Este trabalho apresenta um procedimento simples e robusto para avaliação e análise do desempenho de instalações propulsoras de embarcações de pesca operando no Estado do Espírito Santo. O objetivo é verificar se as embarcações estão operando com baixa eficiência propulsiva, portanto, com consumo de combustível maior do que o desejável, e identificar possíveis ações de melhoria desta eficiência que poderiam ser implementadas com baixo custo. Tendo em vista as condições artesanais da construção e operação das embarcações de pesca no Espírito Santo, o procedimento foi desenvolvido de forma a poder ser aplicado com relativa facilidade pelas pessoas envolvidas na atividade pesqueira artesanal neste Estado. O procedimento envolve o levantamento de informações sobre a geometria do casco, as características da instalação propulsora existente e sobre alguns aspectos do desempenho das embarcações. Para este levantamento são propostos métodos e técnicas suficientemente simples para que possam ser facilmente aplicadas nos estaleiros. Com base nestes dados levantados implementou-se no procedimento proposto diversos algoritmos que permitem determinar o coeficiente propulsivo das embarcações de pesca e a perda de energia útil que ocorre tanto no motor, por conta de condições inadequadas de operação, quanto na transmissão desta energia para o hélice. Para a validação dos métodos e técnicas envolvidos neste procedimento e dos resultados fornecidos por ele, o mesmo foi aplicado em alguns cascos de embarcações de pesca disponíveis em estaleiros visitados no Estado. Para uma destas embarcações o procedimento foi aplicado em sua totalidade, permitindo identificar a baixa eficiência da instalação propulsora e algumas das possíveis causas que provocam a perda de energia útil no sistema. Finalmente, com base nesse exemplo de aplicação, um estudo de possíveis melhorias na instalação propulsora é apresentado ao final do trabalho. / This study presents a simple and robust procedure to the performance evaluation and analysis of propulsion systems of fishing vessels operating in the Espírito Santo State. The goals are to verify if the vessels are operating at low propulsive efficiency, therefore, with a fuel consumption greater than desired, and identify possible actions to improve this efficiency that could be implemented at a low cost. The procedure was developed in view of the conditions of construction and operation of fishing vessels in Espírito Santo, so that it can be applied with relative ease by the people involved in artisanal fishing activity in this State. The procedure involves the collection of information about the geometry of hull, the characteristics of existing propulsion plant and some aspects of the performance of the vessels. To do this data collection, this paper proposes methods and techniques simple enough to be easily applied in the shipyards. Based on these data collected, the proposed procedure implemented several algorithms to ascertain the propulsive coefficient of fishing vessels and the energy loss which may occur due to the inadequate operating conditions and in energy transmission to propeller. It has been applied in some fishing vessel hulls available on sites visited to validate the methods and techniques involved in this procedure and its results. The procedure was applied, in its entirety, in one of this vessels, that allowed to identify the low efficiency of the propulsion plant and some of the possible causes that justify this energy loss in the system. Finally, based on this application example, a study of possible improvements in propulsion plant is presented at the end of work.

Orientadores: Sérgio Valdir Bajay, Mauro Donizeti Berni / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecânica / Made available in DSpace on 2018-08-18T02:54:57Z (GMT). No. of bitstreams: 1 OrtizJerez_AndreaJuliana_M.pdf: 2744402 bytes, checksum: b0694ec37f090e4bdd506a6477bd8c4c (MD5) Previous issue date: 2011 / Resumo: O aumento da demanda de combustíveis e a conseqüente elevação dos níveis de emissões dos veículos de transporte rodoviário nas últimas décadas intensificam as preocupações sobre a segurança no suprimento de petróleo, poluição do ar e aquecimento global ao redor do mundo. As frotas de cidades densamente povoadas como São Paulo e Bogotá não tem sido devidamente acomodadas pela infraestrutura disponível, agravando a qualidade de vida de suas populações. O atual quadro do setor de transporte urbano nas cidades de São Paulo e Bogotá e sua possível evolução, em termos de veículos utilizados no transporte urbano, sua infra-estrutura e consumo de combustíveis constituem os focos deste trabalho. Para analisar tendências da demanda de combustíveis, emissões de poluentes e de gases de efeito estufa no transporte urbano de passageiros, nestas cidades, foi desenvolvido um modelo de projeção do tipo misto econométrico/simulação. São considerados dois cenários para as projeções. O primeiro, denominado "de referência", contempla a manutenção da evolução atual do transporte urbano, enquanto o segundo, denominado "alternativo", contempla uma evolução favorável da economia e o uso de novas tecnologias nos modos de transporte, visando diminuir seus impactos em termos de aquecimento global e poluição local e um uso crescente de combustíveis não fósseis. Medidas de mitigação já implementadas e aquelas que apresentam razoável expectativa de serem adotadas em um futuro próximo são analisadas. Estudos recentes explorando as tendências futuras de demanda de combustíveis e emissões de veículos rodoviários sob várias estratégias são revisados. Recomendações para outros trabalhos também são feitas. Conclui-se que novas estratégias mais abrangentes, serão necessárias para minimizar o impacto adverso dos veículos utilizados no transporte urbano de passageiros nas duas cidades objeto de análise na dissertação / Abstract: Rapidly growing energy demand and emissions from road transportation vehicles in the last decades have raised concerns over oil supply security, urban air pollution and global warming around the world. Fleets of cities with large populations as São Paulo and Bogotá have not been properly accounted for by the available infrastructures, worsening the quality of life of their populations. The current status of urban transport in São Paulo and Bogotá and its possible evolutions, in terms of the vehicles employed, infrastructure available, energy consumption and emissions are the focus of this thesis. To analyze trends of energy demand, pollutants and greenhouse gases emissions from urban passenger transport in these cities, a mixed econometric/simulation forecasting model was developed in the study. Two scenarios are considered for the forecasts. The first one, called a "reference scenario", assumes that the current trends of urban transport will continue in the future, while the second one, an "alternative scenario", assumes that there will substantial economic growth and new technologies will be employed in the transport modes, aiming to reduce their impacts on local pollution and global warming and to increase the use of non-fossil fuels. Mitigation measurements already implemented and those that can reasonably be expected to be adopted in the near future are analyzed. Recent studies exploring the future trends of urban transport fuel consumption and emissions under various strategies are reviewed. Recommendations for further developments are also made. It is concluded that new, more comprehensive strategies will be needed to minimize the adverse impacts of the vehicles used in the urban transport of passengers in São Paulo and Bogotá / Mestrado / Planejamento de Sistemas Energeticos / Mestre em Planejamento de Sistemas Energéticos

Fuel consumption is a major economical component of vehicles, particularly for heavy-duty vehicles. It is dependent on many factors, such as driver and environment, and control over some factors is present, e.g. route, and we can try to optimize others, e.g. driver. The driver is responsible for around 30% of the operational cost for the fleet operator and is therefore important to have efficient drivers as they also inuence fuel consumption which is another major cost, amounting to around 40% of vehicle operation. The difference between good and bad drivers can be substantial, depending on the environment, experience and other factors. In this thesis, two methods are proposed that aim at quantifying and qualifying driver performance of heavy duty vehicles with respect to fuel consumption. The first method, Fuel under Predefined Conditions (FPC), makes use of domain knowledge in order to incorporate effect of factors which are not measured. Due to the complexity of the vehicles, many factors cannot be quantified precisely or even measured, e.g. wind speed and direction, tire pressure. For FPC to be feasible, several assumptions need to be made regarding unmeasured variables. The effect of said unmeasured variables has to be quantified, which is done by defining specific conditions that enable their estimation. Having calculated the effect of unmeasured variables, the contribution of measured variables can be estimated. All the steps are required to be able to calculate the influence of the driver. The second method, Accelerator Pedal Position - Engine Speed (APPES) seeks to qualify driver performance irrespective of the external factors by analyzing driver intention. APPES is a 2D histogram build from the two mentioned signals. Driver performance is expressed, in this case, using features calculated from APPES. The focus of first method is to quantify fuel consumption, giving us the possibility to estimate driver performance. The second method is more skewed towards qualitative analysis allowing a better understanding of driver decisions and how they affect fuel consumption. Both methods have the ability to give transferable knowledge that can be used to improve driver's performance or automatic driving systems. Throughout the thesis and attached articles we show that both methods are able to operate within the specified conditions and achieve the set goal.

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.

This work deal with system design and implement of Trip computer for motorcycle serving as information element of speed and fuel consumption motorcycle. The general aim is design of device with graphic display that shall represent measured values of speed motorcycle, rpm of motor, onboard voltage, charging current, motor temperature and ambient temperature. All measuring data will be saving on memory card. For easily tracking in system menu will be used touch panel on graphic display.

Heavy duty vehicle (HDV) platooning is currently a big topic both in the academic world and in industry. Platooning is a smart way to solve problems such as safety, traffic congestion, fuel consumption and hazardous exhaust emissions since its concept enables several vehicles to drive close to each other while maintaining all the security requisites. This way, each vehicle will use the so called slipstream effect, an atmospheric drag reduction that occurs behind a traveling vehicle, consuming less fuel and consequently reducing the exhausted gases. Furthermore, it increases the traffic flow since the distance between vehicles is significantly reduced. The concept and idea of platooning is not particularly new, but only in the last few decades new technology made it possible. HDV platooning scenarios for scale model trucks were developed in the completely renovated Smart Mobility Lab, in KTH, Stockholm. A LabVIEW application was developed giving a robust and stable control of the trucks while following and driving on a newly designed and built road network. The trucks are able to follow a predefined trajectory, change lane and road, platoon with each other with different platooning distances, overtake when the platoon master is changed in order to take the lead of the platoon and change speed to catch up, among other features. The last part of this thesis covers the analysis of the scenarios developed in the testbed. These scenarios represent several situations of HDV platooning, particularly the platoon catch-up case. The main object of this study was the saved fuel due to platooning, and the break-even point, i.e. the distance ratio when neither driving alone nor catching up a platoon ahead would be more feasible. Using real HDV models and their fuel consumption models, simulations were performed in order to check the benefits of platooning and the data got from the scenarios was analyzed. Finally, conclusions were drawn from the experiments where the parameters such as HDV weight, speed increment when catching up and intermediate distance when platooning were different in each trial. It was concluded that a single HDV has to travel 8 to 15 times more than the initial distance that separates it from the HDV(s) ahead and it can save 5 to 13% of fuel depending if catching up a single HDV or a platoon an already existing platoon. Furthermore, it is less beneficial for a platoon already formed to decide to catch up another HDV.

Med ett växande fokus på ett långsiktigt hållbart samhälle som tar ansvar för miljön strävar fordonstillverkare efter att sänka energiförbrukningen på sina fordon. Detta arbete behandlar hur man kan sänka bränsleförbrukningen för lastbilar med påbyggnader. En påbyggnad kan t.ex. vara en kran, en lastväxlare eller en betongpump. En metod för att sänka energiförbrukningen är att sänka det varvtal som lastbilens dieselmotor arbetar vid. Vid lägre varvtal jobbar motorn oftast mer effektivt och en mindre del av motorarbetet försvinner då i förluster, dock kan inte motorn belastas lika hårt. Varvtalet kan i vissa situationer sänkas under drift av påbyggnaden. Mellan drift då applikationen väntar på användarens kommando kan varvtalet alltid sänkas så att energiförbrukningen sjunker.För att veta när varvtalet ska sänkas används en signal från motorn som anger vilket lastmoment som motorn jobbar mot. Vid låg last sänks varvtalet och bränsle kan sparas, vid hög last höjs varvtalet för att kunna möta det pålagda momentet.Fältstudier har genomförts för att kunna undersöka vilka typer av lastbilspåbyggnader som skulle kunna ha nytta av en funktion som sänker varvtalet när lasten är låg. Under arbetet har även uppskattningar över hur mycket bränsle som skulle kunna sparas om varvtalet sänks mellan operationerna med påbyggnaden gjorts. Resultatet pekar på att det i många fall går att spara bränsle genom att sänka motorns varvtal då lastbilens påbyggnad inte används. De visar också på att det inte går att spara bränsle med denna metod i de fall där föraren sitter kvar i hytten under påbyggnadsanvändningen.

This report is done in collaboration with WirelessCar for the master of science thesis at Halmstad University. Many different parameters influence fuel consumption. The objective of the report is to evaluate if Graph neural networks are a practical model to perform fuel consumption prediction on areas. The model uses a partitioning of geographical locations of trip observations to capture their spatial information. The project also proposes a method to capture the non-stationary behavior of vehicles by defining a vehicle node as a separate entity. The model then captures their different features in a dense layer neural network and utilizes message passing to capture context about neighboring nodes. The model is compared to a baseline neural network with a similar network architecture as the graph neural network. The data is partitioned to define an area with Kmeans and static gridnet partition with and without terrain details. This partition is used to structure a homogeneous graph that is underperforming. The practical drawbacks of the initial homogeneous graph are inspected and addressed to develop a heterogeneous graph that can outperform the neural network baseline.

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. / <p>Presentation was performed remotely using Zoom.</p>

The transportation sector is the dominant source of U.S. fuel consumption and emissions. Specifically, highway travel accounts for nearly 75 percent of total transportation energy use and slightly more than 33 percent of national emissions of EPA's six Criteria pollutants. Enactment of the Clean Air Act Amendment of 1990 (CAAA) and the Intermodal Surface Transportation Efficiency Act of 1991 (ISTEA) have changed the ways that most states and local governments deal with transportation problems. Transportation planning is geared to improve air quality as well as mobility. It is required that each transportation activity be analyzed in advance using the most recent mobile emission estimate model to ensure not to violate the Conformity Regulation. Several types of energy and emission models have been developed to capture the impact of a number of factors on vehicle fuel consumption and emissions. Specifically, the current state-of-practice in emission modeling (i.e. Mobile5 and EMFAC7) uses the average speed as a single explanatory variable. However, up to date there has not been a systematic attempt to quantify the impact of various travel and driver-related factors on vehicle fuel consumption and emissions. This thesis first systematically quantifies the impact of various travel-related and driver-related factors on vehicle fuel consumption and emissions. The analysis indicates that vehicle fuel consumption and emission rates increase considerably as the number of vehicle stops increases especially at high cruise speed. However, vehicle fuel consumption is more sensitive to the cruise speed level than to vehicle stops. The aggressiveness of a vehicle stop, which represents a vehicle's acceleration and deceleration level, does have an impact on vehicle fuel consumption and emissions. Specifically, the HC and CO emission rates are highly sensitive to the level of acceleration when compared to cruise speed in the range of 0 to 120 km/h. The impact of the deceleration level on all MOEs is relatively small. At high speeds the introduction of vehicle stops that involve extremely mild acceleration levels can actually reduce vehicle emission rates. Consequently, the thesis demonstrated that the use of average speed as a sole explanatory variable is inadequate for estimating vehicle fuel consumption and emissions, and the addition of speed variability as an explanatory variable results in better models. Second, the thesis identifies a number of critical variables as potential explanatory variables for estimating vehicle fuel consumption and emission rates. These explanatory variables include the average speed, the speed variance, the number of vehicle stops, the acceleration noise associated with positive acceleration and negative acceleration noise, the kinetic energy, and the power exerted. Statistical models are developed using these critical variables. The statistical models predict the vehicle fuel consumption rate and emission rates of HC, CO, and NOx (per unit of distance) within an accuracy of 88%-96% when compared to instantaneous microscopic models (Ahn and Rakha, 1999), and predict emission rates of HC, CO, and NOx within 95 percentile confidence limits of chassis dynamometer tests conducted by EPA. Comparing with the current state-of-practice, the proposed statistical models provide better estimates for vehicle fuel consumption and emissions because speed variances about the average speed along a trip are considered in these models. On the other hand, the statistical models only require several aggregate trip variables as input while generating reasonable estimates that are consistent with microscopic model estimates. Therefore, these models could be used with transportation planning models for conformity analysis. / Master of Science