Modeling, diagnosis and control of fuel-cell-based technologies and their integration in smart-grids and automotive systems

The main objective of the current Special Section is to collect, formally present and discuss the most recent and relevant advances in control-oriented modeling and validation, system diagnosis and advanced control design of complex energy conversion systems based on fuel cells. Moreover, the Special Section is also focused on providing the researchers and engineers with the state-of-art research and guidelines in these important fields for the next years. In total, the Special Session is composed by 17 contributions covering the research in theoretical aspects related to modelling, diagnosis and control applied to energy management systems based on fuel cells or considering fuel cells as part of overall hybrid systems.Peer ReviewedPostprint (author's final draft

Modeling, diagnosis, and control of fuel-cell-based technologies and their integration in smart grids and automotive systems

Society is gradually becoming aware that the current energy system based on the use of fossil fuels is inefficient, highly polluting, and finite supply. Within the scientific community and industry stakeholders, there is a unified agreement that indicates that hydrogen (H2), as an energy vector, combined with other sources of alternative energy, represents a safe and viable option to mitigate the problems associated with hydrocarbon combustion because the entire system can be developed as an efficient, clean, and sustainable energy source. In this context, the change from the current energy system to a new system with a stronger involvement of H2 relentlessly involves the introduction of fuel cells as elements of efficient energy conversion.Peer Reviewe

Switching-based state-of-charge estimation of lithium-ion batteries

The objective of this thesis is to explore a switching-based approach to estimate the state of charge (SOC) of Li-ion batteries. The knowledge of SOC can be utilized to significantly enhance battery performance and longevity. The thesis first presents a brief discussion on various SOC estimation methods, such as coulomb counting, use of electrochemical model combined with Kalman Filtering and open-circuit voltage (OCV). Subsequently, emphasis is placed on the OCV-based method. The advantage of the OCV method lies in its simplicity. It obviates the need for modeling and lowers computational burden compared to model-based approaches. The method yields accurate SOC estimates if a long period of battery resting time (switch-off time) is allowed. For smaller switch-off durations, the accuracy of SOC estimation reduces. However, experiments show that Li-ion batteries could give acceptable SOC estimates due to their fast transient response during switch-off. In traditional usage scenarios, a switch-off interval may not be practical. However, in distributed power systems with multiple storage elements, a switch-off interval could be provided. Experiments are conducted to characterize the estimation error versus the switch-off time. To reduce the switch-off time to 30 second switch-off time and to increase the accuracy of SOC estimation, a method is proposed to extrapolate the OCV at infinite time from the measured OCV using a time constant. This leads to predicted OCV for infinite switch-off intervals. Experiments are conducted to confirm the improved SOC estimation using the proposed method. For experimentation, a commercially available LiFeMgPO4 battery module as well as a single cell LiFePO4 battery, is used

Modeling and control of fuel cell-battery hybrid energy sources

Environmental, political, and availability concerns regarding fossil fuels in recent decades have garnered substantial research and development in the area of alternative energy systems. Among various alternative energy systems, fuel cells and batteries have attracted significant attention both in academia and industry considering their superior performances and numerous advantages. In this dissertation, the modeling and control of these two electrochemical sources as the main constituents of fuel cell-battery hybrid energy sources are studied with ultimate goals of improving their performance, reducing their development and operational costs and consequently, easing their widespread commercialization. More specifically, Paper I provides a comprehensive background and literature review about Li-ion battery and its Battery Management System (BMS). Furthermore, the development of an experimental BMS design testbench is introduced in this paper. Paper II discusses the design of a novel observer for Li-ion battery State of Charge (SOC) estimation, as one of the most important functionalities of BMSs. Paper III addresses the control-oriented modeling and analysis of open-cathode fuel cells in order to provide a comprehensive system-level understanding of their real-time operation and to establish a basis for control design. Finally, in Paper IV a feedback controller, combined with a novel output-injection observer, is designed and implemented for open-cathode fuel cell temperature control. It is shown that temperature control not only ensures the fuel cell temperature reference is properly maintained, but, along with an uncertainty estimator, can also be used to adaptively stabilize the output voltage --Abstract, page iv

From verified parameter identification to the design of interval observers and cooperativity-preserving controllers : an experimental case study

One of the most important advantages of interval observers and the associated trajectory computation is their capability to provide estimates for a given dynamic system model in terms of guaranteed state bounds which are compatible with measured data subject to bounded uncertainty. However, the inevitable requirement for being able to produce such verified bounds is the knowledge about a dynamic system model in which possible uncertainties and inaccuracies are themselves represented by guaranteed bounds. For that reason, classical point-valued parameter identification schemes are often not sufficient or should, at least, be handled with sufficient care if safety critical applications are of interest. This paper provides an application-oriented description of the major steps leading from a control-oriented system model with an associated interval-valued parameter and disturbance identification to a verified design of interval observers which provide the basis for the development and implementation of cooperativity-preserving feedback controllers. Such combined control and observer structures allow for forecasting guaranteed lower and upper state bounds that can be determined by solving initial value problems for crisp-parameter models. As such, they replace the significantly more demanding task of computing tubes of reachable states by means of general-purpose interval methods. The corresponding computational steps for the cooperativity-preserving control and observer synthesis are described and visualized for the temperature control of a laboratory-scale test rig available at the Chair of Mechatronics at the University of Rostock