Search Results

The paper explores the performance characteristics of a compression ignition HYUNDAI 2.2L engine operating with Dimethyl Ether (DME). Test are carried out at three operating conditions that weigh heavily in the FTP75 certification cycle (1000rpm-12Nm, 1500rpm-50Nm, 2000rpm-100Nm). The engine features a high-pressure common rail fuel injection system designed to operate with liquified gases. The main component of the fuel system is a high-pressure pump that incorporates an electronic inlet metering valve commanded on a crank-angle base to control the rail pressure. The pump, which requires no pressure regulator, provides the flow needed to the injectors without flow returning to the inlet. This novel fueling system is leveraged in tests that are conducted to examine the impact of EGR, combustion phasing, injection pressure on efficiency and emissions. In addition, the impact of introducing 15% Propane by mass is examined.

This paper compares the results from three human factors studies conducted in a motion-based simulator in 2008, 2014 and 2023, to highlight the trends in driver's response to Forward Collision Warning (FCW). The studies were motivated by the goal to develop an effective HMI (Human-Machine Interface) strategy that enables the required driver's response to FCW while minimizing the level of annoyance of the feature. All three studies evaluated driver response to a baseline-FCW and no-FCW conditions. Additionally, the 2023 study included two modified FCW chime variants: a softer FCW chime and a fading FCW chime. Sixteen (16) participants, balanced for gender and age, were tested for each group in all iterations of the studies. The participants drove in a high-fidelity simulator with a visual distraction task (number reading). After driving 15 minutes in a nighttime rural highway environment, a surprise forward collision threat arose during the distraction task.

This work represents an advanced engineering research project partially funded by the U.S. Department of Energy (DOE). Ford Motor Company, FEV North America, and Oak Ridge National Laboratory collaborated to develop a next generation boosted spark ignited engine concept. The project goals, specified by the DOE, were 23% improved fuel economy and 15% reduced weight relative to a 2015 or newer light-duty vehicle. The fuel economy goal was achieved by designing an engine incorporating high geometric compression ratio, high dilution tolerance, low pumping work, and low friction. The increased tendency for knock with high compression ratio was addressed using early intake valve closing (EIVC), cooled exhaust gas recirculation (EGR), an active pre-chamber ignition system, and careful management of the fresh charge temperature.

The rise of greenhouse gas emissions has reached historic levels, with 37 billion tons of CO2 released into the atmosphere in 2018 alone. In the European Union, 32% of these emissions come from transportation, with 73.3% of that percentage coming from vehicles. To address this problem, solutions such as cleaner fuels and more efficient engines are necessary. Artificial Intelligence can also play a crucial role in climate analysis and verification to move towards a more sustainable future. By utilizing connected vehicle data, automakers can analyze real-time vehicle performance data to identify opportunities for improvement and reduce carbon emissions. This approach benefits the environment, improves vehicle quality, and reduces engineering work time, making it a win-win solution. Connected vehicle data offers a wealth of information on vehicle performance, such as fuel consumption and carbon emissions.

In the present work, five surrogate components (n-Hexadecane, n-Tetradecane, Heptamethylnonane, Decalin, 1-Methylnaphthalene) are proposed to represent liquid phase of diesel fuel, and another different five surrogate components (n-Decane, n-Heptane, iso-Octane, MCH (methylcyclohexane), Toluene) are proposed to represent vapor phase of diesel fuel. For the vapor phase, a 5-component surrogate chemical kinetic mechanism has been developed and validated. In the mechanism, a recently updated H2/O2/CO/C1 detailed sub-mechanism is adopted for accurately predicting the laminar flame speeds over a wide range of operating conditions, also a recently updated C2-C3 detailed sub-mechanism is used due to its potential benefit on accurate flame propagation simulation. For each of the five diesel vapor surrogate components, a skeletal sub-mechanism, which determines the simulation of ignition delay times, is constructed for species C4-Cn.

Disc brake squeal is always a challenging multidisciplinary problem in vehicle noise, vibration, and harshness (NVH) that has been extensively researched. Theoretical analysis has been done to understand the mechanism of disc brake squeal due to small disturbances. Most studies have used linear modal approaches for the harmonic vibration of large models. However, time-domain approaches have been limited, as they are restricted to specific friction models and vibration patterns and are computationally expensive. This research aims to use a time-domain approach to improve the modeling of brake squeal, as it is a dynamic instability issue with a time-dependent friction force. The time-domain approach has been successfully demonstrated through examples and data.

This paper, written in collaboration with Ford, evaluates the effectiveness of higher cell density combined with higher porosity, lower thermal mass substrates for emission control capability on a customized, RDE (Real Driving Emissions)-type of test cycle run on a chassis dynamometer using a gasoline passenger car fitted with a three-way catalyst (TWC) system. Cold-start emissions contribute most of the emissions control challenge, especially in the case of a very rigorous cold-start. The majority of tailpipe emissions occur during the first 30 seconds of the drive cycle. For the early engine startup phase, higher porosity substrates are developed as one part of the solution. In addition, further emission improvement is expected by increasing the specific surface area (GSA) of the substrate. This test was designed specifically to stress the cold start performance of the catalyst by using a short, 5 second idle time preceding an aggressive, high exhaust mass flowrate drive cycle.

Electric vehicles (EVs) are a promising and proven technology for achieving sustainable mobility with zero carbon emissions, very low noise pollution, and reducing the dependency on fossil fuels. Global EV sales have been increasing by ~110 % since 2015, with a significant rise in 2021 (~6.75 mils EV registered) mainly led by China, the US, and Europe, amplifying the EV market share to 8.3% compared to 4.2% in 2020. Future developments aimed at designing better batteries and charging technologies that reduce charging time, reduce initial battery cost, and increased flexibility. In India, EVs are emerging significantly due to stringent Carbon di Oxide (CO2) reduction drives, increasing crude oil prices, and the availability of cheaper renewable energy. Leveraging government promotional policies, evolving the entire ecosystem, globally advantageous manufacturing costs, and competitive engineering skills form the perfect blend for India.

This study investigated the potential of generating reactive chemical species (including radicals) through pilot fuel injection in negative valve overlap for improving the combustion and emissions performances of spark ignition gasoline engines under low load and low speed operating conditions. Several Ford sub-models were used for simulating the physics and chemistry processes of injecting a small amount of fuel in NVO (negative valve overlap). Effects of different NVO degrees and different pilot injection timings, factors for fuel conversion were simulated and investigated. CO and H2 conversions during NVO, CO and H2 amounts before spark timing were used for comparing different schemes.

Gasoline compression ignition using a single gasoline-type fuel has been shown as a method to achieve low-temperature combustion with low engine-out NOx and soot emissions and high indicated thermal efficiency. However, key technical barriers to achieving low temperature combustion on multi-cylinder engines include the air handling system (limited amount of exhaust gas recirculation) as well as mechanical engine limitations (e.g. peak pressure rise rate). In light of these limitations, high temperature combustion with reduced amounts of exhaust gas recirculation appears more practical. Furthermore, for high temperature Gasoline compression ignition, an effective aftertreatment system allows high thermal efficiency with low tailpipe-out emissions. In this work, experimental testing was conducted on a 12.4 L multi-cylinder heavy-duty diesel engine operating with high temperature gasoline compression ignition combustion using EEE gasoline.

In order to decarbonize and lower the overall emissions of the transport sector, immediate and cost-effective powertrain solutions are needed. Natural gas offers the advantage of a direct reduction of carbon dioxide (CO2) emissions due to its better Carbon to Hydrogen ratio (C/H) compared to common fossil fuels, e.g. gasoline or diesel. Moreover, an optimized engine design suiting the advantages of natural gas in knock resistance and lean mixtures keeping in mind the challenges of power density, efficiency and cold start manoeuvres. In the public funded project MethMag (Methane lean combustion engine) a gasoline fired three-cylinder-engine is redesigned based on this change of requirements and benchmarked against the previous gasoline engine.

A more accurate combustion model, based on Fluent simulations including the effect of flame stretching and extinction, has been added to cycle and road simulations of an Adaptive Cycle Engine (ACE), where compressions and expansions do not follow a predefined sequence. Also, engine speed data from the Argonne Downloadable Dynamometer Database is used in the road simulations in lieu of the original constant-speed model. Results show a drop in predicted steady-state brake efficiency and bmep around 15% relative to the model using a standard Wiebe function for heat release rate. Performance on road cycles is not greatly affected by the delayed combustion since the relationship between expansion mass and work is largely unchanged. Even with the refined model, future ACE-equipped vehicles are expected to be competitive with electric powertrains in pre-tax cost and overall emissions.

This paper analyzes the use of an ammonia sensor for feedback control in diesel exhaust systems. We build our case around the specific example of the heavy duty transient cycle, and an exhaust system with an SCR catalyst, a single urea injector and an upstream and downstream NOx sensor. A key component in our analysis is the inclusion of the tolerance of the ammonia sensor. We show that with the current understanding of the sensor tolerance, the ammonia sensor has limited benefit for controls.

This paper presents a method of using CAE to determine the pre-load and torque applied to a U-Bolt rear Spring Seat. In this paper it is review two U-bolt design and the stresses generated by the pre-load torque applied, based in this study a process to determine the minimal preload and the torque is discussed. By this process it is possible to determine the minimum Torque and the correct pre-load in the U-Bolt element and assuring the correct fastening of the components avoiding over stress in the Bar elements.

The automotive industry is passing for a big transformation, due to technologies advance. The electrical technologies are also on a good rising curve, calling the attention of the Original Equipment Manufacturer (OEMs). This scenario generates the demand for a faster method to train their new hired engineers, when compared with usual on the job training. Model in the Loop (MiL) consists in one of the real-time embedded systems test phases, which is developed in a computational environment, performing a mathematical modeling of the system, presenting an interface that allows the visualization of its dynamics and the signals involved. Two powerful software in industry that apply MiL are the Matlab and Simulink. A project involving these applications was proposed for a team of new hired engineers, developing models of several vehicle Electronic Control Units (ECUs), with some scope reduction as an example the functional requirements reduction.

A novel surrogate model is presented, which predicts the engine-out Particle Number (PN) emissions of a light-duty, spray-guided, turbo-charged, GDI engine. The model is developed through extensive CFD analysis, carried out using the Siemens Simcenter STAR-CD, and considers a range of part-load operating conditions and single-variable sweeps where control parameters such as start of injection and injection pressure are varied in isolation. The work is attached to the Ford-led APC6 DYNAMO project, which aims to improve efficiency and reduce harmful emissions from the next generation of gasoline engines. The CFD work focused on the air exchange, fuel spray and mixture preparation stages of the engine cycle. A combined Rosin-Rammler and Reitz-Diwakar model, calibrated over a wide range of injection pressure, is used to model fuel atomization and secondary droplets break-up.

As the world searches for ways to reduce humanity’s impact on the environment, the automotive industry looks to extend the viable use of the gasoline engine by improving efficiency. One way to improve engine efficiency is through more effective control. Torque-based control is critical in modern cars and trucks for traction control, stability control, advanced driver assistance systems, and autonomous vehicle systems. Closed loop torque-based engine control systems require feedback signal(s); indicated mean effective pressure (IMEP) is a useful signal but is costly to measure directly with in-cylinder pressure sensors. Previous work has been done in torque and IMEP estimation using crankshaft acceleration and ion sensors, but these systems lack accuracy in some operating ranges and the ability to estimate cycle-cycle variation.

The work presented here is part of the research done in the field of voice biometrics. This paper helps to understand the state-of-the-art in speaker recognition technology potentially capable of solving challenges related to speaker identification (to identify a speaker among multiple speakers) and speaker verification/authentication (to recognize the current speaking person at a pre-defined access level and authenticate accordingly). The research was focused on performing an unbiased evaluation of two individual voice biometric services. The level of accuracy in identifying and authenticating individuals using these services provides an insight into the current state of technology and the state of what other dual authentication methods could be used to achieve a desired True Acceptance Rate (TAR) and False Acceptance Rates (FAR).

This work focuses on reducing the computational effort of a 0-dimensional combustion model developed for compression ignition engines operating on gasoline-like fuels. As in-cylinder stratification significantly contributes to the ignition delay, which in turn substantially influences the entire gasoline compression ignition combustion process, previous modeling efforts relied on the results of a 1-dimensional spray model to estimate the in-cylinder fuel stratification. Insights obtained from the detailed spray model are leveraged within this approach and applied to a reduced order model describing the spray propagation. Using this computationally efficient combustion model showed a reduction in simulation time by three orders of magnitude for an entire engine cycle over the combustion model with the 1-dimensional spray model.

In an Adaptive Cycle Engine (ACE), thermodynamics favors combustion starting while the compressed, premixed air and fuel are still flowing into the cylinder through the transfer valve. Since the flow velocity is typically high and is predicted to reach sonic conditions by the time the transfer valve closes, the flame might be subjected to extensive stretch, thus leading to aerodynamic quenching. It is also unclear whether a single spark, or even a succession of sparks, will be sufficient to achieve complete combustion. Given that the first ACE prototype is still being built, this issue is addressed by numerical simulation using the G-equation model, which accounts for the effect of flame stretching, over a 3D domain representing a flat-piston ACE cylinder, both with inward- and outward-opening valves. A k-epsilon turbulence model was used for the highly turbulent flow field.