Distributed Intelligence in Autonomous PEM Fuel Cell Control

Abel Rubio (), Wilton Agila, Leandro González and Jonathan Aviles-Cedeno
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Abel Rubio: Center for Research, Development and Innovation of Computer Systems (CIDIS)—Faculty of Engineering in Electricity and Computation (FIEC), Escuela Superior Politécnica del Litoral (ESPOL), Guayaquil P.O. Box 09-01-5863, Ecuador
Wilton Agila: Center for Research, Development and Innovation of Computer Systems (CIDIS)—Faculty of Engineering in Electricity and Computation (FIEC), Escuela Superior Politécnica del Litoral (ESPOL), Guayaquil P.O. Box 09-01-5863, Ecuador
Leandro González: Center for Automation and Robotics (CSIC-UPM), Ctra. Campo Real km. 0,200, 28500 Arganda del Rey, Spain
Jonathan Aviles-Cedeno: Center for Research, Development and Innovation of Computer Systems (CIDIS)—Faculty of Engineering in Electricity and Computation (FIEC), Escuela Superior Politécnica del Litoral (ESPOL), Guayaquil P.O. Box 09-01-5863, Ecuador

Energies, 2023, vol. 16, issue 12, 1-25

Abstract: A combination of perceptive and deliberative processes is necessary to ensure the efficient and autonomous control of proton exchange membrane fuel cells (PEMFCs) under optimal humidification conditions. These processes enable monitoring and control tasks across various application scenarios and operating conditions. Consequently, it becomes crucial to adjust parameter values corresponding to different states of the PEMFC during its operation. In this context, this work presents the design and development of an architecture for the control and management of a PEMFC with a maximum power output of 500 [W] based on intelligent agents operating under optimal conditions (membrane humidification). The proposed architecture integrates perception and action algorithms that leverage sensory and contextual information using heuristic algorithms. It adopts a hierarchical structure with distinct layers, each featuring varying time windows and levels of abstraction. Notably, this architecture demonstrates its effectiveness in achieving the desired energy efficiency objective, as evidenced by successful validation tests conducted with different electrical power values delivered by the fuel cell, encompassing three distinct operating states (dry, normal, and flooded). An exemplary application of this scheme is the dynamic control of the humidification of the polymeric membrane, which further highlights the capabilities of this architecture.

Keywords: PEM fuel cell; distributed intelligence; fuzzy controller; fuzzy numbers; agent-based control; expert agent; intelligent agent (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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