Research Project

DOVELAR: Control and energy management of hybrid fuel cell-based electric vehicles

Type

National Project

Start Date

01/01/2019

End Date

30/09/2022

Project Code

RTI2018-096001-B-C32

Project illustration

Staff

Project Description

Project RTI2018-096001-B-C32 funded by MCIN/ AEI /10.13039/501100011033 and by "ERDF A way of making Europe"

The main objective of the project is to contribute to the improvement of fuel cell based electrical powertrains. This will be carried out in three main directions: the construction of an improved fuel cell compared to the state of the art, the improvement of the control and energy management systems of the PEM fuel cell hybrid systems, and the validation and tuning in three specific applications of practical interest. Given that these objectives are fully multidisciplinary, the project will be structured in three subprojects.

In the subproject described here, the efforts will focus on the development of new energy management and control systems, and their validation in three autonomous electric vehicles. One of the vehicles will be an omnidirectional robotic platform that has been developed by the project team. Its current powertrain will be replaced by a hybrid powertrain developed in the project. The omnidirectional autonomous robot is intended to move autonomously being part of a fully automated industrial environment within the framework of Industry 4.0.

Fuel cells are nonlinear distributed dynamic systems. This implies that most control engineering methodologies, such as modeling, parametric identification, state observation and design techniques are difficult to apply. For this reason, the models of the PEM fuel cells (PEMFC) will be revisited, emphasizing efficiency and degradation phenomena and the appropriate model order for implementation. These models will be completed with experimental protocols and on-line and off-line parameter estimation algorithms that will lead to automatic model tuning from experimental data.

The closed Fuel Cell physical structure and its distributed nature makes impossible to measure all the state variables. In this scenario, state observers can play a decisive role in improving the performance of control systems, especially in the aspects related with degradation, a phenomenon that does not affect the entire fuel cell equally. Therefore, state estimation algorithms will be developed, and the simultaneous estimation of the states and parameters will be analyzed. In addition to improving the control systems, it is expected that these algorithms allow the implementation of fault detection and isolation techniques, which are of great interest in preventive maintenance procedures. Fuel cells are only one component of a hybrid traction system which consists of the fuel cell and an energy storage element (i.e. battery or supercapacitor). Therefore, it is vital to determine the optimal instantaneous power flow and the amount of energy stored. To address these aspects, a hardware/software device will be developed to capture power profiles. Based on these profiles, optimal control and energy management systems will be designed with the objectives of minimizing the consumption and degradation of the different elements. Although the control and energy management algorithms will be implemented in all three prototypes addressed in the project, special emphasis will be given to the omnidirectional autonomous robot. In this context, energy management and path planning techniques will be integrated in order to improve the energy efficiency of the entire system.

This UPC sub-project will result in both scientific and technological benefits to the society and industry. The general impact of the subproject will be to make the social widespread use of FC hybrid vehicles closer, which will contribute to electrificationify and clean mobility.

From the scientific point of view, it is expected to report general advances in the Automatic Control domain such as new modeling methodologies to obtain low order models that describe the relevant distributed phenomena and the corresponding parameter identification techniques, integration of parameter identification and state estimation and power management algorithms integrated with vehicle path planning. Regarding PEMFC, it is expected to describe novel state estimation strategies and novel control systems structures for hybrid PEMFC powertrains. These developments will enlarge PEMFC lifetime, which is the most important impediment for FC technology massive introduction into the society. Finally, the physical powertrain integration into three different autonomous vehicles will contribute as demonstration platforms to the scientific divulgation.

Project Publications

Journal Publications

  • A. Cecilia and R. Costa. Addressing the relative degree restriction in nonlinear adaptive observers: A high-gain observer approach. Journal of the Franklin Institute, 359(8): 3857-3882, 2022.

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  • Y. Xing, J. Na, M. Chen, R. Costa and V. Roda. Adaptive nonlinear parameter estimation for a proton exchange membrane fuel cell. IEEE Transactions on Power Electronics, 37(8): 9012-9023, 2022.

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  • V. Sanz, R. Costa and C. Batlle. Literature review of energy management in combined heat and power systems based on high-temperature PEMFC for residential comfort applications. Energies, 15(17): 6423-6444, 2022.

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  • T.P. Puleston, A. Clemente, R. Costa and M. Serra. Modelling and estimation of vanadium redox flow batteries: a review. Batteries, 8(9): 121, 2022.

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  • U. Raveendran Nair, M. Sandelic, A. Sangwongwanich, T. Dragicevic, R. Costa and F. Blaabjerg. Grid congestion mitigation and battery degradation minimisation using model predictive control in PV-based microgrid. IEEE Transactions on Energy Conversion, 36(2): 1500-1509, 2021.

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  • G.A. Ramos, T. Montobbio, C. Domènech-Mestres and R. Costa. Industrial robots fuel cell based hybrid power-trains: A comparison between different configurations. Electronics, 10(12): 1431, 2021.

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  • U. Raveendran Nair, M. Sandelic, A. Sangwongwanich, T. Dragicevic, R. Costa and F. Blaabjerg. An analysis of multi objective energy scheduling in PV-BESS system under prediction uncertainty. IEEE Transactions on Energy Conversion, 36(3): 2276-2286, 2021.

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  • A. Cecilia, S. Sahoo, T. Dragičević, R. Costa and F. Blaabjerg. Detection and mitigation of false data in cooperative DC microgrids with unknown constant power loads. IEEE Transactions on Power Electronics, 36(8): 9565-9577, 2021.

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  • A. Cecilia, M. Serra and R. Costa. Nonlinear adaptive observation of the liquid water saturation in polymer electrolyte membrane fuel cells. Journal of Power Sources, 492: 229641, 2021.

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  • A. Clemente, M. Montiel, F. Barreras, A. Lozano and R. Costa. Vanadium redox fow battery state of charge estimation using a concentration model and a sliding mode observer. IEEE Access, 9: 72368-72376, 2021.

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  • J.C. Gómez, M. Serra and A.P. Husar. Controller design for polymer electrolyte membrane fuel cell systems for automotive applications. International Journal of Hydrogen Energy, 46(45): 23263-23278, 2021.

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  • German A. Ramos, R. Isaza and R. Costa. Robust repetitive control of power inverters for standalone operation in DG systems. IEEE Transactions on Energy Conversion, 35(1): 237-247, 2020.

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  • J.A. Luna, R. Costa and S. Strahl. Chattering free sliding mode observer estimation of liquid water fraction in proton exchange membrane fuel cells. Journal of the Franklin Institute, 357(18): 13816-13833, 2020.

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  • Y. Xing, R. Costa and J. Na. Temperature control for a proton-exchange membrane fuel cell system with unknown dynamic compensations. Complexity, 2020: 8822835, 2020.

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  • A. Cecilia, J. Carroquino, V. Roda, R. Costa and F. Barreras. Optimal energy management in a standalone microgrid, with photovoltaic generation, short-term storage, and hydrogen production. Energies, 13(6): 1454, 2020.

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  • A. Cecilia and R. Costa. Observador de alta ganancia con zona muerta ajustable para estimar la saturación de agua líquida en pilas de combustible tipo PEM. Revista Iberoamericana de Automática e Informática Industrial, 17(2): 169-180, 2020.

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  • A. Clemente and R. Costa. Redox flow batteries: A literature review oriented to automatic control . Energies, 13(17): 4514, 2020.

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  • A. Clemente, G. Andres Ramos and R. Costa. Voltage H∞ control of a vanadium redox flow battery. Electronics, 9(10): 1567, 2020.

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  • Y. Xing, R. Costa, J. Na and H. Renaudineau. Control-oriented modelling and analysis of a solid oxide fuel cell system. International Journal of Hydrogen Energy, 45(40): 20659-20672, 2020.

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  • U. Raveendran Nair and R. Costa. A model predictive control-based energy management scheme for hybrid storage system in islanded microgrids. IEEE Access, 8: 97809-97822, 2020.

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Conference Publications

  • A. Molavi, A.P. Husar, M. Serra, H. Hjortberg, N. Nilsson, M. Kogler, J. Sanchez Monreal and Y.O. Eldigair. State Machine-based architecture to control PEMFC system processes in a fuel cell electric vehicle, 2022 European Hydrogen Energy Conference, 2022, Madrid, pp. 2.

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  • A. Cecilia and R. Costa. On state-estimation in weakly-observable scenarios and implicitly regularized observers, 60th IEEE Conference on Decision and Control, 2021, Austin, TX, USA (Virtual), pp. 3996-4001.

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  • A. Clemente, A. Cecilia and R. Costa. SOC and diffusion rate estimation in redox flow batteries: An I&I-based high-gain observer approach, 20th European Control Conference, 2021, Rotterdam, Netherlands, pp. 1640-1644.

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  • A. Clemente and R. Costa. Flow controlling tuning for the voltage of a redox flow battery considering the effect of overpotentials, 2021 IEEE International Conference on Emerging Technologies and Factory Automation, 2021, Västerås, Sweden.

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  • V. Sanz, G. Lopez, R. Costa and C. Batlle. Combined heat and power using high-temperature proton exchange membrane fuel cells for housing facilities, 2021 IEEE International Conference on Emerging Technologies and Factory Automation, 2021, Västerås, Sweden, pp. 1-8.

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  • R. Domingo-Enrich, A. Cecilia and R. Costa. Control no lineal adaptativo con identificación dispersa, XLII Jornadas de Automática, 2021, Castellón, Spain, pp. 365-372.

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  • A. Clemente, A. Cecilia and R. Costa. Estimación del estado de carga y coeficientes de difusión en baterías de flujo redox, XLII Jornadas de Automática, 2021, Castellón, Spain, pp. 357-364.

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  • A. Cecilia and R. Costa. Library-based adaptive observation through a sparsity-promoting adaptive observer, 20th European Control Conference, 2021, Rotterdam, Netherlands, pp. 2187-2192.

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  • J. Anderson, J. Moré, P.F. Puleston, V. Roda and R. Costa. Implementación y validación experimental del control de un sistema híbrido basado en pilas de combustible para vehículos eléctricos, XXVII Congreso Argentino de Control Automático, 2020, Buenos Aires, Argentina (Virtual), pp. 313-318.

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  • J.M. Díaz, S. Dormido and R. Costa. An interactive teaching/learning approach to the design of robust linear control systems using the closed-loop shaping methodology, 21st IFAC World Congress, 2020, (Virtual), Vol 53 of IFAC Papers Online, pp. 17174-17178, Elsevier.

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  • J.M. Díaz, S. Dormido, B. Nicolau and R. Costa. H∞ interactive controller design for teaching purposes, 21st IFAC World Congress, 2020, (Virtual), Vol 53 of IFAC Papers Online, pp. 17185-17189, Elsevier.

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  • A. Cecilia, M. Serra and R. Costa. PEMFC state and parameter estimation through a high-gain based adaptive observer, 21st IFAC World Congress, 2020, (Virtual), Vol 53 of IFAC Papers Online, pp. 5895-5900, Elsevier.

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  • Y. Xing, J. Na, R. Costa and G. Gao. Adaptive parameter estimation-based observer design for nonlinear systems, 59th IEEE Conference on Decision and Control, 2020, Jeju Island, Republic of Korea, pp. 4170-4175, IEEE.

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