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This paper presents a method for analysing the characteristics of nano-scale particles emitted from a 1.6 Litre, 4-stroke, gasoline direct injection (GDI) and turbocharged spark ignition engine fitted with a three-way catalytic converter. Ensemble Empirical Mode Decomposition (EEMD) is employed in this work to decompose the nano-scale particle size spectrums obtained using a differential mobility spectrometer (DMS) into Intrinsic Mode Functions (IMF). Fast Fourier Transform (FFT) is then applied to each IMF to compute its frequency content. The results show a strong correlation between the IMFs of specific particle ranges and the IMFs of the total particle count at various speed and load operating conditions. Hence, it is possible to characterise the influence of specific nano-scale particle ranges on the total particulate matter signal by analysing the frequency components of its IMFs using the EEMD-FFT method.

Formula (1) vehicles have transitioned from E5 to E10 fuel for the 2022 season to reduce carbon emissions and by 2026 the vehicles are required to use 100% sustainable fuels. The aim of this paper is to identify the operating envelope of the F1 power unit for E10-E100 fuel and the resulting emission levels for these fuel compositions using numerical simulations. To achieve this aim an F1 engine model has been developed in GT-Suite with reference to the FIA 2022 Technical Regulations. The combustion model has been validated using data obtained from literature relating to laminar and turbulent flame speed, friction and heat transfer characteristics within the combustion chamber. One of the main challenges of using ethanol-based fuels is the increased levels of formaldehyde in the tailpipe.

The COVID-19 pandemic has forced governments to implement rigorous containment measures on reduction or cessation of human mobility, transportation and economic activities, to control the spread of the virus. This is considered as a unique opportunity to study the impact of local lockdowns periods, especially, on the vehicle emission levels, and urban air quality in cities with high pollution levels, such as Bogota, Colombia. The first case was confirmed in Colombia on March 6, 2020, since then to prevent its propagation, the government declared a national lockdown starting from March 20 until August 31, 2020. Therefore, this study attempted to analyse the air quality in Bogota by assessing the concentrations of the atmospheric pollutants NO₂, SO₂, O₃, CO, PM₂.₅ and PM₁₀ during the lockdown period and the corresponding concentrations levels during the same period in 2018 and 2019. The data for this pilot study was obtained from the air quality monitoring stations of Bogota.

Formula 1 has always played a major role in technological advancements within the automotive and motorsport sectors. The adaptive changes introduced for the Power Unit (PU) in 2014 forced constructors, in collaboration with industry partners, to invent technologies for exceeding 50% brake thermal efficiency within a short span of time, demonstrating that technology-forcing regulations through motorsport is the favorable route to achieve transformative changes within the automotive sector. Therefore, in an attempt to address arising global warming and health concerns, the present work analytically examines the ambient air quality in track stadia during F1 race events to identify potential PU exhaust emission targets. It models the volume of air contained within the circuits located near heavily built-up areas assuming stagnant air conditions and uniform mixing.

The search for alternative fuel for transport vehicles and also replacement of internal combustion engines in order to reduce the harmful emissions have been forcing the vehicle manufacturers to innovate new technology solutions for meeting the stringent legislative targets. Mexico’s commitment for de-carbonisation of transport sector and meeting the environmental goals is shaping it especially, and with this, it favours the move towards electrification of the vehicles. The aim of the present work is to numerically evaluate the possibility of replacing the IC engine in the existing hybrid vehicles with the Hydrogen fuel cell system. This work modelled a Hydrogen fuel cell vehicle based on Toyota MIRAI and validated the fuel economy performance of the vehicle using experimental data. This validated model was used to estimate the fuel economy for real-world drive cycles generated in 2019 from Mexico City.

Air pollution levels in an urban environment is a major concern for developed and developing countries alike. Governments around the world are constantly trying to control and reduce air pollution levels through regulations. Low emission zones are being designated in cities worldwide in order to reduce the level of pollutants in big cities. The automotive industry is affected by those regulations and they are becoming more demanding over the years. Present work is aimed at developing a control strategy for a hybrid vehicle in order to optimize the fuel economy and emission levels based on GPS information, driver specific driving characteristics and weather forecast data for a given route. It uses powertrain model of a hybrid vehicle for developing route and driver specific control strategy. The full vehicle model has two sub-models: a route selector and a powertrain optimization model.

With a push to continuously develop traditional engine technology efficiencies and meet stringent emissions requirements, there is a need to improve the precision of injection rate measurement used to characterise the performance of the fuel injectors. New challenges in precisely characterising injection rate present themselves to the Original Equipment Manufacturers (OEMs), with the additional requirements to measure multiple injection strategies, increased injection pressure and rate features. One commonly used method of measurement is the rate tube injection analyser; it measures the pressure wave caused by the injection within a column of stationary fluid. In a rate tube, one of the significant sources of signal distortion is a result of the injected fluid pressure waves reflected back from the tube termination.

In the continuous search for technology to improve the fuel economy and reduce greenhouse gas emission levels from the automotive vehicle, the automotive industry has been evaluating various technological options. Since the introduction of stringent legislative targets in Europe as well as in the United States of America in late 20th Century, one of the viable options identified by the industry was the application of alternative powertrain. On the motorsport arena, changes introduced by the Formula 1 governing body (FIA) for the high-performance racing engines also focuses on fuel economy. FIA regulation for 2014 restricts the fuel-flow rate to a maximum of 100kg/hr beyond 10,500 rev/min and prescribe fuel flow rate below 10,500 rev/min operating conditions for the F1 Engines. In addition, Formula1 and Le Mans racing regulations actively promote the integration of the hybrid powertrain in order to achieve optimum fuel economy.

This study details the investigation into the hybridization of engine ancillary systems for 2014+ Le Mans LMP1-H vehicles. This was conducted in order to counteract the new strict fuel-limiting requirements governing the powertrain system employed in this type of vehicle. Dymola 1D vehicle simulation software was used to construct a rectilinear vehicle model with a map based 3.8L V8 engine and its associated ancillary systems, including oil pumps, water pump and fuel pump as well as a full kinetic energy recovery system (ERS). Appropriate validation strategy was implemented to validate the model. A validated model was used to study the difference in fuel consumption for the conventional ancillary drive off of the internal combustion engine in various situational tests and a hybrid-electric drive for driving engine ancillaries.

Stringent emission norms introduced by the legislators over the decades has forced automotive manufacturers to improve the fuel economy and emission levels of their engines continuously. Therefore, the emission levels of modern engines are significantly lower than pre-1990 engines. However, the improvement in fuel economy is marginal when compared to that of emission levels. For example, approximately 30% of total energy in the fuel is being wasted through the cooling systems in the modern engines. Therefore, thermal management systems are being developed to reduce these losses and offer new opportunities for improving the fuel economy of the vehicles. One of the new emerging technologies for thermal management is the use of nanofluids as coolant. Nanofluids are a mixture of nano-sized particles added to a base fluid to improve its thermal characteristics.

This work investigates the effect of a three-way catalytic converter and sampling dilution ratio on nano-scale exhaust particulate matter emissions from a gasoline direct-injection engine during cold-start and warm-up transients. Experimental results are presented from a four cylinder in-line, four stroke, wall-guided direct-injection, turbo-charged and inter-cooled 1.6 litre gasoline engine. A fast-response particulate spectrometer for exhaust nano-particle measurement up to 1000 nm was utilised. It was observed that the three-way catalytic converter had a significant effect on particle number density, reducing the total particle number by up to 65 % over the duration of the cold-start test. The greatest change in particle number density occurred for particles less than 23 nm diameter, with reductions of up to 95 % being observed, whilst the number density for particles above 50 nm diameter exhibited a significant increase.

Improving the thermal efficiency of internal combustion engines over the engine operating range is essential for achieving optimum fuel economy. The thermal efficiency of the engine during cold start is one of the areas where significant improvement can be made if a suitable thermal management strategy is identified and implemented. Thermal management strategy in an engine can allow the engine to work at different operating temperatures in order to reduce the heat transfer loss by ensuring optimum volumetric efficiency, efficient combustion and adequate safety margin for the durability of mechanical components. The aim of the present work was to numerically model the warm-up characteristics of a 4 cylinder, 1.6 litre, turbocharged and intercooled, Euro IV, gasoline direct injected engine. It used a fully validated engine model which works based on the predictive combustion model.

This work investigates the effect of engine operating conditions and exhaust sampling conditions (i.e. dilution ratio) on engine-out, nano-scale, particulate matter emissions from a gasoline direct-injection engine during cold-start and warm-up transients. The engine used for this research was an in-line four cylinder, four stroke, wall-guided direct-injection, turbo-charged and inter-cooled 1.6 l gasoline engine. A fast-response particulate spectrometer for exhaust nano-particle measurement up to 1000 nm was utilized, along with a spark-plug mounted pressure transducer for combustion analysis. It was observed that the total particle count decreases during the cold-start transient, and has a distinct relationship with the engine body temperature. Tests have shown that the engine body temperature may be used as a control strategy for engine-out particulate emissions.

A semi phenomenological and global chemical kinetic model is adopted and applied to predict soot formation in gasoline-fueled spark ignition engines. The adopted model considers acetylene produced from gasoline pyrolysis process as the main precursor for soot inception. The adopted soot model was initially proposed for diffusion flames and this work tries to apply and modify it to gasoline fueled (premixed flame) spark ignition engines. The burned mass fraction and burn rate are used to estimate the instantaneous acetylene, oxygen and Hydroxyl (OH) radical mass fractions at each crank angle of the engine. Experimental data from a single point throttle body injected spark ignition engine is used for validating total particle numbers at different engine operating conditions. The simulation results agree reasonably with the experimental results. Both experimental and predicted results showed that the inception rate increases with the engine load in an exponential form.

The search for next generation transportation fuels in order to fully or partially replace petrol based fuels has resulted in use of varieties of fuels and fuel blends in internal combustion engines. However, the engine management systems are fuel specific and therefore, every major change in fuel composition requires significant amount of calibration work to optimize the operating variables in order to meet legislative emission targets and reduce the real-world emission and improve fuel economy levels. The current work has successfully devised a numerical simulation for the operation of a modern 4-cylinder turbocharged engine using an adaptive combustion modelling methodology that identifies a fuel type during engine start itself, and adapts engine operating parameters for optimum performance. A strategy was devised to use commercially available sensors to obtain and correlate measurable cylinder pressure based information for fuel identification.

This study aims to identify the factors that control particulate matter (PM) formation and size distribution in direct-injection spark-ignition (DISI) engines. The test engine used for this research was a 1.6 litre, wall-guided DISI, turbocharged, intercooled, in-line 4 cylinder, Euro IV engine. The exhaust sampling point was before the catalytic converter, i.e. engine-out emissions were measured. The first part of this paper investigates the characteristics of PM number and size distribution of DISI and throttle body injected (TBI) engines. The second part investigates the effect of combustion characteristics of DISI engines on the number of 5nm and 10nm (nucleation) and 200nm (accumulation) PM. A statistical analysis of the coefficient of variance (COV) of the maximum rate of pressure rise (RPmax) over 100 cycles was performed against the COV of 5nm, 10nm and 200nm total particle number.

Improving fuel economy and reducing greenhouse gas emissions from vehicle sources have been major research themes in recent times. One of the ways to achieve this is to use alternative fuels that can fully or partly replace petroleum-derived fuels using existing internal combustion engine technology so that the benefit from the alternative fuels can be realized immediately without delay. The present work attempted to investigate the performance and emission characteristics of a diesel engine using conventional diesel fuel with mixtures of hydrogen and oxygen generated from water at the point of use. Small amounts of hydrogen and oxygen were introduced in the air stream at the time of induction so that no extra injection system or additional modifications to the existing engine were required.

This work aimed to study nano-scale particulate matter originating from gasoline direct injection engine during cold start and warm up operating conditions and to identify the role of the three-way catalytic converter on nano-scale particulate during cold-start and warm-up operating conditions. This work used a 4-stroke, 1.6 litre, wall guided gasoline direct injected, turbocharged and intercooled SI engine equipped with a three-way catalytic converter for this investigation. It used a fast particle spectrometer for the measurement of exhaust nano-scale particles upto 1000 nm diameter.

This study investigated the role of catalytic converters on tailpipe-out, nano-scale particulates from a Direct-Injection Spark-Ignition (DISI) gasoline engine. The test engine used for this research was a 1.6 litre, wall-guided DISI, turbocharged, intercooled, in-line 4-cylinder, Euro- IV engine. Spectral density of the particles in the exhaust stream before and after the catalytic converter was measured and was split into four size ranges: 5-10nm, 10-50nm, 50-100nm and 100-1000nm diameter for the sake of analysis. These four size ranges represent both nucleation mode (5-50nm) and accumulation mode (50-1000nm) particulates. The study found that for lower engine operating speeds, i.e. 1600rpm, the catalytic converter had a significant effect on the total number of 5-10 and 10-50nm diameter particles. At certain loading conditions the catalytic converter removed up to 60% of the 5-10nm particles and up to 22% of the 10-50nm particles.

The present work attempted to investigate the performance and emission characteristics of a diesel engine using conventional diesel fuel with mixtures of animal and vegetable derived bio-diesel that are available in Mexico and ultra low sulphur diesel with varying proportions. This work aimed at studying the performance of the engine at representative ambient conditions of Mexico City which is at an altitude of 2240m above sea level. The work identified that the levels of CO in the exhaust has a strong correlation with the proportion of bio-diesel in the conventional diesel fuel used. However, the performance of the engine, torque and power, are not affected significantly by varying the proportion of animal and bio-derived fuels in diesel fuel. In addition it also identified the correlation between the proportions of bio-diesel in diesel with the engine out particulate matter and the performance of diesel oxidation catalyst.