Modeling and Control of Fuel Cell Using Artificial Neural Networks

Hayder Sabah Abad Al-Amir; Hayder Abed Dahd; Eiman Ali Eh. Sheet

doi:10.31026/j.eng.2015.12.08

Article Details

Modeling and Control of Fuel Cell Using Artificial Neural Networks

Authors:

Hayder Sabah Abad Al-Amir | Hayder Abed Dahd | Eiman Ali Eh. Sheet

Publisher:

University of Baghdad

Journal:

Journal of Engineering Vol.21 Issue 12, pp.124-138

Document Type:

Article

Publication Date:

1/2015

Document Language:

English

Document ID (Org No.):

2001380980

pISSN:

2520-3339

DOI:

10.31026/j.eng.2015.12.08

Keywords:

Abstract:

 This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback control system using PID controller to stabilize the fuel cell voltage. Particle swarm optimization technique is used to tune the PID controller gains. The voltage error and hydrogen flow rate are input and the actuator of the PID controller respectively. Simulation results showed that using PID controller with proposed model of fuel cell can successfully improve system performance in tracking output voltage under different operating conditions.

Article Details

Modeling and Control of Fuel Cell Using Artificial Neural Networks

Authors:

Hayder Sabah Abad Al-Amir | Hayder Abed Dahd | Eiman Ali Eh. Sheet

Publisher:

University of Baghdad

Journal:

Journal of Engineering Vol.21 Issue 12, pp.124-138

Document Type:

Article

Publication Date:

1/2015

Document Language:

English

Document ID (Org No.):

2001380980

pISSN:

2520-3339

DOI:

10.31026/j.eng.2015.12.08

fuel cell

hydrogen fuel

renewable energy

artificial neural networks

PID

Particle swarm optimization

Issues

Article Details

Modeling and Control of Fuel Cell Using Artificial Neural Networks

Authors: Hayder Sabah Abad Al-Amir | Hayder Abed Dahd | Eiman Ali Eh. Sheet

Publisher: University of Baghdad

Journal: Journal of Engineering Vol.21 Issue 12, pp.124-138

Document Type: Article

Publication Date: 1/2015

Document Language: English

Document ID (Org No.): 2001380980

pISSN: 2520-3339

DOI: 10.31026/j.eng.2015.12.08

fuel cell

hydrogen fuel

renewable energy

artificial neural networks

PID

Particle swarm optimization

Issues

Authors:

Hayder Sabah Abad Al-Amir | Hayder Abed Dahd | Eiman Ali Eh. Sheet

Publisher:

University of Baghdad

Journal:

Journal of Engineering Vol.21 Issue 12, pp.124-138

Document Type:

Article

Publication Date:

1/2015

Document Language:

English

Document ID (Org No.):

2001380980

pISSN:

2520-3339

DOI:

10.31026/j.eng.2015.12.08