Battery Charge Control Research Articles

Simulation and Optimization of a Hybrid Photovoltaic/Li-Ion Battery System

The coupling of solar cells and Li-ion batteries is an efficient method of energy storage, but solar power suffers from the disadvantages of randomness, intermittency and fluctuation, which cause the low conversion efficiency from solar energy into electric energy. In this paper, a circuit model for the coupling system with PV cells and a charge controller for a Li-ion battery is presented in the MATLAB/Simulink environment. A new three-stage charging strategy is proposed to explore the changing performance of the Li-ion battery, comprising constant-current charging, maximum power point tracker (MPPT) charging and constant-voltage charging stages, among which the MPPT charging stage can achieve the fastest maximum power point (MPP) capture and, therefore, improve battery charging efficiency. Furthermore, the charge controller can improve the lifetime of the battery through the constant-current and constant-voltage charging scheme. The simulation results indicate that the three-stage charging strategy can achieve an improvement in the maximum power tracking efficiency of 99.9%, and the average charge controller efficiency can reach 96.25%, which is higher than that of commercial chargers. This work efficiently matches PV cells and Li-ion batteries to enhance solar energy storages, and provides a new optimization idea for hybrid PV/Li-ion systems.

High gain super lift Luo converter for hybrid energy management systems

Recently, there has been a resurgence of interest in the development of alternative energy supplies due to rising fossil fuel prices and issues about the effects of greenhouse gas emissions on the environment. Today's demand is the design of a hybrid electric power generation system that uses solar and wind energy for remote places. This paper presents the design of an optimized hybrid renewable energy system consisting of a photo voltaic wind turbine (savinous type) with a battery and a super lift LUO converter. A solar PV module with an intelligent inverter facilitates the tracking of the maximum power point and the implementation of a battery charge controller for greater battery lifespan as well as reliable performance. Higher power output and clean energy are available from the hybrid power generation system, which combines innovative techniques with solar and wind power.

An improved takagi - sugeno variable step size perturb and observe MPPT algorithm based lead acid battery charge controller for photovoltaic system

The main objective of photovoltaic system controller is to reduce the price of the kWh compared to traditional fuel-based electricity. Thus, the improvement of simple and low – cost controllers is a major challenge. Perturb and Observe (P&O) is the commonly used algorithm in order to ensure the power maximization of the photovoltaic system, due to its simplicity and effectiveness. However, on the main drawbacks of that algorithm is the fixed step size of perturbation, due to working environmental changes, which require dynamic tuning of the controller parameter. In order to overcome the cited disadvantage, a new Takagi - Sugeno variable step P&O is proposed. Based on the real-time measurements of the solar radiation and temperature, the proposed fuzzy system schedules the appropriate step size based on human expertise. A zero order Takagi – Sugeno with singleton output is proposed. The fuzzification were carried out using triangular and trapezoidal membership functions. The centroid defuzzification method based 25 If -Then rules are adopted. In order to verify the effectiveness of the improved P&O, three scenarios were used. The obtained results show the effectiveness of the proposed controller under shaded conditions and various temperatures.

Efficient and robust control of a standalone PV-storage system: An integrated single sensor-based nonlinear controller with TSCC-battery management

The aim of this research undertaking is to investigate an integrated approach that extends the battery life of a single-stage off-grid photovoltaic system while simultaneously increasing the availability of solar photovoltaic power. This paper takes a synergistic approach to addressing these issues, in contrast to the numerous prior papers that have investigated them individually. In regard to the initial issue, this article proposes a hybrid MPPT solution which combines a backstepping controller with a distinct single-sensor MPPT approach. The aforementioned integrated system guarantees the exact attainment of the maximum power point (MPP) of the photovoltaic solar array, regardless of weather fluctuations. With regard to the second issue at hand, the effective management of charge for lead-acid batteries is accomplished by employing a three-stage charging controller (TSCC). The simulation results generated in MATLAB/Simulink indicate that MPPT tracking and battery charge control exhibit markedly improved performance across a range of weather conditions when the climatic conditions of El Jadida city, Morocco are taken into account. The hybrid method, as proposed, indisputable surpasses alternative MPPT approaches such as Inc-PI, FLC, PSO, RegP, and IMP-PO, with respect to convergence time (<3 milliseconds), variation (<0.19 watts), and tracking efficiency (over 99.86 %). Furthermore, the battery station is outfitted with secure and appropriate charging modes. In conclusion, the experimental validation of the proposed system against an actual experimental system in the laboratory verifies its hardware and practical viability.

Design and Development of MPPT Solar Charge Controller for Efficiency Enhancement in Solar PV System

Maximum power point tracking charge controller simulation is done in in proteus 8 professional software and validate using development of hardware model of MPPT solar charge controller for battery. Solar panel does not generate enough voltage all time.Panel can generate 12V to 21V according to solar radiation and environmental condition. For charging of 12V battery minimum required voltage is 14.6V. So, the Maximum power point tracking controller will give extra voltage into usable current, so battery can charge in short period.Development of MPPT Solar Charge Controller is done using ardunionano controller board, ACS 712 current sensor, mosfet driver IR2102, dc-dc buck converter using mosfet, inductor, capacitor and wifi module for data collection, LCD display,LED indication for battery status of charging. Battery charge using three state charging say buck, absorption and float mode. Performance analysis done using simulation model using LCD display status, where first column of display shows PV voltage, PV current and PV power. Second column of display reads battery voltage, status of battery. Third column reads pwm duty cycle in percentage and load status. Voltage level is shown by LED. Yellow LED indicates a fully charged battery, green indicates a regular voltage, and red indicates a low voltage. Performance study was done and the model was validated using a hardware model. All parameters and functionalities for measured solar panel voltage, current, power, battery voltage, charger state, SOC, PWM duty cycle, and load status are shown in real-time on the hardware display. Three-step battery charging algorithms are utilized, specifically the buck stage, absorption stage, and float stage. The battery peak charges to 90% SOC and the battery current is almost steady during the buck stage. In the buck stage, the battery voltage rises to a peak of 14.4V. Absorption occurs in the second phase when the battery's voltage remains constant and its current decreases. Battery current will be very low in the final phase, almost like trickle current.

Разработка эффективного контроллера отслеживания точки максимальной мощности для фотоэлектрической системы

A method is presented to improve the performance of off-grid photovoltaic systems using a battery charge controller equipped with solar panel maximum power point tracking (MPPT) technology. Today, the MPPT controller is an effective technology that ensures the ideal functioning of solar panels by searching and selecting the optimal power point. The purpose of the study is to develop and evaluate the performance of a battery charge controller for solar panels based on the maximum power point tracking method. The proposed method uses a perturbation and observation algorithm and tracks the maximum power point based on the current and voltage output characteristics. A DC/DC buck converter was used in the study. The model of the proposed method was implemented in the Matlab Simulink software environment, and the efficiency of the operating algorithm was assessed. In addition, based on this model, an MPPT controller was developed, which was tested in real conditions. The reliability of the proposed method was also assessed. As a result of the study, the effectiveness of the developed system was revealed through a comparative analysis with a commercial battery charge controller

A smart and intelligence based controlling algorithms for maximum power extraction and effective battery management in EV systems

AbstractAn economically appealing alternative to the use of fossil fuels in many nations is the electric vehicle (EV). Commercial EVs have a battery that powers the motor while also being charged by solar photovoltaic (PV). The original contribution of this research work is to implement a smart and advanced methodologies for accomplishing the objectives of MPPT control and battery management in EVs. Here, a novel spotted hyena optimized (SHO)‐MPPT controlling algorithm is applied to get the most out of the electricity generated by PV panels to meet EV energy requirements. A modified high gain super‐lift Luo converter has been implemented to improve and regulate the output voltage of PV for optimal battery charging and motor control. Then, an adaptive dynamic encoded network controller is designed to improve the voltage regulation and boosting performance of the DC‐DC converter. Consequently, a Henry gas solubility optimization is deployed to perform an effective battery management in EVs by optimally estimating the state of charge, which helps to increase the charging efficiency of EVs. Moreover, a three‐phase voltage source inverter has also been used to lower harmonic levels and deliver high‐quality output power to the EV motor. The results of the proposed MPPT controlling, converter controlling, and battery management strategies are verified in this study using a complete simulation and comparison analysis, where the parameters such as IV‐PV characteristics, motor torque, speed, total harmonic distortions (THDs), and so forth are taken into account for performance validation. By using the proposed controlling methodology, the THD is reduced to 1.09% with the improved vehicle speed of 3000 rpm, and overall performance efficiency of 99%.

A New Design and Embedded Implementation of a Low‐Cost Maximum Power Point Tracking Charge Controller for Stand‐Alone Photovoltaic Systems

This article presents a low‐cost maximum power point tracking (MPPT) charge controller designed to efficiently charge solar batteries using a simple and robust MPPT method, while providing protection against over‐currents and over‐voltages. The proposed MPPT approach utilizes a modified Incremental Conductance (INC) algorithm adapted to low‐cost embedded controllers, as it avoids all the mathematical division calculations typically used in the conventional INC algorithm. It also introduces a modified step size based only on photovoltaic (PV) power change to enhance tracking accuracy and convergence speed. Furthermore, to reduce the stress and switching losses of DC–DC converter, a feedback control with two proportional and integral (PI) compensators is also used to control both the PV voltage and to protect the battery from over‐currents using PV power limitation technique. Simulation results, carried out under MATLAB/Simulink, demonstrate the good performance of the proposed control scheme regarding any variations in atmospheric conditions, both for the MPPT control and for the battery charge control. Finally, a processor‐in‐the‐loop (PIL) test using a low‐cost Arduino MKR ZERO board is also performed to verify the hardware implementation of the proposed method. PIL results are in totally accordance with MATLAB/Simulink simulation results, which further proves the effectiveness of the proposed method.

SIMULATION MODELING OF MULTI-PORT DC-DC CONVERTER IN MPPT SOLAR BATTERY CONTROLLERS UNDER NEURAL NETWORK CONTROL

Photovoltaic generation system - energy system, designed to convert useful solar energy through photovoltaic systems. It can consist of several components, including a solar array, DC/DC and DC/AC semiconductor converter, battery, filter or transformer, control system (CS). Depending on the application, photovoltaic systems can be operated as part of a self-contained power plant or operate on a network. Thus, it is possible to distinguish several basic configurations of photovoltaic generation systems. The standalone generation system is the most common configuration of photovoltaic generation systems, which contains rechargeable batteries (AB). This system is completely independent of the centralized power supply networks and is suitable for comfortable energy supply to consumers. The use of AB makes it possible to increase the reliability of the photovoltaic system and to extend the possibilities of using e.g. battery power is used during insufficient light or when the load exceeds the generation of solar cells. The scope of such configurations are lighting systems of residential and non-residential objects, power supply of houses and buildings, security systems and emergency power supply, power supply of remote residential and non-residential objects, Power supply to spacecraft, etc. Autonomous generation systems typically contain two transducers. The DC/DC converter acts as a battery charge controller. The control system for such a transducer may include the function of tracking the maximum power point for the maximum use of solar energy. The excess energy will be stored in AB. The DC/AC converter converts the DC current energy into the AC energy of the required frequency and voltage. The advantage of such a system is the possibility of using solar energy, both during the day and at night, due to the power of AB and the possibility of using the system at remote sites where there is no grid power supply. The disadvantage of such a system is the loss of double conversion of solar energy and the high cost of batteries. Artificial Neural Network (ANN) provides an alternative way to solve complex problems. A neural network, with the right structure, can compute the values of any continuous function with some predetermined accuracy. The neural network requires no knowledge of the internal parameters of the solar module, learns quickly, has the ability to optimize and approximate. Therefore, the use of INS to track the maximum power point is relevant and of practical and scientific importance. Keywords: multi-port DC converter, artificial neural network (ANN), rechargeable batteries (AB), pulse width modulation (PWM), solar panels (SP), MOSFET power keys

Stand-alone solar lighting system with Programmable Logic Controller

The circuitry modelling of the standalone photovoltaic (PV) maximum power point tracking (MPPT) lithium-ion battery charge controller is presented in this study using the MATLAB/Simulink environment. For the charge controller implementation, a DC-DC converter called a buck topology is used. The Perturb and Observe (P&O) MPPT algorithm monitors the solar panel’s peak power. The lithium-ion battery is charged in three stages by the battery charge controller. The model’s performance is analysed in terms of MPPT tracking performance, battery charging performance, and overall charge controller efficiency performance. With an MPPT efficiency of up to 99.9%, the performance result demonstrates that the MPPT is capable of tracking to the PV panel maximum point at any variation in solar irradiation. For small and medium standalone PV systems, this verified model aids in improved sizing of PV panels and battery energy storage. Techno-economic analysis refers to the assessment of the economic viability and profitability of using this type of lighting compared to other forms of lighting. The maintenance costs and efficiency of these systems can be improved even more by adding a programmable logic controller (PLC).

Metaheuristic Algorithm Based Battery Charge Control Design in Solar Energy Systems

Yenilenebilir güneş enerji sistemlerinde, kısıtlı zaman diliminde ve değişen atmosferik şartlarda güneş enerjisinden elde edilecek enerjinin verimli şekilde yüke aktarılması son derece önemli ve gereklidir. Güneş enerjisinden maksimum seviyede yararlanamayan sistemlerde, Fotovoltaik (PV) panel sayısı artışı, verim düşüşü ve maliyet artışından bahsedilebilir. Bu durumda; güneş enerjisinden alıcıların maksimum seviyede yararlanabilmesi, PV panellerden en üst seviyede yararlanabilmeye bağlıdır. Bunun içinde Maksimum Güç Noktası İzleyiciler (Maximum Power Point Tracker - MPPT) kullanılmalıdır. Bu çalışmada MPPT tekniklerinden Değiştir - Gözle (Perturb &amp;amp; Observe - P&amp;amp;O) yöntemi, Artan İletkenlik Yöntemi (Incremental Conductance - IC) ve Kısmi Açık-Devre Gerilim Yöntemi (Fractional Open-Circuit Voltage) kullanılmıştır. Yük üzerinde sabit bir gerilim elde edebilmek amacıyla kurşun asit bataryanın şarj ve deşarjını kontrol etmek için parametreleri Parçacık Sürüsü Optimizasyon (Particle Swarm Optimization - PSO) algoritması ve Çakal Optimizasyon Algoritması (Coyote Optimization Algorithm - COA) gibi metasezgisel algoritmalarla hesaplanmış kontrolör önerilmiştir.

Development of Light Weight Solar Dryer and Optimization of Drying Process for Bottle Gourd

The light weight solar dryer has been designed and fabricated to align with the atmospheric conditions of Kashmir valley. The experimental studies titled as “ Development of a light weight solar dryer and optimization of drying process for bottle gourd ” were conducted at the Sher-e –Kashmir University of Agricultural science and Technology , Shalimar, Srinagar J&amp;K , in the northern part of India, during summer season of 2023. The solar dryer consists of drying chamber, drying tray, air inlet , exhaust fan for cross ventilation , temperature humidity controller module, solar panel, battery and solar charge controller. The dryer harnesses solar energy for the drying process and holds substantial promise for drying fruits, vegetables , herbs with medicinal properties and a variety of other products. The dryer has dimension of( length=36˝ , width=24˝, front height=30˝, back height 40˝ and a slope for attaining maximum sunlight intensity. This dryer has an average capacity of 4-5kg of the food product for drying. In this experiment tray is loaded with untreated and treated bottle gourd slices. In two separate trials drying completed in 20 and 32 hours for treated and untreated sample respectively .

An improved control for a stand-alone WEC system involving a Vienna rectifier with battery energy storage management

This study focused on efficiency improving, the power flow management and control problem of the standalone wind energy conversion system. Specifically, the system under study consists of a Permanent Magnet Synchronous Generator (PMSM) driving by wind turbine, Vienna rectifier, a Li-ion battery and a DC load. Battery life is vulnerable to fluctuations due to the intermittent nature of the wind, as well as to the demand for energy charging, which reduce considerably battery state of health (SOH) and consequently charging capacity. To overcome these shortcomings, a nonlinear battery charge controller is used to regulate the current supplied to the battery and to the load, and thus guarantee best charging performances. Based on the wind power, the load demand and the battery state of charge (SOC), three operating modes are considered. Specifically, MPPT mode, Constant Current (CC) charging mode and Constant Voltage (CV) charging mode. We also design a new energy management method to protect the energy storage system and increase its lifetime. This algorithm ensure a smooth switching between three controllers designed to provide the three operating modes. The high performances and the efficiency of the proposed controller and management algorithm are highlighted using several MATLAB/SIMULINK simulations.

The Design and Simulation of a Stand-Alone Solar Inverter with Improved Efficiency and Power Quality for Home Appliances

An inverter for solar panels is proposed in this paper. The inverter's various components have been tested with MATLAB Simulink. The output of the inverter has been analysed using MATLAB Simulink to determine whether pure sine waves are being produced. There are two kinds of loads that are employed in-house, inductive and capacitive loads. The outputs of the inverter are connected to the loads, and Irms, THDv, and Vrms have been measured. Additionally, the THDv value can be observed by adjusting the PV array's radiation and temperature. Furthermore, Irms and THDv changes can be accompanied by a change in the load value of inductive capacitance. The inverter's accessories, such as the PV array, Buck Converter, DC-DC, battery charge-controller, and battery connectors, are also tested using MATLAB Simulink. This kind of inverter can be used to illuminate buildings, businesses, and industries. Most household appliances run on alternating current, so to renovate DC to AC, an inverter is rummage-sale.

An Interleaved Battery Charger Circuit for a Switched Capacitor Inverter-Based Standalone Single-Phase Photovoltaic Energy Management System

A single-phase bidirectional DC/DC battery charger with a P&amp;O MPPT current control strategy for a standalone energy management system has been integrated with an interleaved switched capacitor DC/AC inverter with an RMS feedback phase-shifted unipolar sinusoidal PWM control strategy. In the published literature, P&amp;O MPPT control is used to drive a boost converter connected in parallel to a battery charger; this modified strategy combines a P&amp;O MPPT algorithm with current control to drive an interleaving buck-boost battery charger. This battery charger circuit is connected in parallel to a closed loop controlled interleaved inverter that feeds the AC home load. MATLAB/Simulink based simulation circuit was developed and used to validate the successful integration of the interleaved battery charger with the global system. To do this, the system is tested with varying input conditions of irradiance and temperature. The system’s response to these variable inputs is monitored and analysed. The simulation results show the proposed method is effective for standalone battery-based PV systems. The system provides a more efficient and faster response compared with both an interleaved and non-interleaved voltage-controlled battery charger circuit that is also integrated with the global system. This battery charger control strategy is also shown to protect the battery from over-charging as well as discharging below 25%, which can improve and protect the long-term battery performance. Compared with novel industry approaches, the proposed system is simpler by nature due to the reduced number of conversions and therefore a reduced number of components which provides economic advantages.

Battery Charge Control in Solar Photovoltaic Systems Based on Fuzzy Logic and Jellyfish Optimization Algorithm

The study focuses on the integration of a fuzzy logic-based Maximum Power Point Tracking (MPPT) system, an optimized proportional Integral-based voltage controller, and the Jellyfish Optimization Algorithm into a solar PV battery setup. This integrated approach aims to enhance energy harvesting efficiency under varying environmental conditions. The study’s innovation lies in effectively addressing challenges posed by diverse environmental factors and loads. The utilization of MATLAB 2022a Simulink for modeling and the Jellyfish Optimization Algorithm for PI-controller tuning further strengthens our findings. Testing scenarios, including constant and variable irradiation, underscore the significant enhancements achieved through the integration of fuzzy MPPT and the Jellyfish Optimization Algorithm with the PI-based voltage controller. These enhancements encompass improved power extraction, optimized voltage regulation, swift settling times, and overall efficiency gains.

Maximum Power Point Tracking Charge Controller Using Modified Perturb and Observe Algorithm for Lead Acid Battery

A study was undertaken on development of a modified perturb and observe algorithm for maximum power point tracking (MPPT) charge controller. This MPPT algorithm was developed in Matlab/Simulink environment, using three-state charging method for improved battery charging with higher efficiency. A buck topology was utilised as a DC-DC converter for charge controller implementation. The maximum power of the photovoltaic panel was tracked by a modified perturb and observe algorithm. The battery charge controller charged a lead-acid battery using a three- stage charging strategy including the bulk charge, constant voltage (absorption charge), and float charge stage. The performance analysis of Simulink model was carried out by maximum power point tracking performance, battery charging performance, and overall charge controller efficiency performance. The performance results indicated that the maximum power point tracking was capable to track to the maximum power of PV panel at any solar irradiance variation with power tracking efficiency up to 98 per cent. The efficiency of overall charge controller was up to 98.3%, which matched many high-end commercial charge controller product specifications.

Multi-objective control and optimization of a stand-alone photovoltaic power conversion system with battery storage energy management

This paper addresses the problem of controlling a stand-alone photovoltaic (PV) energy conversion system integrated with a battery energy storage system. The study focuses on a series association of PV panels, a DC/AC converter, a Li-ion battery, and a DC load. The intermittent nature of PV power and frequent variations in load demand decrease battery lifetime and its charging performance. To mitigate these issues, an efficient battery charge controller is proposed to instantaneously balance the PV power flow delivered to the DC load and the battery, ensuring optimal utilization of PV power and appropriate battery charging. Based on available solar power, battery state of charge (SOC), and DC load demand The controller adapts to three charging modes, namely, maximum power point tracking (MPPT) charging mode, constant current (CC) charging mode, and constant voltage (CV) charging mode. Additionally, a novel energy management algorithm is designed to ensure battery safety and determine the system’s mode of operation, considering weather conditions and load demand variations. Interestingly, no solar irradiation or battery SOC sensors are required for the implementation of the control system. Nonlinear and robust controllers are developed to provide the necessary control input laws for the management algorithm. The robustness and stability of the system are verified using the Lyapunov theory. Furthermore, the paper quantifies the performance of the proposed strategy through a comparative analysis using integral of absolute error (IAE) indices against two conventional control approaches. Simulation results validate the effectiveness of the proposed controller strategy, demonstrating its high performance and ability to meet the specified objectives. This work presents an innovative approach to enhance the efficiency and reliability of stand-alone PV energy conversion systems with battery storage, offering promising prospects for sustainable energy applications.

Design and Control of Two Stage Battery Charger for Low Voltage Electric Vehicles Using High Gain Buck-Boost PFC AC-DC Converter

The design and control of a two-stage onboard battery charger (OBC) for the low-voltage electric vehicle (LVEVs) are presented in this study. The presented charger operates over a wide range of AC input voltage at high power factor. The presented charger utilizes a bridgeless high gain high power factor AC-DC converter with continuous input current characteristics at its front end. At the back end of the charger, an isolated Cuk DC-DC converter is employed to control and implement different battery charging modes, viz. constant current (CC) and constant voltage (CV) charging profiles. The presented AC-DC converter operates under discontinuous current mode (DCM) operation and achieves minimum control complexity at the AC-DC stage. The DCM design and high voltage conversion ratio allow it to function reliably over a comprehensive range of input and intermediate DC link voltage. This study covers the charger's design for a power rating of 650 W and output battery voltage of 24 to 72 V. The overall operational analysis and effectiveness of the design are verified through both simulations and experimental implementation and the performance is compared with other contemporary power factor correction (PFC) topologies on various parameters.

Solid-State Transformers of Smart High-Power Battery Charger for Electric Vehicles

There is no doubt that society will not turn back: most thermal vehicles will switch to electric ones, not only for cars but also for bigger vehicles. Fast chargers will become more and more essential parts of the global system, they will provide a charge control of batteries and galvanic insulation from the grid. At the present times, compact realizations are based on Solid-State Transformers (SSTs) operating at high frequencies with their well-known advantages and disadvantages, including power limits and reasonably high costs. The authors propose a medium-frequency transformer (MFT) structure using Grain Oriented Electrical Steel (GOES) wound cores and aluminum foil windings. Thanks to this solution, the cost of the device can be reduced. GOES has losses that increase with frequency but decrease with temperature; therefore, the authors propose a transformer structure allowing a hot core inside coils at usual temperatures. This idea is applied to a 400-kW compact battery charger connected to a DC smart grid.