Model-based control of cathode pressure and oxygen excess ratio of a PEM fuel cell system

Danzer, Michael A.; Wilhelm, J.; Aschemann, Harald; Hofer, Eberhard P.

doi:10.1016/j.jpowsour.2007.08.049

Cited by 120 publications

(56 citation statements)

References 8 publications

(8 reference statements)

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“…Equations (3)(4)(5) are identified from the 1.2kW Nexa prototype by using experimental curves, where dVst is a deviation factor of the stack voltage that considers the changes of the stack temperature from the reference temperature T0=35C. An airflow compressor model is obtained by using experimental data taken from the Ballard NEXA 1.2 kW system, following the Reaction Curve Method [6] is the oxygen flow consumed in the reaction.…”

Section: Mathematical Model Of Pem Fuel Cell Systemsmentioning

confidence: 99%

“…These profiles thereby require being parameterized specifically for each PEM fuel, and they should be reidentified when the ideal operating conditions differ significantly from the actual operating conditions. Previously, in [4] a linear control system and a non-linear state space model were proposed to deliver the requested load power by tracking an optimal profile, while [ the oxygen starvation is avoided and the fuel consumption is minimized. The optimal load profile was obtained from a set of maximum power points under ideal operating conditions parameterized using a polynomial function [2].…”

Section: Introductionmentioning

confidence: 99%

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Sistema de control para reducir el consumo de hidrógeno en celdas de combustible PEM considerando incertidumbres paramétricas

Ríos

Ramos‐Paja

Espinosa

2016

TecnoL.

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Este artículo presenta un sistema de control para reducir el consumo de hidrogeno para una celda de combustible de Membrana de Intercambio Protónico, considerando incertidumbres paramétricas. El sistema de control incluye un modelo no lineal en el espacio de estado para la celda de combustible, un filtro de Kalman/estimador, un regulador óptimo cuadrático y algoritmo de seguimiento de puntos de máxima potencia (MPP). El objetivo de control es suministrar la potencia de carga demandada, evitando el agotamiento del oxígeno y minimizando el consumo de hidrógeno por medio de un algoritmo de Perturbación y Observación (P&O). El desempeño del sistema de control es evaluado ante incertidumbres paramétricas al simular escenarios de perdida de desempeño como producto del envejecimiento del compresor. De esta forma, dos escenarios fueron simulados: un primer escenario simula un error entre la ganancia (de lazo abierto) del compresor de la celda de combustible y la del modelo; y un segundo escenario, con un error entre la corriente de pérdidas y del compresor de la celda de combustible con respecto al modelo. Los resultados de simulación muestran que el filtro Kalman/estimador logra contrarrestar las incertidumbres producidas por los cambios paramétricos del sistema. Igualmente, el algoritmo MPP logra suministrar el voltaje del compresor adecuado sin necesidad de un perfil óptimo en condiciones ideales.

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Section: Mathematical Model Of Pem Fuel Cell Systemsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Sistema de control para reducir el consumo de hidrógeno en celdas de combustible PEM considerando incertidumbres paramétricas

Ríos

Ramos‐Paja

Espinosa

2016

TecnoL.

View full text Add to dashboard Cite

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“…The higher the rotation speed, the greater the air flow rate. Yet the air flow rate through the centrifugal compressor is determined by both rotation speed and compressure ratio [9].…”

Section: Oer Performancementioning

confidence: 99%

“…In addition, the air pressure in cathode flow field of the fuel cell stack and the pressure difference between both sides of proton exchange membrane must be maintained in a certain range during operation. Air flow control is important to maintaining the reliability and efficiency of the system, and different air flow control techniques have been provided by researchers [7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Air flow control based on optimal oxygen excess ratio in fuel cells for vehicles

Chen

et al. 2013

J. Mod. Transport.

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Air flow control is one of the most important control methods for maintaining the stability and reliability of a fuel cell system, which can avoid oxygen starvation or oxygen saturation. The oxygen excess ratio (OER) is often used to indicate the air flow condition. Based on a fuel cell system model for vehicles, OER performance was analyzed for different stack currents and temperatures in this paper, and the results show that the optimal OER was affected weakly by the stack temperature. In order to ensure the system working in optimal OER, a control scheme that includes an optimal OER regulator and a fuzzy control was proposed. According to the stack current, a reference value of air flow rate was obtained with the optimal OER regulator and then the air compressor motor voltage was controlled with the fuzzy controller to adjust the air flow rate provided by the air compressor. Simulation results show that the control method has good dynamic and static characteristics.

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“…This allowed an alternate representation of the system, where trajectory planning and nonlinear controller design is clear-cut. These ideas have been used lately in a variety of nonlinear systems across various engineering disciplines including: control of a high-speed linear axis driven by pneumatic muscle actuators [22], control of cathode pressure and oxygen excess ratio of a proton exchange membrane (PEM) fuel cell system [23], steering control of a two-level quantum system [24], reactive power and dc voltage tracking control of a three-phase voltage source converter [25], control of openchannel flow in an irrigation canal [26], current control for three phase three-wire boost converters [27], design of a guidance algorithm for the hypersonic phase of a lifting-body vehicle [28], and control of a space robot with arbitrarily oriented joint axes and two momentum wheels at the base [29].…”

mentioning

confidence: 99%

Analysis of Differential Flatness-Based Control for a Fuel Cell Hybrid Power Source

Thounthong

Pierfederici

Davat

2010

IEEE Trans. Energy Convers.

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Abstract-This paper presents an innovative control law for distributed dc generation supplied by a fuel cell (FC) (main source) and supercapacitor (auxiliary source). This kind of system is a multiconverter structure and exhibits nonlinear behavior. The operation of a multiconverter structure can lead to interactions between the controls of the converters if they are designed separately. Typically, interactions between converters are studied using impedance criteria to investigate the stability of cascaded systems. In this paper, a nonlinear control algorithm based on the flatness properties of the system is proposed. Flatness provides a convenient framework for meeting a number of performance specifications for the hybrid power source. Using the flatness property, we propose simple solutions to hybrid energy management and stabilization problems. The design controller parameters are autonomous of the operating point; moreover, interactions between converters are taken into account by the controllers, and high dynamics in disturbance rejection is achieved. To validate the proposed method, a hardware system is realized with analog circuits, and digital estimation is accomplished with a dSPACE controller. Experimental results with small-scale devices (a polymer electrolyte membrane FC of 1200 W, 46 A and a supercapacitor module of 100 F, 500 A, and 32 V) in a laboratory corroborate the excellent control scheme during a motor-drive cycle.

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Model-based control of cathode pressure and oxygen excess ratio of a PEM fuel cell system

Cited by 120 publications

References 8 publications

Sistema de control para reducir el consumo de hidrógeno en celdas de combustible PEM considerando incertidumbres paramétricas

Sistema de control para reducir el consumo de hidrógeno en celdas de combustible PEM considerando incertidumbres paramétricas

Air flow control based on optimal oxygen excess ratio in fuel cells for vehicles

Analysis of Differential Flatness-Based Control for a Fuel Cell Hybrid Power Source

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