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Carbon canisters have been adapted for automobile use since the early 1970s to control evaporative emissions. Stringent emission regulations and the requirement for an enhanced evaporative emissions test procedure, make this an important issue. The air and evaporative fuel from the carbon canister therefore need important consideration with respect to air to fuel ratio (AFR) control and idle by-pass air control. Although a few complex models of the activated carbon canister have been developed, a control-oriented, simplistic carbon canister model needs to be developed. This paper explores the control-oriented modeling of a canister purge air system along with the on-line estimation of evaporative fuel loading of the activated carbon. An attempt was made at providing an analytical expression for the evaporative fuel and air entering the intake manifold.

Fault diagnosis for automotive systems is driven by government regulations, vehicle repairability, and customer satisfaction. Several methods have been developed to detect and isolate faults in automotive systems, subsystems and components with special emphasis on those faults that affect the exhaust gas emission levels. Limit checks, model-based, and knowledge-based methods are applied for diagnosing malfunctions in emission control systems. Incipient and partial faults may be hard to detect when using a detection scheme that implements any of the previously mentioned methods individually; the integration of model-based and knowledge-based diagnostic methods may provide a more robust approach. In the present paper, use is made of fuzzy residual evaluation and of a fuzzy expert system to improve the performance of a fault detection method based on a mathematical model of the engine.

There is increasing interest in the use of alternative fuels for transportation, due to the increasing cost of petroleum based fuels. One possible alternative to the use of petroleum for transportation is to use electric grid power. This paper explores a possible design solution based on a plug-in fuel cell hybrid. A scaled down version of FC-HEV that is applicable to this concept, has been implemented as a proof of concept with fast prototyping toolkits, including a 32 bit micro processor, Matlab/Simulink software and an embedded system development kit. The resulting prototype vehicle demonstrated a high gasoline equivalent MPG as well as a successful functionality of micro grid power generation.

Due to the stringent emission regulations, On-Board Diagnostics II (OBD II) and the requirement of enhanced evaporative emissions test procedure, an aggressive canister purge control strategy is required for automotive vehicles. The enhanced evaporative emissions test procedure has forced car manufacturer to purge the carbon canister in the vehicle idle condition so that production vehicles meet the SHED and hot soak test requirements. This not only worsens the idle speed quality but also tends to increase exhaust emission levels. Using analytical models of evaporative air and fuel, feed-forward control strategy for both idle by-pass air and air to fuel ratio can be improved. This paper demonstrates an application of evaporative system modeling to the idle air and air to fuel ratio control.

The EcoCAR 2: Plugging into the Future team at the Ohio State University is designing a Parallel-Series Plug-in Hybrid Electric Vehicle capable of 50 miles of all-electric range. The vehicle features a 18.9-kWh lithium-ion battery pack with range extending operation in both series and parallel modes made possible by a 1.8-L ethanol (E85) engine and 6-speed automated manual transmission. This vehicle is designed to drastically reduce fuel consumption, with a utility factor weighted fuel economy of 75 miles per gallon gasoline equivalent (mpgge), while meeting Tier II Bin 5 emissions standards. This report details the rigorous design process followed by the Ohio State team during Year 1 of the competition. The design process includes identifying the team customer's needs and wants, selecting an overall vehicle architecture and completing detailed design work on the mechanical, electrical and control systems. This effort was made possible through support from the U.S.

We have performed an extensive study of cycle-to-cycle variation of engine knock and its occurrence in order to have a better understanding of engine knock. Experimental studies show the randomness of knock as well as its frequency varying nature. We propose using time-frequency based signal detection method to improve knock detection since this method can track frequency variations in the measured signals. The fundamental idea behind time-frequency analysis is to be able to understand and describe how the spectral content of a signal is changing in time. Classical signal analysis has traditionally dealt with time and frequency separately. Such individual descriptions are good in situation where spectral content of signals do not change with time; however, there are often signals that have time-varying spectral content such as engine knock. It is shown that one gains more information about knock signals using time-frequency analysis method.

The EcoCAR 2: Plugging into the Future team at the Ohio State University is designing a Parallel-Series Plug-in Hybrid Electric Vehicle capable of 50 miles of all-electric range. The vehicle features a 18.9-kWh lithium-ion battery pack with range extending operation in both series and parallel modes. This is made possible by a 1.8-L ethanol (E85) engine and 6-speed automated manual transmission. This vehicle is designed to drastically reduce fuel consumption, with a utility factor weighted fuel economy of 51 miles per gallon gasoline equivalent (mpgge), while meeting Tier II Bin 5 emissions standards. This report details the fabrication and control implementation process followed by the Ohio State team during Year 2 of the competition. The fabrication process includes finalizing designs based on identified requirements, building and assembling components, and performing extensive validation testing on the mechanical, electrical and control systems.

Engine knock has been recognized as a major problem limiting the development of fuel efficient spark-ignition engines. Detection methods employed in current knock control systems for spark ignition engines use a measurement of engine block vibration tuned to one or more resonance frequencies to extract knock-related information from the engine structural vibration. A major problem in the detection of knock (especially at higher engine speed) in commercial engines is the isolation of the desired signal from the contributions of the components other than those associated with the phenomenon under investigation. This is generally referred to as background noise. It is known that the engine knock resonance frequencies vary due to changes in combustion chamber volume and temperature during the expansion phase. Therefore, we propose an improved knock detection method using joint time-frequency analysis of engine block vibration and pressure signals.

A number of automotive diagnostic equipment and procedures have evolved over the last two decades, leading to two generations of on-board diagnostic requirements (OBDI and OBDII), increasing the number of components and systems to be monitored by the diagnostic tools. The goal of On-Board Diagnostic is to alert the driver to the presence of a malfunction of the emission control system, and to identify the location of the problem in order to assist mechanics in properly performing repairs. The aim of this paper is to suggest a methodology for the development of an Integrated Powertrain Diagnostic System (EPDS) that can combine the information supplied by conventional tailpipe inspection programs with onboard diagnostics to provide fast and reliable diagnosis of malfunctions.

In this paper, the detection and isolation of actuator faults (both measured and commanded) occurring in the engine breathing and the fueling systems of a spark-ignition direct-injection (SIDI) engine are described. The breathing system in an SIDI engine usually consists of a fresh air induction path via an electronically controlled throttle (ECT) and an exhaust gas recirculation (EGR) path via an EGR valve. They are dynamically coupled through the intake manifold to form a gas mixture, which eventually enters the engine cylinders for a subsequent combustion process. Meanwhile, the fueling system is equipped with a high-pressure common-rail injection for a precise control of the fuel quantity directly injected into the engine cylinders. Since the coupled system is highly nonlinear in nature, the fault diagnosis will be performed by generating residuals based on multiple nonlinear observers.

The integrity of the exhaust emission system in a passenger vehicle can best be maintained by monitoring its performance continuously on board the vehicle. It is with the intent of monitoring emission system performance that the California Air Resources Board has proposed regulations which will require vehicles to be equipped with on-board monitoring systems. These proposed regulations are known as OBDII and will probably be followed by similar Federal EPA regulations.This paper discusses a method of monitoring engine misfire as part of the OBDII requirements for passenger vehicle on-board diagnostics. The method is relatively inexpensive in that it uses an existing sensor for measuring instantaneous crankshaft angular position, and utilizes electronic signal processing which can be implemented in relatively inexpensive custom integrated circuits.

A prototype CO sensor based on anatase TiO2 was fabricated and tested in a Ford V6 engine. Fuel combustion was programmed to be near stoichiometric conditions, and emissions were monitored with an FT-IR analytical instrument. The sensor, positioned near the oxygen sensor in the exhaust manifold, was successfully tested for 50 cycles of revving and idling, and was observed to respond quickly and reproducibly. The sensor response was correlated to the CO concentration at specific engine temperatures and was found to vary systematically with increasing concentrations. This sensor has promising potentials to monitor the efficiency of the catalytic converter.

The EcoCAR 2: Plugging into the Future team at The Ohio State University is designing a Parallel-Series Plug-in Hybrid Electric Vehicle capable of 44 miles of all-electric range. The vehicle features an 18.9-kWh lithium-ion battery pack with range extending operation in both series and parallel modes. This is made possible by a 1.8-L ethanol (E85) engine and 6-speed automated manual transmission. This vehicle is designed to drastically reduce fuel consumption, with a utility factor weighted fuel economy of 50 miles per gallon gasoline equivalent (mpgge), while meeting Tier II Bin 5 emissions standards. This paper details three years of modeling and simulation development for the OSU EcoCAR 2 vehicle. Included in this paper are the processes for developing simulation platform and model requirements, plant model and soft ECU development, test development and validation, automated regression testing, and controls and calibration optimization.

The EcoCAR 2 team at the Ohio State University has designed an extended-range electric vehicle capable of 44 miles all-electric range, which features a 18.9-kWh lithium-ion battery pack with range extending operation in both series and parallel modes made possible by a 1.8-L ethanol (E85) engine and a 6-speed automated manual transmission. This vehicle is designed to reduce fuel consumption, with a utility factor weighted fuel economy of 50 miles per gallon gasoline equivalent (mpgge), while meeting Tier II Bin 5 emissions standards. This report documents the team's refinement work on the vehicle during Year 3 of the competition, including vehicle improvements, control strategy calibration and dynamic vehicle testing, culminating in a 99% buy off vehicle that meets the goals set forth by the team. This effort was made possible through support from the U.S. Department of Energy, General Motors, The Ohio State University, and numerous competition and local sponsors.

This year, in the third year of FutureTruck competition, the Ohio State University team has taken the challenge to convert a 2002 Ford Explorer into a more fuel efficient and environmentally friendly SUV. This goal was achieved by use of a post-transmission, charge sustaining, parallel hybrid diesel-electric drivetrain. The main power source is a 2.5-liter, 103 kW advanced CIDI engine manufactured by VM Motori. A 55 kW Ecostar AC induction electric motor provides the supplemental power. The powertrain is managed by a state of the art supervisory control system which optimizes powertrain characteristics using advanced energy management and emission control algorithms. A unique driver interface implementing advanced telematics, and an interior designed specifically to reduce weight and be more environmentally friendly add to the utility of the vehicle as well as the consumer appeal.

The evolution of the diagnostic equipment for automotive application is the direct effect of the implementation of sophisticated and high technology control systems in the new generation of passenger cars. One of the most challenging issues in automotive diagnostics is the ability to assess, to analyze, and to integrate all the information and data supplied by the vehicle's on-board computer. The data available might be in the form of fault codes or sensors and actuators voltages. Moreover, as environmental regulations get more stringent, knowledge of the concentration of different species emitted from the tailpipe during the inspection and maintenance programs can become of great importance for an integrated powertrain diagnostic system. A knowledge-based diagnostic tool is one of the approaches that can be adopted to carry out the challenging task of detecting and diagnosing faults related to the emissions control system in an automobile.

One of the gray areas in the implementation of regulations limiting the generation of pollutants from mobile sources is the actual effectiveness of the exhaust gas emissions control strategy in vehicles that have been in use for some time. While it is possible today to conduct limited diagnostics with the on-board engine computer by performing periodic checks to verify the validity of the signals measured by the on-board sensors, and to measure tailpipe emissions during routine inspection and maintenance, the task of correlating these measurements with each other to provide an on-line, accurate diagnosis of critical malfunctions has thus far proven to be a very challenging task, especially in the case of misfire.

Ensuring the reliable operation of the emissions control system is a critical factor in complying with increasingly stringent exhaust emissions standards. In spite of significant advances, the performance of available diagnostic and test equipment is still amenable to further improvement, especially as it pertains to the diagnosis of incipient and intermittent faults. This paper presents experimental results pertaining to the diagnosis of complete, partial and intermittent faults in various components of the engine emissions control system. The instrumentation used in the study permitted simultaneous and essentially continuous analysis of the exhaust gases and of engine variables. Tests were conducted using a section of the EPA urban driving cycle (I/M 240), simulated by means of a throttle/dynamometer controller.