Battery Voltage Research Articles

Mode decomposed passivity-based speed control of DC drive with bidirectional Zeta-SEPIC DC-DC converter for light electric vehicles

Currently, light electric vehicles are rapidly developing in various kinds. To power these vehicles with batteries, the simplest electric drive system is a DC motor controlled by a DC-DC converter. This work utilizes a bidirectional Zeta-SEPIC DC-DC converter with an integrated DC motor. This implementation enables control of motor speed and torque in traction and regenerative braking modes. Additionally, it allows for the use of a lower voltage battery compared to the motor's rated voltage, reducing battery weight and increasing safety. In this work, a decomposition approach is applied. Two separate port-controlled Hamiltonian subsystems are obtained to adjust the motor angular velocity in the traction (Zeta) and braking (SEPIC) modes of the DC-DC converter. The Passivity-Based Control (PBC) method is used to synthesize the drive control subsystems in these modes. This method is based on the energy laws of processes in systems and provides asymptotic stability of nonlinear systems, in this case, two fourth-order subsystems for speed control. Two third-order current control subsystems synthesized by the PBC were used to limit the motor current at a given level. The synthesis resulted in sets of possible structures of control influence formers (CIFs) for all PBC subsystems using Zeta and SEPIC DC-DC converters. The study analyzed the operation of the obtained structures of the CIFs, selected the most effective ones, and determined the laws of adaptation of their parameters to the value of the motor angular velocity through computer simulation in Matlab/Simulink. The results of the simulation showed that the drive operated well in both static and dynamic modes.

Design of passive voltage balancer system for lead acid battery

The use of rechargeable batteries for electrical energy storage requires a voltage balancing system. The voltage balancing system requires monitoring in the use of rechargeable batteries so that they can be utilized properly and can improve the electrical energy storage system. In this research, a monitored lead acid battery voltage balancing system was designed so that the management of the battery voltage balance level and the storage of electrical energy in rechargeable batteries can be stored and used optimally. In this research a series of lead acid battery voltage detection and power dissipation circuits were designed. The power dissipation circuit uses the controlled shunt resistor method which is used when the voltage of the lead acid battery being charged exceeds the maximum voltage. This method is easy to implement and can display the value of the lead acid battery voltage and other parameters, so that it can be monitored by the user. The results obtained show that the average voltage error for batteries 1 and 2 is 0.09% and 0.3% respectively. The power dissipation circuit can dissipate lead acid battery power above the reference voltage VREF=±7 V, with a balanced voltage of 6.8 V at 140 minutes and 160 minutes.

Enhancing aqueous Zn-Mn battery performance using Na+ ion conducting ceramic membrane

The low cell voltage and capacity of conventional Zn-MnO2 batteries often result in limited energy density. In this study, we assembled a Zn-MnO2 battery based on the acid-alkaline electrolyte decoupled concept and reversible MnO2/Mn2+ deposition/dissolution chemistry to increase the cell voltage and capacity. We used a Na+ ion conducting NASICON ceramic membrane in the battery to decouple the acid and alkaline electrolytes effectively. The assembled Zn-MnO2 battery demonstrated a cell voltage of 2.43 V and a coulombic efficiency (CE) of 90% at a current density of 0.2 mA/cm2. It also exhibited excellent rechargeability with continuous charge and discharge cycles. After 100 cycles, the battery exhibits a capacity of 0.36 mAh with a maximum CE of 93.42%. A study on the battery’s self-discharge performance showed that a maximum of 71% capacity could be recovered from the charged battery after 24 hours of rest. Finally, we fabricated a pouch-type acid-alkaline electrolyte decoupled Zn-MnO2 battery and examined its feasibility.

Research on the design and balancing strategy with multi-section lithium battery protection IC

This study uses 0.5um BCD technology to design a multi section lithium battery protection chip suitable for small mobile electronic devices such as Bluetooth earphones and smart bracelets. By providing a complete system structure diagram, the principles and design methods of several key circuits in the chip were introduced. This chip can effectively monitor the voltage of lithium batteries, take protective measures against abnormal situations such as overcharging, discharging, and overcurrent, and has a balancing module with dynamic power consumption management function. The balancing module adopts a passive balancing architecture, and the balancing algorithm used is an average based voltage detection algorithm. Using this algorithm can make the balancing system structure simple and reduce system power consumption, reduce the differences between batteries within the group, and thus improve the uniformity of the battery pack. The overcharging detection accuracy of the designed chip is ±25mV, the overcharging detection accuracy is 50mV, and the static working current of the chip is 7uA.

Design and testing of a high-performance solar LED streetlight

This paper presents the development and validation of a high-performance solarpowered charging streetlight. Our controller incorporates various charging modes, including MPPT charging, constant current charging, and constant voltage charging, and the controller can automatically change the charging mode based on the battery level. The streetlight can achieve brightness adjustment through PWM adjustment. The controller turns off the streetlights once the battery voltage reaches the over-discharge protection voltage. However, turning off the streetlights inevitably results in a voltage rebound above the over-discharge protection voltage. Consequently, the streetlights enter a cycling pattern of illumination and extinguishment. We have addressed this issue by incorporating a voltage rise threshold in the controller program, effectively preventing the streetlights from cycling between illumination and extinguishment. The MCU (Micro Controller Unit) can output multiple sets of PWM waves, where each set can control the on/off state of an LED light group. Combining multiple LED groups enables the driving and control of high-power LED street lights. We designed and constructed two solar-powered LED lighting systems to demonstrate the practicality of our approach. Extensive long-term outdoor field tests validate the robust performance of our control system.

A Framework for Managing and Monitoring the Battery Health Parameters of Rental Electric Vehicles

The rapid adoption of electric vehicles (EVs) has paved the way for a sustainable transportation future. However, ensuring the safety and reliability of rental EVs, particularly regarding their battery health, presents unique challenges. This paper proposes a comprehensive framework for monitoring and managing rental EV batteries, encompassing real-time data acquisition, advanced analytics, and proactive maintenance strategies. By implementing such a framework, rental EV providers can optimize battery performance, extend lifespan, and guarantee the safety and convenience of their customers. The surging popularity of rental electric vehicles (EVs) poses unique challenges in ensuring their safety and reliability, particularly concerning battery health. This paper presents a comprehensive framework for proactive monitoring and management of rental EV batteries. The framework encompasses real-time data acquisition of key battery parameters, advanced analytics for predicting degradation and identifying influencing factors, and data-driven maintenance strategies like cell balancing and optimized charging. Implementing this framework empowers rental EV providers to maximize battery lifespan, enhance customer experience, and contribute to a sustainable transportation future. This leads to improving the factors and the process to monitor the battery health parameters of the rental electric vehicle. By adopting the various monitoring algorithms to measure and monitor the battery health parameters such as State of Charge, State of Health, battery voltage, balancing current, and temperature are monitored by the lifespan of the battery is extended and the safety and reliability of the battery is ensured by monitoring the temperature.

Identification of Flowing Electrolyte Lead Acid Battery Operating Voltage

Identification of the operating voltage of a lead acid battery with 30% sulfuric acid electrolyte flow has been carried out. The battery consists of six cells with Pb and PbO as electrodes. The battery is equipped with a 1200 ml reservoir system to collect electrolyte and supply electrolyte to each cell. Each cell has electrolyte inlets and outlets at the top and bottom that circulate through each cell using a peristaltic pump. The battery prototype built was tested for five charge-discharge cycles with a constant current of 2 A for the charging process and 0.5 A for the discharging process using Turnigy Accucell. During the charge-discharge cycle test, monitoring and recording of voltage data is carried out using a Laptop PC. Data processing uses WebplotDigitizer and Microsoft Excel for data graphing. The results are analyzed and used to identify the operating voltage of the battery by taking the average voltage over five charge-discharge cycles. The average voltage is 13.98 V for the charging process and 12.11 V for the discharging process. Six-cell battery with full capacity works at a voltage range of 12.11-13.98 V. In the process of charging with a constant current of 2 A, the battery takes an average of 7.49 hours. So, the charging capacity can be estimated at 14,980 mAh. Whereas the battery discharge process takes an average of 11 hours with a constant current of 0.5 A to a voltage drop of 10.81 V. The resulting capacity of the discharged battery is 5500 mAh.
 Keywords: flowing electrolyte, lead acid battery, operating voltage

Composition-tunable Co3-xFexSe4 as efficient electrocatalysts for the oxygen evolution reaction

In the oxygen evolution reaction (OER), the selection of highly active catalysts is fundamental to curtail overpotentials and to enhance the typically sluggish kinetics characteristic of the reaction. Cobalt selenide (Co3Se4), with its optimally configured electronic structure of cobalt ions, is consistently hailed as a prospective electrocatalyst for the OER, making it highly efficient in facilitating the reaction.Despite the persistent challenges of the exposure of catalytic active sites and the limited electronic conductivity, our study unveils a breakthrough solution. We introduce a highly efficient Fe-doped Co3Se4 electrocatalyst for the OER, addressing these long-standing issues, and it has desirable compositional flexibility, formed Co3-xFexSe4 (0 ≤ x ≤ 3) selenides, by introducing Fe doping, the electronic structure of Co3Se4 is effectively regulated, resulting in a remarkable reduction in the overpotential of the OER under alkaline conditions.Simultaneously, the introduction of Fe induces the formation of highly active Co–O sites, ultimately establishing a highly active and stable catalytic surface for oxygen evolution. Consequently, this leads to a significant improvement in the activity of the oxygen evolution reaction (OER). The synthesized Co2.5Fe0.5Se4 catalyst exhibits lower overpotential (η10 = 220 mV) and Tafel slope (41.2 mV dec−1), which is superior to the general commercial RuO2 benchmark. In addition, Co2.5Fe0.5Se4 also exhibits exceptional structural integrity and sustained operational longevity, with a durability of up to 280 h at 100 mA cmgeo−2. Impressively, the Pt/C∥Co2.5Fe0.5Se4 water electrolysis cell only requires a battery voltage of 1.67 V to provide a current density of 100 mA cmgeo−2 and has excellent long-term stability.

A Bayesian optimized machine learning approach for accurate state of charge estimation of lithium ion batteries used for electric vehicle application

In recent times, battery technology used in electric vehicles has drawn numerous researchers' attention. Monitoring the battery condition, particularly the State of charge, is required to ensure the battery's safe and reliable performance. Despite the fact that many SOC estimation methods have been proposed, further research is necessary to identify an approach that adapts versatile lithium-ion battery chemistries. In the recent study it has been demonstrated that Machine Learning approaches have better prediction accuracy compared to conventional methods. To maximize the performance of Machine learning models, it is imperative to select the optimal hyperparameters and employ appropriate input parameters. At present, researchers employ, established heuristics methods to select hyperparameters, which may involve manual tuning or exhaustive search techniques such as random search and grid search. These techniques make the models less accurate and inefficient. In this paper, a systematic, automated process for selecting hyperparameters with a Bayesian optimization algorithm is proposed. In addition, along with the battery parameters (voltage, current and temperature), vehicle velocity, road condition, motor characteristics and environmental conditions are used as the input parameters for accurate SOC prediction. The highly correlated input features are selected through the MRMR algorithm. The performance of six ML algorithms, namely SVM, ANN, GPR, Ensembler, linear regression and Decision Tree, is tested and validated with and without hyperparameter tuning for different data sets. The experimental results demonstrate that the hyperparameter-tuned model outperforms the standard model in estimating the State of charge (SOC). In addition, the model's estimation error is <1 % across a range of vehicle velocity, road condition, motor torque, battery voltage, current, and temperature.

Lithium-ion battery state of health prognostication employing multi-model fusion approach based on image coding of charging voltage and temperature data

The employment of readily obtainable parameters, including voltage and temperature, derived from the battery management system facilitates the real-time evaluation of lithium-ion batteries health status. However, the complex aging mechanisms and noise interference inherent in lithium-ion batteries present substantial challenges to accurate estimation. Hence, this research proposes a multi-model fusion approach utilizing Gramian Angular Field encoding to accurately predict the health status of lithium-ion batteries. Battery voltage and temperature data are acquired through system aging experiments. The Gramian Angular Field-based image encoding transforms these data into images, accentuating the subtle characteristics of the data and thereby enhancing its recognizability by neural networks. Subsequently, two-dimensional Convolutional Neural Networks are employed to extract features from the images, followed by one-dimensional Convolutional Neural Networks to reduce the dimensions of the feature matrix. The battery health status is then predicted utilizing Long Short-term Memory Networks. The culmination is the evaluation of the model performance through the application of quantitative error metrics. The study results show that the method can pinpoint the prediction error to within 2%, significantly improving accuracy over traditional prediction methods. It proves the great potential of direct data, such as voltage and temperature, in predicting battery health.

Comparative Analysis for Off-Board Vienna Rectifier Electric Vehicle Charger Controlled by VOC and DPC Techniques

Electric vehicle charging stations are generally composed of AC-to-DC and DC-to-DC converters. Many topologies of converters, used for both on-board and off-board EV chargers, have been proposed by the researchers. The off-board Vienna rectifier EV charger is the focus of our work. This EV charger should be controlled for adjusting the system outputs at desired references. Among several control methods existing in the literature, the voltage-oriented and direct power control techniques are selected to control the Vienna rectifier. The aim of this paper is to present a comparative analysis for an Off-board Vienna rectifier controlled individually by the previous mentioned control techniques in order to charge the battery of an electric vehicle from the national grid. A three constant current values of 60A, 80A, and 100A, are imposed to the EV battery as reference currents using PI controllers. The comparison is based on the waveforms of three-phase grid voltages and currents, battery voltages, state of the charge of the battery, and the elapsed time of simulation. The total harmonic distortion (THD) of one phase of the input current at the case of 100A is measured using the fast Fourier transform tool of Matlab/Simulink software which employed for modeling and performing the simulation.

Long-cycling and High-voltage Solid State Lithium Metal Batteries Enabled by Fluorinated and Crosslinked Polyether Electrolytes.

Solid-state lithium metal batteries (LMBs), constructed through the in situ fabrication of polymer electrolytes, are considered a critical strategy for the next-generation battery systems with high energy density and enhanced safety. However, the constrained oxidation stability of polymers, such as the extensively utilized polyethers, limits their applications in high-voltage batteries and further energy density improvements. Herein, an in situ fabricated fluorinated and crosslinked polyether-based gel polymer electrolyte, FGPE, is presented, exhibiting a high oxidation potential (5.1 V). The fluorinated polyether significantly improves compatibility with both lithium metal and high-voltage cathode, attributed to the electron-withdrawing -CF3 group and the generated LiF-rich electrolyte/electrode interphase. Consequently, the solid-state Li||LiNi0.6Co0.2Mn0.2O2 batteries employing FGPE demonstrate exceptional cycling performances of 1000 cycles with 78 % retention, representing one of the best results ever reported for polymer electrolytes. Moreover, FGPE enables batteries to operate at 4.7 V, realizing the highest operating voltage of polyether-based batteries to date. Notably, our designed in situ FGPE provides the solid-state batteries with exceptional cycling stability even at practical conditions, including high cathode loading (21 mg cm-2) and industry-level 18650-type cylindrical cells (1.3 Ah, 500 cycles). This work provides critical insights into the development of oxidation-stable polymer electrolytes and the advancement of practical high-voltage LMBs.

PID Temperature Control of Baby Incubator Transport Battery Efficiency

Transport baby incubators are used to keep babies warm and safe while in transport using battery voltage sources or DC electricity, which are portable and can be used without getting a supply of electrical energy. The problem that often occurs with this tool is the limited battery power system. causes a risk to the infant in the event of power failure or battery exhaustion. We aim to evaluate the battery efficiency of Baby Incubator Transport using a PID temperature controller. The evaluation is done by comparing and analyzing the battery voltage of the device to the standard device, as well as considering the setting temperature and duration of use of the device so that it can provide convenience in evacuating babies in an emergency. The tool uses the PID method to control temperature and maximize battery power. In this design, researchers only look at the efficiency of the PID method on temperature control and the battery to be used. This module will have a display that will display the battery voltage value, battery voltage percentage, skin temperature, chamber temperature, humidity, and temperature control that has been selected in the form of a graph. Compared with the digital multimeter measuring instrument. From the results of data collection, it can be concluded that the PID method has a faster rise time to reach the setting temperature, while the fuzzy method has a longer rise time to reach the setting temperature. However, the PID method requires more battery power than the Fuzzy method. The measurement results between the display and the measuring device have a difference of 3.1% at 34°C, at 35°C it is 3.9%, and at 36°C it is 4.7%. The biggest error is at a temperature of 36ºC, the smallest is at a temperature of 34ºC. Based on the results of the observation analysis of battery power consumption, it is found that the smaller the battery energy, the smaller the current issued, as well as the voltage issued. But if the load is large, the current is inversely proportional to the center, the battery voltage decreases while the current increases.

Fuzzy Logic Temperature Control on Baby Incubator Transport Battery Efficiency

Baby incubator transport is a life support tool used to maintain the body temperature of newborn babies during transportation from one place to another, such as from a hospital to an intensive care center with more complete facilities. The problem that often occurs in transport incubators is limitations in the power system. Baby incubator transport uses a battery as the main power source. However, the limited battery power can cause risks to the baby if there is a problem with the power system or the battery runs out. This study aims to monitor the remaining battery voltage in a transport baby incubator that uses fuzzy logic to control the temperature inside and will compare with the performance of PID control. This research uses a fuzzy logic method to control temperature and maximize battery power. In this study, researchers only looked at the efficiency of the fuzzy logic method in temperature control and the battery that will be used. The research uses a display that will display the battery voltage and current values, battery power percentage, skin temperature, chamber temperature, humidity and the selected temperature control. The module that has been made is then compared with the Digital Multimeter measuring instrument. From the results of data collection, the measurement of the remaining battery voltage between the sensor reading and the measuring instrument has a difference where at a temperature of 34 ºC it is 2.1%, at a temperature of 35 ºC it is 2% and at a temperature of 36 ºC it is 3.9%. When compared to research using PID control, fuzzy logic takes longer to reach the desired temperature and demands more battery power when compared to PID control.

Arduino Controlled Battery Charger

In this project we will learn to use an Arduino and an attached charging circuit to control the charging of NiMH rechargeable batteries. Rechargeable batteries are a great way to power your portable electronics. They can save a lot of money when properly recycled. But it's much more fun to build one for yourself. So, here is how to build an Arduino controlled battery charger. Each type of battery uses a different chemical process to make it work. As a result, each type of battery needs to be charged differently. We are going to focus on the most common type of AA rechargeable battery, Nickel-Metal Hydride (NiMH). Battery Charger is designed for charging 12V sealed lead-acid batteries. The designed device consists Charging unit , Battery Housing Unit (Drawers) with their respective batteries insider the Drawers which can be charged simultaneously. Each Battery Housing Units provided with its driver circuit, transformer and power supply module. Power supply module is designed with thermal analysis &amp; optimization and protection for EMI/EMC issues. Once the battery is connected to the circuit, it then displays battery charging condition. Battery charging level is displayed by LEDS and LCD is used to indicate the keyed input battery voltage and current through keypad 4X4 manually. Battery type and remaining charging time are displayed on screen during charging on LCD display. PIC 18f452 Microcontroller continuously monitors the battery condition and displays it on LCD. Charging stops when battery is fully charged, audio alarm is indicated with a buzzer and finally the ejection of the drawer tray for removal of the charged battery. This is advantageous as it prevents the battery from damage and over charging.

Interface Engineering Overall Seawater Splitting of Self-Supporting CeOx@NiCo2O4 Arrays.

Exploring advanced electrocatalysts for overall seawater splitting is of great significance for large-scale green hydrogen production in which interface engineering has been considered as an effective strategy to enhance the intrinsic activities of the electrocatalysts. In this work, CeOx-modified NiCo2O4 nanoneedle arrays are designed and constructed in situ grown on Ni foam (NF) through a facile two-step synthesis method. Density functional theory calculations reveal that the strong interaction between CeOx and NiCo2O4 can regulate the electronic states of metal surfaces and optimize the electronic structures of the materials, essentially improving the oxygen evolution reaction (OER) and hydrogen evolution reaction (HER) properties. Specifically, in alkaline electrolytes, CeOx@NiCo2O4/NF exhibits superior electrocatalytic activities and stabilities, requiring overpotentials of 238 mV for the OER and 144 mV for the HER to achieve a current density of 10 mA cm-2. When applied to a simulated seawater splitting device, the CeOx@NiCo2O4/NF also maintains a battery voltage of 1.66 V to reach 10 mA cm-2 and exhibits good stability for over 60 h, with high faradic efficiencies (FEs) close to 100% for both the OER and HER.

Improved Discharge Performance of AZ72-0.05La Alloy Anode via Refining Mg17Al12 Phase

The morphology of phases in magnesium alloys is vitally important for their performance. It is found that improved discharge performance is achieved in AZ72-0.05La alloy via a refining Mg17Al12 phase by means of hot rolling. Before rolling, as-cast AZ72-0.05La alloy has a relatively coarse and strip-like Mg17Al12 phase. After rolling, the Mg17Al12 phase becomes much finer, showing a granulated shape. Due to the refinement of the Mg17Al12 phase, the discharge voltage and energy density of an Mg-air battery with as-rolled AZ72-0.05La alloy as the anode increases by 6% and 3% under a discharge current density of 20 mA·cm−2 in a 3.5% NaCl solution, respectively. The corrosion rate of the as-rolled AZ72-0.05La alloy is slightly larger than the as-cast AZ72-0.05La alloy, but still much lower than as-cast AZ72 alloy. The as-rolled AZ72-0.05La alloy possesses a discharge voltage of 0.74 V and an energy density of 918 mWh·g−1 under a discharge current density of 20 mA·cm−2, and a relatively low corrosion rate of 0.51 mg·cm−2·h−1, demonstrating good overall discharge performance. This work provides a method for improving the discharge performance of Mg-air batteries.

Implementing expansion force-based early warning in LiFePO4 batteries with various states of charge under thermal abuse scenarios

The characteristics of thermal runaway in batteries exhibit significant differences depending on their states of charge (SOCs), posing considerable challenges in accurate and timely warning for thermal runaway accidents. This paper conducts an experimental investigation into the external expansion force, voltage, and temperature behaviours of batteries under different SOCs under thermal abuse scenarios. The expansion force signal was found first to exhibit abnormal characteristics (with an indicator value of 5 N/s), offering an earlier warning signal >642 s prior to thermal runaway, when the battery back temperature is merely approximately 318.15 K. To analyse the main causes of abnormal expansion, ultrasonic nondestructive tests were performed and suggested that a higher SOC intensify the side reactions and cause gas generation inside batteries. Notably, compared to normal-charged batteries (0% ≤ SOC ≤ 100%), over-charged batteries (SOC > 100%) are more sensitive to expansion force than normal-charged batteries. Furthermore, compared with voltage and temperature signals, the early warning time of the expansion force rises with the increase in the SOC of an overcharged battery, in contrast to normal-charged batteries. Finally, a novel hazard classification safety warning strategy for battery failure is effectively proposed. These novel findings hold substantial practical implications for creating more accurate early warning systems for battery thermal runaway, enhancing the safe and reliable operation of battery systems.

Design of fuzzy logic controlled zero voltage switching based interleaved high gain converter

The conversion of low level DC voltage to high level DC voltage at lower duty ratios with less ripple current at source side is a challenging task in the distributed generation systems. Active switched inductor (ASL) converter is a high gain converter and has a large amount of input ripple current due to the parallel charging of the inductors during on time of the switches and series discharge of the inductors during off time of the switches. This large input ripple current in the converter when used in distributed generation (DG) affects the life time of low voltage batteries and fuel cells, the efficiency of photovoltaic source, increases the size and losses in the filtering stages and decreases the power density of the converters. In this paper, soft switching of interleaved active switched inductor (IASL) through Zero Voltage Switching (ZVS) is designed to overcome the limitations of ASL. The performance is analyzed in terms of its gain, input current ripple, switching loss and efficiency. An M-type resonant switch is used to achieve soft switching through ZVS technique.A proper value of resonant elements (inductor and Capacitor) is designed to achieve ZVS to improve the efficiency. Regulated voltage of proposed converter is required in DG systems and is possible with closed loop control. Fuzzy Logic controller (FLC) is designed to regulate the voltage and its dynamic performance is analyzed for different load values and also for sudden changes in load. Hardware model of the proposed ZVS based IASL converter with FLC is implemented and the results are verified with simulation results obtained from MATLAB Simulink.

Finite control set model predictive control of three-port converter for interfacing a PV–battery energy storage system to a three-phase stand-alone AC system

Abstract This paper proposes a multiport bidirectional non-isolated converter topology that provides advantages in terms of simultaneous multiple operations, single-stage conversion, high power density and reduced power losses due to the lower number of switches. The proposed multiport converter uses a centralized non-linear controller known as a finite control set model predictive controller to manage the flow of power between different ports. It deals with the parallel operation of photovoltaic and battery energy storage systems for stand-alone alternating current (AC) systems. The converter connects the lower voltage battery to the photovoltaic port using a bidirectional buck/boost converter and the photovoltaic port is linked to the stand-alone AC load through a three-phase full-bridge inverter. Each leg of the three-phase converter will act as a bidirectional direct current (DC)/DC converter as well as an inverter simultaneously. Only six switches manage the power transfer between all the connected ports of photovoltaic–battery energy storage system linked to the stand-alone AC load. The proposed multiport converter is mathematically modelled and controlled by a finite control set model predictive controller. The system is validated in simulation (1-kW rating) and experimental environment (200-W rating). The hardware prototype is developed in the laboratory and the controller is implemented on the field-programmable gate array board. Two independent case studies are carried out to validate the efficacy of the system. The first scenario is for a change in solar irradiance, while the second scenario is for a change in the output load.