A novel cascade control of PEMFC: Regulation of stack voltage and air breathing subsystem
The proton exchange membrane fuel cell (PEMFC) stack is an excellent source of clean energy for electric vehicles with zero carbon footprint. The abrupt changes in power demand in automotive applications can adversely impact the oxygen excess ratio (OER) and stack voltage. Therefore, this study aims...
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| Vydáno v: | International journal of hydrogen energy Ročník 102; s. 1530 - 1545 |
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| Hlavní autoři: | , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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Elsevier Ltd
10.02.2025
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| Témata: | |
| ISSN: | 0360-3199 |
| On-line přístup: | Získat plný text |
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| Abstract | The proton exchange membrane fuel cell (PEMFC) stack is an excellent source of clean energy for electric vehicles with zero carbon footprint. The abrupt changes in power demand in automotive applications can adversely impact the oxygen excess ratio (OER) and stack voltage. Therefore, this study aims to design an intelligent cascade control framework to ensure the durable and efficient operation of PEMFC. A novel mixed locally recurrent fuzzy neural network proportional-integral-derivative (RFNN-PID) control architecture is proposed. The RFNN-PID and proportional-integral (PI) controllers are employed as the primary and secondary controllers in cascaded loops, respectively. Four other cascaded schemes with fuzzy PID and PI (FPID/PI), two-degree-of-freedom PID & two-degree-of-freedom PI (2DOF-PID/2DOF-PI), fractional order PID & fractional order PI (FOPID/FOPI), and PID/PI controllers are designed for comparison. The controller parameters are optimised using the mayfly algorithm (MA) to minimise the integral time absolute error (ITAE). The findings suggest the cascaded RFNN-PID/PI strategy yields the fastest voltage regulation and minimum ITAE (0.3018 s & 3.406), as compared to cascaded FPID/PI (0.4087 s & 4.273), 2DOF-PID/2DOF-PI (0.4213 s & 6.626), FOPID/FOPI (0.8135 s & 9.083) and PID/PI (1.066 s & 10.89). The proposed controller also exhibits robust performance in the presence of disturbance and noise. Hence, it is concluded that the adaptive RFNN-PID/PI controller efficiently controls the voltage and regulates OER even in adverse operating conditions.
[Display omitted]
•A novel cascaded control is developed for the regulation of PEMFC.•RFNN-PID and PI are used as primary and secondary controllers, respectively.•The Mayfly algorithm is utilised to estimate the parameters of the controllers.•Detailed analysis with varying load, noise and disturbance is exhibited. |
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| AbstractList | The proton exchange membrane fuel cell (PEMFC) stack is an excellent source of clean energy for electric vehicles with zero carbon footprint. The abrupt changes in power demand in automotive applications can adversely impact the oxygen excess ratio (OER) and stack voltage. Therefore, this study aims to design an intelligent cascade control framework to ensure the durable and efficient operation of PEMFC. A novel mixed locally recurrent fuzzy neural network proportional-integral-derivative (RFNN-PID) control architecture is proposed. The RFNN-PID and proportional-integral (PI) controllers are employed as the primary and secondary controllers in cascaded loops, respectively. Four other cascaded schemes with fuzzy PID and PI (FPID/PI), two-degree-of-freedom PID & two-degree-of-freedom PI (2DOF-PID/2DOF-PI), fractional order PID & fractional order PI (FOPID/FOPI), and PID/PI controllers are designed for comparison. The controller parameters are optimised using the mayfly algorithm (MA) to minimise the integral time absolute error (ITAE). The findings suggest the cascaded RFNN-PID/PI strategy yields the fastest voltage regulation and minimum ITAE (0.3018 s & 3.406), as compared to cascaded FPID/PI (0.4087 s & 4.273), 2DOF-PID/2DOF-PI (0.4213 s & 6.626), FOPID/FOPI (0.8135 s & 9.083) and PID/PI (1.066 s & 10.89). The proposed controller also exhibits robust performance in the presence of disturbance and noise. Hence, it is concluded that the adaptive RFNN-PID/PI controller efficiently controls the voltage and regulates OER even in adverse operating conditions.
[Display omitted]
•A novel cascaded control is developed for the regulation of PEMFC.•RFNN-PID and PI are used as primary and secondary controllers, respectively.•The Mayfly algorithm is utilised to estimate the parameters of the controllers.•Detailed analysis with varying load, noise and disturbance is exhibited. |
| Author | Mohan, Vijay Panjwani, Bharti Panjwani, Bhawna Yadav, Jyoti Kumar, Pankaj |
| Author_xml | – sequence: 1 givenname: Bharti surname: Panjwani fullname: Panjwani, Bharti email: bharti.cs@sode-edu.in organization: Department of Computer Science & Engineering, Shri Madhwa Vadiraja Institute of Technology and Management, Bantakal, Karnataka, India – sequence: 2 givenname: Jyoti orcidid: 0000-0002-6429-7742 surname: Yadav fullname: Yadav, Jyoti email: jyoti.yadav@nsut.ac.in organization: Department of ICE, Netaji Subhas University of Technology, Sector-3 Dwarka, New Delhi, India – sequence: 3 givenname: Pankaj surname: Kumar fullname: Kumar, Pankaj email: pankaj.kumar@manipal.edu organization: Department of Information and Communication Technology, Manipal Institute of Technology, Manipal Academy of Higher Education, Udupi, 576104, Karnataka, India – sequence: 4 givenname: Bhawna surname: Panjwani fullname: Panjwani, Bhawna email: id24resch11016@iith.ac.in organization: Center for Interdisciplinary Programs, Indian Institute of Technology, Hyderabad, India – sequence: 5 givenname: Vijay orcidid: 0000-0003-1457-2651 surname: Mohan fullname: Mohan, Vijay email: vijay.mohan@manipal.edu organization: Department of Mechatronics, Manipal Institute of Technology, Manipal Academy of Higher Education, Udupi, 576104, Karnataka, India |
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| Keywords | Fuzzy control Mayfly algorithm Hydrogen energy Proton exchange membrane fuel cell Recurrent fuzzy neural network |
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| Title | A novel cascade control of PEMFC: Regulation of stack voltage and air breathing subsystem |
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