Experimental Analysis of a Small-Scale Flowing Electrolyte–Direct Methanol Fuel Cell Stack

2015 ◽  
Vol 12 (4) ◽  
Author(s):  
Yashar Kablou ◽  
Cynthia A. Cruickshank ◽  
Edgar Matida
Keyword(s):  
Fuel Cell ◽  
Flow Rate ◽  
Power Output ◽  
Direct Methanol Fuel Cell ◽  
Operating Conditions ◽  
Solution Flow Rate ◽  
Small Scale ◽  
Solution Flow ◽  
Direct Methanol ◽  
Methanol Fuel Cell

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.

Experimental Investigation on the Performance of a Formic Acid Electrolyte-Direct Methanol Fuel Cell

2013 ◽  
Vol 11 (2) ◽  
Author(s):  
David Ouellette ◽  
Cynthia Ann Cruickshank ◽  
Edgar Matida
Keyword(s):  
Fuel Cell ◽  
Formic Acid ◽  
Power Output ◽  
Direct Methanol Fuel Cell ◽  
Operating Conditions ◽  
Portable Devices ◽  
Acid Electrolyte ◽  
Optimal Operating ◽  
Direct Methanol ◽  
Methanol Fuel Cell

The performance of a new methanol fuel cell that utilizes a liquid formic acid electrolyte, named the formic acid electrolyte-direct methanol fuel cell (FAE-DMFC) is experimentally investigated. This fuel cell type has the capability of recycling/washing away methanol, without the need of methanol-electrolyte separation. Three fuel cell configurations were examined: a flowing electrolyte and two circulating electrolyte configurations. From these three configurations, the flowing electrolyte and the circulating electrolyte, with the electrolyte outlet routed to the anode inlet, provided the most stable power output, where minimal decay in performance and less than 3% and 5.6% variation in power output were observed in the respective configurations. The flowing electrolyte configuration also yielded the greatest power output by as much as 34%. Furthermore, for the flowing electrolyte configuration, several key operating conditions were experimentally tested to determine the optimal operating points. It was found that an inlet concentration of 2.2 M methanol and 6.5 M formic acid, as along with a cell temperature of 52.8 °C provided the best performance. Since this fuel cell has a low optimal operating temperature, this fuel cell has potential applications for handheld portable devices.

Experimental Studies of a Formic Acid Electrolyte: Direct Methanol Fuel Cell

2013 ◽  
Author(s):  
David Ouellette ◽  
Cynthia Ann Cruickshank ◽  
Edgar Matida
Keyword(s):  
Fuel Cell ◽  
Formic Acid ◽  
Power Output ◽  
Direct Methanol Fuel Cell ◽  
Experimental Studies ◽  
Operating Conditions ◽  
Acid Electrolyte ◽  
Direct Methanol ◽  
A Cell ◽  
Methanol Fuel Cell

A new methanol fuel cell that utilizes a liquid formic acid electrolyte, named the formic acid electrolyte-direct methanol fuel cell (FAE-DMFC) is experimentally tested. Three fuel cell configurations were examined; a flowing electrolyte and two circulating electrolyte configurations. From these three configurations, the flowing electrolyte and the circulating electrolyte, with the electrolyte outlet routed to the anode inlet, provided the most stable power output; where minimal decay in performance and less than 3 and 5.6 % variation in power output were observed in the respective configurations. The flowing electrolyte configuration also yielded the greatest power output by as much as 34 %. Furthermore, for the flowing electrolyte configuration, several key operating conditions were experimentally tested to determine the optimal operating points. It was found that an inlet concentration of 2.2 M methanol and 6.5 M formic acid, as well as a cell temperature of 52.8 °C provided the best performance.

Effects of Operating Conditions on Direct Methanol Fuel Cell Performance Using Nafion-Based Polymer Electrolytes

2014 ◽  
Vol 11 (6) ◽  
Author(s):  
Shingjiang Jessie Lue ◽  
Wei-Luen Hsu ◽  
Chen-Yu Chao ◽  
K. P. O. Mahesh
Keyword(s):  
Fuel Cell ◽  
Flow Rate ◽  
Direct Methanol Fuel Cell ◽  
Methanol Solution ◽  
Operating Conditions ◽  
Methanol Concentration ◽  
Cell Performance ◽  
Stoichiometric Ratio ◽  
Direct Methanol ◽  
Methanol Fuel Cell

Systematic experiments were carried out to study the effects of various operating conditions on the performances of a direct methanol fuel cell (DMFC) using Nafion 117 and its modified membranes. The cell performance was studied as a function of cell operating temperature, methanol concentration, methanol flow rate, oxygen flow rate, and methanol-to-oxygen stoichiometric ratio. The experimental results revealed that the most significant factor was the temperature, increasing the cell performance from 50 to 80 °C. We achieved the maximum power density (Pmax) of 86.4 mW cm−2 for a DMFC at 80 °C fed with 1 M methanol (flow rate of 2 ml min−1) and humidified oxygen (80 ml min−1). A methanol concentration of 1 M gave much better performance than using 3 M of methanol solution. The oxygen and methanol flow rates with the same stoichiometric ratio had a beneficial effect on cell performance up to certain values, beyond which further increase in flow rate had limited effect. The Voc using argon plasma-modified Nafion was higher than the pristine Nafion membrane for the cell operated on 3 M methanol solution, which was due to the lower methanol permeability of the Ar-modified Nafion.

Power Generation Experiment of Direct Methanol Fuel Cell

2011 ◽  
Vol 347-353 ◽  
pp. 3281-3285 ◽  
Author(s):  
Xin Zhou ◽  
Xiao Feng Xie ◽  
Motoo Ishikawa
Keyword(s):  
Fuel Cell ◽  
Flow Rate ◽  
Direct Methanol Fuel Cell ◽  
Peak Power ◽  
Gas Flow ◽  
Operating Conditions ◽  
Air Flow Rate ◽  
Direct Methanol ◽  
Oxygen Gas ◽  
Methanol Fuel Cell

An experiment of a single direct methanol fuel cell (DMFC) was conducted at Fuel Cell laboratory of Tsinghua University, China in collaboration with University of Tsukuba, Japan. Influences of the anodic methanol solution's concentration, the cathodic air flow rate, and the cathodic oxygen gas flow rate on the single DMFC performance were investigated to optimize operating conditions of the fuel cell. The experimental results have shown that the single DMFC can reach the peak power density of 0.170 W/cm2 with the current of 0.515 A/cm2 under the condition of the concentration of methanol solution of 2M and the flow rate of oxygen gas of 80 mL/min.

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
Keyword(s):  
Flow Rate ◽  
Direct Methanol Fuel Cell ◽  
Water Solution ◽  
Cell Voltage ◽  
Solution Flow Rate ◽  
Channel Depth ◽  
Solution Flow ◽  
Direct Methanol ◽  
Product Water ◽  
Methanol Fuel Cell

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.

Performance Estimation of Direct Methanol Fuel Cell Using Artificial Neural Network

2015 ◽  
Author(s):  
M. A. Rafe Biswas ◽  
Melvin D. Robinson
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Artificial Neural Networks ◽  
Fuel Cell ◽  
Direct Methanol Fuel Cell ◽  
Cell Voltage ◽  
Operating Conditions ◽  
Direct Methanol ◽  
Artificial Neural ◽  
Methanol Fuel Cell

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.

Direct methanol fuel cell modeling based on the norm optimal iterative learning control

2020 ◽  
Vol 235 (1) ◽  
pp. 68-79
Author(s):  
Nastaran Shakeri ◽  
Zahra Rahmani ◽  
Abolfazl Ranjbar Noei ◽  
Mohammadreza Zamani
Keyword(s):  
Fuel Cell ◽  
Iterative Learning Control ◽  
Direct Methanol Fuel Cell ◽  
Direct Methanol Fuel Cells ◽  
Learning Control ◽  
Iterative Learning ◽  
Operating Conditions ◽  
Primary Model ◽  
Direct Methanol ◽  
Methanol Fuel Cell

Direct methanol fuel cells are one of the most promisingly critical fuel cell technologies for portable applications. Due to the strong dependency between actual operating conditions and electrical power, acquiring an explicit model becomes difficult. In this article, the behavioral model of direct methanol fuel cell is proposed with satisfactory accuracy, using only input/output measurement data. First, using the generated data which are tested on the direct methanol fuel cell, the frequency response of the direct methanol fuel cell is estimated as a primary model in lower accuracy. Then, the norm optimal iterative learning control is used to improve the estimated model of the direct methanol fuel cell with a predictive trial information algorithm. Iterative learning control can be used for controlling systems with imprecise models as it is capable of correcting the input control signal in each trial. The proposed algorithm uses not only the past trial information but also the future trials which are predicted. It is found that better performance, as well as much more convergence speed, can be achieved with the predicted future trials. In addition, applying the norm optimal iterative learning control on the proposed procedure, resulted from the solution of a quadratic optimization problem, leads to the optimal selection of the control inputs. Simulation results demonstrate the effectiveness of the proposed approach by practical data.

In-Situ Estimation of Faradaic Efficiency for a Direct Methanol Fuel Cell Stack by a Carbon Dioxide Saturated Solution Method

2009 ◽  
Author(s):  
Liang Qi ◽  
Xiaofeng Xie ◽  
Ibrahim Alaefour ◽  
Aaron Pereira ◽  
Xianguo Li
Keyword(s):  
Fuel Cell ◽  
Flow Rate ◽  
Direct Methanol Fuel Cell ◽  
Solution Method ◽  
Air Flow ◽  
Saturated Solution ◽  
Air Flow Rate ◽  
Faradaic Efficiency ◽  
Direct Methanol ◽  
Methanol Fuel Cell

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.

Performance and Modeling of a Liquid-Fed Direct Methanol Fuel Cell

2004 ◽  
Author(s):  
Jiabin Ge ◽  
Hongtan Liu
Keyword(s):  
Fuel Cell ◽  
Flow Rate ◽  
Direct Methanol Fuel Cell ◽  
Species Conservation ◽  
Three Dimensional ◽  
Electrochemical Kinetics ◽  
Operating Parameters ◽  
Liquid Feed ◽  
Direct Methanol ◽  
Methanol Fuel Cell

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.

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