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Sensor-less control of methanol concentration based on estimation of methanol consumption rates for direct methanol fuel cell systems
international journal of hydrogen energy 33 (2008) 7163–7171
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Sensor-less control of methanol concentration based on estimation of methanol consumption rates for direct methanol fuel cell systems Tae Jung Haa,b, Jong-Ho Kima, Han-Ik Joha, Soo-Kil Kima, Go-Young Moonc, Tae-Hoon Lima, Chonghun Hanb,**, Heung Yong Haa,* a
Fuel cell Research Center, Korea Institute of Science and Technology (KIST), 39-1 Hawolgok-dong, P.O. Box 131, Seongbuk-gu, Cheongyang, Seoul 130-650, South Korea b School of Chemical & Biological Engineering and Institute of Chemical Process, Seoul National University, San 56-1, Shillim-dong, Kwanak-ku, Seoul 151-744, South Korea c Corporate R&D Center, LG Chem, Ltd., Munji-dong, Yuseong-gu, Daejeon 305-380, South Korea
article info
abstract
Article history:
Adequate control over the concentration of methanol is critically needed in operating
Received 30 May 2008
direct methanol fuel cell (DMFC) systems, because performance and energy efficiency of
Received in revised form
the systems are primarily dependent on the concentration of methanol feed. For this
24 August 2008
purpose, we have built a sensor-less control logic that can operate based on the estimation
Accepted 1 September 2008
of the rates of methanol consumption in a DMFC. The rates of methanol consumption are
Available online 2 November 2008
measured in a cell and the resulting data are fed as an input to the control program to calculate the amount of methanol required to maintain the concentration of methanol at
Keywords:
a set value under the given operating conditions of a cell. The sensor-less control has been
Direct methanol fuel cell (DMFC)
applied to a DMFC system employed with a large-size single cell and the concentration of
Fuel circulation loop
methanol is found to be controlled stably to target concentrations even though there are
Sensor-less methanol concentration
some deviations from the target values.
control
ª 2008 International Association for Hydrogen Energy. Published by Elsevier Ltd. All rights
Methanol consumption rate
reserved.
Methanol crossover
1.
Introduction
Direct methanol fuel cells (DMFCs) have many advantages over other types of fuel cells because of their easy refueling, simple balance of plant (BOP) and high energy density. In order to obtain a maximum performance of a DMFC, the operating conditions such as, the cell temperature, methanol feed concentration, and air flow rate should be optimized. Of all the operating conditions, the concentration of methanol is
an important factor, because it plays a key role in affecting the performance, durability and energy efficiency of DMFC systems [1,2]. In fact, the higher concentration of methanol is required to reduce the anode overpotential, which is normally exaggerated by the limited methanol diffusion rate from the flow field to the catalyst layer of the anode at a high current region [3,4]. However, it induces higher methanol crossover resulting in mixed potential in the cathode, which can lead to lower performance of a cell and lower energy efficiency.
* Corresponding author. Tel.: þ82 2 958 5275; fax: þ82 2 958 5199. ** Corresponding author. Tel.: þ82 2 880 1887; fax: þ82 2 873 2767. E-mail addresses: [email protected] (C. Han), [email protected] (H.Y. Ha). 0360-3199/$ – see front matter ª 2008 International Association for Hydrogen Energy. Published by Elsevier Ltd. All rights reserved. doi:10.1016/j.ijhydene.2008.09.019
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Nomenclature C Ci F A Fa Fc FO2 FN 2 i Nm,f Nm,t Nm,e
Nm,x Nm-CO2 Nx-CO2 T V Vi XCO2
methanol concentration (mol L1) initial methanol concentration (mol L1) Faraday constant (C mol1) active surface area of a cell (cm2) liquid flux in the anode compartment (mol cm2 min1) air flux in the cathode compartment (mol cm2 min1) oxygen flux (mol cm2 min1) nitrogen flux (mol cm2 min1) current density (A cm2) methanol feed rate per unit area (mol cm2 min1) total methanol consumption rate per unit area (mol cm2 min1) methanol consumption rate per unit area by the electrochemical reaction at the anode (mol cm2 min1) methanol consumption rate per unit area by crossover (mol cm2 min1) measured CO2 flux at the cathode (mol cm2 min1) CO2 crossover flux from anode to cathode (mol cm2 min1) fuel cell temperature ( C) total liquid volume in a methanol mixing chamber (L) initial liquid volume in a methanol mixing chamber (L) volumetric concentration of CO2 in the cathode effluent ()
Therefore, concentration of methanol feed needs to be maintained adequately at a predetermined level to ensure a stable and energy-efficient DMFC operation. In active DMFC systems, the methanol pump, which is used to supply methanol solution to the cell should be equipped with methanol sensor to monitor and control the methanol concentration in the inlet stream of the cell [5]. There are various concentration sensors available in the market based on different principles. Zhao et al. [6] used various concentration sensors to evaluate their suitability for the DMFC. Some concentration sensors are utilized to study the physical propensities of methanol solution particularly, the density of methanol [7,8]. Other concentration sensors are used based on the electrochemical reactions in the cell by means of applying electric potential [9,10]. The former type is used to accurately measure the concentration of methanol. However, they are expensive and too big in size to be mounted with the portable DMFC systems. On the other hand, the latter type is cheaper and smaller, but they suffer from poor stability and reliability, because of degradation of the catalyst in the sensors during the usage. The work related with using sensor-less control systems for the DMFC is relatively rare [11–14]. Sudo [11] devised a sensor-less methanol concentration system by constructing a DMFC stack consisting of two sub-stacks, which are
connected in series and the out-flowing methanol solution from the first sub-stack is introduced to the second one. The voltage difference between the two sub-stacks is compared and used as an indication for the change of concentration of methanol during the operation. This method is not affected by the degradation of the membrane-electrode assembly, but it may work only in a limited concentration range. Acker et al. [12] introduced a method to regulate the methanol concentration by continually monitoring the open circuit potentials or short circuit currents. However, in this method, the operating stability and the control of accuracy might be affected by degradation of the MEA during a long-term operation. In another study, Chiu and Lien [13] suggested an alternative method for measuring the methanol concentration by designing an estimation algorithm to build a constant concentration surfaces with respect to cell voltages. However, this method is also vulnerable to degradation of the MEA, because the same voltage cannot be obtained even with a feed of the same methanol concentration if the MEA is deteriorated for any reasons during the course of operation. Chang et al. [14], made a sensor-less control algorithm by using the impulse responses based on the discrete time fuel injection. In fact, this method is not affected by degradation of the MEA, but may not be suitable to dynamic operating conditions that undergo changes in voltage as well as current. As briefly mentioned above, the sensor-less methanol control systems in the literature have some defects in and of themselves. Therefore, we have made an attempt to make our own version and that can satisfy three critical requirements listed below: - It should not be affected by degradation of the MEA during operation. - It should work even under dynamic operating conditions. - It should not be affected by the electric loads applied to the fuel cell systems. The purpose of our study is to make a sensor-less methanol-concentration control system (SLCC) for the DMFCs. In order to do that, we have designed an algorithm to control concentration of methanol and constructed a database that consists of experimental data for the rates of methanol consumption under various operating conditions. Thus formed SLCC has been applied to a real DMFC system to evaluate its accuracy by varying the target concentration.
2.
Building control algorithms for DMFCs
2.1.
Configuration of a DMFC system
In a simple DMFC system, the unreacted methanol exhausted out of the system without reuse. The energy density of this type of system, which is proportional to the amount of the methanol in the reservoir of the system becomes very low because of using low concentration of methanol, usually below 2.0 M (about 6 vol% aqueous solutions). In order to increase the energy density, a pure or high concentration methanol solution needs to be stored in a reservoir even though the concentration of methanol in the feed stream of
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the cell is maintained at a lower concentration, probably below 2 M. For this purpose, the unreacted methanol solution has to be re-circulated and a high concentrated methanol solution should be added to the stream to adjust for the consumed methanol and to keep the concentration of feed methanol at a constant level as shown in Fig. 1. In addition to methanol, water is also consumed by participating in the methanol oxidation reaction in the anode; and it is permeated to the cathode, usually driven by a difference in the activity of water between the electrodes and by electro-osmotic drag [15]. Therefore, water should also be continuously compensated to the methanol stream by any means. Accommodation of largesize pure water reservoir in a DMFC system, however, is unrealistic because it can increase the volume of a system, thereby lowering the power density, in addition it might also increase the cost of the DMFC system. In that situation, the water produced in the cathode side can be captured by using a heat exchanger, which in turn, can be re-circulated to the anode side.
2.2. The sensor-less methanol-concentration control system (SLCC) As mentioned in the previous section, we have aimed to formulate a sensor-less methanol-concentration control system (SLCC) by predicting the rates of methanol consumption under a range of fuel cell operating conditions. In order to do this, first, we have developed relevant equations to correlate the total rates of methanol consumption with those by the electrochemical reaction at the anode, in addition to methanol crossover to the cathode. The mass balance equation for methanol in the entire anode feed loop including anode channels, tubing, and a methanol mixing chamber, where methanol solution exists is as follows: One can get methanol concentration (C ) at time t from Eq. (1): Z (1) VC ¼ Vi Ci þ vðVCÞ=vtdt If we assume that the total liquid volume in the whole anode feed loop remains constant, then Eq. (1) becomes vðVCÞ=vt ¼ VvC=vt at V is constant C ¼ Ci þ
Z vC=vtdt
(2) (3)
where, V is the liquid volume of a methanol mixing chamber at time t, Vi is the initial volume of liquid, C is the
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concentration of methanol of the mixing chamber at time t, Ci is initial concentration of methanol. Eq. (3) indicates that concentration of methanol at time t (C ) is the sum of the initial concentration of methanol and the integrated amount of change of concentration of methanol until time t. On the other hand, the change in concentration of methanol in the solution is the difference between the methanol feeding rate from the methanol reservoir (Nm,f) and the methanol consumption rate at the anode side compartment (Nm,t). (4) vC=vt ¼ Nm;f Nm;t V vC=vt ¼ 0 at Nm;f ¼ Nm;t
(5)
C ¼ Ci: Ci is a target concentration in this case Therefore, the concentration of methanol does not change if the methanol feeding rate (Nm,f) from the reservoir is the same as the total methanol consumption rate (Nm,t). In this case, one can maintain desired concentrations if the initial concentration is the same to that of the target value, while other conditions are well under the control. Therefore, first of all, we have to create a sensor-less methanol-concentration control system (SLCC) as a tool that can accurately predict the rates of methanol consumption under any operating conditions. As described in Eqs. (6) and (7), the total rate of methanol consumption (Nm,t) is sum of the electrochemical methanol oxidation rate (Nm,e) that is proportional to the electric load applied and the methanol crossover rate (Nm,x) from the anode to the cathode through diffusion and electro-osmotic drag. Some loss of methanol can also be anticipated at the gas–liquid separator in the anode-side circulating loop because the exhausted methanol vapor entrained in the CO2 stream that comes out of the anode compartment of a cell. However, in this study, we assume that the loss is negligibly small when compared with the rate of methanol consumption in a cell; because the concentration of methanol is maintained lower than 1 mol L1 and the temperature of the methanol solution in the gas–liquid separator is relatively low at around 40 C. The variation of methanol crossover rate (Nm,x) depends on the load (i) and other operating conditions like temperature, flow rates of reactants, and the concentration of methanol (Eq. (8)). Nm;t ¼ Nm;e þ Nm;x
(6)
Nm;e ¼ f ðiÞ ¼ 10i=F
(7)
Fig. 1 – Configuration of a DMFC system with methanol re-circulation.
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Nm;x ¼ f ði; T; C; Fa ; Fc Þ
(8)
Nm;x ¼ f ði; T; CÞ at constant Fa and Fc
(9)
If we could formulate an equation to predict precisely the rate of methanol consumption at any operating condition, then it would be very easy to create a SLCC. However, it is not as easy as mentioned above. The simple way to make a tool to predict the rates of methanol consumption is to build a database by collecting them through the experiments under various operating conditions within a limited range of our interest. We have carried out a set of experiments to measure methanol crossover rates (Nm,x in Eq. (9)) at different operating conditions by varying current (electric load), temperature, and concentration of methanol. The total rate of methanol consumption that is required to calculate the methanol supply rate is a function of current and temperature (Eq. (10)). By using the experimental data obtained under varying currents and temperatures, a least square regression using Eq. (11) is carried out to calculate the values of the constants in Eq. (10). Therefore, in this model, the current and the temperature are treated as independent variables (input value), and the rate of methanol consumption as a dependent variable (output value) that is calculated with a given set of experimental conditions. Concentration of methanol is also not a variable because the set point for the concentration of methanol does not change during the operation of DMFC in this study. Nm;t ¼ a0 þ a1 T þ a2 i at specific methanol concentration 2
n 6PT 4 P j ij
P T P j2 T P j Tj ij
P 38 9 8 P 9 i P j 7< a0 = < P Nm;t;j = Ti 5 a TN ¼ P j2 j : 1 ; : P j m;t;j ; ij Nm;t;j a2 ij
(10)
(11)
By completing the Eq. (10) that can calculate the rates of methanol consumption, we could set up an algorithm to control the concentration of methanol to a target value in a DMFC system as shown in Fig. 2. Measured temperatures and currents are input to Eq. (10) and then the amount of pure methanol to be supplied to the methanol mixing chamber is calculated. In this system, the total volume of an aqueous solution in the methanol feeding loop that includes a mixing chamber, an anode compartment of a fuel cell, and connecting tubes is maintained constant by continuously supplying the water condensate from the cathode side.
3.
Fig. 2 – Algorithm to control the concentration of methanol through calculating the rates of methanol consumption based on the database that matches the operating conditions.
Experimental
3.1. Measurement of methanol consumption rates in a DMFC We have used a large-size single DMFC with an active area of 138 cm2 to measure methanol crossover rates by varying current, temperature, and concentration of methanol under a fixed flow rate of air and methanol solution. - MEA: size 138 cm2, Nafion 115, anode ¼ 6 mg-PtRu cm2, cathode ¼ 4 mg-Pt cm2
- Flow field: parallel serpentine type - Flow rates of the reactants: anode ¼ 9.23 ml min1, cathode ¼ 1170 ml min1 (dry air) - Concentration of methanol: 0.4, 0.8, 1.2 mol L1 - Cell temperature: 40, 60, 80 C - Electric load: the current was increased from 0 A to a certain value until the voltage remains above 0.4 V with a stepwise increment of 4 A. There are several methods to measure the rates of methanol crossover in DMFCs. One of the methods is to measure the concentration of CO2 in the out-flowing air from the cathode because most of the crossed methanol is oxidized to CO2 at the cathode [16]. For example, Casalegno et al. [17] and Dohle et al. [18] measured the concentration of CO2 in the effluent air to calculate total fluxes of methanol crossover. Therefore, we have measured the concentrations of CO2 by attaching a CO2 analyzer (Vaisala GMP70) to the cathode outlet to determine the methanol crossover rates, with the assumption that the unreacted methanol is negligibly small [17]. However, the observed CO2 in the effluent air is not solely due to methanol crossover, but part of it is due to CO2 crossover from the anode through the diffusion and convection mechanisms [19]. It is not easy to measure the rate of CO2 crossover precisely because it also varies depending on the operating conditions. Therefore, we have decided to use the
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data from Drake et al. [19] even though the data is slightly different from the real values of our system. The total CO2 flux measured at the cathode outlet is expressed as: (12) 0:5XCO2 þ 1 Nm-CO2 ¼ XCO2 FO2 15i=F þ FN2 The rate of methanol consumption by crossover (Nm,x) is the total CO2 flux measured at the cathode outlet ðNm-CO2 Þ minus CO2 crossover ðNx-CO2 Þ (Eq. (13)), and the total rate of methanol consumption at the anode is the sum of the rates of methanol consumption by electrochemical oxidation and methanol crossover (Eq. (14)). Nm;x ¼ Nm-CO2 Nx-CO2
(13)
Nm;t ¼ Nm;e þ Nm;x
(14)
Therefore, to measure the CO2 flux at the cathode outlet ðNm-CO2 Þ, there is a need to calculate the rate of methanol consumption based on the applied current (Nm,e), and also used the CO2 crossover ðNx-CO2 Þ data taken from the literature [19], then we have calculated the pure rate of methanol crossover (Nm,x) and the total consumption rate of methanol at the anode (Nm,t). In developing these equations, we have neglected O2 and N2 diffusion across the membrane from the cathode to the anode.
3.2. Control of methanol concentration in the DMFC system We have set-up an experimental condition to evaluate the performance of the SLCC for the DMFCs (see Fig. 3). Three liquid pumps and one air pump were installed with the system. The liquid pumps were used for feeding pure methanol from the methanol reservoir, supplying pure water to the mixing chamber, and re-circulating the methanol solution to the cell. All the pumps were operated upon pulse signals routed by the computer equipped with a LabVIEW software and a DAQ board (National Instruments). When the level of liquid in the methanol mixing chamber was lowered below its target volume of 100 ml, the water feeding pump started supplying pure water from the water reservoir to the chamber. A refractive index detector (RID) was calibrated with methanol solutions of different concentrations and used as a methanol sensor. The RID was connected in line just in front of the anode inlet of a cell, where a part of the methanol solution was circulated through the RID.
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Experiments were conducted to test the performance of SLCC for the target concentrations of 0.4 M and 0.8 M at an operating temperature of 60 C and 1 atm.
4.
Results and discussion
4.1.
Measurement of methanol consumption rates
As mentioned in the experimental section, in order to build a database to estimate the methanol crossover rates we have measured the concentrations of CO2 in the effluent air stream from the cathode at different concentrations of methanol feed (0.4–1.2 M), cell temperatures (40–80 C), and electric loads (0–225 mA cm2). As shown in Fig. 6 the concentration of CO2 in the effluent air decreased by increasing the current density from 0 to 225 mA cm2 regardless of the temperature of a cell, except the case with the concentration of methanol feed of 1.2 M. This is because when the current density increases, large amount of methanol can be consumed at the anode and thus, the concentration of methanol at the interface between the anode and the membrane decreases, leading to reduce the crossover rate of methanol [17]. However, the slopes of CO2 concentration vs. current density (Table 1) increased with increasing the concentration of methanol and the curves for 1.2 M are almost flat for all the tested temperatures. This shows that the increased concentration of methanol at the anode–membrane interfaces has an impact on the rate of methanol crossover. On the other hand, the CO2 flux is also increased with increasing the temperature of a cell. Based on the data of Fig. 4, the rates of methanol crossover are obtained by subtracting rates of CO2 crossover from the total CO2 fluxes at the cathode outlet as described in Eq. (13). As mentioned in the preceding section the rates of CO2 crossover are not measured in this study, but borrowed from the literature [19]. The total rates of methanol consumption at the anode are calculated by adding the contributions from the electrochemical oxidation of methanol at the anode and methanol crossover from anode to cathode as described in Eq. (14). The total rates of methanol consumption in Fig. 5 are linearly proportional to the current density with linearity coefficients higher than 0.996 (see Table 2) for all cases tested even though the methanol crossover rates decreased with the
Fig. 3 – DMFC system with methanol re-circulation and control process.
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Table 1 – Rates of change in the concentration of CO2 as a function of current Methanol concentration (mol L1) 0.4 0.4 0.4 0.8 0.8 0.8
Temperature ( C)
Slope (mA1 min1)
40 60 80 40 60 80
8E05 5E05 7E05 2E05 4E05 3E05
current density as shown in Fig. 4. This manifests that the contribution of the electrochemical oxidation of methanol to the consumption rate is much higher than the drop in the methanol crossover rate due to lowered interfacial methanol concentration. The slopes are almost constant regardless of the concentration of methanol and the temperature of a cell.
4.2. The sensor-less control for concentration of methanol Before testing the sensor-less control system, we have observed the spontaneous drop of concentration of methanol in a DMFC system at an open circuit condition. As illustrated in Fig. 6, the concentration of the re-circulating methanol stream is lowered in the course of time, before adding fresh methanol into the methanol stream. This drop in concentration of methanol at zero current is only due to the methanol crossover from anode to cathode as shown in Figs. 4 and 5. The rate of concentration drop will be proportional to the size of fuel cell and inversely proportional to the volume of the methanol mixing chamber. Therefore, to maintain the concentration of methanol feed at a constant level in a recirculating DMFC system, the methanol has to be refilled with the same rate as with the rate of methanol consumption in the system. One of the problems in this type of sensor-less control system is that it cannot measure the exact concentration of methanol in the feed stream during the operation. Therefore, if the concentration of methanol deviates from a target value for any reasons, it might create some problem during the operation of a DMFC system. Fig. 7 shows the time profile for
Fig. 5 – Rates of methanol consumption at the anode as a function of the electric load applied at various temperatures and concentration of methanol feed.
concentration of methanol in approaching a set point of 0.8 M when the initial concentration of the stream is 0.6 M. Under the given operating conditions, the concentration gradually rises and it takes nearly about 100 min to reach the target concentration. In the SLCC system, we can only calculate the rates of methanol consumption under the given conditions assuming that its concentration is at the set point. Therefore, supplying rate of methanol to the stream is higher than the required amount to maintain the concentration of methanol, when the initial concentration is lower than the set point. On the contrary, supplying rate of methanol will be lower than the required amount, when the initial concentration is higher than the set point. Hence, the concentration of methanol in the feed stream gradually converges to the target value when the initial concentration is deviated from the set point. The time to set point and the amplitude of fluctuation are also dependent on many parameters such as, the pumping rate, the amount of electric load, and total volume of the anode feed loop including methanol mixing chamber, tubes, and anode channels. In our experiment, we have used a relatively larger mixing chamber of 100 ml for a single cell; and we assume that using this high volume capacity of the chamber is
Table 2 – Linearity coefficients between the rate of methanol consumption and current Methanol concentration (mol L1)
Fig. 4 – Concentration of CO2 in the effluent gas at various current densities, temperatures, and concentrations of methanol feed.
0.4 0.4 0.4 0.8 0.8 0.8 1.2 1.2 1.2
Temperature ( C)
Linearity coefficient
40 60 80 40 60 80 40 60 80
0.9971 0.9986 0.9996 0.9988 0.9981 0.999 0.9984 0.9991 0.9962
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Fig. 6 – Spontaneous drop of concentration of methanol at an open circuit condition (T [ 60 8C).
one of the reasons for the sluggish approaching rate to the target concentration in Fig. 7. Now, we discuss the performance of the SLCC when the DMFC is operated under the dynamic mode with its initial concentration of methanol at a set point to save time while reaching the point. Figs. 8 and 9 show the concentration and voltage profiles that are recorded for the set points of 0.4 M and 0.8 M, respectively, while altering the current stepwise from 0 to 110 mA cm2. When the SLCC is operated at its set point of 0.4 M, the concentration fluctuated around the set point while supplying methanol and water as shown in Fig. 8. In Fig. 8a, one can see that the deviation from the set point getting larger as the electric load (current) increases: the feed concentration reaches 0.52 M at a current density of 110 mA cm2. From the inserted graph, it is confirmed that the abrupt drop and recovery of methanol concentration when water is supplied to the mixing chamber to keep the solution level constant. Fig. 8b shows the voltage profile during operation with the SLCC. As in the case of methanol profile (see Fig. 8a), the voltage fluctuated with amplitude of about 30 mV,
Fig. 7 – Concentration profile from low initial concentration at an open circuit condition (T [ 60 8C).
Fig. 8 – (a) Concentration profile at the desired concentration of 0.4 M (T [ 60 8C). (b) Voltage profile at the desired concentration of 0.4 M (T [ 60 8C).
but it does not diverse far away from average values. As shown in the insert, slight slumps appeared at the transient states of load change; these slumps are speculated to be caused by slow mass transport of methanol in the anode just when the electric load is raised and thus large amount of methanol is consumed instantaneously [20]. Fig. 9a and b shows the concentration and voltage profiles at the set point of 0.8 M. The shapes of the profiles are almost the same as in the case of 0.4 M, but the amplitudes of the fluctuation are larger: the concentration reached as high as 1.0 M at a current density of 110 mA cm2. From these results, it is understood that the control of methanol concentration with our SLCC is found to be satisfactory and the fluctuation in the concentration of methanol during the operation does not have a significant effect on the performance of the DMFCs. The deviations of concentration of methanol from the set points increase by increasing the electric load, but they do not diverge more than 20% from the set points. Further, we believe that these deviations obviously originate from the errors in calculating the methanol crossover rates. In fact, the deviations are positive from the set points and they increase by increasing the electric load, indicating that the methanol crossover rates are overly by taking into account the calculation of the methanol consumption rates. In view of Eq. (14), the errors in the rates of methanol crossover could be
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purpose, we have constructed a database to measure the rates of methanol consumption under various operating conditions such as, changing the electric load, temperature, and concentration of methanol. Under the given operating conditions, the control system is able to calculate the rates of methanol consumption and provide orders to a methanol feeding pump to insert calculated amounts of methanol in a methanol mixing chamber of a DMFC system. From a series of experimental findings, it has been found that the sensor-less methanol control system is able to work to the satisfactory level and it could maintain the concentration of methanol around a target concentration for a long period with a deviation of less than 20%. This system can also work successfully when it is subjected to change of load during the operation. In future study, we can improve our sensor-less control system by utilizing better data for the rates of methanol consumption.
Acknowledgements The authors are grateful for the financial support from ‘‘National RD&D Organization for Hydrogen & Fuel Cell’’ and ‘‘New and Renewable Energy Center’’ which is an affiliated organization of the Ministry of Commerce, Industry and Energy, Korea. Fig. 9 – (a) Concentration profile at the desired concentration of 0.8 M (T [ 60 8C). (b) Voltage profile at the desired concentration of 0.8 M (T [ 60 8C).
caused by either CO2 measurements at the cathode outlet or rates of CO2 crossover data taken from another paper [19]. This argument seems to be reasonable because the variation in the rates of CO2 crossover depends on the type of MEA and operating conditions used to measure the crossover rates. As shown in Figs. 4 and 5 and in Table 2, the measured CO2 data appears to be reasonable and reliable. Therefore, it is suspected that the real CO2 crossover rates are still smaller than what has been shown. In future study, we would like to make careful attempts to measure the rates of CO2 crossover in a more precise way to improve the accuracy of our control system. Fortunately, since the effect of concentration of methanol on the performance of DMFCs is not significant when the concentration of methanol is maintained in the range of 0.5–1.5 M, the sensor-less control system can safely be used as long as the concentration fluctuation is confined within about 20% of the set points.
5.
Conclusion
In this study, we have been able to evolve and design our own version of a sensor-less system to control the concentration of methanol for the use of DMFCs based on the estimation of rates of methanol consumption. For this
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experimental validation of fluxes. J Membr Sci 2006;276: 272–85. Wang JT, Wasmus S, Savinell RF. Real-time mass spectrometric study of the methanol crossover in a direct methanol fuel cell. J Electrochem Soc 1996;143(4):1233–9. Casalegno A, Grassini P, Marchesi R. Experimental analysis of methanol cross-over in a direct methanol fuel cell. Appl Therm Eng 2007;27:748–54. Dohle H, Divisek J, Mergel J, Oetjen HF, Zingler C, Stolten D. Recent developments of the measurement of the methanol permeation in a direct methanol fuel cell. J Power Sources 2002;105:274–82. Drake JA, Wilson W, Killeen K. Evaluation of the experimental model for methanol crossover in DMFCs. J Electrochem Soc 2004;151(3):A413–7. Kim D, Lee J, Lim T, Oh I, Ha HY. Operational characteristics of a 50W DMFC stack. J Power Sources 2006;155:203–12.
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Sensor-less control of methanol concentration based on estimation of methanol consumption rates for direct methanol fuel cell systems Tae Jung Haa,b, Jong-Ho Kima, Han-Ik Joha, Soo-Kil Kima, Go-Young Moonc, Tae-Hoon Lima, Chonghun Hanb,**, Heung Yong Haa,* a
Fuel cell Research Center, Korea Institute of Science and Technology (KIST), 39-1 Hawolgok-dong, P.O. Box 131, Seongbuk-gu, Cheongyang, Seoul 130-650, South Korea b School of Chemical & Biological Engineering and Institute of Chemical Process, Seoul National University, San 56-1, Shillim-dong, Kwanak-ku, Seoul 151-744, South Korea c Corporate R&D Center, LG Chem, Ltd., Munji-dong, Yuseong-gu, Daejeon 305-380, South Korea
article info
abstract
Article history:
Adequate control over the concentration of methanol is critically needed in operating
Received 30 May 2008
direct methanol fuel cell (DMFC) systems, because performance and energy efficiency of
Received in revised form
the systems are primarily dependent on the concentration of methanol feed. For this
24 August 2008
purpose, we have built a sensor-less control logic that can operate based on the estimation
Accepted 1 September 2008
of the rates of methanol consumption in a DMFC. The rates of methanol consumption are
Available online 2 November 2008
measured in a cell and the resulting data are fed as an input to the control program to calculate the amount of methanol required to maintain the concentration of methanol at
Keywords:
a set value under the given operating conditions of a cell. The sensor-less control has been
Direct methanol fuel cell (DMFC)
applied to a DMFC system employed with a large-size single cell and the concentration of
Fuel circulation loop
methanol is found to be controlled stably to target concentrations even though there are
Sensor-less methanol concentration
some deviations from the target values.
control
ª 2008 International Association for Hydrogen Energy. Published by Elsevier Ltd. All rights
Methanol consumption rate
reserved.
Methanol crossover
1.
Introduction
Direct methanol fuel cells (DMFCs) have many advantages over other types of fuel cells because of their easy refueling, simple balance of plant (BOP) and high energy density. In order to obtain a maximum performance of a DMFC, the operating conditions such as, the cell temperature, methanol feed concentration, and air flow rate should be optimized. Of all the operating conditions, the concentration of methanol is
an important factor, because it plays a key role in affecting the performance, durability and energy efficiency of DMFC systems [1,2]. In fact, the higher concentration of methanol is required to reduce the anode overpotential, which is normally exaggerated by the limited methanol diffusion rate from the flow field to the catalyst layer of the anode at a high current region [3,4]. However, it induces higher methanol crossover resulting in mixed potential in the cathode, which can lead to lower performance of a cell and lower energy efficiency.
* Corresponding author. Tel.: þ82 2 958 5275; fax: þ82 2 958 5199. ** Corresponding author. Tel.: þ82 2 880 1887; fax: þ82 2 873 2767. E-mail addresses: [email protected] (C. Han), [email protected] (H.Y. Ha). 0360-3199/$ – see front matter ª 2008 International Association for Hydrogen Energy. Published by Elsevier Ltd. All rights reserved. doi:10.1016/j.ijhydene.2008.09.019
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Nomenclature C Ci F A Fa Fc FO2 FN 2 i Nm,f Nm,t Nm,e
Nm,x Nm-CO2 Nx-CO2 T V Vi XCO2
methanol concentration (mol L1) initial methanol concentration (mol L1) Faraday constant (C mol1) active surface area of a cell (cm2) liquid flux in the anode compartment (mol cm2 min1) air flux in the cathode compartment (mol cm2 min1) oxygen flux (mol cm2 min1) nitrogen flux (mol cm2 min1) current density (A cm2) methanol feed rate per unit area (mol cm2 min1) total methanol consumption rate per unit area (mol cm2 min1) methanol consumption rate per unit area by the electrochemical reaction at the anode (mol cm2 min1) methanol consumption rate per unit area by crossover (mol cm2 min1) measured CO2 flux at the cathode (mol cm2 min1) CO2 crossover flux from anode to cathode (mol cm2 min1) fuel cell temperature ( C) total liquid volume in a methanol mixing chamber (L) initial liquid volume in a methanol mixing chamber (L) volumetric concentration of CO2 in the cathode effluent ()
Therefore, concentration of methanol feed needs to be maintained adequately at a predetermined level to ensure a stable and energy-efficient DMFC operation. In active DMFC systems, the methanol pump, which is used to supply methanol solution to the cell should be equipped with methanol sensor to monitor and control the methanol concentration in the inlet stream of the cell [5]. There are various concentration sensors available in the market based on different principles. Zhao et al. [6] used various concentration sensors to evaluate their suitability for the DMFC. Some concentration sensors are utilized to study the physical propensities of methanol solution particularly, the density of methanol [7,8]. Other concentration sensors are used based on the electrochemical reactions in the cell by means of applying electric potential [9,10]. The former type is used to accurately measure the concentration of methanol. However, they are expensive and too big in size to be mounted with the portable DMFC systems. On the other hand, the latter type is cheaper and smaller, but they suffer from poor stability and reliability, because of degradation of the catalyst in the sensors during the usage. The work related with using sensor-less control systems for the DMFC is relatively rare [11–14]. Sudo [11] devised a sensor-less methanol concentration system by constructing a DMFC stack consisting of two sub-stacks, which are
connected in series and the out-flowing methanol solution from the first sub-stack is introduced to the second one. The voltage difference between the two sub-stacks is compared and used as an indication for the change of concentration of methanol during the operation. This method is not affected by the degradation of the membrane-electrode assembly, but it may work only in a limited concentration range. Acker et al. [12] introduced a method to regulate the methanol concentration by continually monitoring the open circuit potentials or short circuit currents. However, in this method, the operating stability and the control of accuracy might be affected by degradation of the MEA during a long-term operation. In another study, Chiu and Lien [13] suggested an alternative method for measuring the methanol concentration by designing an estimation algorithm to build a constant concentration surfaces with respect to cell voltages. However, this method is also vulnerable to degradation of the MEA, because the same voltage cannot be obtained even with a feed of the same methanol concentration if the MEA is deteriorated for any reasons during the course of operation. Chang et al. [14], made a sensor-less control algorithm by using the impulse responses based on the discrete time fuel injection. In fact, this method is not affected by degradation of the MEA, but may not be suitable to dynamic operating conditions that undergo changes in voltage as well as current. As briefly mentioned above, the sensor-less methanol control systems in the literature have some defects in and of themselves. Therefore, we have made an attempt to make our own version and that can satisfy three critical requirements listed below: - It should not be affected by degradation of the MEA during operation. - It should work even under dynamic operating conditions. - It should not be affected by the electric loads applied to the fuel cell systems. The purpose of our study is to make a sensor-less methanol-concentration control system (SLCC) for the DMFCs. In order to do that, we have designed an algorithm to control concentration of methanol and constructed a database that consists of experimental data for the rates of methanol consumption under various operating conditions. Thus formed SLCC has been applied to a real DMFC system to evaluate its accuracy by varying the target concentration.
2.
Building control algorithms for DMFCs
2.1.
Configuration of a DMFC system
In a simple DMFC system, the unreacted methanol exhausted out of the system without reuse. The energy density of this type of system, which is proportional to the amount of the methanol in the reservoir of the system becomes very low because of using low concentration of methanol, usually below 2.0 M (about 6 vol% aqueous solutions). In order to increase the energy density, a pure or high concentration methanol solution needs to be stored in a reservoir even though the concentration of methanol in the feed stream of
international journal of hydrogen energy 33 (2008) 7163–7171
the cell is maintained at a lower concentration, probably below 2 M. For this purpose, the unreacted methanol solution has to be re-circulated and a high concentrated methanol solution should be added to the stream to adjust for the consumed methanol and to keep the concentration of feed methanol at a constant level as shown in Fig. 1. In addition to methanol, water is also consumed by participating in the methanol oxidation reaction in the anode; and it is permeated to the cathode, usually driven by a difference in the activity of water between the electrodes and by electro-osmotic drag [15]. Therefore, water should also be continuously compensated to the methanol stream by any means. Accommodation of largesize pure water reservoir in a DMFC system, however, is unrealistic because it can increase the volume of a system, thereby lowering the power density, in addition it might also increase the cost of the DMFC system. In that situation, the water produced in the cathode side can be captured by using a heat exchanger, which in turn, can be re-circulated to the anode side.
2.2. The sensor-less methanol-concentration control system (SLCC) As mentioned in the previous section, we have aimed to formulate a sensor-less methanol-concentration control system (SLCC) by predicting the rates of methanol consumption under a range of fuel cell operating conditions. In order to do this, first, we have developed relevant equations to correlate the total rates of methanol consumption with those by the electrochemical reaction at the anode, in addition to methanol crossover to the cathode. The mass balance equation for methanol in the entire anode feed loop including anode channels, tubing, and a methanol mixing chamber, where methanol solution exists is as follows: One can get methanol concentration (C ) at time t from Eq. (1): Z (1) VC ¼ Vi Ci þ vðVCÞ=vtdt If we assume that the total liquid volume in the whole anode feed loop remains constant, then Eq. (1) becomes vðVCÞ=vt ¼ VvC=vt at V is constant C ¼ Ci þ
Z vC=vtdt
(2) (3)
where, V is the liquid volume of a methanol mixing chamber at time t, Vi is the initial volume of liquid, C is the
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concentration of methanol of the mixing chamber at time t, Ci is initial concentration of methanol. Eq. (3) indicates that concentration of methanol at time t (C ) is the sum of the initial concentration of methanol and the integrated amount of change of concentration of methanol until time t. On the other hand, the change in concentration of methanol in the solution is the difference between the methanol feeding rate from the methanol reservoir (Nm,f) and the methanol consumption rate at the anode side compartment (Nm,t). (4) vC=vt ¼ Nm;f Nm;t V vC=vt ¼ 0 at Nm;f ¼ Nm;t
(5)
C ¼ Ci: Ci is a target concentration in this case Therefore, the concentration of methanol does not change if the methanol feeding rate (Nm,f) from the reservoir is the same as the total methanol consumption rate (Nm,t). In this case, one can maintain desired concentrations if the initial concentration is the same to that of the target value, while other conditions are well under the control. Therefore, first of all, we have to create a sensor-less methanol-concentration control system (SLCC) as a tool that can accurately predict the rates of methanol consumption under any operating conditions. As described in Eqs. (6) and (7), the total rate of methanol consumption (Nm,t) is sum of the electrochemical methanol oxidation rate (Nm,e) that is proportional to the electric load applied and the methanol crossover rate (Nm,x) from the anode to the cathode through diffusion and electro-osmotic drag. Some loss of methanol can also be anticipated at the gas–liquid separator in the anode-side circulating loop because the exhausted methanol vapor entrained in the CO2 stream that comes out of the anode compartment of a cell. However, in this study, we assume that the loss is negligibly small when compared with the rate of methanol consumption in a cell; because the concentration of methanol is maintained lower than 1 mol L1 and the temperature of the methanol solution in the gas–liquid separator is relatively low at around 40 C. The variation of methanol crossover rate (Nm,x) depends on the load (i) and other operating conditions like temperature, flow rates of reactants, and the concentration of methanol (Eq. (8)). Nm;t ¼ Nm;e þ Nm;x
(6)
Nm;e ¼ f ðiÞ ¼ 10i=F
(7)
Fig. 1 – Configuration of a DMFC system with methanol re-circulation.
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Nm;x ¼ f ði; T; C; Fa ; Fc Þ
(8)
Nm;x ¼ f ði; T; CÞ at constant Fa and Fc
(9)
If we could formulate an equation to predict precisely the rate of methanol consumption at any operating condition, then it would be very easy to create a SLCC. However, it is not as easy as mentioned above. The simple way to make a tool to predict the rates of methanol consumption is to build a database by collecting them through the experiments under various operating conditions within a limited range of our interest. We have carried out a set of experiments to measure methanol crossover rates (Nm,x in Eq. (9)) at different operating conditions by varying current (electric load), temperature, and concentration of methanol. The total rate of methanol consumption that is required to calculate the methanol supply rate is a function of current and temperature (Eq. (10)). By using the experimental data obtained under varying currents and temperatures, a least square regression using Eq. (11) is carried out to calculate the values of the constants in Eq. (10). Therefore, in this model, the current and the temperature are treated as independent variables (input value), and the rate of methanol consumption as a dependent variable (output value) that is calculated with a given set of experimental conditions. Concentration of methanol is also not a variable because the set point for the concentration of methanol does not change during the operation of DMFC in this study. Nm;t ¼ a0 þ a1 T þ a2 i at specific methanol concentration 2
n 6PT 4 P j ij
P T P j2 T P j Tj ij
P 38 9 8 P 9 i P j 7< a0 = < P Nm;t;j = Ti 5 a TN ¼ P j2 j : 1 ; : P j m;t;j ; ij Nm;t;j a2 ij
(10)
(11)
By completing the Eq. (10) that can calculate the rates of methanol consumption, we could set up an algorithm to control the concentration of methanol to a target value in a DMFC system as shown in Fig. 2. Measured temperatures and currents are input to Eq. (10) and then the amount of pure methanol to be supplied to the methanol mixing chamber is calculated. In this system, the total volume of an aqueous solution in the methanol feeding loop that includes a mixing chamber, an anode compartment of a fuel cell, and connecting tubes is maintained constant by continuously supplying the water condensate from the cathode side.
3.
Fig. 2 – Algorithm to control the concentration of methanol through calculating the rates of methanol consumption based on the database that matches the operating conditions.
Experimental
3.1. Measurement of methanol consumption rates in a DMFC We have used a large-size single DMFC with an active area of 138 cm2 to measure methanol crossover rates by varying current, temperature, and concentration of methanol under a fixed flow rate of air and methanol solution. - MEA: size 138 cm2, Nafion 115, anode ¼ 6 mg-PtRu cm2, cathode ¼ 4 mg-Pt cm2
- Flow field: parallel serpentine type - Flow rates of the reactants: anode ¼ 9.23 ml min1, cathode ¼ 1170 ml min1 (dry air) - Concentration of methanol: 0.4, 0.8, 1.2 mol L1 - Cell temperature: 40, 60, 80 C - Electric load: the current was increased from 0 A to a certain value until the voltage remains above 0.4 V with a stepwise increment of 4 A. There are several methods to measure the rates of methanol crossover in DMFCs. One of the methods is to measure the concentration of CO2 in the out-flowing air from the cathode because most of the crossed methanol is oxidized to CO2 at the cathode [16]. For example, Casalegno et al. [17] and Dohle et al. [18] measured the concentration of CO2 in the effluent air to calculate total fluxes of methanol crossover. Therefore, we have measured the concentrations of CO2 by attaching a CO2 analyzer (Vaisala GMP70) to the cathode outlet to determine the methanol crossover rates, with the assumption that the unreacted methanol is negligibly small [17]. However, the observed CO2 in the effluent air is not solely due to methanol crossover, but part of it is due to CO2 crossover from the anode through the diffusion and convection mechanisms [19]. It is not easy to measure the rate of CO2 crossover precisely because it also varies depending on the operating conditions. Therefore, we have decided to use the
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data from Drake et al. [19] even though the data is slightly different from the real values of our system. The total CO2 flux measured at the cathode outlet is expressed as: (12) 0:5XCO2 þ 1 Nm-CO2 ¼ XCO2 FO2 15i=F þ FN2 The rate of methanol consumption by crossover (Nm,x) is the total CO2 flux measured at the cathode outlet ðNm-CO2 Þ minus CO2 crossover ðNx-CO2 Þ (Eq. (13)), and the total rate of methanol consumption at the anode is the sum of the rates of methanol consumption by electrochemical oxidation and methanol crossover (Eq. (14)). Nm;x ¼ Nm-CO2 Nx-CO2
(13)
Nm;t ¼ Nm;e þ Nm;x
(14)
Therefore, to measure the CO2 flux at the cathode outlet ðNm-CO2 Þ, there is a need to calculate the rate of methanol consumption based on the applied current (Nm,e), and also used the CO2 crossover ðNx-CO2 Þ data taken from the literature [19], then we have calculated the pure rate of methanol crossover (Nm,x) and the total consumption rate of methanol at the anode (Nm,t). In developing these equations, we have neglected O2 and N2 diffusion across the membrane from the cathode to the anode.
3.2. Control of methanol concentration in the DMFC system We have set-up an experimental condition to evaluate the performance of the SLCC for the DMFCs (see Fig. 3). Three liquid pumps and one air pump were installed with the system. The liquid pumps were used for feeding pure methanol from the methanol reservoir, supplying pure water to the mixing chamber, and re-circulating the methanol solution to the cell. All the pumps were operated upon pulse signals routed by the computer equipped with a LabVIEW software and a DAQ board (National Instruments). When the level of liquid in the methanol mixing chamber was lowered below its target volume of 100 ml, the water feeding pump started supplying pure water from the water reservoir to the chamber. A refractive index detector (RID) was calibrated with methanol solutions of different concentrations and used as a methanol sensor. The RID was connected in line just in front of the anode inlet of a cell, where a part of the methanol solution was circulated through the RID.
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Experiments were conducted to test the performance of SLCC for the target concentrations of 0.4 M and 0.8 M at an operating temperature of 60 C and 1 atm.
4.
Results and discussion
4.1.
Measurement of methanol consumption rates
As mentioned in the experimental section, in order to build a database to estimate the methanol crossover rates we have measured the concentrations of CO2 in the effluent air stream from the cathode at different concentrations of methanol feed (0.4–1.2 M), cell temperatures (40–80 C), and electric loads (0–225 mA cm2). As shown in Fig. 6 the concentration of CO2 in the effluent air decreased by increasing the current density from 0 to 225 mA cm2 regardless of the temperature of a cell, except the case with the concentration of methanol feed of 1.2 M. This is because when the current density increases, large amount of methanol can be consumed at the anode and thus, the concentration of methanol at the interface between the anode and the membrane decreases, leading to reduce the crossover rate of methanol [17]. However, the slopes of CO2 concentration vs. current density (Table 1) increased with increasing the concentration of methanol and the curves for 1.2 M are almost flat for all the tested temperatures. This shows that the increased concentration of methanol at the anode–membrane interfaces has an impact on the rate of methanol crossover. On the other hand, the CO2 flux is also increased with increasing the temperature of a cell. Based on the data of Fig. 4, the rates of methanol crossover are obtained by subtracting rates of CO2 crossover from the total CO2 fluxes at the cathode outlet as described in Eq. (13). As mentioned in the preceding section the rates of CO2 crossover are not measured in this study, but borrowed from the literature [19]. The total rates of methanol consumption at the anode are calculated by adding the contributions from the electrochemical oxidation of methanol at the anode and methanol crossover from anode to cathode as described in Eq. (14). The total rates of methanol consumption in Fig. 5 are linearly proportional to the current density with linearity coefficients higher than 0.996 (see Table 2) for all cases tested even though the methanol crossover rates decreased with the
Fig. 3 – DMFC system with methanol re-circulation and control process.
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Table 1 – Rates of change in the concentration of CO2 as a function of current Methanol concentration (mol L1) 0.4 0.4 0.4 0.8 0.8 0.8
Temperature ( C)
Slope (mA1 min1)
40 60 80 40 60 80
8E05 5E05 7E05 2E05 4E05 3E05
current density as shown in Fig. 4. This manifests that the contribution of the electrochemical oxidation of methanol to the consumption rate is much higher than the drop in the methanol crossover rate due to lowered interfacial methanol concentration. The slopes are almost constant regardless of the concentration of methanol and the temperature of a cell.
4.2. The sensor-less control for concentration of methanol Before testing the sensor-less control system, we have observed the spontaneous drop of concentration of methanol in a DMFC system at an open circuit condition. As illustrated in Fig. 6, the concentration of the re-circulating methanol stream is lowered in the course of time, before adding fresh methanol into the methanol stream. This drop in concentration of methanol at zero current is only due to the methanol crossover from anode to cathode as shown in Figs. 4 and 5. The rate of concentration drop will be proportional to the size of fuel cell and inversely proportional to the volume of the methanol mixing chamber. Therefore, to maintain the concentration of methanol feed at a constant level in a recirculating DMFC system, the methanol has to be refilled with the same rate as with the rate of methanol consumption in the system. One of the problems in this type of sensor-less control system is that it cannot measure the exact concentration of methanol in the feed stream during the operation. Therefore, if the concentration of methanol deviates from a target value for any reasons, it might create some problem during the operation of a DMFC system. Fig. 7 shows the time profile for
Fig. 5 – Rates of methanol consumption at the anode as a function of the electric load applied at various temperatures and concentration of methanol feed.
concentration of methanol in approaching a set point of 0.8 M when the initial concentration of the stream is 0.6 M. Under the given operating conditions, the concentration gradually rises and it takes nearly about 100 min to reach the target concentration. In the SLCC system, we can only calculate the rates of methanol consumption under the given conditions assuming that its concentration is at the set point. Therefore, supplying rate of methanol to the stream is higher than the required amount to maintain the concentration of methanol, when the initial concentration is lower than the set point. On the contrary, supplying rate of methanol will be lower than the required amount, when the initial concentration is higher than the set point. Hence, the concentration of methanol in the feed stream gradually converges to the target value when the initial concentration is deviated from the set point. The time to set point and the amplitude of fluctuation are also dependent on many parameters such as, the pumping rate, the amount of electric load, and total volume of the anode feed loop including methanol mixing chamber, tubes, and anode channels. In our experiment, we have used a relatively larger mixing chamber of 100 ml for a single cell; and we assume that using this high volume capacity of the chamber is
Table 2 – Linearity coefficients between the rate of methanol consumption and current Methanol concentration (mol L1)
Fig. 4 – Concentration of CO2 in the effluent gas at various current densities, temperatures, and concentrations of methanol feed.
0.4 0.4 0.4 0.8 0.8 0.8 1.2 1.2 1.2
Temperature ( C)
Linearity coefficient
40 60 80 40 60 80 40 60 80
0.9971 0.9986 0.9996 0.9988 0.9981 0.999 0.9984 0.9991 0.9962
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Fig. 6 – Spontaneous drop of concentration of methanol at an open circuit condition (T [ 60 8C).
one of the reasons for the sluggish approaching rate to the target concentration in Fig. 7. Now, we discuss the performance of the SLCC when the DMFC is operated under the dynamic mode with its initial concentration of methanol at a set point to save time while reaching the point. Figs. 8 and 9 show the concentration and voltage profiles that are recorded for the set points of 0.4 M and 0.8 M, respectively, while altering the current stepwise from 0 to 110 mA cm2. When the SLCC is operated at its set point of 0.4 M, the concentration fluctuated around the set point while supplying methanol and water as shown in Fig. 8. In Fig. 8a, one can see that the deviation from the set point getting larger as the electric load (current) increases: the feed concentration reaches 0.52 M at a current density of 110 mA cm2. From the inserted graph, it is confirmed that the abrupt drop and recovery of methanol concentration when water is supplied to the mixing chamber to keep the solution level constant. Fig. 8b shows the voltage profile during operation with the SLCC. As in the case of methanol profile (see Fig. 8a), the voltage fluctuated with amplitude of about 30 mV,
Fig. 7 – Concentration profile from low initial concentration at an open circuit condition (T [ 60 8C).
Fig. 8 – (a) Concentration profile at the desired concentration of 0.4 M (T [ 60 8C). (b) Voltage profile at the desired concentration of 0.4 M (T [ 60 8C).
but it does not diverse far away from average values. As shown in the insert, slight slumps appeared at the transient states of load change; these slumps are speculated to be caused by slow mass transport of methanol in the anode just when the electric load is raised and thus large amount of methanol is consumed instantaneously [20]. Fig. 9a and b shows the concentration and voltage profiles at the set point of 0.8 M. The shapes of the profiles are almost the same as in the case of 0.4 M, but the amplitudes of the fluctuation are larger: the concentration reached as high as 1.0 M at a current density of 110 mA cm2. From these results, it is understood that the control of methanol concentration with our SLCC is found to be satisfactory and the fluctuation in the concentration of methanol during the operation does not have a significant effect on the performance of the DMFCs. The deviations of concentration of methanol from the set points increase by increasing the electric load, but they do not diverge more than 20% from the set points. Further, we believe that these deviations obviously originate from the errors in calculating the methanol crossover rates. In fact, the deviations are positive from the set points and they increase by increasing the electric load, indicating that the methanol crossover rates are overly by taking into account the calculation of the methanol consumption rates. In view of Eq. (14), the errors in the rates of methanol crossover could be
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purpose, we have constructed a database to measure the rates of methanol consumption under various operating conditions such as, changing the electric load, temperature, and concentration of methanol. Under the given operating conditions, the control system is able to calculate the rates of methanol consumption and provide orders to a methanol feeding pump to insert calculated amounts of methanol in a methanol mixing chamber of a DMFC system. From a series of experimental findings, it has been found that the sensor-less methanol control system is able to work to the satisfactory level and it could maintain the concentration of methanol around a target concentration for a long period with a deviation of less than 20%. This system can also work successfully when it is subjected to change of load during the operation. In future study, we can improve our sensor-less control system by utilizing better data for the rates of methanol consumption.
Acknowledgements The authors are grateful for the financial support from ‘‘National RD&D Organization for Hydrogen & Fuel Cell’’ and ‘‘New and Renewable Energy Center’’ which is an affiliated organization of the Ministry of Commerce, Industry and Energy, Korea. Fig. 9 – (a) Concentration profile at the desired concentration of 0.8 M (T [ 60 8C). (b) Voltage profile at the desired concentration of 0.8 M (T [ 60 8C).
caused by either CO2 measurements at the cathode outlet or rates of CO2 crossover data taken from another paper [19]. This argument seems to be reasonable because the variation in the rates of CO2 crossover depends on the type of MEA and operating conditions used to measure the crossover rates. As shown in Figs. 4 and 5 and in Table 2, the measured CO2 data appears to be reasonable and reliable. Therefore, it is suspected that the real CO2 crossover rates are still smaller than what has been shown. In future study, we would like to make careful attempts to measure the rates of CO2 crossover in a more precise way to improve the accuracy of our control system. Fortunately, since the effect of concentration of methanol on the performance of DMFCs is not significant when the concentration of methanol is maintained in the range of 0.5–1.5 M, the sensor-less control system can safely be used as long as the concentration fluctuation is confined within about 20% of the set points.
5.
Conclusion
In this study, we have been able to evolve and design our own version of a sensor-less system to control the concentration of methanol for the use of DMFCs based on the estimation of rates of methanol consumption. For this
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