IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v10y2022i10p1762-d820757.html
   My bibliography  Save this article

Simulation and State Feedback Control of a Pressure Swing Adsorption Process to Produce Hydrogen

Author

Listed:
  • Mario Martínez García

    (Centro Universitario de los Valles, Universidad de Guadalajara, Carretera Guadalajara-Ameca Km 45.5, Ameca 46600, Mexico)

  • Jesse Y. Rumbo Morales

    (Centro Universitario de los Valles, Universidad de Guadalajara, Carretera Guadalajara-Ameca Km 45.5, Ameca 46600, Mexico)

  • Gerardo Ortiz Torres

    (Centro Universitario de los Valles, Universidad de Guadalajara, Carretera Guadalajara-Ameca Km 45.5, Ameca 46600, Mexico)

  • Salvador A. Rodríguez Paredes

    (Sección de Estudios de Posgrado e Investigación de la ESIME U Azcapotzalco, Instituto Politécnico Nacional, Av. Luis Enrique Erro S/N, Unidad Profesional Adolfo López Mateos, Zacatenco, Alcaldía Gustavo A. Madero, Ciudad de México 07738, Mexico)

  • Sebastián Vázquez Reyes

    (Sección de Estudios de Posgrado e Investigación de la ESIME U Azcapotzalco, Instituto Politécnico Nacional, Av. Luis Enrique Erro S/N, Unidad Profesional Adolfo López Mateos, Zacatenco, Alcaldía Gustavo A. Madero, Ciudad de México 07738, Mexico)

  • Felipe de J. Sorcia Vázquez

    (Centro Universitario de los Valles, Universidad de Guadalajara, Carretera Guadalajara-Ameca Km 45.5, Ameca 46600, Mexico)

  • Alan F. Pérez Vidal

    (Centro Universitario de los Valles, Universidad de Guadalajara, Carretera Guadalajara-Ameca Km 45.5, Ameca 46600, Mexico)

  • Jorge S. Valdez Martínez

    (División Académica de Mecánica Industrial, Universidad Tecnológica Emiliano Zapata del Estado de Morelos, Av. Universidad Tecnológica No. 1, Col. Palo Escrito, Emiliano Zapata 62760, Mexico)

  • Ricardo Pérez Zúñiga

    (Sistema de Universidad Virtual de la Universidad de Guadalajara, Guadalajara 44430, Mexico)

  • Erasmo M. Renteria Vargas

    (Centro Universitario de los Valles, Universidad de Guadalajara, Carretera Guadalajara-Ameca Km 45.5, Ameca 46600, Mexico)

Abstract

One of the separation processes used for the production and purification of hydrogen is molecular sieve adsorption using the Pressure Swing Adsorption (PSA) method. The process uses two beds containing activated carbon and a sequence of four steps (adsorption, depressurization, purge, and repressurization) for hydrogen production and purification. The initial composition is 0.11 CO, 0.61 H 2 , and 0.28 CH 4 in molar fractions. The aim of this work is to bring the purity of hydrogen to 0.99 in molar fraction and implement controllers that can maintain the desired purity even in the presence of the disturbances that occur in the PSA process. The controller design (discrete PID and state feedback control) was based on the Hammerstein–Wiener model, which had an 80% fit over the rigorous PSA model. Both controllers were validated on a virtual plant of the PSA process, showing great performance and robustness against disturbances. The results obtained show that it is possible to follow the desired trajectory and attenuate double disturbances, while managing to maintain the purity of hydrogen at a value of 0.99 in molar fraction, which meets the international standards to be used as a biofuel.

Suggested Citation

  • Mario Martínez García & Jesse Y. Rumbo Morales & Gerardo Ortiz Torres & Salvador A. Rodríguez Paredes & Sebastián Vázquez Reyes & Felipe de J. Sorcia Vázquez & Alan F. Pérez Vidal & Jorge S. Valdez Ma, 2022. "Simulation and State Feedback Control of a Pressure Swing Adsorption Process to Produce Hydrogen," Mathematics, MDPI, vol. 10(10), pages 1-22, May.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:10:p:1762-:d:820757
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/10/10/1762/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/10/10/1762/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Vo, Nguyen Dat & Oh, Dong Hoon & Kang, Jun-Ho & Oh, Min & Lee, Chang-Ha, 2020. "Dynamic-model-based artificial neural network for H2 recovery and CO2 capture from hydrogen tail gas," Applied Energy, Elsevier, vol. 273(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Rumbo-Morales, Jesse Y. & Ortiz-Torres, Gerardo & Sarmiento-Bustos, Estela & Rosales, Antonio Márquez & Calixto-Rodriguez, Manuela & Sorcia-Vázquez, Felipe D.J. & Pérez-Vidal, Alan F. & Rodríguez-Cerd, 2024. "Purification and production of bio-ethanol through the control of a pressure swing adsorption plant," Energy, Elsevier, vol. 288(C).
    2. Raquel de Souza Deuber & Jéssica Marcon Bressanin & Daniel Santos Fernandes & Henrique Real Guimarães & Mateus Ferreira Chagas & Antonio Bonomi & Leonardo Vasconcelos Fregolente & Marcos Djun Barbosa , 2023. "Production of Sustainable Aviation Fuels from Lignocellulosic Residues in Brazil through Hydrothermal Liquefaction: Techno-Economic and Environmental Assessments," Energies, MDPI, vol. 16(6), pages 1-21, March.
    3. Gerardo Ortiz Torres & Jesse Yoe Rumbo Morales & Moises Ramos Martinez & Jorge Salvador Valdez-Martínez & Manuela Calixto-Rodriguez & Estela Sarmiento-Bustos & Carlos Alberto Torres Cantero & Hector M, 2023. "Active Fault-Tolerant Control Applied to a Pressure Swing Adsorption Process for the Production of Bio-Hydrogen," Mathematics, MDPI, vol. 11(5), pages 1-25, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gerardo Ortiz Torres & Jesse Yoe Rumbo Morales & Moises Ramos Martinez & Jorge Salvador Valdez-Martínez & Manuela Calixto-Rodriguez & Estela Sarmiento-Bustos & Carlos Alberto Torres Cantero & Hector M, 2023. "Active Fault-Tolerant Control Applied to a Pressure Swing Adsorption Process for the Production of Bio-Hydrogen," Mathematics, MDPI, vol. 11(5), pages 1-25, February.
    2. Zhang, Zhiwei & Vo, Dat-Nguyen & Nguyen, Tuan B.H. & Sun, Jinsheng & Lee, Chang-Ha, 2024. "Advanced process integration and machine learning-based optimization to enhance techno-economic-environmental performance of CO2 capture and conversion to methanol," Energy, Elsevier, vol. 293(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:10:y:2022:i:10:p:1762-:d:820757. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.