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Article type: Research Article
Authors: Rafikiran, Shaik.a | Devadasu, G.b | Rajendhar, P.c | Likhitha, R.d | Basha, CH Hussaiand; *
Affiliations: [a] Department of EEE, Sri Venkateswara College of Engineering, Tirupati, India | [b] CMR College of Engineering & Technology (Autonomous), Hyderabad, India | [c] Smt. Indira Gandhi College of Engineering, Mumbai, India | [d] NITTE Meenakshi Institute of Technology, Bangalore, India
Correspondence: [*] Corresponding author. CH Hussaian Basha, NITTE Meenakshi Institute of Technology, Bangalore, India. E-mail: sbasha238@gmail.com.
Abstract: The fuel cell-dependent electric vehicle systems are giving an important role in the present automotive systems because their features are less air pollution, high flexibility, reduced oil dependency, and more reliability. However, the fuel stack delivers nonlinear output V-I characteristics. So, the extraction of peak power from the fuel source is very difficult. In this work, a Variable Step Size Radial Basis Functional Network-based Adaptive Fuzzy Logic Controller (VSSDE-AFLC) is proposed for tracking the peak power point of the fuel cell system. The merits of the proposed Maximum Power Point Tracking (MPPT) controller are high tracing speed of functioning point of the fuel cell, more flexibility, high abundant, acceptable oscillations across MPP, and less dependency on modeling of the fuel stack. Also, the single switch converter is utilized for increasing the voltage supply of the fuel cell. The features of the proposed converter are wide input operation, less voltage stress, high supply voltage conversion ratio, and good dynamic response. The proposed fuel cell-dependent boost converter is implemented by utilizing the MATLAB/Simulink software, and the converter is tested successfully by using the desired programmable DC supply.
Keywords: Boost converter, conversion ratio, duty cycle, fast tracing speed, high voltage gain, fewer voltage ripples, and fast dynamic response
DOI: 10.3233/JIFS-224007
Journal: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 4, pp. 6303-6321, 2023
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