Search Results

OBD system requirements were first developed by the California Air Resources Board, the U.S. Environmental Protection Agency, and the European Commission. New OBD requirements should be as consistent as possible with existing requirements to maximize reliability and to minimize system complexity, proliferation of configurations, and consumer cost. New OBD requirements from around the world are briefly reviewed and most are consistent with the original U.S. and European requirements. Worldwide OBD requirements are being further harmonized under the United Nations, Economic Commission for Europe, World Forum for Harmonization of Vehicle Regulations (WP29). Presenter David H. Ferris, General Motors Company

Plug-In Hybrid and Extended Range Electric Vehicle's have quickly become the focus of many OEM's and suppliers. Existing regulations and test procedures did not anticipate this rapid adoption of this new technology, resulting in many product development challenges. The lack of clear requirements is further complicated by CARBs consideration of CO2 inclusion in their next light duty OBD regulation. This presentation provides an overview of the regulatory requirements for OBD systems on hybrid vehicles that intend to certify in California. Near term challenges for EREV?s and PHEV?s are discussed, including concerns with the existing denominator and warm-up cycle calculations. Some proposals are made to address these concerns. Presenter Andrew Zettel, General Motors Company

A combination of laboratory reactor measurements and vehicle FTP testing has been combined to demonstrate a method for diagnosing the formation of NO2 from a diesel oxidation catalyst (DOC). Using small cores from a production DOC and simulated diesel exhaust, the laboratory reactor experiments are used to support a model for DOC chemical reaction kinetics. The model we propose shows that the ability to produce NO2 is chemically linked to the ability of the catalyst to oxidize hydrocarbon (HC). For thermally damaged DOCs, loss of the HC oxidation function is simultaneous with loss of the NO2 production function. Since HC oxidation is the source of heat generated in the DOC under regeneration conditions, we conclude that a diagnostic of the DOC exotherm is able to detect the failure of the DOC to produce NO2. Vehicle emissions data from a 6.6 L Duramax HD pick-up with DOC of various levels of thermal degradation is provided to support the diagnostic concept.

High pressure diesel sprays were visualized under vaporizing and combusting conditions in a constant-volume combustion vessel. Near-simultaneous visualization of vapor and liquid phase fuel distribution were acquired using a hybrid shadowgraph/Mie-scattering imaging setup. This imaging technique used two pulsed LED's operating in an alternative manner to provide proper light sources for both shadowgraph and Mie scattering. In addition, combustion cases under the same ambient conditions were visualized through high-speed combustion luminosity measurement. Two single-hole diesel injectors with same nozzle diameters (100μm) but different k-factors (k0 and k1.5) were tested in this study. Detailed analysis based on spray penetration rate curves, rate of injection measurements, combustion indicators and 1D model comparison have been performed.

Since transient vehicle HVAC computational fluids (CFD) simulations take too long to solve in a production environment, the goal of this project is to automatically create a lumped-parameter flow network from a steady-state CFD that solves nearly instantaneously. The data mining algorithm k-means is implemented to automatically discover flow features and form the network (a reduced order model). The lumped-parameter network is implemented in the commercial thermal solver MuSES to then run as a fully transient simulation. Using this network a “localized heat transfer coefficient” is shown to be an improvement over existing techniques. Also, it was found that the use of the clustering created a new flow visualization technique. Finally, fixing clusters near equipment newly demonstrates a capability to track localized temperatures near specific objects (such as equipment in vehicles).

Cavitation plays a significant role in high pressure diesel injectors. However, cavitation is difficult to measure under realistic conditions. X-ray phase contrast imaging has been used in the past to study the internal geometry of fuel injectors and the structure of diesel sprays. In this paper we extend the technique to make in-situ measurements of cavitation inside unmodified diesel injectors at pressures of up to 1200 bar through the steel nozzle wall. A cerium contrast agent was added to a diesel surrogate, and the changes in x-ray intensity caused by changes in the fluid density due to cavitation were measured. Without the need to modify the injector for optical access, realistic injection and ambient pressures can be obtained and the effects of realistic nozzle geometries can be investigated. A range of single and multi-hole injectors were studied, both sharp-edged and hydro-ground. Cavitation was observed to increase with higher rail pressures.

This paper presents a combined numerical and experimental investigation of the characteristics of spark discharge in a spark-ignition engine. The main objective of this work is to gain insights into the spark discharge process and early flame kernel development. Experiments were conducted in an inert medium within an optically accessible constant-volume combustion vessel. The cross-flow motion in the vessel was generated using a previously developed shrouded fan. Numerical modeling was based on an existing discharge model in the literature developed by Kim and Anderson. However, this model is applicable to a limited range of gas pressures and flow fields. Therefore, the original model was evaluated and improved to predict the behavior of spark discharge at pressurized conditions up to 45 bar and high-speed cross-flows up to 32 m/s. To accomplish this goal, a parametric study on the spark channel resistance was conducted.

Quantitative measurements of direct injection fuel spray density and mixing are difficult to achieve using optical diagnostics, due to the substantial scattering of light and high optical density of the droplet field. For multi-hole sprays, the problem is even more challenging, as it is difficult to isolate a single spray plume along a single line of sight. Time resolved x-ray radiography diagnostics developed at Argonne's Advanced Photon Source have been used for some time to study diesel fuel sprays, as x-rays have high penetrating power in sprays and scatter only weakly. Traditionally, radiography measurements have been conducted along any single line of sight, and have been applied to single-hole and group-hole nozzles with few plumes. In this new work, we extend the technique to multi-hole gasoline direct injection sprays.

A Machine Learning-Genetic Algorithm (ML-GA) approach was developed to virtually discover optimum designs using training data generated from multi-dimensional simulations. Machine learning (ML) presents a pathway to transform complex physical processes that occur in a combustion engine into compact informational processes. In the present work, a total of over 2000 sector-mesh computational fluid dynamics (CFD) simulations of a heavy-duty engine were performed. These were run concurrently on a supercomputer to reduce overall turnaround time. The engine being optimized was run on a low-octane (RON70) gasoline fuel under partially premixed compression ignition (PPCI) mode. A total of nine input parameters were varied, and the CFD simulation cases were generated by randomly sampling points from this nine-dimensional input space. These input parameters included fuel injection strategy, injector design, and various in-cylinder flow and thermodynamic conditions at intake valve closure (IVC).

Computational fluid dynamics of gas-fueled large-bore spark ignition engines with pre-chamber ignition can speed up the design process of these engines provided that 1) the reliability of the results is not affected by poor meshing and 2) the time cost of the meshing process does not negatively compensate for the advantages of running a computer simulation. In this work a flame propagation model that runs with arbitrary hybrid meshes was developed and coupled with the KIVA4-MHI CFD solver, in order to address these aims. The solver follows the G-Equation level-set method for turbulent flame propagation by Tan and Reitz, and employs improved numerics to handle meshes featuring different cell types such as hexahedra, tetrahedra, square pyramids and triangular prisms. Detailed reaction kinetics from the SpeedCHEM solver are used to compute the non-equilibrium composition evolution downstream and upstream of the flame surface, where chemical equilibrium is instead assumed.

The importance of radiative heat transfer on the combustion and soot formation characteristics under nominal ECN Spray A conditions has been studied numerically. The liquid n-dodecane fuel is injected with 1500 bar fuel pressure into the constant volume chamber at different ambient conditions. Radiation from both gas-phase as well as soot particles has been included and assumed as gray. Three different solvers for the radiative transfer equation have been employed: the discrete ordinate method, the spherical-harmonics method and the optically thin assumption. The radiation models have been coupled with the transported probability density function method for turbulent reactive flows and soot, where unresolved turbulent fluctuations in temperature and composition are included and therefore capturing turbulence-chemistry-soot-radiation interactions. Results show that the gas-phase (mostly CO2 ad H2O species) has a higher contribution to the net radiation heat transfer compared to soot.

Autonomous vehicle operation is dependent upon accurate position estimation and thus a major concern of implementing the autonomous navigation is obtaining robust and accurate data from sensors. This is especially true, in case of Inertial Measurement Unit (IMU) sensor data. The IMU consists of a 3-axis gyro, 3-axis accelerometer, and 3-axis magnetometer. The IMU provides vehicle orientation in 3D space in terms of yaw, roll and pitch. Out of which, yaw is a major parameter to control the ground vehicle’s lateral position during navigation. The accelerometer is responsible for attitude (roll-pitch) estimates and magnetometer is responsible for yaw estimates. However, the magnetometer is prone to environmental magnetic disturbances which induce errors in the measurement.

In-cylinder ion sensing is a subject of interest due to its application in spark-ignited (SI) engines for feedback control and diagnostics including: combustion knock detection, rate and phasing of combustion, and mis-fire On Board Diagnostics (OBD). Further advancement and application is likely to continue as the result of the availability of ignition coils with integrated ion sensing circuitry making ion sensing more versatile and cost effective. In SI engines, combustion knock is controlled through closed loop feedback from sensor metrics to maintain knock near the borderline, below engine damage and NVH thresholds. Combustion knock is one of the critical applications for ion sensing in SI engines and improvement in knock detection offers the potential for increased thermal efficiency. This work analyzes and characterizes the ionization signal in reference to the cylinder pressure signal under knocking and non-knocking conditions.

Stringent emission standards are driving the development of diesel-fuel injection concepts to mitigate in-cylinder formation of particulates. While research has demonstrated significant reduction in particulate formation using micro-orifice technology, implementation requires development of industrial processes to fabricate micro-orifices with diameters as low as 50 μm and with large length-to-diameter ratios. This paper reviews the different processes being pursued to fabricate micro-orifices and the advanced techniques applied to characterize the performance of micro-orifices. The latter include the use of phase-contrast x-ray imaging of electroless nickel-plated micro-orifices and laser imaging of fuel sprays at elevated pressures. The experimental results demonstrate an industrially viable process to create small uniform orifices that improve spray formation for fuel injection.

Cast aluminum alloys are normally quenched after solution treatment or solidification process to improve aging responses. Rapid quenching can lead to high residual stress and severe distortion which significantly affects dimension stability, functionality and particularly performance of the product. To simulate residual stress and distortion induced during quenching, a finite element based approach was developed by coupling an iterative zone-based transient heat transfer algorithm with material thermo-viscoplastic constitutive model. With the integrated models, the numeric predictions of residual stresses and distortion in the quenched aluminum castings are in a good agreement with experimental measurements.

Understanding the flow characteristics and, especially, how the aerodynamic forces are influenced by the changes in the vehicle body shape, are very important in order to improve vehicle aerodynamics. One specific goal of aerodynamic shape optimization is to predict the local shape sensitivities for aerodynamic forces. The availability of a reliable and efficient sensitivity analysis method will help to reduce the number of design iterations and the aerodynamic development costs. Among various shape optimization methods, the Adjoint Method has received much attention as an efficient sensitivity analysis method for aerodynamic shape optimization because it allows the computation of sensitivity information for a large number of shape parameters simultaneously.

Fuel economy improvement and stringent emission regulations worldwide require advanced air charging and combustion technologies, such as low temperature combustion, PCCI or HCCI combustion. Furthermore, NOx aftertreatment systems, like Selective Catalyst Reduction (SCR) or lean NOx trap (LNT), are needed to reduce vehicle tailpipe emissions. The information on engine-out NOx emissions is essential for engine combustion optimization, for engine and aftertreatment system development, especially for those involving combustion optimization, system integration, control strategies, and for on-board diagnosis (OBD). A physical NOx sensor involves additional cost and requires on-board diagnostic algorithms to monitor the performance of the NOx sensor.

Cost and robustness are key factors in the design of diesel engines for low power density applications. Although compression ignition engines can produce very high power density output with turbocharging, naturally aspirated (NA) engines have advantages in terms of reduced cost and avoidance of system complexity. This work explores the use of direct injection (DI) and exhaust gas recirculation (EGR) in NA engines using experimental data from a single-cylinder research diesel engine. The engine was operated with a fixed atmospheric intake manifold pressure over a map of speed, air-to-fuel ratio, EGR, fuel injection pressure and injection timing. Conventional gaseous engine-out emissions were measured along with high speed cylinder pressure data to show the load limits and resulting emissions of the NA-DI engine studied. Well known reductions in NOX with increasing levels of EGR were confirmed with a corresponding loss in peak power output.

An iterative learning control (ILC) algorithm has been developed for a test cell electro-hydraulic, fully flexible valve actuation system to track valve lift profile under steady-state and transient operation. A dynamic model of the plant was obtained from experimental data to design and verify the ILC algorithm. The ILC is implemented in a prototype controller. The learned control input for two different lift profiles can be used for engine transient tests. Simulation and bench test are conducted to verify the effectiveness and robustness of this approach. The simple structure of the ILC in implementation and low cost in computation are other crucial factors to recommend the ILC. It does not totally depend on the system model during the design procedure. Therefore, it has relatively higher robustness to perturbation and modeling errors than other control methods for repetitive tasks.

Liquid and vapor envelopes of sprays from a multi-hole fuel injector operating under closely-spaced double-injection conditions were investigated using a combination of high-speed schlieren and Mie scattering imaging. The effects of mass split ratio and dwell time between injections on liquid and vapor penetration have been investigated under engine-like pressures and temperatures. For the conditions evaluated, the results indicate that closely-spaced double-injection generally reduces liquid and vapor penetration.