FPGA-Based Implementation of an Optimization Algorithm to Maximize the Productivity of a Microbial Electrolysis Cell
| Autor: | Victor Alcaraz-Gonzalez, Ixbalank Torres-Zúñiga, Mario A. Ibarra-Manzano, José de Jesús Colín-Robles |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Computer science
hydrogen production Bioengineering 02 engineering and technology TP1-1185 Control theory Search algorithm VHDL 0202 electrical engineering electronic engineering information engineering Microbial electrolysis cell Chemical Engineering (miscellaneous) Field-programmable gate array QD1-999 golden section search FPGA computer.programming_language Hardware architecture super-twisting controller business.industry Process Chemistry and Technology Chemical technology 020208 electrical & electronic engineering MEC 021001 nanoscience & nanotechnology Digital architecture Chemistry Golden section search 0210 nano-technology business computer Computer hardware online optimization |
| Zdroj: | Processes, Vol 9, Iss 1111, p 1111 (2021) Processes Volume 9 Issue 7 |
| ISSN: | 2227-9717 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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