1. Towards digital twinning of electrical motors – simulation modelsGoran Kurtović, Luka Živković, Tin Benšić, Željko Hederić, Marinko Stojkov, 2025, original scientific article Abstract: This paper presents a methodological framework for building a digital shadow of an induction motor based on standardised tests and a two‑axis (dq) simulation model. The tests were carried out according to IEEE Std 112 and IEC 60034‑2‑1. The parameters of the equivalent circuit were identified and entered into the model. Validation was performed by comparing the torque–speed and current–speed curves at 180 V and 220 V, while the nominal behaviour at 400 V was estimated using the model and voltage scaling. The model was then calibrated to reduce the discrepancy between the simulation and measurements, and the error was quantified using the root‑mean‑square error (RMSE) and mean absolute percentage error (MAPE). An automated load‑simulation setup that reproduces the torque test is also presented, enabling rapid evaluation of parameter influence. The results show a very good match in the current channel, with larger deviations in the prediction of characteristic torque points, indicating the limitations of linearised parameters and motivating nonlinear model extensions. The approach enables summarised reliable estimates at nominal voltage when direct measurements are not feasible.
Keywords: induction motor, digital shadow, standardised tests, dq model, torque test, automated load simulation, model calibration
Published in DKUM: 01.10.2025; Views: 0; Downloads: 2
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2. Incorporating enriched empirical models into optimization algorithm to enhance biogas productionTina Kegl, Andreja Goršek, Darja Pečar, 2025, original scientific article Abstract: This paper introduces a novel approach to optimization of the anaerobic co-digestion (AcoD) process by developing enriched versions of first-order kinetic, modified Gompertz, and single-stage combined kinetic models. The key innovation of these enriched models lies in the introduction of new kinetic parameters that depend on both temperature and substrate composition, resulting in a set of new model parameters. These parameters are calibrated simultaneously across various process conditions, unlike existing models where kinetic constants are calibrated for only one operating regime. The enriched models are successfully calibrated and validated with experimental data from a batch AcoD of chicken manure with sawdust and fungal-pretreated Miscanthus; the relative index of agreement is higher than 0.99 for the produced biogas under all considered process conditions. By using the calibrated models to optimize the substrate composition and the AcoD process temperature profile, the results indicate that biogas production can increase by up to 50 %. Moreover, the proposed optimization allows for a favorable cost-benefit ratio; the estimated net energy gain can increase by up to 40 %. The proposed enriched models enable accurate prediction of biogas production at various process conditions and optimization of the AcoD process, representing a significant advancement over existing empirical models.
Keywords: biogas production, Pleurothus ostreatus, kinetic model parameters calibration, process optimization, gradient-based optimization, energy trade-offs
Published in DKUM: 29.05.2025; Views: 0; Downloads: 3
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3. Evaluation of measurement uncertainty contributions in ring gauge calibrationBojan Ačko, Jasna Tompa, Rok Klobučar, 2024, original scientific article Abstract: Measurements are of paramount importance in industry and other areas of importance to society. They are used to determine the characteristics of processes and products, to control and regulate processes, to decide on the acceptable quality of products, etc. To ensure the quality of measurements, we have to calibrate measuring devices regularly. In our laboratory – the holder of the national length standard, we mainly calibrate high-precision standards from accredited laboratories. As the demands on the accuracy of measurements are constantly increasing, we are also forced to continuously improve the accuracy of our calibration procedures. This article presents the development of methods for calibrating the diameter of ring gauges, which represent an important standard for calibrating measuring instruments for measuring internal dimensions. The main objective of this development is to reduce the measurement uncertainty based on a scientific investigation of all influencing parameters. The presented study focuses in particular on the control and reduction of the influence of geometric anomalies of the calibrated rings on the measurement uncertainty during calibration.
Keywords: measurement traceability, calibration, measurement uncertainty, error simulation
Published in DKUM: 11.03.2025; Views: 0; Downloads: 7
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4. Mathematical model-based optimization of trace metal dosage in anaerobic batch bioreactorsTina Kegl, Balasubramanian Paramasivan, Bikash Chandra Maharaj, 2025, original scientific article Abstract: Anaerobic digestion (AD) is a promising and yet a complex waste-to-energy technology. To optimize such a process, precise modeling is essential. Developing complex, mechanistically inspired AD models can result in an overwhelming number of parameters that require calibration. This study presents a novel approach that considers the role of trace metals (Ca, K, Mg, Na, Co, Cr, Cu, Fe, Ni, Pb, and Zn) in the modeling, numerical simulation, and optimization of the AD process in a batch bioreactor. In this context, BioModel is enhanced by incorporating the influence of metal activities on chemical, biochemical, and physicochemical processes. Trace metal-related parameters are also included in the calibration of all model parameters. The model’s reliability is rigorously validated by comparing simulation results with experimental data. The study reveals that perturbations of 5% in model parameter values significantly increase the discrepancy between simulated and experimental results up to threefold. Additionally, the study highlights how precise optimization of metal additives can enhance both the quantity and quality of biogas production. The optimal concentrations of trace metals increased biogas and CH4 production by 5.4% and 13.5%, respectively, while H2, H2S, and NH3 decreased by 28.2%, 43.6%, and 42.5%, respectively.
Keywords: anaerobic digestion, batch bioreactor, methane production, model parameters calibration, active set optimization method, perturbation of model parameter, gradient based optimization, trace metals
Published in DKUM: 30.01.2025; Views: 0; Downloads: 4
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6. Modeling and multi-objective optimization of forward osmosis processTina Kegl, Jasmina Korenak, Hermina Bukšek, Irena Petrinić, 2024, original scientific article Abstract: In order to ensure efficient wastewater treatment and seawater desalination, adequate modeling and optimization of the forward osmosis (FO) process has the potential to be very helpful. This paper deals with the FO model parameters calibration and FO process optimization by a gradient-based optimization method. For this purpose, an upgraded FO model, which involves temperature- and agent-dependent parameters, was developed. The FO model calibration was done using NaCl as agents in draw solution, while MgCl2 was used for model validation. The agreements between simulated and measured FO performance were satisfactory; relative index of agreement are higher than 0.99. By using the proposed FO model, the optimization of FO process conditions was performed with various definitions of the objective and constraint functions. In case of maximizing the water flux, minimizing reverse solute flux, and fulfilling the required constraints, the ratio of water flux and reverse solute flux increased up to 40 % for NaCl and up to 20 % for MgCl2; meanwhile the effective osmotic pressure difference was improved 2-times for NaCl and up to 3.8-times for MgCl2. The optimization process proved to be stable and efficient and can easily be adapted or upgraded for more complex dynamic FO modeling.
Keywords: forward osmosis, modeling, model and process parameters, calibration procedure, gadient-based optimization
Published in DKUM: 23.08.2024; Views: 67; Downloads: 36
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7. Calibration of the microsimulation traffic model using different neural network applicationsIrena Ištoka Otković, Tomaž Tollazzi, Matjaž Šraml, Damir Varevac, 2023, original scientific article Keywords: urban traffic, microsimulation, calibration, neural networks, rundabouts, validation
Published in DKUM: 15.04.2024; Views: 239; Downloads: 16
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8. Sensitivity Analysis of Hybrid Powertrain Pre-calibration Algorithms : magistrsko deloSimon Šegula, 2023, master's thesis Abstract: Currently, meeting the new fuel consumption and emissions standards is the biggest challenge in the automotive industry. One of the solutions is hybridization of the vehicle’s powertrain. This brings with it larger complexity of the vehicle control unit and its pre-calibration. This thesis explores gear shift map and load point shift map, which are two pre-calibration maps included in the vehicle control unit. More specifically it delves in to how the pre-calibration maps are created and how changing their parameters impacts the fuel consumption of the vehicle. Algorithms and optimization simulations were created and performed using AVL’s tool called the Powertrain system optimizer (PSO) which was created within the MATLAB software.
Keywords: Hybrid electric vehicle, Hybrid powertrain, Gear shift map, Load point shift map, Pre-calibration.
Published in DKUM: 23.11.2023; Views: 393; Downloads: 0 |
9. Development of a methodology to calibrate a pedestrian microsimulation model : doctoral dissertationChiara Gruden, 2022, doctoral dissertation Abstract: Walking, as a mode of transport, is becoming widespread, in a world, where urban conglomerates are broadening and becoming denser. Modern lifestyle trends on a side, and eco-friendly policies on the other, push people into walking habits, increasing the need for a suitable, attractive, accessible, connected and safe walking infrastructure. To reach such a result, it is necessary to understand, what are the needs of the users of this infrastructure, taking into consideration the behavioral specificities and the safety needs of pedestrians. In this process pedestrian microsimulation models, surrogate safety techniques, and technologies able to measure specific traits of pedestrian dynamics play a central role. The firsts allow to reproduce repeatedly in a virtual environment a specific infrastructure and to study the response of pedestrians. Nevertheless, to be accurate and efficient, they need to go through long and tedious calibration and validation processes, that are often seen as an important limitation by technicians. Surrogate safety techniques are methods, that are based on the concept, that it is possible to predict the safety level of a location, using near accidents. The main advantage of such techniques is that they are proactive. Till this moment, these techniques have been mainly applied to on-field measurements and are primarily centered on motorized road users. Less interest has been shown for vulnerable road users, especially for pedestrians, who have been less extensively studied. Finally, an element that could highly affect pedestrian safety is their reaction time. Nevertheless, its measurement has long been a big issue. Eye-tracking technology could be one of the solutions, allowing to analyze the directions and objects fixated by pedestrians. These listed issues are also the topics that are addressed by this research work. Focusing on the study of the action of pedestrians while crossing the road on an unsignalized crosswalk set on a roundabout entry leg, the dissertation thesis aims at studying the crossing time, reaction time and surrogate safety aspects typical of pedestrians at the recalled location. The main purpose of the research work is to develop a methodology to calibrate pedestrian Social Force Model at a selected location, using a specifically formulated neural network as a tool to fine-tune model's behavioral parameters. Eight parameters have been chosen to be fine-tuned, five of those are related to pedestrian behavior and three of them are related to car-following behavior. After the selection of input parameters, a feedforward network has been formulated. Its application in the framework of the whole calibration process has brought to considerably positive results, finding a combination of input parameters that improved the performance of the microsimulation model of 37 % in comparison to the default one. The outputs of the calibrated model have been used to calculate three measures of surrogate safety, and also in this case results demonstrated an improvement in the calculation of surrogate safety measures when using the calibrated outcomes in comparison to their calculation on the “default” model outputs. Finally, reaction time measurement and prediction have been addressed by the thesis, in order to be able to describe pedestrian crossing action in its completeness. Quantitative eye-tracking outputs have been the starting point for the calculation of pedestrian reaction time at different locations, and they allowed to create a database of behavioral, geometric, regulatory and flow characteristics, which was the foundation for the formulation of a new prediction model for pedestrian reaction time. The prediction model, which consists of a cascade-correlation neural network, gave a good response to the learning and generalization steps, turning a 74 % correlation between the measured reaction time values and the predicted ones, and being able to follow the variability of these values.
Keywords: pedestrian, microsimulation model, calibration, neural network, surrogate safety indicators, reaction time.
Published in DKUM: 03.10.2022; Views: 873; Downloads: 118
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10. Simulation of automotive air-conditioning system in 1D simulation software : diplomsko deloMarko Copot, 2019, undergraduate thesis Abstract: The development of state-of-the-art vehicles requires advanced simulations tools in heating, ventilation and air-conditioning (HVAC). The focus of this thesis is the construction of an automotive HVAC model, its calibration and the simulation of the behaviour of the HVAC model in various ambient conditions. The theoretical background of refrigeration system as part of the HVAC system is presented. The model is constructed with following components: compressor, condenser, throttling device, evaporator and battery chiller, which is a heat exchanger between coolant and refrigerant. The description and role of each component in the HVAC model is presented. All heat exchangers are calibrated, which is done with multiple simulations that have defined input data. The results are compared to experimental data. With addition of vehicle cabin with air recirculation, HVAC control logic is implemented. The behaviour of the system is simulated in defined environmental conditions. The results of the simulations are presented in graphs and tables.
Keywords: 1D simulations, air-conditioning, HVAC, calibration, thermodynamics, cooling
Published in DKUM: 23.09.2019; Views: 1453; Downloads: 120
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