The work reported in this thesis was conducted to study the effects of variable valve actuation on combustion, emissions, and fuel economy in a modern design of 4-valve per cylinder SI engine. The use of statistically-based procedures for the design of experiments allowed a limited number of tests to be used to explore a wide region of each of the experimental variables. A series of steady-flow tests was conducted to assess the effects of valve lift on flow past the valves and the nature of any in-cylinder motion generated. Results from the former were incorporated into a filling and emptying model that allowed levels of trapped residuals and pumping work to be estimated for different valve strategies. The in-cylinder motion tests explored asymmetric valve lifts, that is to say where the two valves were opened by a different amount. These results allowed a pair of response surfaces to be established to model the intensity of both axial and barrel swirl within the cylinder over the range of valve lifts. Engine tests were conducted in two parts. The first explored the effects of changes in exhaust event phasing, intake event phasing, intake event duration, and peak intake valve lift. The design of the experiment allowed linear, quadratic, and interactions between the variables to be modelled using regression analysis. Statistical analysis allowed the most influential factors (both main effects and interactions) to be identified. Contour plots of the modelled response were used to draw conclusions about the nature of the response surface and to isolate the effects of valve opening and closure angles as well as overlap. The results were correlated with those from the steady-flow tests and from the computer model. The strategy for the second phase of tests was chosen after considering the previous results. The steady-flow tests indicated that there was considerable potential for enhancing in-cylinder motion by adopting a valve deactivation strategy and combining it with a low lift of the active intake valve. The second phase investigated the use of such a technique in conjunction with large overlaps over a range of duration of the intake valve event. The results from both phases of engine tests indicated possible strategies to reduce emissions from future engines.

Stringent government mandates for the fuel economy and emissions of light-duty consumer vehicles have forced manufacturers to focus on improvements in these areas. Increased consumer pressure has also shifted the automobile market towards higher efficiency vehicles. This study investigates the use of intelligent engine peripheral control to improve fuel efficiency and reduce vehicle emissions. The conventional automotive alternator control strategy contributes to higher overall vehicle losses and increased fuel consumption through indiscriminate loading of the engine. The improved method focuses on the selective reduction of engine loading and the recapture of vehicle energy during braking using intelligent control of the alternator system. The concept was demonstrated on the Mississippi State University Challenge X hybrid vehicle. The fuel economy and NOx emissions of the vehicle were improved by 6.6% and 10.5% respectively over the drive cycle developed by the 2006 Mississippi State University Challenge X team to evaluate emissions.

Dans le contexte où le secteur automobile apparaît comme l’un des principaux émetteurs de gaz à effet de serre, des efforts doivent être apportés pour répondre à des normes antipollution de plus en plus contraignantes. L’objectif de la thèse est alors de développer un système qui aide le conducteur à adopter globalement une conduite plus économique, et qui plus est, écologique et sécuritaire. Notre approche se différencie des études et systèmes déjà existants par la stratégie utilisée. Celle-ci prend à la fois en compte les caractéristiques du véhicule, celles de l’infrastructure (pente, dévers, courbure) et surtout les contraintes sécuritaires que doit respecter le conducteur (limitation de vitesse légale, distance intervéhiculaire). Partant de ces informations, le problème d’optimisation de la consommation en carburant est formulé et résolu par la programmation dynamique. La stratégie de calcul en ligne est par la suite adoptée pour rendre le système adaptatif aux conditions de trafic. C’est ainsi que, sur la base de cette stratégie, le couplage entre le problème de sécurité routière et de réduction de consommation est réalisé. Des expérimentations de ce système informatif suggestif sur véhicule prototype montrent que le suivi des consignes, données par le système, est tout à fait réalisable par le conducteur. Ces essais confirment aussi le potentiel d’économie en carburant et l’amélioration de la sécurité grâce à notre système. En comparaison avec le style d’éco-conduite des conducteurs, l’économie en carburant en moyenne est de 7.5% et peut atteindre 12.9% et des réductions des dépassements de vitesse de 50% en moyenne et atteint près de 80% pour certains conducteurs. / In the context where the automobile sector represents one of the major greenhouse gas emitters, significant efforts should be made to answer the demand for increasingly restricted emissions standards. The object of this thesis is to develop a fuel-efficient support tool which helps the driver to adopt more economical, ecological and safe driving. our approach differs from studies in the literature by the introduction of a strong coupling of fuel optimization and safety maintaining problems. As inputs of the system, we use the vehicle states such as the vehicle and engine speeds, the gear used, the road geometry and information related to safety (inter-vehicle speed, traffic conditions, legal speed limit...). Optimisation algorithms compute in real-time a speed and gear profile for fuel economy and improvement of safety.. The experimental results of this informative and suggestive system show that instructions, given by the system, are quite feasible by the driver. These tests also confirm the potential for fuel economy and the safety

<p>In modern heavy vehicles low fuel consumption as well as good ride comfort and driveability is desired. Assuming that the road altitude ahead of the vehicle is known the optimal control regarding fuel and time consumption can be calculated. However this results in a bang-singular-bang control which decreases the ride comfort by introducing high jerk levels and oscillations in acceleration as well as jerk originating from the dynamics in the driveline.</p><p>In this thesis several methods to supress these behaviours are presented. A qualitative study of the methods impact on ride comfort as well as fuel and time consumption is carried out. A driveline model is implemented in Simulink and used for the evaluations. The aim is not to find a optimal strategy but rather to suggest methods and evaluate these as far as can be done in simulation to enable for future test runs.</p>

This study is concentrated on modelling and developing the controller for the light-duty hybrid electric truck. The hybrid electric vehicle has advantages in fuel economy. However, there have been relatively few studies on commercial HEVs, whilst a considerable number of studies on the hybrid electric system have been conducted in the field of passenger cars. So the current status and the methodologies to develop the LD hybrid electric truck model have been studied through the literature review. The modelling process used in this study is divided into three major stages. The first stage is to determine the structure of the hybrid electric truck and define the hardware. The second is the component modelling using the AMESim simulation tool to develop a forward facing model. In order to complete the component modelling, the information and data were collected from various sources including references and ADVISOR. The third stage is concerned with the controller which was written in Simulink. This was run in a co-simulation with the AMESim vehicle model. Through the initial simulation, the charge-sustaining performance of this controller was verified and improved. Finally, the simulations for the complete model were carried out over a number of drive cycles, such as CBDTRUCK, JE05, and TRL LGV drive cycle, to evaluate and analyse the effect on the fuel economy and the vehicle performance by the engine operating zone and the EM power capacity. The report presents a comparison of the fuel efficiency of the conventional vehicle and the LD hybrid electric truck. The results obtained by the simulation show the feasibility to build the complete vehicle with the designed controller.

In modern heavy vehicles low fuel consumption as well as good ride comfort and driveability is desired. Assuming that the road altitude ahead of the vehicle is known the optimal control regarding fuel and time consumption can be calculated. However this results in a bang-singular-bang control which decreases the ride comfort by introducing high jerk levels and oscillations in acceleration as well as jerk originating from the dynamics in the driveline. In this thesis several methods to supress these behaviours are presented. A qualitative study of the methods impact on ride comfort as well as fuel and time consumption is carried out. A driveline model is implemented in Simulink and used for the evaluations. The aim is not to find a optimal strategy but rather to suggest methods and evaluate these as far as can be done in simulation to enable for future test runs.

No description available.

The automotive industry is in a state of flux at the moment. Traditional combustion engine technologies are becoming challenged by newer, more efficient and environmentally friendly propulsion methods. These include bio-fuel, hybrid, and hydrogen fuel-cell technologies. Propulsion alone, however, is not the only area where improvements can be made in vehicle efficiency. Current vehicle research and development focuses heavily on propulsion systems with relatively few resources dedicated to auxiliary systems. These auxiliary systems, however, can have a significant impact on overall vehicle efficiency and fuel economy. The objective of this work is to improve the efficiency of a Fuel Cell Electric Vehicle (FCEV) through intelligent auxiliary system control. The analysis contained herein is applicable to all types of vehicles and may find applications in many vehicle architectures. A survey is made of the various types of alternative fuels and vehicle architectures from conventional gasoline vehicles to hybrids and fuel cells. Trends in auxiliary power systems and previous papers on control of these systems are discussed. The FCEV developed by the University of Waterloo Alternative Fuels Team (UWAFT) is outlined and the design process presented. Its powertrain control strategy is analyzed with a proposal for modifications as well as the addition of an auxiliary control module to meet the aforementioned objectives. Simulations are performed to predict the efficiency and fuel economy gains that can potentially be realized using these proposed techniques. These gains prove to be significant, with an almost 2% improvement realized through intelligent control of the air conditioning compressor, and further gains possible through other auxiliary power reduction techniques.

The automotive industry is in a state of flux at the moment. Traditional combustion engine technologies are becoming challenged by newer, more efficient and environmentally friendly propulsion methods. These include bio-fuel, hybrid, and hydrogen fuel-cell technologies. Propulsion alone, however, is not the only area where improvements can be made in vehicle efficiency. Current vehicle research and development focuses heavily on propulsion systems with relatively few resources dedicated to auxiliary systems. These auxiliary systems, however, can have a significant impact on overall vehicle efficiency and fuel economy. The objective of this work is to improve the efficiency of a Fuel Cell Electric Vehicle (FCEV) through intelligent auxiliary system control. The analysis contained herein is applicable to all types of vehicles and may find applications in many vehicle architectures. A survey is made of the various types of alternative fuels and vehicle architectures from conventional gasoline vehicles to hybrids and fuel cells. Trends in auxiliary power systems and previous papers on control of these systems are discussed. The FCEV developed by the University of Waterloo Alternative Fuels Team (UWAFT) is outlined and the design process presented. Its powertrain control strategy is analyzed with a proposal for modifications as well as the addition of an auxiliary control module to meet the aforementioned objectives. Simulations are performed to predict the efficiency and fuel economy gains that can potentially be realized using these proposed techniques. These gains prove to be significant, with an almost 2% improvement realized through intelligent control of the air conditioning compressor, and further gains possible through other auxiliary power reduction techniques.

A Hybrid Electric Vehicle (HEV) is a complex electro-mechanical-chemical system that involves two or more energy sources. The inherent advantages of HEVs are their increased fuel economy, reduced harmful emissions and better vehicle performance. The extent of improvement in fuel economy and vehicle performance greatly depends on selecting optimal component sizes. The complex interaction between the various components makes it difficult to size specific components manually or analytically. So, simulation-based multi-variable design optimization is a possible solution for such kind of system level design problems. The multi-modal, noisy and discontinuous nature of the Hybrid Vehicle design requires the use of derivativeree global algorithms because the derivative-based local algorithms work poorly with such design problems. In this thesis, a Hybrid Vehicle is optimized using various Global Algorithms ? DIviding RECTangles (DIRECT), Simulated Annealing (SA), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO). The objective of this study is to increase the overall fuel economy on a composite of city and highway driving cycle and to improve the vehicle performance. The performance of each algorithm is compared on a six variable hybrid electric vehicle design problem. Powertrain System Analysis Tool (PSAT), a state-of-the-art powertrain simulator, developed in MATLAB/Simulink environment by Argonne National Laboratory is used as the vehicle simulator. Further, a Hybrid algorithm that is a combination of global and local algorithm is developed to improve the convergence of the global algorithms. The hybrid algorithm is tested on two simple mathematical functions to check its efficiency.