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Taking into account the limited capability of proton exchange membrane fuel cells (PEMFCs) to produce energy, it is mandatory to provide solutions, in which an efficient power produced by PEMFCs can be attained. The maximum power point tracker (MPPT) plays a considerable role in the performance improvement of the PEMFCs. Conventional MPPT algorithms showed good performances due to their simplicity and easy implementation. However, oscillations around the maximum power point and inefficiency in the case of rapid change in operating conditions are their main drawbacks. To this end, a new MPPT scheme based on a current reference estimator is presented. The main goal of this work is to keep the PEMFCs functioning at an efficient power point. This goal is achieved using the backstepping technique, which drives the DC–DC boost converter inserted between the PEMFC and the load. The stability of the proposed algorithm is demonstrated by means of Lyapunov analysis. To verify the ability of the proposed method, an extensive simulation test is executed in a Matlab–Simulink TM environment. Compared with the well-known proportional–integral (PI) controller, results indicate that the proposed backstepping technique offers rapid and adequate converging to the operating power point.

Proton exchange membrane fuel cell (PEMFC) topology is becoming one of the most reliable and promising alternative resource of energy for a wide range of applications. However, efficiency improvement and lifespan extension are needed to overcome the limited market of fuel cell technologies. In this paper, an efficient approach based on a super-twising algorithm (STA) is proposed for the PEMFC system. The control objective is to lengthen the fuel cell lifetime by improving its power quality, as well as to keep the system operating at an optimal and efficient power point. The algorithm adjusts the PEMFC operating point to the optimum power by tuning the duty cycle of the boost converter. The closed-loop system includes the Heliocentris hy-ExpertTM PEMFC, DC–DC boost converter, DSPACE DS1104, dedicated PC, and a programmable electronic load. The practical implementation of the proposed STA on a hardware setup is performed using a dSPACE real-time digital control platform. The data acquisition and the control system are conducted together with the dSPACE 1104 controller board. To demonstrate the performance of the proposed algorithm, experimental results are compared with 1-order sliding mode control (SMC) under different load resistance. The obtained results demonstrate the validity of the proposed control scheme by ensuring at least 72% of the maximum power produced by PEMFC. In addition, it is proven that the STA ensures all the fundamental properties of the 1-order SMC, as well as providing chattering reduction of 91%, which will ameliorate as a consequence the fuel cell lifetime.

In this article a new Transformer and Switched Capacitor-based Boost Converter (T & SC-BC) is proposed for high-voltage/low-current renewable energy applications. The proposed T & SC-BC is an original extension for DC-DC boost converter which is designed by utilizing a transformer and switched capacitor (T & SC). Photovoltaic (PV) energy is a fast emergent segment among the renewable energy systems. The proposed T & SC-BC combines the features of the conventional boost converter and T & SC to achieve a high voltage conversion ratio. A Maximum Power Point Tracking (MPPT) controller is compulsory and necessary in a PV system to extract maximum power. Thus, a photovoltaic MPPT control mechanism also articulated for the proposed T & SC-BC. The voltage conversion ratio (Vo/Vin) of proposed converter is (1 + k)/(1 − D) where, k is the turns ratio of the transformer and D is the duty cycle (thus, the converter provides 9.26, 13.88, 50/3 voltage conversion ratios at 78.4 duty cycle with k = 1, 2, 2.6, respectively). The conspicuous features of proposed T & SC-BC are: (i) a high voltage conversion ratio (Vo/Vin); (ii) continuous input current (Iin); (iii) single switch topology; (iv) single input source; (v) low drain to source voltage (VDS) rating of control switch; (vi) a single inductor and a single untapped transformer are used. Moreover, the proposed T & SC-BC topology was compared with recently addressed DC-DC converters in terms of number of components, cost, voltage conversion ratio, ripples, efficiency and power range. Simulation and experimental results are provided which validate the functionality, design and concept of the proposed approach.

This paper provides an in-depth analysis of photovoltaic (PV) system control within the MATLAB/Simulink environment, focusing on optimizing Maximum Power Point Tracking (MPPT) algorithms for enhanced efficiency under dynamic conditions. While conventional algorithms are widely used, their performance is limited under fluctuating conditions. To address this, we propose a novel hybrid approach combining Incremental Conductance with Fuzzy Logic Control (FLC), utilizing two innovative input variables: the sum of Conductance and Incremental Conductance (SInC) and its rate of change (CSI). The performance of the proposed algorithm, in comparison to other hybrid FLC methods, is evaluated through simulations using a boost converter under dynamic conditions, including abrupt irradiance changes and load variations. The results demonstrate that the proposed hybrid algorithm achieves superior performance, with an average MPPT efficiency of 97.7%, a convergence time of 53.5 ms, and an RMS of 97.8%, outperforming both conventional and other hybrid techniques. This work advances PV system control by providing a robust and adaptive solution for maximizing power extraction under diverse operating conditions.

Integration of maximum power point tracking (MPPT) with photovoltaic (PV) systems is a necessity to track and deliver maximum power available. This paper focuses on comparing the tracking efficiencies of Perturb and Observation method (P&O), Incremental Conductance (IC) and Fuzzy-Logic System based MPPT technique. Change in atmospheric condition such as varying irradiance causes the output power to continuously vary over time. IC as well as P&O based MPPT techniques exhibit poor dynamic responses and so operating points keeps fluctuating. Variation in solar irradiance over a day at constant temperature is given as input to the solar PV module. The algorithm used here implements tracking over the period of a day. All the simulation study are implemented with the use of MATLAB/SIMULINK.

This paper investigates the critical role of Direct Current to Direct Current (DC-DC) converters in satellite power systems, emphasizing the need for efficient and reliable energy conversion under dynamic space conditions. A novel Fuzzy Model Control (FMC) strategy is proposed for a quasi-Trans-Z-Source DC-DC boost converter, addressing the inherent challenges of nonlinear power dynamics and multiport energy flow management in space applications. The proposed approach enhances mode transitions, improves solar energy extraction from photovoltaic (PV) panels, and ensures stable voltage regulation under fluctuating load conditions. A comprehensive theoretical analysis of the circuit topology highlights its advantages over conventional boost converters, including continuous input current, higher voltage gain, and reduced passive component stress. Simulation and experimental results demonstrate that the proposed FMC achieves ± 1.5% voltage regulation accuracy, reduces current ripple by 28%, and improves transient response time by 35% compared to a conventional Proportional-Integral (PI) controller. The overall system efficiency reaches 94.7% under nominal conditions. Furthermore, the control strategy effectively manages constraints such as duty cycle limits and dynamic disturbances, confirming its real-time applicability for spaceborne platforms such as nanosatellites and CubeSats.

PV systems require a dc–dc converter to operate at the maximum power point (MPP). However, switching based operation of these converters causes ripple current. This ripple current causes a voltage ripple due to the I-V characteristics of the PV panel. Both current and voltage ripple lead to power ripple and reduce the average energy extracted from the PV system. In this study, a two-stage boost converter (PTS-BC) topology is designed. The first stage, configured as an interleaved TP-BC fixed at , drastically suppresses the input current ripple, while the second stage, operating as a conventional SP-BC, regulates the output voltage. The key novelty of this architecture stems from the use of dedicated stages for ripple cancellation and voltage regulation, thereby ensuring ripple-free PV input current across the entire duty range without requiring bulky input capacitors. The design has been validated through simulations and experimental studies performed on a 450 W PV prototype system. Within the examined operating range, duty cycle ( D ) changes from 10% to 80%, the PTS-BC provides a 12% and a 17% ripple reduction in input current ripple and power ripple, respectively, compared to conventional converters such as single phase boost converter (SP-BC), two phase boost converter (TP-BC), etc. In addition, PTS-BC requires significantly lower D than SP-BC and TP-BC for the same output voltage, thereby reducing conduction losses and voltage stress on switching devices in a two-stage configuration. The PTS-BC reaches a peak efficiency of approximately 98%, representing improvements of about 0.7% and 1.6% over the TP-BC and SP-BC, respectively. These results confirm that the proposed topology offers superior energy conversion performance and makes it a strong candidate for high-performance PV systems that require low input ripple and high efficiency.

The conventional DC-DC architecture is often used in photovoltaic systems, with control based on incremental conductance-based maximum power point tracking (MPPT-IC) algorithms. Despite its simplicity and ability to ensure voltage balance across the output capacitors, this architecture suffers several drawbacks. These drawbacks cause undesirable problems such as high power ripples, overshoot, and limited dynamic response. Therefore, this paper proposes a three-level quadratic DC-DC boost converter as a suitable solution to replace conventional inverters in photovoltaic systems, while combined with an advanced MPPT method. The new approach is MPPT based on NARX neural network (NARAX-NN) algorithms. This proposed strategy is designed for high accuracy, robustness, and fast dynamic response compared to the MPPT-IC strategy. In this work, the MPPT-NARX-NN strategy of a three-level quadratic DC-DC boost converter is compared with several different strategies (MPPT-IC, MPPT based on type 1 fuzzy logic (MPPT-T1FL), and MPPT based on type 2 fuzzy logic (MPPT-T2FL)). This comparison is performed using MATLAB under different operating conditions. Simulation results indicate that the MPPT-NARX-NN approach significantly improves the operational performance of a three-level quadratic DC-DC boost converter compared to other strategies, increasing the reliability and deployment of photovoltaic systems. The numerical results show that the MPPT-NARX-NN strategy improves the rise time by 96.43, 97.34, and 94.50% compared to MPPT-IC, MPPT-T1FL, and MPPT-T2FL, respectively. Also, the settling time is improved by 50, 66.66, and 6.66% compared to MPPT-IC, MPPT-T1FL, and MPPT-T2FL, respectively. Furthermore, the strategy increases the average tracking efficiency (%) by 3.86 and 1.12% for MPPT-IC and MPPT-T1FL, respectively. These results highlight the effectiveness of the three-level quadratic DC-DC boost converter based on the MPPT-NARX-NN strategy in extracting energy, increasing performance and flexibility, and improving system reliability, making solar PV systems more efficient and a promising and indispensable solution.

Polymer electrolyte membrane (PEM) fuel cells demonstrate potential as a comprehensive and general alternative to fossil fuel. They are also considered to be the energy source of the twenty-first century. However, fuel cell systems have non-linear output characteristics because of their input variations, which causes a significant loss in the overall system output. Thus, aiming to optimize their outputs, fuel cells are usually coupled with a controlled electronic actuator (DC-DC boost converter) that offers highly regulated output voltage. High-order sliding mode (HOSM) control has been effectively used for power electronic converters due to its high tracking accuracy, design simplicity, and robustness. Therefore, this paper proposes a novel maximum power point tracking (MPPT) method based on a combination of reference current estimator (RCE) and high-order prescribed convergence law (HO-PCL) for a PEM fuel cell power system. The proposed MPPT method is implemented practically on a hardware 360W FC-42/HLC evaluation kit. The obtained experimental results demonstrate the success of the proposed method in extracting the maximum power from the fuel cell with high tracking performance.

In this paper, a metaheuristic optimized multilayer feed‐forward artificial neural network (ANN) controller is proposed to extract the maximum power from available solar energy for a three-phase shunt active power filter (APF) grid connected photovoltaic (PV) system supplying an arc welding machine. Firstly, in order to improve the maximum power point (MPP) delivered by PV arrays and to overcome the drawbacks in the conventional MPPT method under irradiation variation, a hybrid MPPT controller is designed, in which the input parameters include the PV array voltage and current, and the output parameter is the duty cycle of the DC/DC boost converter. The proposed approach abbreviated as ANN-ACO MPPT controller is based on an ant colony optimization (ACO) algorithm which is useful to train the developed ANN and to evolve the connection weights and biases to get the optimal values of duty cycle converter corresponding to the MPP of a PV array. Secondly, aiming to meet the various grid requirements such as power quality improvement, distortion free signals etc., a three-phase shunt APF is utilized, and a direct power control algorithm is designed for distributing the solar energy between the DC-link capacitor, arc welding machine and the AC grid. Finally, the performance of proposed control system is confirmed by simulation tests on a 12.2 kW PV system. Both simulation and experimental results have demonstrated that the deigned ANN-ACO MPPT controller can provide a better MPP tracking with a faster speed and a high robustness with a minimal steady-state oscillation than those obtained with the conventional INC method. Also, with the use of a three-phase shunt APF, all the power fluctuations from the arc welding machine disturbances are damped out and the output active and reactive power become controllable.