On-line diagnosis method and equipment for flooding fault of fuel cell system stack

Abstract

The invention discloses a fuel cell system stack flooding fault on-line diagnosis method comprising the following steps: S1, obtaining stack state parameters, and determining that a stack has a fault according to a first set condition; s2, the cathode flow is increased, and it is judged that the stack cathode breaks down according to a second set condition; and S3, applying instantaneous pulse current excitation to the galvanic pile, recording the voltage change condition of each single cell of the galvanic pile, and judging that the anode of the galvanic pile has a fault according to a third set condition. According to the fuel cell system stack flooding fault on-line diagnosis method, the instantaneous current pulse is applied to the stack through the load, and the corresponding voltage signal is detected in real time, so that the low-frequency impedance characteristic of the cell is simulated, the flooding problem in the stack can be effectively diagnosed, additional equipment is not needed, the cost is low, and the fault diagnosis efficiency is high. The invention also discloses diagnosis equipment for implementing the on-line diagnosis method for the electric pile flooding fault of the fuel cell system.

Description

Technical Field

[0001] The present invention belongs to the technical field of fuel cells, and in particular, the present invention relates to an online diagnosis method and device for a fuel cell system stack flooding fault. Background Art

[0002] As the global energy crisis and environmental problems become increasingly severe, proton exchange membrane fuel cells have attracted widespread attention due to their high efficiency, low carbon, and wide fuel sources. Figure 5 As shown, hydrogen and oxygen in the air undergo electrochemical reactions inside the fuel cell membrane electrode to generate water, electricity, and excess waste heat, which are then discharged through the flow channel. Studies have shown that when a fuel cell is flooded or lacks gas during operation, it will cause the stack to fail, greatly reducing the performance and service life of the fuel cell.

[0003] like Figure 5 As shown in the figure, water in the battery exists in two forms: one is the water distributed inside the fuel cell and combined with the resin in the proton exchange membrane and the catalyst layer; the other is the excess liquid water distributed in the flow channel of the fuel cell. Studies have shown that since the proton conductivity of the membrane electrode is positively correlated with the water content in the membrane electrode, high-frequency impedance is often used to characterize the amount of internal bound water; and for the excess liquid water in the flow channel, it will occupy the gas transmission channel in the battery, resulting in a series of phenomena such as increased gas transmission resistance, increased flow resistance, and uneven internal current and potential distribution. Therefore, low-frequency impedance, pressure difference method, current distribution or multi-point potential distribution methods can be used for fault diagnosis.

[0004] However, the existing differential pressure method, current distribution method, multi-point potential method, and multi-point high and low frequency impedance method all require the addition of expensive sensors or complex analytical algorithms for diagnosis, resulting in a series of problems such as increased system cost and increased volume, and low fault diagnosis efficiency.

[0005] It is hoped to provide an online diagnosis method for water flooding faults in a fuel cell system stack, particularly with regard to how to reduce costs and improve fault diagnosis efficiency. Summary of the invention

[0006] The present invention aims to solve at least one of the technical problems existing in the prior art. To this end, the present invention provides an online diagnosis method for a fuel cell system stack flooding fault, the purpose of which is to improve the fault diagnosis efficiency.

[0007] In order to solve the above technical problems, the technical solution adopted by the present invention is: a fuel cell system stack flooding fault online diagnosis method, comprising the steps of:

[0008] S1, obtaining a battery stack state parameter, and determining that a battery stack fault occurs according to a first set condition;

[0009] S2, increasing the cathode flow rate, and determining that the cathode of the stack is faulty according to the second set condition;

[0010] S3. Apply instantaneous pulse current excitation to the battery stack, record the voltage change of each single battery in the battery stack, and determine whether the anode of the battery stack is faulty based on the third set condition.

[0011] In the step S3, the amplitude of the instantaneous pulse current applied is 10%-300% of the existing current.

[0012] In step S1, the first set condition is that the average voltage and voltage deviation of the stack do not reach a set threshold.

[0013] In step S1, the stack state parameters include the anode inlet temperature, cathode inlet temperature, anode inlet humidity, cathode inlet humidity, anode inlet pressure, cathode inlet pressure, anode outlet pressure and cathode outlet pressure of the stack.

[0014] In step S2, the second setting condition is that the average voltage and voltage deviation of the battery stack are improved, the average voltage of the battery stack is the average value of the voltages of all single cells in the battery stack, and the voltage deviation is the difference between the average voltage and the minimum single cell voltage.

[0015] In step S2, the voltage deviation is set to be less than 10-30 mV.

[0016] In step S3, the minimum cell voltage value of the battery stack needs to be checked at all times. The minimum cell voltage is set not to exceed the minimum voltage alarm threshold, which is 0.4-0.5V.

[0017] In step S3, the third set condition is that the average voltage and voltage deviation of the fuel cell stack exceed set thresholds.

[0018] The period of the instantaneous pulse current is set to 1-3s.

[0019] The present invention also provides a diagnostic device for implementing the online diagnosis method of water flooding fault of a fuel cell system stack, including a load and a single cell voltage inspection system, wherein the load is configured to apply instantaneous pulse current excitation to the stack, and the single cell voltage inspection system is configured to detect the voltage of each single cell in the stack.

[0020] The online diagnosis method for water flooding fault of a fuel cell system stack of the present invention applies an instantaneous current pulse to the stack through a load and detects the corresponding voltage signal in real time, thereby simulating the low-frequency impedance characteristics of the battery, and further can effectively diagnose the water flooding problem inside the stack. No additional equipment is required, the cost is low, and the fault diagnosis efficiency is high. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 It is a flow chart of the online diagnosis method of water flooding fault of fuel cell system stack of the present invention;

[0022] Figure 2 is a schematic diagram of the connection between the diagnostic equipment and the fuel cell system;

[0023] Figure 3 It is the specific operation content of the online diagnosis method in the embodiment of the present invention;

[0024] Figure 4 is a schematic diagram of the diagnosis results of the online diagnosis method in the embodiment of the present invention under different anode and cathode humidity;

[0025] Figure 5 This is a schematic diagram of the operation principle of a proton exchange membrane fuel cell;

[0026] The markings in the above figures are: 1. load; 2. single cell voltage inspection system; 3. diffusion layer; 4. proton exchange membrane; 5. catalyst layer. DETAILED DESCRIPTION

[0027] The specific implementation methods of the present invention are further explained in detail below by describing the embodiments with reference to the accompanying drawings, with the aim of helping those skilled in the art to have a more complete, accurate and in-depth understanding of the concept and technical solution of the present invention and facilitating its implementation.

[0028] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly connected by technicians in the technical field to which the present invention belongs. The terminology used in the specification of the present invention is for the purpose of describing specific embodiments and is not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more related listed items.

[0029] like Figure 1 As shown, the present invention provides an online diagnosis method for fuel cell system stack flooding fault, comprising the following steps:

[0030] S1, obtaining a battery stack state parameter, and determining that a battery stack fault occurs according to a first set condition;

[0031] S2, increasing the cathode flow rate, and determining that the cathode of the stack is faulty according to the second set condition;

[0032] S3. Apply instantaneous pulse current excitation to the battery stack, record the voltage change of each single battery in the battery stack, and determine whether the anode of the battery stack is faulty based on the third set condition.

[0033] Specifically, in order to solve the problems of low accuracy of the voltage drop method in the prior art for diagnosing the flooding state of a fuel cell and high additional cost based on the impedance method and the multi-point voltage inspection method, an embodiment of the present invention provides an online diagnosis method for fuel cell flooding faults using an instantaneous current pulse method. It only requires utilizing the existing electronic load of the system to apply an instantaneous current pulse to the fuel cell stack, and detecting the feedback voltage signal through the existing single-cell voltage inspection system, thereby realizing online rapid diagnosis of the battery flooding fault.

[0034] Generally, when a fuel cell is flooded or lacks gas, the mass transfer resistance of the membrane electrode will increase. Assuming that the cathode of the membrane electrode is flooded, it can be judged by increasing the cathode gas flow rate and observing whether the voltage fluctuates significantly. Furthermore, a load is applied to the stack with an instantaneous current pulse signal of a certain amplitude, and the corresponding voltage fluctuation is detected to simulate the low-frequency impedance measurement of the stack. When a certain chip in the stack deviates significantly, it can be judged that this chip is flooded.

[0035] like Figure 1 As shown, in the above step S1, the stack state parameters are obtained, and the stack performance and consistency are judged according to the internal state of the stack to see whether they have reached the set threshold. The first set condition is that the average voltage and voltage deviation of the stack have not reached the set threshold. The average voltage of the stack is the average voltage of all the single cells in the stack, and the voltage deviation is the difference between the average voltage and the minimum single cell voltage. If the first set condition is met, it is judged that the stack has a fault, and then subsequent fault online diagnosis operations are performed.

[0036] In the above step S1, the stack state parameters include the anode inlet temperature, cathode inlet temperature, anode inlet humidity, cathode inlet humidity, anode inlet pressure, cathode inlet pressure, anode outlet pressure and cathode outlet pressure of the stack, the cathode inlet enters air, and the anode inlet enters hydrogen. At the same time, it is necessary to obtain the voltage of each single cell in the stack, the maximum voltage value and the minimum voltage value of all the obtained single cell voltages, the single cell position corresponding to the maximum voltage value, the single cell position corresponding to the minimum voltage value, the average voltage value, the voltage deviation value and other information.

[0037] In the above step S1, the average voltage value and the voltage deviation value of the fuel cell stack are used to determine whether the fuel cell stack is faulty; when the average voltage value and the voltage deviation value of the fuel cell stack do not meet the requirements, it is considered that the fuel cell stack is faulty.

[0038] like Figure 1 As shown, in the above step S2, the cathode flow is appropriately increased to make the cathode flow reach the set value, and the cathode flow is stabilized for a period of time, and the internal state changes of the stack voltage are recorded; if the average voltage of the stack and the average reduction minimum are significantly improved, it is considered that the cathode is flooded or lacks gas.

[0039] In the above step S2, the second setting condition is that the average voltage and voltage deviation of the battery stack are improved, the average voltage of the battery stack is the average value of the voltages of all single cells in the battery stack, and the voltage deviation is the difference between the average voltage and the minimum single cell voltage.

[0040] In the above step S2, the increase in cathode flow should meet the demand of the stack for cathode gas when applying the current pulse in step S3, so as to avoid cathode gas shortage during the operation in step S3. At the same time, problems such as excessive flow causing the membrane to dry out should also be avoided.

[0041] In the above step S3, an electronic load is used to apply instantaneous pulse current excitation to the battery stack, and the current is stabilized for a period of time, and the voltage change of each single cell in the battery stack during this process is recorded.

[0042] In the above step S3, the amplitude of the instantaneous pulse current applied is 10%-300% of the current. It is necessary to make the hydrogen flow required by the pulse current greater than the existing cathode gas volume, so that the anode is instantly short of gas, thereby amplifying the anode flooding problem and causing the battery voltage to appear.

[0043] In the above step S3, since the anode may be short of gas, the period of the instantaneous pulse current is set to 1-3s to avoid long-term short of gas at the anode and irreversible damage to the membrane electrode. Therefore, when performing this operation, it is necessary to always check the minimum single cell voltage value of the battery stack, and the minimum single cell voltage value is set not to exceed the minimum voltage alarm threshold, which is 0.4-0.5V, to prevent battery damage or more serious failures.

[0044] In the above step S3, the third setting condition is that the average voltage and voltage deviation of the stack exceed the set threshold. If the average voltage and voltage deviation of the stack exceed the set threshold during the instantaneous pulse current excitation process, it is considered that there is a water flooding or gas shortage fault inside the stack.

[0045] In the above step S3, in order to reduce the risk of anode gas deficiency, the stack can be diagnosed by using a series of current pulses with different amplitudes when the characteristic target of the voltage is clear enough.

[0046] The present invention also provides a diagnostic device for implementing the above-mentioned fuel cell system stack water flooding fault online diagnosis method, the diagnostic device includes a load and a single cell voltage inspection system, the load is configured to apply instantaneous pulse current excitation to the stack, and the single cell voltage inspection system is configured to detect the voltage of each single cell in the stack.

[0047] The above-mentioned fuel cell system stack flooding fault online diagnosis method and diagnostic equipment have the following advantages:

[0048] The present invention applies instantaneous current pulses to the battery stack through a load and detects the corresponding voltage signal in real time, thereby simulating the low-frequency impedance characteristics of the battery, and then diagnosing whether the battery stack is flooded or lacks gas. Through the solution of the present invention, no additional additional equipment is required, such as multi-point fixed-frequency impedance, DC / DC converter, current distribution equipment, high-precision pressure sensor or multiple sets of voltage inspection, etc., and online diagnosis of flooding and lack of gas faults can be achieved at a low cost.

[0049] Furthermore, the present invention causes instantaneous local gas deficiency in the anode of the battery stack through an instantaneous current pulse, thereby amplifying the anode flooding or gas deficiency effect, thereby being able to effectively diagnose the flooding problem inside the battery stack with high diagnostic efficiency.

[0050] Example

[0051] like Figure 2 The diagnostic device for implementing the online diagnostic method of the present invention is shown, which mainly includes a load for applying an instantaneous current pulse to the fuel cell stack and a single cell voltage inspection system connected to the fuel cell stack. Usually, this device is a conventional device that comes with the test bench or system, and no additional purchase is required.

[0052] The load used is a high-precision load that can satisfy the function of applying instantaneous pulses to the battery stack. Its pulse period is 1-5s, the waveform is rectangular, and the amplitude is 10%-500% of the current.

[0053] The single-cell voltage inspection system used has a high sampling frequency voltage inspection, and the sampling frequency is usually at the ms level.

[0054] The selected fuel cell short stack is a unit formed by stacking multiple membrane electrodes and fuel cell stack bipolar plates in series. Specifically, this embodiment selects 20 self-humidifying fuel cell short stacks as the implementation object of the diagnosis method proposed in the present invention.

[0055] The fuel cell system stack flooding fault online diagnosis method of this embodiment includes the following steps:

[0056] S1. First, start the battery stack and run it at 0.1A / cm 2 The operation is stable under stable conditions. The excess coefficients of hydrogen and air in the fuel cell stack are 9 and 2.3 respectively. At this time, the average voltage and voltage deviation of the fuel cell stack are checked.

[0057] S2. Then, the hydrogen excess coefficient and air excess coefficient of the battery stack are increased to 9 and 8.5 respectively (corresponding to 0.1A / cm 2 ) and checked the internal parameters of the fuel cell stack, such as the average voltage and voltage deviation value. The fuel cell stack maintained stable operation, indicating that the fuel cell stack had problems such as cathode gas deficiency and water flooding.

[0058] S3, then, apply an instantaneous current pulse to the battery stack, with a pulse period of 3s and a pulse amplitude of 0.1A / cm 2 -0.5A / cm 2 ; Record the internal status of the battery stack.

[0059] In order to more accurately simulate the internal state of the battery stack and the implementation effect of the diagnostic method of the present invention, the diagnosis results of the battery stack under different water content states are simulated by changing the humidity of the cathode and anode of the battery stack;

[0060] Among them, test condition 1 is that the anode humidity is 40%, the cathode humidity is 0%, and the stack is in dry operation state;

[0061] Then, test condition 2 is 100% anode humidity and 0% cathode humidity, which is a moderate operating state of the stack;

[0062] Secondly, test condition 3 is that the anode humidity is 140% and the cathode humidity is 0%, which is the anode flooding operation state of the stack;

[0063] Finally, test condition 4 is 100% anode humidity and 100% cathode humidity, which is a comfortable operating state for the battery stack.

[0064] Test results such as Figure 3 As shown in Table 1, it can be seen that the diagnostic method can effectively identify conditions 1 and 4, and their mean value minus the minimum value has changed significantly.

[0065] Table 1 Diagnostic results of the online diagnosis method in the embodiment of the present invention under different anode and cathode humidity

[0066]

[0067] The present invention is described above by way of example in conjunction with the accompanying drawings. It is obvious that the specific implementation of the present invention is not limited to the above-mentioned method. As long as various non-substantial improvements are made using the method concept and technical solution of the present invention, or the concept and technical solution of the present invention are directly applied to other occasions without improvement, they are all within the protection scope of the present invention.

Claims

1. A fuel cell system stack flooding fault online diagnosis method, characterized in that: Includes steps: S1, obtaining a battery stack state parameter, and determining that a battery stack fault occurs according to a first set condition; S2, increasing the cathode flow rate, and determining that the cathode of the stack is faulty according to the second set condition; S3. Apply instantaneous pulse current excitation to the battery stack, record the voltage change of each single battery in the battery stack, and determine whether the anode of the battery stack is faulty based on the third set condition.

2. The method for online diagnosis of water flooding fault in a fuel cell system stack according to claim 1, characterized in that: In the step S3, the amplitude of the instantaneous pulse current applied is 10%-300% of the existing current.

3. The method for online diagnosis of water flooding fault in a fuel cell system stack according to claim 1, characterized in that: In step S1, the first set condition is that the average voltage and voltage deviation of the fuel cell stack do not reach a set threshold.

4. The method for online diagnosis of water flooding fault in a fuel cell system stack according to any one of claims 1 to 3, characterized in that: In step S1, the stack state parameters include the anode inlet temperature, cathode inlet temperature, anode inlet humidity, cathode inlet humidity, anode inlet pressure, cathode inlet pressure, anode outlet pressure and cathode outlet pressure of the stack.

5. The method for online diagnosis of water flooding fault in a fuel cell system stack according to any one of claims 1 to 4, characterized in that: In step S2, the second setting condition is that the average voltage and voltage deviation of the battery stack are improved, the average voltage of the battery stack is the average value of the voltages of all single cells in the battery stack, and the voltage deviation is the difference between the average voltage and the minimum single cell voltage.

6. The method for online diagnosis of water flooding fault in a fuel cell system stack according to claim 5, characterized in that: In the step S2, the voltage deviation is set to be less than 10-30 mV.

7. The method for online diagnosis of water flooding fault in a fuel cell system stack according to any one of claims 1 to 6, characterized in that: In step S3, it is necessary to check the minimum single cell voltage value of the battery stack at all times. The minimum single cell voltage is set not to exceed the minimum voltage alarm threshold, and the minimum voltage alarm threshold is 0.4-0.5V.

8. The method for online diagnosis of water flooding fault in a fuel cell system stack according to any one of claims 1 to 7, characterized in that: In step S3, the third set condition is that the average voltage and voltage deviation of the fuel cell stack exceed set thresholds.

9. The method for online diagnosis of water flooding fault in a fuel cell system stack according to any one of claims 1 to 8, characterized in that: The period of the instantaneous pulse current is set to 1-3s.

10. A diagnostic device for implementing the online diagnostic method for fuel cell system stack flooding fault according to any one of claims 1 to 9, characterized in that: It includes a load and a single cell voltage inspection system. The load is configured to apply instantaneous pulse current excitation to the battery stack, and the single cell voltage inspection system is configured to detect the voltage of each single cell in the battery stack.

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