Fpga-based implementation of an optimization algorithm to maximize the productivity of a microbial electrolysis cell

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Abstract

In this work, the design of the hardware architecture to implement an algorithm for optimizing the Hydrogen Productivity Rate (HPR) in a Microbial Electrolysis Cell (MEC) is presented. The HPR in the MEC is maximized by the golden section search algorithm in conjunction with a super-twisting controller. The development of the digital architecture in the implementation step of the optimization algorithm was developed in the Very High Description Language (VHDL) and synthesized in a Field Programmable Gate Array (FPGA). Numerical simulations demonstrated the feasibility of the proposed optimization strategy embedded in an FPGA Cyclone II. Results showed that only 21% of the total logic elements, 5.19% of dedicated logic registers, and 64% of the total eight-bits multipliers of the FPGA were used. On the other hand, the estimated power consumption required by the FPGA-embedded optimization algorithm was only 146 mW.

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Colín-Robles, J. de J., Torres-Zúñiga, I., Ibarra-Manzano, M. A., & Alcaraz-González, V. (2021). Fpga-based implementation of an optimization algorithm to maximize the productivity of a microbial electrolysis cell. Processes, 9(7). https://doi.org/10.3390/pr9071111

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