Informacja

Drogi użytkowniku, aplikacja do prawidłowego działania wymaga obsługi JavaScript. Proszę włącz obsługę JavaScript w Twojej przeglądarce.

English (EN)·Polski (PL)·Yкраїнський (UK)
Przejdź do strony domowej biblioteki Centralna Biblioteka Wojskowa Link otwiera się w nowym oknie Logo biblioteki Prolib Integro - strona głównaCentralna Biblioteka Wojskowa

Wyszukujesz frazę "hybrid modeling" wg kryterium: Wszystkie pola

  Lista filtrów
Wyrównaj
Wyświetlanie 1-15 z 23
Tytuł:
Hybrid modeling in CAD
Autorzy:
Wypysiński, R.
Powiązania:
https://bibliotekanauki.pl/articles/132136.pdf
Data publikacji:
2015
Wydawca:
Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:
hybrid modelling
CAD
solid-surface modeling
Opis:
Computer aided 3D modeling is rapidly growing field of techniques. Various modeling techniques are continuously developed and improved – but hybrid modeling as combination of the best features seems to be worthy of interest. This article describe main principle of full hybrid modeling with examples of practical applications.
Źródło:
Advanced Technologies in Mechanics; 2015, 2, no. 1 (2); 15-22
2392-0327
Pojawia się w:
Advanced Technologies in Mechanics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Hybrid Modeling Methods of Cranial Implants
Autorzy:
Wyleżoł, Marek
Powiązania:
https://bibliotekanauki.pl/articles/102702.pdf
Data publikacji:
2018
Wydawca:
Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:
cranial implant
voxel
haptic modeling
CATIA v5
ClayTools
implant czaszki
woksel
modelowanie haptyczne
Opis:
This article deals with a three hybrid modeling methods of virtual skull implants, developed by the author. 3D models of cranial implants are nowadays necessary for the creation of real implants using modern manufacturing technologies. These methods combine simultaneous usage of three modeling systems (which causes their hybridity): computer tomography system (as a reverse engineering system), surface modeling system and haptic modeling system, and their characteristic modeling methods and techniques. Whereby to commonly used three different modeling systems we have obtained a synergic effect of the implant shape model quality increasing. The result of using the developed hybrid methods are models of exemplary cranial implants. The common feature of these methods is that the target virtual model of the cranial implant is always well-suited the coastline of bone hole in the skull. The time of developed of the virtual model of any cranial implant using proposed methods is very shorter compared to use only one of the standard (not medically specialized) computer-aided systems. Similarly, the amount of modeling work is also much smaller than using only one standard 3D system. The article describes hybrid modeling methods developed by the author only.
Źródło:
Advances in Science and Technology. Research Journal; 2018, 12, 4; 35-47
2299-8624
Pojawia się w:
Advances in Science and Technology. Research Journal
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Research on speed control of high speed trains based on hybrid modeling
Autorzy:
Hou, Tao
Tang, Li.
Niu, Hong-xia
Zhao, Tingyang
Powiązania:
https://bibliotekanauki.pl/articles/27311802.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:
high-speed train
hybrid modeling
speed control
error compensation
pociąg ekspresowy
modelowanie hybrydowe
kontrola prędkości
kompensacja błędów
Opis:
With the continuous improvement of train speed, the automatic driving of trains instead of driver driving has become the development direction of rail transit in order to realize traffic automation. The application of single modeling methods for speed control in the automatic operation of high-speed trains lacks exploration of the combination of train operation data information and physical model, resulting in low system modeling accuracy, which impacts the effectiveness of speed control and the operation of high-speed trains. To further increase the dynamic modeling accuracy of high-speed train operation and the high-speed train's speed control effect, a high-speed train speed control method based on hybrid modeling of mechanism and data drive is put forward. Firstly, a model of the high-speed train's mechanism was created by analyzing the train's dynamics. Secondly, the improved kernel-principal component regression algorithm was used to create a data-driven model using the actual operation data of the CRH3 (China Railway High-speed 3) high-speed train from Huashan North Railway Station to Xi'an North Railway Station of "Zhengxi High-speed Railway," completing the mechanism model compensation and the error correction of the speed of the actual operation process of the high-speed train, and realizing the hybrid modeling of mechanism and data-driven. Finally, the prediction Fuzzy PID control algorithm was developed based on the natural line and train characteristics to complete the train speed control simulation under the hybrid model and the mechanism model, respectively. In addition, analysis and comparison analysis were conducted. The results indicate that, compared to the high-speed train speed control based on the mechanism model, the high-speed train speed control based on hybrid modeling is more accurate, with an average speed control error reduced by 69.42%. This can effectively reduce the speed control error, improve the speed control effect and operation efficiency, and demonstrate the efficacy of the hybrid modeling and algorithm. The research results can provide a new ideal of multi-model fusion modeling for the dynamic modeling of high-speed train operation, further improve control objectives such as safety, comfort, and efficiency of high-speed train operation, and provide a reference for automatic driving and intelligent driving of high-speed trains.
Źródło:
Archives of Transport; 2023, 66, 2; 77--82
0866-9546
2300-8830
Pojawia się w:
Archives of Transport
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Research on hybrid modeling and predictive energy management for power split hybrid electric vehicle
Autorzy:
Wang, Shaohua
Zhang, Sheng
Shi, Dehua
Sun, Xiaoqiang
Yang, Tao
Powiązania:
https://bibliotekanauki.pl/articles/2173576.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
power split HEV
energy management
mixed logical dynamical model
piecewise affine
model predictive control
podział mocy
zarządzanie energią
silnik hybrydowy
model dynamiczny
model mieszany
model logiczny
technologia fragmentarycznie pokrewna
kontrola predykcyjna modelu
Opis:
Due to the coexistence of continuity and discreteness, energy management of a multi-mode power split hybrid electric vehicle (HEV) can be considered a typical hybrid system. Therefore, the hybrid system theory is applied to investigate the optimum energy distribution strategy of a power split multi-mode HEV. In order to obtain a unified description of the continuous/discrete dynamics, including both the steady power distribution process and mode switching behaviors, mixed logical dynamical (MLD) modeling is adopted to build the control-oriented model. Moreover, linear piecewise affine (PWA) technology is applied to deal with nonlinear characteristics in MLD modeling. The MLD model is finally obtained through a high level modeling language, i.e. HYSDEL. Based on the MLD model, hybrid model predictive control (HMPC) strategy is proposed, where a mixed integer quadratic programming (MIQP) problem is constructed for optimum power distribution. Simulation studies under different driving cycles demonstrate that the proposed control strategy can have a superior control effect as compared with the rule-based control strategy.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 3; art. no. e137064
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Research on hybrid modeling and predictive energy management for power split hybrid electric vehicle
Autorzy:
Wang, Shaohua
Zhang, Sheng
Shi, Dehua
Sun, Xiaoqiang
Yang, Tao
Powiązania:
https://bibliotekanauki.pl/articles/2128153.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
power split HEV
energy management
mixed logical dynamical model
piecewise affine
model predictive control
podział mocy
zarządzanie energią
silnik hybrydowy
model dynamiczny
model mieszany
model logiczny
technologia fragmentarycznie pokrewna
kontrola predykcyjna modelu
Opis:
Due to the coexistence of continuity and discreteness, energy management of a multi-mode power split hybrid electric vehicle (HEV) can be considered a typical hybrid system. Therefore, the hybrid system theory is applied to investigate the optimum energy distribution strategy of a power split multi-mode HEV. In order to obtain a unified description of the continuous/discrete dynamics, including both the steady power distribution process and mode switching behaviors, mixed logical dynamical (MLD) modeling is adopted to build the control-oriented model. Moreover, linear piecewise affine (PWA) technology is applied to deal with nonlinear characteristics in MLD modeling. The MLD model is finally obtained through a high level modeling language, i.e. HYSDEL. Based on the MLD model, hybrid model predictive control (HMPC) strategy is proposed, where a mixed integer quadratic programming (MIQP) problem is constructed for optimum power distribution. Simulation studies under different driving cycles demonstrate that the proposed control strategy can have a superior control effect as compared with the rule-based control strategy.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 3; e137064, 1--15
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
E-REV’s hybrid vehicle range modeling
Autorzy:
Polak, F.
Powiązania:
https://bibliotekanauki.pl/articles/245454.pdf
Data publikacji:
2018
Wydawca:
Instytut Techniczny Wojsk Lotniczych
Tematy:
battery
simulation model
electric vehicle
E-REV
Opis:
Article presents the influence of battery capacity and electric generator power on a series hybrid vehicle range. Vehicles equipped with increased battery capacity and small power generator are special type of series hybrid vehicles called Extended Range Electric Vehicles – E-REV. The increasing number of hybrid and electric vehicles increases the demand for durable and efficient sources of energy storage for vehicles. The hybrid vehicle's battery driven range is increased as battery power density is increased and its cost is decreased. This is due to the battery cell cost decreasing and improvement of cell chemistry. That cause higher and higher distance driven on electric mode in hybrid vehicles. First series hybrid vehicle engine power was equal to engine powered the vehicle’s wheels. Nowadays, series hybrid vehicles are more electric vehicles with small power generator (piston or turbine engine. In such a constructions, battery is used as an energy buffer and combustion engine is used more as emergency power supply. To minimize this phenomenon, manufacturers use counteracting solutions that include mounting additional cells in the battery that are switched on when the battery controller identifies a particular battery cell’s failure or high degradation. This is due to the deep and shallow discharges of the battery, the numbers of charging and discharging cycles, and the age and technology of battery packs. AMESim software was used for the simulation of the E-REV hybrid vehicle range. The research was based on modelling the range of the vehicle with different battery capacity works with power generator of different power. By modelling different capacity of battery and power of small generator, it is possible to determine the vehicle range.
Źródło:
Journal of KONES; 2018, 25, 2; 281-286
1231-4005
2354-0133
Pojawia się w:
Journal of KONES
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Hybrid system for modeling and optimization of production chain in metal forming
Autorzy:
Rauch, L.
Madej, L.
Pietrzyk, M.
Powiązania:
https://bibliotekanauki.pl/articles/1429405.pdf
Data publikacji:
2008
Wydawca:
Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:
optimization
modelling
production chain
metal forming
Opis:
The paper presents design and implementation of the hybrid system, which is the part of investigation focused on application of multiscale modeling in simulation of real industrial processes. The hybrid system is dedicated to support production processes based on metal forming, by using artificial intelligence and optimization algorithms. The proposed system is based on the multilayer architecture and consists of several functional components responsible for management of production process, modeling and simulations and, finally, optimization. The latter module aims at searching for optimial parameters of selected production processes, which form production chain, i.e. rod rolling and cold forging. Optimization is performed using results obtained from multiscale modeling calculations. Then, the optimized approach is passed directly to the configuration and control centre of the real industrial process as a feedback to obtain better quality of products employing lower costs of manufacturing. Moreover, the hybrid system is designed to exchange information with other external systems implemented inside an enterprise e.g. ERP and its modules. The internal structure of presented system is described in the paper, as well as measurable advantages of hybrid system application to real environment.
Źródło:
Journal of Machine Engineering; 2008, 8, 2; 14-22
1895-7595
2391-8071
Pojawia się w:
Journal of Machine Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Hybrid CNN-Ligru acoustic modeling using sincnet raw waveform for hindi ASR
Autorzy:
Kumar, Ankit
Aggarwal, Rajesh Kumar
Powiązania:
https://bibliotekanauki.pl/articles/1839250.pdf
Data publikacji:
2020
Wydawca:
Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:
automatic speech recognition
CNN
CNN-LiGRU
DNN
Opis:
Deep neural networks (DNN) currently play a most vital role in automatic speech recognition (ASR). The convolution neural network (CNN) and recurrent neural network (RNN) are advanced versions of DNN. They are right to deal with the spatial and temporal properties of a speech signal, and both properties have a higher impact on accuracy. With its raw speech signal, CNN shows its superiority over precomputed acoustic features. Recently, a novel first convolution layer named SincNet was proposed to increase interpretability and system performance. In this work, we propose to combine SincNet-CNN with a light-gated recurrent unit (LiGRU) to help reduce the computational load and increase interpretability with a high accuracy. Different configurations of the hybrid model are extensively examined to achieve this goal. All of the experiments were conducted using the Kaldi and Pytorch-Kaldi toolkit with the Hindi speech dataset. The proposed model reports an 8.0% word error rate (WER).
Źródło:
Computer Science; 2020, 21 (4); 397-417
1508-2806
2300-7036
Pojawia się w:
Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Application of hybrid CFD/CAA technique for modeling pressure fluctuations in transonic flows
Autorzy:
Dykas, S.
Wróblewski, W.
Rulik, S.
Powiązania:
https://bibliotekanauki.pl/articles/1955297.pdf
Data publikacji:
2013
Wydawca:
Politechnika Gdańska
Tematy:
transonic flow
aeroacoustic noise
hybrid technique
Opis:
Solving AeroAcoustics (CAA) problems by means of the Direct Numerical Simulation (DNS) or even the Large Eddy Simulation (LES) for a large computational domain is very time consuming and cannot be applied widely for engineering purposes. In this paper in-house CFD and CAA codes are presented. The in-house CFD code is based on the LES approach whereas the CAA code is an acoustic postprocessor solving non-linearized Euler equations for fluctuating (acoustic) variables. These codes are used to solve the pressure waves generated aerodynamically by a flow over a rectangular cavity and by the vortex street behind a turbine blade. The obtained results are discussed with respect to the application of the presented numerical techniques to pressure waves modeling in steam turbine stages.
Źródło:
TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk; 2013, 17, 3-4; 145--154
1428-6394
Pojawia się w:
TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Hybrid texture and gradient modeling for dynamic background subtraction identification systemin tobacco plant using 5G data service
Autorzy:
Gowda Thirthe, M.T.
Chandrika, J.
Powiązania:
https://bibliotekanauki.pl/articles/38699145.pdf
Data publikacji:
2023
Wydawca:
Instytut Podstawowych Problemów Techniki PAN
Tematy:
background subtraction
local binary pattern
tobacco plant
texture
Gaussian mixture model
illumination change
plant disease identification system
usuwanie tła
lokalny wzorzec binarny
tytoń
tekstura
model mieszaniny Gaussa
zmiana oświetlenia
system identyfikacji chorób roślin
Opis:
Background: Detecting the plants as objects of interest in any vision-based input sequence is highly complex due to nonlinear background objects such as rocks, shadows,etc. Therefore, it is a difficult task and an emerging one with the development of precision agriculture systems. The nonlinear variations of pixel intensity with illuminationand other causes such as blurs and poor video quality also make the object detection taskchallenging. To detect the object of interest, background subtraction (BS) is widely usedin many plant disease identification systems, and its detection rate largely depends on thenumber of features used to suppress and isolate the foreground region and its sensitivitytoward image nonlinearity. Methodology: A hybrid invariant texture and color gradient-based approach is proposed to model the background for dynamic BS, and its performance is validated byvarious real-time video captures covering different kinds of complex backgrounds and various illumination changes. Based on the experimental results, a simple multimodal featureattribute, which includes several invariant texture measures and color attributes, yieldsfinite precision accuracy compared with other state-of-art detection methods. Experimental evaluation of two datasets shows that the new model achieves superior performanceover existing results in spectral-domain disease identification model. 5G assistance: After successful identification of tobacco plant and its analysis, the finalresults are stored in a cloud-assisted server as a database that allows all kinds of 5G servicessuch as IoT and edge computing terminals for data access with valid authentication fordetailed analysis and references.
Źródło:
Computer Assisted Methods in Engineering and Science; 2023, 30, 1; 41-54
2299-3649
Pojawia się w:
Computer Assisted Methods in Engineering and Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A hybrid deep learning framework for modeling the short term global horizontal irradiance prediction of a solar power plant in India
Hybrydowa struktura głębokiego uczenia do modelowania krótkoterminowych prognoz globalnego natężenia napromienienia poziomego elektrowni słonecznej w Indiach
Autorzy:
Rajaprasad, S. V. S.
Mukkamala, Rambabu
Powiązania:
https://bibliotekanauki.pl/articles/27312530.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Instytut Gospodarki Surowcami Mineralnymi i Energią PAN
Tematy:
global horizontal irradiance
energy
deep neural networks
hybrid model
globalne natężenie napromienienia poziomego
energia
głębokie sieci neuronowe
model hybrydowy
Opis:
The rapid development of grid integration of solar energy in developing countries like India has created vital concerns such as fluctuations and interruptions affecting grid operations. Improving the consistency and accuracy of solar energy forecasts can increase the reliability of the power grid. Although solar energy is available in abundance around the world, it is viewed as an unpredictable source due to uncertain fluctuations in climate conditions. Global horizontal irradiance (GHI) prediction is critical to efficiently manage and forecast the power output of solar power plants. However, developing an accurate GHI forecasting model is challenging due to the variability of weather conditions over time. This research aims to develop and compare univariate LSTM models capable of predicting GHI in a solar power plant in India over the short term. The present study introduces a deep neural network-based (DNN) hybrid model with a combination of convolutional neural network bi-directional long short-term memory (CNN BiLSTM) to predict the one minute interval GHI of a solar power plant located in the southern region of India. The model’s effectiveness was tested using data for the month of January 2023. In addition, the results of the hybrid model were compared to the long short-term memory (LSTM) and BiLSTM deep-learning (DL) models. It has been observed that the proposed hybrid model framework is more accurate compared to the LSTM and BiLSTM architectures. Finally, a GHI prediction tool was developed to understand the trend of the results.
Szybki rozwój integracji energii słonecznej z siecią elektroenergetyczną w krajach rozwijających się, takich jak Indie, wywołał istotne obawy, m.in. związane z wahaniami i przerwami wpływającymi na działanie sieci. Poprawa spójności i dokładności prognoz dotyczących energii słonecznej może zwiększyć niezawodność sieci energetycznej. Chociaż energia słoneczna jest dostępna w dużych ilościach na całym świecie, jest ona postrzegana jako nieprzewidywalne źródło ze względu na niepewne wahania warunków klimatycznych. Prognozowanie globalnego natężenia napromienienia horyzontalnego (GHI) ma kluczowe znaczenie dla efektywnego zarządzania i prognozowania mocy elektrowni słonecznych. Jednak opracowanie dokładnego modelu prognozowania GHI jest trudne ze względu na zmienność warunków pogodowych w czasie. Badania te mają na celu opracowanie i porównanie modeli LSTM zdolnych do przewidywania GHI w elektrowni słonecznej w Indiach w krótkim czasie. W niniejszym badaniu wprowadzono hybrydowy model oparty na głębokiej sieci neuronowej (DNN) z kombinacją dwukierunkowej konwolucyjnej sieci neuronowej z długą pamięcią krótkotrwałą (CNN BiLSTM) w celu przewidywania jednominutowych interwałów GHI elektrowni słonecznej zlokalizowanej w południowym regionie Indii. Skuteczność modelu została przetestowana przy użyciu danych za styczeń 2023 roku. Ponadto wyniki modelu hybrydowego porównano z modelami uczenia głębokiego (DL) z długą pamięcią krótkotrwałą (LSTM) i BiLSTM. Zaobserwowano, że proponowany model hybrydowy jest dokładniejszy w porównaniu do architektur LSTM i BiLSTM. Ostatecznie opracowano narzędzie do przewidywania GHI, aby zrozumieć trend wyników.
Źródło:
Polityka Energetyczna; 2023, 26, 3; 101--116
1429-6675
Pojawia się w:
Polityka Energetyczna
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Modeling and selection of the work of a powertrain hybrid wheeled vehicle
Autorzy:
Banaś, W.
Kost, G.
Nierychlok, A.
Powiązania:
https://bibliotekanauki.pl/articles/99683.pdf
Data publikacji:
2011
Wydawca:
Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:
hybrid vehicle
concept of control
stabilization process
Opis:
The paper presents the main issues of control the combustion engine by stabilizing power. Algorithms work, certain flue units for which the work of the internal combustion engine is most effective. A method of modeling the flow of energy between an engine and an electric generator as a function of engine speed and load of the specific fuel consumption - the greatest efficiency. Presented a stabilization system diagram under the internal combustion engine and generator for hybrid vehicle. Described to adopted algorithm the stabilization of power for the engine and generator exhaust in the rotational speed to stabilize at a point and stability in the area.
Źródło:
Journal of Machine Engineering; 2011, 11, No. 1-2; 162-170
1895-7595
2391-8071
Pojawia się w:
Journal of Machine Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Some aspects of application of artificial neural network for numerical modeling in civil engineering
Autorzy:
Lefik, M.
Powiązania:
https://bibliotekanauki.pl/articles/202028.pdf
Data publikacji:
2013
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
hybrid code FEM-ANN
inverse solution with ANN
Opis:
In order to obtain reliable results of computations in civil engineering, the numerical procedures that are used at the stage of design should be calibrated by comparison of the theoretical results with an observed behavior of previously modeled and then executed structures. The hybrid Finite Element code with an Artificial Neural Network inserted as a representation of a constitutive law, offers a possibility to adjust not only parameters of the constitutive relationships but also its qualitative form. Because of this, the representation of constitutive law by the ANN is presented in this paper. The constitutive data should be calibrated to fit well the observable values, measured in experiments. If the constitutive law is expressed by ANN, the inverse problem can be reduce to a training of the ANN inserted into the Finite Element code. An example of a solution of the inverse problem in calibration of constitutive law is presented. An identification of parameters of flow of pollutant in soils is described as another example of application of ANN in engineering.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2013, 61, 1; 39-50
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Energy management system of the hybrid ultracapacitor-battery electric drive vehicles
Autorzy:
Pielecha, Ireneusz
Powiązania:
https://bibliotekanauki.pl/articles/1832900.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
electric vehicle
battery
ultracapacitor
energy flow modeling
pojazd elektryczny
bateria
ultrakondensator
Opis:
The search for new, alternative propulsion and energy sources in transport is one of the economic and technological priorities of the current decade. The modern development of hybrid drives and electric means of transport makes it possible to at least partially diversify conventional drive systems. The study discusses the use of a battery and ultracapacitor in electric vehicles. Simulation analyzes of energy flow were performed using the solutions of electric drive systems and various energy storage control algorithms. The research was carried out in relation to the use of braking energy, its con-version into electricity and its storage in a battery or ultracapacitor. The operating conditions of the battery and the ultra-capacitor were assessed in terms of specific energy consumption while driving. The article proposed the use of a drive system connected in series, the last link of which was an ultracapacitor. Such a solution significantly reduced the use of the battery as well as its regular charging-discharging. At the same time, it required the use of a high-capacity ultracapacitor, which contributed to increasing its charging time. The analyzes were carried out using standardized research tests as well as tests in real traffic conditions. The research was carried out with the use of the AVL Cruise software for the analysis of energy flow in vehicles; a middle class passenger vehicle was selected for the tests, equipped with an electrochemical battery and – in the next stage of the research – an ultracapacitor. Three research models were used: I) typical electric drive system; II) a system with the use of ultracapacitors ran by a simple control algorithm; III) a system with the use of ultracapacitors with an advanced control algorithm (the algorithm took into account the change of driving conditions to the ultracapacitor charging conditions). The advantages of using ultracapacitors in the electric drive of a vehicle were demonstrated, especially for results obtained in real traffic conditions. Analyzing the simulation tests results allowed to determine the most advantageous options of utilizing these systems, in particular in the aspect of increased possibilities of algorithms controlling the flow of electricity in the drive system.
Źródło:
Archives of Transport; 2021, 58, 2; 47-62
0866-9546
2300-8830
Pojawia się w:
Archives of Transport
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Modeling and simulation of stand-alone hybrid power system with fuzzy MPPT for remote load application
Autorzy:
Bogaraj, T.
Kanakaraj, J.
Chelladurai, J.
Powiązania:
https://bibliotekanauki.pl/articles/140494.pdf
Data publikacji:
2015
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
Solar PV system
Wind energy conversion system
Hybrid power system
DC-DC converters
fuzzy logic based MPPT
Three phase PWM inverter
Opis:
Many parts of remote locations in the world are not electrified even in this Advanced Technology Era. To provide electricity in such remote places renewable hybrid energy systems are very much suitable. In this paper PV/Wind/Battery Hybrid Power System (HPS) is considered to provide an economical and sustainable power to a remote load. HPS can supply the maximum power to the load at a particular operating point which is generally called as Maximum Power Point (MPP). Fuzzy Logic based MPPT (FLMPPT) control method has been implemented for both Solar and Wind Power Systems. FLMPPT control technique is implemented to generate the optimal reference voltage for the first stage of DC-DC Boost converter in both the PV and Wind energy system. The HPS is tested with variable solar irradiation, temperature, and wind speed. The FLMPPT method is compared with P&O MPPT method. The proposed method provides a good maximum power operation of the hybrid system at all operating conditions. In order to combine both sources, the DC bus voltage is made constant by employing PI Controllers for the second stage of DC-DC Buck-Boost converter in both Solar and Wind Power Systems. Battery Bank is used to store excess power from Renewable Energy Sources (RES) and to provide continuous power to load when the RES power is less than load power. A SPWM inverter is designed to convert DC power into AC to supply three phase load. An LC filter is also used at the output of inverter to get sinusoidal current from the PWM inverter. The entire system was modeled and simulated in Matlab/Simulink Environment. The results presented show the validation of the HPS design.
Źródło:
Archives of Electrical Engineering; 2015, 64, 3; 487-504
1427-4221
2300-2506
Pojawia się w:
Archives of Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Wyświetlanie 1-15 z 23

Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies