Nonlinear observation in fuel cell systems: a comparison between disturbance estimation and High-Order Sliding-Mode techniques

© . This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/This paper compares two Nonlinear Distributed Parameter Observers (NDPO) for the observation of a Proton Exchange Membrane Fuel Cell (PEMFC). Both NDPOs are based on the discretisation of distributed parameters models and they are used to estimate the state profile of gas concentrations in the anode and cathode gas channels of the PEMFC, giving detailed information about the internal conditions of the system. The reaction and water transport flow rates from the membrane to the channels are uncertainties of the observation problem and they are estimated throughout all the length of the PEMFC without the use of additional sensors. The first observation approach is a Nonlinear Disturbance Observer (NDOB) for the estimation of the disturbances in the NDPO. In the second approach, a novel implementation of a High-Order Sliding-Mode (HOSM) observer is developed to estimate the true value of the states as well as the reaction terms. The proposed observers are tested and compared through a simulation example at different operating points and their performance and robustness is analysed over a given case study, the New European Driving Cycle.Peer ReviewedPostprint (author's final draft

Algebraic observer design for PEM fuel cell system

© 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.In this paper, the concept of the algebraic observer is applied to Proton Exchange Membrane Fuel Cell (PEMFC) system. The aim of the proposed observer is to reconstruct the oxygen excess ratio through estimation of their relevant states in real time from the measurement of the supply manifold air pressure. A robust differentiation method is adopted to estimate in finite-time the time derivative of the supply manifold air pressure. Then, the relevant states are reconstructed based on the output-state inversion model. The objective is to minimize the use of extra sensors in order to reduce the costs and enhance the system accuracy. The performance of the proposed observer is analyzed through simulations considering measurement noise and different stack-current variations. The results show that the algebraic observer estimates in finite time and robustly the oxygen-excess ratio.Peer ReviewedPostprint (author's final draft

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

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

The main contribution of this work is the improvement of the efficiency of a PEMFC power system while guaranteeing conditions that also improve its durability. Adopting the NMPC scheme with the distributed parameter model and the nonlinear observer, the efficiency of the PEMFC-based system can be maximized guaranteeing at the same time the appropriate internal gas concentration profiles to avoid global and local hydrogen and oxygen starvation and proper membrane humidification.Peer ReviewedPostprint (author's final draft

Adaptive online parameter estimation algorithm of PEM fuel cells

Since most of fuel cell models are generally nonlinearly parameterized functions, existing modeling techniques rely on the optimization approaches and impose heavy computational costs. In this paper, an adaptive online parameter estimation approach for PEM fuel cells is developed in order to directly estimate unknown parameters. The general framework of this approach is that the electrochemical model is first reformulated using Taylor series expansion. Then, one recently proposed adaptive parameter estimation method is further tailored to estimate the unknown parameters. In this method, the adaptive law is directly driven by the parameter estimation errors without using any predictors or observers. Moreover, parameter estimation errors can be guaranteed to achieve exponential convergence. Besides, the online validation of regressor matrix invertibility are avoided such that computation costs can be effectively reduced. Finally, comparative simulation results demonstrate that the proposed approach can achieve better performance than least square algorithm for estimating unknown parameters of fuel cells.Postprint (published version

Nonlinear observer design for PEM fuel-cell systems using first-order sliding mode techniques

This paper presents a nonlinear observer design for Proton Exchange Membrane Fuel-Cell (PEMFC) systems. The aim of the proposed observer is to reconstruct the oxygen excess ratio through the estimation of their relevant states in real time from the measurement of the supply manifold air pressure. A First-Order Sliding Mode (FOSM) differentiation method is adopted to estimate, in finite time, the time derivative of the supply manifold air pressure. By means of the output-state inversion model, the relevant states are reconstructed. The objective of the proposed appproach is to minimize the use of additional sensors in order to reduce the costs and enhance the system accuracy. The performance of the proposed observer is analyzed through simulations considering measurement noise and different stack-current variations. The results show that the nonlinear observer properly estimates in finite time and robustly the oxygen excess ratio.Peer ReviewedPostprint (author's final draft

Nonlinear distributed parameter observer design for fuel cell systems

This paper presents the development of a nonlinear state observer to estimate the different gas species concentration profiles in a Proton Exchange Membrane Fuel Cell energy system. The selection of the estimated states follows functionality and fuel cell performance criteria. The implementation is based on the finite element discretisation of a fuel cell distributed parameter model. Forward and backwards discretisation of the partial derivative equations is performed to take advantage of the boundary conditions of the problem and also to apply lumped systems theory in the synthesis procedure of the observer. A second-order sliding-mode super-twisting corrective input action is implemented to reduce the estimation error to zero in a finite amount of time. The sliding-mode control approach grants a suitable corrective action without incrementing the model-dependency of the observer. Simulation results are presented to show the performance of the proposed observer of the fuel cell internal states and to extract conclusions for future research work.This work is partially funded by the Spanish national MICINN project DPI2011-25649, as well as by the 7th Framework Programme of the European Commission in the context of the Fuel Cells and Hydrogen Joint Undertaking (FCH JU) through the project PUMA-MIND FP7 303419.Peer Reviewe

Algebraic observer-based output-feedback controller design for a PEM fuel cell air-supply subsystem

© 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.In this paper, an algebraic-observer-based output-feedback controller is proposed for a Proton Exchange Membrane Fuel Cell (PEMFC) air-supply subsystem, based on both algebraic differentiation and sliding-mode control approaches. The goal of the design is to regulate the Oxygen Excess Ratio (OER) towards its optimal setpoint value in the PEMFC air-supply subsystem. Hence, an algebraic estimation approach is used to reconstruct the OER based on a robust differentiation method. The proposed observer is known by its finite-time convergence and low computational time compared to other observers presented in the literature. Then, a twisting controller is designed to control the OER by manipulating the compressor motor voltage. The parameters of the twisting controller have been calculated by means of an off-line tuning procedure. The performance of the proposed algebraic-observer-based output-feedback controller is analyzed through simulations for different stack-current changes, for parameter uncertainties and for noise rejection. Results show that the proposed approach properly estimates and regulates the OER in finite-time.Peer ReviewedPostprint (author's final draft

Investigating controller performance in hybrid SOFC systems in the presence of unknown nonlinearities

Solid oxide fuel cells (SOFCs) are energy conversion devices that offer many benefits over various other fuel cell types as a result of high operating temperatures (800-1000 °C). Unfortunately, SOFCs tend to possess poor load following capabilities due to delays along the fuel path and complex system dynamics. Maintaining safe operating conditions during changes in power demand is addressed using a controller designed to regulate the fuel cell current based on fuel flow measurement. In order to compensate for the resulting mismatch between demanded and delivered power, the SOFC system is hybridized with an energy storage device, such as an ultra-capacitor. Prior research at the HySES laboratory at RIT has led to control designs that guarantee robustness to uncertainties in system parameters such power electronics efficiencies. However, existing controllers for this system were developed under assumptions made about the unknown dynamics of the fuel supply system (FSS), such as exponential or bounded tracking. Retaining these controller designs, this thesis develops a general set of closed loop system equations in which the prior assumptions about the FSS are relaxed. The FSS behavior is treated as an unknown nonlinearity. Thereafter, concepts of absolute stability, Lyapunov stability and linear system approximation are used to evaluate the closed-loop system. The analysis leads to analytical conditions relating the controller gains and the local behavior of the FSS, predicting the onset of instability in the closed-loop system. The results are validated using simulations and using a hardware-in-the-loop test stand. Additionally, the problem of transient fuel utilization control of SOFCs is revisited and addressed by using a nonlinear observer design and an auxiliary hydrogen injection strategy. These approaches aim to compensate for fuel path delays and maintain desired operating conditions during transient loading conditions. Findings are validated using desktop simulations