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

Harrag, Abdelghani; Bahri, Hamza

doi:10.1002/fuce.201800122

Cited by 17 publications

(15 citation statements)

References 41 publications

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“…In this study, the mean squared errors (MSE) algorithm has been used to train the neural network controller by minimizing the overall error measure between the data generated previously using the conventional single sensor MPPT [26] and the neural networks output. Figure 3 shows the MSE evolution.…”

Section: Neural Network Trainingmentioning

confidence: 99%

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

Harrag¹

2021

JNMES

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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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Section: Neural Network Trainingmentioning

confidence: 99%

“…The performance of the implemented neural network single sensor MPPT Matlab/Simulink model has been compared to the performance of the single sensor MPPT studied previously [26] considering two test cases: • Case 1: Fast temperature (T) changing;…”

Section: Nominal Voltage Vg (V) 47mentioning

confidence: 99%

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

Harrag¹

2021

JNMES

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“…Harrag et al addressed a variable step fuzzy based MPPT controller, but the setting of fuzzy rules and proportional quantization factors needed the support of practical experience 24 . Harrag et al proposed a single sensor variable step size MPPT method for PEMFC, although the steady state performance could meet the demand, the dynamic performance was not particularly satisfactory 25 . Liu et al designed a fractional order high pass filter (FOHPF) to improve traditional extremum seeking control (ESC), but the response speed was difficult to guarantee 26 .…”

Section: Introductionmentioning

confidence: 99%

Maximum power point tracking of PEMFC based on hybrid artificial bee colony algorithm with fuzzy control

2022

Sci Rep

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Maximum power point tracking (MPPT) is an effective method to improve the power generation efficiency and power supply quality of a proton exchange membrane fuel cell (PEMFC). Due to the inherent nonlinear characteristics of PEMFC, conventional MPPT methods are often difficult to achieve a satisfactory control effect. Considering this, artificial bee colony algorithm combining fuzzy control (ABC-fuzzy) was proposed to construct a MPPT control scheme for PEMFC. The global optimization ability of ABC algorithm was used to approach the maximum power point of PEMFC and solve the problem of falling into local optimization, and fuzzy control was used to eliminate the problems of large overshoot and slow convergence speed of ABC algorithm. The testing results show that compared with perturb & observe algorithm, conductance increment and ABC methods, ABC-fuzzy method can make PEMFC obtain greater output power, faster regulation speed, smaller steady-state error, less oscillation and stronger anti-interference ability. The MPPT scheme based on ABC-fuzzy can effectively realize the maximum power output of PEMFC, and plays an important role in improving the service life and power supply efficiency of PEMFC.

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“…A single sensor based MPPT controller was proposed for 7 kW PEMFC under variable temperature and variable pressure condition in Ref. 8. The cost of the controller was reduced drastically which intern reduces the complexity of the system.…”

Section: Introductionmentioning

confidence: 99%

A variable step size fuzzy logic controller based maximum power point tracking controller for proton exchange membrane fuel cell powered resonant pulse width modulation high step up converter with multicarrier sinusoidal pulse width modulation inverter fed induction motor

Karthikeyan¹,

Sundararaju²,

Palanisamy

2021

Int Trans Electr Energ Syst

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Summary A variable step size Fuzzy logic based MPPT algorithm is proposed to ensure maximum power extraction from 1.26 kW Proton Exchange Membrane Fuel Cell (PEMFC). The Resonant PWM High Step up Converter (RPHC) is designed with soft switching capability to boost PEMFC output voltage and ensured optimum power tracking during dynamic operating condition by triggering RPHC switches with pulses generated from MPPT controller. The proposed variable step size FLC controller results are compared with conventional P&O and IC algorithm. To run a three‐phase induction motor, three‐phase Voltage source inverter connected at the output port of step up converter whose switching pattern is given by Multicarrier Sinusoidal Pulse Width Modulation (MSPWM) controller which reduces THD in output voltage and current. A detailed simulation analysis is done with MATLAB/Simulink environment and discussed the results. The hardware prototype model is implemented to validate the simulation results.

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

Cited by 17 publications

References 41 publications

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

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

Maximum power point tracking of PEMFC based on hybrid artificial bee colony algorithm with fuzzy control

A variable step size fuzzy logic controller based maximum power point tracking controller for proton exchange membrane fuel cell powered resonant pulse width modulation high step up converter with multicarrier sinusoidal pulse width modulation inverter fed induction motor

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