Real-Time Performance Optimization and Diagnostics during Long-Term Operation of a Solid Anolyte Microbial Fuel Cell Biobattery

Abstract

This study describes a novel approach for real-time energy harvesting and performance diagnostics of a solid anolyte microbial fuel cell (SA-MFC) representing a prototype smart biobattery. The biobattery power output was maximized in real time by combining intermittent power generation with a Perturbation-and-Observation algorithm for maximum power point tracking. The proposed approach was validated by operating the biobattery under a broad range of environmental conditions affecting power production, such as temperature (4–25 °C), NaCl concentration (up to 2 g L⁻¹), and carbon source concentration. Real-time biobattery performance diagnostics was achieved by estimating key internal parameters (resistance, capacitance, open circuit voltage) using an equivalent electrical circuit model. The real time optimization approach ensured maximum power production during 388 days of biobattery operation under varying environmental conditions, thus confirming the feasibility of biobattery application for powering small electronic devices in field applications.

Key findings

• ▸Real-time energy harvesting and performance diagnostics were achieved using a Perturbation-and-Observation algorithm for maximum power point tracking.
• ▸The biobattery power output was maximized in real-time under a broad range of environmental conditions, including temperature (4–25 °C), NaCl concentration (up to 2 g L⁻¹), and carbon source concentration.
• ▸Real-time biobattery performance diagnostics was achieved by estimating key internal parameters (resistance, capacitance, open circuit voltage) using an equivalent electrical circuit model.

Keywords

Identifiers

DOI

10.3390/batteries5010009

Journal

Batteries

Year

2019