Optimization of Microbial Fuel Cells: Enhancing Electrical Output Through Gradient-Based Optimization

Abstract

Microbial Fuel Cells (MFCs) are environment-friendly devices to generate energy through microbial metabolism of the chemical energy of organic compounds. Few of the critical challenges of implementing MFCs are their low power density, high internal resistance, and poor electron transport. These factors are major drawbacks to the MFCs efficiency and ability to scale up MFCs. The proposed work aims to enhance the MFC performance by optimizing the proportions of key operational parameters to overcome the implementation challenges. These parameters include Substrate Concentration $(S)$, Anodophilic Biomass $(x_{a})$, Methanogenic Biomass $(x_{m})$, and Oxidized Mediator $(M_{ox})$. The parameters are optimized using a Gradient Based Optimization (GBO). During the optimization process, it was imperative to establish a sound mathematical model that predicted MFC's biological and physical behavior. With the implementation of the GBO algorithm, the output current is enhanced by 8. 89 percent. The results shows that promising future of the proposed method.

Key findings

• ▸Low power density, high internal resistance, and poor electron transport are critical challenges in implementing MFCs.
• ▸Optimizing substrate concentration, anodophilic biomass, methanogenic biomass, and oxidized mediator can overcome these challenges.
• ▸The proposed method enhances the MFC's output current by 8.89% using a gradient-based optimization algorithm.

Keywords

Identifiers

DOI

10.1109/ICRAI62391.2024.10894349

Journal

2024 International Conference on Robotics and Automation in Industry (ICRAI)

Year

2024