Nonlinear predictive control for durability enhancement and efficiency improvement in a fuel cell power system

© . This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/In this work, a nonlinear model predictive control (NMPC) strategy is proposed to improve the efficiency and enhance the durability of a proton exchange membrane fuel cell (PEMFC) power system. The PEMFC controller is based on a distributed parameters model that describes the nonlinear dynamics of the system, considering spatial variations along the gas channels. Parasitic power from different system auxiliaries is considered, including the main parasitic losses which are those of the compressor. A nonlinear observer is implemented, based on the discretised model of the PEMFC, to estimate the internal states. This information is included in the cost function of the controller to enhance the durability of the system by means of avoiding local starvation and inappropriate water vapour concentrations. Simulation results are presented to show the performance of the proposed controller over a given case study in an automotive application (New European Driving Cycle). With the aim of representing the most relevant phenomena that affects the PEMFC voltage, the simulation model includes a two-phase water model and the effects of liquid water on the catalyst active area. The control model is a simplified version that does not consider two-phase water dynamics.Peer ReviewedPostprint (author's final draft

Operating Point Optimization of a Hydrogen Fueled Hybrid Solid Oxide Fuel Cell-Steam Turbine (SOFC-ST) Plant

This paper presents a hydrogen powered hybrid solid oxide fuel cell-steam turbine (SOFC-ST) system and studies its optimal operating conditions. This type of installation can be very appropriate to complement the intermittent generation of renewable energies, such as wind generation. A dynamic model of an alternative hybrid SOFC-ST configuration that is especially suited to work with hydrogen is developed. The proposed system recuperates the waste heat of the high temperature fuel cell, to feed a bottoming cycle (BC) based on a steam turbine (ST). In order to optimize the behavior and performance of the system, a two-level control structure is proposed. Two controllers have been implemented for the stack temperature and fuel utilization factor. An upper supervisor generates optimal set-points in order to reach a maximal hydrogen efficiency. The simulation results obtained show that the proposed system allows one to reach high efficiencies at rated power levels.This work has been carried out in the Intelligent Systems and Energy research group of the University of the Basque Country (UPV/EHU) and has been supported by the UFI11/28 research grant of the UPV/EHU and by the IT677-13 research grant of the Basque Government (Spain) and by DPI2012-37363-CO2-01 research grant of the Spanish Ministry of Economy and Competitiveness

Synthetic biology and microdevices : a powerful combination

Recent developments demonstrate that the combination of microbiology with micro-and nanoelectronics is a successful approach to develop new miniaturized sensing devices and other technologies. In the last decade, there has been a shift from the optimization of the abiotic components, for example, the chip, to the improvement of the processing capabilities of cells through genetic engineering. The synthetic biology approach will not only give rise to systems with new functionalities, but will also improve the robustness and speed of their response towards applied signals. To this end, the development of new genetic circuits has to be guided by computational design methods that enable to tune and optimize the circuit response. As the successful design of genetic circuits is highly dependent on the quality and reliability of its composing elements, intense characterization of standard biological parts will be crucial for an efficient rational design process in the development of new genetic circuits. Microengineered devices can thereby offer a new analytical approach for the study of complex biological parts and systems. By summarizing the recent techniques in creating new synthetic circuits and in integrating biology with microdevices, this review aims at emphasizing the power of combining synthetic biology with microfluidics and microelectronics

Control-oriented modeling of dynamic thermal behavior and two‒phase fluid flow in porous media for PEM fuel cells

textThe driving force behind research in alternative clean and renewable energy has been the desire to reduce emissions and dependence on fossil fuels. In the United States, ground vehicles account for 30% of total carbon emission, and significantly contribute to other harmful emissions. This issue causes environmental concerns and threat to human health. On the other hand, the demand on fossil fuel grows with the increasing energy consumption worldwide. Particularly in the United States of America, transportation absorbs 75% of this energy source. There is an urgent need to reduce the transportation dependence on fossil fuel for the purpose of national security. Polymer electrolyte membrane (PEM) fuel cells are strong potential candidates to replace the traditional combustion engines. Even though research effort has transferred the fuel cell technology into real‒world vehicle applications, there are still several challenges hindering the fuel cell technology commercialization, such as hydrogen supply infrastructure, cost of the fuel cell vehicles, on‒board hydrogen storage, public acceptance, and more importantly the performance, durability, and reliability of the PEM fuel cell vehicles themselves. One of the key factors that affect the fuel cell performance and life is the run‒time thermal and water management. The temperature directly affects the humidification of the fuel cell stack and plays a critical role in avoiding liquid water flooding as well as membrane dehydration which affect the performance and long term reliability. There are many models exists in the literature. However, there are still lacks of control‒oriented modeling techniques that describe the coupled heat and mass transfer dynamics, and experimental validation is rarely performed for these models. In order to establish an in‒depth understanding and enable control design to achieve optimal performance in real‒time, this research has explored modeling techniques to describe the coupled heat and mass transfer dynamics inside a PEM fuel cell. This dissertation is to report our findings on modeling the temperature dynamics of the gas and liquid flow in the porous media for the purpose of control development. The developed thermal model captures the temperature dynamics without using much computation power commonly found in CFD models. The model results agree very well with the experimental validation of a 1.5 kW fuel cell stack after calibrations. Relative gain array (RGA) was performed to investigate the coupling between inputs and outputs and to explore the possibility of using a single‒input single‒output (SISO) control scheme for this multi‒input multi‒output (MIMO) system. The RGA analyses showed that SISO control design would be effective for controlling the fuel cell stack alone. Adding auxiliary components to the fuel cell stack, such as compressor to supply the pressurized air, requires a MIMO control framework. The developed model of describing water transport in porous media improves the modeling accuracy by adding catalyst layers and utilizing an empirically derived capillary pressure model. Comparing with other control‒oriented models in the literature, the developed model improves accuracy and provides more insights of the liquid water transport during transient response.Mechanical Engineerin