Modelling and Analysis of Hybrid Fuzzy Tuned PI Controller based PMBLDC Motor for Electric Vehicle Applications

Kavin, K S; P, Subha Karuvelam; Pathak, Abhinav; Premila, T R; Hemalatha, R; Kumar, Tharwin

doi:10.14445/23488379/ijeee-v10i2p102

Cited by 5 publications

(1 citation statement)

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“…In recent years, especially home and industrial applications for energy from sustainable sources have increased considerably [1]. The grid's ability to successfully integrate solar PV has been continuously prospering, yet it has certain effects on the amount of electricity is produced [2].…”

Section: Introductionmentioning

confidence: 99%

PV based Systems with Advanced Control Strategies for Load Balancing in Multilevel Inverter

2024

Int. Res. J. multidiscip. Technovation

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In an era driven by sustainable energy solutions, the synergy of photovoltaic (PV) system stands as a beacon of hope for meeting the world's growing energy demands while minimizing environmental impact. This research ventures into the domain of renewable energy integration by seamlessly including a PV system, ingeniously controlled by Chaotic Flower Pollination Optimized Adaptive Neuro Fuzzy Inference System (ANFIS) based MPPT (Maximum Power Point Tracking) controller capable of optimizing the efficiency in the face of ever-changing weather dynamics. The PV system's quest for optimal efficiency receives a substantial boost through the implementation of the High Gain Modified Luo Converter. Designed to achieve an optimal PV output voltage, this converter's prowess finds its true calling in grid applications, where precision and efficiency are paramount. Furthermore, this research extends its purview to incorporate a bidirectional converter linked to an energy storage solution, such as a battery, through a common DC link. The output power is then passed to the Flyback Converter, seamlessly connected to a 31 level Cascaded H Bridge Multi-Level Inverter (31-level CHB MLI) controlled by PI controller. This formidable inverter architecture facilitates the efficient delivery of power to the grid, ensuring a smooth and controlled integration of renewable energy resources. This strategic integration bolsters the system's adaptability, enabling the seamless management of energy flows and grid interactions along with load balancing in MLI. The MATLAB simulation platform is used for confirming the system's overall performance. According to the simulation results, the proposed approach achieves the maximum efficiency with the lowest THD value of 94.5% and 2.5%, respectively.

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Section: Introductionmentioning

confidence: 99%

PV based Systems with Advanced Control Strategies for Load Balancing in Multilevel Inverter

2024

Int. Res. J. multidiscip. Technovation

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Optimal synergetic control using chaotic dragon fly-based MPPT with cascaded ANFIS method for ultrafast electric vehicle charging by hybrid RES systems

Patil,

Linus

2024

Electr Eng

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A novel bald eagle search optimised ANFIS controlled high gain sepic converter-based efficient regenerative charging control for electric vehicles

Ramadevi,

Senthil kumar,

Balamurugan

2024

Electr Eng

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Modelling and Analysis of Hybrid Fuzzy Tuned PI Controller based PMBLDC Motor for Electric Vehicle Applications

Cited by 5 publications

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PV based Systems with Advanced Control Strategies for Load Balancing in Multilevel Inverter

PV based Systems with Advanced Control Strategies for Load Balancing in Multilevel Inverter

Optimal synergetic control using chaotic dragon fly-based MPPT with cascaded ANFIS method for ultrafast electric vehicle charging by hybrid RES systems

A novel bald eagle search optimised ANFIS controlled high gain sepic converter-based efficient regenerative charging control for electric vehicles

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