scholarly journals Characteristics of Carbon Dioxide and Product Water Exhausts in a Direct Methanol Fuel Cell with Serpentine Channels

2019 ◽  
Vol 26 (3) ◽  
pp. 137-144
Author(s):  
Kohei Nakashima

Abstract This study utilized a transparent direct methanol fuel cell, with serpentine channels with a width of 2 mm and an initial depth of 2 mm, and investigated the relationship between the behaviours of carbon dioxide (CO2) slugs, product water accumulations, and voltage fluctuation. It examined the exhaust volumes of CO2 slugs and product water accumulations from the channels over time, comparing an anode channel with a depth of 1.2 mm to one with a depth of 2 mm (without changing the cathode depth of 2 mm, nor the width of 2 mm in both the anode and the cathode). Results indicated that cell voltage fluctuated, rising while CO2 slugs were ejected, and falling between ejections. In the case of an anode channel depth of 2 mm and a lower methanol-water solution flow rate, CO2 slugs were ejected less frequently, so cell voltage fluctuated widely. (Product water accumulations in the cathode had a minimum effect on this cell voltage fluctuation.) In the case of a higher methanol-water solution flow rate, CO2 slugs were ejected more frequently, with less exhaust volume per CO2 slug, reducing the fluctuation in cell voltage. Finally, with an anode channel depth of 1.2 mm, the exhaust volume per CO2 slug became even smaller, and these small CO2 slugs were rapidly ejected. With this shallow depth, the cell voltage increased with a lower methanol-water solution flow rate, but decreased with a higher methanol-water solution flow rate by crossover.

2015 ◽  
Vol 12 (4) ◽  
Author(s):  
Yashar Kablou ◽  
Cynthia A. Cruickshank ◽  
Edgar Matida

A small-scale five-cell flowing electrolyte–direct methanol fuel cell (FE-DMFC) stack with U-type manifold configuration and parallel serpentine flow bed design was studied experimentally. The active area of a single cell was approximately 25 cm2. For every stack cell, diluted sulphuric acid was used as the flowing electrolyte (FE) which was circulated through a porous medium placed between two Nafion® 115 polymer electrolyte membranes. The stack performance was studied over a range of several operating conditions, such as temperature (50–80 °C), FE flow rate (0–17.5 ml/min), methanol concentration (0.5–4.0 M), and methanol solution flow rate (10–20 ml/min). In addition, the stack cell to cell voltage variations and the effects of the FE stream interruption on the output voltage were investigated at various operating loads. Experimental results showed that utilization of the FE effectively reduced methanol crossover and improved the stack power output. It was found that increasing the FE flow rate enhanced the stack capability to operate at higher inlet methanol concentrations without any degradation to the performance. The results also demonstrated that the stack power output can be directly controlled by regulating the FE stream especially at high operating currents.


2010 ◽  
Vol 14 (2) ◽  
pp. 469-477 ◽  
Author(s):  
Ebrahim Alizadeh ◽  
Mousa Farhadi ◽  
Kurosh Sedighi ◽  
Mohsen Shakeri

In this study the effect of various operating conditions on 10 cm ?10 cm active area of in-house fabricated direct methanol fuel cell was investigated experimentally. The effect of the cell temperature, methanol concentration, and oxygen flow rate on cell performance was studied. The study reveals that current density is not monotonous function of temperature, but has an optimum operating condition for each cell voltage. The experiments also indicate that the cell performance increases with an increased of oxygen flow rate up to a certain value and then further increase has no significant effect. Furthermore, for methanol concentration greater than 1.5 M, a reduction of cell voltage was indicated which is due to an increase of methanol cross over.


Author(s):  
M. A. Rafe Biswas ◽  
Melvin D. Robinson

A direct methanol fuel cell can convert chemical energy in the form of a liquid fuel into electrical energy to power devices, while simultaneously operating at low temperatures and producing virtually no greenhouse gases. Since the direct methanol fuel cell performance characteristics are inherently nonlinear and complex, it can be postulated that artificial neural networks represent a marked improvement in performance prediction capabilities. Artificial neural networks have long been used as a tool in predictive modeling. In this work, an artificial neural network is employed to predict the performance of a direct methanol fuel cell under various operating conditions. This work on the experimental analysis of a uniquely designed fuel cell and the computational modeling of a unique algorithm has not been found in prior literature outside of the authors and their affiliations. The fuel cell input variables for the performance analysis consist not only of the methanol concentration, fuel cell temperature, and current density, but also the number of cells and anode flow rate. The addition of the two typically unconventional variables allows for a more distinctive model when compared to prior neural network models. The key performance indicator of our neural network model is the cell voltage, which is an average voltage across the stack and ranges from 0 to 0:8V. Experimental studies were carried out using DMFC stacks custom-fabricated, with a membrane electrode assembly consisting of an additional unique liquid barrier layer to minimize water loss through the cathode side to the atmosphere. To determine the best fit of the model to the experimental cell voltage data, the model is trained using two different second order training algorithms: OWO-Newton and Levenberg-Marquardt (LM). The OWO-Newton algorithm has a topology that is slightly different from the topology of the LM algorithm by the employment of bypass weights. It can be concluded that the application of artificial neural networks can rapidly construct a predictive model of the cell voltage for a wide range of operating conditions with an accuracy of 10−3 to 10−4. The results were comparable with existing literature. The added dimensionality of the number of cells provided insight into scalability where the coefficient of the determination of the results for the two multi-cell stacks using LM algorithm were up to 0:9998. The model was also evaluated with empirical data of a single-cell stack.


2012 ◽  
Vol 23 (07) ◽  
pp. 1250055 ◽  
Author(s):  
J. L. TANG ◽  
C. Z. CAI ◽  
T. T. XIAO ◽  
S. J. HUANG

The purpose of this paper is to establish a direct methanol fuel cell (DMFC) prediction model by using the support vector regression (SVR) approach combined with particle swarm optimization (PSO) algorithm for its parameter selection. Two variables, cell temperature and cell current density were employed as input variables, cell voltage value of DMFC acted as output variable. Using leave-one-out cross-validation (LOOCV) test on 21 samples, the maximum absolute percentage error (APE) yields 5.66%, the mean absolute percentage error (MAPE) is only 0.93% and the correlation coefficient (R2) as high as 0.995. Compared with the result of artificial neural network (ANN) approach, it is shown that the modeling ability of SVR surpasses that of ANN. These suggest that SVR prediction model can be a good predictor to estimate the cell voltage for DMFC system.


Author(s):  
Liang Qi ◽  
Xiaofeng Xie ◽  
Ibrahim Alaefour ◽  
Aaron Pereira ◽  
Xianguo Li

A direct methanol fuel cell (DMFC) system consisting of 40 single cells was assembled to study the influence of the transport phenomena at the anode and stack faradaic efficiencies by a CO2 saturated solution method. This method corrected the common experimental error in measuring methanol crossover caused by the simultaneous CO2 permeation from the anode to cathode. Both anode and stack faradaic efficiencies were estimated using this method. An equivalent “carbon-flow current” has been defined and a relationship between the transport phenomena and efficiencies was developed. Also the effect of methanol concentration, methanol flow rate and air flow rate on stack efficiency was studied. The results show that lower methanol flow rate, lower methanol concentration and higher air flow rate are all helpful in decreasing the methanol crossover and increase the stack faradaic efficiency.


2011 ◽  
Vol 347-353 ◽  
pp. 3275-3280 ◽  
Author(s):  
Xian Qi Cao ◽  
Ji Tian Han ◽  
Ze Ting Yu ◽  
Pei Pei Chen

In this work, the effect of the current-collector structure on the performance of a passive direct methanol fuel cell (DMFC) was investigated. Parallel current-collector (PACC) and other two kinds of perforated current collectors (PECC) were designed, fabricated and tested. The studies were conducted in a passive DMFC with active membrane area of 9 cm2, working at ambient temperature and pressure. Two kinds of methanol solution of 2 M and 4 M were used. Results showed that the PACC as anode current-collector has a positive effect on cell voltage and power. For the cathode current-collector structure, the methanol concentration of 2 M for PECC-2 (higher open ratio 50.27 %) increased performance of DMFC. But the methanol concentration of 4 M led to an enhancement of fuel cell performance that used PACC or PECC-2 as cathode current-collector.


Author(s):  
Jiabin Ge ◽  
Hongtan Liu

Systematic experiments have been conducted to study the effects of various operating parameters on the performance of a direct methanol fuel cell (DMFC). The effects of cell operating temperature, anode flow rate, air flow rate, and methanol concentration have been studied. The experimental results showed that the operating parameters have significant effects on the DMFC performances, and some of the effects are complicated and deserve further detailed studies. Selected results are presented in this paper. A three dimensional, single-phase, multi-component model has been developed for liquid-feed DMFC. The traditional continuity, momentum, and species conservation equations are used. At the anode, liquid phase is considered, and at the cathode, only gas phase is considered. In addition to the regular electrochemical kinetics at the anode and cathode, the mixed potential effects due to methanol crossover are also included in the model. The modeling results compared well with our experimental data.


Author(s):  
Mario Apreotesi ◽  
Greg Mouchka ◽  
Keith Davis ◽  
Alex Tulchinsky ◽  
Deborah Pence

Desorption in micro-scale plate heat exchangers having a branching flow network is investigated as a function of oil flow rate, solution flow rate, manifold pressure and channel depth. The solution is an aqueous-ammonia solution with an inlet concentration held fixed at 30%. Mass flow rate and ammonia mass fraction of the generated vapor stream are characterized as is the heat exchange effectiveness of the various heat exchange desorbers. The effects of operating or exit plenum pressure and channel height on desorption and heat transfer characteristics are considered. Microscale channels are employed for enhanced heat and mass transport. The branching nature of the flow network is employed for flow symmetry and low pressure drop penalties. An operational model is generated to correctly size and efficiently integrate the desorber into an absorption cycle.


2019 ◽  
Vol 2 (24) ◽  
pp. 31-43
Author(s):  
Ji Eun Choi ◽  
Young Chan Bae ◽  
Dong Lae Kim

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