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Li-ion batteries (LIBs) optimum performance and lifetime depend on temperature, with the commonly suggested operating temperature being in the range of 25 to 40 °C. It's also crucial to keep the temperature difference between battery cells below 5°C. Operation at different temperature ranges can adversely affect or degrade the performance and lifetime of LIBs. A battery thermal management system (BTMS) is essential for keeping the battery temperature within the optimum range. This paper aims to develop and analyze the BTMS for an electric heavy-duty truck. To achieve this aim, battery cells and modules are modelled in ANSYS Fluent software. Validation with experimental results and mesh sensitivity studies are also performed to increase confidence in simulation data. The model is then analyzed for a specific cooling systems to investigate its effect on battery thermal performance during the operation.

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.

To decarbonize heavy-duty vehicles solely through electrification with batteries is challenging as large batteries are required for a meaningful range, severely impacting payload. Employment of hybrid electric powertrains where fuel cells are integrated with batteries can deliver increased range and payload. However, the energy balance between the fuel cell and the battery needs to be analyzed to optimize the sizing of the powertrain components. This study has performed a multi-objective optimization using genetic algorithm to obtain the optimum range and hydrogen consumption for a DAF 44 tons heavy-duty truck. The proposed truck powertrain has been numerically modelled in AVL CRUISE M software. The electric drive from Involution Technologies Ltd and Bramble Energy Ltd’s printed circuit board fuel cell (PCBFC) are used in the model.

Electrification of the transportation sector requires an energy-efficient electric powertrain supported by renewable sources of energy to limit the use of fossil fuels. However, the integration of battery electric powertrains in heavy-duty trucks seems more challenging than other types due to the high battery demand and negative impacts on the truck’s cargo capacity. In this paper, the battery sizing of a 41-tons Mercedes Actros truck is performed based on battery safety zone operating conditions. A parametric study is conducted to assess the impacts of sizing on a truck’s total cargo capacity as well as the body dynamic parameters. The numerical model of the Mercedes Actros electric powertrain is developed in AVL CRUISETM M software. The hybrid pulsed power characterization tests are performed on 3Ah lithium-ion NMC cells in the lab for fitting the second-order equivalent circuit model’s parameters used in the analysis.

Electrification is one of the main solutions for the decarbonization of the transport system. It is employed widely by the automotive industry in light- and medium-duty vehicles and recently started to be considered in heavy-duty applications. However, powertrain electrification of heavy-duty vehicles, especially for Class 8 trucks, is very challenging. In this study, the battery-electric powertrain energy and technical performance of a DAF 44 tones truck are compared for two different electric drives. The case study truck is modeled in AVL CRUISE M software and the battery electric powertrain is evaluated for long haul driving cycle. The minimum number of battery packs is determined by defining the lowest energy consumption of the powertrain designed for the proposed drive cycle. Also, a transient analysis is accomplished to investigate the impact of various electric drives on energy consumption and performance of the proposed electric powertrain.

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.

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.

The focus of this study is to analyse changes in soot particle size along the predicted pathlines as they pass through different in-cylinder combustion histories obtained from Kiva-3v CFD simulation with a series of Matlab routines. 3500 locations representing soot particles were selected inside the cylinder at 8° CA ATDC as soot was formed in high concentration at this CA. The dominant soot particle size was recorded within the size range of 20-50 nm at earlier CA and shifted to 10-20 nm after 20° CA ATDC. Soot particle quantities reduce sharply until 20° CA ATDC after which they remain steady at around 1500 particles. Soot particles inside the bowl region tend to stick to the bowl walls and those remaining in the bowl experience an increase in size. Soot particles that move to the upper bowl and squish regions were observed to experience a decrease in size.

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.

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.

Soot formation and distribution inside the cylinder of a light-duty direct injection diesel engine, have been predicted using Kiva-3v CFD software. Pathlines of soot particles traced from specific in-cylinder locations and crank angle instants have been explored using the results for cylinder charge motion predicted by the Kiva-3v code. Pathlines are determined assuming soot particles are massless and follow charge motion. Coagulation and agglomeration have not been taken into account. High rates of soot formation dominate during and just after the injection. Oxidation becomes dominant after the injection has terminated and throughout the power stroke. Computed soot pathlines show that soot particles formed just below the fuel spray axis during the early injection period are more likely to travel to the cylinder wall boundary layer. Soot particles above the fuel spray have lesser tendency to be conveyed to the cylinder wall.

This work attempted to correlate the ultra fine particulate count to the flame propagation time, in-cylinder peak pressure, and in-cylinder ageing time (the time the particulates stay inside the cylinder) of a throttle body gasoline injected engine. The engine was tested at different loads and speeds ranging from 20 Nm to 100 Nm and 2000 to 3400 rpm respectively. A fast particle spectrometer, a mass spectrometer, and an in-cylinder pressure measurement system were used to characterize the particulate emission. This work identified the correlation between the nucleation of particulates and rate of burning, the particulate count for particles size greater than 200 nm and the in-cylinder ageing time. It identified that an increase in engine load at constant speed increased the particle number density of the 10 nm diameter particles; the effect was less significant on the particles of diameter greater than 50 nm and almost absent on particles of diameter greater than 200 nm.

This study attempted to identify the correlation between the gaseous species and nano-scale exhaust particles from a gasoline engine using simultaneous particulate and gaseous measurement. A fast particle spectrometer for particulates and a quadrupole mass spectrometer for gaseous species were employed in this work. Two commercially available super unleaded gasoline fuels were used in this study to establish a link between the gaseous species and nano-scale particulates. The possible correlations between the gaseous species such as acetylene, 1, 5 hexadyne, toluene, benzene and furaldehyde and nano-scale particles were identified and are detailed in this paper.

Recent developments in measurement techniques enabled researchers to measure ultra-fine particulates of nano-scale range and provided more evidence that the smaller particulates typically emitted from gasoline engines may have more severe impacts on human respiratory system than the bigger particulates from diesel engines. The knowledge of the characteristics of particulates from gasoline engines, especially, the effect of fuel borne additives is sparse. This work presents the findings from a study into the effect of aftermarket additives on nano-scale particulates. Four commercially available fuel borne additives used in gasoline engines mainly by private vehicle owners in the United Kingdom were selected for this study. The combustion and emission performance of the additive fuels were compared against that of commercially available gasoline fuel using a 4-stroke, throttle body injected gasoline engine.