This dissertation presents a new type of fuel control algorithm for gaseous fuelled vehicles. Gaseous fuels such as hydrogen and natural gas have been shown to be less polluting than liquid fuels such as gasoline, both at the tailpipe and on a total cycle basis. Unfortunately, it can be expensive to convert vehicles to gaseous fuels, partially due to small production runs for these vehicles. One of major development costs for a new vehicle is the development and calibration of the fuel controller. The research presented here includes a fuel controller which does not require an expensive calibration phase.<p>The controller is based upon a two-part model, separating steady state and dynamic effects. This model is then used to estimate the optimum fuelling for the measured operating condition. The steady state model is calculated using an artificial neural network with an online learning scheme, allowing the model to continually update to improve the controller's performance. This is important during both the initial learning of the characteristics of a new engine, as well as tracking changes due to wear or damage.<p>The dynamic model of the system is concerned with the significant transport delay between the time the fuel is injected and when the exhaust gas oxygen sensor makes the reading. One significant result of this research is the realization that a previous commonly used model for this delay has become significantly less accurate due to the shift from carburettors or central point injection to port injection.<p>In addition to a description of the control scheme used, this dissertation includes a new method of algebraically inverting a neural network, avoiding computationally expensive iterative methods of optimizing the model. This can greatly speed up the control loop (or allow for less expensive, slower hardware).<p>An important feature of a fuel control scheme is that it produces a small, stable limit cycle between rich and lean fuel-air mixtures. This dissertation expands the currently available models for the limit cycle characteristics of a system with a linear controller as well as developing a similar model for the neural network controller by linearizing the learning scheme.<p>One of the most important aspects of this research is an experimental test, in which the controller was installed on a truck fuelled by natural gas. The tailpipe emissions of the truck with the new controller showed better results than the OEM controller on both carbon monoxide and nitrogen oxides, and the controller required no calibration and very little information about the properties of the engine.<p>The significant original contributions resulting from this research include:<br> -collection and summarization of previous work,<br> -development of a method of automatically determining the pure time delay between the fuel injection event and the feedback measurement,<br> -development of a more accurate model for the variability of the transport delay in modern port injection engines,<br> -developing a fuel-air controller requiring minimal knowledge of the engine's parameters,<br> -development of a method of algebraically inverting a neural network which is much faster than previous iterative methods,<br> -demonstrating how to initialize the neural model by taking advantage of some important characteristics of the system,<br> -expansion of the models available for the limit cycle produced by a system with a binary sensor and delay to include integral controllers with asymmetrical gains,<br> -development of a limit cycle model for the new neural controller, and<br> -experimental verification of the controller's tailpipe emissions performance, which compares favourably to the OEM controller.

This dissertation presents a new type of fuel control algorithm for gaseous fuelled vehicles. Gaseous fuels such as hydrogen and natural gas have been shown to be less polluting than liquid fuels such as gasoline, both at the tailpipe and on a total cycle basis. Unfortunately, it can be expensive to convert vehicles to gaseous fuels, partially due to small production runs for these vehicles. One of major development costs for a new vehicle is the development and calibration of the fuel controller. The research presented here includes a fuel controller which does not require an expensive calibration phase.<p>The controller is based upon a two-part model, separating steady state and dynamic effects. This model is then used to estimate the optimum fuelling for the measured operating condition. The steady state model is calculated using an artificial neural network with an online learning scheme, allowing the model to continually update to improve the controller's performance. This is important during both the initial learning of the characteristics of a new engine, as well as tracking changes due to wear or damage.<p>The dynamic model of the system is concerned with the significant transport delay between the time the fuel is injected and when the exhaust gas oxygen sensor makes the reading. One significant result of this research is the realization that a previous commonly used model for this delay has become significantly less accurate due to the shift from carburettors or central point injection to port injection.<p>In addition to a description of the control scheme used, this dissertation includes a new method of algebraically inverting a neural network, avoiding computationally expensive iterative methods of optimizing the model. This can greatly speed up the control loop (or allow for less expensive, slower hardware).<p>An important feature of a fuel control scheme is that it produces a small, stable limit cycle between rich and lean fuel-air mixtures. This dissertation expands the currently available models for the limit cycle characteristics of a system with a linear controller as well as developing a similar model for the neural network controller by linearizing the learning scheme.<p>One of the most important aspects of this research is an experimental test, in which the controller was installed on a truck fuelled by natural gas. The tailpipe emissions of the truck with the new controller showed better results than the OEM controller on both carbon monoxide and nitrogen oxides, and the controller required no calibration and very little information about the properties of the engine.<p>The significant original contributions resulting from this research include:<br> -collection and summarization of previous work,<br> -development of a method of automatically determining the pure time delay between the fuel injection event and the feedback measurement,<br> -development of a more accurate model for the variability of the transport delay in modern port injection engines,<br> -developing a fuel-air controller requiring minimal knowledge of the engine's parameters,<br> -development of a method of algebraically inverting a neural network which is much faster than previous iterative methods,<br> -demonstrating how to initialize the neural model by taking advantage of some important characteristics of the system,<br> -expansion of the models available for the limit cycle produced by a system with a binary sensor and delay to include integral controllers with asymmetrical gains,<br> -development of a limit cycle model for the new neural controller, and<br> -experimental verification of the controller's tailpipe emissions performance, which compares favourably to the OEM controller.

Cylinder speed variations in a combustion engine is an unwanted phenomenon caused by a number of different reasons. Inaccurate fuel delivery from the individual injectors, resonance frequencies in the drive train and faulty sensor readings are some probable causes. There is a need to investigate the potential of different cylinder balancing controllers in a simulation environment before implementing them in the ECU hardware. The thesis is about developing a simulation framework where different controllers can be tested. The framework will generate an engine speed signal based on injected fuel mass to the individual cylinders. A PI controller that makes individual fuel adjustments to the cylinders is implemented in the framework and tested for three different operating points and three different types of disturbances. The results show that the framework is able to generate an accurate engine speed signal based on the commanded fuel amount. Moreover the controller is able to eliminate imbalances caused by error in injected fuel mass as well as specific type of periodic load disturbances in the drive line. Some disturbances cannot be handled by the PI controller, as they lie outside of its controllable region. The simulation framework shows promising results and while further work is needed in some areas, it can work as a foundation for future development and controller evaluation.

Indiana University-Purdue University Indianapolis (IUPUI) / Electronic Fuel Control (EFC) valve regulates fuel flow to the injector fuel supply line in the Cummins Pressure Time (PT) fuel system. The EFC system controls the fuel flow by means of a variable orifice that is electrically actuated. The supplier of the EFC valves inspects all parts before they are sent out. Their inspection test results provide a characteristic curve which shows the relationship between pressure and current provided to the EFC valve. This curve documents the steady state characteristics of the valve but does not adequately capture its dynamic response. A dynamic test procedure is developed in order to evaluate the performance of the EFC valves. The test itself helps to understand the effects that proposed design changes will have on the stability of the overall engine system. A by product of this test is the ability to evaluate returned EFC valves that have experienced stability issues. The test determines whether an EFC valve is faulted or not before it goes out to prime time use. The characteristics of a good valve and bad valve can be observed after the dynamic test. In this thesis, a mathematical model has been combined with experimental research to investigate and understand the behavior of the characteristics of different types of EFC valves. The model takes into account the dynamics of the electrical and mechanical portions of the EFC valves. System Identification has been addressed to determine the transfer functions of the different types of EFC valves that were experimented. Methods have been used both in frequency domain as well as time domain. Also, based on the characteristic patterns exhibited by the EFC valves, fuzzy logic has been implemented for the use of pattern classification.

No presente trabalho, emprega-se a medida da concentração de etanol do combustível para efetuar correções estequiométricas de maneira direta e instantânea, a fim de eliminar o período necessário para adaptação a partir da medida do sensor de oxigênio (sonda lambda) em eventos de reabastecimento no veículo. Com o objetivo de assegurar a operação flex-fuel, foram empregados métodos para a regulação ar/combustível em malha fechada, realimentados por sensores de oxigênio (banda larga amplificada e banda estreita). O projeto foi implementado em uma ECU (Eletronic Control Unit) idealizada para desenvolvimento de rotinas de programa voltadas ao gerenciamento eletrônico para motores de combustão interna ciclo Otto, denominada Flex-ECU. A ETAS/Bosch Flex-ECU possui programação aplicada à ferramenta ASCET (Advanced Simulation and Control Engineering Tool), o qual trata-se de um código open source para sistemas embarcados de tempo real. Por fim, são exibidos resultados de controle, desempenho e eficiência do motor para diferentes composições de combustível comercializados para a frota de veículos leves em território nacional. Os experimentos revelam a dinâmica de funcionamento do controle A/C bicombustível e discute as suas principais características, com o objetivo de exemplificar métodos de otimização de sua eficiência. / In the present work, the ethanol fuel concentration is used to establish stoichiometric corrections in a direct and instantaneous manner, to eliminate the period necessary for adaptation, from the measurement of the oxygen sensor (lambda probe) in events of refueling. To ensure Flex-fuel operation, closed-loop air/fuel regulation methods were used, fed by oxygen sensors (amplified wide band and narrow band). The project was implemented in an ECU (Electronic Control Unit) designed for the development of code routines for electronic management of an Otto cycle internal combustion engine, labeled Flex-ECU. The ETAS / Bosch Flex-ECU has programming applied to the ASCET (Advanced Simulation and Control Engineering Tool) tool, which is an open source code for real time embedded systems. Finally, results of engine control, performance, and efficiency are presented for different fuel compositions available in Brazil for the fleet of light vehicles. The experiments show the dynamics of the operation of the bi-fuel A/C control and discusses its main characteristics, aiming to exemplify optimization methods of its efficiency.

In Valencia region (SE Spain), many post-fire communities are dominated by non-resprouting (seeder) species, because of the long history of land exploitation and subsequent abandonment during the last half of 20th century. These communities accumulate fine dry biomass and, therefore, can burn again easily. In fact, Mediterranean forests are suffering from an increase in wildfire frequency since the early 1970s. Wildfires shape the composition and functioning of Mediterranean ecosystems, but we do not know how these ecosystems respond to both the higher fire recurrence and shorter recovery times expected for future climatic scenarios. In this sense, Aleppo pine forest (Pinus halepensis) is one of the most fire affected vegetation of this type in the Mediterranean Basin and to know how it respond to fire is fundamental to design management plans. After fire, regeneration of this forest can be highly variable, and it can go from extremely dense tree stands (overstocked pine) to treeless shrublands dominated by seeder species. All these regenerated stands are fire prone with limited ability to deliver multiple ecosystem services. Although several management techniques are applied to redirect these post-fire ecosystems towards less vulnerable and more functional communities, we do not know yet which amongst them could serve to foster more diverse and multifunctional landscapes. Therefore, the general objective of this thesis is to investigate the functioning of these Mediterranean ecosystems as consequence of shifts in fire regime and forest management application, using different techniques, in different post-fire regenerated ecosystems (overstocked pine forests and dense shrublands). To do so, we calculate, within Mediterranean Pinus halepensis forests affected by wildfires, the supply of multiple ecosystem services (biodiversity conservation, carbon sequestration, disturbance regulation, food production, supporting services, and multifunctionality), through up to 25 aboveground and belowground attributes. Our main findings are (1) High fire recurrence and time since last fire interacted to determine ecosystem services but did not affect their synergies and trade-offs between them. Their combined effects reduced carbon sequestration and multifunctionality. Disturbance regulation diminished drastically with the first fire, with no effect of further fires. However, their effects dampened, and even became positive, for biodiversity conservation and food production services if provided enough time to recover. (2) Thinning in overstocked pine stands enhances ecosystem attributes associated with biodiversity conservation without compromising the provision of carbon sequestration. After 10 years, two levels of thinning, (600 and 1200 trees·ha-1), similarly affected ecosystem attributes, which suggest that 1200 trees·ha-1 suffice to enhance individual ecosystem attributes. (3) Clearing within dense shrubland dominated by seeder species enhances ecosystem attributes associated with biodiversity conservation without compromising the capacity of ecosystem to sequester carbon. (4) Plantation of resprouting species combined with thinning and clearing, in overstocked pine forests and dense shrublands respectively, can enhance the provision of ecosystem services of disturbance regulation, food production and ecosystem multifunctionality. (5) Prescribed burning reduces the amount of dead fuel, increases biodiversity conservation, and improves food production. However, these effects become negative, in addition to the decline in disturbance regulation and multifunctionality, if prescribed burning is applied frequently. (6) Combining different management activities can enhance the supply of multiple ecosystem services simultaneously by reducing the trade-offs in between them and therefore, establish multifunctional Mediterranean landscapes.