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001-es BibID:	BIBFORM081235
035-os BibID:	(WoS)000498391700069 (Scopus)85074976334
Első szerző:	Afghan, Syeda Adila (mérnök)
Cím:	Modelling and Analysis of Energy Harvesting in Internet of Things (IoT) : Characterization of a Thermal Energy Harvesting Circuit for IoT based Applications with LTC3108 / Syeda Adila Afghan, Géza Husi
Dátum:	2019
ISSN:	1996-1073
Megjegyzések:	This paper presents a simulation-based study for characterizing and analyzing the performance of a commercially available thermoelectric cooler (TEC) as a generator for harvesting heat energy along with a commercial-off-the-shelf (COTS) power management integrated circuit (PMIC); LTC3108. In this model, the transformation of heat was considered in terms of an electrical circuit simulation perspective, where temperature experienced by TEC on both cold and hot sides was incorporated with voltage supply as Vth and Vtc in the circuit. When it comes to modeling a system in a simulation program with an integrated circuit emphasis (SPICE) like environment, the selection of thermoelectric generator (TEG) and extraction methods are not straightforward as well as the lack of information from manufacturer's datasheets can limit the grip over the analysis parameters of the module. Therefore, it is mandatory to create a prototype before implementing it over a physical system for energy harvesting circuit (EHC) optimization. The major goal was to establish the basis for devising the thermal energy scavenging based Internet of Things (IoT) system with two configurations of voltage settings for the same TEG model. This study measured the data in terms of current, voltage, series of resistive loads and various temperature gradients for generating the required power. These generated power levels from EHC prototype were able to sustain the available IoT component's power requirement, hence it could be considered for the implementation of IoT based applications.
Tárgyszavak:	Műszaki tudományok Informatikai tudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk
Megjelenés:	Energies. - 12 : 20 (2019), p. 1-13. -
További szerzők:	Husi Géza (1962-) (gépészmérnök, mechatronikai mérnök, számítógépes tervezőmérnök)
Internet cím:	DOI Intézményi repozitóriumban (DEA) tárolt változat
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001-es BibID:	BIBFORM124258
035-os BibID:	(Scopus)85205072958 (WoS)001324053400001
Első szerző:	Babangida, Aminu (Informatics)(mérnök)
Cím:	Dynamic Modeling and Control Strategy Optimization of a Volkswagen Crafter Hybrid Electrified Powertrain / Aminu Babangida, Péter Tamás Szemes
Dátum:	2024
ISSN:	1996-1073
Megjegyzések:	This article studies the transformation and assembly process of the Volkswagen (VW) Crafter from conventional to hybrid vehicle of the department of vehicles engineering, University of Debrecen, and uses a computer-aided simulation (CAS) to design the vehicle based on the real measurement data (hardware-in-the-loop, HIL method) obtained from an online CAN bus data measurement platform using MATLAB/Simulink/Simscape and LabVIEW software. The conventional vehicle powered by a 6-speed manual transmission and a 4-stroke, 2.0 Turbocharged Direct Injection Common Rail (TDI CR) Diesel engine and the transformed hybrid electrified powertrain are designed to compare performance. A novel methodology is introduced using Netcan plus 110 devices for the CAN bus analysis of the vehicle`s hybrid version. The acquired raw CAN data is analyzed using LabVIEW and decoded with the help of the database (DBC) file into physical values. A classical proportional integral derivative (PID) controller is utilized in the hybrid powertrain system to manage the vehicle consumption and CO2 emissions. However, the intricate nonlinearities and other external environments could make its performance unsatisfactory. This study develops the energy management strategies (EMSs) on the basis of enhanced proportional integral derivative-based genetic algorithm (GA-PID), and compares with proportional integral-based particle swarm optimization (PSO-PI) and fractional order proportional integral derivative (FOPID) controllers, regulating the vehicle speed, allocating optimal torque and speed to the motor and engine and reducing the fuel and energy consumption and the CO2 emissions. The integral time absolute error (ITAE) is proposed as a fitness function for the optimization. The GA-PID demonstrates superior performance, achieving energy efficiency of 90%, extending the battery pack range from 128.75 km to 185.3281 km and reducing the emissions to 74.79 gCO2/km. It outperforms the PSO-PI and FOPID strategies by consuming less battery and motor energy and achieving higher system efficiency
Tárgyszavak:	Műszaki tudományok Informatikai tudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk DBC file diesel engine electrified powertrain HIL LabVIEW
Megjelenés:	Energies. - 17 : 18 (2024), p. 1-38. -
További szerzők:	Szemes Péter Tamás (1976-) (gépészmérnök, villamosmérnök)
Pályázati támogatás:	TKP2020-NKA-04 Egyéb K143595 OTKA
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
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001-es BibID:	BIBFORM118893
035-os BibID:	(Scopus)85187411022 (WoS)001182753600001
Első szerző:	Neamah, Husam A. (mérnök)
Cím:	Development of a Volkswagen Jetta MK5 Hybrid Vehicle for Optimized System Efficiency Based on a Genetic Algorithm / Husam A. Neamah, Mohammed Dulaimi, Alaa Silavinia, Aminu Babangida, Péter Tamás Szemes
Dátum:	2024
ISSN:	1996-1073
Megjegyzések:	Hybrid electric vehicles (HEVs) have emerged as a trendy technology for reducing overdependence on fossil fuels and a global concern of gas emissions across transportation networks. This research aims to design the hybridized drivetrain of a Volkswagen (VW) Jetta MK5 vehicle on the basis of its mathematical background description and a computer-aided simulation (MATLAB/Simulink/Simscape, MATLAB R2023b). The conventional car operates through a five-speed manual gearbox, and a 2.0 TDI internal combustion engine (ICE) is first assessed. A comparative study evaluates the optimal fuel economy between the conventional and the hybrid versions based on a proportional-integral-derivative (PID) controller, whose optimal set-point is predicted and computed by a genetic algorithm (GA). For realistic hybridization, this research integrated a Parker electric motor and the diesel engine of a VW Crafter hybrid vehicle from the faculty of engineering to reduce fuel consumption and optimize the system performance of the proposed car. Moreover, a VCDS measurement unit is developed to collect vehicle data based on real-world driving scenarios. The simulation results are compared with experimental data to validate the model`s accuracy. The simulation results prove the effectiveness of the proposed energy management strategy (EMS), with an approximately 89.46% reduction in fuel consumption for the hybrid powertrain compared to the gas-powered traditional vehicle, and 90.05% energy efficiency is achieved.
Tárgyszavak:	Műszaki tudományok Informatikai tudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk drivetrain genetic algorithm (GA) internal combustion engine (ICE) 1.9 TDI PD engine 2.0 TDI CR diesel engine
Megjelenés:	Energies. - 17 : 5 (2024), p. 1-25. -
További szerzők:	Dulaimi, Mohammed Silavinia, Alaa Babangida, Aminu (1988-) (Informatics)(mérnök) Szemes Péter Tamás (1976-) (gépészmérnök, villamosmérnök)
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
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