A Novel Single Sensor Variable Step Size Maximum Power Point Tracking for Proton Exchange Membrane Fuel Cell Power System

Fuel Cells ◽  
2019 ◽  
Vol 19 (2) ◽  
pp. 177-189 ◽  
Author(s):  
A. Harrag ◽  
H. Bahri
Author(s):  
Jianxin Liu ◽  
Tiebiao Zhao ◽  
YangQuan Chen

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.


2021 ◽  
Vol 24 (1) ◽  
pp. 43-48
Author(s):  
Abdelghani Harrag

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.


IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Jye Yun Fam ◽  
Shen Yuong Wong ◽  
Hazrul Mohamed Basri ◽  
Mohammad Omar Abdullah ◽  
Kasumawati Lias ◽  
...  

2019 ◽  
Vol 16 (2) ◽  
pp. 740-744
Author(s):  
R. Geethamani ◽  
C. Pavithra ◽  
B. Niranjana ◽  
V. Gomathy ◽  
P. Chitra

A Variable step size Incremental resistance algorithm for PV system was designed for maximum power point tracking. The outputs are generated with help of MATLAB/SIMLUNK. The performance of the PV system for partial shading condition was observed. The output for the system was found to be more efficient and attains stability much faster than any other controller. The power output can be controlled by varying the scaling factor.


Sign in / Sign up

Export Citation Format

Share Document