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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%).

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.

With the wider use of biofuels in the marketplace, a program was conducted to study the deposit forming tendencies and performance of E85 (85% denatured ethanol and 15% gasoline) in a modern Flexible Fuel Vehicle (FFV). The test vehicle for this program was a 2006 General Motors Chevrolet Impala FFV equipped with a 3.5 liter V-6 powertrain. A series of 5,000 mile Chassis Dynamometer (CD) Intake Valve Deposits (IVD) and performance tests were conducted while operating the FFV on conventional (E0) regular unleaded gasoline and E85 to determine the deposit forming tendencies of both fuels. E85 test fuels were found to generate significantly higher levels of IVD than would have been predicted from the base gasoline component alone. The effects on the weight and composition of IVD due to a corrosion inhibitor and sulfates that were indigenous to one of the ethanols were also studied.

Production software validation is critical during software development, allowing potential quality issues that could occur in the field to be minimized. By developing automated and repeatable software test methods, test cases can be created to validate targeted areas of the control software for confirmation of the expected results from software release to release. This is especially important when algorithm/software development timing is aggressive and the management of development activities in a global work environment requires high quality, and timely test results. This paper presents a hardware-in-the-loop (HIL) test bench for the validation of production transmission controls software. The powertrain model used within the HIL consists of an engine model and a detailed automatic transmission dynamics model. The model runs in an OPAL-RT TestDrive based HIL system.

This paper describes a new tool to capture cylinder pressure information, calculate combustion parameters, and implement control algorithms. There are numerous instrumentation and prototyping systems which can provide some or all of this capability. The Cylinder Pressure Development Controller (CPDC) is unique in that it uses advanced high volume automotive grade circuitry, packaging, and software methodologies. This approach provides insight regarding the implementation of cylinder pressure based controls in a production engine management system. A high performance data acquisition system is described along with a data reduction technique to minimize data processing requirements. The CPDC software architecture is discussed along with model-based algorithm development and autocoding. Finally, CPDC calculated combustion parameters are compared with those from a well established combustion analysis system and thermodynamic simulations.

Advanced chassis control systems enable a vehicle to achieve new levels of performance in handling stability and responsiveness. In recent work by NHTSA and others, the performance of Electronic Stability Control (ESC) systems has been studied with focus on yaw stability and roll stability of vehicles on high friction surfaces. However, it is recognized that vehicle handling responsiveness is also an important aspect that should be maintained. This paper explores the trade-offs between yaw rate, side slip, and roll motions of a vehicle, and their relationships to handling stability and handling responsiveness. This paper further describes how various control systems are able to manage these motions. The paper also discusses methods to assess vehicle stability and responsiveness using specific maneuvers and measurements, and it includes data from vehicle tests on a slippery surface.

The paper describes the development of a vehicle stability indicator based on the correlation between various current vehicle chassis sensors such as hand wheel angle, yaw rate and lateral acceleration. In general, there is a correlation between various pairs of sensor signals when the vehicle operation is linear and stable and a lack of correlation when the vehicle is becoming unstable or operating in a nonlinear region. The paper outlines one potential embodiment of the technology that makes use of the Mahalanobis distance metric to assess the degree of correlation among the sensor signals. With this approach a single scalar metric provides an accurate indication of vehicle stability.

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.

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.

This paper presents a hardware-in-the-loop (HIL) test bench for the validation of production transmission controls software, with a focus on a closed-loop vehicle drive-train model incorporating a detailed automatic transmission plant dynamics model developed for certain applications. Specifically, this paper presents the closed-loop integration of a 6-speed automatic transmission model developed for our HIL transmission controller and algorithm test bench (Opal-RT TestDrive based). The model validation, integration and its application in an HIL test environment are described in details.

In a CAS system, the distance and relative velocity between front and host vehicles are estimated to calculate time-to-collision (TTC). The distance estimates by different methods will certainly include noise which should be removed to ensure the accuracy of TTC calculations. Kalman filter is a good tool to filter such type of noise. Nevertheless, Kalman filter is a model based filter, which means a correct model is important to get the good filtering results. Usually, a vehicle is either moving with a constant velocity (CV) or constant acceleration (CA) maneuvers. This means the distance data between front and host vehicles can be described by either constant velocity or constant acceleration model. In this paper, first, CV and CA models are used to design two Kalman filters and an interacting multiple model (IMM) is used to dynamically combine the outputs from two filters.

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.

Automotive rollover is a complex mechanical phenomenon. In order to understand the mechanism of rollover and develop any potential countermeasures for occupant protection, efficient and repeatable laboratory tests are necessary. However, these tests are not well understood and are still an active area of research interest. It is not always easy or intuitive to estimate the necessary initial and boundary conditions for such tests to assure repeatability. This task can be even more challenging when rollover is a second or third event (e.g. frontal impact followed by a rollover). In addition, often vehicle and occupant kinematics need to be estimated a-priori, first for the safe operation of the crew and equipment safety, and second for capturing and recording the event. It is important to achieve the required vehicle kinematics in an efficient manner and thus reduce repetitive tests. Mathematical modeling of the phenomenon can greatly assist in understanding such kinematics.

Adaptive Cruise Control (ACC) technology is presently emerging in the automotive market as a convenience function intended to reduce driver workload. It allows the host vehicle to maintain a set speed and distance from preceding vehicles by a forward object detection sensor. The forward object detection sensor is the focal point of the ACC control system, which determines and regulates vehicle acceleration and deceleration through a powertrain torque control system and an automatic brake control system. This paper presents a design of an automatic braking system that utilizes a microprocessor-controlled brake hydraulic modulator. The alternatively qualified automatic braking means is reviewed first. The product level requirements of the performance, robustness, and durability for an automatic brake system are addressed. A brief overview of the presented system architecture is described.

This paper proposes the concept of Generalized Diagnostic Component (GDC) and presents a modular fault diagnostic strategy for safety critical automotive systems. The diagnostic strategy makes full use of hierarchical techniques, integrates the generalized diagnostic design into all-purpose vehicle diagnoses based on reconfiguration of the GDCs, and inherits the model-based diagnostic algorithms developed for Steering/Braking-By-Wire systems. The GDC-based approach simplifies the design and integration of diagnostics in complex dynamical control systems, and has been successfully implemented in an eight degrees of freedom NAVDyn (Non-Linear Analysis of Vehicle Dynamics) simulation model using Matlab Simulink. The simulation results are provided in this paper to testify that the diagnostic strategy and implementation are feasible, efficient and dependable.

Among the performance concerns in brake design, drag and fluid displacement are getting more attention in the requirement definition. High drag not only affects fuel efficiency and lining life, it is also a contributing factor to rotor thickness variation and brake pulsation. In this paper, a system approach to drag performance of a disc brake caliper is presented. A one-dimensional simulation model, which considers all the significant factors, including lining stiffness and hysteresis, housing stiffness, seal/groove characteristic, and stick-slide behavior between the seal and piston, is developed to capture the interactive impact of each parameter to caliper drag performance. The system model is validated with experimental measurements for caliper fluid displacement and piston retraction. A parameter study is then conducted to investigate the component interactive impact to the drag performance.

A squeal analysis on a front disc brake is presented here utilizing the new complex eigenvalue capability in ABAQUS/Standard. As opposed to the direct matrix input approach that requires users to tailor the friction coupling matrix, this method uses nonlinear static analyses to calculate the friction coupling prior to the complex eigenvalue extraction. As a result, the effect of non-uniform contact pressure and other nonlinear effects are incorporated. Friction damping is used to reduce over-predictions and the velocity dependent friction coefficient is defined to contribute negative damping. Complex eigenvalue predictions of the example cases show very good correlation with test data for a wide range of frequencies. Finally, the participation of rotor tangential modes is also discussed.

Computer modeling and simulation have become one of the primary methods for development and design of automobile occupant protection systems (OPS). To ensure the accuracy and reliability of a math-based OPS design, the correlation quality assessment of mathematical models is essential for program success. In a typical industrial approach, correlation quality is assessed by comparing chart characteristics and scored based on an engineer's modeling experience and judgment. However, due to the complexity of the OPS models and their responses, a systematic approach is needed for accuracy and consistency. In this paper, a correlation grading methodology for the OPS models is presented. The grading system evaluates a wide spectrum of a computer model's performances, including kinematics, dynamic responses, and dummy injury measurements. Statistical analysis is utilized to compare the time histories of the tested and simulated dynamic responses.

This study utilizes complex eigenvalue analysis to investigate the sensitivity of dynamic system stability to the mechanical properties of the friction material. The friction material is modeled as a transverse isotropic material exhibiting different in-plane and out-of-plane moduli. Parametric studies are performed to evaluate system stability under various combinations of these properties. The initial analysis results show good correlation with laboratory testing for both squeal frequency and mode shape. Additional laboratory testing reveals a change in friction material can have a significant effect on the noise performance of a system. Analysis was performed with corresponding friction materials and the results were directionally consistent. This helped to validate the analysis model and establish confidence in the analysis results. In general, for the specific system considered, decreasing both in-plane and out-of-plane moduli encouraged system stability.