A strategy of estimating fuel concentration in a direct liquid-feed fuel cell system

Chiu, Yu-Jen; Lien, Hsin-Chung

doi:10.1016/j.jpowsour.2005.12.099

Cited by 31 publications

(8 citation statements)

References 11 publications

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“…The additional gain for the PI observer Figure 2 shows the time evolution of the three components of the input vector u(t) defined in (4), that drive both the linear and the nonlinear state-space DMFC models described in Section III. As shown in the figure, at t = 200 s the injection pump speed u IP changes from its initial operatingpoint value of 23.6 % to 28.3 %, followed by a step-down change at t = 3000 s that returns it to its initial value.…”

Section: Resultsmentioning

confidence: 99%

“…This method uses an offline developed database of measurements, and needs a large amount of data for calibration. Chiu and Lien [4] propose an interpolation algorithm to estimate the concentration of methanol using constant-concentration surfaces, and Shen et al [5] develop an algorithm that expands the method in [4] by adding corrections for voltage degradation and accounting for the overall water content in the system. Arisetty et al [6] propose a method that adjusts the concentration of methanol using the cell voltage as the feedback feedback signal and seeking to produce maximum power.…”

Section: Introductionmentioning

confidence: 99%

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Methanol concentration estimation in a direct methanol fuel cell system

Mudiraj

Crisalle

2014

2014 American Control Conference

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An inferential sensor based on state estimation techniques is proposed for measuring the methanol concentration in an open-cathode direct methanol fuel cell. The strategies considered include full-state and reduced-state Luenberger observers along with a proportional-integral observer. The estimators are designed using linear dynamics derived from a comprehensive nonlinear dynamic model of an experimental open-cathode direct methanol fuel cell. A representative simulation study is used to assess the performance of the estimation schemes deployed on both the linear and nonlinear dynamic models of the system. All three estimation methods are initially tuned to deliver adequate performance on the linear model. The simulation results show that the proportional-integral state observer outperforms the other designs when the dynamics are driven away from the linear regime. It is argued that the additional robustness of the proposed proportional-integral observer design holds significant promise for use as the basis for developing an effective inferential methanol composition sensor.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Methanol concentration estimation in a direct methanol fuel cell system

Mudiraj

Crisalle

2014

2014 American Control Conference

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“…At the same time, the methanol concentration has dropped to be very low in the fuel cell stack anode catalyst layer of fluid channels, and the concentration of methanol which mass transfer to the catalyst layer of the nuclear surface of the aggregates is lower. The methanol mass transfer rate is less than the anode oxidation reaction rate, so with the over potential of anode increasing rapidly, it cause large concentration overpotential and ohmic losses [6][7][8][9][10]. Therefore, the fuel cell stack generally does not work in this range.…”

Section: Energy Management For Fuzzy Control Strategymentioning

confidence: 99%

The Research of Energy Management Strategy for Direct Methanol Fuel Cell/Battery Hybrid System

Cao

Liu

2010

2010 Asia-Pacific Power and Energy Engineering Conference

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As the heart of a hybrid fuel cell/battery system, energy management strategies play an important role in system efficiency. Base on the operation principles of low-power direct methanol fuel cell (DMFC), we established a parameter identification model for the system. Fuzzy-logic based control strategies for energy distribution were presented to ensure the high efficiency of DMFC and the battery state of charge (SOC) at a reasonable level. Simulations under MATLB/Simulink were carried out using the designed model to show the effectiveness of the proposed methods.

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“…However, until now, there are only two types of methanol sensors for DMFCs as reported . One is electrochemical liquid sensor based on measuring the oxidation current, open-circuit voltage, short-circuit current, or the operating voltage at different concentration of methanol. ,− Another is physical liquid sensor, which is based on measuring corresponding physical properties (such as heat capacity, density, relative dielectric constant, viscosity) of responding to concentration changes of methanol liquid, but stronger interference of Cu 2+ , Fe 3+ in electrolyte would limit their application to DMFCs. Therefore, it is necessary to establish a novel methanol detection system with good environmental vapor or liquid adaptability, which has the ability of achieving a large linear relationship with high selectivity.…”

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confidence: 99%

Facile Wearable Vapor/Liquid Amphibious Methanol Sensor

Jiang

et al. 2018

ACS Sens.

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Detection of methanol is a significant segment for body health and work safety in the production of chemical industry. However, there hardly exists highly selective methanol detection system with green environment for vapor or liquid adaptability, as well as large linear relationship. A facile wearable vapor/liquid amphibious electrochemical sensor for monitoring methanol has been carried out for the first time in this Article. This wearable methanol sensor was fabricated by using a simple screen-printing technology for accomplishing a microdevice platform, showing good linear relationship, high selectivity (multiple volatile chemical compounds), reliable repeatability, good stability, and excellent stretching and bending performance (nitrile glove-based sensor) without pretreatment or adding any polymers into inks. Owing to its good environmental adaptability of vapor or liquid and various sensing behaviors (high sensitivity and wide linear range) by being modified with different content of platinum catalyst, this methanol sensor would have tremendous potential application for environmental monitoring on smart wearable devices when employed based on various platforms (such as PET, cotton, and nitrile gloves).

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A strategy of estimating fuel concentration in a direct liquid-feed fuel cell system

Cited by 31 publications

References 11 publications

Methanol concentration estimation in a direct methanol fuel cell system

Methanol concentration estimation in a direct methanol fuel cell system

The Research of Energy Management Strategy for Direct Methanol Fuel Cell/Battery Hybrid System

Facile Wearable Vapor/Liquid Amphibious Methanol Sensor

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