Search Results

The Cooperative Automotive Research for Advanced Technology (CARAT) program is designed to accelerate the commercialization of innovative technologies that will overcome barriers to achieving the goals of the Partnership for a New Generation of Vehicles Program. Aimed at harnessing the creativity and capabilities of American small businesses and colleges and universities, this unique technology R&D program seeks to develop and bring advanced technologies into use in production vehicles at a faster rate. CARAT's focus is developing and commercializing technology that overcomes key technical barriers preventing the production of vehicles with ultra-high fuel efficiency. CARAT begins with technologies that already have a firm technical basis and, through a unique three-stage process, ends with fully validated technologies ready for mass production. The program is open to all U.S. entrepreneurs and small businesses, colleges, and universities.

It is widely understood that cold ambient temperatures increase vehicle fuel consumption due to heat transfer losses, increased friction (increased viscosity lubricants), and enrichment strategies (accelerated catalyst heating). However, relatively little effort has been dedicated to thoroughly quantifying these impacts across a large set of real world drive cycle data and ambient conditions. This work leverages experimental dynamometer vehicle data collected under various drive cycles and ambient conditions to develop a simplified modeling framework for quantifying thermal effects on vehicle energy consumption. These models are applied over a wide array of real-world usage profiles and typical meteorological data to develop estimates of in-use fuel economy. The paper concludes with a discussion of how this integrated testing/modeling approach may be applied to quantify real-world, off-cycle fuel economy benefits of various technologies.

Cavitation plays an important role in fuel injection systems. It alters the nozzle's internal flow structure and discharge coefficient, and also contributes to injector wear. Quantitatively measuring and mapping the cavitation vapor distribution in a fuel injector is difficult, as cavitation occurs on very short time and length scales. Optical measurements of transparent model nozzles can indicate the morphology of large-scale cavitation, but are generally limited by the substantial amount of scattering that occurs between vapor and liquid phases. These limitations can be overcome with x-ray diagnostics, as x-rays refract, scatter and absorb much more weakly from phase interfaces. Here, we present an overview of some recent developments in quantitative x-ray diagnostics for cavitating flows. Measurements were conducted at the Advanced Photon Source at Argonne National Laboratory, using a submerged plastic test nozzle.

While sulfur in diesel fuels helps reduce friction and prevents wear and galling in fuel pump and injector systems, it also creates environmental pollution in the form of hazardous particulates and SO2 emissions. The environmental concern is the driving force behind industry's efforts to come up with new alternative approaches to this problem. One such approach is to replace sulfur in diesel fuels with other chemicals that would maintain the antifriction and antiwear properties provided by sulfur in diesel fuels while at the same time reducing particulate emissions. A second alternative might be to surface-treat fuel injection parts (i.e., nitriding, carburizing, or coating the surfaces) to reduce or eliminate failures associated with the use of low-sulfur diesel fuels. Our research explores the potential usefulness of a near-frictionless carbon (NFC) film developed at Argonne National Laboratory in alleviating the aforementioned problems.

The addition of metal nanoparticles to standard coolant fluids dramatically increases the thermal conductivity of the liquid. The properties of the prepared nanofluids will allow for lighter, smaller, and higher efficiency spacecraft thermal control systems to be developed. Nanofluids with spherical or rod-shaped metal nanoparticles were investigated. At a volume concentration of 0.5%, the room temperature thermal conductivity of a 2 nm spherical gold nanoparticle-water solution was increased by more than 10% over water alone. Silver nanorods increased the thermal conductivity of ethylene glycol by 53% and water by 26%.

Applying nanotechnology to thermal engineering, ANL has addressed the interesting and timely topic of nanofluids. We have developed methods for producing both oxide and metal nanofluids, studied their thermal conductivity, and obtained promising results: (1) Stable suspensions of nanoparticles can be achieved. (2) Nanofluids have significantly higher thermal conductivities than their base liquids. (3) Measured thermal conductivities of nanofluids are much greater than predicted. For these reasons, nanofluids show promise for improving the design and performance of vehicle thermal management systems. However, critical barriers to further development and application of nanofluid technology are agglomeration of nanoparticles and oxidation of metallic nanoparticles. Therefore, methods to prevent particle agglomeration and degradation are required.

Model-based control system design improves quality, shortens development time, lowers engineering cost, and reduces rework. Evaluating a control system's performance, functionality, and robustness in a simulation environment avoids the time and expense of developing hardware and software for each design iteration. Simulating the performance of a design can be straightforward (though sometimes tedious, depending on the complexity of the system being developed) with mathematical models for the hardware components of the system (plant models) and control algorithms for embedded controllers. This paper describes a software tool and a methodology that not only allows a complete system simulation to be performed early in the product design cycle, but also greatly facilitates the construction of the model by automatically connecting the components and subsystems that comprise it.

Many of today's automotive control system simulation tools are suitable for simulation, but they provide rather limited support for model building and management. Setting up a simulation model requires more than writing down state equations and running them on a computer. The role of a model library is to manage the models of physical components of the system and allow users to share and easily reuse them. In this paper, we describe how modern software techniques can be used to support modeling and design activities; the objective is to provide better system models in less time by assembling these system models in a “plug-and-play” architecture. With the introduction of hybrid electric vehicles, the number of components that can populate a model has increased considerably, and more components translate into more possible drivetrain configurations. To address these needs, we explain how users can simulate a large number of drivetrain configurations.

In an effort to reduce fuel consumption and emissions, hybrid vehicles incorporating fuel cell systems are being developed by automotive manufacturers, their suppliers, federal agencies (specifically, the U.S. Department of Energy) and national laboratories. The fuel cell system will require an air management subsystem that includes a compressor/expander. Certain components in the compressor will require innovative lubrication technology in order to reduce parasitic energy losses and improve their reliability and durability. One such component is the air bearing for air turbocompressors designed and fabricated by Meruit, Inc. Argonne National Laboratory recently developed a carbon-based coating with low friction and wear attributes; this near-frictionless-carbon (NFC) coating is a potential candidate for use in turbocompressor air bearings. We presents here an evaluation of the Argonne coating for air compressor thrust bearings.

This paper focuses on detailed numerical simulations of direct injection diesel and gasoline sprays from production grade, multi-hole injectors. In a dual-fuel engine the direct injection of both the fuels can facilitate appropriate mixture preparation prior to ignition and combustion. Diesel and gasoline sprays were simulated using high-fidelity Large Eddy Simulations (LES) with the dynamic structure sub-grid scale model. Numerical predictions of liquid penetration, fuel density distribution as well as transverse integrated mass (TIM) at different axial locations versus time were compared against x-ray radiography data obtained from Argonne National Laboratory. A necessary, but often overlooked, criterion of grid-convergence is ensured by using Adaptive Mesh Refinement (AMR) for both diesel and gasoline. Nine different realizations were performed and the effects of random seeds on spray behavior were investigated.

Argonne National Laboratory (ANL) researchers have embarked on an ambitious program to quantitatively demonstrate the potential of hydrogen as a fuel for internal combustion engines (ICEs) in hybrid-electric vehicle applications. In this initiative, ANL researchers need to investigate different hybrid configurations, different levels of hybridization, and different control strategies to evaluate their impacts on the potential of hydrogen ICEs in a hybrid system. Because of limitations in the choice of motor and battery hardware, a common practice is to fix the size of the battery and motor, depending on the hybrid configuration (starter/alternator, mild hybrid, or full hybrid) and to tune the system control for the above-available electrical power/energy. ANL has developed a unique, flexible, Hardware-In-the-Loop (HIL) platform for advanced powertrain technology evaluation: The Mobile Advanced Technology Testbed (MATT).

Given the importance of the fuel-injection process on the combustion and emissions performance of gasoline direct injected engines, there has been significant recent interest in understanding the fluid dynamics within the injector, particularly around the needle and through the nozzles. The pressure losses and transients that occur in the flow passages above the needle are also of interest. Simulations of these injectors typically use the nominal design geometry, which does not always match the production geometry. Computed tomography (CT) using x-ray and neutron sources can be used to obtain the real geometry from production injectors, but there are trade-offs in using these techniques. X-ray CT provides high resolution, but cannot penetrate through the thicker parts of the injector. Neutron CT has excellent penetrating power but lower resolution.

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.

Hybrid electric vehicles (HEVs) may have key fuel economy and emissions advantages over current conventional vehicles, but they have drawbacks such as frequent engine starts that can slow down market penetration of HEVs. First, the hydrocarbon emissions due to the numerous engine starts would make newly developed HEV powertrains even more demanding on the emission control system. Second, frequent starts may make the engine deteriorate quickly. This study is an attempt to gain a better understanding of the engine start characteristics of two limited-production HEVs (Toyota Prius and Honda Insight). Using fast-response (5 ms) hydrocarbon and NO (nitric oxide) analyzers, the transient emissions were measured in the engine exhaust ports during cold and hot engine starts. On the basis of the experimental findings, several recommendations were made to improve performance and emissions of future HEVs.

The application of polyalkylene glycol (PAG) as a base stock for engine oil formulation has been explored for substantial fuel economy gain over traditional formulations with mineral oils. Various PAG chemistries were explored depending on feed stock material used for manufacturing. All formulations except one have the same additive package. The friction performance of these oils was evaluated in a motored single cylinder engine with current production engine hardware in the temperature range 40°C-120°C and in the speed range of 500 RPM-2500 RPM. PAG formulations showed up to 50% friction reduction over GF-5 SAE 5W-20 oil depending on temperature, speed, and oil chemistry. Friction evaluation in a motored I-4 engine showed up to 11% friction reduction in the temperature range 40°C-100°C over GF-5 oil. The paper will share results on ASTM Sequence VID fuel economy, Sequence IVA wear, and Sequence VG sludge and varnish tests. Chassis roll fuel economy data will also be shared.

When compared with new oil, used diesel engine oils exhibited thermal conductivity that increases as the concentration of soot increases. The magnitude of the effect depends on the oil composition, and on the size and dispersion of the soot particles. Although soot in engine oil is generally deleterious to engine performance from the standpoint of wear and deposits, no negative effects were observed on the thermal performance of the oil itself; indeed, even slight positive effects are expected for oils that maintain soot in stable dispersion. Therefore, the thermal challenge for engine oils in diesel engines that use exhaust gas recirculation will be to prevent soot deposition on engine surfaces.

Mobile source emissions standards are becoming more stringent and particulate emissions from gasoline direct injection (GDI) engines represent a particular challenge. Gasoline particulate filter (GPF) is deemed as one possible technical solution for particulate emissions reduction. In this work, a study was conducted on eight formulations of lubricants to determine their effect on GDI engine particulate emissions and GPF performance. Accelerated ash loading tests were conducted on a 2.4L GDI engine with engine oil injection in gasoline fuel by 2%. The matrix of eight formulations was designed with changing levels of sulfated ash (SASH) level, Zinc dialkyldithiophosphates (ZDDP) level and detergent type. Comprehensive evaluations of particulates included mass, number, size distribution, composition, morphology and soot oxidation properties. GPF performance was assessed through filtration efficiency, back pressure and morphology.

This study is a continuation of previous work assessing the robustness of a Cummins XPI common rail injection system operating with gasoline-like fuel. All the hardware from the original study was retained except for the high pressure pump head and check valves which were replaced due to cavitation damage. An additional 400 hour NATO cycle was run on the refurbished fuel system to achieve a total exposure time of 800 hours and detect any other significant failure modes. As in the initial investigation, fuel system parameters including pressures, temperatures and flow rates were logged on a test bench to monitor performance over time. Fuel and lubricant samples were taken every 50 hours to assess fuel consistency, metallic wear, and interaction between fuel and oil. High fidelity driving torque and flow measurements were made to compare overall system performance when operating with both diesel and light distillate fuel.

In an earlier paper, the authors described how Model-Based System Engineering could be utilized to provide a virtual Hardware-in-the-Loop simulation capability, which creates a framework for the development of virtual ECU software by providing a platform upon which embedded control algorithms may be developed, tested, updated, and validated. The development of virtual ECU software is increasingly valuable in automotive control system engineering because vehicle systems are becoming more complex and tightly integrated, which requires that interactions between subsystems be evaluated during the design process. Variational analysis and robustness studies are also important and become more difficult to perform with real hardware as system complexity increases. The methodology described in this paper permits algorithm development to be performed prior to the availability of vehicle and control system hardware by providing what is essentially a virtual integration vehicle.

As batteries become a major component of numerous advanced vehicles, significant efforts have been allocated towards characterizing and estimating battery energy capability over the lifetime of a vehicle. Currently, battery State of Charge (SOC) is one of the primary values used for this characterization; however SOC usage has several issues when implemented in Electric Vehicle (EV), Hybrid Electric Vehicle (HEV), and Plug-In Hybrid Electric Vehicle (PHEV) systems. One of the main issues with reporting battery SOC as a characterization of battery energy capability is that it only gives a percentage of the energy available to the operator. SOC does not accurately represent the true capability or capacity of the battery, and thus fails to account for the impact to capability with respect to battery size, age, and recent operational history.