Finite elements used in the vertical discretization of the fully compressible core of the ALADIN system

The finite-element method with B splines is used for definition of vertical operators in the nonhydrostatic fully compressible dynamical core of the ALADIN system. It represents a generalization of the same method used in the hydrostatic dynamical core shared by the ALADIN system and the global forecast system ARPEGE/IFS. The method is shown to be robust enough in idealized academic tests and real simulations. Its theoretical superiority is shown when compared with the finite-difference method

Un modelo no hidrostático global con coordenada vertical basada en altura

Memoria presentada en la Universitat de València para optar grado de de DoctorEsta tesis documenta la investigación que he realizado en modelización atmosférica: se parte de las ecuaciones físicas de la atmósfera y se aplican métodos numéricos eficientes para encontrar una solución a dichas ecuaciones a partir de unas condiciones iniciales dadas. Para este fin, se ha desarrollado un modelo atmosférico cuyas características principales son: espectral en la representación horizontal de los campos, discretización vertical de alto orden de exactitud, y semi-implícito en la integración temporal. Además, el modelo es no hidrostático y tiene una coordenada vertical basada en altura, en vez de la tradicional coordenada vertical basada en presión hidrostática. Se ha usado una formulación covariante de las ecuaciones de Euler, lo que ha permitido una expresión compacta y robusta de las condiciones de contorno y del operador divergencia. Una vez planteado y resuelto el problema, se han realizado una completa serie de test ampliamente documentados en la literatura científica para evaluar la precisión y eficiencia del modelo. Los resultados de los test son satisfactorios, quedando así demostrada la calidad de los métodos propuestos

Una aplicación de los sistemas de predicción por conjuntos para avisos meteorológicos

Los sistemas de predicción por conjuntos son herramientas de vital importancia para la emisión de avisos meteorológicos. Dada su naturaleza, pueden explorar el espacio de estados atmosféricos posibles ofreciendo un abanico de escenarios meteorológicos, algunos de los cuales pueden dar lugar a fenómenos adversos. Pero la cantidad de información que brindan los SPC es ingente, por lo que es de vital importancia condensarla con métodos de síntesis adecuados sin perder información relevante. En este capítulo presentamos una aplicación informática desarrollada en AEMET que, basándose en estos principios, ofrece a los predictores del tiempo una serie limitada de mapas que les permite tomar decisiones en tiempos reducidos

Diagnóstico, de la turbulencia a partir de los datos AMDAR y salidas de modelos numéricos de predicción

Presentación realizada en el Foro de Usuarios Aeronáuticos, celebrado el 28 de febrero de 2018 en los Servicios Centrales de AEMET en Madri

Un modelo no hidrostático global con coordenada vertical basada en altura

Esta tesis documenta la investigación que he realizado en modelización atmosférica: se parte de las ecuaciones físicas de la atmósfera y se aplican métodos numéricos eficientes para encontrar una solución a dichas ecuaciones a partir de unas condiciones iniciales dadas. Para este fin, se ha desarrollado un modelo atmosférico cuyas características principales son: espectral en la representación horizontal de los campos, discretización vertical de alto orden de exactitud, y semi-implícito en la integración temporal. Además, el modelo es no hidrostático y tiene una coordenada vertical basada en altura, en vez de la tradicional coordenada vertical basada en presión hidrostática. Se ha usado una formulación covariante de las ecuaciones de Euler, lo que ha permitido una expresión compacta y robusta de las condiciones de contorno y del operador divergencia. Una vez planteado y resuelto el problema, se han realizado una completa serie de test ampliamente documentados en la literatura científica para evaluar la precisión y eficiencia del modelo. Los resultados de los test son satisfactorios, quedando así demostrada la calidad de los métodos propuestos

Using a Multiobjective Approach to Compare Multiple Design Alternatives An Application to Battery Dynamic Model Tuning

[EN] A design problem is usually solvable in different ways or by design alternatives. In this work, the term concept is used to refer to the design alternatives. Additionally, it is quite common that a design problem has to satisfy conflicting objectives. In these cases, the design problem can be formulated as a multiobjective optimization problem (MOP). One of the aims of this work was to show how to combine multiobjective requirements with concepts comparisons, in order to attain a satisfactory design. The second aim of this work was to take advantage of this methodology to obtain a battery model that described the dynamic behavior of the main electrical variables. Two objectives related to the model accuracy during the charge and discharge processes were used. In the final model selection, three different concepts were compared. These concepts differed in the complexity of their model structure. More complex models usually provide a good approximation of the process when identification data are used, but the approximation could be worse when validation data are applied. In this article, it is shown that a model with an intermediate complexity supplies a good approximation for both identification and validation data sets.This work was partially supported by the Ministerio de Economia y Competitividad (Spain), Grant Numbers: DPI2015-71443-R and FPU15/01652.Pajares-Ferrando, A.; Blasco, X.; Herrero Durá, JM.; Simarro Fernández, R. (2017). Using a Multiobjective Approach to Compare Multiple Design Alternatives An Application to Battery Dynamic Model Tuning. Energies. 10(7):1-19. https://doi.org/10.3390/en10070999S11910

Control-Oriented Modeling of the Cooling Process of a PEMFC-Based u-CHP System

[EN] Micro-combined heat and power systems (¿-CHP) based on proton exchange membrane fuel cell stacks (PEMFC) are capable of supplying electricity and heat for the residential housing sector with a high energy efficiency and a low level of CO2 emissions. For this reason, they are regarded as a promising technology for coping with the current environmental challenges. In these systems, the temperature control of the stack is crucial, since it has a direct impact on its durability and electrical efficiency. In order to design a good temperature control, however, a dynamic model of the ¿-CHP cooling system is required. In this paper, we present a model of the cooling system of a PEMFC-based ¿-CHP system, which is oriented to the design of the temperature control of the stack. The model has been developed from a ¿-CHP system located in the laboratory of our research team, the predictive control and heuristic optimization group (CPOH). It is based on first principles, dynamic, non-linear, and has been validated against the experimental data. The model is implemented in Matlab/Simulink and the adjustment of its parameters was carried out using evolutionary optimization techniques. The methodology followed to obtain it is also described in detail. Both the model and the test data used for its adjustment and validation are accessible to anyone who wants to consult them. The results show that the model is able to faithfully represent the dynamics of the ¿-CHP cooling system, so it is appropriate for the design of the stack temperature controlThis work was supported in part by the Ministerio de Economia y Competitividad, Spain, under Grant DPI2015-71443-R and Grant RTI2018-096904-B-I00, and in part by the Local Administration Generalitat Valenciana under Project GV/2017/029Navarro-Giménez, S.; Herrero Durá, JM.; Blasco, X.; Simarro Fernández, R. (2019). Control-Oriented Modeling of the Cooling Process of a PEMFC-Based u-CHP System. IEEE Access. 7:95620-95642. https://doi.org/10.1109/ACCESS.2019.2928632S9562095642

Design and Experimental Validation of the Temperature Control of a PEMFC Stack by Applying Multiobjective Optimization

[EN] The current environmental challenges require the implementation of environmentally friendly energy production systems. In this context, proton exchange membrane fuel cell stacks (PEMFC) represent, due to their high electrical efficiency and their low level of CO2 emissions, a promising alternative technology. However, there are still many technical aspects that need to be improved before they become a commercial reality. One of them is the temperature control of the stack, since its electrical efficiency and its lifetime depend on the performance of this control. In this work, we design a multiloop PID control of the temperature of a PEMFC stack and validate it experimentally. The stack is the prime mover of a micro combined heat and power system (micro-CHP). For this task, we use a previously developed nonlinear model and apply a multiobjective optimization methodology. To assess its performance, the PID control is compared to a second PID control designed with a linearized model. The results show, on the one hand, the importance of having a nonlinear model valid in a wide operation range for the correct design of the temperature control of a PEMFC stack and, on the other hand, the advantages of applying a multiobjective optimization methodology to this problem.This work was supported in part by the Spanish Ministry of Science, Innovation, and Universities under Grant RTI2018-096904-B-I00, and in part by the Generalitat Valenciana Regional Government under Project AICO/2019/055.Navarro-Giménez, S.; Herrero Durá, JM.; Blasco, X.; Simarro Fernández, R. (2020). Design and Experimental Validation of the Temperature Control of a PEMFC Stack by Applying Multiobjective Optimization. IEEE Access. 8:183324-183343. https://doi.org/10.1109/ACCESS.2020.3029321S183324183343

Multivariable controller design for the cooling system of a PEM fuel cell by considering nearly optimal solutions in a multi-objective optimization approach

[EN] This paper presents a design for the multivariable control of a cooling system in a PEM (proton exchange membrane) fuel cell stack. This system is complex and challenging enough: interactions between variables, highly nonlinear dynamic behavior, etc. This design is carried out using a multiobjective optimization methodology. There are few previous works that address this problem using multiobjective techniques. Also, this work has, as a novelty, the consideration of, in addition to the optimal controllers, the nearly optimal controllers nondominated in their neighborhood (potentially useful alternatives). In the multiobjective optimization problem approach, the designer must make decisions that include design objectives; parameters of the controllers to be estimated; and the conditions and characteristics of the simulation of the system. However, to simplify the optimization and decision stages, the designer does not include all the desired scenarios in the multiobjective problem definition. Nevertheless, these aspects can be analyzed in the decision stage only for the controllers obtained with a much less computational cost. At this stage, the potentially useful alternatives can play an important role. These controllers have significantly different parameters and therefore allow the designer to make a final decision with additional valuable information. Nearly optimal controllers can obtain an improvement in some aspects not included in the multiobjective optimization problem. For example, in this paper, various aspects are analyzed regarding potentially useful solutions, such as (1) the influence of certain parameters of the simulator; (2) the sample time of the controller; (3) the effect of stack degradation; and (4) the robustness. Therefore, this paper highlights the relevance of this in-depth analysis using the methodology proposed in the design of the multivariable control of the cooling system of a PEM fuel cell. This analysis can modify the final choice of the designer.This study was supported in part by the Ministerio de Ciencia, Innovacion y Universidades (Spain) (grant no. RTI2018-096904-B-I00) and by the Generalitat Valenciana regional government through project AICO/2019/055.Pajares-Ferrando, A.; Blasco, X.; Herrero Durá, JM.; Simarro Fernández, R. (2020). Multivariable controller design for the cooling system of a PEM fuel cell by considering nearly optimal solutions in a multi-objective optimization approach. Complexity. 2020:1-17. https://doi.org/10.1155/2020/8649428S1172020Gunantara, N. (2018). A review of multi-objective optimization: Methods and its applications. Cogent Engineering, 5(1), 1502242. doi:10.1080/23311916.2018.1502242Engau, A., & Wiecek, M. M. (2007). Generating ε-efficient solutions in multiobjective programming. European Journal of Operational Research, 177(3), 1566-1579. doi:10.1016/j.ejor.2005.10.023Loridan, P. (1984). ?-solutions in vector minimization problems. Journal of Optimization Theory and Applications, 43(2), 265-276. doi:10.1007/bf00936165White, D. J. (1986). Epsilon efficiency. Journal of Optimization Theory and Applications, 49(2), 319-337. doi:10.1007/bf00940762Pajares, A., Blasco, X., Herrero, J. M., & Reynoso-Meza, G. (2018). A Multiobjective Genetic Algorithm for the Localization of Optimal and Nearly Optimal Solutions Which Are Potentially Useful: nevMOGA. Complexity, 2018, 1-22. doi:10.1155/2018/1792420Schutze, O., Vasile, M., & Coello, C. A. C. (2011). Computing the Set of Epsilon-Efficient Solutions in Multiobjective Space Mission Design. Journal of Aerospace Computing, Information, and Communication, 8(3), 53-70. doi:10.2514/1.46478Pajares, A., Blasco, X., Herrero, J. M., & Reynoso-Meza, G. (2019). A New Point of View in Multivariable Controller Tuning Under Multiobjective Optimization by Considering Nearly Optimal Solutions. IEEE Access, 7, 66435-66452. doi:10.1109/access.2019.2915556Fredriksson, A., Forsgren, A., & Hårdemark, B. (2011). Minimax optimization for handling range and setup uncertainties in proton therapy. Medical Physics, 38(3), 1672-1684. doi:10.1118/1.3556559Lee, J., & Johnson, G. E. (1993). Optimal tolerance allotment using a genetic algorithm and truncated Monte Carlo simulation. Computer-Aided Design, 25(9), 601-611. doi:10.1016/0010-4485(93)90075-yAndújar, J. M., & Segura, F. (2009). Fuel cells: History and updating. A walk along two centuries. Renewable and Sustainable Energy Reviews, 13(9), 2309-2322. doi:10.1016/j.rser.2009.03.015Mehta, V., & Cooper, J. S. (2003). Review and analysis of PEM fuel cell design and manufacturing. Journal of Power Sources, 114(1), 32-53. doi:10.1016/s0378-7753(02)00542-6De las Heras, A., Vivas, F. J., Segura, F., Redondo, M. J., & Andújar, J. M. (2018). Air-cooled fuel cells: Keys to design and build the oxidant/cooling system. Renewable Energy, 125, 1-20. doi:10.1016/j.renene.2018.02.077Kandlikar, S. G., & Lu, Z. (2009). Thermal management issues in a PEMFC stack – A brief review of current status. Applied Thermal Engineering, 29(7), 1276-1280. doi:10.1016/j.applthermaleng.2008.05.009Yan, Q., Toghiani, H., & Causey, H. (2006). Steady state and dynamic performance of proton exchange membrane fuel cells (PEMFCs) under various operating conditions and load changes. Journal of Power Sources, 161(1), 492-502. doi:10.1016/j.jpowsour.2006.03.077Maghanki, M. M., Ghobadian, B., Najafi, G., & Galogah, R. J. (2013). Micro combined heat and power (MCHP) technologies and applications. Renewable and Sustainable Energy Reviews, 28, 510-524. doi:10.1016/j.rser.2013.07.053Notter, D. A., Kouravelou, K., Karachalios, T., Daletou, M. K., & Haberland, N. T. (2015). Life cycle assessment of PEM FC applications: electric mobility and μ-CHP. Energy & Environmental Science, 8(7), 1969-1985. doi:10.1039/c5ee01082aMartinez, S., Michaux, G., Salagnac, P., & Bouvier, J.-L. (2017). Micro-combined heat and power systems (micro-CHP) based on renewable energy sources. Energy Conversion and Management, 154, 262-285. doi:10.1016/j.enconman.2017.10.035Elmer, T., Worall, M., Wu, S., & Riffat, S. B. (2015). Fuel cell technology for domestic built environment applications: State of-the-art review. Renewable and Sustainable Energy Reviews, 42, 913-931. doi:10.1016/j.rser.2014.10.080Hawkes, A., Staffell, I., Brett, D., & Brandon, N. (2009). Fuel cells for micro-combined heat and power generation. Energy & Environmental Science, 2(7), 729. doi:10.1039/b902222hEllamla, H. R., Staffell, I., Bujlo, P., Pollet, B. G., & Pasupathi, S. (2015). Current status of fuel cell based combined heat and power systems for residential sector. Journal of Power Sources, 293, 312-328. doi:10.1016/j.jpowsour.2015.05.050Strahl, S., & Costa-Castelló, R. (2017). Temperature control of open-cathode PEM fuel cells. IFAC-PapersOnLine, 50(1), 11088-11093. doi:10.1016/j.ifacol.2017.08.2492Zhang, G., & Kandlikar, S. G. (2012). A critical review of cooling techniques in proton exchange membrane fuel cell stacks. International Journal of Hydrogen Energy, 37(3), 2412-2429. doi:10.1016/j.ijhydene.2011.11.010Navarro Gimenez, S., Herrero Dura, J. M., Blasco Ferragud, F. X., & Simarro Fernandez, R. (2019). Control-Oriented Modeling of the Cooling Process of a PEMFC-Based $\mu$ -CHP System. IEEE Access, 7, 95620-95642. doi:10.1109/access.2019.2928632Herrero, J. M., García-Nieto, S., Blasco, X., Romero-García, V., Sánchez-Pérez, J. V., & Garcia-Raffi, L. M. (2008). Optimization of sonic crystal attenuation properties by ev-MOGA multiobjective evolutionary algorithm. Structural and Multidisciplinary Optimization, 39(2), 203-215. doi:10.1007/s00158-008-0323-7Bristol, E. (1966). On a new measure of interaction for multivariable process control. IEEE Transactions on Automatic Control, 11(1), 133-134. doi:10.1109/tac.1966.1098266Blasco, X., Herrero, J. M., Sanchis, J., & Martínez, M. (2008). A new graphical visualization of n-dimensional Pareto front for decision-making in multiobjective optimization. Information Sciences, 178(20), 3908-3924. doi:10.1016/j.ins.2008.06.010Schmittinger, W., & Vahidi, A. (2008). A review of the main parameters influencing long-term performance and durability of PEM fuel cells. Journal of Power Sources, 180(1), 1-14. doi:10.1016/j.jpowsour.2008.01.07

Desarrollo de nuevos productos para fenómenos adversos de impacto

Presentación realizada en el Foro de Usuarios Aeronáuticos, celebrado el 21 de febrero de 2017 en los Servicios Centrales de AEMET en Madri