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Exhaust pressures (P3) are hard parameters to measure and can be readily estimated, the cost of the sensors and the temperature in the exhaust system makes the implementation of an exhaust pressure sensor in a vehicle control system a costly endeavor. The contention with measured P3 is the accuracy required for proper engine and vehicle control can sometimes exceed the accuracy specification of market available sensors and existing models. A turbine inlet exhaust pressure observer model based on isentropic expansion and heat transfer across a turbocharger turbine was developed and investigated in this paper. The model uses 4 main components; an open loop P3 orifice flow model, a model of isentropic expansion across the turbine, a turbine and pipe heat transfer models and an integrator with the deviation in the downstream turbine outlet parameter.

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.

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.

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.

With the introduction of new technologies ranging from developing new alternative energy vehicles to passive and active safety systems, the automakers are responding to the increased complexity of the control system by embracing Model Based Design (MBD) and Auto-code Generation (ACG) tools for control system design. This translates into lower development costs, higher quality and faster time-to-market. The Ford Motor Company production hybrid group launched a pilot project to study the feasibility of using MBD to speed up the development and testing of the next generation Torque Monitor software. This software uses a custom data storage format, called Double Store Variable (DSV) format, for all the critical signals. Each variable contains two fields, one for storing the actual data and the second for storing a transformed copy (e.g. one's complement) of the data. This allows the software to detect run-time corruption of the data in real-time.

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 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.

The current Brazilian tax legislation promotes vehicles, powered by engines with up to 1.0l displacement. In order to offer the customer an engine with the maximum tax advantage, a supercharged derivative of the Ford 1.0l Zetec RoCam engine was developed. The market specific boundary conditions in South America require powertrains with immediate response especially at low engine speeds. This can be achieved by a supercharged engine concept. The paper discusses the required engine modifications for the supercharger application. The combustion system was changed to benefit from the higher volumetric efficiency, including the optimisation of the intake, exhaust and bypass control system. Extensive modifications of the base engine were required to adapt the engine to the higher thermal load and the specific boundary condition of a supercharger application.

The purpose of this paper is to describe and define the interaction between a brake based stability control system and a passive coupler (viscous coupling unit) inside the transfer case of a Four-Wheel Drive (4WD) vehicle. This paper will focus on the driveline system and the impact that a stability control system can have on it. It will provide understanding of torque transfer on 4WD vehicles that are equipped with a brake based stability control system and use this knowledge to recommend ways to reduce the undesirable torque transfer interaction between the two systems. These recommendations can be readily applied to future 4WD/AWD vehicles to improve compatibility between the two systems.

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.

Most people still remember the introduction of the IBM PC in 1981 and the first Microsoft Windows operating system in 1985. These were the pioneering technologies that started a revolution in automotive test equipment in the service bay. What was once a purely mechanical garage environment where information was published annually in large paper manuals has evolved into a highly technical computing environment. Today vehicle networks link onboard vehicle control systems with diagnostic systems and updated service information is published daily over the Internet. A lot has changed over the last twenty years, and manufacturers of diagnostic test equipment are learning to deal with the constantly evolving computing platforms and host operating systems. This paper traces the history of automotive diagnostic equipment at Ford Motor Company and shares some of the hard lessons learned from the early systems.

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.

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.

This paper describes a procedure used to aid in the control of IC engine knock, an autoignition phenomenon that results in customer annoyance, loss of power, and potential engine damage. Since a control system can only function as well as the signal it is provided, input signal optimization is critical to the robustness of the system. Optimization of the input signal starts with a properly located physical transducer on the engine block. The locating process begins with laser holometry to evaluate compliant regions of the block. Holographic data, block vibration spectra and empirical engine data are then used to identify the most promising sensor locations. These locations are then verified with a broadband accelerometer mounted on a dynamometer engine. This process allows the highest available signal to noise locations to be found in a systematic and efficient manner.

The effect of port injected small fuel droplets was evaluated for several different modes of engine operation. The droplets were generated by an Air Forced Injector (AFI), Figure 1, which uses high velocity air through a nozzle to produce fuel droplets on the order of 10mm Sauter Mean Diameter (SMD). AFI results were compared to those from a standard production pintle injector. Steady state data, “motored cold start” data, and injector cut-out data were collected. All three data sets illustrate functional advantages of AFI over standard Electronic Fuel Injection (EFI). Steady state testing showed that the AFI delivers complete freedom for specifying injection timing with respect to HC emissions. This freedom is highly advantageous for transient conditions because open valve injection with small droplets causes much less port wall wetting. Therefore, less control system compensation is necessary, and more accurate air-fuel ratio control is achievable.

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.

A new estimator for IC engine A/F ratio is described. A/F ratio is important for engine operation since it determines the quantities of engine emissions, such as HC, CO, NOx, the conversion efficiency of catalyst systems, and the engine combustion stability. The A/F ratio estimator described in this paper is based on a fundamental metric that relies on inducing and detecting crankshaft speed fluctuations caused by modulating the engine's fuel injection pulse widths. Fuel pulse width modulation varies the instantaneous combustion A/F ratio crankshaft velocity. Synchronous measurement of crankshaft velocity provides a metric that, when used with other engine state variables as inputs to a conventional neural network, can accurately estimate A/F ratio. The estimator provides A/F information when a physical sensor is not available.

This paper describes the development of a Matrixx Model of an electronically controlled on-demand 4 Wheel-Drive (4WD) Transfer Case. The model was partially validated with respect to available vehicle test data and subsequently used for control system design and evaluation.

The tremendous growth of complexity in automotive control system electronics in the past 30 years has driven the industry to employ ever more advanced development techniques, ranging from formally managing functional architecture to employing more sophisticated functional safety development processes. The industry now finds itself facing emerging trends that will include more vehicle electrification, connectivity, personalization, and automation. Contextual and location awareness will also play larger roles. In light of these trends, vehicle control development processes will need to continue to evolve. This paper will explore some of the challenges that automakers will face as they move to incorporate these new technologies.

Hierarchical computer systems are an effective way of combining the features of mini- and maxi-computers in automation projects. By distributing the functions in a multi-computer system, the mini-computers can retain the responsiveness and reliability of simple configurations while the more extensive information handling is performed by the larger host computers. This approach overcomes most of the problems found with independent small control systems on one hand and over-extended, centralized computer systems on the other. This philosophy is illustrated with actual applications at Ford Motor Co.