Thèses : « Fuel consumpion »

1

Alghadhi, Mostafa. « Validation of vehicle fuel consumption ». Thesis, University of Huddersfield, 2015. http://eprints.hud.ac.uk/id/eprint/24697/.

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The state of environmental degradation demands that factors contributing to it be looked into. A chief cause of environmental degradation is exhaust emissions from vehicles, especially passenger cars. This paper attempts to quantify the relationship between vehicle fuel emissions and the various factors that contribute to it such as speed, acceleration, throttle position etc. The central contention was to come up with anempirical correlation that could be used to reliably tabulate the fuel consumption of a passenger vehicle. The derivation of an empirical correlation between vehicle fuel consumption and the factors contributing to it would allow an optimisation of vehicle fuel consumption to reduce greenhouse gas emissions. Using a comparison of different driving cycles, the New European Driving Cycle (NEDC) was taken as the basic framework for testing. The research was carried out in two different phases i.e. laboratory testing and real life drive tests. Laboratory testing was utilised to generate the major parameters that affected vehicle fuel consumption. This was then used to derive an empirical correlation that was then tested in the field to determine its validity. The proposed empirical correlation was tested against real life driving conditions which proved the reliability of the empirical correlation. A number of different driving conditions were simulated including urban driving, extra urban driving and highway driving. The varied testing scheme ensured that the empirical correlation was valid for various driving situations at the same time. The derivation of such an empirical correlation through this work removed one of the chief defects of different driving cycles which was the lack of standardisation for testing. With the application of this tested model it would be easier and convenient to control pollution considerably through additional research in the future.

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Rohani, Munzilah. « Bus driving behaviour and fuel consumption ». Thesis, University of Southampton, 2012. https://eprints.soton.ac.uk/352191/.

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The behaviour of driver is influenced by many factors, which include the personal characteristics (attitude, experience etc.) environmental (road geometry, traffic control etc.) and vehicle characteristics (performance, load etc.). Professional drivers, such as bus drivers, generally have higher levels of training and experience, and by virtue of their profession have attitudes, which are more likely to promote with save driving. However bus drivers experience the same environmental traffic condition as other drives, as well as additional constraints imposed by the vehicle characteristics, concern for passenger comfort/safety and the need to adhere to timetables. This research is focussed on understanding the behaviour differences both between and within bus drivers leaving from different types of stops. Understanding such differences will enable approaches to be developed to modifying behaviour so as to improve fuel consumption. A substantial database was collected with the cooperation of the UniLink bus operation in Southampton. The database consisted of detailed knowledge of bus location, instantaneous speed (reflecting the combination of behaviour and vehicle control), acceleration, accelerator pedal position(reflecting driver behaviour) and fuel consumption records. The data was gathered using a Portable Vehicle CANBus System (PVCS) combined with GLOBAL positioning System (GPS) on 2 buses. This research adopted advanced technology to mount the instantaneous accelerator pedal control of the driver, acceleration and fuel consumption. The devices used in this study provide a transferable methodology for the appraisal of fuel consumption saving through changes in acceleration behaviour (within 10 seconds leaving from stationary). The finding of this study revealed that the bus fuel consumption is sensitive to the level of acceleration. In the situation studied, the fuel consumption increased 67% for acceleration increase in the range 0.5 ms-2 to 1.5 ms-2 when leaving from stationary. More than 50 ml fuel is saved per acceleration within 10 second leaving from stationary if the driver reduces the rate of acceleration. Shifting driving behaviour from aggressive toward normal driving or from normal to economic save more than 20% or 40% fuel consumption respectively. However, the driving behaviour of the bus was influenced by factors such environment, passenger on board, and road condition that influences bus ability to accelerate and hence affect fuel consumption.

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3

Yue, Huanyu. « Mesoscopic Fuel Consumption and Emission Modeling ». Diss., Virginia Tech, 2008. http://hdl.handle.net/10919/26695.

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The transportation sector is a major contributor to U.S. fuel consumption and emissions. Consequently, assessing the environmental impacts of transportation activities is essential for air-quality improvement programs. Current state-of-the-art models estimate vehicle emissions based on typical urban driving cycles. Most of these models offer simplified mathematical expressions to compute fuel consumption and emission rates based on average link speeds while ignoring transient changes in a vehicleâ s speed and acceleration level as it travels on a highway network. Alternatively, microscopic models capture these transient effects; however, the application of microscopic models may be costly and time consuming. Also, these tools may require a level of input data resolution that is not available. Consequently, this dissertation attempts to fill the void in energy and emission modeling by a framework for modeling vehicle fuel consumption and emissions mesoscopically. This framework is utilized to develop the VT-Meso model using a number of data sources. The model estimates average light-duty vehicle fuel consumption and emission rates on a link-by-link basis using up to three independent variables, namely: average travel speed, average number of stops per unit distance, and average stop duration. The mesoscopic model utilizes a microscopic vehicle fuel consumption and emission model that was developed at Virginia Tech to compute mode-specific fuel consumption and emission rates. This model, known as VT-Micro, predicts the instantaneous fuel consumption and emission rates of HC, CO and NOx of individual vehicles based on their instantaneous speed and acceleration levels. The mesoscopic model utilizes these link-by-link input parameters to construct a synthetic drive cycle and compute average link fuel consumption and emission rates. After constructing the drive cycle, the model estimates the proportion of time that a vehicle typically spends cruising, decelerating, idling and accelerating while traveling on a link. A series of fuel consumption and emission models are then used to estimate the amount of fuel consumed and emissions of HC, CO, CO2, and NOX emissions for each mode of operation. Subsequently, the total fuel consumed and pollutants emitted by a vehicle while traveling along a segment are estimated by summing across the different modes of operation and dividing by the distance traveled to obtain distance-based average vehicle fuel consumption and emission rates. The models are developed for normal and high emitting vehicles. The study quantifies the typical driver deceleration behavior for incorporation within the model. Since this model constructs a drive cycle which includes a deceleration mode, an accurate characterization of typical vehicle deceleration behavior is critical to the accurate modeling of vehicle emissions. The study demonstrates that while the deceleration rate typically increases as the vehicle approaches its desired final speed, the use of a constant deceleration rate over the entire deceleration maneuver is adequate for environmental modeling purposes. Finally, the study validates the model on a freeway and urban arterial network. The results demonstrate that the model provides accurate estimates of vehicle fuel consumption and emission rates and is adequate for the evaluation of transportation operational projects.
Ph. D.

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4

Ahn, Kyoungho. « Microscopic Fuel Consumption and Emission Modeling ». Thesis, Virginia Tech, 1998. http://hdl.handle.net/10919/36471.

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Mathematical models to predict vehicle fuel consumption and emission metrics are presented in this thesis. Vehicle fuel consumption and emissions are complex functions to be approximated in practice due to numerous variables affecting their outcome. Vehicle energy and emissions are particularly sensitive to changes in vehicle state variables such as speed and acceleration, ambient conditions such as temperature, and driver control inputs such as acceleration pedal position and gear shift speeds, among others. Recent empirical studies have produced large amounts of data concerning vehicle fuel consumption and emissions rates and offer a wealth of information to transportation planners. Unfortunately, unless simple relationships are found between fuel consumption and vehicle emission metrics, their application in microscopic traffic and macroscopic planning models becomes prohibitive computationally. This thesis describes the development of microscopic energy and emission models using nonlinear multiple regression and neural network techniques to approximate vehicle fuel consumption and emissions field data. The energy and emission models described in this thesis utilized data collected by the Oak Ridge National Laboratory. The data include microscopic fuel consumption and emission measurements (CO, HC, and NOx) for eight light duty vehicles as a function of vehicle speed and acceleration. The thesis describes modeling processes and the tradeoffs between model accuracy and computational efficiency. Model verification results are included for two vehicle driving cycles. The models presented estimate vehicle fuel consumption within 2.5% of their actual measured values. Vehicle emissions errors fall in the range of 3-33% with correlation coefficients ranging between 0.94 and 0.99. Future transportation planning studies could also make use of the modeling approaches presented in the thesis. The models developed in this study have been incorporated into a microscopic traffic simulation tool called INTEGRATION to further demonstrate their application and relevance to traffic engineering studies. Two sample Intelligent Transportation Systems (ITS) application results are included. In the case studies, it was found that vehicle fuel consumption and emissions are more sensitive to the level of vehicle acceleration than to the vehicle speed. Also, the study shows signalization techniques can reduce fuel consumption and emissions significantly, while incident management techniques do not affect the energy and emissions rates notably.
Master of Science

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5

Burzlaff, Marcus. « Aircraft Fuel Consumption - Estimation and Visualization ». Aircraft Design and Systems Group (AERO), Department of Automotive and Aeronautical Engineering, Hamburg University of Applied Sciences, 2017. http://d-nb.info/1148997490.

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In order to uncover the best kept secret in today's commercial aviation, this project deals with the calculation of fuel consumption of aircraft. With only the reference of the aircraft manufacturer's information, given within the airport planning documents, a method is established that allows computing values for the fuel consumption of every aircraft in question. The aircraft's fuel consumption per passenger and 100 flown kilometers decreases rapidly with range, until a near constant level is reached around the aircraft's average range. At longer range, where payload reduction becomes necessary, fuel consumption increases significantly. Numerical results are visualized, explained, and discussed. With regard to today's increasing number of long-haul flights, the results are investigated in terms of efficiency and viability. The environmental impact of burning fuel is not considered in this report. The presented method allows calculating aircraft type specific fuel consumption based on publicly available information. In this way, the fuel consumption of every aircraft can be investigated and can be discussed openly.

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6

Ivan, Jean-Paul. « Principal Component Modelling of Fuel Consumption ofSeagoing Vessels and Optimising Fuel Consumption as a Mixed-Integer Problem ». Thesis, Mälardalens högskola, Akademin för utbildning, kultur och kommunikation, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-51847.

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The fuel consumption of a seagoing vessel is, through a combination of Box-Cox transforms and principal component analysis, reduced to a univariatefunction of the primary principle component with mean model error −3.2%and error standard deviation 10.3%. In the process, a Latin-hypercube-inspired space partitioning sampling technique is developed and successfully used to produce a representative sampleused in determining the regression coefficients. Finally, a formal optimisation problem for minimising the fuel use is described. The problem is derived from a parametrised expression for the fuel consumption, and has only 3, or 2 if simplified, free variables at each timestep. Some information has been redacted in order to comply with NDA restrictions. Most redactions are either names (of vessels or otherwise), units, andin some cases (especially on figures) quantities.

Presentation was performed remotely using Zoom.

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7

Adenfelt, Elin. « What happens when we have no more crude oil ? » Thesis, Konstfack, Industridesign, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:konstfack:diva-866.

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8

Salih, Fawzi Mohamed. « Automotive fuel economy measures and fuel usage in Sudan ». Thesis, University of Leeds, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.293763.

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9

Söderstedt, Fredrik. « Fuel Consumption Estimation for Vehicle Conﬁguration Optimization ». Thesis, Linköpings universitet, Fordonssystem, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-112259.

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Fuel consumption is one of the factors that are considered when deciding a vehicle’s optimal speciﬁcation. In order to swiftly estimate the fuel consumed during real world driving scenarios, a simulation tool has been developed that is well suited for vehicle conﬁguration exploration applications. The simulation method described in this paper diﬀers from the static calculation method currently in use at Scania cv since the dynamic translation of the vehicle is considered, yet the simulation time is kept low. By adopting a more dynamic approach, the estimation accuracy is increased and simulation of fuel saving technology, e.g. intelli- gent driver support system, is enabled. In this paper, the modeling and implementation process is described. Diﬀerent approaches is discussed and the choices made during the development is presented. In order to achieve a low simulation time and obtain a good compatability with Scania’s current software application, some of the inﬂuencial factors have been omitted from the model or described using simple relations. The validation of the fuel consumption estimation indicates an accuracy within three percent for motorway driving. Utilizing the newly devised simulation tool, a look-ahead cruise controller has been implemented and simulated. Instead of continuously ﬁnding the optimal control signals during the driving scenario like most look-aheadcontrollers, a dynamic programming algorithm is used to ﬁnd a fuel eﬃcient speed proﬁle for the entire route. The speed proﬁle is used as the reference speed for a conventional cruise controller and comparison with another simulation tool indicates that this is a fast and accurate way to emulate a real look-ahead controller.

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10

Cheung, Wing Ho. « Neural network aided aviation fuel consumption modeling ». Thesis, Virginia Tech, 1997. http://hdl.handle.net/10919/36998.

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This thesis deals with the potential application of neural network technology to aviation fuel consumption estimation. This is achieved by developing neural networks representative jet aircraft. Fuel consumption information obtained directly from the pilot's flight manual was trained by the neural network. The trained network was able to accurately and efficiently estimate fuel consumption of an aircraft for a given mission. Statistical analysis was conducted to test the reliability of this model for all segments of flight. Since the neural network model does not require any wind tunnel testing nor extensive aircraft analysis, compared to existing models used in aviation simulation programs, this model shows good potential. The design of the model is described in depth, and the MATLAB source code are included in appendices.
Master of Science

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11

Chen, Rongjun. « Utilization of upland phytomass for fuel / ». [Hong Kong] : University of Hong Kong, 1993. http://sunzi.lib.hku.hk/hkuto/record.jsp?B1354455X.

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12

Sivertsson, Martin. « Optimization of Fuel Consumption in a Hybrid Powertrain ». Thesis, Linköpings universitet, Fordonssystem, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-63563.

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Increased environmental awareness together with new legislative demands on lowered emissions and a rising fuel cost have put focus on increasing the fuel efficiency in new vehicles. Hybridization is a way to increase the efficiency of the powertrain.The Haldex electric Torque Vectoring Device is a rear axle with a built in electric motor, designed to combine all-wheel drive with hybrid functionality. A method is developed for creating a real time control algorithm that minimizes the fuel consumption. First the consumption reduction potential of the system is investigated using Dynamic Programming. A real time control algorithm is then devised that indicates a substantial consumption reduction potential compared to all-wheel drive, under the condition that the assumed and measured efficiencies are accurate. The control algorithm is created using equivalent consumption minimization strategy and is implemented without any knowledge of the future driving mission. Two ways of adapting the control according to the battery state of charge are proposed and investigated. The controller optimizes the torque distribution for the current gear as well as assists the driver by recommending the gear which would give the lowest consumption. The simulations indicate a substantial fuel consumption reduction potential even though the system primarily is an all-wheel drive concept. The results from vehicle tests show that the control system is charge sustaining and the driveability is deemed good by the test-drivers.

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13

Macias, Ajaillo Daniel. « Estimation of Fuel Consumption for Real Time Implementation ». Thesis, KTH, Reglerteknik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-98871.

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With an unstable oil market and increasing prices, the focus has never been higher on reducing the fuel consumption costs. Using a navigation system that presents the fastest route, can today help a driver to reduce the fuel consumption by reducing the risk of not finding the target. A further development of such system is eco-routing: route optimization with regard to fuel consumption. Eco-routing is today being introduced to the market by several passenger car manufacturers. An essential part of an eco-routing system is estimation of fuel consumption. The requirements of a fuel consumption model for trucks is studied in this thesis. Two estimation methods were evaluated and compared, one of the methods was estimating fuel consumption using look up tables consisting fuel consumption data. The other method was estimation doing real time calculations with a fuel consumption model. With a simplified real time model the modelling error was approximately lower than 5% for rural and highway driving, however for city driving the accuracy was significantly reduced. Ecorouting simulations for a truck showed a mean saving of 8.5% for a set of long haulage routes.

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14

Schilling, Glenn D. « Modeling Aircraft Fuel Consumption with a Neural Network ». Thesis, Virginia Tech, 1997. http://hdl.handle.net/10919/36533.

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This research involves the development of an aircraft fuel consumption model to simplify Bela Collins of the MITRE Corporation aircraft fuelburn model in terms of level of computation and level of capability. MATLAB and its accompanying Neural Network Toolbox, has been applied to data from the base model to predict fuel consumption. The approach to the base model and neural network is detailed in this paper. It derives from the basic concepts of energy balance. Multivariate curve fitting techniques used in conjunction with aircraft performance data derive the aircraft specific constants. Aircraft performance limits are represented by empirical relationships that also utilize aircraft specific constants. It is based on generally known assumptions and approximations for commercial jet operations. It will simulate fuel consumption by adaptation of a specific aircraft using constants that represent the relationship of lift-to-drag and thrust-to-fuel flow. The neural network model invokes the output from MITRE1s algorithm and provides: (1) a comparison to the polynomial fuelburn function in the fuelburn post- processor of the FAA Airport and Airspace Simulation Model (SIMMOD), (2) an established sensitivity of system performance for a range of variables that effect fuel consumption, (3) a comparison of post fuel burn (fuel consumption algorithms) techniques to new techniques, and (4) the development of a trained demo neural network. With the powerful features of optimization, graphics, and hierarchical modeling, the MATLAB toolboxes proved to be effective in this modeling process.
Master of Science

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15

Chen, Zehua. « Modeling of fuel consumption in a road network ». Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-281955.

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The fuel consumption accounts for a large portion of operational cost for logistics companies and hence building an accurate fuel prediction model is of the key importance. Recently machine learning methods have been widely used in this area, and data like historical GPS data, road conditions, weather conditions are involved when building such models. This study aims at investigating the possibility to replace the road condition features with an index that is constructed by aggregating the data collected and maintained by Scania. Two normalization methods are used for building fuel consumption index, some commonly used models including Support Vector Machine, Random Forest and Gradient Boosted Machines are trained and evaluated both with and without it. The experimental results show that the Random Forest model outperforms the others in most cases. By comparing the results with the previous studies, we can see that replacing road conditions by a fuel consumption index can lead to almost the same performance of machine learning models. To guarantee the reliability of this index, approximately 4000 to 5000 samples are expected for each road segment, this is however not realistic for many of them. When predicting fuel consumption for a given route, the more road segments with adequate samples it contains, the higher predictive accuracy we can expect.
För logistikföretag står bränsleförbrukningen för en stor del av driftskostnaden och därför är det viktigt att bygga en exakt modell för bränsleprognos. Under senare år har maskininlärningsmetoder använts i stor utsträckning inom detta område, och data som historiska GPS-positioner, vägförhållanden och väderförhållanden är involverade när man bygger dessa modeller. Denna studie syftar till att undersöka möjligheten att ersätta karrakteristika beskrivande vägtillståndet med ett index som är konstruerat genom att använda de uppgifter som samlas in och underhålls av Scania. Två normaliseringsmetoder används för att bygga bränsleförbrukningsindex. En uppsättning vanliga modeller inkluderande supportvektormaskinen, Random Forest och Gradient Boosted Machines tränas och utvärderas både med och utan normalisering. De experimentella resultaten visar att Random Forest-modellen överträffar de andra i de flesta fall. Genom att jämföra resultaten med tidigare studier kan vi se att byte av vägförhållandekarrakteristika mot ett bränsleförbrukningsindex kan leda till nästan samma prestanda som maskininlärningsmodeller. För att garantera tillförlitligheten för detta index behövs cirka 4000 till 5000 prover för varje vägsegment, men detta är dock inte realistiskt för många av segmenten. När vi predicerar bränsleförbrukningen för en given rutt blir förväntad prediktionsnoggranhet högre desto fler vägsegment med adekvata dataprover den innehåller.

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16

Ekström, Lukas. « Estimating fuel consumption using regression and machine learning ». Thesis, KTH, Optimeringslära och systemteori, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-235819.

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This thesis focuses on investigating the usage of statistical models for estimating fuel consumption of heavy duty vehicles. Several statistical models are assessed, along with machine learning using artiﬁcial neural networks. Data recorded by sensors on board trucks in the EU describe the operational usage of the vehicle. The usage of this data for estimating the fuel consumption is assessed, and several variables originating from the operational data is modelled and tested as possible input parameters. The estimation model for real world fuel consumption uses 8 parameters describing the operational usage of the vehicles, and 8 parameters describing the vehicles themselves. The operational parameters describe the average speed, topography, variation of speed, idling, and more. This model has an average relative error of 5.75%, with a prediction error less than 11.14% for 95% of all tested vehicles. When only vehicle parameters are considered, it is possible to make predictions with an average relative error of 9.30%, with a prediction error less than 19.50% for 95% of all tested vehicles. Furthermore, a computer software called Vehicle Energy Consumption Calculation tool(VECTO) must be used to simulate the fuel consumption for all heavy duty vehicles, according to legislation by the EU. Running VECTO is a slow process, and this thesis also investigates how well statistical models can be used to quickly estimate the VECTO fuel consumption. The model estimates VECTO fuel consumption with an average relative error of 0.32%and with a prediction error less than 0.65% for 95% of all tested vehicles.
Denna rapport fokuserar på att undersöka användningen av statistiska mod-eller för att uppskatta bränsleförbrukningen hos tunga fordon. Flera statistiska modeller utvärderas, tillsammans med maskinlärning med artiﬁciella neurala nätverk. Data som registreras av sensorer ombord på Scania-lastbilar i EU beskriver fordonets drift. Användningen av dessa data för att uppskatta bränsleförbrukningen undersöks och ﬂera variabler som kommer från operativa data modelleras och testas som möjliga in-parametrar. Uppskattningsmodellen för den verkliga bränsleförbrukningen använder 8 parametrar som beskriver användningen av fordonet och 8 parametrar som beskriver själva fordonet. Bland annat beskrivs medelhastighet, topograﬁ, hastighetsvariation, andel tomgång. Denna modell har ett genomsnittligt relativfel på 5.75 %, med ett skattningsfel mindre än 11.14% för 95% av de de fordon som testats. Om endast fordonsparametrar beaktas som in-parametrar är det möjligt att göra skattningar med ett genomsnittligt relativfel på 9.30 %, med ett skattningsfel mindre än 19.50% för 95% av de de fordon som testats. Ett datorprogram kallat VECTO måste användas för att simulera bränsleförbrukningen för alla tunga fordon enligt EU-lagstiftning. Att köra VECTO är en tidskrävande process, och denna rapport undersöker också hur väl statistiska modeller kan användas för att snabbt uppskatta VECTO-bränsleförbrukningen. Modellen uppskattar VECTO-bränsleförbrukningen med ett genomsnittligt relativfel på 0.32% och med ett skattningsfel mindre än 0.65% för 95% av de de fordon som testats.

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Aksoy, Can Aksoy. « Fuel consumption measurements and fuelconditioning in high-pressure fuel systemfor single cylinder test cell ». Thesis, Karlstads universitet, Fakulteten för hälsa, natur- och teknikvetenskap (from 2013), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-75439.

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This master thesis is part of a bigger project issued by AVL with the purpose to design a high pressure compression ignition fuel system for their single cylinder test cell at their facility in Södertälje. Typically compression-ignition fuel tests are being run within an operating pressure range of 500-2400 bar, but this system has to be able to run with pressures up to 3500 bar. The project was intended to be carried out by two participants where this master thesis covers the evaluation of how fuel consumption rates shall be measured in the system described above as well as how the fuel shall be conditioned. The selected concept for measuring fuel consumption rate was based on measuring the mass flow on the low-pressure side of the system with a Coriolis flowmeter. The chosen temperature sensor for monitoring the temperature on the high-pressure side was a K-type thermocouple which would be directly connected to the fuel rail in the system. A bleeder was selected on the basis that it had been used in one of AVL's old test cells. A heat exchanger could not be chosen. However a rough estimation of the capacity needed for a heat exchanger was calculated for future reference. The methodology used to develop a concept was based on the engineering project process taught to students at Karlstad University. First a project plan was made followed by a solution-independently expressed product specification including a specification of requirements and QFD-matrix. Several concepts were generated for measuring the fuel consumption by evaluating different measuring principles, available components, possible positions of the components within the system and combinations with different fuel supply concepts. Less extensive methods were used for the remaining tasks in the detailed engineering phase of the project. The concepts were compared using Pugh's analysis and a concept was selected in collaboration with AVL. The majority of the objectives for this master thesis could be successfully carried out. The documentation and drawings requested by the client, manufacturing of the system, implementation and validation into the test cell could not be done due to lack of time. This, along with the selection of a heat exchanger and low-pressure thermocouple was left for future work.

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18

陳榮均 et Rongjun Chen. « Utilization of upland phytomass for fuel ». Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1993. http://hub.hku.hk/bib/B29913482.

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Ramos, Paja Carlos Andrés. « Fuel cell modelling and control for hydrogen consumption optimization ». Doctoral thesis, Universitat Rovira i Virgili, 2009. http://hdl.handle.net/10803/8467.

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en Español:
Se propone un modelo de FC basado en ecuaciones electroquímicas para predicción del exceso de oxígeno y de la temperatura de la pila, permitiendo además una conexión circuital con la carga. Así mismo, se presenta una técnica de modelado basada en Fuzzy, orientada a la emulación, obteniendo gran precisión con carga computacional reducida. Usando este último modelo se diseña e implementa un emulador. Estos modelos y el sistema de emulación fueron validados usando un sistema experimental.
Adicionalmente, diferentes topologías de sistemas de potencia basados en FC se proponen y analizan, obteniendo un criterio de selección dependiendo de la aplicación. Así mismo, se presentan criterios de control para una operación segura y eficiente del sistema. Finalmente, se proponen una metodología para la caracterización de los puntos óptimos de operación, y una estructura de control para operar en esas condiciones óptimas, siendo validados en un sistema experimental representativo del estado del arte.
in English:
A new FC modeling approach based on electrochemical equations for thermal and oxygen excess ration prediction with a circuit-based load connection is introduced. A fuzzy-based modeling technique is also proposed for emulation purposes, it reproducing the fuel cell dynamics with a high accuracy and a short computational time. The implementation of a fuel cell emulation system, based on this model, is described and analyzed. The models and the emulation system are experimentally validated by using a benchmark fuel cell system.
Different topologies for fuel cell-auxiliary storage devices interaction are also proposed and analyzed, thus giving an architecture selection criterion based on the load profile. Controllers, dynamic constrains and control objectives are designed for a safe and efficient fuel cell operation. Finally, a methodology for the identification of the fuel cell optimal operation conditions has been proposed, and a control strategy for operating in that optimal profile is introduced and validated.

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Vogetseder, Georg. « Functional Analysis of Real World Truck Fuel Consumption Data ». Thesis, Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-1148.

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This thesis covers the analysis of sparse and irregular fuel consumption data of long

distance haulage articulate trucks. It is shown that this kind of data is hard to analyse with multivariate as well as with functional methods. To be able to analyse the data, Principal Components Analysis through Conditional Expectation (PACE) is used, which enables the use of observations from many trucks to compensate for the sparsity of observations in order to get continuous results. The principal component scores generated by PACE, can then be used to get rough estimates of the trajectories for single trucks as well as to detect outliers. The data centric approach of PACE is very useful to enable functional analysis of sparse and irregular data. Functional analysis is desirable for this data to sidestep feature extraction and enabling a more natural view on the data.

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Lodi, Faisal Samad. « Reducing cold start fuel consumption through improved thermal management ». Connect to thesis, 2008. http://repository.unimelb.edu.au/10187/3601.

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The thesis presents research in achieving faster warm-up of an SI engine, thereby affecting the fuel economy penalty. The faster warm-up relates to faster heating of the cylinder head and engine block, targeting reducing viscous friction in the cold oil as the most likely candidate to improve. The strategy applied was to reduce the coolant flow circulation rate to achieve a faster warm-up of the engine. A lumped parameter model for engine heat transfer, coolant flow and heat capacities, in a single cylinder, based on engine operating points like spark advance, engine speed and MAP was built in Modelica.
The engine used for experimentation was a Ford in-line, 4 stroke, 6-cylinder engine, with a compression ratio of 10.3:1, in which 56 K-type thermocouples were installed at different locations to measure the temperature. The experiments were performed with varying coolant flow rate from normal down to zero, utilizing an electric water pump, over an approximation to the New European Drive Cycle (NEDC), at a speed of 1161 rev/min and load of 48 Nm. The selected speed and load were the average operating condition for 180 seconds of engine running over the urban part of a simulated NEDC. In addition, the coolant circuit was modified to a split cooling supply and the sets of results analyzed to find the reduction in engine warm-up time and fuel consumption.
It is shown from the results that the warm-up time of the engine and the fuel consumption were notably reduced, as the flow was reduced from maximum to minimum in steps. On average over an interval of engine running for 300 seconds from cold start, the cylinder head temperature was increased by about 2°C , the average engine block temperature was increased by about 6.5°C and the average cylinder head coolant temperature was increased by about 4°C . However, the bulk temperature of the oil in the oil sump showed marginal improvement and remained consistent, even at the lowest coolant flow rate. Nonetheless, the improvements in block temperature had significant effects on reducing the friction between the piston and cylinder walls.
Analysis of the results show that the coolant flow pattern changed with the use of an electric water pump. The flow is less evenly distributed around the cylinders with the use of an electric water pump, whilst retaining the mechanical water pump body, compared to the mechanical water pump operation.
The model was applied to simulate for two engine operating points, i.e., 1161 rev/min, 48 Nm load and 700 rev/min and 0 Nm load. The model was calibrated at 1161 rev/min, 48 Nm load and validated at 700 rev/min, 0 Nm load. The modeling results were in fair agreement with the experimental results. The model can be employed to investigate electric water pump control.
The important finding is that around 3% fuel consumption savings are possible over the NEDC by management strategies that lead to faster cylinder block warm up, even though this may result in little or no change in oil temperature as measured in the sump.

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Hallvig, Richard. « Fuel Consumption Tuning for Electric All Wheel Drive System ». Thesis, Uppsala universitet, Signaler och System, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-197509.

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This report investigates methods to reduce fuel consumption in SAAB's prototype hybrid car. It is primarily concerned with changes in the final drive ratio (FDR) of the gearbox. Reducing the FDR lowers the engine speed, allowing the engine to run at a more efficient operating point. However, this has a negative impact on engine power and vehicle performance. It was thought that the hybrid's eXWD (electric cross wheel drive) system could make up for this loss of performance. Computer simulations showed significant improvements in fuel economy when the FDR was reduced. This was confirmed by real world tests on a chassis dynamometer, although the number of tests were too low to establish the precise fuel consumption reduction. The effects on performance were evaluated by creating a quasi static model of the drivetrain and calculating which combinations of speed and acceleration corresponded to the engine's torque limits. The loss of acceleration was found to be lower than the increase in acceleration made possible by eXWD for most choices of FDR. It is therefore possible to reduce the FDR in the hybrid version of the car and still maintain a performance advantage compared to the front wheel drive version. No other major disadvantageous effects were found. The conclusion was therefore that a reduction of the final drive ratio is a feasible method to improve the fuel economy of the prototype car, given that maximizing performance is deemed less important than increasing fuel economy.

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Lu, Tao. « The influence of pavement stiffness on vehicle fuel consumption ». Thesis, University of Nottingham, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.539177.

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Johnsen, Sofia, et Sarah Felldin. « Improving Knowledge of Truck Fuel Consumption Using Data Analysis ». Thesis, Linköpings universitet, Reglerteknik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-130047.

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The large potential of big data and how it has brought value into various industries have been established in research. Since big data has such large potential if handled and analyzed in the right way, revealing information to support decision making in an organization, this thesis is conducted as a case study at an automotive manufacturer with access to large amounts of customer usage data of their vehicles. The reason for performing an analysis of this kind of data is based on the cornerstones of Total Quality Management with the end objective of increasing customer satisfaction of the concerned products or services. The case study includes a data analysis exploring how and if patterns about what affects fuel consumption can be revealed from aggregated customer usage data of trucks linked to truck applications. Based on the case study, conclusions are drawn about how a company can use this type of analysis as well as how to handle the data in order to turn it into business value. The data analysis reveals properties describing truck usage using Factor Analysis and Principal Component Analysis. Especially one property is concluded to be important as it appears in the result of both techniques. Based on these properties the trucks are clustered using k-means and Hierarchical Clustering which shows groups of trucks where the importance of the properties varies. Due to the homogeneity and complexity of the chosen data, the clusters of trucks cannot be linked to truck applications. This would require data that is more easily interpretable. Finally, the importance for fuel consumption in the clusters is explored using model estimation. A comparison of Principal Component Regression (PCR) and the two regularization techniques Lasso and Elastic Net is made. PCR results in poor models difficult to evaluate. The two regularization techniques however outperform PCR, both giving a higher and very similar explained variance. The three techniques do not show obvious similarities in the models and no conclusions can therefore be drawn concerning what is important for fuel consumption. During the data analysis many problems with the data are discovered, which are linked to managerial and technical issues of big data. This leads to for example that some of the parameters interesting for the analysis cannot be used and this is likely to have an impact on the inability to get unanimous results in the model estimations. It is also concluded that the data was not originally intended for this type of analysis of large populations, but rather for testing and engineering purposes. Nevertheless, this type of data still contains valuable information and can be used if managed in the right way. From the case study it can be concluded that in order to use the data for more advanced analysis a big-data plan is needed at a strategic level in the organization. The plan summarizes the suggested solution for the managerial issues of the big data for the organization. This plan describes how to handle the data, how the analytic models revealing the information should be designed and the tools and organizational capabilities needed to support the people using the information.

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Bensel, Artur. « Characteristics of the Specific Fuel Consumption for Jet Engines ». Aircraft Design and Systems Group (AERO), Department of Automotive and Aeronautical Engineering, Hamburg University of Applied Sciences, 2018. http://d-nb.info/1175791237.

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Purpose of this project is a) the evaluation of the Thrust Specific Fuel Consumption (TSFC) of jet engines in cruise as a function of flight altitude, speed and thrust and b) the determination of the optimum cruise speed for maximum range of jet airplanes based on TSFC characteristics from a). Related to a) a literature review shows different models for the influence of altitude and speed on TSFC. A simple model describing the influence of thrust on TSFC seems not to exist in the literature. Here, openly available data was collected and evaluated. TSFC versus thrust is described by the so-called bucket curve with lowest TSFC at the bucket point at a certain thrust setting. A new simple equation was devised approximating the influence of thrust on TSFC. It was found that the influence of thrust as well as of altitude on TSFC is small and can be neglected in cruise conditions in many cases. However, TSFC is roughly a linear function of speed. This follows already from first principles. Related to b) it was found that the academically taught optimum flight speed (1.316 times minimum drag speed) for maximum range of jet airplanes is inaccurate, because the derivation is based on the unrealistic assumption of TSFC being constant with speed. Taking account of the influence of speed on TSFC and on drag, the optimum flight speed is only about 1.05 to 1.11 the minimum drag speed depending on aircraft weight. The amount of actual engine data was extremely limited in this project and the results will, therefore, only be as accurate as the input data. Results may only have a limited universal validity, because only four jet engine types were analyzed. One of the project's original value is the new simple polynomial function to estimate variations in TSFC from variations in thrust while maintaining constant speed and altitude.

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Chien, Jui-Yu. « The future and outlook of alternative fuel bus industry and its marketing strategy ». CSUSB ScholarWorks, 2002. https://scholarworks.lib.csusb.edu/etd-project/2332.

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According to the current governmental regulations, all diesel buses will be replaced in the United States and the European market within the next ten years. There are over 60,000 buses in the United States and each year over 3,000 new buses of approximately 40 feet in length are purchased. The bus market has a growth rate of four to five percent per year over the last two years. The improvements in technology offered by United States companies prove unsatisfactory in terms of bus performance and the emissions of new buses. The energy crisis in the United States and concern over the health hazards of the diesel fuel exhaust gases and particulates, alternative fuel vehicles are in great demand in the transit market world wide.

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Brooks, Thomas D. « Split-main fuel injection strategies for diesel engines and their influence on emissions and fuel consumption ». Thesis, University of Nottingham, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.417186.

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Abdul-, Rasool Mustafa. « THE IMPACT OF ECOROLL ON FUEL CONSUMPTION - USING LOOK AHEAD ». Thesis, KTH, Reglerteknik, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-55838.

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EcoRoll reduces fuel consumption with small development costs, since no additional hardware is required. It is a function that enables a more efficient conversion of potential to kinetic energy, when travelling downhill. This is achieved by opening the powertrain, and let the engine run on idle to reduce engine losses. In this Master’s thesis, two control strategies were developed, where one is based on prevailing conditions and one utilizes Look-Ahead data. Compared to a vehicle with a conventional cruise control, the first strategy gave a fuel reduction of approximately 3.4% and the other 3.7%. This was simulated on the highway between Södertälje and Norrköping in Sweden.

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Norman, Gustav, et Mengxi Wu. « Optimal Driving Strategies for Minimizing Fuel Consumption and Travelling Time ». Thesis, KTH, Optimeringslära och systemteori, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-116772.

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Gable, Adam V. « Study of Naval Air Station operations to reduce fuel consumption ». Thesis, Monterey, California : Naval Postgraduate School, 2014. http://hdl.handle.net/10945/42629.

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Approved for public release; distribution is unlimited
Naval aviation accounts for 54% of all naval fuel usage. With such a large footprint, even small reductions in fuel consumption can have a significant impact on the bottom line. Recognizing this fact, the Chief of Naval Operations has targeted naval aviation to achieve a 4% reduction in non-mission fuel burn without adversely affecting mission execution or safety. In this thesis, we model ground operations at Naval Air Station (NAS) Oceana and NAS Lemoore to identify and reduce the time an aircraft spends with engines online during post-flight operations. Specifically, by reducing the processes performed while conducting hot brake checks and reducing resources required at the hot skids, we are able to save over $8 million at NAS Oceana and Lemoore alone. In addition, we have identified zero-cost coordination efforts that increase synchronization of fuel truck delivery to their consumers, such as noting refueling intentions on schedules to allow fuel truck managers to allocate trucks more efficiently, leading to additional savings. We provide recommendations specific to each base and recommendations that can be adopted fleet-wide. Finally, we identify that the current allocation of aircraft among bases is suboptimal and provide policy recommendations that would improve overall readiness.

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HOMSI, GABRIEL ANDRE. « SHIP ROUTING AND SPEED OPTIMIZATION WITH HETEROGENEOUS FUEL CONSUMPTION PROFILES ». PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2018. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=34172@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO
COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR
CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO
PROGRAMA DE EXCELENCIA ACADEMICA
A indústria de transporte marítimo é essencial para o comércio internacional. No entanto, no despertar da crise financeira de 2008, essa indústria foi severamente atingida. Nessas ocasiões, empresas de transporte só são capazes de obter lucro se suas frotas forem roteadas de forma eficaz. Neste trabalho, nós estudamos uma classe de problemas de roteamento de navios relacionados ao Pickup and Delivery Problem with Time Windows. Para resolver esses problemas, nós introduzimos um método heurístico e um exato. O método heurístico é uma meta-heurística híbrida com uma vizinhança larga baseada em set partitioning, enquanto o método exato é um algoritmo de branch-and-price. Nós conduzimos experimentos em um conjunto de instâncias baseadas em rotas de navios reais. Os resultados obtidos mostram que nossos algoritmos superam as metodologias estado da arte. Em seguida, nós adaptamos o conjunto de instâncias para modelar um problema de roteamento de navios no qual a velocidade em cada segmento de rota é uma variável de decisão, e o consumo de combustível por unidade de tempo é uma função convexa da velocidade e carga do navio. A fim de resolver esse novo problema de roteamento de navios com otimização de velocidade, nós estendemos nossa meta-heurística para encontrar decisões de velocidade ótimas em toda avaliação de solução vizinha de uma busca local. Nossos experimentos demonstram que essa abordagem pode ser altamente rentável, e que requer apenas um aumento moderado de recursos computacionais.
The shipping industry is essential for international trade. However, in the wake of the 2008 financial crisis, this industry was severely hit. In these times, transportation companies can only obtain profit if their fleet is routed effectively. In this work, we study a class of ship routing problems related to the Pickup and Delivery Problem with Time Windows. To solve these problems, we introduce a heuristic and an exact method. The heuristic method is a hybrid metaheuristic with a set-partitioning-based large neighborhood, while the exact method is a branch-and-price algorithm. We conduct experiments on a benchmark suite based on real-life shipping segments. The results obtained show that our algorithms largely outperform the state-of-the-art methodologies. Next, we adapt the benchmark suite to model a ship routing problem where the speed on each sailing leg is a decision variable, and fuel consumption per time unit is a convex function of the ship speed and payload. To solve this new ship routing problem with speed optimization, we extend our metaheuristic to find optimal speed decisions on every local search move evaluation. Our computational experiments demonstrate that such approach can be highly profitable, with only a moderate increase in computational effort.

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Napier, Parhys L. « The individual contribution of automotive components to vehicle fuel consumption ». Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/68851.

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Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2011.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 47-51).
Fuel consumption has grown to become a major point of interest as oil reserves are depleted. The purpose of this study is to determine the key components that cause variation in the instantaneous fuel consumption of vehicles and their level of impact using an in-depth literature review of technical papers. The literature is rigorously screened using an algorithm that excluded unreliable studies by criteria defined herein. Papers that are identified using this strategy are stratified according to vehicle subsystem and component. Relationships are established between external factors and fuel consumption using linear regression models and ranked by level of importance. Results show that coolant, air conditioning, alternator, rolling resistance and lubricants have an impact on vehicle fuel consumption and its variation. More specifically, coolant flow rate, oil viscosity, ambient temperature and tire pressure are found to be significant factors to fuel economy for the automobile.
by Parhys L. Napier.
S.B.

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Шапочка, Микола Костянтинович, Николай Константинович Шапочка, Mykola Kostiantynovych Shapochka, Олександр Вікторович Лямцев, Александр Викторович Лямцев et Oleksandr Viktorovych Liamtsev. « Optimization of fuel consumption and decrease of transport vehicles emissions ». Thesis, Вид-во СумДУ, 2010. http://essuir.sumdu.edu.ua/handle/123456789/8278.

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Kumar, Sri Adarsh A. « Cloud Computing based Velocity Profile Generation for Minimum Fuel Consumption ». The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1331083555.

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Li, Huan. « Energy consumption minimization strategy for fuel cell hybrid electric vehicles ». Thesis, Bourgogne Franche-Comté, 2018. http://www.theses.fr/2018UBFCA034/document.

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Le réchauffement climatique, la pollution de l'environnement et l'épuisement des énergies pétrolières ont attiré l'attention de l'humanité dans le monde entier. Les véhicules électriques hybrides à pile à combustible (FCHEV), utilisant l’hydrogène comme carburant et n’émettant aucune émission, sont considérés par les organismes publics et privés comme l’un des meilleurs moyens de résoudre ces problèmes. Cette thèse de doctorat considère un FCHEV avec trois sources d'énergie: pile à combustible, batterie et supercondensateur, ce qui complique l'élaboration d'une stratégie de gestion de l'énergie (EMS) pour répartir la puissance entre différentes sources d'alimentation. Parmi les méthodes de gestion de l'énergie de la littérature actuelle, la stratégie de minimisation de la consommation équivalente (ECMS) a été sélectionnée car elle permet une optimisation locale sans connaissance préalable des conditions de conduite et cela en donnant des résultats optimaux.En raison de la faible densité énergétique du supercondensateur, sa consommation équivalente d'hydrogène est négligée dans la plupart des références bibliographiques, ce qui va non seulement à l'encontre de l'objectif de minimiser la consommation totale d'hydrogène, mais accroît également la complexité du système EMS en raison du besoin d'un système EMS supplémentaire pour calculer la demande en puissance du supercondensateur. Ainsi, une stratégie ECMS à programmation quadratique séquentielle (SECMS) est proposée pour prendre en compte le coût énergétique des trois sources d’énergie dans la fonction objectif. Une stratégie de contrôle basée sur des règles (RBCS) et une stratégie hybride (HEOS) a été également conçues pour être comparée à SECMS. La dégradation des sources d'énergie représente un défi majeur pour la stabilité du système SECMS développé. Basé sur l'estimation en ligne de l'état de santé de la pile à combustible et de la batterie, le système ECMS adaptatif (AECMS) a été implémenté en ajustant le facteur équivalent et le taux de changement dynamique de la pile à combustible. Les résultats de la simulation montrent que l’AECMS peut assurer le maintien de la charge de la batterie et l’augmentation de la durabilité de la pile à combustible.Pour valider les algorithmes de gestion de l'énergie et les modèles numériques proposés, un banc d'essai expérimental a été construit autour de l'interface temps réel DSPACE. La comparaison des résultats de la simulation numérique et des résultats expérimentaux a montré que le système SECMS proposé fonctionne à un rendement maximal, que le supercondensateur fournit la puissance de pointe et que la batterie fonctionne comme un tampon d’énergie. Il a été prouvé que la négligence de la consommation d'hydrogène équivalente au supercondensateur dans l'ECMS conduit à un fonctionnement non optimal. Comparé à RBCS et HEOS, la SECMS a le moins d'hydrogène consommé et le courant de pile à combustible le plus stable
Global warming, environment pollution and exhaustion of petroleum energies have risen their attention of the humanity over the world. Fuel cell hybrid electric vehicle (FCHEV) taking hydrogen as fuel and have zero emission, is thought by public and private organisms as one of the best ways to solve these problems. This PhD dissertation consider a FCHEV with three power sources: fuel cell, battery and supercapacitor, which increases the difficult to design an energy management strategy (EMS) to split the power between the different power sources.Among the EMS available in the current literature, the Equivalent consumption minimization strategy (ECMS) was selected because it allows a local optimization without rely on prior knowledge of driving condition while giving optimal results.Due to low energy density of supercapacitor, its equivalent hydrogen consumption is neglected in most bibliographic references, which not only counter to the aim of minimizing whole hydrogen consumption but also increase the complication of EMS due to the need of an additional EMS to calculate supercapacitor power demand. Thus, a sequential quadratic programming ECMS (SECMS) strategy is proposed to consider energy cost of all three power sources into the objective function. A rule based control strategy (RBCS) and hybrid strategy (HEOS) are also designed in order to to be compared with SECMS. Degradation of energy sources represents a major challenge for the stability of the developed SECMS system. So, based on online estimating state of heath of fuel cell and battery, an adaptive ECMS (AECMS) has been designed through adjusting the equivalent factor and dynamical change rate of fuel cell. The simulation results show that the AECMS can ensure the charge sustenance of battery and the increase of fuel cell durability.To validate the proposed energy management algorithms and the numerical models an exerimental test bench has been built around the real time interface DSPACE. The comparison of the simulation and experimental results showed that the proposed SECMS is operated at around maximum efficiency, supercapacitor supplies peak power, battery works as the energy buffer. It has been proved that the neglect of supercapacitor equivalent hydrogen consumption in ECMS leads to not optimal operation. Compared with RBCS and HEOS, SECMS has least hydrogen consumption and most stable fuel cell current

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Arter, Micah. « The effects of diesel fuel density on fuel consumption measurements of portable in-use emissions measurement systems ». Morgantown, W. Va. : [West Virginia University Libraries], 2007. https://eidr.wvu.edu/etd/documentdata.eTD?documentid=5509.

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Thesis (M.S.)--West Virginia University, 2007.
Title from document title page. Document formatted into pages; contains vii, 91 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 60-62).

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Edwardes, William Andrew. « Modeling Diesel Bus Fuel Consumption and Dynamically Optimizing Bus Scheduling Efficiency ». Thesis, Virginia Tech, 2014. http://hdl.handle.net/10919/49707.

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There are currently very few models that estimate diesel and hybrid bus fuel consumption levels. Those that are available either require significant dynamometer data gathering to calibrate the model parameters and also produce a bang-bang control system (optimum control entails maximum throttle and braking input). This thesis extends the Virginia Tech Comprehensive Power-Based Fuel Consumption Model (VT-CPFM) to model diesel buses and develops an application for it. A procedure is developed to calibrate the bus parameters using publicly available data from the Altoona Bus Research and Testing Center. In addition, calibration is also made using in-field bus fuel consumption data. The research presented in this thesis calibrates model parameters for a total of 10 standard diesel buses and 3 hybrid buses from Altoona and 10 buses from Blacksburg Transit. In the case of the Altoona data, the VT-CPFM estimated fuel consumption levels on the Orange County bus cycle dynamometer test produce an average error of 4.7%. The estimation error is less than 6% for all but two buses with a maximum error of 10.66% for one hybrid bus. The VT-CPFM is also validated using on-road fuel consumption measurements that are derived by creating drive cycles from acceleration information producing an average estimation error of 22%. These higher errors are attributed to the errors associated with constructing the in-field drive cycles given that they are not available. In the case of the Blacksburg Transit buses, the calibrated parameters produce a low sum of mean squared error, less than 0.002, and a coefficient of determination greater than 0.93. Finally an application of the VT-CPFM is presented in the form of a dynamic bus scheduling algorithm.
Master of Science

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Svensson, Martin. « Improved truck engine control for crane driving : - Focusing on fuel consumption ». Thesis, KTH, Maskinkonstruktion (Inst.), 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-100223.

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Due to increased demands on fuel economy the question of a more intelligent engine control for driving a truck-mounted crane has been raised. The aim of this thesis is to develop a new engine control for crane driving. The primary concern for the new engine control is fuel economy, but other factors, such as driver environment and drivability, have been taken into consideration as well. A literature study investigating engine control in construction machines has also been carried out and the results are presented in this report. Due to the fact that the hydraulic control system as well as the diesel engine control system is designed by the same construction machine manufacturer, more complex control strategies are utilized in these applications. In order to test the new control strategy a full-scale test has been carried out on a Scania truck with a crane from Hiab. The results point towards lower fuel consumption, better driver experience and lower noise levels. Some of the control features of the new control are suggested to be placed in the crane, and some in the truck. Only a small expansion of the communication between truck and crane would be necessary in order for the new control strategy to work. The experiences from the literature study point on several features utilized in construction machines that could be implemented in the crane control of the future.
På grund av ökade krav på minskad bränsleförbrukning har frågan om en förbättrad motorstyrning vid krankörning av lastbilsmonterade kranar blivit aktuell. Målet för detta examensarbete är att utveckla en ny motorstyrning anpassad för krankörning. I första hand syftar den nya motorstyrningen till att minska bränsleförbrukningen, men även andra faktorer såsom förarmiljö och körbarhet har tagits hänsyn till. En litteraturstudie om motorstyrning i hydrauliska grävmaskiner och andra hydrauliska maskiner har också utförts och resultatet finns presenterat i denna rapport. Eftersom det hydrauliska styrsystemet såväl som dieselmotorstyrsystemet är sammansatt hos en och samma tillverkare används mer komplicerade styralgoritmer i dessa tillämpningar. För att testa den nyutvecklade motorstyrningen har fullskaletest utförts på en Scanialastbil utrustad med en kran från Hiab. Resultaten pekar på lägre bränsleförbrukning, bättre förarupplevelse och lägre ljudnivå. Somliga av funktionerna i den nya styrningen föreslås placeras i lastbilen och andra i kranen. Bara en mycket liten utvidgning av kommunikationen mellan kran och lastbil skulle behövas för att denna styralgoritm skulle fungera. Lärdomarna ifrån litteraturstudien visar på att flera av de styrfunktioner som används ibland annat grävskopor skulle kunna komma till nytta i motor- och kran styrningen i en lastbilsmonterad kran i framtiden.

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Jiao, Xin. « Effect of Pavement-Vehicle Interaction on Highway Fuel Consumption and Emission ». FIU Digital Commons, 2015. http://digitalcommons.fiu.edu/etd/2251.

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Vehicle fuel consumption and emission are two important effectiveness measurements of sustainable transportation development. Pavement plays an essential role in goals of fuel economy improvement and greenhouse gas (GHG) emission reduction. The main objective of this dissertation study is to experimentally investigate the effect of pavement-vehicle interaction (PVI) on vehicle fuel consumption under highway driving conditions. The goal is to provide a better understanding on the role of pavement in the green transportation initiates. Four study phases are carried out. The first phase involves a preliminary field investigation to detect the fuel consumption differences between paired flexible-rigid pavement sections with repeat measurements. The second phase continues the field investigation by a more detailed and comprehensive experimental design and independently investigates the effect of pavement type on vehicle fuel consumption. The third study phase calibrates the HDM-IV fuel consumption model with data collected in the second field phase. The purpose is to understand how pavement deflection affects vehicle fuel consumption from a mechanistic approach. The last phase applies the calibrated HDM-IV model to Florida’s interstate network and estimates the total annual fuel consumption and CO2 emissions on different scenarios. The potential annual fuel savings and emission reductions are derived based on the estimation results. Statistical results from the two field studies both show fuel savings on rigid pavement compared to flexible pavement with the test conditions specified. The savings derived from the first phase are 2.50% for the passenger car at 112km/h, and 4.04% for 18-wheel tractor-trailer at 93km/h. The savings resulted from the second phase are 2.25% and 2.22% for passenger car at 93km/h and 112km/h, and 3.57% and 3.15% for the 6-wheel medium-duty truck at 89km/h and 105km/h. All savings are statistically significant at 95% Confidence Level (C.L.). From the calibrated HDM-IV model, one unit of pavement deflection (1mm) on flexible pavement can cause an excess fuel consumption by 0.234-0.311 L/100km for the passenger car and by 1.123-1.277 L/100km for the truck. The effect is more evident at lower highway speed than at higher highway speed. From the network level estimation, approximately 40 million gallons of fuel (combined gasoline and diesel) and 0.39 million tons of CO2 emission can be saved/reduced annually if all Florida’s interstate flexible pavement are converted to rigid pavement with the same roughness levels. Moreover, each 1-mile of flexible-rigid conversion can result in a reduction of 29 thousand gallons of fuel and 258 tons of CO2 emission yearly.

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Venkateswaran, Prabhakar. « Measurements and modeling of turbulent consumption speeds of syngas fuel blends ». Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/47561.

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Increasingly stringent emission requirements and dwindling petroleum reserves have generated interest in expanding the role of synthesis gas (syngas) fuels in power generation applications. Syngas fuels are the product of gasifying organic-based feedstock such as coal and biomass and are composed of mainly H₂ and CO. However, the use of syngas fuels in lean premixed gas turbine systems has been limited in part because the behavior of turbulent flames in these mixtures at practical gas turbine operating conditions are not well understood. This thesis presents an investigation of the influence of fuel composition and pressure on the turbulent consumption speed, ST,GC, and the turbulent flame brush thickness, FBT, for these mixtures. ST,GC and FBT are global parameters which represent the average rate of conversion of reactants to products and the average heat release distribution of the turbulent flame respectively. A comprehensive database of turbulent consumption speed measurements obtained at pressures up to 20 atm and H₂/CO ratios of 30/70 to 90/10 by volume is presented. There are two key findings from this database. First, mixtures of different H₂/CO ratios but with the same un-stretched laminar flame speeds, SL,0, exposed to the same turbulence intensities, u'rms , have different turbulent consumption speeds. Second, higher pressures augment the turbulent consumption speed when SL,0 is held constant across pressures and H₂/CO ratios. These observations are attributed to the mixture stretch sensitivities, which are incorporated into a physics-based model for the turbulent consumption speed using quasi-steady leading points concepts. The derived scaling law closely resembles Damkhler's classical turbulent flame speed scaling, except that the maximum stretched laminar flame speed, SL,max, arises as the normalizing parameter. Scaling the ST,GC data by SL,max shows good collapse of the data at fixed pressures, but systematic differences between data taken at different pressures are observed. These differences are attributed to non-quasi-steady chemistry effects, which are quantified with a Damkhler number defined as the ratio of the chemical time scale associated with SL,max and a fluid mechanic time scale. The observed scatter in the normalized turbulent consumption speed data correlates very well with this Damkhler number, suggesting that ST,GC can be parameterized by u'rms/SL,max and the leading point Damkhler number. Finally, a systematic investigation of the influence of pressure and fuel composition on the flame brush thickness is presented. The flame brush thickness is shown to be independent of the H₂/CO ratio if SL,0 is held constant across the mixtures. However, increasing the equivalence ratio for lean mixtures at a constant H₂/CO ratio, results in a thicker flame brush. Increasing the pressure is shown to augment the flame brush thickness, a result which has not been previously reported in the literature. Classical correlations based on turbulent diffusion concepts collapse the flame brush thickness data obtained at fixed u'rms/U₀ and pressure reasonably well, but systematic differences exist between the data at different u'rms/U₀ and pressures.

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Khan, Bruno Shakou. « Optimization of the fuel consumption of a parallel hybrid electric vehicle ». Thesis, Georgia Institute of Technology, 2001. http://hdl.handle.net/1853/16763.

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Modisette, Joel D. « A Model for the Propulsion Fuel Consumption of an Aircraft Carrier ». Thesis, Monterey, California. Naval Postgraduate School, 1990. http://hdl.handle.net/10945/37529.

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Approved for public release; distribution is unlimited.
Speed and propulsion fuel consumption characteristics of United States aircraft carriers are modeled to determine how unpredictabilities in operational, engineering, and wartime environments affect the endurance capability of the ship. Research into the characteristics of steam propulsion plants on ships show that variability may exist in the amount of propulsion fuel required to support ship operation for a given period of time. Sources if this variability include the nonlinear transformation of operational data into fuel logistics data, the nearly deterministic engine reacting to inputs from a stochastic environment, and the effects of increased engine wear and ship's crew fatigue on engine performance. Implementations of this variation in a simulation indicate that conventional estimation techniques for fuel consumption may seriously overestimate the endurance capability if the aircraft carriers. The simulation results show that the distribution of endurance time resembles a normal distribution, with the estimated mean decreasing variance increasing as unpredictabilities in various environments are considered.

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Gheriani, Eran (Eran Y. ). « Fuel consumption prediction methodology for early stages of naval ship design ». Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/70435.

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Thesis (S.M. in Mechanical Engineering)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering; and, (S.M. in Naval Architecture and Marine Engineering)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, February 2012.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 72).
In recent years, fuel consumption has increased in importance as a design parameter in Navy ships. Economical fuel consumption is important not only for operating cost measures but also for ship endurance tankage requirements. Minimizing fuel consumption has many benefits for both naval and commercial ships. This thesis work will suggest a new comprehensive approach to early-stage ship design to determine fuel consumption for the whole system. A hull must be designed to work harmoniously with an optimized propulsor and propulsion plant to ensure best performance and to comply with imposed design requirements. Thus, this work will address three main aspects of the fuel consumption equation: -- Ship's resistance is calculated using a computational fluid dynamics simulation of the vessel in calm water at various speeds up to maximum speed. -- Propeller performance is based on propeller curves for the chosen propulsor. -- Efficiencies of the drive train and electrical production and distribution system are calculated for all operating conditions. Note that for an electric-drive ship, the non-propulsion electrical loads must be included in the calculations. These three major components of the ship efficiency equation are assessed for each speed and battle condition of the mission profile. In addition, the corresponding operating conditions for each piece of machinery will be specified to estimate the total fuel consumption and tankage required. In this thesis work, I will suggest a design methodology to determine hull resistance and total power for a given ship with a specified operational profile. The total power for the operational profile will be translated to fuel consumption, thus producing annual fuel consumption requirements and recommended tankage to support the operational needs.
by Eran Gheriani.
S.M.in Naval Architecture and Marine Engineering
S.M.in Mechanical Engineering

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Bodell, Victor. « Comparing Machine Learning Estimation of Fuel Consumption of Heavy-duty Vehicles ». Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-279826.

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Fuel consumption is one of the key factors in determining expenses of operating a heavy-duty vehicle. A customer may therefor request an estimate of the fuel consumption of a given vehicle. Scania uses modular design when constructing heavy-duty vehicles. The modular design allows a customer to specify which building blocks to use when constructing the vehicle, such as gear box, engine and chassis type. The many possible combinations means that the same vehicle is rarely sold twice, which can make fuel consumption measurements unfeasible. This study investigates the accuracy of machine learning algorithms in predicting fuel consumption for heavy-duty vehicles. The study is conducted at Scania. Scania has also provided the data used in the study. This study also examines the prediction power of different parameters. Performance is evaluated by reporting the prediction error on both simulated data and operational measurements. The performance of Linear regression (LR), K-nearest neighbor (KNN) and Artificial neural networks (ANN) is compared using statistical hypothesis testing. It is found that using Country as an input parameter yields a performance increase in all the algorithms. The statistical evaluation procedure finds that ANNs have the lowest prediction error compared to LR and KNN in estimating fuel consumption on both simulated and operational data. The performance of the final models is comparable to models of previous studies in both the simulated and operational estimation scenarios.
Bränsleförbrukning utgör en av nyckelfaktorerna för att avgöra hur mycket det kostar att använda tunga lastbilar. En köpare av en tung lastbil kan därmed begära en uppskattning av hur mycket bränsle ett givet fordon förbrukar. Scania använder sig av en modulär designprincip vid fordonskonstruktion, vilket ger kunden möjlighet att bestämma vilka byggnadsblock som ska utgöra ett for- don. Detta gör att det kan vara omöjligt att mäta förbrukningen av ett tidigare icke-producerat fordon. Den här studien undersöker exaktheten av maskininlärningsalgoritmer för att estimera bränsleförbrukning av tunga lastbilar. Studien genomförs vid Scania, som även tillhandahåller data. Användbarheten av olika in-parametrar undersöks. Algoritmernas prestanda utvärderas genom att rapportera det kvadrerade felvärdet uppmätt mellan det riktiga uppmätta värdet och det av algoritmen uppskattade värdet. Bränsleförbrukning estimeras för simulerad data och för uppmätta värden från fordon i bruk. Tre kategorier av algoritmer undersöks: Artificiella neurala nätverk, linjär regression och K-nearest neighbor. Jämförelsen mellan algoritmer använder statistisk hypotes-testning. Resultatet visar att parametern som beskriver vilket land fordonet registrerats i förbättrar samtliga algoritmers estimering. Den statistiska utvärderingen finner att artificiella neurala nätverk ger det lägsta felet av de tre kategorierna av algoritmer i estimering av simulerade och uppmätta värden. De slutgiltiga modellernas exakthet är jämförbar med resultat från tidigare studier.

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Chandramouli, Nitish. « Engine Idle Sailing with Driver Assistant Systems For Fuel Consumption Minimization ». The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1523531254267084.

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Hall, Marcus, et David Forsberg. « Reduced Fuel Consumption of Heavy-Duty Vehicles using Pulse and Glide ». Thesis, Linköpings universitet, Fordonssystem, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-159656.

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The transport sector always strive towards reduced fuel consumption for heavydutyvehicles. One promising control strategy is to use Pulse and Glide. Themethod works by acceleration to a high speed and then glide in neutral gear to alow speed.Two different control strategies and four different glide options were investigated.The two strategies were either to follow the optimal BSFC-line or using optimalcontrol. For each strategy, different velocity spans between the upper and lowervelocity were tested.The results show that the fuel consumption can be reduced up to 8.1 % comparedto a constant speed driving strategy. The fuel consumption was reduced the mostfor lower velocities and if the difference between the upper and lower velocity forthe Pulse and Glide strategy was kept small. The fuel saving can be explaineddue to increased engine efficiency during the pulse. The results also show thatthe difference between the rule-based and optimization based control strategy issmall. It can be concluded that a near-optimal strategy for a heavy-duty vehicleutilizing Pulse and Glide is to always pulse on the optimal BSFC-line.

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De, Cesare Matteo <1969&gt. « Powertrain Architectures and Technologies for New Emission and Fuel Consumption Standards ». Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amsdottorato.unibo.it/8901/4/De_Cesare_M_Tesi_PhD_DIMSAI_XXXI_Ciclo.pdf.

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New powertrain design is highly influenced by CO2 and pollutant limits defined by legislations, the demand of fuel economy in for real conditions, high performances and acceptable cost. To reach the requirements coming from both end-users and legislations, several powertrain architectures and engine technologies are possible (e.g. SI or CI engines), with many new technologies, new fuels, and different degree of electrification. The benefits and costs given by the possible architectures and technology mix must be accurately evaluated by means of objective procedures and tools in order to choose among the best alternatives. This work presents a basic design methodology and a comparison at concept level of the main powertrain architectures and technologies that are currently being developed, considering technical benefits and their cost effectiveness. The analysis is carried out on the basis of studies from the technical literature, integrating missing data with evaluations performed by means of powertrain-vehicle simplified models, considering the most important powertrain architectures. Technology pathways for passenger cars up to 2025 and beyond have been defined. After that, with support of more detailed models and experimentations, the investigation has been focused on the more promising technologies to improve internal combustion engine, such as: water injection, low temperature combustions and heat recovery systems.

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Vasudevan, Gopal. « Fuel optimal rendezvous including a radial constraint ». Thesis, Virginia Polytechnic Institute and State University, 1986. http://hdl.handle.net/10919/94484.

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Fuel-optimal rendezvous in orbit is examined using thrust-impulses and coasting arcs. Necessary conditions for the optimality of fuel-optimal rendezvous with and without radial constraints are derived. These conditions are then used to verify the optimality of trajectories obtained from a parameter-optimization technique. For rendezvous problems with radial constraint, locally optimal trajectories include constrained arcs or touch-point arcs. Numerical procedures to compute the costates and the jumps in the costates at the touch point and at the entry point to the constraint arc are provided. Locally optimal solutions for non-optimal trajectories with a minimum radius-constraint are obtained using criteria due to Lion and Handelsmann. Numerical solutions show that multiple-impulse trajectories almost always result in a lower cost function than the corresponding two impulse trajectories. It is also observed that trajectories comprised of only touch-point arcs can often be improved by using an additional impulse.
M. S.

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Meyer, Mark J. « Understanding the challenges in HEV 5-cycle fuel economy calculations based on dynamometer test data ». Thesis, Virginia Tech, 2011. http://hdl.handle.net/10919/35648.

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EPA testing methods for calculation of fuel economy label ratings, which were revised beginning in 2008, use equations that weight the contributions of fuel consumption results from multiple dynamometer tests to synthesize city and highway estimates that reflect average U.S. driving patterns. The equations incorporate effects with varying weightings into the final fuel consumption, which are explained in this thesis paper, including illustrations from testing. Some of the test results used in the computation come from individual phases within the certification driving cycles. This methodology causes additional complexities for hybrid electric vehicles, because although they are required to have charge-balanced batteries over the course of a full drive cycle, they may have net charge or discharge within the individual phases. The fundamentals of studying battery charge-balance are discussed in this paper, followed by a detailed investigation of the implications of per-phase charge correction that was undertaken through testing of a 2010 Toyota Prius at Argonne National Laboratoryâ s vehicle dynamometer test facility. Using the charge-correction curves obtained through testing shows that phase fuel economy can be significantly skewed by natural charge imbalance, although the end effect on the fuel economy label is not as large. Finally, the characteristics of the current 5-cycle fuel economy testing method are compared to previous methods through a vehicle simulation study which shows that the magnitude of impact from mass and aerodynamic parameters vary between labeling methods and vehicle types.
Master of Science

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Carson, Christopher Edward. « An investigation of stratified charging of two-stroke engines ». Thesis, Queen's University Belfast, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.241331.

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