Performance enhancement of energy extraction capability for fuel cell implementations with improved Cuckoo search algorithm

İnci, Mustafa; Çalışkan, Abdullah

doi:10.1016/j.ijhydene.2020.02.069

Cited by 60 publications

(26 citation statements)

References 47 publications

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“…The predator moves according to Brownian approach, whereas the prey moves according to Lévy flight approach. The population is divided into two subsections; the first section employs (19) and (20), whereas the other section uses ( 21) and ( 22) to modify the locations as follows:…”

Section: Optimization Methodology a Mpa Optimizermentioning

confidence: 99%

“…In [18], the water cycle optimization algorithm has been proposed to determine the MPPT corresponding PEMFC voltage, which is tracked using cascaded PID controller. The dynamic cuckoo search optimization algorithm (DCSA) has been introduced for directly adjusting the duty cycle duration of boost DC/DC converter [19]. However, increased number of sensors is needed in the above-mentioned methods.…”

Section: Introductionmentioning

confidence: 99%

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Marine Predators Algorithm Optimized Reduced Sensor Fuzzy-Logic Based Maximum Power Point Tracking of Fuel Cell-Battery Standalone Applications

et al. 2021

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Fuel cell (FC) represents one of the promising efficient solutions for future energy supply. Improving performance and integration methods of FCs via maximum power point tracking (MPPT) and high boosting factor inverters are key requirements for research in renewable energy fields. Recently, hybrid FC-battery structures have shown wide applications in several areas. Accordingly, marine predators algorithm (MPA) is proposed in this article for optimizing the design of reduced sensor fuzzy-logic based MPPT scheme. The proposed scheme inherits the following benefits: reduced sensors and hence reduced costs, more flexibility and smooth performance due to fuzzy-logic based MPPT, and optimized design method of fuzzy-logic based MPPT through MPA method. Moreover, a high boosting ratio inverter is introduced in this article based on using the switched capacitor multilevel inverter (SCMLI). The proposed system achieves self capacitor voltage control without complex control or extra sensors. The proposed hybrid FC-battery system has been validated at various operating points. In addition, comprehensive comparisons with existing schemes in the literature are provided in the paper. The superiority of the proposed scheme has been verified with robust, fast and accurate tracking, reduced cost, flexible, simple, and smooth output waveforms. The proposed method achieves the lowest output power fluctuations with fast tracking speed compared to the studied classical methods.INDEX TERMS Battery, fuel cells (FCs), fuzzy logic control, marine predators algorithm, maximum power point tracking, stand alone applications.

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Section: Optimization Methodology a Mpa Optimizermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Marine Predators Algorithm Optimized Reduced Sensor Fuzzy-Logic Based Maximum Power Point Tracking of Fuel Cell-Battery Standalone Applications

et al. 2021

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“…It is well known that the use of metaheuristic algorithms comprises an effective technique for solving nonlinear optimization problems. Many metaheuristic algorithms have been applied to resolve complex engineering problems [12][13][14][15]. However, threedimensional (3D) indoor location systems based on visible-light communication can be viewed as a global optimization problem, and a variety of metaheuristic optimization algorithms have been used to address the problem.…”

Section: Introductionmentioning

confidence: 99%

Indoor High-Precision 3D Positioning System Based on Visible-Light Communication Using Improved Whale Optimization Algorithm

et al. 2022

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Visible-light communication (VLC) is a promising method for indoor positioning. The received signal strength algorithm is the most widely used localization algorithm in visible-light positioning (VLP) systems. However, in a VLP system, the photodiode (PD) will have a small rotation angle during movement, which will result in a massive positioning error ignoring the angle. In this study, a three-dimensional (3D) indoor VLP system using an improved whale optimization algorithm (IWOA) is proposed to reduce the error caused by the PD rotation. Firstly, the model of the VLC system with the PD rotation angles is introduced. Secondly, a novel IWOA with an elite opposition-based learning strategy and Lévy flight strategy is proposed. The convergence speed and accuracy of the WOA are improved. Lastly, the IWOA algorithm is efficiently utilized to address the problem with the PD rotation in the indoor VLP system. Simulation results show that the average error of 3D positioning is 2.14 cm with no PD rotation. When the PD has a rotation angle, the average positioning error estimated by ignoring the rotation angle is 27.14 cm, while that estimated by considering the rotation angle is 7.85 cm. In the VLP system, the positioning error with the PD rotation angle is effectively reduced by the proposed algorithm, which can be applied in a variety of indoor location scenes.

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“…It has strong versatility and can solve various continuous problems as well as discrete problems. [3][4][5] Up to now, there have been many mature metaheuristic algorithms with good performance, such as Sparrow Search Algorithm (SSA), [6][7][8] Genetic Algorithm (GA), [9][10][11] Butterfly Optimization Algorithm (BOA), [12][13][14] Differential Evolution (DE), [15][16][17][18] Cuckoo Search (CS), [19][20][21] Harris Hawk Optimization (HHO), [22][23][24] Gray Wolf Optimization (GWO), [25][26][27][28] Fish Migration Optimization (FMO), 29,30 Particle Swarm Optimization (PSO), [31][32][33][34] Phasmatodea Population Evolution algorithm (PPE), 35,36 Cat Swarm Optimization (CSO), [37][38][39] and Ant Colony Optimization (ACO) [40][41][42][43] .…”

Section: Introductionmentioning

confidence: 99%

A novel Fruit Fly Optimization Algorithm with quasi-affine transformation evolutionary for numerical optimization and application

Wang

et al. 2022

International Journal of Distributed Sensor Networks

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The Fruit Fly Optimization Algorithm is a swarm intelligence algorithm with strong versatility and high computational efficiency. However, when faced with complex multi-peak problems, Fruit Fly Optimization Algorithm tends to converge prematurely. In response to this situation, this article proposes a new optimized structure—Quasi-affine Transformation evolutionary for the Fruit fly Optimization Algorithm. The new algorithm uses the evolution matrix in QUasi-Affine TRansformation Evolution algorithm to update the position coordinates of particles. This strategy makes the movement of particles more scientific and the search space broader. In order to prove its effectiveness, we compare Quasi-affine Transformation evolutionary for the Fruit fly Optimization Algorithm with five other mature intelligent algorithms, and test them on 22 different types of benchmark functions. In order to observe the multi-faceted performance of Quasi-affine Transformation evolutionary for the Fruit fly Optimization Algorithm more intuitively, we also conduct experiments on algorithm convergence analysis, the Friedman test, the Wilcoxon signed-rank test, and running time comparison. Through the above several comparative experiments, Quasi-affine Transformation evolutionary for the Fruit fly Optimization Algorithm has indeed demonstrated its strong competitiveness. Finally, we apply it to Capacitated Vehicle Routing Problem. Through comparing with the contrast algorithms, it is confirmed that Quasi-affine Transformation evolutionary for the Fruit fly Optimization Algorithm can achieve better vehicle routes planning.

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Performance enhancement of energy extraction capability for fuel cell implementations with improved Cuckoo search algorithm

Cited by 60 publications

References 47 publications

Marine Predators Algorithm Optimized Reduced Sensor Fuzzy-Logic Based Maximum Power Point Tracking of Fuel Cell-Battery Standalone Applications

Marine Predators Algorithm Optimized Reduced Sensor Fuzzy-Logic Based Maximum Power Point Tracking of Fuel Cell-Battery Standalone Applications

Indoor High-Precision 3D Positioning System Based on Visible-Light Communication Using Improved Whale Optimization Algorithm

A novel Fruit Fly Optimization Algorithm with quasi-affine transformation evolutionary for numerical optimization and application

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