In early design phase for new hybrid electric vehicle (HEV) powertrains, simulation isused for the estimation of vehicle fuel consumption. For hybrid electric powertrains,fuel consumption is highly related to powertrain efficiency. While powertrainefficiency of hybrid electric powertrain is not a linear product of efficiencies ofcomponents, it has to be analysed as a sequence of energy conversions includingcomponent losses and energy interaction among components.This thesis is aimed at studying the energy losses and flows and present them in theform of Sankey diagram, later, an adaptive energy management system is developedbased on current rule-based control strategy. The first part involves developing energycalculation block in GT-SUITE corresponding to the vehicle model, calculating allthe energy losses and flows and presenting them in Sankey diagram. The secondpart involves optimizing energy management system control parameters according todifferent representative driving cycles. The third part involves developing adaptiveenergy management system by deploying optimal control parameter based on drivingpattern recognition with the help of SVM (support vector machine).In conclusion, a sturctured way to generate the Sankey diagram has been successfullygenerated and it turns out to be an effective tool to study HEV powertrain efficiencyand fuel economy. In addition, the combination of driving pattern recognition andoptimized control parameters also show a significant potential improvement in fuelconsumption. / Under den tidiga utvecklingsfasen av nya elektrifieradedrivlinor for hybridapplikationer (HEV) används simulering för uppskattning avfordonets bränsleförbrukning. För dess drivlinor är bränsleförbrukningen i hög gradkopplad till drivlinans verkningsgrad. Även om drivlinans verkningsgrad inte ären linjär prokukt av komponenternas verkningsgrad behöve rden analyseras somen sekvens av energiomvandlingar, inklusive förluster och energipåverkan mellankomponenter.Detta examensarbete syftar till att undersöka energiförluster och flöden samtpresentera dessa i form av sankey diagram. Senare utvecklas ett anpassningsbartenergihanteringssystem baserat på nuvarande regelbaserad kontrollstrategi. Deninledande delen involverar utvecklandet av energianalys i GT-SUITE som motsvararfordonsmodellen, beräkningar av totala energiförluster och flöden samt presentationav dessa i ett sankey diagram. Den andra delen innefattar optimering avenergihanteringssystems kontrollparametrar enligt olika representativa körcykler.Den tredje delen involverar utveckling av anpassningsbara energihanteringssystemgenom användning av optimala kontrollparameterar baserad på detektering avkörbeteende med hjälp av SVM ( stödvektormaskin).Slutligen, ett strukturerat sätt att generera sankey diagrammet har med framgånggenererats och visat sig vara ett effektivt verktyg för studier av HEV drivlinorseffektivitet och bränsleekonomi. Dessutom visar kombinationen av detektering avkörbeteende och optimerade kontrollparametrar på en markant potentiell förbättringi bränsleförbrukning.

The automotive industry is facing some of the most difficult design challenges in industry history. Developing innovative methods to reduce fossil fuel dependence is imperative for maintaining compliance with government regulations and consumer demand. In addition to powertrain design, route selection contributes to vehicle environmental impact. The objective of this thesis is to develop a methodology for evaluating the energy consumption of each route option for a specific vehicle. A 'backwards' energy tracking method determines tractive demand at the wheels from route requirements and vehicle characteristics. Next, this method tracks energy quantities at each powertrain component. Each component model is scalable such that different vehicle powertrains may be approximated. Using an 'ecorouting' process, the most ideal route is selected by weighting relative total energy consumption and travel time. Only limited powertrain characteristics are publicly available. As the future goal of this project is to apply the model to many vehicle powertrain types, the powertrain model must be reasonably accurate with minimal vehicle powertrain characteristics. Future work expands this model to constantly re-evaluate energy consumption with real-time traffic and terrain information. While ecorouting has been applied to conventional vehicles in many publications, electrified vehicles are less studied. Hybrid vehicles are particularly complicated to model due to additional components, systems, and operation modes. This methodology has been validated to represent conventional, battery electric, and parallel hybrid electric vehicles. A sensitivity study demonstrates that the model is capable of differentiating powertrains with different parameters and routes with different characteristics. / Master of Science

The Hybrid Electric Vehicle Team of Virginia Tech (HEVT) is participating in the 2012-2014 EcoCAR 2: Plugging in to the Future Advanced Vehicle Technology Competition series organized by Argonne National Lab (ANL), and sponsored by General Motors Corporation (GM) and the U.S. Department of Energy (DOE). The goals of the competition are to reduce well-to-wheel (WTW) petroleum energy consumption (PEU), WTW greenhouse gas (GHG) and criteria emissions while maintaining vehicle performance, consumer acceptability and safety. Following the EcoCAR 2 Vehicle Development Process (VDP) of designing, building, and refining an advanced technology vehicle over the course of the three year competition using a 2013 Chevrolet Malibu donated by GM as a base vehicle, the selected powertrain is a Series-Parallel Plug-In Hybrid Electric Vehicle (PHEV) with P2 (between engine and transmission) and P4 (rear axle) motors, a lithium-ion battery pack, an internal combustion engine, and an automatic transmission. Development of a charge sustaining control strategy for this vehicle involves coordination of controls for each of the main powertrain components through a distributed control strategy. This distributed control strategy includes component controllers for each individual component and a single supervisory controller responsible for interpreting driver demand and determining component commands to meet the driver demand safely and efficiently. For example, the algorithm accounts for a variety of system operating points and will penalize or reward certain operating points for other conditions. These conditions include but are not limited to rewards for discharging the battery when the state of charge (SOC) is above the target value or penalties for operating points with excessive emissions. Development of diagnostics and remedial actions is an important part of controlling the powertrain safely. In order to validate the control strategy prior to in-vehicle operation, simulations are run against a plant model of the vehicle systems. This plant model can be run in both controller Software- and controller Hardware-In-the-Loop (SIL and HIL) simulations. This paper details the development of the controls for diagnostics, major selection algorithms, and execution of commands and its integration into the Series-Parallel PHEV through the supervisory controller. This paper also covers the plant model development and testing of the control algorithms using controller SIL and HIL methods. This paper details reasons for any changes to the control system, and describes improvements or tradeoffs that had to be made to the control system architecture for the vehicle to run reliably and meet its target specifications. Test results illustrate how changes to the plant model and control code properly affect operation of the control system in the actual vehicle. The VT Malibu is operational and projected to perform well at the final competition. / Master of Science

<pre>Coherent lidar uses a chirped laser pulse for 3D imaging of distant targets.However, existing coherent lidar image reconstruction methods do not account for the system's aperture, resulting in sub-optimal resolution.Moreover, these methods use majorization-minimization for computational efficiency, but do so without a theoretical treatment of convergence.<br> <br>In this work, we present Coherent Lidar Aperture Modeled Plug-and-Play (CLAMP) for multi-look coherent lidar image reconstruction.CLAMP uses multi-agent consensus equilibrium (a form of PnP) to combine a neural network denoiser with an accurate physics-based forward model.CLAMP introduces an FFT-based method to account for the effects of the aperture and uses majorization of the forward model for computational efficiency.We also formalize the use of majorization-minimization in consensus optimization problems and prove convergence to the exact consensus equilibrium solution.Finally, we apply CLAMP to synthetic and measured data to demonstrate its effectiveness in producing high-resolution, speckle-free, 3D imagery.</pre><p></p>

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.

El sector hortícola del Litoral Norte del Uruguay tiene como objetivo la oferta de fresón principalmente en los meses de invierno. Frente a una falta de abastecimiento de plantas adecuadas para una producción precoz, se ha desarrollado un método de cultivo basado en plantas locales, obtenidas a través del enraizado directamente en maceta en el vivero y cultivares resultantes del proyecto de mejora genética nacional, siendo "INIA Yvahé" el más utilizado. La planta de maceta directa ha mostrado problemas de adaptación en cultivares como "Camarosa". Además existen nuevas selecciones avanzadas nacionales con mayor resistencia a oidio y ácaros que "Yvahé" y nuevos cultivares introducidos del exterior que es necesario evaluar. El método de producción de plantas en bandeja de alvéolos o "plug plant" demanda menos demanda de mano de obra, sustrato y costos de transporte. La zona norte también dispone de infraestructura de invernaderos que podrían ser una alternativa a los túneles bajos por menor tiempo de manejo y mayores oportunidades de realizar operaciones en el cultivo. Durante tres campañas, entre 2006 y 2008, se investigó la influencia en el comportamiento productivo, vegetativo, fenológico y de calidad de fruta de tipos de planta con cepellón, la fecha de plantación, cultivares y sistemas de forzado y la interacción entre dichos factores. El cultivar ("Guenoa"), con maceta directa y trasplante a mediados de marzo, obtuvo los mejores resultados en producción, peso medio de fruto y estabilidad en la producción de invierno entre campañas. En "Camarosa" se encontraron mejoras en su comportamiento con maceta directa al retrasar el trasplante y también con el uso de plantas en bandejas, lográndose un mejor equilibrio entre precocidad y desarrollo de planta. La producción fue mayor con túnel bajo que en invernadero, aunque la influencia de los factores fue independiente del forzado. / Vicente Castro, CE. (2009). Bases para la utilización de plantas con cepellón como material de plantación del fresón: influencia de la fecha de plantación y los cultivares bajo cultivo protegido en el Litoral Norte de Uruguay [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/6477

Целью исследования является создание эффективного инструмента на платформе визуального программирования Dynamo в Autodesk Revit для автоматизации аэродинамического расчета систем воздуховодов в цифровой информационной модели. Задачи: исследовать возможности платформы визуального программирования Dynamo; разработать алгоритмы и скрипты для проведения аэродинамики в цифровой информационной модели. Гипотеза исследования предполагает, что автоматизация аэродинамического расчета позволит сократить время проектирования и уменьшить вероятность ошибок. Результаты исследования подтвердили эффективность использования разработанного скрипта для автоматизации расчета: он ускоряет процесс, обеспечивает более точные результаты и повышает качество проектных решений в области вентиляции. / The aim of the study is to create an effective tool on the Dynamo visual programming platform in Autodesk Revit for automating the aerodynamic calculation of duct systems in a digital information model. Tasks: to explore the possibilities of the Dynamo visual programming platform; to develop algorithms and scripts for conducting aerodynamics in a digital information model. The hypothesis of the study suggests that automation of aerodynamic calculation will reduce design time and reduce the likelihood of errors. The results of the study confirmed the effectiveness of using the developed script to automate the calculation: it speeds up the process, provides more accurate results and improves the quality of design solutions in the field of ventilation.

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Ces travaux de thèse consistent en la conception et la réalisation d’une chaîne de tractionintégrée pour véhicule hybride plug-in. L’étude s’oriente vers une solution de convertisseur mutualisé,dans l’objectif de partager la traction et les modes chargeurs de batteries, la structure en NPC à 3niveaux est retenue. Le chargeur monophasé se base une topologie de redresseur à MLI monophaséavec trois bras entrelacés, avec l’utilisation des enroulements du moteur pour le filtrage. En chargeurtriphasé nous adaptons la topologie pour réaliser un montage en double boost triphasé. Pour chaqueconfiguration, les passifs sont dimensionnés pour répondre aux contraintes en courant BF et HF. Lecontrôle adopté se base sur les correcteurs résonants. Enfin, un prototype de 5 kW a été réalisé pourvalider les différents modes de l’application.Dans une seconde partie, nous proposons une solution de chargeur isolé sans étage continu auprimaire à double ponts actifs (DAB). La topologie est modélisée au premier harmonique et unecommande assurant l’absorption sinusoïdale est étudiée. Une configuration isolée triphasée permetl’accès aux puissances plus élevées ainsi que la réduction des ondulations de courant BF en sortie. / This thesis consists on the design and realization of a plug-in hybrid vehicle integrated tractiondrive supply. The work turns to a solution of a mutualized converter, in the objective to imagine asolution which shared drive and battery chargers modes, the three-level NPC topology has beenretained. The single phase charger is based on an interleaved PWM rectifier, and motor windings areused as smoothing inductors. A double-boost PFC configuration is introduced to ensure the threephasecharger. Passives are sized in each configuration in order to take in account the whole currentconstraints (LF and HF). The PFC behavior is based on the resonant controllers. Then, a 5 kWprototype has been realized to validate the different application modes.In a second part, a single-stage isolated charger based on a Dual-Active-Bridge (DAB) isproposed. The topology is modeled to the fundamental and the PFC control law is studied. A threephaseconfiguration is simulated in order to achieve higher charging powers and to reduce batterycurrent low-frequency ripple.

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