CN114695925A - Abnormality detection method and apparatus for vehicle-mounted fuel cell, and vehicle - Google Patents
Abnormality detection method and apparatus for vehicle-mounted fuel cell, and vehicle Download PDFInfo
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- 238000001514 detection method Methods 0.000 title claims abstract description 95
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- 230000005856 abnormality Effects 0.000 title claims abstract description 31
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- 238000004364 calculation method Methods 0.000 description 9
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- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 description 6
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- 238000012360 testing method Methods 0.000 description 5
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- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
- H01M8/00—Fuel cells; Manufacture thereof
- H01M8/04—Auxiliary arrangements, e.g. for control of pressure or for circulation of fluids
- H01M8/04298—Processes for controlling fuel cells or fuel cell systems
- H01M8/04313—Processes for controlling fuel cells or fuel cell systems characterised by the detection or assessment of variables; characterised by the detection or assessment of failure or abnormal function
- H01M8/04664—Failure or abnormal function
- H01M8/04679—Failure or abnormal function of fuel cell stacks
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- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
- H01M8/00—Fuel cells; Manufacture thereof
- H01M8/04—Auxiliary arrangements, e.g. for control of pressure or for circulation of fluids
- H01M8/04298—Processes for controlling fuel cells or fuel cell systems
- H01M8/04992—Processes for controlling fuel cells or fuel cell systems characterised by the implementation of mathematical or computational algorithms, e.g. feedback control loops, fuzzy logic, neural networks or artificial intelligence
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- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
- H01M2250/00—Fuel cells for particular applications; Specific features of fuel cell system
- H01M2250/20—Fuel cells in motive systems, e.g. vehicle, ship, plane
Abstract
The application discloses an abnormality detection method and device for a vehicle-mounted fuel cell and a vehicle, wherein the method comprises the following steps: detecting actual magnetic induction of at least one detection point around each cell group of the vehicle-mounted fuel cell; judging whether the actual magnetic induction intensity is in a preset magnetic induction intensity interval or not; and when the actual magnetic induction intensity of any detection point is not in the preset magnetic induction intensity interval, judging that the battery pack corresponding to any detection point is flooded or abnormal membrane is existed. Therefore, the problems that whether the single battery is flooded or abnormal membrane dryness or the like cannot be detected at present are solved.
Description
Technical Field
The present disclosure relates to the field of vehicle technologies, and in particular, to a method and an apparatus for detecting an abnormality of a vehicle-mounted fuel cell, and a vehicle.
Background
The optimal working condition of the fuel cell stack is constant-current steady-state output, and the working mode can realize the longest and optimal working life of the fuel cell stack. Therefore, the fuel cell has outstanding advantages as a green clean energy source in the aspects of fixed emergency power stations, ships and the like.
However, the working conditions of the vehicle are complex and changeable, and in order to ensure that the power generation performance of the hydrogen fuel cell stack can meet the requirements of changeable working conditions, the situation of sudden loading/sudden unloading of the stack inevitably exists. The great damage of the sudden load increase/sudden load decrease to the fuel cell is the main reason causing the great reduction of the service life of the fuel cell and also the main reason hindering the large-scale popularization and application of the current fuel cell vehicles
In the related art, the voltage polling meter CVM is the only means for detecting the power generation condition of each single cell of the stack at present, however, the voltage detected by the CVM can only reflect whether a single cell is in a normal state, and does not have the capability of detecting the local power generation condition of the single cell, so that whether the single cell is flooded or abnormal membrane dryness cannot be detected, and a solution is needed.
Content of application
The application provides an abnormality detection method and device for a vehicle-mounted fuel cell and a vehicle, and aims to solve the problem that whether a single cell is flooded or abnormal membrane is not detected at present.
An embodiment of a first aspect of the present application provides an abnormality detection method for a vehicle-mounted fuel cell, including the steps of: detecting actual magnetic induction of at least one detection point around each cell group of the vehicle-mounted fuel cell; judging whether the actual magnetic induction intensity is in a preset magnetic induction intensity interval or not; and when the actual magnetic induction intensity of any detection point is not in the preset magnetic induction intensity interval, judging that the battery pack corresponding to any detection point is flooded or abnormal membrane.
Further, before determining whether the actual magnetic induction intensity is in the preset magnetic induction intensity interval, the method further includes: acquiring reference magnetic induction intensity at each detection point; and acquiring the magnetic induction interval according to the reference magnetic induction.
Further, the acquiring the reference magnetic induction at each detection point comprises: acquiring the number of single batteries in the current battery pack; and determining the reference magnetic induction intensity according to the number of the single batteries.
Further, when the number is single;
the reference magnetic induction is as follows:
wherein k is
N is the number of all the single batteries, delta (n-12i) represents the magnetic induction intensity of the (n-12i) th battery pack, and n is a positive integer;
the magnetic induction intensity interval is as follows: [0.97Bn，1.03Bn]。
Further, when the number is two;
if the number of all the single batteries is an even number, the reference magnetic induction intensity is as follows:
wherein k is
An integer part, wherein delta (n-6i) represents the magnetic induction intensity of the (n-6i) th battery pack, n is a positive integer, and 2n represents the number of all single batteries;
if the number of all the single batteries is odd, the reference magnetic induction intensity is as follows:
wherein k is
The integral part, 2n +1 represents the number of all the single batteries, and the magnetic induction intensity of the 2n +1 th single battery is as follows:
further, when the number is two, the magnetic induction intervals are:
[0.97(B2n-1+B2n)，1.03(B2n-1+B2n)]；
the magnetic induction intensity interval of the 2n +1 th single battery is as follows:
[0.97B2n+1，1.03B2n+1]。
further, when the number is three:
if the vehicle-mounted fuel cell includes 3n single cells, the reference magnetic induction is:
wherein k is
An integral part, wherein delta (n-4i) is the magnetic induction intensity of the (n-4i) th battery pack;
if the vehicle-mounted fuel cell comprises 3n +1 single cells, the reference magnetic induction is as follows:
wherein, the magnetic induction intensity of the 3n +1 th single battery is:
if the vehicle-mounted fuel cell includes 3n +2 single cells, the reference magnetic induction is:
wherein, the magnetic induction intensity of the 3n +1 and 3n +2 single batteries is:
further, when the number is three, the magnetic induction intervals are:
[0.97(B3n-2+B3n-1+B3n)，1.03(B3n-2+B3n-1+B3n)]；
the magnetic induction intensity interval of the 3n +1 th single battery is as follows:
[0.97B3n+1，1.03B3n+1]；
the magnetic induction intensity interval of the 3n +2 th single battery is as follows:
[0.97(B3n-2+B3n-1)，1.03(B3n-2+B3n-1)]。
an embodiment of a second aspect of the present application provides an abnormality detection device for a vehicle-mounted fuel cell, including: the detection module is used for detecting the actual magnetic induction intensity of at least one detection point around each battery pack of the vehicle-mounted fuel cell; the judging module is used for judging whether the actual magnetic induction intensity is in a preset magnetic induction intensity interval or not; and the judging module is used for judging that the battery pack corresponding to any one of the detection points is flooded or abnormal membrane dryness when the actual magnetic induction intensity of the any one of the detection points is not in the preset magnetic induction intensity interval.
An embodiment of a third aspect of the present application provides a vehicle including the abnormality detection apparatus of the vehicle-mounted fuel cell described in the above-described embodiment.
Whether the battery pack is flooded or abnormal membrane is judged through magnetic induction intensity around the battery pack of the vehicle-mounted fuel cell, and when the actual magnetic induction intensity is not in a preset magnetic induction intensity interval, the battery pack is judged to be flooded or abnormal membrane, so that the local power generation condition of the battery pack is detected on line in real time by using an objective rule that different current intensities generate different magnetic field intensities, and the load adding/load reducing amplitude of the fuel cell can be controlled according to the local power generation condition. Therefore, the problems that whether the single battery is flooded or abnormal membrane dryness or the like cannot be detected at present are solved.
Additional aspects and advantages of the present application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the present application.
Drawings
The foregoing and/or additional aspects and advantages of the present application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is a schematic diagram of a toroidal magnetic field generated by a membrane electrode in an ideal state;
FIG. 2 is a schematic diagram of the annular magnetic field generated by the membrane electrode when the anode is locally flooded with water;
FIG. 3 is a schematic diagram of the annular magnetic field generated by the membrane electrode when the anode membrane is dry/cathode flooded with water;
fig. 4 is a schematic structural view of a unit cell in the fuel cell;
FIG. 5 is a schematic representation of the Biot-Saval law;
FIG. 6 is a schematic coordinate diagram of a rectangular power generation unit;
fig. 7 is a flowchart of an abnormality detection method for a vehicle-mounted fuel cell according to an embodiment of the present application;
FIG. 8 is a schematic view of a magnetic strain gage arrangement according to an embodiment of the application;
FIG. 9 is a schematic diagram of a magnetic strain gage arrangement for a first detection accuracy in accordance with an embodiment of the present application;
FIG. 10 is an idealized plan view of a rectangular power generation unit according to an embodiment of the present application;
fig. 11 is a schematic diagram illustrating the influence of the induced magnetic field of n single cells on the magnetic induction intensity of the magnetic strain gauge according to the embodiment of the present application;
FIG. 12 is a schematic diagram of a detection point that can cover stacked cells according to an embodiment of the present disclosure;
FIG. 13 is an exemplary diagram of a bench test according to an embodiment of the present application;
FIG. 14 shows q according to an embodiment of the present application1The calibration diagram of the gantry of (1);
FIG. 15 shows q according to an embodiment of the present application2The calibration diagram of the gantry of (1);
FIG. 16 shows q according to an embodiment of the present application3The calibration diagram of the gantry of (a);
FIG. 17 is a graph of q according to an embodiment of the present application4The calibration diagram of the gantry of (1);
FIG. 18 is a graph of q according to an embodiment of the present application5The calibration diagram of the gantry of (a);
fig. 19 is a schematic diagram of calculation of induced magnetic field strength of the first to twelfth battery packs according to the embodiment of the present application;
fig. 20 is a schematic view of an arrangement of even-numbered magnetic strain gauges in a cell according to an embodiment of the present application;
fig. 21 is a schematic view of an arrangement of magnetic strain gages in which the number of unit cells is odd at the second detection accuracy according to the embodiment of the present application;
FIG. 22 shows i according to an embodiment of the present application1The calibration diagram of the gantry of (1);
FIG. 23 shows i according to an embodiment of the present application2The calibration diagram of the gantry of (1);
fig. 24 is a schematic view illustrating an arrangement manner of magnetic strain gauges in which the number of unit batteries is 3n according to an embodiment of the present application;
FIG. 25 is a schematic diagram illustrating an arrangement of 3n +1 magnetic strain gages in the number of single batteries according to an embodiment of the present application;
FIG. 26 is a schematic diagram illustrating an arrangement of 3n +2 magnetic strain gages according to an embodiment of the present application;
FIG. 27 shows j according to an embodiment of the present application1Table calibration schematic ofA drawing;
fig. 28 is an example diagram of an abnormality detection device of a vehicle-mounted fuel cell according to an embodiment of the present application.
Detailed Description
Reference will now be made in detail to embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are exemplary and intended to be used for explaining the present application and should not be construed as limiting the present application.
The present application is based on the recognition and discovery by the inventors of the following problems:
when the electric pile is loaded suddenly, the electric pile generates electricity by small current and large current, a large amount of hydronium ions at the anode penetrate through the proton membrane and are transmitted to the cathode, so that the partial proton membrane at the anode side is lack of water to generate membrane dryness, and the partial catalytic layer and the GDL layer at the cathode are gathered by water to be flooded. Cathode side flooding and anode membrane dry respectively lead to cathode oxygen deficiency and anode proton transmission impedance increase, and finally show that the pile heats seriously, and the power generation performance is reduced, and the cathode generates hydrogen along with the cathode, thereby further worsening the cathode oxygen deficiency degree caused by flooding. Meanwhile, the cathode oxygen reduction reaction is incomplete due to the excessively low potential, and radicals such as-OH or-OOH are generated to attack and degrade sulfonic acid groups, end groups and a main chain of the proton membrane, so that the proton transfer capacity and the hydrophilicity of the proton membrane are permanently and irreversibly reduced.
When the electric pile suddenly drops, the electric pile generates electricity by the large current and the small current, and the quantity of anode hydronium ions transmitted to the cathode through the proton membrane is also reduced sharply, so that the anode water flooding is generated by water gathering of the anode local catalytic layer and the GDL layer. Anode hydrogen starvation can be caused by anode flooding, carbon on a cathode GDL layer is corroded, cathode carbon corrosion can cause Pt catalytic particles of a cathode to fall off, an inherent GDL diffusion structure of the cathode collapses, so that oxygen starvation can be caused on the cathode more easily, and vicious cycle is realized.
Therefore, the load-up/load-down amplitude of the fuel cell vehicle needs to be controlled, and the phenomena of local flooding and membrane dryness caused by overlarge current change amplitude are prevented, so that the service life of the fuel cell is further influenced. How to detect the power generation condition of each single battery on line in real time has very important guiding significance for controlling the loading/unloading amplitude of the fuel cell stack.
In the prior art, a voltage polling meter (CVM) is the only means for detecting the power generation condition of each single battery of the pile. However, the voltage detected by the CVM can only indicate whether the power generation of the entire single cell is normal, and does not have the capability of detecting the local power generation of the single cell. When the anode partial flooding, the anode partial membrane dry and the cathode partial flooding of the single-chip battery occur, even if the partial potential value is abnormal, the CVM is still not easy to detect for the voltage of the whole battery because the membrane electrode (hereinafter referred to as MEA) is used as a power generation unit and has a large area. While the local power generation abnormality is the most main cause of the service life attenuation of the fuel cell, the CVM has no capability of detecting the local power generation condition.
The biot-savart law in magnetostatics is applied to the calculation of the magnetic field generated by a steady current. The amount of current does not change with time and the charge does not accumulate or disappear at any position. The biot-savart law fails when the current changes too quickly over time, or when the wire moves quickly. The above is an application scenario of the biot-savart law, and it is obvious that the power generation mechanism of the galvanic pile conforms to the biot-savart law. As shown in fig. 1, ideally, a membrane electrode with a uniform gas distribution would generate a uniform toroidal magnetic field around it, where a11To AijFinite element analysis of the membrane electrode is shown, with an area of the MEA broken down into i rows and j columns of current elements.
Anode partial water flooding: the anode flooding causes partial hydrogen starvation, and water in a starved area is electrolyzed to separate out oxygen to generate an anode oxygen-enriched area. If the MEA continues to generate power, due to the excellent conductivity of the catalytic layer and the GDL layer, the oxygen-rich region absorbs electrons and protons in the surrounding region to perform an oxygen reduction reaction, so that a closed current is locally generated, and then according to the gauss law, the region where the closed current is generated does not generate an induced magnetic field, so that the induced magnetic field in a ring shape around the MEA is distorted, as shown in fig. 2.
Anode film dry/cathode flooding: the distortion of the toroidal magnetic field is much weaker than anode flooding, since anode membrane dry/cathode flooding only reduces the power generation capability of the local MEA, i.e. the induced magnetic field strength is weaker. But ultimately appears to distort the MEA toroidal induced magnetic field as shown in figure 3.
The electric pile is formed by stacking hundreds of single cells in series, and the power generation unit of each single cell is MEA, so the electric pile can be regarded as a large cell consisting of hundreds of cells. As shown in fig. 4, the unit cell is shown in the following figure, wherein the black part is MEA, and the upper and lower bipolar plates are understood as positive and negative electrodes of the cell. Wherein, as shown in the Biot-Saval law 5, the induced magnetic field strength of any point dz on the wire CD at the point P is
Therefore, the scalar quantity of the induced magnetic field strength of the whole wire at the point P of the wire CD is calculated as follows:
therefore, the perpendicular line from the point P to the lead wire and the intersection point O of the lead wire, the point O current element induces the magnetic field intensity at the point P to be
The rectangular power generation cell MEA is shown in fig. 6 at any point P (coordinates (0, b)) at a vertical distance c-a from the long side.
The induced magnetic field strength vector is:
the scalar of the induced magnetic field strength of the point P is:
wherein D is the rectangular area (length D, width a) enclosed by the MEA.
The abnormality detection method of the vehicle-mounted fuel cell, the apparatus, and the vehicle of the embodiment of the present application will be described below with reference to the drawings. In order to solve the problem that whether a single battery is flooded or abnormal membrane stem cannot be detected at present, which is mentioned by the background technology center, the application provides an abnormality detection method for a vehicle-mounted fuel cell. Therefore, the problems that whether the single battery is flooded or abnormal membrane dryness or the like cannot be detected at present are solved.
Specifically, fig. 7 is a schematic flowchart of an abnormality detection method for a vehicle-mounted fuel cell according to an embodiment of the present application.
As shown in fig. 7, the abnormality detecting method of the vehicle-mounted fuel cell includes the steps of:
in step S101, the actual magnetic induction of at least one detection point around each cell group of the vehicle-mounted fuel cell is detected.
In this embodiment, the present application may detect the actual magnetic induction intensity through magnetic strain gauges arranged around the battery pack, where one magnetic strain gauge is one detection point. The battery pack may include one battery, two batteries, or three batteries, and may be determined according to the accuracy of specific detection.
Taking the battery pack including one battery as an example, as shown in fig. 8, the magnetic strain gauge is disposed on the outer casing of the stack, the black dots represent the magnetic strain gauge, and the upper 5 are connected to form a line, which is the position of the stack case (for simplicity of the drawing, the stack case is not shown in the figure).
One rectangle in fig. 9 represents one fuel cell, f1Represents the firstInduced magnetic field strength of 1 detection point, fnRepresenting the induced magnetic field strength at the nth detection point, n1Represents the 1 st fuel cell, nnRepresenting the nth fuel cell, and e is the thickness of a single cell. Fig. 9 shows an arrangement of the magnetic strain gauges with the first detection accuracy, that is, an arrangement of the magnetic strain gauges with one measurement, and other detection accuracies will be described in the following embodiments, which will not be described here.
In step S102, it is determined whether the actual magnetic induction is within a preset magnetic induction interval.
It can be understood that, in the embodiment of the present application, whether the battery pack is abnormal or not can be determined according to the magnetic induction intensity of the detection point, and therefore, after the actual magnetic induction intensity is obtained through detection, it is further determined whether the battery pack is in the preset magnetic induction intensity interval or not, so as to be used as a basis for determining whether the battery pack is abnormal or not. The preset magnetic induction intensity interval is the range of normal magnetic induction intensity of the detection point.
In this application embodiment, before judging whether actual magnetic induction is in preset magnetic induction interval, still include: acquiring reference magnetic induction intensity at each detection point; and acquiring a magnetic induction intensity interval according to the reference magnetic induction intensity.
The range of normal magnetic induction can be determined according to the reference magnetic induction at the detection point. In this embodiment, the obtaining of the reference magnetic induction at each detection point includes: acquiring the number of single batteries in the current battery pack; and determining the reference magnetic induction intensity according to the number of the single batteries.
Because the group battery includes the difference of battery cell number, therefore the corresponding reference magnetic induction intensity calculation mode of detection point is different, specifically as follows:
(1) when the number is single;
the reference magnetic induction is:
wherein k is
N is the number of all single batteries, delta (n-12i) represents the magnetic induction intensity of the (n-12i) th battery pack, and n is a positive integer;
the magnetic induction interval is as follows: [0.97Bn，1.03Bn]。
(2) When the number is two;
if the number of all the single batteries is even, the reference magnetic induction intensity is as follows:
wherein k is
An integer part, wherein delta (n-6i) represents the magnetic induction intensity of the (n-6i) th battery pack, n is a positive integer, and 2n represents the number of all single batteries;
if the number of all the single batteries is odd, the reference magnetic induction intensity is as follows:
wherein k is
The integral part, 2n +1 represents the number of all the single batteries, and the magnetic induction intensity of the 2n +1 th single battery is as follows:
when the number is two, the magnetic induction interval is:
[0.97(B2n-1+B2n)，1.03(B2n-1+B2n)]；
the magnetic induction intensity interval of the 2n +1 th single battery is as follows:
[0.97B2n+1，1.03B2n+1]。
(3) when the number is three:
if the vehicle-mounted fuel cell includes 3n single cells, the reference magnetic induction is:
wherein k is
An integral part, wherein delta (n-4i) is the magnetic induction intensity of the (n-4i) th battery pack;
if the vehicle-mounted fuel cell includes 3n +1 unit cells, the reference magnetic induction is:
wherein, the magnetic induction intensity of the 3n +1 th single battery is:
if the vehicle-mounted fuel cell includes 3n +2 single cells, the reference magnetic induction is:
wherein, the magnetic induction intensity of the 3n +1 and 3n +2 single batteries is:
when the number is three, the magnetic induction interval is:
[0.97(B3n-2+B3n-1+B3n)，1.03(B3n-2+B3n-1+B3n)]；
the magnetic induction intensity interval of the 3n +1 th single battery is as follows:
[0.97B3n+1，1.03B3n+1]；
the magnetic induction intensity interval of the 3n +2 th single battery is as follows:
[0.97(B3n-2+B3n-1)，1.03(B3n-2+B3n-1)]。
in step S103, when the actual magnetic induction at any detection point is not within the preset magnetic induction range, it is determined that the battery pack corresponding to any detection point is flooded or abnormal.
It can be understood that when the actual magnetic induction intensity of the detection point is within the preset magnetic induction intensity interval, the fuel cell is normal; when the actual magnetic induction intensity of any one detection point is not in the preset magnetic induction intensity interval, determining that the battery pack corresponding to the detection point is flooded or abnormal membrane stem exists; therefore, the problem that the local water flooding/membrane dryness of the fuel cell cannot be detected on line in real time is effectively solved.
It should be noted that the detection accuracy of the embodiment of the present application includes first to third detection accuracies, which will be described in detail below.
1. When the detection accuracy is the first detection accuracy, the abnormality detection method for the vehicle-mounted fuel cell includes:
1.1, first consider that in an ideal plane, a single cell is assumed to be a rectangle with no thickness, length d, and width a, as shown in fig. 10, since the distance between the long side of the MEA and the housing is typically around 3mm, i.e., c-a is 3mm, and the single cell a of the stack is typically between 150mm and 200mm, c is approximately equal to a, and the scalar of the induced magnetic field strength of the rectangular MEA at the stack housing is a function related to b only.
Wherein b is a variable. Thus in the plane, the induced magnetic field strength of the MEA at the detection point is related only to b. In fact, the single cells are thick and are not negligible, so that in the stacking direction of the stack, assuming that the induced magnetic field of n single cells has an influence on the magnetic strain gauge, as shown in fig. 11, the first single cell corresponds to the induced magnetic field strength of the black dot, and it can be known from the above formula:
B(cosθ1-cosθ2)，
wherein B is verified as a function related to B by the above calculation, the induced magnetic field strength of the first cell to the black dot in the present invention is:
in the stacking direction, the only factor influencing the strength of the induced magnetic field at the detection point is cos theta1，cosθ2. The induced magnetic field strength of the nth cell to the black dot is calculated as follows:
Therefore, it can be considered that the induced magnetic field strength (black dots) detected by one detection point can cover 12 single cells in the positive and negative directions of the stacking direction, as shown in fig. 12, f2-f1The result obtained is n13At f2Magnetic strength and n1At f1Difference in magnetic strength.
1.2, calculating the magnetic field intensity of the 13 th to the nth single batteries, comprising the following steps: as shown in fig. 13, the peripheral induced magnetic field strength at a distance from the battery 5e is Bn, and n represents the battery number. In the arrangement of FIG. 9 of the embodiments of the present application, f13～fnAre all detection points which all accord with fn-fn-1＝Bn-Bn-12And (5) regularity. Let Δ n be fn-fn-1The results are shown in table 1:
TABLE 1
If f is guaranteed1～f12Can separately detect B1～B12Then, the permutation and combination n shown in Table 2 are obtained1～nnThe method for calculating the induced magnetic field strength B of each piece of the fuel cell comprises the following steps:
TABLE 2
The magnetic field intensity calculation method comprises the following steps:
B13＝Δ1+Δ13；B14＝Δ2+Δ14，…，B25＝Δ1+Δ13+Δ25，…
therefore it has the advantages of
Wherein k is taken
And n is not less than 13.
1.3 magnetic field intensity B of first to twelfth cell groups1～B12The calculation method is as follows:
from the above formula, B1～B12Directly influences the rear pair B13～BnIs calculated, thus n1To n12The magnetic strength calculation of the battery is very key. In the embodiment of the application, 5 correction coefficients q need to be introduced1、q2、q3、q4And q is5For accurately calculating B1～B12. The 5 correction factors are determined based on the following 5 bench test calibrations, respectively。
q1The calibration of the stand is shown in FIG. 14, which respectively obtains f in the above figure1、f1-f2Obtaining a unitary linear function relation with the current density to obtain two function slopes with k respectively1、j1Therefore, it is
q2Is shown in FIG. 15, with q1The calibration methods of the racks are consistent to obtain
q3As shown in figure 16,
q4as shown in figure 17,
q5as shown in figure 18,
thus, as shown in FIG. 19, n1To n12The induced magnetic field strength is calculated as follows:
Δ1＝B1＝f1；
Δ2＝B2＝f2-q1f1；
Δ3＝B3＝f3-q2f2；
Δ4＝B4＝f4-q3f3；
Δ5＝B5＝f5-q4f4；
Δ6＝B6＝f6-q5f5；
Δ7＝B7＝f7-q5f6；
Δ8＝B8＝f8-q4f7；
Δ9＝B9＝f9-q3f8；
10、Δ10＝B10＝f10-q2f9；
11、Δ11＝B11＝f11-q1f10；
12、Δ12＝B12＝f12-f11；
1.4, the fuel cell local power generation condition determination includes:
due to the fact that the correction coefficient q is being performed1At calibration, a bench test as shown in FIG. 13 has been obtained, with the induced magnetic field around as a function of current density at a distance of cell 5e, set to G1B (i), where G subscript 1 represents detection accuracy.
2. When the detection accuracy is the second detection accuracy, the abnormality detection method for the vehicle-mounted fuel cell includes:
2.1, the arrangement of the magnetic strain gages with the second detection accuracy is shown in fig. 20 and 21, wherein fig. 20 is an even number 2n of the single cells, and fig. 21 is an odd number 2n +1 of the single cells.
2.2, calibrating correction coefficient and calculating magnetic strength
2 correction coefficients i are calibrated when the second detection precision is achieved1、i2。
i1The calibration of the stand is shown in FIG. 22, which respectively obtains f in the above figure1、f1-f2A linear function of the current density, the slope ratio being i1。i2Gantry calibration is shown in FIG. 23, i2Calculation method and i1And (5) the consistency is achieved.
n1～n12The magnetic strength of the battery is as follows,
Δ1＝B1+B2＝f1；
Δ2＝B3+B4＝f2-i1f1；
Δ3＝B5+B6＝f3-i2f2；
Δ4＝B7+B8＝f4-i2f3；
Δ5＝B9+B10＝f5-i1f4；
Δ6＝B11+B12＝f6-f5。
n13～n2nbattery No.:
B13+B14＝Δn1+Δn7，B15+B16＝Δn2+Δn8，…,B25+B26＝Δn1+Δn7+Δn13，…
therefore, the number sequence when the total number of the unit cells is 2n is shown in table 3:
TABLE 3
Thus, from table 3 it is possible to obtain:
wherein k is
The integer part of (2).
The number sequence for a total number of cells of 2n +1 is shown in table 4:
TABLE 4
The nth can be obtained from Table 42n+1Each battery:
2.3, because the correction coefficient i is being performed1At calibration, a bench test as shown in FIG. 22 has been obtained, and the induced magnetic field around as a function of current density at a distance from the cell 4e is set to G2B (i), where G subscript 2 represents detection accuracy.
In addition, when the number of slices is odd 2n +1, the last slice should coincide
And judging that the power generation is normal.
3. When the detection accuracy is the third detection accuracy, the abnormality detection method for the vehicle-mounted fuel cell includes:
3.1, the arrangement of the magnetic strain gages with the number of the single batteries being 3n is shown in FIG. 24, the arrangement of the magnetic strain gages with the number of the single batteries being 3n +1 is shown in FIG. 25, and the arrangement of the magnetic strain gages with the number of the single batteries being 3n +2 is shown in FIG. 26.
3.2, calibration of correction coefficient and calculation of magnetic field intensity
In the third detection precision, only one correction coefficient j needs to be calibrated1. Wherein j is1As shown in fig. 27, respectively obtain f in the above figure1、f1-f2A linear function of the current density, the slope ratio is j1。
n1～n12Battery No.:
Δ1＝B1+B2+B3＝f1；
Δ2＝B4+B5+B6＝f2-j1f1；
Δ3＝B7+B8+B9＝f3-j1f2；
Δ4＝B10+B11+B12＝f4-f5；
n13～n3nnumber battery
B13+B14+B15＝Δn1+Δn5，B16+B17+B18＝Δn2+Δn5，…,B25+B26+B27＝Δn1+Δn5+Δn9,…
Therefore, in the third detection accuracy, the number sequence when the total number of the unit batteries is 3n is shown in table 5:
TABLE 5
Therefore it has the advantages of
k is taken
An integer portion.
The number list for the total number of cells of 3n +1 is shown in table 6:
TABLE 6
If there are 3n +1, the nth3n+1Battery No.:
the number sequence when the total number of the unit cells is 3n +2 is shown in table 7:
TABLE 7
If there are 3n +2, the nth3n+1Number and n3n+2Battery No.:
3.3 because the correction coefficient j is being performed1At calibration, a bench test as shown in FIG. 26 has been obtained, and the induced magnetic field around as a function of current density at a distance of cell 3e is set to G3B (i), where G subscript 3 represents detection accuracy.
In addition, when the total number of the single batteries is 3n +1, the last battery should be matched
And judging that the power generation is normal.
When the total number of the single batteries is 3n +2, the last two batteries are in accordance with
And judging that the power generation is normal.
In summary, since the cell has a large area, the local power generation condition of the cell cannot be detected through the voltage, and the reference significance of the CVM detection result is small in the face of the working condition that the fuel cell vehicle needs to load up/down suddenly. The embodiment of the application can detect the local power generation condition of the single cell in real time on line by utilizing the objective rule that different current intensities generate different magnetic field intensities, thereby effectively solving the problem of difficulty in the real-time on-line detection of the local water flooding/membrane dryness of the fuel cell.
According to the abnormality detection method for the vehicle-mounted fuel cell, whether the battery pack is flooded or abnormal membrane stems is judged according to the magnetic induction intensity around the battery pack of the vehicle-mounted fuel cell, and when the actual magnetic induction intensity is not in the preset magnetic induction intensity interval, the battery pack is judged to be flooded or abnormal membrane stems, so that the local power generation condition of the battery pack is detected on line in real time by using the objective rule that different current intensities generate different magnetic field intensities, and the load-up/load-down amplitude of the fuel cell can be controlled according to the local power generation condition.
Next, an abnormality detection device for a vehicle-mounted fuel cell proposed according to an embodiment of the present application is described with reference to the drawings.
Fig. 28 is a block schematic diagram of an abnormality detection device of a vehicle-mounted fuel cell of the embodiment of the present application.
As shown in fig. 28, the abnormality detection device 10 for a vehicle-mounted fuel cell includes: a detection module 100, a judgment module 200 and a judgment module 300.
The detection module 100 is used for detecting the actual magnetic induction intensity of at least one detection point around each battery pack of the vehicle-mounted fuel cell; the judging module 200 is configured to judge whether the actual magnetic induction intensity is within a preset magnetic induction intensity interval; the determination module 300 is configured to determine that the battery pack corresponding to any one of the detection points is flooded or abnormal membrane dryness when the actual magnetic induction intensity of any one of the detection points is not within the preset magnetic induction intensity interval.
It should be noted that the foregoing explanation of the embodiment of the abnormality detection method for the vehicle-mounted fuel cell is also applicable to the abnormality detection device for the vehicle-mounted fuel cell of this embodiment, and will not be described again here.
According to the abnormality detection device for the vehicle-mounted fuel cell, whether the battery pack has flooding or membrane dry abnormality is judged through magnetic induction intensity around the battery pack of the vehicle-mounted fuel cell, and the flooding or membrane dry abnormality is judged when the actual magnetic induction intensity is not within a preset magnetic induction intensity interval, so that the local power generation condition of the battery pack is detected on line in real time by using an objective rule that different current intensities generate different magnetic field intensities, and the load-up/load-down amplitude of the fuel cell can be controlled according to the local power generation condition.
An embodiment of the present application also provides a vehicle including the abnormality detection device of the vehicle-mounted fuel cell of the above-described embodiment. According to the vehicle provided by the embodiment of the application, whether the battery pack is flooded or abnormal membrane is judged through the magnetic induction intensity around the battery pack of the vehicle-mounted fuel cell, and when the actual magnetic induction intensity is not in the preset magnetic induction intensity interval, the battery pack is judged to be flooded or abnormal membrane, so that the local power generation condition of the battery pack is detected on line in real time by using the objective rules that different current intensities generate different magnetic field intensities, and the loading/unloading amplitude of the fuel cell can be controlled according to the local power generation condition.
In the description herein, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or N embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the feature. In the description of the present application, "N" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more N executable instructions for implementing steps of a custom logic function or process, and alternate implementations are included within the scope of the preferred embodiment of the present application in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of implementing the embodiments of the present application.
The logic and/or steps represented in the flowcharts or otherwise described herein, such as an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or N wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
It should be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
In addition, functional units in the embodiments of the present application may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a stand-alone product, may also be stored in a computer readable storage medium.
The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc. Although embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application, and that variations, modifications, substitutions and alterations may be made to the above embodiments by those of ordinary skill in the art within the scope of the present application.
Claims (10)
1. An abnormality detection method for a vehicle-mounted fuel cell, characterized by comprising the steps of:
detecting actual magnetic induction of at least one detection point around each cell group of the vehicle-mounted fuel cell;
judging whether the actual magnetic induction intensity is in a preset magnetic induction intensity interval or not; and
and when the actual magnetic induction intensity of any detection point is not in the preset magnetic induction intensity interval, judging that the battery pack corresponding to any detection point is flooded or abnormal membrane is caused.
2. The method of claim 1, before determining whether the actual magnetic induction is within the preset magnetic induction interval, further comprising:
acquiring reference magnetic induction intensity at each detection point;
and acquiring the magnetic induction interval according to the reference magnetic induction.
3. The method of claim 2, wherein the obtaining the reference magnetic induction at each detection point comprises:
acquiring the number of single batteries in the current battery pack;
and determining the reference magnetic induction intensity according to the number of the single batteries.
4. The method of claim 3, wherein when said number is single;
the reference magnetic induction is as follows:
wherein k is
N is the number of all the single batteries, delta (n-12i) represents the magnetic induction intensity of the (n-12i) th battery pack, and n is a positive integer;
the magnetic induction intensity interval is as follows: [0.97Bn，1.03Bn]。
5. The method of claim 3, wherein when said number is two;
if the number of all the single batteries is an even number, the reference magnetic induction intensity is as follows:
wherein k is
An integer part, wherein delta (n-6i) represents the magnetic induction intensity of the (n-6i) th battery pack, n is a positive integer, and 2n represents the number of all single batteries;
if the number of all the single batteries is odd, the reference magnetic induction intensity is as follows:
wherein k is
The integral part, 2n +1 represents the number of all the single batteries, and the magnetic induction intensity of the 2n +1 th single battery is as follows:
6. the method according to claim 5, wherein when said number is two, said magnetic induction interval is:
[0.97(B2n-1+B2n)，1.03(B2n-1+B2n)]；
the magnetic induction intensity interval of the 2n +1 th single battery is as follows:
[0.97B2n+1，1.03B2n+1]。
7. the method of claim 3, wherein when the number is three:
if the vehicle-mounted fuel cell includes 3n single cells, the reference magnetic induction is:
wherein k is
An integer part, delta (n-4i) is the magnetic induction of the (n-4i) th battery pack;
if the vehicle-mounted fuel cell includes 3n +1 single cells, the reference magnetic induction is:
wherein, the magnetic induction intensity of the 3n +1 th single battery is:
if the vehicle-mounted fuel cell includes 3n +2 single cells, the reference magnetic induction is:
wherein, the magnetic induction intensity of the 3n +1 and 3n +2 single batteries is:
8. the method of claim 7, wherein when said number is three, said magnetic induction intervals are:
[0.97(B3n-2+B3n-1+B3n)，1.03(B3n-2+B3n-1+B3n)]；
the magnetic induction intensity interval of the 3n +1 th single battery is as follows:
[0.97B3n+1，1.03B3n+1]；
the magnetic induction intensity interval of the 3n +2 th single battery is as follows:
[0.97(B3n-2+B3n-1)，1.03(B3n-2+B3n-1)]。
9. an abnormality detection device for a vehicle-mounted fuel cell, characterized by comprising:
the detection module is used for detecting the actual magnetic induction intensity of at least one detection point around each battery pack of the vehicle-mounted fuel cell;
the judging module is used for judging whether the actual magnetic induction intensity is in a preset magnetic induction intensity interval or not; and
and the judging module is used for judging that the battery pack corresponding to any one of the detection points is flooded or abnormal membrane dryness when the actual magnetic induction intensity of the any one of the detection points is not in the preset magnetic induction intensity interval.
10. A vehicle characterized by comprising the abnormality detection device of the vehicle-mounted fuel cell according to claim 9.
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