Simulation modeling is important for resource management and operational strategy within the industry. Optimation AB specializes in modeling and simulation of complex systems using Dymola, but also offers solutions for decision support by solving simplified optimal control problems (OCPs). Since simulation models can be exported as functional mock-up units (FMUs), interfacing the underlying equations, this thesis explores the use of FMUs to formulate and solve OCPs in Python, proposing a workflow based on the softwares CasADi, Rockit and IPOPT. Test cases of increasing complexity, including a cogeneration plant OCP, were employed to evaluate the workflow. Promising results were obtained for simplified models, though scaling, initial guesses and solver settings require further consideration. Collocation demonstrated the fastest convergence time and overall robustness. It could be concluded that integrating FMUs into OCPs is feasible, although complex models require modifications. This suggest that creating simplified component libraries in Dymola, tailored for optimization, could improve method implementation and re-usability.

La contribution des sources d'énergie renouvelables dans le mix de la production d'électricité augmente largement. De ce fait, l'intégration des technologies de stockage d'énergie dans le réseau électrique devient inévitable afin de remédier aux inconvénients des sources renouvelables. Ainsi, l'objectif de cette thèse est d'évaluer la rentabilité, d'optimiser et d'étudier le comportement dynamique d'un cycle adiabatique de stockage d'énergie par air comprimé fonctionnant à pression fixe (IA-CAES). Ce système est caractérisé d'une part par la récupération de la chaleur de compression et d'autre part par le stockage d'air comprimé sous pression fixe dans des réservoirs hydropneumatiques. Ceux-ci permettent d'améliorer l'efficacité et la densité énergétiques du système de stockage et d'éviter l'utilisation de sources d'énergie fossiles.Tout d'abord, un modèle statique est développé pour achever des analyses énergétiques et exergétique du système IA-CAES. Un modèle exergoéconomique est également réalisé dans le but d'optimiser la rentabilité du système de stockage en utilisant un algorithme génétique. Ainsi, une fonction objective, qui prend en compte le coût d'investissement et le coût d'exploitation, est définie pour être minimisée. L'efficacité du système est de 55,1% dans le cas de base, elle est améliorée à 56,6% après optimisation avec une diminution du capital investi de 5,6%.D'autre part, un modèle dynamique est développé pour étudier la flexibilité du système de stockage et sa capacité à répondre aux besoins du réseau électrique (réserves primaires et secondaires) en évaluant la durée des phases transitoires. Les résultats montrent que le système de stockage a besoin d’un temps supérieur à 2 min avant de pouvoir consommer tout l'excès d'énergie disponible sur le réseau électrique et supérieur à 5 min avant d'être capable de produire toute l'énergie requise par le réseau électrique. Des suggestions sont analysées dans l'objectif d'améliorer la flexibilité du système de stockage tel que le fonctionnement du système en mode de veille avec des vitesses réduites. Il permet de réduire les pertes d'énergie de 68% en mode de stockage et de 27% en mode de production par rapport au mode de veille en vitesses nominales. / The contribution of the renewable energy sources in the electricity generation mix is greatly increasing. Thereby, the integration of the energy storage technologies into the electrical grid is becoming crucial to reduce the drawbacks of the renewable energy sources. Then, the objective of this thesis is to evaluate the cost-effectiveness, to optimize and to study the transient behavior of a novel isobaric adiabatic compressed air energy storage (IA-CAES) system. This plant is characterized by the recovery of the compression heat and the storage of the compressed air under fixed pressure in hydro-pneumatic tanks. These allow improving the efficiency and the energy density of the storage system and avoiding the use of fossil fuel sources.Firstly, a steady state model is developed to perform energy and exergy analyses of the IA-CAES system. An exergoeconomic model is also carried out in order to optimize the cost-effectiveness of the storage system by using a genetic algorithm. So, an objective function, which includes the investment cost and the operating cost, is defined to be minimized. The system efficiency is 55.1% in the base case, it is improved to 56.6% after optimization with a decrease in the capital investment by 5.6%.Secondly, a dynamic model is developed to study the flexibility of the storage system and its ability to meet the electrical grid requirements (primary and secondary reserves) by evaluating the duration of the transient states. The results show that the storage system needs more than 2 min before being able to consume all the excess energy available on the electrical grid and more than 5 min before being able to produce all the energy required by the electrical grid. Suggestions are analyzed to improve the flexibility of the storage system such as the operation of the storage system in standby mode with low speeds. It allows reducing the energy losses by 68% during the storage mode and by 27% during the production mode compared to the standby mode in nominal speeds.

Two methods using lumped element (lumped parameter) methods to model flexible bodies have been presented. The methods are based on the concept of using a Guyan reduced stiffness matrix to describe the elasticity of a body. The component to be modeled has been divided into two parts using FE software and the mass and inertia tensor for the respective part of the component have been retrieved. The first method has been based on including the elements from the stiffness matrix in compliant constraints. The compliant constraints have been derived and a prototype has been implemented in MATLAB. It has been shown that using compliant constraints and stiffness parameters from a Guyan reduced stiffness matrix it is possible, with highly accurate results, to describe the deformation of a flexible body in multibody simulations. The second method is based on springs and dampers and has been implemented in the simulation environment Dymola. The springs and dampers have been constructed to include coupling elements from a Guyan reduced stiffness matrix. It has been shown that using the proposed method it is possible, with highly accurate results, to describe the static deformation of a flexible body. Further, using dynamic simulations of a full robot manipulator model, it has been shown that it is possible to use the spring-damper model to capture the deformation of the links of a manipulator in dynamic simulations with large translations and rotations.

<p>Development of modern aircraft has become more and more expensive and time consuming. In order to minimize the development cost, an improvement of the conceptual design phase is needed. The desired goal of the project is to enhance the functionality of an in house produced framework conducted at the department of machine design, consisting of parametric models representing a large variety of aircraft concepts.</p><p>The first part of the work consists of the construction of geometric aircraft control surfaces such as flaps, aileron, rudder and elevator parametrically in CATIA V5.</p><p>The second part of the work involves designing and simulating an Inverse dynamic model in Dymola software.</p><p>An Excel interface has been developed between CATIA and Dymola. Parameters can be varied in the interface as per user specification; these values are sent to CATIA or Dymola and vice versa. The constructed concept model of control surfaces has been tested for different aircraft shapes and layout. The simulation has been done in Dymola for the control surfaces.</p>

<p>As modeling and simulation becomes a more important part of the modeling process, the demand on a known accuracy of the results of a simulation has grown more important. Sensitivity analysis (SA) is the study of how the variation in the output of a model can be apportioned to different sources of variation. By performing SA on a system, it can be determined which input/inputs influence a certain output the most. The sensitivity measures examined in this thesis are the Effective Influence Matrix, EIM, and the Main Sensitivity Index, MSI.</p><p>To examine the sensitivity measures, two tests have been made. One on a laboratory equipment including a hydraulic servo, and one on the conceptual landing gear model of the Gripen aircraft. The purpose of the landing gear experiment is to examine the influence of different frictions on the unfolding of the landing gear during emergency unfolding. It is also a way to test the sensitivity analysis method on an industrial example and to evaluate the EIM and MSI methods.</p><p>The EIM and MSI have the advantage that no test data is necessary, which means the robustness of a model can be examined early in the modeling process. They are also implementable in the different stages of the modeling and simulation process. With the SA methods in this thesis, documentation can be produced at all stages of the modeling process. To be able to draw correct conclusions, it is essential that the information that is entered into the analysis at the beginning is well chosen, so some knowledge is required of the model developer in order to be able to define reasonable values to use.</p><p>Wishes from the model developers/users include: the method and model quality measure should be easy to understand, easy to use and the results should be easy to understand. The time spent on executing the analysis has also to be well spent, both in the time preparing the analysis and in analyzing the results.</p><p>The sensitivity analysis examined in this thesis display a good compromise between usefulness and computational cost. It does not demand knowledge in programming, nor does it demand any deeper understanding of statistics, making it available to both the model creators, model users and simulation result users.</p>

Development of modern aircraft has become more and more expensive and time consuming. In order to minimize the development cost, an improvement of the conceptual design phase is needed. The desired goal of the project is to enhance the functionality of an in house produced framework conducted at the department of machine design, consisting of parametric models representing a large variety of aircraft concepts. The first part of the work consists of the construction of geometric aircraft control surfaces such as flaps, aileron, rudder and elevator parametrically in CATIA V5. The second part of the work involves designing and simulating an Inverse dynamic model in Dymola software. An Excel interface has been developed between CATIA and Dymola. Parameters can be varied in the interface as per user specification; these values are sent to CATIA or Dymola and vice versa. The constructed concept model of control surfaces has been tested for different aircraft shapes and layout. The simulation has been done in Dymola for the control surfaces.

As modeling and simulation becomes a more important part of the modeling process, the demand on a known accuracy of the results of a simulation has grown more important. Sensitivity analysis (SA) is the study of how the variation in the output of a model can be apportioned to different sources of variation. By performing SA on a system, it can be determined which input/inputs influence a certain output the most. The sensitivity measures examined in this thesis are the Effective Influence Matrix, EIM, and the Main Sensitivity Index, MSI. To examine the sensitivity measures, two tests have been made. One on a laboratory equipment including a hydraulic servo, and one on the conceptual landing gear model of the Gripen aircraft. The purpose of the landing gear experiment is to examine the influence of different frictions on the unfolding of the landing gear during emergency unfolding. It is also a way to test the sensitivity analysis method on an industrial example and to evaluate the EIM and MSI methods. The EIM and MSI have the advantage that no test data is necessary, which means the robustness of a model can be examined early in the modeling process. They are also implementable in the different stages of the modeling and simulation process. With the SA methods in this thesis, documentation can be produced at all stages of the modeling process. To be able to draw correct conclusions, it is essential that the information that is entered into the analysis at the beginning is well chosen, so some knowledge is required of the model developer in order to be able to define reasonable values to use. Wishes from the model developers/users include: the method and model quality measure should be easy to understand, easy to use and the results should be easy to understand. The time spent on executing the analysis has also to be well spent, both in the time preparing the analysis and in analyzing the results. The sensitivity analysis examined in this thesis display a good compromise between usefulness and computational cost. It does not demand knowledge in programming, nor does it demand any deeper understanding of statistics, making it available to both the model creators, model users and simulation result users.

Computer aided calculations are booming nowadays and thanks to more powerfull computers and sofistikated simulators we are able to modelling more and more complex problems in much more engineering domains. Also in power engineering are are simulators used more frequntly. They are used for or checking transmission lines and in testing different kinds of working states including fails.

With increasing oil price and mounting environment concerns, cleaner and sustainable energy solutions have been demanded. At present transportation constitutes a large portion of the energy consumed and pollution created. In this work, two hybrid vehicle powertrain technologies were studied, a fuel cell - battery hybrid and two internal combustion engine - battery/ultracapacitor hybrids. Powertrain performance models were built to simulate the performance of these new designs, and to assess the feasibility of a fuel cell hybrid power backup system for a special type of vehicles, elevators in high-rise buildings, using the ADvanced VehIcle SimulatOR (ADVISOR) first. The model was then applied to evaluate the two-mode hybrid powertrain for more common vehicles - commercial trucks, showing potential fuel consumption reduction. To improve modeling accuracy, a new and more flexible tool for modeling multi-physics systems, Modelica/Dymola, was used to carry out the modeling and analysis of next generation hybrid electric vehicles, exploring the potentials of new hybrid powertrain architectures and energy storage system designs. The study forms the foundation for further research and developments.

Im Rahmen der vorliegenden Arbeit werden dynamische Modelle eines IGCC-Kraftwerkes mit CO2-Abtrennung unter Verwendung des Modellierungstools Modelica/Dymola entwickelt. Dabei liegt der Schwerpunkt auf dem Gaspfad der Gasreinigung. Es ist vorteilhaft, für verschiedene Aufgaben, Modelle mit unterschiedlicher Tiefe zu verwenden. Mit den detaillierten Modellen werden Simulationen der Teilprozesse durchgeführt. Für den Aufbau eines Gesamtsystems werden vereinfachte Modelle verwendet. Anhand des Gesamtsystems werden drei Regelkonzepte (Gleitdruckregelung, Leistungsregelung der Gasturbine, Leistungsregelung des Vergasers) untersucht und bewertet. Des Weiteren werden drei Störfallszenarien (Ausfall des Sättigers im Brennstoffsystem, Betriebsstörung in der Vergaserinsel, Unterbrechung der Stickstoffzumischung im Brennstoffsystem) getestet.