proposed. A discrete-time transformed form of a rigid-body crankshaft dynamics model is constructed based on the kinetic energy theorem, as the basis expression for total torque estimation.

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.

A multi-dimensional combustion code implementing the Conditional Moment Closure turbulent combustion model interfaced with a well-established RANS two-phase flow field solver has been employed to study a broad range of operating conditions for a heavy duty direct-injection common-rail Diesel engine. These conditions include different loads (25%, 50%, 75% and full load) and engine speeds (1250 and 1830 RPM) and, with respect to the fuel path, different injection timings and rail pressures. A total of nine cases have been simulated. Excellent agreement with experimental data has been found for the pressure traces and the heat release rates, without adjusting any model constants. The chemical mechanism used contains a detailed NOx sub-mechanism. The predicted emissions agree reasonably well with the experimental data considering the range of operating points and given no adjustments of any rate constants have been employed.

This paper describes cyclic Air/Fuel ratio (AFR) measurements carried out with a novel device (fUEGO) based on a production Universal Exhaust Gas Oxygen sensor, but modified to give an improved frequency response. The results are compared to AFR calculated from a fast CO/CO2 analyser and a fast response flame ionization detector (FID). The direct comparison of the two different methods for determining the cyclic AFR reveals that the electrochemical device is in reasonable agreement with the more complex carbon balance method and can provide reliable cyclic AFR measurements with a reduced requirement for equipment and data post processing. The fUEGO however is sensitive to elevated levels of uHC's (unburned hydrocarbons) during misfires or partial burns and readings during such situations usually show deviations compared to the carbon balance method.

It is well known that accurate EGR control is paramount to controlling engine out emissions during steady state and transient operation of a diesel engine. The direct measurement of EGR is however non-trivial and especially difficult in engines with no external EGR control where the intake manifold CO2 levels can be measured more readily. This work studies the EGR behaviour in a medium duty diesel engine with a passive EGR rebreathing strategy for steady state and transient operation. High speed (response time ∼1ms) in-cylinder sampling using modified GDI valves is coupled with high frequency response analysers to measure the cyclic in-cylinder CO2, from which the EGR rate is deduced. It was found that controlling the EGR using the passive rebreathing strategy during certain combined speed and load transients is challenging, causing high smoke and NO emissions.

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.