A Novel Hybrid MPPT Controller for PEMFC Fed High Step-Up Single Switch DC-DC Converter

. At present, there are diferent types of Renewable Energy Resources (RESs) available in nature which are wind, tidal, fuel cell, and solar. Te wind, tidal, and solar power systems give discontinuous power supply which is not suitable for the present automotive systems. Here, the Proton Exchange Membrane Fuel Stack (PEMFS) is used for supplying the power to the electrical vehicle systems. Te features of fuel stack networks are very quick static response, plus low atmospheric pollution. Also, this type of power supply system consists of high fexibility and more reliability. However, the fuel stack drawback is a nonlinear power supply nature. As a result, the functioning point of the fuel stack varies from one position to another position on the V-I curve of the fuel stack. Here, the frst objective of the work is the development of the Grey Wolf Optimization Technique (GWOT) involving a Fuzzy Logic Controller (FLC) for fnding the Maximum Power Point (MPP) of the fuel stack. Tis hybrid GWOT-FLC controller stabilizes the source power under various operating temperature conditions of the fuel stack. However, the fuel stack supplies very little output voltage which is improved by introducing the Single Switch Universal Supply Voltage Boost Converter (SSUSVBC) in the second objective. Te features of this proposed DC-DC converter are fewer voltage distortions of the fuel stack output voltage, high voltage conversion ratio, and low-level voltage stress on switches. Te fuel stack integrated SSUSVBC is analyzed by selecting the MATLAB/Simulink window. Also, the proposed DC-DC converter is tested by utilizing the programmable DC source.


Introduction
From the present literature survey, the availability of Nonrenewable Energy Resources (NESs) is decreasing extensively because of its disadvantages such as high catchment area for the installation, more environmental efects, a high efect on the ozone layer, direct efect on human life, and more power generation price [1].In addition, this type of power system is not suitable for rural areas.So, the current research is focusing on the RES for supplying the energy to all local as well as urban people.Te classifcation of RES is wind, geothermal energy, ocean energy, hydropower, solar energy, and bioenergy.In article [2], the authors discussed the wind power supply networks for generating electricity in the coastal regions.In this wind network, the modern turbines with very low specifc ratings plus high hub heights increase the wind energy potential.As a result, the overall wind power system installation cost is reduced [3].Here, the wind turbines capture the wind velocity for running the dual-fed induction machine.Te major problem of wind power systems is noise creation by wind turbines which may not be accepted by human beings [4].Especially, birds and bats are seriously afected by the wind power network.Also, the main challenge of the wind system is the minimization of levelized production costs.Levelized production cost of the wind system is decided based on the energy production cost concerning the economic life time of the utilized system [5].Finally, the wind systems are installed in limited places because of the potential impact on the environment.
All of the wind systems' drawbacks are limited by utilizing the geothermal power supply networks.In these geothermal systems, the fuids are collected from the underground reservoirs and it is used for the conversion of water into steam.Te generated steam is sent to the turbines to run the electrical machine [6].In the literature, there are various types of geothermal power networks available such as fash steam, dry steam, and binary cycle.Here, the type of power conversion depends on the power plant design which is mainly focused on the fuid surface and its operating temperature.Te dry steam power plant takes hydrothermal fuids which are closely available in the form of steam [7].In this system, the available steam is directly sent to the rotating turbine which is directly coupled with the functioning generator for supplying the peak power to the emergency applications like shopping malls and hospitals.Te dry steam power plants are a very old type of power plant that was frst referred to by Lardarello in the nineteenth century.Similarly, the fash type of power network is a commonly used power network that collects the fuids with high functioning temperatures [8].Finally, the binary cycle geothermal power network is used for supplying power to the local consumers at low as well as high fuid operating temperature conditions [9].Te merits of geothermal systems are low-level environmental pollution, moderate sustainability, massive potential, and more reliability.However, the disadvantages of geothermal systems are minor environmental pollution, suitable for a specifc location, mostly preferable for urban areas, and high initial cost [10].
Te demerits of geothermal systems are limited by using ocean energy systems.In this ocean energy, the wave energy is captured by using the turbines and is transferred into the electrical power supply by using the bidirectional electrical machines.Te features of ocean energy systems are naturefree, unlimited availability, high potential, good reliability, and zero environmental pollution.Te demerits of this system are high installation cost and need for high scalability.In addition, the urban areas will beneft from the help of the ocean energy system.Te limitations of ocean energy systems are overcome by using the hydropower networks [11].From the literature review, there are diferent types of hydraulic systems available in nature and all of these systems utilize the kinetic energy of water fow from upstream to downstream.Here, high-pressurized storage water is utilized to achieve the kinetic energy of the water.Te features of hydrosystems are useful for peak load demand, nonpolluting sources of energy, more resilience, and low distribution power cost [12].However, the drawbacks of hydrosystems are limited by utilizing solar power systems.From the literature review, sunlight energy is available in nature excessively free of cost.Here, the sunlight insolation comes to the earth with diferent incident angles.Te solar photovoltaic panels are installed on the earth in such a way that the incident angle of sunlight irradiation is exactly perpendicular to the PV panel [13].Once the PV panel receives the sunlight insolation energy, the free electrons in the P-N type materials of the PV absorb the sun energy and start functioning to generate the electrical power supply [14].
Te working behavior of the PV is exactly similar to the normal P-N diode operation.Solar cells are developed by utilizing the various categories of advanced manufacturing technologies which are named thin flm, polycrystalline, and monocrystalline.Te thin flm-based solar cells have various types of advantages when compared to the 1 st generation silicon solar cells in terms of lighter weight, thin construction, and more fexibility [15].Due to these merits, the thin flm model solar systems are utilized in integrated residential buildings and water heating systems.In [16], the authors utilized the polycrystalline model solar cells for the large-scale solar power network installation.Here, there are multiple crystalline solar cells involved in each polycrystalline model solar panel.As a result, polycrystalline solar cells work at very low functioning temperature conditions of the sunlight system.Tese types of solar cells are used in large-scale commercial buildings for supplying electricity to consumers [17].So, most human beings are independent of the central grid for power consumption.However, thin flm and polycrystalline solar cells have drawbacks such as low sunlight energy conversion efciency, being less suitable for domestic application, and being moderately expensive [18].So, monocrystalline silicon solar panels are utilized in most places because their merits are more efciency, crystal structure, and more reliability.However, these solar modules require high implementation costs and less power production under high operating temperature conditions of the solar systems.
Each solar cell voltage production is 0.95 V to 1 V which is not at all useful for any local consumers.So, the solar modules are series connected to enhance the voltage capability of the overall system.Sometimes, the peak loads require a high number of currents; then, the solar modules are placed in a parallel fashion [19].So, multiple types of solar cells are connected in parallel plus series for supplying the power to the electric vehicle applications.Te major issue of solar systems is discontinuous power supply and less useful for industrial applications.So, in this article, the fuel stack technology is utilized for the four-wheeler system for the continuous functioning of the electric vehicle network.Here, the fuel modules are diferentiated based on the usage of electrolytes in the system.Te fuel modules are classifed as Alkaline Fuel Module (AFM), Molten Carbonate Fuel Module (MCFM), Regenerative Fuel Module (RFM), Proton Exchange Membrane Fuel Module (PEMFM), Phosphoric Acid Fuel Module (PAFM), and Solid Oxide Fuel Module (SOFM).Te alkaline fuel network is utilized in the article [20] for supplying the rated voltage to the microgrid network.Now, the microgrid is gaining a lot of attention.Te microgrid involves the battery charging station, fuel stack, and various renewable energy systems [21].All the power supply networks are interfaced to one common busbar for maintaining the constant load voltage.Here, the alkaline model fuel network supplies heat combined with water and electrical power supply by utilizing the inputs oxygen plus hydrogen chemical decomposition.In this fuel stack, the electrode is placed in between the anode material and cathode material and it is manufactured by selecting the alkaline membrane [22].
Te merits of an alkaline fuel stack network are moderate efciency, very simple heat management, moderate startup time, high chemical activity, and less expensive anode and cathode materials.In addition, the internal combustion of an 2 International Transactions on Electrical Energy Systems alkaline network is easy when equated with the battery system [23].As a result, the fuel stack takes less money for power supplying to the global industries.Especially, the alkaline fuel stack networks are more useful for saving labor time and less installation space and are more suitable for peak load application.Te main applications of alkaline fuel stacks are backup power supply, highly useful for commercial and residential building applications [24].However, the alkaline fuel stacks are very intolerant to carbon dioxide because CO 2 consumes more alkaline chemical decomposition.As a result, the overall system chemical reaction and operating system efciency are reduced extensively.Te demerits of alkaline fuel cell modules are limited by applying the reversible fuel stacks.In these reversible fuel stacks, the input hydrogen fuel is obtained from pure water [25].Here, the water is split into hydrogen and oxygen ions by using other renewable energy systems like wind and solar systems.On the other hand, the reversible fuel stack gives heated steam which is again fed back to the power supply system by converting into water.Tis type of fuel stack network is more popular for emergency power supply applications.Te disadvantages of reversible fuel stacks are compensated by applying the molten carbonate fuel module.In this MCFM, the alkali metal carbonate electrolyte is used and its maximum functioning temperature capability is 650 °C.Due to this high operating temperature, the selected input fuel for the MCFM is directly fed to the electrolytic channel for generating the electrical power supply with high operating efciency [26].Te selected input chemicals to the MSFM are carbon dioxide, hydrogen, and oxygen, and the heated water is released from the output of the fuel stack.Te MCFM advantages are high operating pressure, less reversible, and good output power conversion efciency.However, this fuel stack is not suitable for portable applications and needs sealing [27].So, the proton exchange membrane fuel module is used in this work for supplying power to the electrical vehicle systems.Tis fuel stack can work at very low as well as high operating temperatures.Te major features of this PEMFM are compact design, highenergy density, and maximum values of specifc power per unit and volume.In addition, its starting speed is very high when equated with the other fuel cells.Te present demand for fuel stacks is illustrated in Figure 1, and the types of fuel stacks are represented in Table 1.
All the fuel stack disadvantages are continuous variations of power due to the continuous variation of the functioning point of the fuel stack.So, there are diferent categories of Maximum Power Point Tracking (MPPT) methodologies used in the literature to stabilize the functioning point of the fuel stack which are machine learning algorithms, optimization technologies, soft computing, nature-inspired algorithms, and conventional controllers.In [29], the researchers applied the Perturb & Observe (P&O) conventional controller to identify the working point of the fuel stack interfaced bidirectional three-phase power converter.Here, initially, the working point of the fuel stack is identifed on the V-I curve of the system.Suppose the identifed functioning point of the fuel stack is on the left side of the V-I curve and then the equivalent resistance of the source system is modifed by enhancing the operating duty cycle of the converter.Otherwise, the equivalent resistance of the overall system is reduced to move the working point of the fuel stack to the actual MPP position [30].Te general merits of this controller are simple in design, less implementation cost, easy to install, and less manpower requirement.However, this controller gives more steady-state fuctuations.As a result, the overall system gets vibrated.All the renewable energy-based power converters create fuctuated voltage and power.In the Kalman flter concept, the available voltage ripples and power ripples are fed to the Kalman flter block for suppressing the fuctuations of fuel stack output power.Tis controller identifes the functioning point of the renewable energy system by utilizing the ripples of the voltage and power [31].So, it does not require any additional flters.Due to this condition, the overall system installation and manufacturing costs are limited.However, this controller is useful for only constant operating temperature conditions of the fuel stack.
For fuctuated temperature conditions of the fuel stack, the researchers are referring to the nature-inspired power point tracking controllers.In this work, the grey wolf optimization technique involves an adaptive fuzzy logic controller developed for enhancing the power conversion efciency of the fuel stack [32].Te merits of this proposed nature-inspired hybrid MPPT controller are less level of dependence on fuel stack modeling, very good dynamic response, more suitable for all types of operating temperature conditions of the fuel stack, high tracking speed, fast convergence ratio, and useful for continuous peak load conditions.However, another issue with the fuel stack is the very high supply current [33][34][35][36].If the fuel stack is directly interfaced with the battery, then the overall network power supply conduction losses are increased.Due to that, the entire system's functioning efciency is reduced.From the literature survey, the power converters are applied to the electric vehicle systems to optimize the fuel stack output supply current.Te power converters are diferentiated based on the utilization of transformer and rectifer circuits.Te transformers including power converters are feedforward, push-pull fyback, and bridge-type converter.Here, isolation means the separation of the source with a converter device to protect the overall network from overvoltage [37].Te merits of isolated power converters are strong antiinterference ability, easy-to-achieve multiple outputs, easy conversion of buck and boost operation, more security, and fewer possibilities of load damage.Also, these converters are useful for wide input voltage operation [38].However, the isolated power converter networks have many disadvantages which lead to very low power transformation efciency, relatively very large volumes, more expensive, and very high design complexity.So, the current industry is focusing on the transformerless power converters which are buck-boost, Cuk, and Luo converters [39].However, these fundamental power transformation circuits have the disadvantage of less power transmission efciency and are moderately suitable for peak load conditions [40,41].So, in this article, a Wide Supply Voltage Power Converter Circuit (WSVPCC) is International Transactions on Electrical Energy Systems proposed to reduce the fuel stack output current and improve the supply voltage profle of the overall system.Te proposed power converter fed power point identifer is shown in Figure 2. From Figure 2, the power converter gives high voltage gain, low output voltage fuctuations, and very little current and voltage stress on power switches.In addition to that, this converter takes very little space for installation and its manufacturing cost is also reduced.

Literature Review on Past Published Works
From the literature review, the past isolated power converter circuits needed more implementation cost and needed more reliability.Also, these converter topologies require high installation space.So, transformerless power converter circuits are developed in [42] for battery charging systems with the help of solid oxide cells.Te basic buck converter circuit is utilized in the PV/fuel stack microgrid system for balancing the power in the all-distribution loads.Tese converters required only one capacitor, plus one switch for balancing the supply voltage.Similarly, a simple boost converter circuit is applied in a telecommunication network for solar battery charging, plus discharging.Te general boost converter circuit required less manufacturing cost, was easy to handle, and needed very low space for installation.However, these types of power converter circuits give less efciency for high switching frequency applications.In [43], the authors worked out the hybrid electric vehicle technology to reduce the dependency on fuel engines.Te combustion engine is interlinked with the electric drive network for regulating the power of the vehicle at various working temperature conditions of the fuel engine.Te hybrid EV network's overall efciency depends on the electric vehicle powertrain.
In EVs, the permanent magnet machine is utilized along with the battery for running the EV at constant speed.In [44], the solid oxide fuel stack network is merged with the quasisource DC-DC converter topology and it is applied to the fourwheeler electric vehicle system to improve the efciency of the system.In SOFS, the electricity supply process happens by utilizing the ceramic electrolyte [45].Here, the negative oxygen ions fow from the cathode layer to the anode layer via a ceramic electrolyte.Te analysis and the specifcations of various categories of fuel stacks are explained in Table 1.In the SOFS, there is a high level of chemical decomposition happening at high operating temperature conditions of the fuel stack.As a result, the performance efciency of the overall system is improved.Also, it consists of high fuel fexibility, less carbon dioxide emissions, and a relatively very low cost of implementation when compared to the phosphoric acid fuel cell [46].Te interleaved single-phase power electronic circuit topology is applied for the high voltage rating battery-based fuel stack system for running the battery in a dual power fow direction at peak load conditions.Te lithium-ion battery state of charge and the state of discharge parameters are supplied to the incremental resistance MPPT block for optimizing the discharge state of the battery.In this MPPTmethodology, the variation of fuel stack voltage and current variables is utilized for fnding the duty ratio of the bidirectional power converter [47].Here, the incremental resistive value is positive when the controller reaches the required MPP place.Otherwise, it may go to the left side of the MPP position of the fuel stack V-I curve.
Te modifed slider methodology is utilized in the hybrid diesel engine, battery, and fuel stack system for identifying the peak power point of the fuel stack, plus enhancing the dynamic response of the overall network [48].In this power production network, the interleaved multiphase power converter is utilized for equal power distribution to all local loads.In this slider controller, the fuel stack oxygen ions, resistive load voltage, and hydrogen decomposition constants are utilized as the state input variables, and the output variable is the switching signal to the fuel stack-fed rectifer circuit [49].All the rectifers generate fuctuated currents and voltages which are given to the Kalman flter block for mitigating the losses of the hybrid PV/fuel stack network.Te merits of this slider MPPT method are very easy, plus good static response.Also, it helps to optimize the fuel stack system power conduction losses.However, this slider controller may not give efcient converter output power.Te demerits of this slider controller are overcome by using Artifcial Neural Networks (ANNs) [50].International Transactions on Electrical Energy Systems

International Transactions on Electrical Energy Systems
Te ANN controller is developed from the human brain's behavior and the human brain consists of multiple nodes that are interlinked with each other [51].All the nodes are exchanging their information to identify the required objective.In [52], the PEMFS/battery-fed bidirectional power conversion circuit duty signal is monitored with the help of a neural network-based MPPT controller.Te merits of these neural networks are very low implementation cost, more useful for all nonlinear issues, ease of use for highly complex problems, and the capability to alter any unknown conditions [52].However, these neural networks need high convergence time, plus more complexity in the ANN structure.Te feedforward neural network is utilized in the diesel/battery/PEMFS system for controlling the converter duty signal at various atmospheric conditions of the fuel stack [53].A detailed analysis of diferent types of MPPT controllers is given in Table 2.

Design and Performance Study of Fuel Cell
As we know nonrenewable power system utilization is reducing drastically in electric vehicle systems because of its demerits such as large space for installation, plus high-power generation cost [59].So, renewable power systems are playing the predominant role in the present electric vehicle systems for optimizing environmental pollution and reducing grid dependence.From the literature study, there are diferent types of renewable power systems available in the society.However, most of the renewable power supply networks give discontinuous power supply.So, in this work, the fuel stack technology is referred for continuous power supply to the automotive systems.In [60], the researchers studied the phosphoric acid fuel stack-based microgrid network for giving energy to local consumers.In this microgrid, the PV/wind/fuel stacks are involved in storing the energy in batteries, and the stored energy is utilized for emergency applications.In PAFSM, the phosphoric liquid is utilized as an electrolyte, and it is highly tolerant to carbon monoxide and carbon dioxide [61].In addition, it is pollution-free and eco-friendly.Te PAFSM is very less sensitive to CO 2 and it has the capability of regeneration of heat along with electricity.Finally, the phosphoric acid fuel network consists of very low volatility.In this fuel stack, the anode accelerates the hydrogen oxidation reaction rate in phosphoric acid.In this fuel stack, the anode must and should be stable for high operating temperature conditions of the phosphoric acid.Sometimes, hydrogen starvation happens in the PAFSM and then the anode gets afected by reverse polarization.However, this fuel stack is inherently much less powerful when compared to the other fuel cells [62].
Te demerits of the phosphoric acid fuel stack are limited by using the solid oxide fuel cell.In the SOFSM, the natural gas fows through the steam reforming process for generating electricity [63].Here, the methane and oxygen chemical recombination generates carbon monoxide, carbon dioxide, water, and hydrogen.Te merits of solid oxide cells are high-functioning efciency, long-term stability, fuel fexibility, less emission, relatively low cost, and low environmental pollution.Te biggest disadvantage of SOFSM is taking more time to start functioning.However, the demerits of SOFSM are limited by using the polymer membrane fuel stack.In this PEMFSM, the proton ions are transferred from the anode chamber to the cathode chamber via a polymer electrolyte.Here, the membrane structure is in the form of a thin plastic flm and it is permeable with the proton when the membrane is saturated with water.However, it may not conduct with the electrons.Te working block diagram of the polymer membrane fuel stack and its corresponding functioning circuits are illustrated in   International Transactions on Electrical Energy Systems International Transactions on Electrical Energy Systems Figures 3(a) and 3(b).From Figure 3(a), in the cathode chamber, the protons are reacted with the electrons, and oxygen for generating the heat, and water are the byproducts.In this fuel stack, the single cell voltage is defned as V FC and in this stack are "N" number of cells are utilized for meeting the peak load demand voltage (V 0L ).
From Figure 3(b), the variables R 0L and R AL are the ohmic power loss of the electrode plus active region power loss of the electrode.Finally, the term R CL is identifed as concentrative power loss of the fuel stack.3.

Design and Performance Study of Various MPPT Controllers
From the literature study, all of the renewable energy systems' power supply is nonlinear.So, the direct power supply from the renewable energy systems to the local consumers is not possible.So, the power electronics devices are used in the renewable power supply systems for maintaining the constant load to the electric vehicle systems [64].However, the functioning point of all renewable power systems is not constant.So, there are various categories of MPPT methodologies that are applied to the renewable power supply network to identify the operating point of the fuel stack.
From the literature review, the MPPT controllers are differentiated as artifcial intelligence, machine learning, nature-inspired, soft computing, and fuzzy logic controllers.
In [65], the authors discussed the fundamental power point tracking methods that are suitable for constant functioning   International Transactions on Electrical Energy Systems temperature conditions of the solid oxide fuel stacks.In [66], the authors proposed the multiple layers involved in neural networks for operating the polymer membrane fuel stack network under various environmental operating temperature conditions.Here, all the neural controllers were developed based on the human brain functioning conditions.Te multilayer neural network MPPT controller utilized structure is shown in Figure 5. Based on the multilayer structure, the selected input neurons in the frst layer are two which are fuel stack supply current (M (1)  1 � I FC ) and fuel stack supply voltage (M (1)  2 � V FC ).Te middle layer collects the signals from the source layer, and the middle layer neurons are 629.Due to this large number of neurons and their corresponding layers, the multilayer neural network takes more data training time, and it requires high convergence time [67].Here, the weights of the neurons are adjusted by utilizing the backpropagation algorithm which is given in (10) and (11) .Here, the terms f(n), b, k, and L are the activation function, the total number of hidden layer nodes, the hidden layer output, and the output node.Finally, the variable "v" defnes the overall neurons in between the input and output layers.
w (2)  vn � w (2)  vn + ∆w vn , (13) After weight updating of all the neurons, there is an error existing in the output layer which is given in (16).From ( 16), the terms V required and V are the required peak voltage and available fuel stack voltage.

Genetic Controller Optimized Artifcial Neural Network
Controller.Te genetic optimization methodology is used in [68] to identify the functioning point of the solar and fuel stack system.Tis algorithm does not require any derivate information.Te merits of this algorithm are more exploration of search space, good fexibility, more adaptability, good parallel processing information, and global optimization.However, this algorithm has many disadvantages which are more computational complexity, high difculty in tuning parameters, more dependence on randomness, risk of premature convergence, and limited understanding of results.So, the genetic algorithm is combined with the proportional and integral block to improve the steady-state response of the system and maintain the transient stability of the overall system.In [69], the genetic controller is combined with the artifcial neural network for tracking the MPP of the hybrid wind/PV/FS power generation system with high efciency.Here, initially, the neural network collects the signals from the fuel stack and solar networks which are sunlight intensity, fuel stack power, solar power, and functioning temperature of all the sources for moving the functioning point of the overall system from the initial stage to the required MPP location.Once, the functioning point of the hybrid network stabilizes with the actual MPP point, then the hill climb starts working to generate the highly accurate nonlinear power characteristics of the system [70].
Te overall training samples considered in this neural network are 689.Te operation of a genetic algorithmdependent neural controller is given in Figure 6.From Figure 6, the generated error signal from the neural controller is monitored by applying the proportional controller.
Here, the continuous changes in fuel stack temperature (T FC ), water membrane (T M ), fuel stack current (I F ), and voltage (V F ) are selected for generating the duty signal to the DC-DC converter.Te time constant of the integral controller is T ic , and fnally, the constraints of the proportional and integral controllers are S P and S i .
From ( 19) and ( 20), the parameters "n", S, W, P, b, a, h, Q, μ, and ψ are the number of neurons, number of iterations, weight of neurons, middle layer constants, output layer constants, time constant of the proportional controller, and weight updating constants.Also, the parameters T ic , U, and D are input variable, hidden layer, and duty signal of the DC-DC converter.

Adjustable Step Change of Fuzzy Controller with
Incremental Conductance.Conventional neural networks take more time to achieve the optimal nonlinear solution of the fuel stack network because it takes more convergence time, 10 International Transactions on Electrical Energy Systems high training data are needed when the neural network involves multiple layers in the structure, and it is less suitable for continuous changes of the environmental conditions of the fuel stack network [71].So, the artifcial neural network limitations are overcome by using the fuzzy logic controller.Fuzzy logic is one type of approach which is used to process the variable towards the true value.Most of the fuzzy controllers are used for solving highly complex nonlinear problems.Te features of fuzzy systems are easy to implement, highly robust, more fexible, good interpretability, and easy to understand.However, the fuzzy logic MPPT controller may not be accurate in the MPP position.In addition, it cannot recognize the neural network and machine learning patterns.Also, it required a highly knowledgeable person to implement the fuzzy logic controller, was very difcult in tuning, less accurate in MPP tracking, and had high computational complexity [72].So, the fuzzy logic is combined with the incremental conductance method for reducing the tracking time of the fuel stack MPP.Here, initially, the fuzzy controller methodology is used for adjusting the step value of the IC controller for optimizing the oscillations across the fuel stack MPP position.Te functioning diagram of this MPPT controller is given in Figure 7. From Figure 7, the continuous variation of fuel stack current (I FC ) and voltage (V FC ) are collected and the resultant error signal is given to the incremental conductance controller.H vold and H vnew are the previously stored fuel stack V-I curve slope and present available fuel stack slope.Te terms D, ΔV, and ΔP are the converter duty signal, change of fuel stack voltage, and change of power.

Fuzzy Logic Controller-Dependent Hill Climb MPPT Controller.
Tere are various conventional controllers available in the literature, which are Perturb & Observe and incremental conductance controllers.However, these controllers are not useful for the rapid changes in the functioning temperature conditions of the fuel stack.So, the researchers referred to the hill climb methodology in [73] for the hybrid wind/fuel stack network power supply system to meet the peak load demand of the local consumers.However, the implementation cost of the hill climb controller is very high when equated to the other controller.So, the fuzzy logic is combined with the hill climb controller to extract the peak power from the renewable energy system.Here, the fuzzy concept is applied to fx the step size value of the hill climb controller [74].Here, the fuzzy logic block captures w 12 (2) w 13 (2) w 14 x 2 (2) (r) x 3 (2) (r) x 4 (2) (r) x 5 (2) (r) f (X 5 (2) )

Signal receiving layer Middle (hidden) layers
Output layer function of activation direction of the data fow (28)

Optimization of Fuzzy Logic Controller by Using Modifed
Grey Wolf Optimizer.Most of the neural network-based power point tracking controllers required high training data of the polymer membrane fuel stack system [75].Also, it required well-experienced person to select the number of layers in the neural network structure.Te drawbacks of neural controllers are overcome by utilizing fuzzy systems.In the fuzzy system, the selection of a membership function is a very difcult task and its functioning efciency depends on the accuracy of membership function selection.In the literature, there are various optimization technologies that are applied to optimize the membership function values.
Here, in this article, the modifed grey wolf methodology is used to improve the functioning efciency of the fuzzy controller.Te pseudocode of the modifed grey wolf controller is shown in Figure 8. From Figure 8, the selected fuel stack variables for fnding the duty signal value of the DC-DC converter are fuel stack current, fuel stack power, and fuel stack voltage.In this grey wolf method, the collected data from the fuel stack are assigned to the various wolves.
Here, all the wolves start searching for the optimized duty value by interchanging their information towards the required objective identifcation.In the frst iteration, the wolves move in diferent directions with diferent velocities.After reaching certain iterations, the wolves move in one direction to fnd the optimal solution for the nonlinear problem of the fuel stack network.Finally, the grey wolf controller tries to make the system stabilize at any one of the local MPP positions of the fuel stack network.After that, the grey wolf controller gives the information to the fuzzy block as shown in Figure 9. From Figure 9, the fuzzy logic system consists of three major blocks which are fuzzifcation, inference network, and defuzzifcation network.In the fuzzifcation system, the input supply variables are transferred into fuzzy sets.Te inference network collects the fuzzy sets for generating the required output of the fuel stack.Finally, the defuzzifcation methodology is used for transferring the fuzzy outputs into crisp solutions.Te fuzzy logic starts identifying the global functioning point of the fuel stack.Here, ( 29) is used to move the functioning point of the fuel stack from the origin position of the V-I curve to the global MPP place.Sometimes, the working point of the fuel stack is on the right-hand side of the V-I curve of the fuel stack and then (30) is used to move the functioning point of the fuel stack towards the actual MPP place.From ( 29) and ( 30), the variables ψ, Power present , and Power previous are the error stabilizing factor and fuel stack powers.

Development of Single Switch Universal Supply Voltage Boost Converter
From the literature study, the isolated power DC-DC converters are not applied for fuel stack running electric vehicle applications because of its disadvantages such as more implementation cost, high space requirement for installation, less efciency for electric vehicle systems, and difculty in developing the switching circuit [76] 4.

Working Stage of Converter (DCCM and CCM): I.
In this stage, the converter works in both the stages of operation which are Discontinuous Conduction Mode (DCCM) and Continuous Conduction Mode (CCM).Tese modes of operation purely depend on the input inductor selection value.Suppose, the selected inductor L q value is more than the converter works in the continuous power supply stage.Otherwise, the utilized power converter works in discontinuous power supply mode.Here, the source is a polymer membrane fuel module for automotive applications.So, the selected input supply inductor value should be very high to work in the continuous power supply mode of operation of International Transactions on Electrical Energy Systems the converter.In this stage, the switch (S) starts working in forward bias condition and then the inductors start absorbing the source currents and voltages which are identifed as I Lq− chrg , I Lw− chrg , V Lq− chrg , and V Lw− chrg .After a certain time duration, the inductors start delivering the currents and voltages which are defned as Similarly, the capacitors' (C l , C k , C j , C h , and C k ) stored currents and voltages are and V Cg− chrg .Finally, the capacitors' discharging parameters are represented as and V Cg− dicg .Te converter inductor charging voltages are given in Figures 11(a) and 11(b).From Figure 11(a), the capacitor voltages and inductor currents are derived in (31) and (32).

Working Stage of Converter (DCCM and CCM): II and III.
In the second mode of converter operation, the available voltage across the MOSFET is reduced and the switch starts moving from the amplifying stage to the blocking stage.
Here, the capacitors C l and C w give the energy to the load side capacitors C j , C h , and C g .From Figure 11(b), the switch-of voltage in the converter fows towards the diodes to make the diodes run in the active region condition.From Figure 12(c), all the switches and diodes are going into the discontinuous functioning stage.As a result, the polymer membrane fuel stack network supplies fuctuated power which is desirable for the four-wheeler electric vehicle network.Here, the switching voltages and currents are completely in a zero-level state.Under steady-state operation of a single switch more power conversion ratio of the DC-DC converter, the available voltage at the load side is derived in (38).Te converter operated duty is defned as D and the time duration of the converter voltage is represented as T S .Under the discontinuous functioning stage of the converter, the time duration of the converter current is T x .Te selected load parameter in the converter is the resistor (R n ) and its corresponding current and voltage are identifed as V n and I n .
From the literature study, the power converter study has been done in terms of their working efciency.Here, in this article, investigation of various categories of power electronics converters has been done in terms of voltage gain availability, total number of semiconductors devices applied for designing the converter, voltage appeared across the switch, type of current fow in the converter circuit, and necessity of ground required for the power converter.In [54], the authors utilized the general nonisolated converter structure for the microgrid power supply system to improve the voltage stability of the fuel stack network.Te advantages of this converter are simple in structure, good reliability, high robustness, and more adaptability.However, this converter needs a high operating duty cycle for high voltagerating electric vehicle applications.As a result, the entire fuel stack power supply network conduction losses are increased extensively.So, the wide output voltage gain, universal supply voltage power converter circuit is utilized in this work for continuous power supply to the automotive system.Te voltage gain and current stress of the proposed converter are given in Table 5.

Analysis of Simulation Results
Te proposed system involves the polymer membrane fuel stack and power point tracking controller along with the high voltage gain DC-DC converter.As of now, the polymer membrane-based fuel stack modules are used for electric vehicle systems because of their features such as high temperature withstanding ability, less atmospheric pollution, easy functioning, less maintenance required, more lifetime, and easy installation.However, the polymer membrane fuel system generates nonlinear power characteristics.So, the identifcation of the functioning point of the fuel stack is quite difcult work.In addition, the available source voltage is very low which is not acceptable for industrial as well as local consumer applications.So, the hybrid power point tracking controller is introduced in this work for catching the exact position of the polymer membrane fuel stack network.Te merits of this MPPT controller are its ability in identifying MPP location quickly, fewer iteration requirement for identifying the local MPP position, better 16 International Transactions on Electrical Energy Systems dynamic response of the system, and being most suitable for rapid changes of operating temperature conditions of the fuel stack system.Here, the fuel stack current fow is optimized by utilizing the single switch power DC-DC converter.

Analysis of Overall Proposed System at Static Temperature (325 K).
Te selected supply side capacitors (C l , C j, C k , C h , and C g ) for the design of the power converter are 32.5 μF, 37.99 μF, 58.55 μF, 58.55 μF, and 45.37 μF, respectively.Similarly, the utilized inductor (L q and L w ) values are 260 μH, and 280 μH, respectively.Te source side inductor L q tries to suppress the distortions of fuel stack voltage and power.Te capacitor C l helps stabilize the fuel stack voltage and removes the sudden various source voltages to protect the switch "S."Here, the proposed system is studied at uniform working temperature conditions of the fuel stack which is selected as 325 K. Te converter modeling has been done by utilizing the MOSFET switch and the selected load resistor value is equal to 85 Ω. Te utilized parameters for tracking the fuel stack network MPP are fuel stack power, current, and voltage.Tese variables help linearize the overall system and optimize the duty cycle of the power DC-DC converter.Te available fuel stack supply current and fuel stack voltages are given in Figures 12(a) and 12(b).Te converter's functioning duty signal and its related current, voltage, and powers are shown in Figures 12(c  International Transactions on Electrical Energy Systems small when equated to the other power point tracking controllers.Also, the design and implementation cost is very moderate when compared to the CSVHCFC.International Transactions on Electrical Energy Systems

Experimental Validation of the Proposed Converter
In this section, the proposed power converter is investigated for improving the load power rating of the overall system.Here, the selected power converter network is analyzed by considering the programming-based DC source device which is mentioned in Figure 14.From Figure 14, the 0-12 V transformer is used for reducing the source voltage from a higher level to a lower level to activate the TLP-250 MOSFET driver circuit.Here, the IRF-640 MOSFET device is selected for running the proposed converter under a continuous power supply mode of operation.Te MOS-FET features are high source impedance, less power absorption losses, more thermal stability, and more temperature withstanding ability.From Figure 14, the supply and load voltage and current parameters are determined by selecting the diferential voltage and current meters.Te selected switching device is protected by using the TLP-250 controller from the quick changes in supply voltages.Te switching conditions of the MOSFET are optimized by interfacing with the analog discovery device.Te MOSFET device receives the switching signals from the analog discovery device which is equal to 10%.Te supplied voltage across the gate terminal of the MOSFET is 4.617 V and the current passing through the drain terminal is 1.8942A as mentioned in Figure 15.From Figure 15, the drain voltage of the MOSFET is higher than the current passing through the device low and it attains high value when the switching voltage is low.Te utilized input voltage for this converter is 59.51 V and it is enhanced to 128.46 V with a 10% duty cycle as shown in Figure 16.Te overall setup design parameters are given in Table 7.

. Conclusion
Te overall GWAFC interfaced polymer membrane fuel stack system is developed by using the MATLAB software.
Here, the polymer membrane fuel cell is selected because of its attractive features such as fast response, easy handling, ability to work in low as well as high-temperature conditions, more energy density, and simple construction.However, the fuel stack source voltage is very low which is not suitable for electric vehicle application.So, the new power DC-DC single switch converter is developed to enhance the system voltage to meet the required peak load demand.Te advantages of this converter are a good voltage conversion ratio, fewer power components required for implementation, easy handling, wide output voltage operation, and suitable for all renewable energy system applications.Here, the duty signal of the converter is obtained by using the grey wolf optimization-based fuzzy logic power point tracking controller.In this MPPT controller, the fuzzy membership functions are selected by applying the grey wolf controller.Te merits of this proposed MPPT controller are high fexibility, good dynamic response, easy handling, high robustness, and more reliability.

Figure 2 :
Figure 2: Grey wolf optimized adaptive fuzzy MPPT controller fed WSVPCC for fuel stack application.

Figure 8 :
Figure 8: Working pseudocode of the proposed power point tracking controller.

Figure 9 :Figure 10 :
Figure 9: Overall working structure of the fuzzy membership functions optimized grey wolf MPPT controller.

Figure 11 :
Figure 11: (a) Working of the converter under continuous power supply mode and (b) fuctuated power supply mode.

Figure 13 :
Figure 13: (a) Source current, (b) source voltage, (c) duty cycle, (d) load O/P current, (e) load O/P voltage, and (f ) load O/P power at dynamic temperatures.

Figure 14 :Figure 15 :
Figure 14: Testing of the proposed single switch power converter by using programming DC source.

Figure 16 :Table 7 :
Figure 16: Supplied converter voltage parameters and current parameters at 0.1.

Table 2 :
Te detailed investigation of various power point identifers for PEMFS-fed DC-DC converter.
Te related voltages of the fuel stack are represented as V 0L , V AL , and V CL .Te generated power and voltage curves are illustrated in Figures4(a) and 4(b).Te term T F is the functioning temperature of the fuel stack.Te partial oxygen pressure and hydrogen pressure are identifed as P O2 and P H2 .Te anode humidity vapor pressure and cathode humidity vapor pressure are identifed as RH Ap and RH Cp and its related internal pressures are P Ap and P Cp .Te water pressure and current fowing through the electrode are represented as P sat H 2 O and I S .Te utilized electrode area and empirical coefcients are defned as A, z 1 , z 2 , z 3 , and z 4 .Te design constraints of the utilized fuel stack are shown in Table

Table 3 :
Design variables of selected fuel stack network.
Lw and the voltages appearing across those elements are V Cl , V Cj , V Ck , V Ch , V Cg , V Lq , and V Lw .Finally, the voltages appearing across the switches and diodes are V S , V Dq , V Dw , V De , and V Dt .Te detailed working structure of the converter is shown in Figures10(a), 10(b), and 10(c).Te switching states of the converter are given in Table FET) is used for enhancing the fuel stack supply voltage from one level to another level.Te features of MOSFET are high voltage withstanding ability, more switching speed, less power consumption, very little power dissipation, high input impedance, more power control capability, less driver circuit implementation complexity, and high temperature withstanding ability.Te utilized diodes in this proposed converter circuit are D q , D w , D e , and D t .Similarly, the selected capacitors in the wide output voltage range DC-DC converter are C l , C j, C k , C h , and C g .Te available inductors and resistors in the converter L q , L w , and R n .When the converter starts working, the currents fowing through capacitors and inductors are I Cl , I Cj , I Ck , I Ch , I Cg , I Lq , and I

Table 4 :
Functioning stages of wide input voltage proposed DC-DC converter.
)-12(f ) From Figures 12(a) and 12(b), the available current and voltage parameters of the fuel stack under static temperature conditions by applying the MLNNC, GCOANC, ASCFC, CSVHCFC, and GWAFC are 112.7 A, 39.84 V, 112.82 A, 40.53 V, 112.44 A, 40.76 V, 111.81 A, 42.13 V, 110.32 A, and 43.48 V, respectively.Tese high available currents and lower voltages of the fuel stacks are not useful for any local as well as industrial applications.So, the wide input supply voltage and less voltage stress-based DC-DC proposed converter is integrated with the source network and MPPT controller block for improving the load power, voltage, and current ratings.Te achieved load current, voltage across the converter output, and load power by utilizing the MLNNC, GCOANC, ASCFC, CSVHCFC, and GWAFC MPPT controllers are 8.213 A, 527.32 V, 4330.87W, 8.38 A, 528.72 V, 4430.67 W, 8.412 A, 530.33 V, 4461.13W, 8.672 A, 534.8 V, 4637.78W, 8.79 A, 535.99 V, and 4711.35W, respectively.At static functioning temperature conditions of the fuel stack, the GWAFC-fed fuel stack supply voltage stabilizing time is 0.015 sec which is very

Table 5 :
Analysis of various categories of power electronics converters for renewable energy systems.

Table 6 :
Detailed analysis of various categories of power point tracking controllers at diferent operating temperature conditions of the fuel stack.