Ingenious golden section search MPPT algorithm for PEM fuel cell power system

Bahri, Hamza; Harrag, Abdelghani

doi:10.1007/s00521-020-05581-4

Cited by 15 publications

(7 citation statements)

References 60 publications

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“…Bahri, et al [ 32 ] introduced an ingenius golden search‐based MPPT controlling algorithm for PEMFCs. The golden search is a method for determining a curve's maximum or lowest value through a defined range of values or for a unimodal function by gradually reducing the range of values inside which a parameter point is known to be present.…”

Section: Related Workmentioning

confidence: 99%

An Amplified Salp Swarm Optimization Algorithm for Maximum Power Point Tracking Control of Proton Exchange Membrane Fuel Cells

Injarapu Edukondala Sanyasi,

Sambana,

Chilukoti

et al. 2023

Energy Tech

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The proton exchange membrane fuel cell (PEMFC), one of the many fuel cell varieties on the market, is distinguished by its low temperatures of operation, high reliability, and extended lifespan. The fuel cell system's maximum output can only be achieved at one specific operating point under varying operating circumstances. Hence, it is essential to get the most power possible from the PEMFC for improved functioning and optimal exploitation of grid systems. Thus, the design of a maximum power point tracking (MPPT) controller for a PEMFC power system using an amplified salp swarm optimization (AS2O) algorithm is focused on. Here, an interleaved Luo converter is also used to produce a regulated output voltage with less switching stress and frequency. Moreover, the proposed work intends to effectively satisfy the energy demand of grid systems by obtaining the maximum electrical energy from the PEMFCs with less harmonics and low system complexity. The simulation and performance results of the proposed AS2O‐MPPT controlling model are validated and compared using several parameters using MATLAB/Simulink tool. Using the proposed controlling technique, the total harmonics distortion is reduced up to 1.16%, with the settling time of 0.0062 s, rise time of 0.0010 s, and peak overshoot of 0.255 W.

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Section: Related Workmentioning

confidence: 99%

An Amplified Salp Swarm Optimization Algorithm for Maximum Power Point Tracking Control of Proton Exchange Membrane Fuel Cells

Injarapu Edukondala Sanyasi,

Sambana,

Chilukoti

et al. 2023

Energy Tech

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“…MPPT techniques are used to maximise the power utilization from the input source. Many MPPT techniques were proposed for the tracking of maximum power from solar PV and fuel cells [13][14][15].…”

Section: Fig1 Block Diagram Of Conventional Dc-dc Convertermentioning

confidence: 99%

Fuel Cell-Based Hybrid Electric Vehicle Systems Multi-Input Bi-Directional DC to DC Converter Topology

Priyadharshini¹,

ARCHANA²

2022

Preprint

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Usage of electric vehicles has increased over the last decade due to awareness and development. Battery-operated Electric Vehicles were the primary choice due to their simple design, but alternate sources were also developed for EVs. Fuel cells are one of the sources used in electric vehicles due to their near-zero emissions, lowest pressure, and temperature. Many converter topologies and control algorithms were presented to transfer the energy from the PEM fuel cell used as a primary choice. This paper introduces a modified multi-input DC-DC converter with multiple input sources to connect a fuel cell and a battery simultaneously. This setup is used to drive brushless DC (BLDC) motor which can be suitable for electric vehicle applications. Using incremental conductance and Grey Wolf algorithm based maximum power point tracking approaches, the presented circuit is analysed, and the findings are presented. The simulation results demonstrate that the suggested topology provides a suitable response for both MPPT approaches.

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“…To overcome these drawbacks, the second class of MPPT approaches uses techniques based on intelligent control like neural networks, fuzzy logic (FL), genetic algorithms, fast atom search optimization, and the golden section technique. 11,12 Among the intelligent-based methods, FL theory is known for its ability to handle nonlinearities in mathematical logic by operating with common inputs as an alternative to a correct mathematical model. This interesting property has prompted some researchers in the field of TEG to use this technique to improve the performance of MPPT controllers.…”

Section: Introductionmentioning

confidence: 99%

“…INR, on the other hand, successfully eliminates the oscillation around the MPP, but it still suffers from the dynamic response. To overcome these drawbacks, the second class of MPPT approaches uses techniques based on intelligent control like neural networks, fuzzy logic (FL), genetic algorithms, fast atom search optimization, and the golden section technique 11,12 …”

Section: Introductionmentioning

confidence: 99%

A robust type‐2 fuzzy logic‐based maximum power point tracking approach for thermoelectric generation systems

Rezk

Harrag

2021

Intl J of Energy Research

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A robust type-2 fuzzy logic (FL)-based approach for maximum power point tracking (MPPT) is proposed in this work. The method is used to increase the energy efficiency of thermoelectric generators (TEGs). Type-2 FL was applied to adapt the variable step size of incremental resistance (INR) MPPT to track the maximum available power of a TEG. The output power from a TEG relies mostly on the difference in temperature of its two sides added to the load value. Consequently, MPPT must be robust to extract the optimum operation point continually under varying operational conditions. The aim of the

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Ingenious golden section search MPPT algorithm for PEM fuel cell power system

Cited by 15 publications

References 60 publications

An Amplified Salp Swarm Optimization Algorithm for Maximum Power Point Tracking Control of Proton Exchange Membrane Fuel Cells

An Amplified Salp Swarm Optimization Algorithm for Maximum Power Point Tracking Control of Proton Exchange Membrane Fuel Cells

Fuel Cell-Based Hybrid Electric Vehicle Systems Multi-Input Bi-Directional DC to DC Converter Topology

A robust type‐2 fuzzy logic‐based maximum power point tracking approach for thermoelectric generation systems

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