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On Neural Networks Based Electrothermal Modeling of GaN Devices

IEEE ACCESS 2019年 7卷 94205-94214页

作者： Jarndal, Anwar Univ Sharjah Elect & Comp Engn Dept Sharjah 27272 U Arab Emirates

This paper presents an effcient artificial neural network (ANN) electrothermal modeling approach applied to GaN devices. The proposed method is based on decomposing the device nonlinearity into intrinsic trapping-induced and thermal-induced nonlinearities that can be simulated by low-order ANN models. The ANN models are then interconnected in the physics-relevant equivalent circuit to accurately simulate the transistor. genetic algorithm (GA)-based training procedure has been implemented to find optimal values for the weights of the ANN models. The modeling approach is used to develop a large-signal model for a 1-mm gate-width GaN high-electron mobility transistor (HMET). The model has been implemented in the advanced design system (ADS) and it has been validated by pulsed and continues small- and large-signal measurements. The model simulations showed a very good agreement with the measurements and verify the validity of the developed technique for dynamic electrothermal modeling of active devices.

关键词： GaN HEMT electrothermal modeling neural networks genetic algorithm optimization

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Design and optimization of water drop curve baffles in high temperature PEMFC channel

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IONICS 2024年第12期30卷 8221-8232页

作者： Yang, Hao Cheng, Taihong Mao, Yi Wenzhou Univ Coll Mech & Elect Engn Wenzhou 325035 Peoples R China

The operating temperature of high-temperature proton exchange membrane fuel cells (HT-PEMFC) exceeds 120 degrees C. The strategic addition of baffles in the HT-PEMFC flow channel can facilitate the diffusion of reactant gases towards the gas diffusion layer (GDL), increase the reaction area of the catalytic layer, improve the reaction rate, and enhance overall performance. The water drops curve baffle proposed in this study exhibits a more optimal curvature profile for gas flow compared to previous baffle designs. In this study, the optimal quantity, inlet and outlet orientations, and size parameters of the water drop curve baffles were examined by combining three-dimensional simulation modeling with genetic algorithm optimization. A comparison of net power density for configurations ranging from zero to four baffles in the HT-PEMFC demonstrated that the configuration with four baffles achieved superior performance, resulting in a net power density of 0.368 W/cm2, which represents a 5.74% increase compared to the basic channel without baffles. Additionally, it was observed that reverse flow incurs an additional pressure drop of 1.12% compared to forward flow. Following optimization, with the variables set to a = 0.730123 and b = 0.317671, the net power density increased to 0.3759 W/cm2, reflecting a 2.17% improvement over the non-optimized state, thereby achieving the optimal performance level for HT-PEMFC.

关键词： High-temperature PEMFC Water drop curve baffles genetic algorithm optimization Net power density

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Optimizing thermal energy storage in rectangular unit: Exploring the impact of moving fin with phase change material

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JOURNAL OF ENERGY STORAGE 2024年 99卷

作者： Izgi, Burak Demirag, Hueseyin Zahit Yozgat Bozok Univ Dept Mech Engn TR-66200 Yozgat Turkiye

This research presents an innovative moving fin design for a latent heat storage unit, with the objective of improving thermal performance. The methodology integrates numerical simulation, a machine learning approach, and a multi-objective genetic optimization algorithm (NSGA-II). The study optimizes fin parameters, such as fin velocity (Vf), V f ), fin thickness (tf), t f ), fin length (Lf) L f ) and initial fin position (yf). y f ). The optimization process aims to maximize both power (P) P ) and stored energy per mass (Em), E m ), assigning equal importance to both criteria. The outcomes reveal a considerable rise in power with minor compromises in stored energy per mass. The incorporation of moving fins in rectangular enclosure with PCM leads to a significant power boost while preserving stored latent energy with minimal compromise. In comparison to the no-fin condition, fixed 1-fin and fixed 3-fin configurations lead to stored energy losses of 4.16 % and 11.73 %, respectively, accompanied by power increases of 20.48 % and 51.17 %, respectively. Conversely, the optimized condition for maximum power with moving fins incurs a mere 2.73 % stored energy loss but achieves a remarkable 173.92 % increase in power. The optimized design parameters for maximizing power (P) P ) include Vf f = 22.5 x 10-3 mm/s, yf f = 60 mm, tf= f = 2 mm, and Lf f = 40 mm.

关键词： Thermal energy storage genetic algorithm optimization Dynamic thermal systems

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Parametric Analysis and Design optimization of a Pyrotechnically Actuated Device

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INTERNATIONAL JOURNAL OF AERONAUTICAL AND SPACE SCIENCES 2016年第3期17卷 409-422页

作者： Han, Doo-Hee Sung, Hong-Gye Jang, Seung-Gyo Ryu, Byung-Tae Korea Aerosp Univ Dept Aerosp & Mech Engn Gyeonggi 10540 South Korea Agcy Def Developmen4 Adv Prop Technol Ctr POB 35 Daejeon 34060 South Korea

A parametric study based on an unsteady mathematical model of a pyrotechnically actuated device was performed for design optimization. The model simulates time histories for the chamber pressure, temperature, mass transfer and pin motion. It is validated through a comparison with experimentally measured pressure and pin displacement. Parametric analyses were conducted to observe the detailed effects of the design parameters using a validated performance analysis code. The detailed effects of the design variables on the performance were evaluated using the one-at-a-time (OAT) method, while the scatter plot method was used to evaluate relative sensitivity. Finally, the design optimization was conducted by employing a genetic algorithm (GA). Six major design parameters for the GA were chosen based on the results of the sensitivity analysis. A fitness function was suggested, which included the following targets: minimum explosive mass for the uniform ignition (small deviation), light casing weight, short operational time, allowable pyrotechnic shock force and finally the designated pin kinetic energy. The propellant mass and cross-sectional area were the first and the second most sensitive parameters, which significantly affected the pin's kinetic energy. Even though the peak chamber pressure decreased, the pin kinetic energy maintained its designated value because the widened pin cross-sectional area induced enough force at low pressure.

关键词： Pyrotechnically actuated device Performance analysis Sensitivity analysis genetic algorithm optimization

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Fractional Adaptive Control Optimized by genetic algorithms, Applied to Automatic Voltage Regulators.

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REVISTA IBEROAMERICANA DE AUTOMATICA E INFORMATICA INDUSTRIAL 2016年第4期13卷 403-409页

作者： Ortiz-Quisbert, Marco E. Duarte-Mermoud, Manuel A. Milla, Freddy Castro-Linares, Rafael Univ Chile Dept Ingn Elect Ave Tupper 2007 Santiago Chile Univ Chile Ctr Avanzado Tecnol Mineria AMTC Ave Tupper 2007 Santiago Chile IPN CINVESTAV Dept Ingn Elect Ave Inst Politecn Nacl 2508 Mexico City DF Mexico

The technique Fractional Order Model Reference Adaptive Control (FOMRAC) applied to an Automatic Voltage Regulator (AVR) is presented in this paper. The work is focused on tuning the adaptive gains and the derivation order of the adaptive laws of the FOMRAC, determined through the minimization of a criterion function defined for the simplified model of the AVR, by means of the genetic algorithm (GA) optimization technique. Based on the criterion function proposed by other authors a simulated comparative study is performed, comparing the proposed methodology with the integer order PID control reported in (Zamani et al., 2009). It is shown that the FOMRAC with parameters optimized by GA provides better results in terms of robustness under parameters variations of the system under control and improvements in the convergence speed of the control error.

关键词： Fractional Order Model Reference Adaptive Model Reference Adaptive Control Fractional Control Automatic Voltage Regulator genetic algorithms genetic algorithm optimization

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New method for power allocation of multi-power sources considering speed-up transient vibration of planetary power-split HEVs driveline system

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MECHANICAL SYSTEMS AND SIGNAL PROCESSING 2019年 128卷 1-18页

作者： Wang, Feng Zhang, Jian Xu, Xing Cai, Yingfeng Zhou, Zhiguang Sun, Xiaoqiang Jiangsu Univ Automot Engn Res Inst Zhenjiang 212013 Jiangsu Peoples R China Chongqing Univ Technol Minist Educ Key Lab Adv Manufacture Technol Automobile Parts Chongqing 400054 Peoples R China Chery Automobile Co Ltd Powertrain Technol Ctr New Energy Dev Dept Wuhu 241009 Peoples R China

One of the major issues for hybrid electric vehicles (HEVs) powertrain is the torsional vibration in the process of speed-up condition, which is unavoidable. The broader goal of this article is to re-examine the classical gear transmission machinery transient vibration problem in the context of a 4 + N degree of freedom nonlinear torsional system that essentially describes a planetary coupling transmission system (PCTS) of HEVs example, and further provide a new method for power allocation of multi-power sources considering speed-up transient vibration of planetary power-split HEVs driveline system. In particular, resonant amplifications during acceleration, as excited by angular displacement-based meshing stiffness of gear teeth, are investigated using a nonlinear torsional model, and the transient vibration predictions are successfully compared with test bench results. Then a quasi-linear model during acceleration process is proposed and numerically solved to obtain the transient vibration acceleration as well as its envelope curve. Dynamic response results of PCTS are also successfully compared and analyzed under different speed-allocation rules. Finally, an improved genetic algorithm method is applied to construct optimal relationship between the motor speeds and vehicle speeds, and the influences of vibration character and energy consumption are successfully considered in multi-optimized function. Experimental results under the speed-up condition show that transient vibration acceleration of the optimized powertrain is decreased within the safe range, thus new power-allocation solutions provide more insight to the enhancement of planetary power-split HEVs quality. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Transient vibration-induced power allocation Angular displacement-based meshing stiffness Planetary coupling transmission system Multi-power source machinery genetic algorithm optimization

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Zinc Oxide Thin Films Characterization, AFM, XRD and X-ray Reflectivity

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EXPERIMENTAL TECHNIQUES 2016年第4期40卷 1297-1306页

作者： Solookinejad, Gh. Rozatian, A. S. H. Habibi, M. H. Islamic Azad Univ Dept Phys Marvdasht Branch Marvdasht Iran Univ Isfahan Dept Phys Esfahan *** Iran Univ Isfahan Dept Chem Esfahan *** Iran

In this study, surface structures of two zinc oxide (ZnO) thin films, prepared by sol-gel spin and dip-coating methods, were investigated. Ex situ Atomic Force Microscopy (AFM), X-ray diffraction (XRD), and X-ray reflectivity measurements were carried out in order to study the surface structure. XRD measurements showed nanostructured ZnO thin films with well-defined orientations. Fractal analysis was applied on the AFM data to illustrate the surface morphology of thin films. Fractal analysis provided a precious depiction of irregularities found in ZnO thin films and revealed that both interface width W and lateral correlation length xi are strongly affected by coating method. Calculations showed that the film that was prepared by dip-coating had correlation length, interface width and fractal dimension of 56.2, 2.3, and 2.2 nm, respectively. These parameters for spin-coated sample were 354.8, 8.5, and 2.64 nm, respectively. optimization of X-ray reflectivity by genetic algorithm optimization revealed structural parameters of thin films such as surface and interface roughness and thickness of the films. These calculations showed that dip-coated thin film has a smooth surface, whereas spin-coated thin film has a rough surface.

关键词： Zinc Oxide Surface Structure Spin and Dip Coatings genetic algorithm optimization

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Optimal planning and design of run-of-river hydroelectric power projects

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RENEWABLE ENERGY 2019年 141卷 858-873页

作者： Ibrahim, Mohamed Imam, Yehya Ghanem, Ashraf Cairo Univ Fac Engn Dept Irrigat & Hydraul Giza Egypt Univ Sci & Technol Zewail City Sci & Technol Environm Engn Program Giza Egypt

An optimal planning and preliminary-design (OPD) model was developed to maximize the annual net benefit of run-of-river (RoR) hydropower projects along a stream. The OPD model identifies optimal, non-overlapping RoR projects along the given stream. For each project, the OPD model determines intake location;penstock diameter and length;and type, number, and discharge of turbines. The OPD model applies genetic algorithm in two stages. The first stage optimizes design of individual potentially overlapping projects densely spaced at uniform intervals along the stream and the second stage determines the set of non-overlapping projects that maximizes the net hydropower benefit. Results of the OPD model compared favorably to results of previous models for a hypothetical case study. Further application of the OPD model to idealized case studies with different stream elevation profiles and with tributary flows indicated that the model gives reliable results. The OPD model was used to identify optimal RoR projects for the Guder River, Ethiopia. The OPD model identified 22 optimal RoR projects covering similar to 49 km of the 127-km-long Guder River. The total annual generated energy from the identified projects is similar to 540 GWh and the installed capacity for individual projects ranges between similar to 1 MW and 21 MW. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Hydropower Run-of-river genetic algorithm optimization Guder river

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Optimal design of passive-adaptive pendulum tuned mass damper for the global vibration control of offshore wind turbines

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WIND ENERGY 2021年第6期24卷 573-595页

作者： Bertollucci Colherinhas, Gino Petrini, Francesco de Morais, Marcus Vinicius Girao Bontempi, Franco Univ Brasilia Fac Tecnol Campus Darcy Ribeiro Brasilia DF Brazil Sapienza Univ Roma Sch Engn Via Eudossiana 18 Rome Italy

This paper presents an optimal design procedure for a pendulum tuned mass damper (PTMD) to mitigate the global structural vibrations of offshore wind turbines (OWTs) in the fore-aft and side-side directions. The procedure is tested to the design of a PTMD to be applied to the 5-MW benchmark baseline monopile wind turbine proposed by the National Renewable Energy Lab (NREL). The computation of wind and wave spectra, as well as the evaluation of the hydrodynamic and aerodynamic loads, is conducted by using an in-house built MATLAB (R) routine working together with an ANSYS (R) 3-D finite element (FE) global model for evaluating the resultant peak displacement response at the OWT hub by a power spectral density (PSD) analysis. In order to validate the OWT FEM model, a result comparison is made with the NREL OpenFAST, finding good matches between the two codes. An in-house built genetic algorithm (GA) toolbox, coded in MATLAB (R), is then used to optimally design the parameters of a PTMD with a simplified 2-degrees-of-freedom (2DOF) model. The chosen GA fitness function targets the minimization of the peak response of the primary structure as evaluated by the 2DOF model. The design parameters of the PTMD are the flexural rigidity and damping, the mass ratio and pendulum length. After the 3-D FE model of the OWT without any control device has been validated, and the PTMD has been optimized by the simplified 2DOF model, the performances of the PTMD are examined on a 3-D global FE OWT + PTMD model in ANSYS (R).

关键词： genetic algorithm optimization offshore wind turbine pendulum tuned mass damper power spectral density analysis structural control

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A GA optimization for lithium-ion battery equalization based on SOC estimation by NN and FLC

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2015年 73卷 318-328页

作者： Zhang, ShuMei Yang, Lin Zhao, XiaoWei Qiang, Jia Xi Shanghai Jiao Tong Univ Inst Automot Elect Technol Shanghai 200240 Peoples R China

An intelligent control proposal for battery equalization is presented by genetic algorithm optimization integrated with fuzzy logic control-neural network algorithm. First, an effective two-stage DC/DC converter architecture is developed, which pave the way for the hardware module. Then, an equivalent circuit model in weighted combination with ampere-hour counting method is adopted by fuzzy logic control scheme to obtain static SOC estimation. Then the dynamic battery SOC is precisely estimated on basis of static SOC by means of neural network. The most important is the genetic algorithm optimization for battery equalization to improve the energy efficiency and time efficiency of the equalization system. Finally, certification of simulation is demonstrated to validate the proposed novel equalization scheme. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Fuzzy logic control-neural network algorithm Two-stage DC/DC converter Equivalent circuit model Ampere-hour counting method genetic algorithm optimization

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