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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.

This paper includes a numerical and experimental study of fluid flow in automotive catalytic converters. The numerical work involves using computational fluid dynamics (CFD) to perform three-dimensional calculations of turbulent flow in an inlet pipe, inlet cone, catalyst substrate (porous medium), outlet cone, and outlet pipe. The experimental work includes using hot-wire anemometry to measure the velocity profile at the outlet of the catalyst substrate, and pressure drop measurements across the system. Very often, the designer may have to resort to offset inlet and outlet cones, or angled inlet pipes due to space limitations. Hence, it is very difficult to achieve a good flow distribution at the inlet cross section of the catalyst substrate. Therefore, it is important to study the effect of the geometry of the catalytic converter on flow uniformity in the substrate.

Computer simulation was used as a complement to crash and injury field data analysis and physical sled and barrier tests to investigate and predict the spinal injuries of a rear impact in an IndyCar. The model was expected to relate the spinal loads to the observed injuries, thereby predicting the probability and location of spinal fractures. The final goal is to help reduce the fracture risk by optimizing the seat and restraint system design and the driver's position using computer modeling and sled testing. MADYMO Full FE Human Body Model (HBM) was selected for use because of its full spinal structural details and its compatibility with the vehicle and restraint system models. However, the IndyCar application imposed unique challenges to the HBM. First, the driver position in a race car is very different from that in a typical passenger car.

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.

In the field of vehicle diagnostics accurate instantaneous engine speed information enables the detection and diagnosis of many engine problems, even subtle ones. Currently, there is a limited choice in the ways of obtaining such information. For example, it is known that one can tap into the crank sensor wiring, or use a separate, intrusive method, such as mounting a sensor in the bell housing to sense the rotation of the ring gear. However, the shortcomings of these approaches are locating and gaining access to the crank sensor connector, the location of which varies from vehicle to vehicle. Thus, authors proposed a novel, robust and manufacturing friendly speed sensor. The concept is based on the Villari effect. The sensor, which is attached to the front end of the engine crankshaft, consists of a coil of magnetostrictive wire supplied with AC current. During engine rotation the magnetostrictive wire become stressed due to centrifugal force.

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.

2-Step variable-valve lift and timing is a high-value technology for the further development of automotive internal combustion engines. 2-Step valve train systems provide improved engine efficiency, emissions, and performance using components that are relatively low-cost and compatible with new and existing cylinder heads. This paper describes the design and development of a 2-Step rocker arm using a combination of analytical tools and physical testing. Prototype hardware was built to confirm the design. Performance and durability test results are presented.

Modern engines are becoming highly complex, with several strongly interactive subsystems - - variable cam phasers on both intake and exhaust, along with various kinds of variable valve lift mechanisms. Isolated component models may not yield adequate information to deal with system-level interactive issues, especially when it comes to transient behavior. In addition, massive amounts of expensive experimental work will be required for optimization. Recent computing speed improvements are beginning to permit the use of co-simulation to couple highly detailed and accurate submodels of the various engine components, each created using the most appropriate available simulation package. This paper describes such a system model using GT-Power to model the engine, AMESim to model cam phasers and the engine lubrication system, and Matlab/Simulink to model the engine controllers and the vehicle.

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.

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.

An analytical study of spray from an outwardly opening pressure swirl injector has been presented in this paper. A number of model injectors with varying design configurations have been used in this study. The outwardly opening injection process has been modeled using a modified spray breakup model presented in an earlier study. It has been observed that simulation results from the study clearly capture the mechanism by which an outwardly opening conical spray interacts with the downstream flow field. Velocity field near the tip of the injector shows that the conical streams emanating from an outwardly opening injector have the tendency to entrap air into the flow stream which is responsible for finer spray. A deviation from the optimum set of physical parameters showed a high propensity to produce large spray droplets. This study also emphasizes the importance of computational fluid dynamics (CFD) as an engineering tool to understand the complex physical processes.

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.

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 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.

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.

Worldwide regulatory demands to reduce emissions of greenhouse gases and other airborne pollutants are leading to significant changes in internal combustion engines. Many engine subsystems such as fuel injection, valvetrain, turbochargers and EGR, are being changed to address these demands. Additionally, advanced combustion modes such as HCCI are being pursued to address the key shortcomings of today's gasoline and diesel engines. Cylinder pressure based control is an enabling technology to the development and application of advanced engine subsystems and a key control element for advanced combustion modes. This paper describes a tool for rapid development of closed-loop cylinder pressure based algorithms. The Cylinder Pressure Development Controller (CPDC) is an affordable, automotive grade package containing a unique architecture enabling real-time, next engine cycle combustion feedback control.

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.