Using PV Fuzzy Tracking Algorithm to Charge Electric Vehicles

Chuang, Yao Lung; Herrera, Miguel F.; Balal, Afshin

doi:10.31763/ijrcs.v2i2.636

Cited by 6 publications

(4 citation statements)

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“…The fuzzy logic control system is a control system that utilizes ambiguous reasoning to control operations and infer solutions in the system. It has been widely studied and used in controlling various systems and controllers [96], [97], [98], [99], [100], [101]. In the context of robotic arm motor control, the Mamdani method is commonly used to estimate the ambiguous control input, as shown in Fig.…”

Section: Fuzzy Logic Control Systemmentioning

confidence: 99%

Adaptive P Control and Adaptive Fuzzy Logic Controller with Expert System Implementation for Robotic Manipulator Application

Chotikunnan

Pititheeraphab

2023

Journal of Robotics and Control

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This study aims to develop an expert system implementation of P controller and fuzzy logic controller to address issues related to improper control input estimation, which can arise from incorrect gain values or unsuitable rule-based designs. The research focuses on improving the control input adaptation by using an expert system to resolve the adjustment issues of the P controller and fuzzy logic controller. The methodology involves designing an expert system that captures error signals within the system and adjusts the gain to enhance the control input estimation from the main controller. In this study, the P controller and fuzzy logic controller were regulated, and the system was tested using step input signals with small values and larger than the saturation limit defined in the design. The PID controller used CHR tuning to least overshoot, determining the system's gain. The tests were conducted using different step input values and saturation limits, providing a comprehensive analysis of the controller's performance. The results demonstrated that the adaptive fuzzy logic controller performed well in terms of %OS and settling time values in system control, followed by the fuzzy logic controller, adaptive P controller, and P controller. The adaptive P controller showed similar control capabilities during input saturation, as long as it did not exceed 100% of the designed rule base. The study emphasizes the importance of incorporating expert systems into control input estimation in the main controller to enhance the system efficiency compared to the original system, and further improvements can be achieved if the main processing system already possesses adequate control ability. This research contributes to the development of more intelligent control systems by integrating expert systems with P controllers and fuzzy logic controllers, addressing the limitations of traditional control systems and improving their overall performance.

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Section: Fuzzy Logic Control Systemmentioning

confidence: 99%

Adaptive P Control and Adaptive Fuzzy Logic Controller with Expert System Implementation for Robotic Manipulator Application

Chotikunnan

Pititheeraphab

2023

Journal of Robotics and Control

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“…Terdapat dua jenis MPPT yang dapat digunakan untuk memaksimalkan daya keluaran panel surya, yaitu MPPT statis dan dinamis. MPPT statis merupakan metode pencarian titik daya maksimum panel surya berdasarkan kurva karakteristik, sedangkan MPPT dinamis merupakan metode yang digunakan pada penelitian ini dimana pencarian titik daya maksimum panel surya berdasarkan sudut datang sinar matahari terhadap panel surya [6], [16].…”

Section: Pendahuluanunclassified

Prototipe Solar Tracking Berbasis Arduino dan Sensor Light Dependent Resistor (LDR)

Saputra

Ma’arif

2022

Buletin Ilmiah Sarjana Teknik Elektro

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The government prioritizes the availability of electrical energy, especially in the industrial sector and urban areas, but the infrastructure to provide access to electricity in rural areas, especially street lighting, is still very lacking as a result of the need for a different energy source to overcome this problem. Solar cells are power plants that can convert solar energy into electricity, but most solar panels are installed statically which results in less than optimal absorption of solar energy. The purpose of this research is to make a prototype solar tracking based on the Arduino Mega 2560 microcontroller with the fuzzy logic method with an LDR sensor as a light sensor and a servo motor as a driver so that the solar panel can track the movement of the sun to get the maximum light intensity. The results of this study there are four test conditions which indicate that the percentage of the comparison value of solar panels statically and tracking in cloudy conditions is 34.07% while the test in cloudy sunny conditions is 25.603%. Pemerintah memprioritaskan ketersediaan energi listrik khususnya di sektor industri dan wilayah perkotaan tetapi infrastruktur untuk memberikan akses listrik di daerah pedesaan terutama penerangan jalan masih sangatlah kurang akibatnya perlunya sumber energi yang berbeda diperlukan untuk mengatasi masalah ini. Sel surya adalah pembangkit listrik yang dapat mengubah energi matahari menjadi listrik namun sebagian besar Panel surya dipasang secara statis yang mengakibatkan penyerapan energi matahari kurang optimal. Tujuan dari penelitian ini adalah membuat Prototype solar tracking berbasis mikrokontroler Arduino Mega 2560 dengan metode fuzzy logic dengan sensor LDR sebagai sensor cahaya dan motor servo sebagai penggerak sehingga panel surya dapat melacak pergerakan matahari untuk mendapatkan intensitas cahaya yang maksimal. Hasil dari penelitian ini terdapat empat kondisi pengujian yang menunjukkan bahwa persentase nilai perbandingan panel surya secara statis dan tracking dalam kondisi mendung sebesar 34,07% sedangkan pengujian dalam kondisi cerah Berawan sebesar 25,603%.

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“…Although, every BMS have varied goals, a typical BMS has the following three goals: It ensures that the battery is always available for use, safeguards the battery cells from misuse and damage, and maximizes battery life 27 . According to the literature study, it is analyzed that an effective MPPT control and BMS 27‐29 are highly essential for improving the overall performance and efficacy of the EV systems. In the conventional studies, several MPPT controlling approaches and battery management strategies are developed using the optimization approaches for EV applications 9 .…”

Section: Introductionmentioning

confidence: 99%

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

Nambi,

Muthubalaji,

Srinivasan

et al. 2024

Energy Storage

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An 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%.

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Using PV Fuzzy Tracking Algorithm to Charge Electric Vehicles

Cited by 6 publications

References 0 publications

Adaptive P Control and Adaptive Fuzzy Logic Controller with Expert System Implementation for Robotic Manipulator Application

Adaptive P Control and Adaptive Fuzzy Logic Controller with Expert System Implementation for Robotic Manipulator Application

Prototipe Solar Tracking Berbasis Arduino dan Sensor Light Dependent Resistor (LDR)

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

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