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There have been many articles published in the last decade or so concerning the components of an electronic stability control (ESC) system, as well as numerous statistical studies that attempt to predict the effectiveness of such systems relative to crash involvement. The literature however is free from papers that discuss how engineers might develop such systems in order to achieve desired steering, handling, and stability performance. This task is complicated by the fact that stability control systems are very complex and their designs and what they can do have changed considerably over the years. These systems also differ from manufacturer to manufacturer and from vehicle to vehicle in a given maker of automobiles. In terms of ESC hardware, differences can include all the components as well as the addition or absence of roll rate sensors or active steering gears to name a few.

Exhaust gas air-fuel ratio (A/F) sensors are common devices in powertrain feedback control systems aimed at minimizing emissions. Both resistive (using TiO2) and electrochemical (using ZrO2) mechanisms are used in the high temperature ceramic devices now being employed. In this work a new mechanism for making the measurement is presented based on the change in the workfunction of a Pt film in interaction with the exhaust gas. In particular it is found that the workfunction of Pt increases reversibly by approximately 0.7 V at that point (the stoichiometric ratio) where the exhaust changes from rich to lean conditions. This increase arises from the adsorption of O2 on the Pt surface. On returning to rich conditions, catalytic reaction of the adsorbed oxygen with reducing species returns the workfunction to its original value. Two methods, one capacitive and one thermionic, for electrically sensing this workfunction change and thus providing for a practical device are discussed.

The crush performance of lightweight composite automotive structures varies significantly between static and dynamic test conditions. This paper discusses the development of a new dynamic testing facility that can be used to characterize crash performance at high loads and constant speed. Previous research results from the Energy Management Working Group (EMWG) of the Automotive Composites Consortium (ACC) showed that the static crush resistance of composite tubes can be significantly greater than dynamic crush results at speeds greater than 2 m/s. The new testing facility will provide the unique capability to crush structures at high loads in the intermediate velocity range. A novel machine control system was designed and projections of the machine performance indicate its compliance with the desired test tolerances. The test machine will be part of a national user facility at the Oak Ridge National Laboratory (ORNL) and will be available for use in the summer of 2002.

This paper proposes a novel algorithm. This algorithm is called Self-Organizing Fuzzy Neural Network (SOFNN). SOFNN revolutionizes how researchers apply control theories, image/signal processing on control systems and other applications. In general, SOFNN is an identification technique that automatically initiates, builds and fine-tunes the required network parameters. SOFNN evaluates required structures without predefined parameters or expressions regarding systems. SOFNN sets out to learn and configure a system's characteristics. Self-constructing and self-tuning features enable SOFNN to handle complex, non-linear, and time-varying systems with higher accuracy, making systems identification easier. SOFNN constructs and fine-tunes the system parameter through two phases. The two phases are the construction and the parameter-tuning phase. The two phases run concurrently allowing SOFNN to identify systems on-line.

The Auto Industry is responding to the environment and energy conservation concerns by ramping up production of hybrid electric vehicles (HEV). As the initial hurdles of making the powertrain operate are overcome, challenges such as making the powertrain feel more refined and intuitive remain. This paper investigates one of the key parameters for delivering that refinement: engine RPM behavior. Ideal RPM behavior is explored and included in the design of a control system. System implications are examined with regard to the effect of engine RPM scheduling on Battery usage and vehicle responsiveness.

For urea Selective Catalytic Reduction (SCR) systems, adaptive control is of interest to provide a capability of maintaining high NOx conversion efficiency and low ammonia slip in the presence of uncertainties in the system. In this paper, the dynamics of the urea SCR system are represented by a control-oriented model which is based on a linear transfer function, with parameters dependent on engine operating conditions. The parameters are identified from input-output data generated by a high fidelity full chemistry model of the urea SCR system. The use of the full chemistry model facilitated the representation of the dynamics of stored ammonia (not a directly measurable parameter) as well as post SCR NOx and ammonia slip. A closed-loop Proportional-plus-Integral (PI) controller was first designed using the estimate of stored ammonia as a feedback signal.

The continued increase in complexity of automotive electronics has further necessitated for systems to be designed for optimal testing and servicing in the field. Locating failures within complex, interactive electronic systems can create conditions of both high warranty costs and customer dissatisfaction. Decisions about levels of system integration and diagnostics early in the design phases are fundamental parts of these considerations and are addressed in this paper. The approach focuses on projecting field repair rates and maintenance costs using a Monte Carlo computer simulation method given various component parameters such as part costs, reliability, labor time, and field diagnostic strategies. Results of the projection technique were shown to be quite accurate in projecting field warranty costs of a complex electronic system.

For many years, carmakers have developed unique system designs to gain a competitive advantage using some unique technology or an optimization of a design to cut costs or improve quality. This leads to continual increase in complexity, long development times and high development costs. A common platform, based on an "open architecture,'' provides a solution for many of the problems associated with the conventional automotive approach to electrical/electronic system designs. The PC industry is a prime example of how an open architecture can provide benefits to the consumer, manufacturers of software and hardware components, as well as complete system integrators. The PC, based on the initial IBM computer developed in the early eighties, has become a de facto standard that has survived 20 years of fast and dramatic changes in the fundamental technologies used within the platform.

Automatic headway control is an evolutionary step towards an automatic vehicle guidance and control system. This system expands the capability of the currently available production option-speed control. This paper describes the system from a theoretical and hardware viewpoint, with emphasis on the control logic. The electronic and electromechanical hardware design based on the theory presented is fully described. The limitations and advantages of the system are explained, based on test results from actual trial runs on an implemented vehicle. Capacity and safety benefits are made somewhat tangible by direct comparison with test results obtained on a roadway similar to that for which this system is recommended, under test conditions directly analogous to the operating characteristics of the automatic headway control system.

In this paper, we compare controllers for the electronic throttle and variable geometry turbocharger in boosted stoichiometric gasoline direct injection engines. The control objectives are fast response and small overshoot of the intake manifold pressure. The problem is treated within the multi-objective optimization framework, applied to a simulation model of the engine. Pareto optimal fronts are constructed for each of the controllers and compared to each other. The best controller is thereby identified and further options to improve its response via preview-based control are discussed.

In recent years, rapid and significant advances in fuel cell technology, together with advances in power electronics and control methodology, has enabled the development of high performance fuel cell powered electric vehicles. A key advance is that the low temperature (80°C) proton-exchange-membrane (PEM) fuel cell has become mature and robust enough to be used for automotive applications. Apart from the apparent advantage of lower vehicle emission, the overall fuel cell vehicle static and dynamic performance and power and energy efficiency are critically dependent on the intelligent design of the control systems and control methodologies. These include the control of: fuel cell heat and water management, fuel (hydrogen) and air (oxygen) supply and distribution, electric drive, main and auxiliary power management, and overall powertrain and vehicle systems.

Reduced complexity, improved driveability, and increased energy efficiency are among the advantages which can be obtained through Con-board) computer control of powertrains in both conventional and electric vehicles. This paper describes the design and implementation of a control system for an advanced electric vehicle powertrain, incorporating an integrated induction motor and two speed automatic transaxle. The control system employs a distributed computer architecture utilizing a fiber optic communication system for computer coordination. The software architecture utilizes a unique combination of standard multitasking concepts and finite state automata techniques. This approach allows individual tasks to be defined and prioritized and permits data and system resources to be shared effectively. Through the use of torque and gear shift scheduling, internal combustion engine torque characteristics can be duplicated to improve driveability.

This paper presents a description of intelligent sensor-based manufacturing, reviews previous research in this area, and identifies control system requirements necessary to support successful application of this technology. Current production control systems inhibit the successful implementation of advanced manufacturing control technologies. It is often difficult, if not impossible, to integrate new sensing technologies and advanced control algorithms with existing control platforms. To address this difficulty, hardware and software needs to support intelligent sensor-based manufacturing are discussed.

Hybrid electric vehicle (HEV) powertrains have become key to developing environmentally friendly and fuel efficient vehicles. As such, companies are continually investing in developing new hybrid powertrain architectures. Ford Motor Company has developed a new “Dual-Drive” full hybrid electric vehicle that overcomes some attribute deficiencies of existing hybrid powertrain architectures due to the kinematic arrangement of the engine, motors and driveline components. This hybrid powertrain is comprised of conventional powertrain components as its base with an electric motor on the rear axle, and a crank integrated starter generator, engine and transmission on the front axle. It forms a complex configuration which provides fuel economy improvement over a conventional powertrain.

Automotive display designers are faced with the task of providing more information to the driver through the implementation of an increased amount of on-board vehicle electronic systems. Package space in and around the instrument panel however, is at a premium. One remedy to this situation is the implementation of a dot matrix display with enough flexibility to fulfill several potential applications. Once a dot matrix display is integrated into a vehicle, information can be reformatted for presentation to the driver without redesigning the display device or its associated electronics. The system designer can then concentrate development resources on the remaining display subsystem components and issues such as user interface, display lighting, and packaging requirements for a specific application.

Feasibility of wall-flow diesel exhaust filter trap particulate aftertreatment emission control systems to meet the U.S. Federal, CARB, and EC passenger car standards for 1997/2003 and beyond for the 1360 kg (3000 lb.) EAO (Ford European Automotive Operations) 1.8 liter Sierra Turbo-Diesel passenger car is investigated. Plain and Pd catalyzed monolith wall flow diesel particulate traps are examined using Phillips No. 2 diesel fuel (Reference Standard), low sulfur (0.05% S) diesel fuel and an ultra-low sulfur (0.001% S) diesel fuel. Comparisons are made with baseline FTP75 and Highway exhaust emissions and Federal and CARB mandated particulate standards for 1997 and 2003. Effectiveness of catalyzed traps, plain traps, copper octoate trap regeneration fuel additive, and fuel sulfur content on the particulate emissions is determined.

The objective of this study was to quantify engine-out emissions of potentially toxic compounds from a modern diesel engine operated with different fuels including 15% v/v dimethoxy methane in a low sulfur diesel fuel. Five diesel fuels were examined: a low-sulfur, low-aromatic hydrocracked (∼1 ppm) fuel, the same low sulfur fuel containing 15% v/v dimethoxy methane, a Fischer-Tropsch fuel, a CARB fuel, and an EPA number 2 certification fuel. A DaimlerChrysler OM611 CIDI engine was controlled with a SwRI Rapid Prototyping Electronic Control system. The engine was operated over 4 speed-load modes. Each operating mode and fuel combination was run in triplicate. Thirty three potentially toxic compounds were measured for each fuel and mode.

The objective of this study was to quantify the effect of pilot fuel injection on engine-out emissions of potentially toxic compounds from a modern diesel engine operated with different fuels including 15% v/v dimethoxy methane in a low-sulfur diesel fuel. Five diesel fuels were examined: a low-sulfur (∼1 ppm), low aromatic, hydrocracked fuel, the same low-sulfur fuel containing 15% v/v dimethoxy methane, a Fischer-Tropsch fuel, a California reformulated fuel, and a EPA number 2 certification fuel. A DaimlerChrysler OM611 CIDI engine was controlled with a SwRI Rapid Prototyping Electronic Control system. The pilot fuel injection was either turned off or turned on with engine control by either Location of Peak Pressure (LPP) of combustion or the original equipment manufacturer (OEM) calibration strategy. These three control strategies were compared over 2 speed-load modes run in triplicate. Thirty-three potentially toxic compounds were measured.

This paper describes the results of an experiment concerning driver behavior in car following tasks. The motivation for this experiment was a desire to understand typical driver car following behavior as a guide for setting the automatic control characteristics of an ACC (Adaptive Cruise Control) system. Testing was conducted under both test track and open road driving conditions. The results indicate that car following is carried out under much lower bandwidth conditions than typical steering processes. Dynamic analysis shows driver time delay in response to lead vehicle velocity change on the order of several seconds. Typical longitudinal acceleration distributions show standard deviations of less than 0.05 g (acceleration due to gravity).

Particulate and manganese mass emissions have been measured as a function of mileage for four Escort and four Explorer vehicles using 1) MMT (Methylcyclopentadienyl Manganese Tricarbonyl) added to the gasoline at 1/32 g Mn/gal and 2) gasoline without MMT. The MMT was used in half of the fleet starting at 5,000 miles. The vehicles were driven on public roads at an average speed of 54 mph to accumulate mileage. This report describes the particulate and manganese emissions, plus emissions of four air toxics at 5,000, 20,000, 55,000, 85,000 and 105,000 miles. Four non-regulated emissions were measured and their average values for vehicles without MMT were 0.6 mg/mi for formaldehyde, 0.7 mg/mi for 1,3-butadiene, 9 mg/mi for benzene and 12 mg/mi for toluene. Corresponding values for MMT-fueled vehicles were between 1.5 and 2.4 times higher.