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Testing of ducted fuel injection (DFI) in a single-cylinder engine with production-like hardware previously showed that adding a duct structure increased soot emissions at the full load, rated speed operating point [1]. The authors hypothesized that the DFI flame, which travels faster than a conventional diesel combustion (CDC) flame, and has a shorter distance to travel, was being re-entrained into the on-going fuel injection around the lift-off length (LOL), thus reducing air entrainment into the on-going injection. The engine operating condition and the engine combustion chamber geometry were duplicated in a constant pressure vessel. The experimental setup used a 3D piston section combined with a glass fire deck allowing for a comparison between a CDC flame and a DFI flame via high-speed imaging. CH* imaging of the 3D piston profile view clearly confirmed the re-entrainment hypothesis presented in the previous engine work.

Ducted fuel injection (DFI), a concept that utilizes fuel injection through ducts, was implemented in a constant pressure High Temperature Pressure Vessel at 60 bar ambient pressure, 800-1000 K ambient temperature, and 21 % oxygen. The ducts were 14 mm long and placed 3-4.7 mm from the orifice exit. The duct diameters ranged from 1.6-3.2 mm and had a rounded inlet and a tapered outlet. Diesel fuel was used in single-orifice fuel injectors operating at 250 MPa rail pressure. The objective of this work was to study soot reduction for various combinations of orifice and duct diameters. A complete data set was taken using the 150 μm orifice. A smaller data set was acquired for a 219 μm orifice, showing similar trends. Soot reduction peaked at an optimal duct diameter of 2-2.25 mm, corresponding to an 85-90 % spray area reduction for the 150 μm orifice. Smaller or larger duct diameters were less effective. Duct diameter had a minimal effect on ignition delay.

An improved method for studying mixing-controlled compression ignition (MCCI) flame interactions with an engine combustion chamber has been developed. It is implemented in a constant pressure vessel, which contains a portion of a piston and a portion of a cylinder head, where the cylinder head is emulated by a transparent fused silica window. This method allows for vaporizing or combusting fuel jets to be imaged from two orthogonal directions. The piston and cylinder head can be adjusted to emulate in-engine piston positions from top dead center (TDC) to approximately 15 mm away from TDC. The design allows for pistons from engine bore sizes up to approximately 175 mm to be studied, including the ability to simulate injector spray included angles from 120°-180°. In this study, the piston was made as an extruded piston bowl profile, where the length of the extrusion approximated the arc length between two neighboring jets from a 6-hole injector.

The study of spray-wall interaction is of great importance to understand the dynamics during fuel-surface impingement process in modern internal combustion engines. The identification of droplet post-impingement pattern (contact, transition, non-contact) and droplet characteristics can quantitatively provide an estimation of energy transfer for spray-wall interaction, thus further influencing air-fuel mixing and emissions under combusting conditions. Theoretical criteria of single droplet post-impingement pattern on a dry wall have been experimentally and numerically studied by many researchers to quantify the hydrodynamic droplet behaviors. However, apart from model fidelity, another issue is the scalability. A theoretical criterion developed from one case might not be well suited to another scenario. In this paper, a data-driven approach for single droplet-dry wall post-impingement pattern utilizing arithmetical machine learning classification methods is proposed and demonstrated.

Off road navigation demands ground robots to traverse complex and often changing terrain. Classification and assessment of terrain can improve path planning strategies by reducing travel time and energy consumption. In this paper we introduce a terrain classification and assessment framework that relies on both exteroceptive and proprioceptive sensor modalities. The robot captures an image of the terrain it is about to traverse and records corresponding vibration data during traversal. These images are manually labelled and used to train a support vector machine (SVM) in an offline training phase. Images have been captured under different lighting conditions and across multiple locations to achieve diversity and robustness to the model. Acceleration data is used to calculate statistical features that capture the roughness of the terrain whereas angular velocities are used to calculate roll and pitch angles experienced by the robot.

The study of spray-wall interaction is of great importance to understand the dynamics that occur during fuel impingement onto the chamber wall or piston surfaces in internal combustion engines. It is found that the maximum spreading length of an impinged droplet can provide a quantitative estimation of heat transfer and energy transformation for spray-wall interaction. Furthermore, it influences the air-fuel mixing and hydrocarbon and particle emissions at combusting conditions. In this paper, an analytical model of a single diesel droplet impinging on the wall with different inclined angles (α) is developed in terms of βm (dimensionless maximum spreading length, the ratio of maximum spreading length to initial droplet diameter) to understand the detailed impinging dynamic process.

The proliferation of small silicon micro-chips has led to a large assortment of low-cost transducers for data acquisition. Production vehicles on average exploit more than 60 on board sensors, and that number is projected to increase beyond 200 per vehicle by 2020. Such a large increase in sensors is leading the fourth industrial revolution of connectivity and autonomy. One major downfall to installing many sensors is compromises in their accuracy and processing power due to cost limitations for high volume production. The same common errors in data acquisition such as sampling, quantization, and multiplexing on the CAN bus must be accounted for when utilizing an entire array of vehicle sensors. A huge advantage of onboard sensors is the ability to calculate vehicle parameters during a daily drive cycle to update ECU calibration factors in real time. One such parameter is driveline damping, which changes with gear state and drive mode. A damping value is desired for every gear state.

Automotive exhaust noise is one of the major sources of noise pollution and it is controlled by passive control system (mufflers) and active control system (loudspeakers and active control algorithm). Mufflers are heavy, bulky and large in size while loudspeakers have a working temperature limitation. Carbon nanotube (CNT) speakers generate sound due to the thermoacoustic effect. CNT speakers are also lightweight, flexible, have acoustic and light transparency as well as high operating temperature. These properties make them ideal to overcome the limitations of the current exhaust noise control systems. An enclosed, coaxial CNT speaker is designed for exhaust noise cancellation application. The development of a 3D multi-physics (coupling of electrical, thermal and acoustical domains) model, for the coaxial speaker is discussed in this paper. The model is used to simulate the sound pressure level, input power versus ambient temperature and efficiency.

Continuing research introduced at the 2018 WCX conference, this paper shows the result of simulations where a midsize sedan (1700 kg) fitted with an adaptive cycle engine and a CVT is operated over three standard duty cycles: US06, UDDS, and HWFET, and compared with the results obtained from other engine cycles installed on the same vehicle. Four different engine cycles are compared: conventional 4-stroke, 6-stroke cycle with no air storage, 6-stroke cycle with air storage, and fully adaptive cycle with air storage and a number of strokes determined by instantaneous demand and state of charge of the storage tank. Results show that the fully adaptive engine achieves a better mileage in all scenarios, closely followed by the partially adaptive 6-stroke cycle with storage. Gains over a conventional 4-stroke powerplant range from 3.4 mpg on the HWFET cycle, to 7.6 mpg on the UDDS cycle.

Fuel spray-wall interaction frequently occurs on intake manifold wall in the port fuel injection engine and on the piston in the direct injection engine, especially during the cold start. The heat transfer between the spray and wall is involved in this interaction process and influences the dynamics of the impinged spray which can further affect the engine performance. The physics of impact dynamics of a single droplet serves as a fundamental for better comprehension of spray impingement. In our previous studies, we have focused on diesel droplets, at ambient temperature, impinging on both heated and non-heated wall and found impinged droplet morphology differences. To understand the effect of heat transfer and thermophysical properties on dynamics of droplet-wall interaction better, droplet temperature variation was introduced in this study. Therefore, different conditions were framed to explore the impact of thermophysical properties of the droplet.

The Society of Automotive Engineers Fatigue Design & Evaluation Committee [SAE FD&E] is actively working on a total life project for weldments, in which the welding residual stress is a key contributor to an accurate assessment of fatigue life. Physics-based welding process simulation and various types of residual stress measurements were pursued to provide a representation of the residual stress field at the failure location in the fatigue samples. A well-controlled and documented robotic welding process was used for all sample fabrications to provide accurate inputs for the welding simulations. One destructive (contour method) residual stress measurement and several non-destructive residual stress measurements-surface X-ray diffraction (XRD), energy dispersive X-ray diffraction (EDXRD), and neutron diffraction (ND)-were performed on the same or similarly welded samples.

The increase in computational power in recent times has led to multidimensional computational fluid dynamics (CFD) modeling tools being used extensively for optimizing the diesel engine piston design. However, it is still common practice in engine CFD modeling to use constant uniform boundary temperatures. This is either due to the difficulty in experimentally measuring the component temperatures or the lack of measurements when simulation is being used predictively. This assumption introduces uncertainty in heat flux predictions. Conjugate heat transfer (CHT) modeling is an approach used to predict the component temperatures by simultaneously modeling the heat transfer in the fluid and the solid phase. However, CHT simulations are computationally expensive as they require more than one engine cycle to be simulated to converge to a steady cycle-averaged component temperature.

An over-expanded spark ignited engine was investigated in this work via engine simulation with a design constrained, mechanically actuated Atkinson cycle mechanism. A conventional 4-stroke spark-ignited turbo-charged engine with a compression ratio of 9.2 and peak brake mean effective pressure of 22 bar was selected for the baseline engine. With geometry and design constraints including bore, stroke, compression ratio, clearance volume at top dead center (TDC) firing, and packaging, one over-expanded engine mechanism with over expansion ratio (OER) of 1.5 was designed. Starting with a validated 1D engine simulation model which included calibration of the in-cylinder heat transfer model and SI turbulent combustion model, investigations of the Atkinson engine including cam optimization was studied. The engine simulation study included the effects of offset of piston TDC locations as well as different durations of the 4-strokes due to the mechanism design.

Traditionally, internal combustion engines follow thermodynamic cycles comprising a fixed number of crank revolutions, in order to accommodate compression of the incoming air as well as expansion of the combustion products. With the advent of computer-controlled valve trains, we now have the possibility of detaching compression from expansion events, thus achieving an “adaptive cycle” molded to the performance required of the engine at any given time. The adaptive cycle engine differs from split-cycle engines in that all phases of the cycle take place within the same cylinder, so that in an extreme case the gas contained in all cylinders can be undergoing expansion events, resulting in a large increase in power density over the conventional four-stroke and two-stroke cycles. Key to the adaptive cycle is the addition of a variable-timing “transfer” valve to each cylinder, plus a space for air storage between compression and expansion events.

Mandated pollutant emission levels are shifting light-duty vehicles towards hybrid and electric powertrains. Heavy-duty applications, on the other hand, will continue to rely on internal combustion engines for the foreseeable future. Hence there remain clear environmental and economic reasons to further decrease IC engine emissions. Turbocharged diesels are the mainstay prime mover for heavy-duty vehicles and industrial machines, and transient performance is integral to maximizing productivity, while minimizing work cycle fuel consumption and CO2 emissions. 1D engine simulation tools are commonplace for “virtual” performance development, saving time and cost, and enabling product and emissions legislation cycles to be met. A known limitation however, is the predictive capability of the turbocharger turbine sub-model in these tools.

An accurate estimation of cycle-by-cycle in-cylinder mass and the composition of the cylinder charge is required for spark-ignition engine transient control strategies to obtain required torque, Air-Fuel-Ratio (AFR) and meet engine pollution regulations. Mass Air Flow (MAF) and Manifold Absolute Pressure (MAP) sensors have been utilized in different control strategies to achieve these targets; however, these sensors have response delay in transients. As an alternative to air flow metering, in-cylinder pressure sensors can be utilized to directly measure cylinder pressure, based on which, the amount of air charge can be estimated without the requirement to model the dynamics of the manifold.

This paper aims to extend the existing Volume of Fluid (VOF) model by implementing an evaporation sub-model in an open source Computational Fluid Dynamics (CFD) software, OpenFOAM. The paper applies the new model to numerically study the evaporation of spherical n-heptane droplets impinging on a hot wall at atmospheric pressure and a temperature above the Leidenfrost temperature. Volume of Fluid (VOF) method is chosen to track the liquid gas interface and the capability of VOF method implemented in interDyMFoam solver of OpenFOAM to simulate hydrodynamics during droplet-droplet interaction and droplet-film interaction is explored. Firstly, the in-built solver is used to simulate problems in isothermal conditions and the simulation results are compared qualitatively with the published results to validate the solver. A numerical method for modeling heat and mass transfer during evaporation is implemented in conjunction with the VOF.

Today’s business climate and economy demand new, innovative strategies from the initial kickoff of research and development - to the mining of ore from the earth - to the final inspection of a finished product in a mid-western factory. From startup companies with two employees to the largest companies, the world faces new and challenging requirements every day. The demands from companies, customers, executives, and shareholders continue to drive for higher outputs with more efficient use of personnel and investments. Fortunately, the rate of technology continues to exponentially accelerate, which allows those at the cutting edge of technology to capitalize. Caterpillar has been a pioneer in advanced technology since its inception and has been developing the foundation for autonomy over the past four decades.

China has become the world’s largest vehicle market in terms of sales volume. Automobiles sales keep growing in recent years despite the declining economic growth rate. Due to the increasing attention given to the environmental impact, more stringent emission regulations are being drafted to control traditional internal combustion engine emissions. In order to reduce vehicle emissions, environmentally-friendly new-energy vehicles, such as electric vehicles and plug-in hybrid vehicles, are being promoted by government policies. The Chinese government plans to boost sales of new-energy cars to account for about five percent of China’s total vehicle sales. It is well known that more electric and electronic components will be integrated into a vehicle platform during vehicle electrification.

It is beneficial but challenging to operate spark-ignition engines under highly lean and dilute conditions. The unstable ignition behavior can result in downgraded combustion performance in engine cylinders. Numerical approach is serving as a promising tool to identify the ignition requirements by providing insight into the complex physical/chemical phenomena. An effort to simulate the early stage of flame kernel initiation in lean and dilute fuel/air mixture has been made and discussed in this paper. The simulations are set to validate against laboratory results of spark ignition behavior in a constant volume combustion vessel. In order to present a practical as well as comprehensive ignition model, the simulations are performed by taking into consideration the discharge circuit analysis, the detailed reaction mechanism, and local heat transfer between the flame kernel and spark plug.