Optimal parameter estimation of polymer electrolyte membrane fuel cells model with chaos embedded particle swarm optimization

Ozturk, 2020, Life cycle assessment of hydrogen-based electricity generation in place of conventional fuels for residential buildings, Int J Hydrogen Energy, 45, 26536, 10.1016/j.ijhydene.2019.05.150 Temiz, 2020, Design and analysis of a combined floating photovoltaic system for electricity and hydrogen production, Int J Hydrogen Energy, 45, 3457, 10.1016/j.ijhydene.2018.12.226 Sorgulu, 2018, A renewable source based hydrogen energy system for residential applications, Int J Hydrogen Energy, 43, 5842, 10.1016/j.ijhydene.2017.10.101 Toghyani, 2020, Performance analysis and exergoeconomic assessment of a proton exchange membrane compressor for electrochemical hydrogen storage, Int J Hydrogen Energy, 45, 34993, 10.1016/j.ijhydene.2020.01.232 Bayrak, 2016, A low-cost power management system design for residential hydrogen & solar energy based power plants, Int J Hydrogen Energy, 41, 12569, 10.1016/j.ijhydene.2016.01.093 Özdemir, 2020, The effects of the FOPI controller and time delay on stability region of the fuel cell microgrid, Int J Hydrogen Energy, 45, 35064, 10.1016/j.ijhydene.2020.05.211 Yildirim, 2020, Advanced controller design based on gain and phase margin for microgrid containing PV/WTG/Fuel cell/Electrolyzer/BESS, Int J Hydrogen Energy Sharma, 2020, Waste-to-energy nexus for circular economy and environmental protection: recent trends in hydrogen energy, Sci Total Environ, 713, 136633, 10.1016/j.scitotenv.2020.136633 Yildirim, 2020, Gain and phase margins based stability region analysis of time-delayed shipboard microgrid with sea wave energy, IET Electr Power Appl, 14, 1347, 10.1049/iet-epa.2019.0762 Sharma, 2020, Sustainable environmental management and related biofuel technologies, J Environ Manag, 273, 111096, 10.1016/j.jenvman.2020.111096 Saleh, 2020, Recent trends in functionalized nanoparticles loaded polymeric composites: an energy application, Mater Sci Energy Technol, 3, 515 Srivastava, 2020, Sustainable energy from waste organic matters via efficient microbial processes, Sci Total Environ, 722, 137927, 10.1016/j.scitotenv.2020.137927 Wang, 2014, The development of an exchangeable PEMFC power module for electric vehicles, Int J Hydrogen Energy, 39, 3855, 10.1016/j.ijhydene.2013.12.128 Wilberforce, 2017, Developments of electric cars and fuel cell hydrogen electric cars, Int J Hydrogen Energy, 42, 25695, 10.1016/j.ijhydene.2017.07.054 Changizian, 2020, Performance optimization of hybrid hydrogen fuel cell-electric vehicles in real driving cycles, Int J Hydrogen Energy, 45, 35180, 10.1016/j.ijhydene.2020.01.015 Lapeña-Rey, 2017, A fuel cell powered unmanned aerial vehicle for low altitude surveillance missions, Int J Hydrogen Energy, 42, 6926, 10.1016/j.ijhydene.2017.01.137 Bayrak, 2020, Investigation of PEMFC performance for cruising hybrid powered fixed-wing electric UAV in different temperatures, Int J Hydrogen Energy, 45, 7036, 10.1016/j.ijhydene.2019.12.214 Yigit, 2020, Speed controlling of the PEM fuel cell powered BLDC motor with FOPI optimized by MSA, Int J Hydrogen Energy, 45, 35097, 10.1016/j.ijhydene.2020.04.091 Özdemir, 2014, Development of FPGA based power flow monitoring system in a microgrid, Int J Hydrogen Energy, 39, 8596, 10.1016/j.ijhydene.2014.01.011 Yildirim, 2020, Enhancing stability region of time-delayed smart power grids by non-integer controllers, Int J Energy Res, 5711 Yigit, 2016, Mathematical modeling and dynamic Simulink simulation of high-pressure PEM electrolyzer system, Int J Hydrogen Energy, 41, 13901, 10.1016/j.ijhydene.2016.06.022 Yang, 2016, Modeling and optimization for proton exchange membrane fuel cell stack using aging and challenging P systems based optimization algorithm, Energy, 109, 569, 10.1016/j.energy.2016.04.093 Ijaodola, 2019, Energy efficiency improvements by investigating the water flooding management on proton exchange membrane fuel cell (PEMFC), Energy, 179, 246, 10.1016/j.energy.2019.04.074 Giner-Sanz, 2018, Mechanistic equivalent circuit modelling of a commercial polymer electrolyte membrane fuel cell, J Power Sources, 379, 328, 10.1016/j.jpowsour.2018.01.066 Grondin-Perez, 2014, Mechanistic model versus artificial neural network model of a single-cell PEMFC, Engineering, 6, 418, 10.4236/eng.2014.68044 Jemei, 2002, Black-box modeling of proton exchange membrane fuel cell generators. IEEE, Annu. Conf. Ind. Electron. Soc. IECON, 2, 1474 Amphlett, 1995 Ohenoja, 2010, Validation of genetic algorithm results in a fuel cell model, Int J Hydrogen Energy, 35, 12618, 10.1016/j.ijhydene.2010.07.129 Mohamed, 2004, Proton exchange membrane (PEM) fuel cell stack configuration using genetic algorithms, J Power Sources, 131, 142, 10.1016/j.jpowsour.2004.01.012 Mo, 2006, Parameter optimization for a PEMFC model with a hybrid genetic algorithm, Int J Energy Res, 30, 585, 10.1002/er.1170 Zhang, 2013, An adaptive RNA genetic algorithm for modeling of proton exchange membrane fuel cells, Int J Hydrogen Energy, 38, 219, 10.1016/j.ijhydene.2012.10.026 Zhu, 2014, Circular genetic operators based RNA genetic algorithm for modeling proton exchange membrane fuel cells, Int J Hydrogen Energy, 39, 17779, 10.1016/j.ijhydene.2014.07.081 Ye, 2009, Parameter identification for proton exchange membrane fuel cell model using particle swarm optimization, Int J Hydrogen Energy, 34, 981, 10.1016/j.ijhydene.2008.11.026 Yuan, 2020, Parameter identification for a proton exchange membrane fuel cell model, WCX SAE World Congr. Exp., 10.4271/2020-01-0858 Isa, 2013, 442 Askarzadeh, 2011, Optimization of PEMFC model parameters with a modified particle swarm optimization, Int J Energy Res, 35, 1258, 10.1002/er.1787 Chakraborty, 2012, PEM fuel cell modeling using differential evolution, Energy, 40, 387, 10.1016/j.energy.2012.01.039 Gong, 2013, Accelerating parameter identification of proton exchange membrane fuel cell model with ranking-based differential evolution, Energy, 59, 356, 10.1016/j.energy.2013.07.005 Dai, 2011, Seeker optimization algorithm for global optimization: a case study on optimal modelling of proton exchange membrane fuel cell (PEMFC), Int J Electr Power Energy Syst, 33, 369, 10.1016/j.ijepes.2010.08.032 Askarzadeh, 2011, Artificial immune system-based parameter extraction of proton exchange membrane fuel cell, Int J Electr Power Energy Syst, 33, 933, 10.1016/j.ijepes.2010.12.036 Zhang, 2013, Hybrid artificial bee colony algorithm for parameter estimation of proton exchange membrane fuel cell, Int J Hydrogen Energy, 38, 5796, 10.1016/j.ijhydene.2013.01.058 Li, 2012, Development and investigation of efficient artificial bee colony algorithm for numerical function optimization, Appl Soft Comput, 12, 320, 10.1016/j.asoc.2011.08.040 Askarzadeh, 2013, A new heuristic optimization algorithm for modeling of proton exchange membrane fuel cell: bird mating optimizer, Int J Energy Res, 37, 1196, 10.1002/er.2915 Niu, 2014, A biogeography-based optimization algorithm with mutation strategies for model parameter estimation of solar and fuel cells, Energy Convers Manag, 86, 1173, 10.1016/j.enconman.2014.06.026 Askarzadeh, 2014, A backtracking search algorithm combined with Burger's chaotic map for parameter estimation of PEMFC electrochemical model, Int J Hydrogen Energy, 39, 11165, 10.1016/j.ijhydene.2014.05.052 Niu, 2014, An improved TLBO with elite strategy for parameters identification of PEM fuel cell and solar cell models, Int J Hydrogen Energy, 39, 3837, 10.1016/j.ijhydene.2013.12.110 Ali, 2017, Effective parameters' identification for polymer electrolyte membrane fuel cell models using grey wolf optimizer, Renew Energy, 111, 455, 10.1016/j.renene.2017.04.036 El-Fergany, 2018, Extracting optimal parameters of PEM fuel cells using Salp Swarm Optimizer, Renew Energy, 119, 641, 10.1016/j.renene.2017.12.051 El-Fergany, 2018, Electrical characterisation of proton exchange membrane fuel cells stack using grasshopper optimiser, IET Renew Power Gener, 12, 9, 10.1049/iet-rpg.2017.0232 El-Fergany, 2019, Semi-empirical PEM fuel cells model using whale optimization algorithm, Energy Convers Manag, 201, 112197, 10.1016/j.enconman.2019.112197 Xu, 2019, Parameter estimation of proton exchange membrane fuel cells using eagle strategy based on JAYA algorithm and Nelder-Mead simplex method, Energy, 173, 457, 10.1016/j.energy.2019.02.106 Priya, 2019, Application of flower pollination algorithm for enhanced proton exchange membrane fuel cell modelling, Int J Hydrogen Energy, 44, 18438, 10.1016/j.ijhydene.2019.05.022 İnci, 2020, Performance enhancement of energy extraction capability for fuel cell implementations with improved Cuckoo search algorithm, Int J Hydrogen Energy, 45, 11309, 10.1016/j.ijhydene.2020.02.069 Yuan, 2020, A new technique for optimal estimation of the circuit-based PEMFCs using developed Sunflower Optimization Algorithm, Energy Rep, 6, 662, 10.1016/j.egyr.2020.03.010 Yuan, 2020, Developed Coyote Optimization Algorithm and its application to optimal parameters estimation of PEMFC model, Energy Rep, 6, 1106, 10.1016/j.egyr.2020.04.032 Yin, 2020, PEMFC identification using deep learning developed by improved deer hunting optimization algorithm, Int J Power Energy Syst, 40 Menesy A, 2020, Effective parameter extraction of different polymer electrolyte membrane fuel cell stack models using a modified artificial ecosystem optimization algorithm, IEEE Access, 8, 31892, 10.1109/ACCESS.2020.2973351 Fathy, 2020, A novel approach based on hybrid vortex search algorithm and differential evolution for identifying the optimal parameters of PEM fuel cell, Renew Energy, 146, 1833, 10.1016/j.renene.2019.08.046 Gurau, 2010, Technique for characterization of the wettability properties of gas diffusion media for proton exchange membrane fuel cells, J Colloid Interface Sci, 350, 577, 10.1016/j.jcis.2010.07.011 Ashraf, 2020, Analyzing different planar biogas-fueled SOFC stack designs and their effects on the flow uniformity, Energy, 190, 116450, 10.1016/j.energy.2019.116450 Ma, 2018, Data-driven proton exchange membrane fuel cell degradation predication through deep learning method, Appl Energy, 231, 102, 10.1016/j.apenergy.2018.09.111 Chen, 2019, Degradation model of proton exchange membrane fuel cell based on a novel hybrid method, Appl Energy, 252, 113439, 10.1016/j.apenergy.2019.113439 Alatas, 2009, Chaos embedded particle swarm optimization algorithms, Chaos, Solit Fractals, 40, 1715, 10.1016/j.chaos.2007.09.063 Eberhart, 1995, A new optimizer using particle swarm theory, MHS’95. Proc. Sixth Int. Symp. Micro Mach. Hum. Sci., 39, 10.1109/MHS.1995.494215 Özdemir, 2017, Comparative performance analysis of optimal PID parameters tuning based on the optics inspired optimization methods for automatic generation control, Energies, 10, 2134, 10.3390/en10122134 Yildirim, 2019, Design of integer order approximation fractional order controller with for automatic voltage regulation system, 1 Öztürk, 2017, Load-frequency optimization with heuristic techniques in A autonomous hybrid AC microgrid, Int J Energy Smart Grid, 2, 2, 10.23884/IJESG.2017.2.1.01 Celik, 2018, Field-oriented control of the PMSM with 2-DOF PI controller tuned by using PSO, 1 Özdemir, 2015, Tuning of optimal classical and fractional order PID parameters for Automatic generation control based on the bacterial swarm optimization, IFAC-PapersOnLine, 48, 501, 10.1016/j.ifacol.2015.12.429 Serbet, 2017, Design of digital IIR filter using particle swarm optimization, 202 Kalender, 2020, Modelling to predict moisture ratio in infrared drying of machine plaster by particle swarm optimization, Curr Phys Chem, 10, 126, 10.2174/1877946810666200218092820