In this work, the effect of the external load on the current and power generation, as well as on the pollutant removal by microbial fuel cells (MFCs), has been studied by step-wise modifying the external load. The load changes included a direct scan, in which the external resistance was increased from 120 Ω to 3300 Ω, and a subsequent reverse scan, in which the external resistance was decreased back to 120 Ω. The reduction in the current, experienced when increasing the external resistance, was maintained even in the reverse scan when the external resistance was step-wise decreased. Regarding the power exerted, when the external resistance was increased below the value of the internal resistance, an enhancement in the power exerted was observed. However, when operating near the value of the internal resistance, a stable power exerted of about 1.6 µW was reached. These current and power responses can be explained by the change in population distribution, which shifts to a more fermentative than electrogenic culture, as was confirmed by the population analyses. Regarding the pollutant removal, the effluent chemical oxygen demand (COD) decreased when the external resistance increased up to the internal resistance value. However, the effluent COD increased when the external resistance was higher than the internal resistance. This behavior was maintained in the reverse scan, which confirmed the modification in the microbial population of the MFC.

The paper describes a novel approach in battery storage system modelling. Different types of lithium-ion batteries exhibit differences in performance due to the battery anode and cathode materials being the determining factors in the storage system performance. Because of this, the influence of model parameters on the model accuracy can be different for different battery types. These models are used in battery management system development for increasing the accuracy of SoC and SoH estimation. The model proposed in this work is based on Tremblay model of the lithium-ion battery. The novelty of the model lies in the approach used for parameter estimation as a function of battery physical properties. To make the model perform more accurately, the diffusion resistance dependency on the battery current and the Peukert effect were also included in the model. The proposed battery model was validated using laboratory measurements with a LG JP 1.5 lithium-ion battery. Additionally, the proposed model incorporates the influence of the battery charge and discharge current level on battery performance.

This paper presents an innovative approach to the design of a forthcoming, fully electric-powered cargo vessel. This work begins by defining problems that need to be solved when designing vessels of this kind. Using available literature and market research, a solution for the design of a power management system and a battery management system for a cargo vessel of up to 1504 TEU capacity was developed. The proposed solution contains an innovative approach with three parallel energy sources. The solution takes into consideration the possible necessity for zero-emission work with the optional function of operation as an autonomous vessel. Energy storage system based on lithium-ion battery banks with a possibility of expanding the capacity is also described in this work as it is the core part of the proposed solution. It is estimated that the operation range for zero-emission work mode of up to 136 nautical miles can be achieved through the application of all fore-mentioned parts.

The energy contained in wastewaters has been identified as a promising sustainable energy resource that could be harvested by using microbial fuel cells (MFC). When dealing with real wastewaters, the MFCs should be able to manage high flow rates and flow rates fluctuations. In this work, the short-term effects of the influent flow rate variations on the performance of a microbial fuel cell has been studied. With this aim, the influent flow rate was stepwise increased from 0.72 to 7.2 L/d and then stepwise decreased. The obtained results indicate that, on the one hand, an increase in the influent flow rate leads to higher chemical oxygen demand removal rates up to 396 g/(L/d) and higher electric power generation almost 18 mW/m², but to lower coulombic efficiencies. On the other hand, the reduction of the flow rate increases the coulombic efficiencies, as well as the percentage of chemical oxygen demand removed, but decreases electric power generation. In the short-term, the exposition to higher influent flow rates causes the growth of the microbial population of the MFC, the growth of the non-electrogenic microorganisms being higher than that of the electrogenic ones. The higher growth of non-electrogenic microorganisms may lead to lower coulombic efficiencies.

This paper presents a static electrical model developed to analyze results from the Test Without Active Gases (TWAG) procedure, which characterizes fuel cell behavior in the absence of electrochemically active gases. The model topology is inspired by electric double-layer supercapacitor circuits and was derived from first principles using Lagrangian formalism. It was validated using five experimental TWAG discharge curves recorded at temperatures between 40°C and 120°C. Despite its simplicity and low computational cost, the model achieved satisfactory accuracy. The extracted parameters indicate potential for further refinement, such as introducing temperature-dependent components. The approach provides insight into the intrinsic electrochemical properties of high-temperature proton exchange membrane fuel cells in states without active gases and may serve as a foundation for broader diagnostic and modeling applications. Future developments may include extending the RC circuit, incorporating nonlinear elements, or applying the model to other fuel cell technologies. Testing on deliberately degraded cells could also help correlate model parameters with cell health.