Linköping Electronic Conference Proceedings
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Multiphysics Acausal Modeling and Simulation of Satellites using a Modelica Library
Full text linkThe multiphysics modeling has a great importance when a complex space system (as a satellite) is considered. Indeed, it is necessary to analyse how the system’s behavior is affected by the space environment or by on board failures. In this paper, the Modelica Library is used to hierarchically build and connect the main subsystems that can be found in a traditional satellite. Specifically, the modeling and simulation of the entire system is carried out in the Dymola environment. Finally, the FMI is applied to simulate in Dymola some specific satellite models/logics created with higher fidelity in the Matlab/Simulink domain
Evaluation of environmental and economic impact of wind turbine blade manufacture at life-cycle level
Full text linkLife cycle analysis is considered as a valuable decision-making tool to oversee the environmental impact of a product through its various stages. Starting from the raw material sourcing up to the end-of-life processes of the product. Life cycle costing is added to the life cycle analysis to augment the economic aspects. One of the main drawbacks of the life cycle analysis is the focus on single path for the life stages as it evaluates single option for each life stage and adds the impact to the following stages. This study presents a tool to evaluate the environmental and economic impact of different options in life cycle stages, determine the possible combination of different life cycle choices, and calculate the emissions, energy intensity and cost of each combination scenario. The study takes wind turbine blade as a case study, where glass fiber reinforced polymers and carbon fibers reinforced polymers are considered as a row material alternative with two supply options Europe or China markets, four manufacturing site options (onsite, Denmark, Germany, and China) and four end of life processing options (reuse, pyrolysis, landfill, and mechanical grinding). The results range the different combinations scenarios emissions in the range of (74 – 17) tons of CO2 eq, the energy intensity between 261 GJ and 863 GJ, and the cost vary from 89000€ to 22,000€. This work presented a logical method for mapping, analyzing, and evaluating the environmental and economic sustainability of a wind turbine blade through different life cycle pathways
A Battery model for transportation and stationary applications
Full text linkBatteries are used in electric vehicles as well as for stationary applications. In the first case we usually want a high energy density as kWh/kg, while stationary applications are less sensitive to the energy density. Principally it may be a good idea to first use batteries for transportation applications and then when capacity has reached a certain level start using them for other applications in a “second life”. Both for optimizing the performance of operations in 1st and 2nd life as well as for making fair commercial agreements when selling used batteries for 2nd life applications, we need to make prediction of remaining useful life (RUL) as well as SOH (State of Health). For this purpose battery models are needed. In the paper we show a methodology for building useful battery models built on own experiments as well as literature data. Single cells of NMC (Li-NiMnCo-batteries) as well as LFP (Li-ionphosphate batteries) have been cycled as well as cells in series. EIS, Electrochemical Impedance spectra as well as dQ/dV has been measured for each cycle. These data then have been used for development of SOH and RUL models using different regression methods. The models are described, discussed and results shown in the paper
Assessment of Data-Driven Techniques for Flow Rate Estimation in sub sea oil production
No full textAccurate measurement of flow rate of the multiphase flow of oil, gas and water from the oil wells, is an important part of the oil and gas industry. This enables the safe operation and proper optimization of the production. With the increasing availability of process data, machine learning algorithms are used to create models for various applications. The application of these algorithms for flow rate estimation provides a more accurate representation of the oil and gas production process. In this paper, two oil wells and ten machine learning algorithms are evaluated. Long short-term memory (LSTM) provides the best results with Mean absolute percentage error of 1.96% for Well 1 and 1.56% for Well 2. In addition, the effects of noise on the models are explored. Median filter with window size of three provides good noise reduction. The uncertainty of the predictions are quantified using 95% confidence intervals in XGBoost model
Equilibrium analysis for methanation focusing on CO2 derived substitute natural gas
Full text linkIn this study the methanation of synthesis gas (syngas) is investigated with a focus on achieving maximum methane and minimum CO by full methanation of CO2. For this study, we have considered a comprehensive thermodynamics analysis of CO2 hydrogenation. This will help us to understand the thermodynamic behaviour of the reactions involved in the methanation process. We have discussed the behavior of the species, CO2, H2, CH4, and H2O at the equilibrium with temperature, pressure, and fuel ratio variation in order to get the desired output. The preliminary study will focus on selecting the optimum conditions (temperature, pressure, and H2/CO2 ratio) for performing the experiments and for catalyst development
Modeling of a tire mounted energy harvester using an inertial and analytical tire deformation model
Full text linkIn this work, an analytical tire deformation model is created, which can be parameterized using simple measurements. The model consists of three equations which are solved to provide a shape function for the tire.This model can be used to provide excitation input for energy harvesters embedded inside the tire for example in FEM simulations. Additionally the model can be used in differential equation based simulations for quick parameterized simulations. With this model it is possible to study the effect of tyre inflation state to the energy harvesting performance of the system.Two different simulation cases are presented in this work. First is a vibration energy harvester simulation using the model with an inertial energy harvester. The second case illustrates an energy harvester using the deformation of the tire as the excitation for the energy harvester as opposed to inertial type harvester
Driving force model for a real-time control concept of a hybrid heavy duty vehicle
Full text linkThe electrification of heavy vehicles and work machinery is developing rapidly. The main motivators are green transition and requirements from the customers. In Finland, there are many hightech market-leading companies in this segment. Mass-produced equipment and machines are suitable for general applications and thus tailoring design for specific conditions and/or needs results in better productivity and efficiency. In heavy electric vehicle applications, the challenge is to make new products economically viable and configure them to meet customer needs. In these applications, the number of solutions is an order of magnitude higher than in traditional mechanical solutions. However, electronic solutions enable new features and energy efficiency improvements to have measurable benefits in the application. The research investigates the effects of electric axle solutions for hybrid heavy duty vehicles. Modelling and simulations consider both the effects of engine and usage of battery charge and surroundings of vehicle, for example road profile, traffic, outdoor temperature, and friction. A system level model of a vehicle has been utilized to simulate its longitudinal dynamics interacting with estimated surroundings followed by model-based control. The planned route can be made further favorable by utilizing real-time model predictive control (MPC) receiving online data from changing conditions. MPC gives new suggestions for optimal battery usage based on deviations from the best matching model from a database. Control strategy is important when considering economic benefits for a hybrid heavy duty vehicle with a high degree of freedom in system design
CARLA-based digital twin via ROS for hybrid mobile robot testing
Full text linkAutonomously driving vehicles and robots that drive in public environments need to be safe and reliable under all weather conditions, including arctic winter conditions. Digital twins provide an opportunity to test autonomous vehicles in a safer, faster, and less expensive environment than carrying out tests in real-life conditions. We developed the data connection via ROS (Robot Operating System) between a mobile robot and its digital twin. This allows for almost real-time exchange of commands, information, and sensor data between the twins.The digital twins of the robo t and the testing ground are constructed in a CARLA-based autonomous driving simulator, which simulates realistic arctic winter weather conditions.The digital twin design was informed by the intended future use cases: Testing, optimizing, controlling, and monitoring autonomous driving and snow cleaning functions first with the digital twin, then in hybrid approaches.In our test setup we tested the hybrid case, where both robot twins were moving in the simulation and the real-world test area at the same time. We verified our digital twin, assessed delays, and the applicability in the intended use cases. Our results show that the digital testing ground would profit from inbuilt reference points to examine the alignment with its real-world counterpart. The communication via ROS was occurring in almost real-time , therefore, the digital twin setup was found to be applicable in hybrid digital twin testing. In the future, we will introduce an autonomous car into this digital twin setup and equip the testing ground with a 5G network
Optimizing Annual-Coupled Industrial Energy Systems with Sequential Time Dependencies in a Two-Stage Algorithm
Full text linkThe use of mathematical methods in simulation and optimization models is widely spread to solve the current and future problems of an efficient and sustainable energy supply. Especially MILP is commonly used for industrial and municipal energy systems, where hourly resolved demand profiles are addressed in the time frame of one year in a quasi-stationary optimization. Certain technical or regulatory circumstances make necessitate considering all time steps in one coupled optimization problem. This results in a level of model complexity where today's solvers often struggle to find a solution within a reasonable timeframe. Application examples are annual maximum runtime restrictions or finding the optimum loading strategy of a seasonal storage. Regulatory examples in Germany include the full-load hour restricted CHP-surcharge, the high-efficiency-criterion or the maximum emission of a CO2-Budget which lead to an annual integral limitation. In this work, we present a two-stage approach with a simplified year-round-coupled first stage and a fully resolved second stage with a rolling horizon. To compress the input data in the simplified first stage while maintaining the order of the time sequence, we use different resolutions of downsampling and LP-relaxation. For the second stage, we derive corresponding additional boundary conditions and evaluate these in this study.Various use-cases involving both MILP and MIQCP models are evaluated using different compression parameters. The aim is to achieve high accuracy while saving computation time and furthermore enabling the solution of problems that would otherwise be computationally unsolvable without this method
Individual Puck Possessions Part II: Speed Bursts and Possession Times within Teams
Full text linkIn ice hockey, handling and keeping control of the puck (possession) are valued skills. In this paper we study several metrics of individual player puck possessions from 2023-24 regular season NHL games. These metrics include players’ speed while carrying the puck, and the distribution of puck possession times for players within their team (i.e., does a team have a few players who have a larger share of possession time or are times more equally distributed). Our goal in this paper is to examine and highlight different skills and roles related to puck possession and to design metrics that might be helpful in roster construction and/or creating line combinations