The power produced in a photovoltaic (PV) system is highly dependent on meteorological conditions and the features of the connected load. Therefore, maximum power point tracking (MPPT) methods are crucial to optimize the power delivered. An MPPT method needs a DC-DC converter for its implementation. The proper selection of both the MPPT technique and the power converter for a given scenario is one of the main challenges since they directly influence the overall efficiency of the PV system. This paper presents an exhaustive study of the performance of four step-down/step-up DC-DC converter topologies: Buck-Boost, SEPIC, Zeta and Cuk, using three of the most commonly implemented MPPT techniques: incremental conductance (IncCond), perturb and observe (P&O) and fuzzy logic controller (FLC). Unlike other works available in the literature, this study compares and discusses the performance of each MPPT/converter combination in terms of settling time and tracking efficiency of MPPT algorithms, and the conversion efficiency of power converters. Furthermore, this work jointly considers the effects of incident radiation variations, the temperature of the PV panel and the connected load. The main contribution of this work, other than selecting the best combination of converter and MPPT strategy applied to typical PV systems with DC-DC power converters, is to formulate a methodology of analysis to support the design of efficient PV systems. The results obtained from simulations performed in Simulink/MATLAB show that the FLC/Cuk set consistently achieved the highest levels of efficiency, and the FLC/Zeta combination presents the best transient behavior. The findings can be used as a valuable reference for the decision to implement a particular MPPT/converter configuration among those included in this study.

This paper presents the design and implementation of a digital control strategy for a Buck converter, used as a solar charger of valve-regulated lead acid (VRLA) batteries. The control system consists of two fuzzy logic controllers (FLCs), which adjust the appropriate increment of the converter duty cycle based on battery state of charge according to a three-stage charging scheme. One FLC works as a maximum power point tracker (FLC-MPPT), while the other regulates the battery voltage (FLC-VR). This approach of using two different set of membership functions overcomes the limitations of the battery chargers with a single control function, where the voltage supplied to the battery is either not constant due to the operation of the MPPT algorithm (possibly damaging the battery) or is constant due to the operation of the voltage control (hence, MPP cannot be achieved). In this way, the proposed control approach has the advantage of extracting the maximum energy of the PV panel, preventing battery damage caused by variable MPPT voltage, thereby extending the battery’s lifetime. Moreover, it allows overcoming of the drawbacks of the conventional solar chargers, which become slow or inaccurate during abrupt changes in weather conditions. The strategy is developed to be implemented in a low-cost AT91SAM3X8E Arduino Due microcontroller. Simulations by MATLAB/Simulink and experimental results from hardware implementation are provided and discussed, which validate the reliability and robustness of the control strategy.

This paper presents a methodology for choosing the most suitable Maximum Power Point Tracking - MPPT for charging the batteries of an autonomous photovoltaic energy supply system. Experimental results are provided.

In photovoltaic (PV) generation systems, the energy produced is limited by the low efficiency of the solar panels, the variability of weather conditions, and the characteristics of the load connected, so the use of maximum power point tracking (MPPT) methods is essential to maximize the power supplied. Implementing an MPPT requires a power converter as the interface between the PV array and the load, so the converter's behavior is also an important factor to be considered in the overall performance of a PV system. Several MPPT techniques have been proposed over the years, but little literature is still available when required to be compared to the combined performance of different MPPT/converter sets. In this context, the present work presents a comparative study of the performance of three MPPT techniques: constant voltage (CV), perturb and observe (P&O), and incremental conductance (IncCond), acting on two different topologies of DC-DC power converters: Buck and Buck-Boost. Each combination is analyzed considering its transient response and steady-state average efficiency. The study was carried out based on simulations in Matlab/Simulink environment. To obtain more realistic conditions, a model for the commercial PV module Kyocera KC85TS was developed. Results obtained from the PV system operating under various radiation and temperature conditions are compared and discussed, which show that the CV/Buck-Boost combination showed the best transient behavior and that the IncCond/Buck combination had the highest steady-state efficiency.

Battery charging systems are crucial for energy storage in off-grid photovoltaic (PV) installations. Since the power generated by a PV panel is conditioned by climatic conditions and load characteristics, a maximum power point tracking (MPPT) technique is required to maximize PV power and accelerate battery charging. On the other hand, a battery must be carefully charged, ensuring that its charging current and voltage limits are not exceeded, thereby preventing premature degradation. However, the voltage generated by the PV panel during MPPT operation fluctuates, which can harm the battery, particularly during periods of intense radiation when overvoltages are likely to occur. To address these issues, the design and construction of an enhanced solar battery charger utilizing a single-ended primary-inductor converter (SEPIC) and soft computing (SC)-based control is presented. A control strategy is employed that integrates voltage stabilization and MPPT functions through two dedicated fuzzy logic controllers (FLCs), which manage battery charging using a three-mode scheme: MPPT, Absorption, and Float. This approach optimizes available PV power while guaranteeing fast and safe battery charging. The developed charger leverages the SEPIC’s notable features for PV applications, including a wide input voltage range, minimal input current ripple, and an easy-to-drive switch. Moreover, unlike most PV charger control strategies in the literature that combine improved traditional MPPT methods with classical proportional integral (PI)-based control loops, the proposed control adopts a fully SC-based strategy, effectively addressing common drawbacks of conventional methods, such as slowness and inaccuracy during sudden atmospheric fluctuations. Simulations in MATLAB/Simulink compared the FLCs’ performance with conventional methods (P&O, IncCond, and PID). Additionally, a low-power hardware prototype using an Arduino Due microcontroller was built to evaluate the battery charger’s behavior under real weather conditions. The simulated and experimental results both demonstrate the robustness and effectiveness of the solar charger.