Optimal Parameter Identification of Single-Sensor Fractional Maximum Power Point Tracker for Thermoelectric Generator

Abdul Ghani Olabi, Hegazy Rezk, Enas Taha Sayed, Tabbi Awotwe, Samah Ibrahim Alshathri, Mohammad Ali Abdelkareem

Research output: Contribution to journalArticlepeer-review


A thermoelectric generator (TEG) is used for converting temperature difference and into DC directly to electric energy based on the Seebeck effect. This new technology has attracted researchers of sustainable energy. The energy obtained from the TEG depends on the temperature difference between the two sides of the TEG. A reliable MPP “maximum power point” tracker (MPPT) is mandatory to guarantee that the TEG is working close to the MPP under different operational conditions. There are two common methods that have been widely used to track the MPP: hill climbing (HC) and incremental conductance (INR). The HC method is very fast in tracking the MPP; however, oscillation can occur under a high steady state. On the contrary, the INR method needs more time to track the MPP but does not oscillate around the MPP. To overcome these issues, fractional control is adopted. Furthermore, the proposed MPPT requires only a single current sensor, as opposed to conventional MPPTs, which require at least two sensors: current and voltage sensors. The cost of the control system is reduced when the number of sensors is reduced. Hunger games search optimization is used to estimate the parameters of a single sensor optimized fractional MPPT (OFMPPT). During the optimization process, three parameters were assigned as decision variables: proportional gain, integral gain, and order, with the objective function being the TEG’s energy. The results demonstrated the superiority of OFMPPT in both transient and steady state compared to HC and INR.
Original languageEnglish
Article number5054
Number of pages13
Issue number6
Early online date13 Mar 2023
Publication statusPublished - Mar 2023

Bibliographical note

Copyright © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

Funding: This research was funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP2023R197), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.


  • MPPT
  • fractional control
  • single sensor
  • thermoelectric generator


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