The automotive industry is undertaking major technological steps in an effort to reduce emissions and fight climate change. To reduce the reliability on fossil fuels a lot of research is invested into electric motors (EM) and their applications. One such application is plug-in hybrid electric vehicles (PHEV), in which internal combustion engines (ICE) and EM are used in combination, and take turns to propel the vehicle based on driving conditions. The main optimization problem of PHEV is to decide when to use which motor. If this optimization is done with respect to emissions, the entire electric charge should be used up before the end of the trip. But if the charge is used up too early, latter driving segments for which the optimal choice would have been to use the EM will have to be done using the ICE. To address this optimization problem, we studied the fuel consumption during different driving conditions. These driving conditions are characterized by hundreds of sensors which collect data about the state of the vehicle continuously when driving. From these data, we constructed 150 seconds segments, including e.g. vehicle speed, before new descriptive features were engineered for each segment, e.g. max vehicle speed. By using the characteristics of typical driving conditions specified by the Worldwide Harmonized Light Vehicles Test Cycle (WLTC), segments were labelled as a highway or city road segments. To reduce the dimensions without losing information, principle component analysis was conducted, and a Gaussian mixture model was used to uncover hidden structures in the data. Three machine learning regression models were trained and tested: a linear mixed model, a kernel ridge regression model with linear kernel function, and lastly a kernel ridge regression model with an RBF kernel function. By splitting the data into a training set and a test set the models were evaluated on data which they have not been trained on. The model performance and explanation rate obtained for each model, such as R2, Mean Absolute Error and Mean Squared Error, were compared to find the best model. The study shows that the fuel consumption can be modelled by the sensor data of a PHEV test fleet where 6 features contributes to an explanation ratio of 0.5, thus having highest impact on the fuel consumption. One needs to keep in mind the data were collected during the Covid-19 outbreak where travel patterns were not considered to be normal. No regression model can explain the real world better than what the underlying data does. / Fordonsindustrin vidtar stora tekniska steg för att minska utsläppen och bekämpa klimatförändringar. För att minska tillförlitligheten på fossila bränslen investeras en hel del forskning i elmotorer (EM) och deras tillämpningar. En sådan applikation är laddhybrider (PHEV), där förbränningsmotorer (ICE) och EM används i kombination, och turas om för att driva fordonet baserat på rådande körförhållanden. PHEV: s huvudoptimeringsproblem är att bestämma när man ska använda vilken motor. Om denna optimering görs med avseende på utsläpp bör hela den elektriska laddningen användas innan resan är slut. Men om laddningen används för tidigt måste senare delar av resan, för vilka det optimala valet hade varit att använda EM, göras med ICE. För att ta itu med detta optimeringsproblem, studerade vi bränsleförbrukningen under olika körförhållanden. Dessa körförhållanden kännetecknas av hundratals sensorer som samlar in data om fordonets tillstånd kontinuerligt vid körning. Från dessa data konstruerade vi 150 sekunder segment, inkluderandes exempelvis fordonshastighet, innan nya beskrivande attribut konstruerades för varje segment, exempelvis högsta fordonshastighet. Genom att använda egenskaperna för typiska körförhållanden som specificerats av Worldwide Harmonized Light Vehicles Test Cycle (WLTC), märktes segment som motorvägs- eller stadsvägsegment. För att minska dimensioner på data utan att förlora information, användes principal component analysis och en Gaussian Mixture model för att avslöja dolda strukturer i data. Tre maskininlärnings regressionsmodeller skapades och testades: en linjär blandad modell, en kernel ridge regression modell med linjär kernel funktion och slutligen en en kernel ridge regression modell med RBF kernel funktion. Genom att dela upp informationen i ett tränings set och ett test set utvärderades de tre modellerna på data som de inte har tränats på. För utvärdering och förklaringsgrad av varje modell användes, R2, Mean Absolute Error och Mean Squared Error. Studien visar att bränsleförbrukningen kan modelleras av sensordata för en PHEV-testflotta där 6 stycken attribut har en förklaringsgrad av 0.5 och därmed har störst inflytande på bränsleförbrukningen . Man måste komma ihåg att all data samlades in under Covid-19-utbrottet där resmönster inte ansågs vara normala och att ingen regressionsmodell kan förklara den verkliga världen bättre än vad underliggande data gör.

Tesis por compendio / It was not that long ago, just in the first half on the 1990s, when mobile phones were first introduced, being big and expensive. All you could do with them was to make phone calls. Since then mobile devices have experienced a great technological advance: we carry smartphones in our pockets that provide Internet access, having accelerometers that can measure acceleration, a gyroscope that can provide orientation information, different wireless interfaces such as Bluetooth connections, and above all, great computing power. On the other hand, the automobile industry has evolved significantly during the last 10 years. One of the most exciting advances in vehicle development is vehicle-to-vehicle V2V communication, which allows cars to communicate with each other over a dedicated Wi-Fi band, and share information about vehicle speed, route direction, traffic flow, and road and weather conditions. An example of such a system is GM's (General Motors) OnStar, introduced in 1996, and that provides automatic response in case of an accident, stolen-vehicle recovery, remote door unlock, and vehicle diagnostics. Also, the standard On Board Diagnosis (OBD-II), available for several years, allows us to connect to the Electronic Control Unit (ECU) via a Bluetooth OBD-II connector. This connection interface allows connectivity between the smartphone and the vehicle, and can be purchased for just over 15 euros. The spectrum of possibilities that arise when combining the car and the smartphone is unlimited, such as performing the diagnosis of the car by assuming the tasks performed by the car's On Board Unit (OBU), or sending the collected data to a platform where the diagnosis or maintenance of the system can be realized in order to detect possible faults, help you to save gas and reduce environment pollution, and notify you of your car's problems, among other features. The general objective pursued with this doctoral thesis is to help drivers to correct bad habits in their driving. To achieve this we promote the combination between smartphones and vehicular networks to design and develop a platform able to offer useful tips to achieve safer driving and greater fuel economy. It is well-known that intelligent driving can lead to lower fuel consumption, with the consequent positive impact on the environment. The proposal that has been carried out in this doctoral thesis begins with the data capture from the vehicles' OBD-II port and data analysis through the use of graphs, maps, and statistics, both, on the server itself and in the smartphone's application developed. We applied data mining techniques and neural networks to analyze, study and generate a classiffication on driving styles based on the analysis of the characteristics of each specific route used for testing. In a second phase, we demostrate the relationship between fuel consumption and driving style. To achieve that goal, the first thing that we had to realize was how to apply different algorithms for the instantaneous consumption calculation (this parameter cannot be obtained directly from the vehicle ECU). Later, we studied and analyzed all data that was collected from the drivers who shared their monitored data with the server. Although drivers do not recognize themselves as being in a state of anxiety while driving, they are more stressed than in any other daily activity, for example, when trying to stay in the right lane, keeping the car at a certain speed, and starting and stopping the vehicle. In general, drivers are more concentrated than they think, which causes an increase in the heart rate. Many factors influence heart rate while at rest, e.g. stress, medications, medical conditions, even genes play a role. In our study we also investigate how stress and the driving behavior influence the heart rate. So, in the last phase, we demostrate the correlation between heart rate and driving style, showing how the driving style can make the heart rate vary by 3 %. / No hace mucho tiempo, tan sólo en la primera mitad en la década de los 90, cuando los teléfonos móviles aparecieron, eran grandes y caros, todo lo que se podía hacer con ellos era realizar llamadas telefónicas. Desde entonces los dispositivos móviles han experimentado un gran avance tecnológico, llevamos teléfonos inteligentes en el bolsillo con acceso a Internet, acelerómetros que calculan la aceleración instantánea, giroscopios que proporcionan información de orientación, diferentes conexiones inalámbricas como Bluetooth, y sobre todo, gran capacidad de computación. Por otro lado, la industria del automóvil ha evolucionado mucho durante los últimos 10 años. Uno de los avances más interesantes en el desarrollo de vehículos ha sido la conectividad, V2V, o comunicación vehículo a vehículo, permite a los automóviles comunicarse mediante Wi-Fi y compartir información sobre la velocidad del vehículo, la dirección de la ruta actual, el tráfico, así como las condiciones de la carretera y las condiciones ambientales. Por otra parte, el estándar On Board Diagnosis (OBD-II), disponible desde hace varios años, permite conectarnos de forma sencilla a la ECU (Electronic Control Unit) mediante un conector Bluetooth OBD-II. Este interfaz de conexión permite la conectividad entre el dispositivo móvil y el vehículo, se puede adquirir por poco más de 15 euros. El espectro de posibilidades que surgen al combinar el automóvil y el Smartphone es amplísimo, como por ejemplo realizar el diagnóstico del coche a través del móvil asumiendo las tareas que hace la unidad On Board Unit (OBU) del coche, o bien enviar los datos recogidos a una plataforma donde se pueda realizar el diagnóstico o mantenimiento del sistema, detectando posibles fallos puede ayudar a ahorrar en el consumo de combustible, notificar los problemas del coche en tiempo real, entre otras características. El objetivo general que se persigue con esta tesis doctoral es ayudar al conductor a corregir malos hábitos en su forma de conducción. Conseguimos esto mediante la combinación entre smartphones y las redes vehiculares, diseñamos y desarrollamos una plataforma capaz de ofrecer consejos útiles para conseguir una conducción más segura y un mayor ahorro de combustible. Es conocido que una conducción inteligente puede llevarnos a un menor consumo de combustible, con el consiguiente impacto positivo que ello conlleva sobre el medio ambiente. La propuesta que se ha llevado a cabo en esta tesis doctoral comienza con la obtención de los datos desde el OBD-II del coche y su presentación y análisis mediante el uso de gráficas, mapas, estadísticas, tanto en el propio servidor como en la aplicación móvil desarrollada para la obtención de datos recibidos desde la ECU. Se aplicaron técnicas de minería de datos y redes neuronales para analizar, estudiar y generar una clasificación sobre los estilos de conducción en base al análisis de las características de la vía sobre la que ha realizado la ruta. En una segunda fase se demostró la relación entre el consumo de combustible con el estilo de conducción, para ello lo primero que tuvimos que realizar fue aplicar diversos algoritmos para el cálculo del consumo instantáneo, este parámetro no es posible obtenerlo directamente de la ECU del vehículo. Posteriormente se realizó el estudio y el análisis de todos los datos que se recogieron de los conductores que se prestaron a la realización del estudio enviando los datos al servidor. Muchos factores influyen en la frecuencia cardíaca en reposo, por ejemplo, el estrés, los medicamentos, las condiciones médicas, incluso los genes tienen su influencia, el envejecimiento tiende a acelerarlo, y el ejercicio regular tiende a ralentizarlo. En nuestro estudio también investigamos cómo el estrés y el comportamiento en la conducción influyen en la frecuencia cardíaca. En la última fase vemos la correlación existente entre el ri / No fa molt de temps, tan sols en la primera mitat en la dècada dels 90, quan els telèfons mòbils van aparéixer, eren grans i cars, tot el que es podia fer amb ells era realitzar telefonades. Des de llavors els dispositius mòbils han experimentat un gran avanç tecnològic, portem telèfons intel_ligents en la butxaca amb accés a Internet, acceleròmetres que calculen l'acceleració instantània, giroscopis que proporcionen informació d'orientació, diferents connexions sense _ls com Bluetooth, i sobretot gran capacitat de computació. D'altra banda, la indústria de l'automòbil ha evolucionat molt durant els últims 10 anys. Un dels avanços més interessants en el desenrotllament de vehicles ha sigut la connectivitat, V2V, o comunicació vehicle a vehicle, permet als automòbils comunicar-se per mitjà de la banda de Wi-Fi i compartir información sobre la velocitat del vehicle, la direcció de la ruta actual, les condicions del trà_c, així com l'estat de la carretera i les condicions ambientals. D'altra banda l'estàndard On Board Diagnosi (OBD-II), disponible des de fa diversos anys, permet connectar-nos de forma senzilla a l'ECU (Electronic Control Unit) per mitjà d'un connector Bluetooth OBD-II. Esta interfície de connexió permet la connectivitat entre el dispositiu mòbil i el vehicle, es pot adquirir per poc més de 15 euros. L'espectre de possibilitats que sorgixen al combinar l'automòbil i el Smartphone és il_limitat, com per exemple realitzar el diagnòstic del cotxe a través del móvil assumint les tasques que fa la unitat On Board Unit (OBU) del cotxe, o bé enviar les dades arreplegades a una plataforma on es puga realitzar el diagnòstic o manteniment del sistema, detectant possibles fallades, ajuda a estalviar en el consum de combustible, noti_car els problemes del cotxe en temps real, entre altres característiques. L'objectiu general que es perseguix amb esta tesi doctoral és ajudar al conductor a corregir mals hàbits en la seua forma de conducció. Aconseguim açò mitjançant de la combinació entre smartphones i les xarxes vehiculares, dissenyem i desenrotllem una plataforma capaç d'oferir consells útils per a aconseguir una conducció més segura i un major estalvi de combustible. És conegut que una conducció intel_ligent pot emportar-nos a un menor consum de combustible, amb el consegüent impacte positiu que això comporta sobre el medi ambient. La proposta que s'ha dut a terme en esta tesi doctoral comença amb l'obtenció de les dades des de l'OBD-II del cotxe i la seua presentació i anàlisi per mitjà de l'ús de grà_ques, mapes, estadístiques, tant en el propi servidor, com en l'aplicació mòbil desenrotllada per a l'obtenció de dades rebudes des de l'ECU. S'apliquen tècniques de mineria de dades i xarxes neuronals per a analitzar, estudiar i generar una classi_cació sobre els estils de conducció basant-se en l'anàlisi de les característiques de la via sobre la qual ha realitzat la ruta. En una segona fase es va a demostrar la relació entre el consum de combustible amb l'estil de conducció, per a això la primera cosa que vam haver de realizar va ser aplicar diversos algorismes per al càlcul del consum instantani, este paràmetre no és possible obtindre-ho directament de l'ECU del vehicle. Posteriorment es va realitzar l'estudi i l'anàlisi de totes les dades que es van arreplegar dels conductors que es van prestar a la realització de l'estudi enviant les dades al servidor. Molts factors in_ueixen en la freqüència cardíaca en repòs, per exemple, l'estrès, els medicaments, les condicions mèdiques, _ns i tot els gens tenen la seua in_uència, l'envelliment tendeix a accelerar-ho, i l'exercici regular tendeix a ralentir-ho. En el nostre estudi només estem interessats en com l'estrès i el comportament en la conducció in_ueixen en la freqüència cardíaca. En l'última fase vam veure la correlació existent entre el ritme cardíac i l'estil de conducci / Meseguer Anastasio, JE. (2017). A novel framework to promote eco-driving through smartphone-vehicle integration [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/84287 / Compendio

Ausgangspunkt der Untersuchung ist die Frage, ob Hybridkonzepte auf hydrostatischer Grundlage eine realistische Alternative zu elektrohybriden Antriebskonfigurationen für Dieseltriebwagen sein können. Die Untersuchung dieser Fragestellung erfolgt mit Hilfe von Simulationsmodellen, die auf der 1-d-Simulationsumgebung Imagine.Lab AMESim beruhen. Zunächst wird die fahrdynamische und antriebstechnische Modellierung eines dieselhydraulischen Regionaltriebwagens unter Berücksichtigung einer energiesparenden Fahrweise dargestellt. Ausgehend von Massenbilanzen werden untereinander vergleichbare Hybridkonfigurationen auf hydrostatischer (Gasdruckspeicher), elektrostatischer (Doppelschichtkondensatoren) und elektrochemischer (Li-Ionen-Speicher) Basis entwickelt. Die Modellierung der hydraulischen und elektrischen Antriebsstränge wird eingehend diskutiert. Die abgeleiteten Hybridkonfigurationen werden anschließend bezüglich spezieller Fahrspiele und Betriebskonzepte detailliert untersucht, um auf dieser Grundlage günstige Parametrierungen der Systeme ableiten und die günstigste Betriebsstrategie identifizieren zu können. Anschließend wird eine umfangreiche Analyse des Verhaltens der verschiedenen Hybridkonfigurationen auf ausgewählten realen Nahverkehrsstrecken vorgenommen. Im Rahmen der durchgeführten Simulationen wird schließlich das Kraftstoffeinsparpotential in Abhängigkeit von Streckenprofil, Hybridkonfiguration und Zugart ermittelt und verglichen.

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.

The thesis deals with the current situation in the construction of tractors, particularly engines and accessories. The work includes a methodology for measuring tractor rigs in traffic as well as methodology for plough/plow kits measuring. The measured values were tabulated, graphically presented and analysed. The thesis provides an overview of the issue of the combustion engine load placed on the engine by working conditions in transport, during primary soil tillage with different modes of operation of the tractor set. The thesis aim is to find out the practical effect of the engine load on the monitored parameters and to indicate possibilities for achieving higher efficiency in tractor units with minimum fuel performance

Följande studie är gjord på uppdrag av Sjöfartsverket. I studien undersöktes hur en installation av ett Common Rail-system ombord på isbrytaren Ymer påverkat bränsleförbrukningen samt utsläppen av kväveoxider. Rådata som loggats ombord på Ymer har analyserat och bearbetat. Material och information från tillverkare, besättning samt teknisk chef på Sjöfartsverket, Albert Hagander har använts under studien. Tillsammans med uppmätta mätdata och tidigare gjord litteraturstudie stöds resultaten i studien. Det är ingen slump att system av Common Rail-typ redan är tillämpat inom de flesta branscher så som transport, personbilsindustri och jordbruk. Huvudsyftet med Common Rail är att minska bränsleåtgången samt minska utsläppen genom en renare och mer effektiv förbränning av bränslet.  Huvudsakligen undersöktes hur det nyinstallerade systemet påverkat bränsleförbrukningen och hur bränslebesparingen varierar med belastningen av maskinen. Vidare granskades hur utsläppen av kvävedioxider påverkats efter installationen. Problematiken med ökad NOx-produktion till följd av en högre förbränningstemperatur som Common Railsystemet medför diskuteras i rapporten. De resultat vi kommit fram till att en bränslebesparing kan göras ombord på Ymer genom att ersätta det gamla bränslesystemet med ett bränslesystem av Common Rail-typ. Vidare har installationen medfört andra förbättringar så som fartygsmaskinens reaktion på de många lastväxlingar som förekommer under isbrytning. / The following study has been carried out on behalf of Sjöfartsverket. The study examines how the installation of a common rail system on board the icebreaker Ymer affected fuel consumption and emissions of nitrogen oxides. The raw data logged on board Ymer was analyzed and processed. Materials and information from manufacturers, crew and the technical manager at the Swedish Maritime Administration, Albert Hagander have been used during the study. Together with measured data and previously made research study the findings of the study are supported. It is no coincidence that the system of the common rail type is already applied in most industries such as transport, car industry and agriculture. The main purpose of the Common Rail is to reduce fuel consumption and reduce emissions through cleaner and more efficient combustion of the fuel. We primarily examined how the newly installed system affected fuel consumption and the fuel savings will vary with the load of the machine. Furthermore, we examined how emissions of nitrogen oxides were affected after installation. The problem of increased NOx production due to a higher combustion temperature as the common rail system entails are discussed in the report. The result that was concluded was that fuel savings can be made on board Ymer by replacing the old fuel system with a common rail fuel type. Furthermore, the installation has brought other improvements such as ship machine's reaction to the many load changes that occur during icebreaking.

Dans un contexte où la consommation de carburant est un poste de coût de plus en plus important, la consommation et la vitesse moyenne d'un poids-lourds est l'une des caractéristiques clés estimées durant le développement des nouveaux véhicules. Ainsi, nous désirons créer différents modèles de conducteurs en termes de consommation et de vitesse moyenne, c'est à dire en termes de conduite rationnelle. Nous proposons une méthode en deux étapes: premièrement la reconnaissance des évènements de conduite grâce à des attributs de conduite. Puis la quantification de trois types de conduite différents sur ces évènements. Suite à ces deux étapes, nous pouvons implémenter nos résultats dans un outil qui crée différents modèles de conducteurs pour la simulation et le banc à rouleaux. Les écarts entre conducteurs se mesurent en termes de consommation de carburant et de vitesse moyenne. Le taux de classification des évènements s'étend de 74% à 91% selon le type d'évènements. Ces résultats sont dus à la nature même des données et aux similarités entre les classes, mais nous estimons que ces taux sont suffisants pour notre application. Nous obtenons également des corrélations prometteuses entre les attributs de conduite sélectionnés et l'indicateur de conduite rationnelle. Nous avons notamment porté notre étude sur les évènements classiques: les ronds-points, les péages et les arrêts. Les résultats de l'outil que nous avons développé sont pertinents. Nous pouvons désormais simuler différents types de chauffeurs. Sur nos essais en simulation, l'adaptation de seulement 10% des évènements d'un cycle découle sur un gain en consommation de 1.5% et une vitesse moyenne 3% plus élevée pour un conducteur efficace. Ces résultats sont encourageants, surtout que le travail à venir visera à augmenter la diversité des évènements couverts. / Realistic driver behavior modeling for energy efficiency estimation during heavy-trucks vehicles development Abstract: In the context where fuel consumption is a growing cost center, fuel consumption of a truck coupled with its average speed is one of the key vehicle characteristics that needs to be optimized and accurately estimated during the truck design process. Consequently, we aim to create different driver behavior models for testing trucks regarding fuel consumption and average speed issues, i.e., rational driving. We propose a two-step method to model more accurately driving behavior: first, the identification of driving events through driving features. Second, the quantification of three different driving behaviors on the recognized driving events. Then we implement our results in a tool that creates these different driving behaviors. The output of this tool is a cycle adapted to a driver type in terms of fuel consumption and average speed, and that can be used in simulation and on chassis-dynamometer. The classification of driving events reaches classification rates between 74% and 91% depending on the events. We believe that they are sufficient for our application due to the raw nature of driving events and the similarities between the different classes. We also obtain promising results concerning the correlation between driving features and rational driving index. We focus especially on typical events, namely roundabout on extra-urban roads, toll on highways and stop on urban roads. The results of the developed tool prove to be efficient since we can now simulate different driving behaviors. On our test run in simulation, adapting only 10% of the events of a cycle produces fuel savings of 1.5% and an average speed which is 3% faster for an efficient driver than a non-efficient driver. These results are promising and we need to implement other events in the future.

This dissertation focuses on the introduction and development of an integrated model-based design and optimization platform to solve the optimal design and optimal control, or hardware and software co-design, problem for hybrid electric propulsion systems. Specifically, the hybrid and plug-in hybrid electric powertrain systems with diesel and natural gas (NG) fueled compression ignition (CI) engines and large Li-ion battery energy storage system (ESS) for propelling a hybrid electric marine vessel are investigated. The combined design and control optimization of the hybrid propulsion system is formulated as a bi-level, nested optimization problem. The lower-level optimization applies dynamic programming (DP) to ensure optimal energy management for each feasible powertrain system design, and the upper-level global optimization aims at identifying the optimal sizes of key powertrain components for the powertrain system with optimized control. Recently, Li-ion batteries became a promising ESS technology for electrified transportation applications. However, these costly Li-ion battery ESSs contribute to a large portion of the powertrain electrification and hybridization costs and suffer a much shorter lifetime compared to other key powertrain components. Different battery performance modelling methods are reviewed to identify the appropriate degradation prediction approach. Using this approach and a large set of experimental data, the performance degradation and life prediction model of LiFePO4 type battery has been developed and validated. This model serves as the foundation for determining the optimal size of battery ESS and for optimal energy management in powertrain system control to achieve balanced reduction of fuel consumption and the extension of battery lifetime. In modelling and design of different hybrid electric marine propulsion systems, the life cycle cost (LCC) model of the cleaner, hybrid propulsion systems is introduced, considering the investment, replacement and operational costs of their major contributors. The costs of liquefied NG (LNG), diesel and electricity in the LCC model are collected from various sources, with a focus on present industrial price in British Columbia, Canada. The greenhouse gas (GHG) and criteria air pollutant (CAP) emissions from traditional diesel and cleaner NG-fueled engines with conventional and optimized hybrid electric powertrains are also evaluated. To solve the computational expensive nested optimization problem, a surrogate model-based (or metamodel-based) global optimization method is used. This advanced global optimization search algorithm uses the optimized Latin hypercube sampling (OLHS) to form the Kriging model and uses expected improvement (EI) online sampling criterion to refine the model to guide the search of global optimum through a much-reduced number of sample data points from the computationally intensive objective function. Solutions from the combined hybrid propulsion system design and control optimization are presented and discussed. This research has further improved the methodology of model-based design and optimization of hybrid electric marine propulsion systems to solve complicated co-design problems through more efficient approaches, and demonstrated the feasibility and benefits of the new methods through their applications to tugboat propulsion system design and control developments. The resulting hybrid propulsion system with NG engine and Li-ion battery ESS presents a more economical and environmentally friendly propulsion system design of the tugboat. This research has further improved the methodology of model-based design and optimization of hybrid electric marine propulsion systems to solve complicated co-design problems through more efficient approaches, and demonstrated the feasibility and benefits of the new methods through their applications to tugboat propulsion system design and control developments. Other main contributions include incorporating the battery performance degradation model to the powertrain size optimization and optimal energy management; performing a systematic design and optimization considering LCC of diesel and NG engines in the hybrid electric powertrains; and developing an effective method for the computational intensive powertrain co-design problem. / Graduate

This report describes a thesis project conducted at Direktflyg in Borlänge, in early 2012, where the aim was to analyse the difference in noise level, audio frequency and fuel consumption between propellers of the older type McCauley and the newer type MT on the aircraft type BAe Jetstream 32. To perform the analysis, the authors reviewed current procedures regarding noise certification from air safety agencies to be able to identify suitable methods for the noise level and audio frequency measurements. The results of the conducted noise level measurements show a general lower noise level throughout the cabin and a significant reduction in noise level behind row 2 when using the MT propeller compared to the McCauley type. In practice this means a lower perceived noise level for most passengers at an average passenger load factor. The frequency measurements show that the MT propeller generates audio frequencies which are perceived as lower in noise levels and are therefore more comfortable for passengers. The fuel consumption was also slightly lower when using the MT propeller compared to the McCauley type over the assigned time period and the determined limiting parameters. / Denna rapport beskriver ett examensarbete som genomfördes på Direktflyg i Borlänge under början av 2012, där syftet var att analysera skillnaden i ljudnivå, ljudfrekvens och bränslekonsumtion på flygplanstypen Jetstream 32 efter genomfört byte av propellrar från typen McCauley till typen MT på en av bolagets flygplansindivider. För att genomföra analysen har författarna granskat gällande procedurer angående ljudnivåmätning från styrande luftsäkerhetsorgan för att sedan kunna fastställa passande metoder för utförandet av ljudnivå- samt ljudfrekvensmätningar. Resultaten från ljudnivåmätningarna visar på en lägre ljudnivå över hela kabinen samt betydligt lägre ljudnivå bakom rad 2 vid användning av MT-propellrar jämfört med McCauley. I praktiken innebär detta en lägre upplevd ljudnivå för de flesta passagerare vid en genomsnittlig kabinfaktor. Frekvensmätningarna visar att MT-propellern genererar ljudfrekvenser som uppfattas som lägre i ljudnivå och därav också som behagligare för passagerarna. Bränslekonsumtionen var vidare något lägre vid användande av MT-propellrar jämfört med McCauley över den tidsperiod som innefattades inom arbetet och de begränsande parametrar som fastställdes.

The need for a reduced dependence on fossil fuels is motivated by a wide range of factors: from increasing fuel costs, to national security implications of supply, to rising concern for environmental impact. Although much focus is given to terrestrial systems, over 90% of the world's freight is transported by ship. Likewise, naval warfighting systems are critical in supporting U.S. national interests abroad. Yet the vast majority of these vessels rely on fossil fuels for operation. The results of this thesis illustrate a common theme that hybrid mechanical-electrical marine propulsion systems produce substantially better fuel efficiency than other technologies that are typically emphasized to reduce fuel consumption. Naval and commercial powertrains in the 60-70 MW range are shown to benefit substantially from the utilization of mechanical drive for high speed propulsion; complemented by an efficient electric drive system for low speed operations. This hybrid architecture proves to be able to best meet the wide range of performance requirements for each of these systems, while also being the most easily integrated technology option. Naval analyses evaluate powertrain options for the DDG-51 Flight III. Simulation results using actual operational profile data show a CODLAG system produces a net fuel savings of up to 12% more than a comparable all-electric system, corresponding to a savings of 37% relative the existing DDG-51 powertrain. These results prove that a mechanical linkage for the main propulsion engine greatly reduces fuel consumption and that for power generation systems requiring redundancy, diesel generators represent a vastly superior option to gas turbines. For the commercial application it is shown that an augmented PTO/PTI hybrid system can better reduce cruise fuel consumption than modern sail systems, while also producing significant benefit with regard to CO2 emissions. In addition, using such a shaft mounted hybrid system for low speed electric drive in ports reduces NOx emissions by 29-43%, while CO is reduced 57-66% and PM may be reduced up to 25%, depending on the specific operating mode. As an added benefit, fuel consumption rates under these conditions are reduced 20-29%. / text