Thermodynamically consistent reduced dimensionality electrochemical model for proton exchange membrane fuel cell performance modelling and control

Kravos, Andraž; Ritzberger, Daniel; Tavčar, Gregor; Hametner, Christoph; Jakubek, Stefan; Katrašnik, Tomaž

doi:10.1016/j.jpowsour.2020.227930

Cited by 28 publications

(39 citation statements)

References 26 publications

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“…The model is a zero-dimensional physical PEMFC model, and Figure 1 gives a schematic overview. It utilizes, amongst others, mass balances, linear nozzle equations, diffusion equations, electrochemical equations, and the ideal gas law [22][23][24]. However, it does not consider energy balances and thus cannot model the FC temperature over time.…”

Section: Model Descriptionmentioning

confidence: 99%

Efficient Two-Step Parametrization of a Control-Oriented Zero-Dimensional Polymer Electrolyte Membrane Fuel Cell Model Based on Measured Stack Data

Steindl

Jakubek

2021

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This paper proposes a new efficient two-step method for parametrizing control-oriented zero-dimensional physical polymer electrolyte membrane fuel cell (PEMFC) models with measured stack data. Parametrizations of these models are computationally intensive due to the numerous unknown parameters and the typically nonlinear, stiff model properties. This work reduces an existing model to decrease its stiffness for accelerated numerical simulations. Subdividing the parametrization into two consecutive subproblems (thermodynamic and electrochemical ones) reduces the solution space significantly. A parameter sensitivity analysis further reduces each sub-solution space by excluding non-significant parameters. The method results in an efficient parametrization process. The two-step approach minimizes each sub-solution space’s dimension by two-thirds, respectively three-fourths, compared to the global one. An achieved R2 value between simulation and measurement of 91% on average provides the required accuracy for control-oriented models.

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Section: Model Descriptionmentioning

confidence: 99%

Efficient Two-Step Parametrization of a Control-Oriented Zero-Dimensional Polymer Electrolyte Membrane Fuel Cell Model Based on Measured Stack Data

Steindl

Jakubek

2021

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“…The electrochemical submodel, i.e., the dependence of the FC voltage V on the current I and internal states, is adopted from [33]. The power produced by the FC stack is defined as P st = V I.…”

Section: Power and Efficiencymentioning

confidence: 99%

Model-Predictive-Control-Based Reference Governor for Fuel Cells in Automotive Application Compared with Performance from a Real Vehicle

2021

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In this paper, a real-time capable reference governor superordinate model predictive controller (RG-MPC) is developed for fuel cell (FC) control suitable for automotive application. The RG-MPC provides reference trajectories for the subordinate proportional-integral (PI) controllers, which act directly on the FC system. Antiwindup and decoupling schemes, which are common problems in multivariable PI control, are unnecessary, given that the RG-MPC can inherently consider constraints and multivariable systems. The PI dynamics are incorporated into the prediction model used for control, ensuring the feasibility of the provided references for the PI controllers. The successive linearization technique is used in the RG-MPC to cope with the model’s nonlinear nature in real-time. The concept has been illustrated in a simulation scenario featuring efficient and safe power control of an FC stack in automotive application using real driving data obtained from an in-house-built FC vehicle. This work is the first step towards upgrading an existing, PI-based control scheme without the necessity of completely rebuilding the interface.

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“…This corresponds with to the fact that the time constants of the electrochemical reactions are several orders of magnitude faster then the time-constants associated with the convective and diffusive transport of species [29]. The electrochemical model is described and discussed in detail in [30]. Aggregating all differential equations describing the fuel cell stack leads to a highly non-linear state-space model of the formẋ…”

Section: Derivation Of Model Equationsmentioning

confidence: 99%

A Real-Time Dynamic Fuel Cell System Simulation for Model-Based Diagnostics and Control: Validation on Real Driving Data

2020

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Fuel cell systems are regarded as a promising candidate in replacing the internal combustion engine as a renewable and emission free alternative in automotive applications. However, the operation of a fuel cell stack fulfilling transient power-demands poses significant challenges. Efficiency is to be maximized while adhering to critical constraints, avoiding adverse operational conditions (fuel starvation, membrane flooding or drying, etc.) and mitigating degradation as to increase the life-time of the stack. Owing to this complexity, advanced model-based diagnostic and control methods are increasingly investigated. In this work, a real time stack model is presented and its experimental parameterization is discussed. Furthermore, the stack model is integrated in a system simulation, where the compressor dynamics, the feedback controls for the hydrogen injection and back-pressure valve actuation, and the purging strategy are considered. The resulting system simulation, driven by the set-point values of the operating strategy is evaluated and validated on experimental data obtained from a fuel cell vehicle during on-road operation. It will be shown how the internal states of the fuel cell simulation evolve during the transient operation of the fuel cell vehicle. The measurement data, for which this analysis is conducted, stem from a fuel cell research and demonstrator vehicle, developed by a consortium of several academic and industrial partners under the lead of AVL List GmbH.

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Thermodynamically consistent reduced dimensionality electrochemical model for proton exchange membrane fuel cell performance modelling and control

Cited by 28 publications

References 26 publications

Efficient Two-Step Parametrization of a Control-Oriented Zero-Dimensional Polymer Electrolyte Membrane Fuel Cell Model Based on Measured Stack Data

Efficient Two-Step Parametrization of a Control-Oriented Zero-Dimensional Polymer Electrolyte Membrane Fuel Cell Model Based on Measured Stack Data

Model-Predictive-Control-Based Reference Governor for Fuel Cells in Automotive Application Compared with Performance from a Real Vehicle

A Real-Time Dynamic Fuel Cell System Simulation for Model-Based Diagnostics and Control: Validation on Real Driving Data

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