Maximum power point tracking of a proton exchange membrane fuel cell system using PSO-PID controller

2017 ◽  
Vol 42 (32) ◽  
pp. 20430-20443 ◽  
Author(s):  
S. Ahmadi ◽  
Sh. Abdi ◽  
M. Kakavand
Keyword(s):  
Pid Controller ◽  
Proton Exchange Membrane ◽  
Cell System ◽  
Proton Exchange ◽  
Fuel Cell System ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point ◽  
Exchange Membrane

scholarly journals Predictive Maximum Power Point Tracking for Proton Exchange Membrane Fuel Cell System

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Jye Yun Fam ◽  
Shen Yuong Wong ◽  
Hazrul Mohamed Basri ◽  
Mohammad Omar Abdullah ◽  
Kasumawati Lias ◽  
...  
Keyword(s):  
Fuel Cell ◽  
Proton Exchange Membrane ◽  
Cell System ◽  
Proton Exchange ◽  
Fuel Cell System ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point ◽  
Exchange Membrane

Maximum Power Point Tracking of Proton Exchange Membrane Fuel Cell With Fractional Order Filter and Extremum Seeking Control

2015 ◽  
Author(s):  
Jianxin Liu ◽  
Tiebiao Zhao ◽  
YangQuan Chen
Keyword(s):  
Proton Exchange Membrane ◽  
Proton Exchange ◽  
Extremum Seeking ◽  
Maximum Power Point ◽  
Pass Filter ◽  
Extremum Seeking Control ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point ◽  
Exchange Membrane

Proton Exchange Membrane FC (PEMFC) is widely recognized as a potentially renewable and green energy source based on hydrogen. Maximum power point tracking (MPPT) is one of the most important working conditions to be considered. In order to improve the searching performance such as convergence and robustness under disturbance and uncertainty, a kind of fractional order low pass filter (FOLPF) is applied for the MPPT controller design based on general Extremum Seeking Control (ESC). The controller is designed with FOLPF and high pass filter (HPF) substituting the normal LPF and HPF in the original ESC design. With this FOLPF ESC, better convergence and smooth performance is gained while maintaining the robust specifications. Simulation results are included to validate the proposed new FOLPF ESC scheme under disturbance and comparisons between FOLPF ESC and general ESC method are also provided.

scholarly journals Fuzzy logic MPPT control algorithm for a Proton Exchange Membrane Fuel Cells System

2021 ◽  
Vol 03 (01) ◽  
pp. 13-22
Author(s):  
Badreddine KANOUNI ◽  
◽  
Abd Essalam BADOUD ◽  
Saad MEKHILEF ◽  
◽  
...  
Keyword(s):  
Fuel Cells ◽  
Fuel Cell ◽  
Proton Exchange Membrane ◽  
Cell System ◽  
Proton Exchange ◽  
Maximum Power ◽  
Fuel Cell System ◽  
Maximum Power Point ◽  
Power Point ◽  
Exchange Membrane

Fuel cells output power depends on the operating conditions, including cell temperature, oxygen pressure, hydrogen pressure, tempureter . In each particular condition, there is only one unique operating point for a fuel cell system with the maximum output. Thus, a maximum power point tracking (MPPT) controller is needed to increase the efficiency of the PEMFC systems. In this paper an efficient method fuzzy logic controller is proposed for MPPT of the proton exchange membrane (PEM) fuel cells, boost converter. FLC adjusts the operating point of the PEM fuel cell to the maximum power by tuning of the boost converter duty cycle. To demonstrate the performance of the proposed algorithm, simulation results are sumulated in two cases, in normel condution and variation in temperature .the FLC algorithm with fast convergence, high accuracy and very low power fluctuations tracks the maximum power point of the fuel cell system

scholarly journals Novel Neural network single sensor MPPT for Proton Exchange Membrane Fuel Cell

2021 ◽  
Vol 24 (1) ◽  
pp. 43-48
Author(s):  
Abdelghani Harrag
Keyword(s):  
Neural Network ◽  
Fuel Cell ◽  
Proton Exchange Membrane ◽  
Proton Exchange ◽  
Maximum Power ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Single Sensor ◽  
Power Point ◽  
Exchange Membrane

This paper presents a new neural network single sensor maximum power point tracking algorithm controlling the DC-DC boost converter to guarantee the transfer of the proton exchange membrane fuel cell maximum generated power to the load. The implemented neural network single sensor controller has been developed and trained firstly in offline mode using single sensor maximum power point tracking data obtained previously; and secondly used in online mode to track the maximum output power of the fuel cell power system. Comparative simulation results prove the superiority of the proposed neural network single sensor maximum power point compared to the single sensor one especially in transit response reducing by the way the overshoot and the tracking time which leads to an overall energy losses reduction. In addition, the implemented neural network single sensor MPPT employs only one sensor which will reduce the complexity and the cost of PEM fuel cell power system. To our knowledge, this study is a pioneering work using a neural network single sensor controller as PEM fuel cell MPPT.

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