Search Results

Abstract The ASTM D130 was first issued in 1922 as a tentative standard for the detection of corrosive sulfur in gasoline. A clean copper strip was immersed in a sample of gasoline for three hours at 50°C with any corrosion or discoloration taken to indicate the presence of corrosive sulfur. Since that time, the method has undergone many revisions and has been applied to many petroleum products. Today, the ASTM D130 standard is the leading method used to determine the corrosiveness of various fuels, lubricants, and other hydrocarbon-based solutions to copper. The end-of-test strips are ranked using the ASTM Copper Strip Corrosion Standard Adjunct, a colored reproduction of copper strips characteristic of various degrees of sulfur-induced tarnish and corrosion, first introduced in 1954. This pragmatic approach to assessing potential corrosion concerns with copper hardware has served various industries well for a century.

Abstract The predictive control of commercial vehicle energy management systems, such as vehicle thermal management or waste heat recovery (WHR) systems, are discussed on the basis of information sources from the field of environment recognition and in combination with the determination of the vehicle system condition. In this article, a mathematical method for predicting the exhaust gas mass flow and the exhaust gas temperature is presented based on driving data of a heavy-duty vehicle. The prediction refers to the conditions of the exhaust gas at the inlet of the exhaust gas recirculation (EGR) cooler and at the outlet of the exhaust gas aftertreatment system (EAT). The heavy-duty vehicle was operated on the motorway to investigate the characteristic operational profile.

Abstract Composite ceramic brake discs are made of ceramic material reinforced with carbon fibers and offer exceptional advantages that translate directly into higher vehicle performance. In the case of an electric vehicle, it could increase the range of the vehicle, and in the case of conventional internal combustion engine vehicles, it means lower fuel consumption (and consequently lower CO2 emissions). These discs are typically characterized by complex internal geometries, further complicated by the presence of drilling holes on both friction surfaces. To estimate the aerothermal performance of these discs, and for the thermal management of the vehicle, a reliable model for predicting the air flowing across the disc channels is needed. In this study, a real carbon-ceramic brake disc with drilling holes was investigated in a dedicated test rig simulating the wheel corner flow conditions experimentally using the particle image velocimetry technique and numerically.

Abstract This work presents a generalized methodology for the optimal thermal management of different powertrain devices. The methodology is based on the adoption of an electrically driven pump and on the development of a specifically designed controller algorithm. This is achieved following a Model Predictive Control approach and requires a generalized lumped-parameters model of the thermal exchange between the device walls and the coolant. The methodology is validated at a test rig, with reference to a four-cylinder spark-ignition engine. Results show that the proposed approach allows a reduction in fuel consumption of about 2-3% during the engine warm-up, a decrease in fuel consumption of about 1-2% during fully warmed operation, and an estimated fuel consumption reduction of about 2.5-3% in an NEDC. Finally, the investigation highlights that the proposed approach reduces the risk of after-boiling when the engine is rapidly switched off after a prolonged high-load operation.

Abstract Thermoelectric devices (TEDs) allow direct electric and thermal energy mutual conversion. Because of the absence of working fluids and moving components, they can be used where it is not possible to refer to conventional technologies. In automotive applications, TEDs can give support in air conditioning and internal combustion engine (ICE) thermal heat recovery, contributing to increase the overall vehicle efficiency. Phenomena taking place in these devices are of a different nature and involve electric, thermal, and thermoelectric aspects, being highly influenced by materials’ characteristics and by system geometry. With the aim to offer a design tool, a TED mathematical model is presented in this article. The proposed model is based on a distributed parameter approach and has been conceived to consider heat transfer actual conditions. It accurately describes thermal energy production and removal terms due to Peltier and Joule effects.

Abstract The cold crank-start stage, including the first three engine cycles, is responsible for a significant amount of the cold-start phase emissions in a Gasoline Direct Injection (GDI) engine. The engine crank-start is highly transient due to substantial engine speed changes, Manifold Absolute Pressure (MAP) dynamics, and in-cylinder temperatures. Combustion characteristics change depending on control inputs variations, including throttle angle and spark timing. Fuel injection strategy, timing, and vaporization dynamics are other parameters causing cold-start first cycles analysis to be more complex. Hybrid Electric Vehicles (HEVs) provide elevated cranking speed, enabling technologies such as cam phasing to adjust the valve timing and throttling, and increased fuel injection pressure from the first firings.

Abstract Linear internal combustion engine-linear generator integrated system (LICELGIS) is an innovative energy conversion device with the ability of converting mechanical energy into electrical energy, which allows it to be a range extender for hybrid vehicles. This article presents a fundamental analysis for the steady-state operation of the LICELGIS, concentrating on electromagnetic force and motion characteristics. Simple assumptions are made to represent ideal gases instantaneous heat release and rejection. Based on assumptions, sensitivity analysis is carried out for key factors of electromagnetic force. The theoretical velocity model in mathematics is derived from analyzing the LICELGIS theory model. It shows that fuel injection quantity and stroke length are the most sensitive factors in key parameters. The piston velocity around the top dead center (TDC) changes greater than that at any other position, which is caused by the combustion process.

Abstract Performing an uncertainty analysis for complex measurement tasks, such as those found in engine research, presents unique challenges. Also, because of the excessive computational costs, modeling-based approaches, such as a Monte Carlo approach, may not be practical. This work provides a traditional statistical approach to uncertainty analysis that incorporates the uncertainty tree, which is a graphical tool for complex uncertainty analysis. Approaches to calculate the required sensitivities are discussed, including issues associated with numerical differentiation, numerical integration, and post-processing. Trimming of the uncertainty tree to remove insignificant contributions is discussed. The article concludes with a best practices guide in the Appendix to uncertainty propagation in experimental engine combustion post-processing, which includes suggested post-processing techniques and down-selected functional relationships for uncertainty propagation.

Abstract Autonomous vehicles (AVs) are expected to have a great impact on mobility by decreasing commute time and vehicle fuel consumption and increasing safety significantly. However, there are still issues that can jeopardize their wide impact and their acceptance by the public. One of the main limitations is motion sickness (MS). Hence, the last year’s research is focusing on improving motion comfort within AVs. On one hand, users are expected to perceive AVs driving style as more aggressive, as it might result in excessive head and body motion. Therefore, speed reduction should be considered as a countermeasure of MS mitigation. On the other hand, the excessive reduction of speed can have a negative impact on traffic. At the same time, the user’s dissatisfaction, i.e., acceptance and subjective comfort, will increase due to a longer journey time.

Abstract One of the key factors for accurate mass burn fraction and energy conversion point calculations is the accuracy of the compression ratio. The method presented in this article suggests a workflow that can be applied to determine or correct the compression ratio estimated geometrically or measured using liquid displacement. It is derived using the observation that, in a motored engine, the heat losses are symmetrical about a certain crank angle, which allows for the derivation of an expression for the clearance volume [1]. In this article, a workflow is implemented in real time, in a current production engine indicating system. The goal is to improve measurement data quality and stability for the energy conversion points calculated during measurement procedures. Experimental and simulation data is presented to highlight the benefits and improvement that can be achieved, especially at the start of combustion.

Abstract With the introduction of advanced lightweight materials with complex microstructures and behaviors, more focus is put on the accurate determination of their forming limits, and that can only be possible through experiments as the conventional theoretical models for the forming limit curve (FLC) prediction fail to perform. Despite that, CAE engineers, designers, and toolmakers still rely heavily on theoretical models due to the steep costs associated with formability testing, including mechanical setup, a large number of tests, and the cost of a stereo digital image correlation (DIC) system. The international standard ISO 12004-2:2021 recommends using a stereo DIC system for formability testing since two-dimensional (2D) DIC systems are considered incapable of producing reliable strains due to errors associated with out-of-plane motion and deformation.

Abstract Turbocharging can provide a low cost means for increasing the power output and fuel economy of an internal combustion engine. Currently, turbocharging is common in multi-cylinder engines, but due to the inconsistent nature of intake air flow, it is not commonly used in single-cylinder engines. In this article, we propose a novel method for turbocharging single-cylinder, four-stroke engines. Our method adds an air capacitor-an additional volume in series with the intake manifold, between the turbocharger compressor and the engine intake-to buffer the output from the turbocharger compressor and deliver pressurized air during the intake stroke. We analyzed the theoretical feasibility of air capacitor-based turbocharging for a single-cylinder engine, focusing on fill time, optimal volume, density gain, and thermal effects due to adiabatic compression of the intake air.

Abstract An efficient vehicle thermal management is essential to fulfil the requirements of fuel consumption and passenger comfort. Therefore, the design and dimensioning of the cooling system is under high scrutiny in new vehicle architectures. With increasing electrification, no longer just the load peaks define the design frame but also the dynamics of thermal loading and recovery. Consequently, electrified vehicle architectures such as plug-in hybrid fuel cell vehicles demand for alternative approaches regarding the design of cooling systems and the definition of the decisive criteria. This article presents a new methodology for designing the cooling system related to its demands in customer operation. The recorded fleet data is first filtered for high load driving, using the so-called thermal load integral (LI) as a filter criterion.

Abstract Technological advancements and growth in electric motors and battery packs enable vehicle propulsion electrifications, which minimize the need for fossil fuel consumption. The mobility shift to electric motors creates a demand for an efficient electric motor thermal management system that can accommodate heat dissipation needs with minimum power requirements and noise generation. This study proposes an intelligent hybrid cooling system that includes a gravity-aided passive cooling solution coupled with a smart supplementary liquid cooling system. The active cooling system contains a radiator, heat sink, variable frequency drive, alternating current (AC) fan, direct current (DC) pump, and real-time controller. A complete nonlinear mathematical model is developed using a lumped parameter approach to estimate the optimum fan and pump operations at each control interval.

Abstract Automotive interior coatings for flexible and rigid substrates represent an important segment within automotive coating space. These coatings are used to protect plastic substrates from mechanical and chemical damage, in addition to providing colour and design aesthetics. These coatings are expected to resist aggressive chemicals, fluids, and stains while maintaining their long-term physical appearance and mechanical integrity. Designing such coatings, therefore, poses significant challenges to the formulators in effectively balancing these properties. Among many factors affecting coating properties, the cross-link density (XLD) and solubility parameter (δ) of coatings are the most predominant factors.

Abstract Fast charging is significant for the driving convenience of an electric vehicle (EV). However, this technology causes lithium (Li)-ion batteries’ massive heat generation under such severe current rates. To ensure the thermal performance and lifespan of a Li-ion battery module under fast charging, an artificial neural network (ANN) regression method is proposed for a hybrid phase change material (PCM)—liquid coolant-based battery thermal management system (BTMS) design. Two ANN regression models are trained based on experimental data considering two targets: maximum temperature (Tmax ) and temperature standard deviation (TSD) of the hybrid cooling-based battery module. The regression accuracy reaches 99.942% and 99.507%, respectively. Four sets of experimental data are employed to validate the reliability of this method, and the cooling effect (Tmax and TSD) of the hybrid BTMS are predicted using the trained ANN regression models.

Abstract Stratified lean combustion has proven to be a promising approach for further increasing the thermal efficiency of gasoline direct injection engines in low load conditions. In this work, a new injection strategy for stratified operation mode is introduced. A side and a central-mounted solenoid multi-hole injector are simultaneously operated in a single-cylinder engine. Thermodynamic investigations show that this concept leads to improved stability, faster combustion, reduced particle number emissions, and lower fuel consumption levels compared to using only one injector. Experiments at an optical engine and three-dimensional computational fluid dynamics (CFD) simulations explain the improvements by a more compact mixture and reduced piston wetting with two injectors. Finally, the application of external EGR in combination with the above concept allows NOx emissions to be effectively kept at a low level while maintaining a stable operation.

Abstract Realizing the potential of the gasoline direct injection (GDI) concept lies in effectively stratifying the charge at different engine operating conditions. This is generally obtained by properly directing the air and fuel through carefully oriented intake port(s) and fuel spray and appropriately changing injection parameters. However, robust methods of charge stratification are essential to extend the lean operating range, particularly in small GDI engines. In this work, a novel piston shape was developed for a 200 cm3, single-cylinder, four-stroke gasoline engine to attain charge stratification. Stratification of charge is achieved even when the fuel was injected early in the intake stroke by a specially shaped wedge on the piston crown that produced twin vortices during compression and physically separated the charge into two sides in the combustion chamber.

Abstract Measuring the dynamic parameters of liquid fragments generated in the near-field of atomizing sprays poses a significant challenge due to the random nature of the fragments, the instability of the spray, and the limitations of current measuring technology. Precise determination of these parameters can aid in improving the control of the atomization process, which is necessary for providing suitable spray structures with appropriate flow rates and droplet size distributions for various applications such as those used in heat engines. In piston and gas turbine engines, controlling spray characteristics such as penetration, cone angle, particle size, and droplet size distribution is crucial to improve combustion efficiency and decrease exhaust emissions. This can be accomplished by adjusting the structural and/or operating parameters of the fuel supply system.

Abstract Due to the incoming phase out of fossil fuels from the market in order to reduce the carbon footprint of the automotive sector, hydrogen-fueled engines are candidate mid-term solution. Thanks to its properties, hydrogen promotes flames that poorly suffer from the quenching effects toward the engine walls. Thus, emphasis must be posed on the heat-up of the oil layer that wets the cylinder liner in hydrogen-fueled engines. It is known that motor oils are complex mixtures of a number of mainly heavy hydrocarbons (HCs); however, their composition is not known a priori. Simulation tools that can support the early development steps of those engines must be provided with oil composition and properties at operation-like conditions. The authors propose a statistical inference-based optimization approach for identifying oil surrogate multicomponent mixtures. The algorithm is implemented in Python and relies on the Bayesian optimization technique.