Search Results

This study focuses on evaluation of various fuels within a conventional gasoline internal combustion engine (ICE) vehicle and the implementation of advanced emissions reduction technology. It shows the robustness of the implemented technology packages for achieving ultra-low tailpipe emissions to different market fuels and demonstrates the potential of future GHG neutral powertrains enabled by drop-in lower carbon fuels (LCF). An ultra-low emission (ULE) sedan vehicle was set up using state-of-the-art engine technology, with advanced vehicle control and exhaust gas aftertreatment system including a prototype rapid catalyst heating (RCH) unit. Currently regulated criteria pollutant emission species were measured at both engine-out and tailpipe locations. Vehicle was run on three different drive cycles at the chassis dynamometer: two standard cycles (WLTC and TfL) at 20°C, and a real driving emission (RDE) cycle at -7°C.

Several governments are increasing the blending mandate of renewable fuels to reduce the life-cycle greenhouse gas emissions of the road transport sector. Currently, ethanol is a prominent renewable fuel and is used in low-level blends, such as E10 (10 %v/v ethanol, 90 %v/v gasoline) in many parts of the world. However, the exact concentration of ethanol amongst other renewable fuel components in commercially available fuels can vary and is not known. To understand the impact of the renewable fuel content on the emissions from Euro 6d-TEMP emissions specification vehicles, this paper examines the real-driving emissions (RDE) from four 2020 to 2022 model-year vehicles run on E0 and E10 fuels. CO, CO2, NO, and NO2 were measured through a Portable Emissions Measuring System (PEMS).

In the context of the energy transition, CO2-neutral solutions are of enormous importance for all sectors, but especially for the mobility sector. Hydrogen as an energy carrier has therefore been the focus of research and development for some time. However, the development of hydrogen combustion engines is in many respects still in the conception phase. Automotive system providers and engineering companies in the field of software development and simulation are showing great interest in the topic. In a joint project with the industrial partners Robert Bosch GmbH and AVL Germany, combustion in a H2-DI-engine for use in light-duty vehicles was methodically investigated using the CFD tool AVL FIRE®. The collaboration between Robert Bosch GmbH and the Institute for Mobile Systems (IMS) at Otto von Guericke University Magdeburg has produced a model study in which model approaches for the combustion of hydrogen can be analyzed.

Under the proposed Green Deal program, the European Union will aim to achieve zero net greenhouse gas (GHG) emissions by 2050. The interim target is to reduce GHG by 55% by 2030. In the current debate concerning CO2-neutral powertrains, bio-fuels and e-fuels could play an immediate and practical role in reducing lifecycle engine emissions. Hydrogen however, is one of the few practical fuels that can result in near zero CO2 emissions at the tailpipe, which is the main focus of current legislation. Compared to gasoline, hydrogen presents a higher laminar flame speed, a wider range of flammability and higher auto-ignition temperatures, making it among the most attractive of fuels for future engines. As a challenge, hydrogen requires a very low ignition energy. This may imply an increased susceptibility to Low Speed Pre-Ignition (LSPI), surface ignition and back-fire phenomena. In order to exploit hydrogen’s potential, the injection system plays an extremely important role.

X-Domain describes the merging of different domains (i.e., braking, steering, propulsion, suspension) into single functionalities. One example in this context is torque-vectoring. Different goals can be pursued by applying X-Domain features. On the one hand, savings in fuel consumption and an improved vehicle driving performance can be potentially accomplished. On the other hand, safety can be improved by taking over a failed or degraded functionality of one domain by other domains. The safety-aspect from the viewpoint of requirements is highlighted within this contribution. Every automotive system being developed and influencing the vehicle safety must fulfill certain safety objectives. These are top-level safety requirements (ISO 26262-1) specifying functionalities to avoid unreasonable risk. Every safety objective is associated with an Automotive Safety Integrity Level (ASIL) derived from a Hazard Analysis and Risk Assessment (HARA).

Low temperature heat release (LTHR) has been of interest to researchers for its potential to mitigate knock in spark ignition (SI) engines and control auto-ignition in advanced compression ignition (ACI) engines. Previous studies have identified and investigated LTHR in both ACI and SI engines before the main high temperature heat release (HTHR) event by appropriately curating the in-cylinder thermal state during compression, or in the case of SI engines, timing the spark discharge late to reveal LTHR (sometimes referred to as pre-spark heat release). In this work, LTHR is demonstrated in isolation from HTHR events. Tests were run on motored single-cylinder engines and inlet air temperatures and pressures were adjusted to realise LTHR from n-heptane and iso-octane (2,2,4-trimethylpentane) without entering the HTHR regime. LTHR was observed for a lean n-heptane-air mixture at inlet temperatures ranging from 60°C to 100°C and inlet pressures of 0.9 bar (absolute).

Historically, whenever the automotive solutions’ state of art reaches a saturation level, the integration of new verticals of technology has always raised new opportunities to innovate, enhance and optimize automotive solutions. The predictive powertrain solutions using connectivity elements (e.g., navigation unit, e-Horizon or cloud-based services) are one of such areas of huge interest in automotive industry. The prior knowledge of trip destination and its route characteristics has potential to make prediction of powertrain modes or events in certain order and therefore it can add value in various application areas such as optimized energy management, lower fuel consumption, superior safety and comfort, etc.

Nowadays automobiles are getting smart and there is a growing need for the physical behavior to become part of its software. This behavior can be described in a compact form by differential equations obtained from modeling and simulation tools. In the offline simulation domain the Functional Mockup Interface (FMI) [3], a popular standard today supported by many tools, allows to integrate a model with solver (Co-Simulation FMU) into another simulation environment. These models cannot be directly integrated into embedded automotive software due to special restrictions with respect to hard real-time constraints and MISRA compliance. Another architectural restriction is organizing software components according to the AUTOSAR standard which is typically not supported by the physical modeling tools. On the other hand AUTOSAR generating tools do not have the required advanced symbolic and numerical features to process differential equations.

Particulate emissions from gasoline direct injection (GDI) engines continue to be a topic of substantial research interest. Forthcoming regulation both in the USA and the EU will further reduce their emission and drive innovation. Substantial research effort is spent undertaking experiments to understand, characterize, and research particle number (PN) emissions from engines and vehicles. Recent advances in computing power, data storage, and understanding of artificial intelligence algorithms now mean that these are becoming an important tool in engine research. In this work a random forest (RF) algorithm is used for the prediction of PN emissions from a highly boosted (up to 32 bar BMEP) GDI engine. Particle size, concentration, and the accumulation mode geometric standard deviation (GSD) are all predicted by the model. The results are analysed and an in depth study on parameter importance is carried out.

Low temperature combustion (LTC) of diesel fuel offers a path to low engine emissions of nitrogen oxides (NOx) and particulate matter (PM), especially at low loads. Borescopic optical imaging offers insight into key aspects of the combustion process without significantly disrupting the engine geometry. To assess LTC combustion, two-colour pyrometry can be used to quantify local temperatures and soot concentrations (KL factor). High sensitivity photo-multiplier tubes (PMTs) can resolve natural luminosity down to low temperatures with adequate signal-to-noise ratios. In this work the authors present the calibration and implementation of a borescope-based system for evaluating low luminosity LTC using spatially resolved visible flame imaging and high-sensitivity PMT data to quantify the luminous-area average temperature and soot concentration for temperatures from 1350-2600 K.

This study looked into the application of active thermal coatings on the surfaces of the combustion chamber as a method of improving the thermal efficiency of internal combustion engines. The active thermal coating was applied to a production aluminium piston and its performance was compared against a reference aluminium piston on a single-cylinder diesel engine. The two pistons were tested over a wide range of speed/load conditions and the effects of EGR and combustion phasing on engine performance and tailpipe emissions were also investigated. A detailed energy balance approach was employed to study the thermal behaviour of the active thermal coating. In general, improvements in indicated specific fuel consumption were not statistically significant for the coated piston over the whole test matrix. Mean exhaust temperature showed a marginal increase with the coated piston of up to 6 °C.

The European Particle Measurement Program (PMP) defines the current standard for measurement of Particle Number (PN) emissions from vehicles in Europe. This specifies a 50% count efficiency (D50) at 23 nm and a 90% count efficiency (D90) at 41 nm. Particulate emissions from Gasoline Direct Injection (GDI) engines have been widely studied, but usually only in the context of PMP or similar sampling procedures. There is increasing interest in the smallest particles - i.e. smaller than 23 nm - which can be emitted from vehicles. The literature suggest that by moving D50 to 10 nm, PN emissions from GDI engines might increase by between 35 and 50% but there remains a lot of uncertainty.

Ingestion of high altitude atmospheric ice particles can be hazardous to gas turbine engines in flight. Ice accretion may occur in the core compression system, leading to blockage of the core gas path, blade damage and/or flameout. Numerous engine powerloss events since 1990 have been attributed to this mechanism. An expansion in engine certification requirements to incorporate ice crystal conditions has spurred efforts to develop analytical models for phenomenon, as a method of demonstrating safe operation. A necessary component of a complete analytical icing model is a thermodynamic accretion model. Continuity and energy balances are performed using the local flow conditions and the mass fluxes of ice and water that are incident on a surface to predict the accretion growth rate.

A significant number of historical engine powerloss events have recently been attributed to ingestion of high altitude ice crystals, prompting regulators to expand engine certification envelopes to incorporate ‘ice crystal icing’ conditions. There has been a resulting effort by OEMs and academia to develop analytical and semi-empirical models for the phenomenon, partly through use of rig testing. The current study presents results and analysis of experiments conducted in the National Research Council’s Research Altitude Test Facility (RATFac). The experiments used a simplified compressor stator vane test article, designed to produce data to build semi-empirical models and validate an existing ice crystal icing code. Accretion growth rates, extracted from backlit shadowgraphy, are presented as a function of test condition, and the algorithm of a new image processing technique using Canny filtering is discussed.

Numerous turbofan power-loss events have occurred in high altitude locations in the presence of ice crystals. It is theorized that ice crystals enter the engine core, partially melt in the compressor and then accrete onto stator blade surfaces. This may lead to engine rollback, or shed induced blade damage, surge and/or flameout. The first generation of ice crystal icing predictive models use a single flow field where there is no accretion to calculate particle trajectories and accretion growth rates. Recent work completed at the University of Oxford has created an algorithm to automatically detect the edge of accretion from experimental video data. Using these accretion profiles, numerical simulations were carried out at discrete points in time using a manual meshing process.

High altitude ice crystals can pose a threat to aircraft engine compression and combustion systems. Cases of engine damage, surge and rollback have been recorded in recent years, believed due to ice crystals partially melting and accreting on static surfaces (stators, endwalls and ducting). The increased awareness and understanding of this phenomenon has resulted in the extension of icing certification requirements to include glaciated and mixed phase conditions. Developing semi-empirical models is a cost effective way of enabling certification, and providing simple design rules for next generation engines. A comprehensive ice crystal icing model is presented in this paper, the Ice Crystal Icing ComputationaL Environment (ICICLE). It is modular in design, comprising a baseline code consisting of an axisymmetric or 2D planar flowfield solution, Lagrangian particle tracking, air-particle heat transfer and phase change, and surface interactions (bouncing, fragmentation, sticking).

Combustion recession, an end of injection (EOI) diesel spray phenomenon, has been found to be a robust correlation parameter for UHC in diesel LTC strategies. Previous studies have shown that the likelihood of capturing combustion recession in numerical simulations is highly dependent on the details of the low-temperature chemistry reaction mechanisms employed. This study aims to further the understanding of the effects of different chemical mechanisms in the prediction of a reactive diesel spray and its EOI process: combustion recession. Studies were performed under the Engine Combustion Network’s (ECN) “Spray A” conditions using the Reynolds-Averaged Navier-Stokes simulation (RANS) and the Flamelet Generated Manifold (FGM) combustion model with four different chemical mechanisms for n-dodecane that are commonly used in the engine simulation communities - including recently developed reduced chemistry mechanisms.

Chromium-molybdenum alloy steel pistons, which have been used in commercial vehicle applications for some time, have more recently been proposed as a means of improving thermal efficiency in light-duty applications. This work reports a comparison of the effects of geometrically similar aluminium and steel pistons on the combustion characteristics and energy flows on a single cylinder high-speed direct injection diesel research engine tested at two speed / load conditions (1500 rpm / 6.9 bar nIMEP and 2000 rpm/25.8 bar nIMEP) both with and without EGR. The results indicate that changing to an alloy steel piston can provide a significant benefit in brake thermal efficiency at part-load and a reduced (but non-negligible) benefit at the high-load condition and also a reduction in fuel consumption. These benefits were attributed primarily to a reduction in friction losses.

In-cylinder flow motion has a significant effect on mixture preparation and combustion. Therefore, it is vital that CFD engine simulations are capable of accurately predicting the in-cylinder velocity fields. High-speed planar Particle Image Velocimetry (PIV) experiments have been performed on a single-cylinder GDI optical engine in order to validate CFD simulations for a range of engine conditions. Novel metrics have been developed to quantify the differences between experimental and simulated velocity fields in both alignment and magnitude. The Weighted Relevance Index (WRI) is a variation of the standard Relevance Index that accounts for the local velocity magnitudes to provide a robust comparison of the alignment between two vector fields. Similarly, the Weighted Magnitude Index (WMI) quantifies the differences in the local magnitudes of the two velocity fields.

In-cylinder temperatures and their cyclic variations strongly influence many aspects of internal combustion engine operation, from chemical reaction rates determining the production of NOx and particulate matter to the tendency for auto-ignition leading to knock in spark ignition engines. Spatially resolved measurements of temperature can provide insights into such processes and enable validation of Computational Fluid Dynamics simulations used to model engine performance and guide engine design. This work uses a combination of Two-Colour Planar Laser Induced Fluorescence (TC-PLIF) and Laser Induced Grating Spectroscopy (LIGS) to measure the in-cylinder temperature distributions of a firing optically accessible spark ignition engine. TC-PLIF performs 2-D temperature measurements using fluorescence emission in two different wavelength bands but requires calibration under conditions of known temperature, pressure and composition.