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With the inception of model-based design and automatic code generation, many organizations are developing controls and diagnostics algorithms in model-based development tools to meet customer and regulatory requirements. Advances in model-based design have made it easier to generate C code from models and help software engineers streamline their workflow. Typically, after the software has been developed, the models are handed over to a calibration team responsible for calibrating the features to meet specified customer and regulatory requirements. However, once the models are handed over to the calibration team, the calibration engineers are unaware of how to calibrate the features because documentation is not available. Typically, model documentation trails behind the software process because it is created manually, most of this time is spent on formatting. As a result, lack of model documentation or up-to date documentation causes a lot of pain for OEM’s and Tier 1 suppliers.

The information provided by the in-cylinder pressure signal is of great importance for modern engine management systems. The obtained information is implemented to improve the control and diagnostics of the combustion process in order to meet the stringent emission regulations and to improve vehicle reliability and drivability. The work presented in this paper covers the experimental study and proposes a comprehensive and practical solution for the estimation of the in-cylinder pressure from the crankshaft speed fluctuation. Also, the paper emphasizes the feasibility and practicality aspects of the estimation techniques, for the real-time online application. In this study an engine dynamics model based estimation method is proposed. A discrete-time transformed form of a rigid-body crankshaft dynamics model is constructed based on the kinetic energy theorem, as the basis expression for total torque estimation.

The primary function of an airbag control module is to detect crashes, discriminate and predict if a deployment is necessary, then deploy the restraint systems including airbags and where applicable, pretensioners. At General Motors (GM), the internal term for airbag control module is Sensing and Diagnostic Module (SDM). In the 1994 model year, GM introduced its SDM on some of its North American airbag-equipped vehicles. A secondary function of that SDM and all subsequent SDMs is to record crash related data. This data can include data regarding impact severity from internal accelerometers and pre-crash vehicle data from various chassis and powertrain modules. Previous researchers have addressed the accuracy of both the velocity change data, recorded by the SDM, and the pre-crash data, but the assessment of the timing of the pre-crash data has been limited to a single family of modules (Delphi SDM-G).

A single-cylinder engine was used to study the potential of a high-efficiency combustion concept called gasoline direct-injection compression-ignition (GDCI). Low temperature combustion was achieved using multiple injections, intake boost, and moderate EGR to reduce engine-out NOx and PM emissions engine for stringent emissions standards. This combustion strategy benefits from the relatively long ignition delay and high volatility of regular unleaded gasoline fuel. Tests were conducted at 6 bar IMEP - 1500 rpm using various injection strategies with low-to-moderate injection pressure. Results showed that triple injection GDCI achieved about 8 percent greater indicated thermal efficiency and about 14 percent lower specific CO2 emissions relative to diesel baseline tests on the same engine. Heat release rates and combustion noise could be controlled with a multiple-late injection strategy for controlled fuel-air stratification. Estimated heat losses were significantly reduced.

Electro-hydraulic actuation has been used widely in automatic transmission designs. With greater demand for premium shift quality of automatic transmissions, higher pressure control accuracy of the transmission electro-hydraulic control system has become one of the main factors for meeting this growing demand. This demand has been the driving force for the development of closed loop pressure controls technology. This paper presents the further research done based upon a previously developed closed loop system. The focus for this research is on the system requirements, such as solenoid driver selection and system latency handling. Both spin-stand and test vehicle setups are discussed in detail. Test results for various configurations are given.

Global demand for alternative fuels to combat rising energy costs has sparked a renewed interest in catalysts that can effectively remediate NOx emissions resulting from combustion of a range of HC based fuels. Because many of these new engine technologies rely on lean operating environments to produce efficient power, the resulting emissions are also present in a lean atmosphere. While HCs are easily controlled in such environments, achieving high NOx conversion to N2 has continued to elude fully satisfactory solution. Until recently, most approaches have relied on catalysts with precious metals to either store NOx and subsequently release it as N2 under rich conditions, or use NH3 SCR catalysts with urea injection to reduce NOx under lean conditions. However, new improvements in Ag based technologies also look very promising for NOx reduction in lean environments.

Low-cost lean NOx aftertreatment is one of the main challenges facing high-efficiency gasoline and diesel engines operating with lean mixtures. While there are many candidate technologies, they all offer tradeoffs. We have investigated a multi-component Dual SCR aftertreatment system that is capable of obtaining NOx reduction efficiencies of greater than 90% under lean conditions, without the use of precious metals or urea injection into the exhaust. The Dual SCR approach here uses an Ag HC-SCR catalyst followed by an NH3-SCR catalyst. In bench reactor studies from 150 °C to 500 °C, we have found, for modest C/N ratios, that NOx reacts over the first catalyst to predominantly form nitrogen. In addition, it also forms ammonia in sufficient quantities to react on the second NH3-SCR catalyst to improve system performance. The operational window and the formation of NH3 are improved in the presence of small quantities of hydrogen (0.1–1.0%).

As diesel emission regulations continue to increase, the use of exhaust aftertreatment systems containing, for example the diesel oxidation catalyst (DOC) and diesel particulate filter (DPF) will become necessary in order to meet these stringent emission requirements. The addition of a DOC and DPF in conjunction with utilizing biodiesel fuels requires extensive research to study the implications that biodiesel blends have on emissions as well as to examine the effect on aftertreatment devices. The proceeding work discusses results from a 2006 VM Motori four-cylinder 2.8L direct injection diesel engine coupled with a diesel oxidation catalyst and catalyzed diesel particulate filter. Tests were done using ultra low sulfur diesel fuel blended with 20% choice white grease biodiesel fuel to evaluate the effects of biodiesel emission products on the performance and effectiveness of the aftertreatment devices and the effect of low temperature combustion modes.

In recent years, gasoline direct injection (GDi) engines have been popular due to their inherent potential for reduction of exhaust emissions and fuel consumption to meet stringent EPA standards. These engines require high-pressure fuel injection in order to improve the atomization process and accelerate mixture preparation. The high-pressure fuel pump is an essential component in the GDi system. Therefore, understanding the flow characteristics of this device and its associated behavior is critical for improving the performance of this category of engines. In this paper, the fluid flow characteristics in a high-pressure single-piston pump for use in GDi engines are analyzed using 1-D LMS Imagine.Lab AMESim system and 3-D Ansys Fluent computational fluid dynamics (CFD) models. The flow rate of the fuel pump under various cam speeds has been examined along with characteristics of the pump's control valve.

This paper describes a correlation study on fuel spray pattern recognition of multi-hole injectors for gasoline direct injection (GDi) engines. Spray pattern is characterized by patternation length, which represents the distance of maximum droplet concentration from the axis of the injector. Five fuel injectors with different numbers and sizes of nozzle holes were considered in this study. Experimental data and CFD modeling results were used separately to develop regression models for spray patternation. These regressions predicted the influence of a number of injector operating and design parameters, including injection system operating pressure, valve lift, injector hole length-to-diameter ratio (L/d) and the orientation of the injector hole. The regression correlations provided a good fit with both experimental and CFD spray simulation results. Thus CFD offers a good complement to experimental validation during development efforts to meet a desired injector spray pattern.

The need for improved emissions control in lean exhaust to meet tightening, world-wide NOx emissions standards has led to the development of selective catalytic reduction of NOx with ammonia as a major technology for emissions control. Current systems are being designed to use a solution of urea (32.5 wt %) dissolved in water or Diesel Exhaust Fluid (DEF) as the ammonia source. While DEF or AdBlue® is widely used as a source of ammonia, it has a number of issues at low temperatures, including freezing below −12 °C, solid deposit formation in the exhaust, and difficulties in dosing at exhaust temperatures below 200 °C. Additionally creating a uniform ammonia concentration can be problematic, complicating exhaust packaging and usually requiring a discrete mixer.

This paper presents the development of a transmission closed loop pressure control system. The objective of this system is to improve transmission pressure control accuracy by employing closed-loop technology. The control system design includes both feed forward and feedback control. The feed forward control algorithm continuously learns solenoid P-I characteristics. The closed loop feedback control has a conventional PID control with multi-level gain selections for each control channel, as well as different operating points. To further improve the system performance, Robust Optimization is carried out to determine the optimal set of control parameters and controller hardware design factors. The optimized design is verified via an L18 experiment on spin dynamometer. The design is also tested on vehicle.

Air Conditioning systems with reheat reduction based for energy efficiency have generally been implemented with either electronic variable compressors through active stroke control or with fixed displacement compressors through modifying the cycling set point. The present work demonstrates a unique concept of achieving energy efficiency via cycling a pneumatic variable compressor at elevated set points. The energy efficiency of such a system approaches that of an electronic variable but significantly higher than that of a fixed displacement compressor system. The cost of the system, on the other hand, is substantially lower than that of an electronic compressor. Secondary benefits include a softer start than with a fixed compressor and a considerably simpler control scheme than that required by an electronic variable compressor.

Both Crash-Avoidance and Pre-Crash active safety technologies are being developed to help reduce the number of crashes and minimize the severity of crashes. The root basis in the development of new and improved active safety technologies always begins with gaining further knowledge about crash kinds and causes. The dynamics of crashes are quite complex. The evolving precursor crash situation initiated in the Crash-Avoidance time-period will vary from the imminent crash situation in the Pre-Crash time-period. As such, in order to develop the appropriate requirements for both crash-avoidance and pre-crash technologies, they must be analyzed from their respective crash data. A data-driven methodology process has been developed which partitions the field data with a perspective to crash-avoidance and pre-crash.

With increasingly stringent emissions regulations and concurrent requirements for enhanced engine thermal efficiency, a comprehensive characterization of the automotive gasoline fuel spray has become essential. The acquisition of accurate and repeatable spray data is even more critical when a combustion strategy such as gasoline direct injection is to be utilized. Without industry-wide standardization of testing procedures, large variablilities have been experienced in attempts to verify the claimed spray performance values for the Sauter mean diameter, Dv90, tip penetration and cone angle of many types of fuel sprays. A new SAE Recommended Practice document, J2715, has been developed by the SAE Gasoline Fuel Injection Standards Committee (GFISC) and is now available for the measurement and characterization of the fuel sprays from both gasoline direct injection and port fuel injection injectors.

The paper describes a new strategy for real-time sensor diagnostics that is based on the statistical correlation of various sensor signal pairs. During normal fault-free operation there is a certain correlation between the sensor signals which is lost in the event of a fault. The proposed algorithm quantifies the correlation between sensor signal pairs using real-time scalar metrics based on the Mahalanobis-distance concept. During normal operation all metrics follow a similar pattern, however in the event of a fault; metrics involving the faulty sensor would increase in proportion to the magnitude of the fault. Thus, by monitoring this pattern and using a suitable fault-signature table it is possible to isolate the faulty sensor in real-time. Preliminary simulation results suggest that the strategy can mitigate the false-alarms experienced by most model-based diagnostic algorithms due to an intrinsic ability to distinguish nonlinear vehicle behavior from actual sensor faults.

Traffic engineers use time-of-day travel time databases to characterize normal travel times on roads. This information is used by traffic management centers together with information from sensors in the highway to identify problems and to make alternate route recommendations. In this paper, the travel time database concept is extended to a vehicle-to-vehicle communications network for traffic and safety information, wherein the travel time database is generated and stored by vehicles in the network, and used by the vehicles to identify abnormal traffic conditions. This infrastructure-free approach is attractive due to the potential to eliminate highway sensor and sensor maintenance costs, which are major factors that limit the growth of traffic information beyond major roadways in urban regions. Initial work indicates that database storage requirements in the vehicle should be manageable.

Some Electronic Throttle Control (ETC) Air Control Valves (ACV) on automotive internal combustion engines are susceptible to icing of the throttle valve. Ice formation can result in an increase in torque required to open or close the valve. Laboratory studies were conducted to improve the understanding of throttle valve icing on electronic throttle control valves with both aluminum and composite (plastic) bodies over various bore sizes (4 cylinder to 8 cylinder engines). Study results indicated that ice compression at the bore and valve gap, not ice adhesion, is the major contributor to the ETC-ACV icing phenomenon. In addition, testing of parts with various bore sizes, orientations and surface cleanliness resulted in further understanding of the icing issue.

During the production controller and software development process, one critical step is the controller and software verification. There are various ways to perform this verification. One of the commonly used methods is to utilize an HIL (hardware-in-the-loop) test bench to emulate powertrain hardware for development and validation of powertrain controllers and software. A key piece of an HIL bench is the plant dynamics model used to emulate the external environment of a modern controller, such as engine (ECM), transmission (TCM) or powertrain controller (PCM), so that the algorithms and their software implementation can be exercised to confirm the desired results. This paper presents a 6-speed automatic transmission plant dynamics model development for hardware-in-the-loop (HIL) test bench for the validation of production transmission controls software. The modeling method, model validation, and application in an HIL test environment are described in details.

A key quantity for use in engine control is the exhaust manifold pressure. For production applications it is an important component in the calculation of the engine volumetric efficiency, as well as EGR flow and residual fraction. For cost reasons, however, it is preferable to not have to measure the exhaust manifold pressure for production applications. For that reason, it is advantageous to develop a model for estimating the exhaust manifold pressure in production application software that is small, accurate, and simple to calibrate. In this paper, a mean-value model for calculating the exhaust manifold pressure is derived from the compressible flow equation, treating the exhaust system as a fixed-geometry restriction between the exhaust manifold and the outlet of the tailpipe. Validation data from production applications is presented.