Search Results

Two-stage turbochargers are a recent solution to improve engine performance. The large flexibility of these systems, able to operate in different modes, can determine a reduction of the turbo-lag phenomenon and improve the engine tuning. However, the presence of two turbochargers that can be in part operated independently requires effort in terms of analysis and optimization to maximize the benefits of this technology. In addition, the design and calibration of the control system is particularly complex. The transitioning between single stage and two-stage operations poses further control issues. In this scenario a model-based approach could be a convenient and effective solution to investigate optimization, calibration and control issues, provided the developed models retain high accuracy, limited calibration effort and the ability to run in real time.

This paper describes the development and experimental validation of a Plug-in Hybrid Electric Vehicle (PHEV) dynamic simulator that enables development, testing, and calibration of a traction control strategy. EcoCAR 2 is a three-year competition between fifteen North American universities, sponsored by the Department of Energy and General Motors that challenges students to redesign a Chevrolet Malibu to have increased fuel economy and decreased emissions while maintaining safety, performance, and consumer acceptability. The dynamic model is developed specifically for the Ohio State University EcoCAR 2 Team vehicle with a series-parallel PHEV architecture. This architecture features, in the front of the vehicle, an ICE separated from an automated manual transmission with a clutch as well as an electric machine coupled via a belt directly to the input of the transmission. The rear powertrain features another electric machine coupled to a fixed ratio gearbox connected to the wheels.

For simulation and analysis of vehicles there is a need to have a means of generating drive cycles which have properties similar to real world driving. A method is presented which uses measured vehicle speed from a number of vehicles to generate a Markov chain model. This Markov chain model is capable of generating drive cycles which match the statistics of the original data set. This Markov model is then used in an iterative fashion to generate drive cycles which match constraints imposed by the user. These constraints could include factors such number of stops, total distance, average speed, or maximum speed. In this paper, systematic analysis was done for a PHEV fleet which consists of 9 PHEVs that were instrumented using data loggers for a period of approximately two years. Statistical analysis using principal component analysis and a clustering approach was carried out for the real world velocity profiles.

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.

An appropriate fault diagnosis and Isolation (FDI) strategy is very useful to prevent system failure. In this paper, a model-based fault diagnosis strategy is developed for an internal combustion engine (ICE) under speed control. Engine throttle fault and the manifold pressure sensor fault are detected and isolated. A nonlinear observer based residual generation approach is proposed. Manifold pressure and throttle are observed. Fault codes are designed with redundancy to prevent bit error. Performance of fault diagnosis strategy has been evaluated with simulations.

Two-stage turbochargers are a recent solution to improve engine performance, reducing the turbo-lag phenomenon and improving the matching. However, the definition of the control system is particularly complex, as the presence of two turbochargers that can be in part operated independently requires effort in terms of analysis and optimization. This work documents a characterization study of two-stage turbocharger systems. The study relies on a mean-value model of a Diesel engine equipped with a two-stage turbocharger, validated on experimental data. The turbocharger is characterized by a VGT actuator and a bypass valve (BPV), both located on the high-pressure turbine. This model structure is representative of a “virtual engine”, which can be effectively utilized for applications related to analysis and control. Using this tool, a complete characterization was conducted considering key operating conditions representative of FTP driving cycle operations.

In recent years, the increasing interest and requirements for improved engine diagnostics and control has led to the implementation of several different sensing and signal processing technologies. In order to optimize the performance and emission of an engine, detailed and specified knowledge of the combustion process inside the engine cylinder is required. In that sense, the torque generated by each combustion event in an IC engine is one of the most important variables related to the combustion process and engine performance. This paper introduces torque estimation techniques in the real-time basis for engine control applications using the measurement of crankshaft speed variation. The torque estimation scheme presented in this paper consists of two entirely different approaches, “Stochastic Analysis” and “Frequency Analysis”.

This paper shall present the design and development of a family of high power, high-speed transport and combat vehicles based on a common module. The system looks to maximize performance at both high-speed operation and low-speed, heavy/severe-duty operation. All-wheel drive/steer-by-wire autonomous traction modules provide the basis for the vehicle family. Each module can continuously develop 300-400 kW of power at the wheels and has nearly double peak capability, exploiting the flexibility of the electric traction system. The maximum starting tractive effort developed by one module can reach 10-15 tons, and the full rated power can be produced at speeds of 100 mph. This paper will present the design and layout of the autonomous modules. Details will be provided about the tandem electric axles, with electric differentials and independent steering.

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.

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.

This paper discusses the use of intelligent control techniques for the control of a parallel hybrid electric vehicle powertrain. Artificial neural networks and fuzzy logic are used to implement a load leveling strategy. The resulting vehicle control unit, a supervisory controller, coordinates the powertrain components. The presented controller has the ability to adapt to different drivers and driving cycles. This allows a control strategy which includes both fuel-economy and performance modes. The strategy was implemented on the Ohio State University FutureCar.

Crankshaft angular position measurements are fundamental to all modern automotive engines. These measurements are required to control fuel injection timing as well as ignition timing. However, many other functions can be performed from such measurements through the use of advanced signal processing. These additional functions are essentially diagnostic in nature although there is potential for substitution of primary fuel and ignition control functions. This paper illustrates the application of crankshaft angular position measurement to the estimation of individual cylinder indicated and/or brake torque in IC engines from measurement of crankshaft position/velocity.

The introduction of advanced electronic controls in passenger vehicles over the last decade has made traditional diagnostic methods inadequate to satisfy on- and off-board diagnostic needs. Due to the complexity of today's automotive control systems, it is imperative that appropriate diagnostic tools be developed that are capable of satisfying current and projected service and on-board requirements. 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. It is our contention that significant improvement is possible in these areas. This paper briefly summarizes the evolution of on- and off-board diagnostic tools documented in the published literature, with the aim of giving the reader an understanding of their capabilities and limitations, and it further proposes alternative solutions that may be adopted as a basis for an advanced diagnostic instrument.

Legislation pertaining to automobile emissions has caused an increased focus on the cold-start performance of internal combustion engines. Of particular concern is the period of time before all available sensors become active. Present engine control strategies must rely on methods other than feedback control while these sensors are not active. Without feedback control during this critical period, engine emissions performance is not optimized. These conditions cause difficulty in performing comprehensive cold-start experiments. For these reasons, we have developed several methods for feedback control during cold-start to aid in laboratory investigations of engine emissions phenomena.

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.

An approach to fault diagnosis for internal combustion engines is considered. It is based on the estimation of cylinder indicated torque by means of sliding mode observers. Instead of measuring indicated pressure in cylinders directly, crankshaft speed is measured as the input of observers, which estimate the indicated torque. Several engine models are considered with different levels of complexity. The indicated torque estimation using sliding mode observers is based on the equivalent control method. The estimation technique is validated experimently on a research engine.

In recent years considerable interest has been placed on the detection of engine misfire. As part of the California Air Resources Board on-board diagnostics regulations for 1994 model year vehicles, misfire should be monitored continuously by the engine diagnostic system. It is expected that the next generation of on-board diagnostics regulations will demand monitoring of partial misfire as well. Several solutions to the misfire detection problem have been proposed and demonstrated for the detection of complete misfires. However, the performance of these methods in the presence of partial misfire is not altogether clear. The aim of this paper is to evaluate the performance of various misfire detection indices, all based on a measurement of crankshaft angular velocity, in the presence of partial misfire. The proposed algorithms are compared to a standard based on a measurement of indicated pressure.

The aim of this paper is to present the application of some signal processing and statistical analysis methods to the problem of detecting and isolating misfire occurrences in a twelve-cylinder high-performance engine. The method employed in this work is based on a measurement of engine angular velocity, processed in the frequency domain to extract a number of spectral components that are shown to be strongly affected by misfire events. These spectral components are then subject to a procedure known as Principal Components Analysis, in which the principal features of the angular speed waveform are extracted to generate individual cylinder misfire signatures. A clustering method is then implemented to permit the isolation of the cylinder responsible for the misfire. The paper briefly reviews the signal analysis method and presents experimental results supporting the validity of the approach.

This paper describes the background and development of a program focused on motorsports engineering education currently in progress at the Ohio State University (OSU). An interdisciplinary curriculum, with the involvement of various engineering departments, is being proposed for development in an attempt to address some of the engineering education needs of the motorsports industry. The program described in this paper strives to provide engineering students with an interdisciplinary background race engineering, and also provides opportunities for motorsports oriented thesis projects. The paper briefly summarizes the key elements of the curriculum, and describes how the integration of course material from different disciplines with team work on student competition projects, possibly coupled with internships with racing teams, can provide an ideal setting for the education of a new generation of race engineers.