Boosting microbial fuel cell performance by combining with an external supercapacitor

Microbial Fuel Cells (MFC) technology finds space as a promising technology as a green alternative power-generating device, by the possibility to convert organic matter directly into electricity by microbially catalysed reactions, especially for the potential of the simultaneous treatment of wastewaters. Despite the studies that were carried out over the decades, MFCs still provide insufficient power and current densities in order to be commercially attractive in the energy market. Scientific community today pursues two main strategies in order to increase the overall performance output of the MFC. The first is to support the cells with an external supercapacitor (SC), which is able to accept and deliver charge much faster than normal capacitors, thanks to the use of an electrostatic double-layer capacitance, in combination with pseudocapacitance. The second is to implement directly the SC into the MFC, by using carbon electrodes with high surface area, similar to the SC. Both strategies are eventually supported by the use of charge boosters, respect to the application of the MFC. Galvanostatic measures for the MFC and SCs are performed at different currents, alone and by integration of both devices. The SCs used have a capacitance respectively of 1F, 3F and 6F. Subsequently, a stack of MFCs is assembled and paired to a 3F SC, in order to power an ambient diffuser, able to spray at intervals with a can and a controller. In conclusion, the use of a SC in parallel to the MFCs increases the overall performance of the system. The SC remove the discharge current limit of the MFC and increases the energy and power delivered by the system, allowing it to power for a certain time the ambient diffuser successfully. The key factor highlighted by the final experiment was the insufficient charging time of the SC, resulting finally in a voltage that is inadequate to power the device. Further studies are therefore necessary to improve the performance of the MFCs.

Development of an innovative non rule-based energy management strategy for a Hybrid Electric Vehicle, structured for predictive driving controls based on external information knowledge

Recently, the interest of the automotive market for hybrid vehicles has increased due to the more restrictive pollutants emissions legislation and to the necessity of decreasing the fossil fuel consumption, since such solution allows a consistent improvement of the vehicle global efficiency. The term hybridization regards the energy flow in the powertrain of a vehicle: a standard vehicle has, usually, only one energy source and one energy tank; instead, a hybrid vehicle has at least two energy sources. In most cases, the prime mover is an internal combustion engine (ICE) while the auxiliary energy source can be mechanical, electrical, pneumatic or hydraulic. It is expected from the control unit of a hybrid vehicle the use of the ICE in high efficiency working zones and to shut it down when it is more convenient, while using the EMG at partial loads and as a fast torque response during transients. However, the battery state of charge may represent a limitation for such a strategy. That’s the reason why, in most cases, energy management strategies are based on the State Of Charge, or SOC, control. Several studies have been conducted on this topic and many different approaches have been illustrated. The purpose of this dissertation is to develop an online (usable on-board) control strategy in which the operating modes are defined using an instantaneous optimization method that minimizes the equivalent fuel consumption of a hybrid electric vehicle. The equivalent fuel consumption is calculated by taking into account the total energy used by the hybrid powertrain during the propulsion phases. The first section presents the hybrid vehicles characteristics. The second chapter describes the global model, with a particular focus on the energy management strategies usable for the supervisory control of such a powertrain. The third chapter shows the performance of the implemented controller on a NEDC cycle compared with the one obtained with the original control strategy.

Optimal bidding strategies of an electric vehicle aggregator in an electricity market

In recent years Electric Vehicles (EVs) are getting more importance as future transport systems, due to the increase of the concerns relevant to the greenhouse gases emission and the use fossil fuel. The management of the charging and discharging process of EVs could provide new business model for participating in the electricity markets. Moreover, vehicle to grid systems have the potential of increasing utility system flexibility. This thesis develops some models for the optimal integration of the EVs in the electricity market. In particular, the thesis focuses on the optimal bidding strategy of an EV aggregator participating to both the day ahead market and the secondary reserve market. The aggregator profit is maximized taking into account the energy balance equation, as well as the technical constraints of energy settlement, power supply and state of charge of the EVs. The results obtained by using the GAMS (General Algebraic Modelling System) environment are presented and discussed.