CN115932611A - Lithium ion battery internal short circuit fault diagnosis method based on relaxation process - Google Patents
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Abstract
The invention provides a relaxation process-based lithium ion battery internal short-circuit fault diagnosis method, which is an internal short-circuit fault early warning method based on a relaxation voltage curve. Whether the internal short circuit fault occurs to the battery to be tested is judged by comparing the voltages of the internal short circuit fault battery and the normal battery in the relaxation process, and the magnitude of the internal short circuit resistance can be calculated to judge the severity of the fault. The method is low in calculation complexity, is convenient to implement in an embedded battery management system, and provides a new idea for simple and efficient internal short circuit fault early warning.
Description
Technical Field
The invention belongs to the field of lithium ion battery fault diagnosis, and particularly relates to a lithium ion battery internal short circuit fault diagnosis method based on a relaxation process.
Background
Due to the advantages of high power density, long cycle life and the like, the lithium ion battery is widely applied to new energy vehicles, consumer electronics products, power grids, user side energy storage and other scenes. However, the battery may malfunction due to a bad use scenario and a complicated use condition, and even cause a safety problem, for example, an internal short circuit fault caused by abuse of the battery may cause thermal runaway of the battery, and further cause serious safety accidents such as fire and explosion. Therefore, early warning of short circuits in the battery is indispensable to prevent thermal runaway of the battery during use.
Because the mechanism of the internal short-circuit fault is complex, the internal short-circuit fault is generated as a result of multi-factor coupling, an experiment is difficult to design to analyze the internal short-circuit fault of the commercial battery, researchers establish a thermoelectric coupling model of the lithium battery for exploring the fault mechanism of the internal short-circuit and realizing early warning of the internal short-circuit fault, and substitute the detected voltage and temperature data of the battery into the model for calculation to obtain electrochemical characteristics capable of reflecting the state of the internal short-circuit, so that early warning of the internal short-circuit is realized by the characteristics. However, the model-based method firstly needs to determine model parameters, a complex electrochemical model comprises a large number of parameters, and parameter identification is needed before the internal short circuit fault of the battery is evaluated each time. In addition, the complex electrochemical model is difficult to realize online evaluation, and the electrochemical model consists of a large number of partial differential equations and is difficult to realize online calculation in an embedded system. In order to simplify calculation, another scholars evaluate the internal short-circuit fault by comparing the discharge capacity with the charge capacity, the method firstly needs to evaluate the charge state in the charge and discharge process and calculate the maximum chargeable and dischargeable electric quantity of the battery, if the internal short-circuit fault occurs, the charged energy of the battery is larger than the dischargeable energy, but the charge state evaluation still needs to establish a circuit model and introduce Kalman filtering to update the model parameters. To date, a simple and effective internal short circuit fault assessment and early warning method is still lacking.
Disclosure of Invention
In order to solve the technical problems, the invention provides a lithium ion battery internal short-circuit fault diagnosis method based on a relaxation process, which is an internal short-circuit fault early warning method based on a relaxation voltage curve. Whether the internal short circuit fault occurs to the battery to be tested is judged by comparing the voltages of the internal short circuit fault battery and the normal battery in the relaxation process, and the magnitude of the internal short circuit resistance can be calculated to judge the severity of the fault. The method is low in calculation complexity, is convenient to implement in an embedded battery management system, and provides a new idea for simple and efficient internal short circuit fault early warning.
In order to achieve the purpose, the invention adopts the technical scheme that:
a lithium ion battery internal short circuit fault diagnosis method based on a relaxation process judges whether a tested battery has internal short circuit fault or not by comparing the voltages of a fault battery with a normal battery in the relaxation process, and calculates the size of a short circuit resistor to judge the severity of the fault, and specifically comprises the following steps:
the magnitude of the polarization is expressed as an overpotential, which increases with increasing current intensity; the relaxation is the inverse process of polarization, namely the process that the battery returns to the equilibrium potential after the battery finishes charging and discharging; once the internal short circuit occurs in the battery, the short-circuit current consumes electric energy, the SOC of the battery is reduced, and the voltage of the battery is reduced; identifying an ISC fault by analyzing a voltage response after battery discharge;
step 2, analyzing the relaxation process of the internal short-circuit fault battery:
the relaxation process and the loss process of the internal short-circuit fault battery both influence the voltage of the battery after the battery stops working, and the influence of the relaxation process and the loss process are independent; relaxation voltage V for internal short-circuit fault battery after discharging FR And a loss voltage V D Summing to obtain voltage response V of internal short-circuit fault battery SC As shown in formula (1):
V SC ＝V FR +V D (1)
loss voltage V in formula (1) D Related to the short circuit resistance for evaluating an internal short circuit fault level of the battery; the short-circuit resistance value is reduced, the short-circuit current is increased, the charge state is further reduced, and the loss voltage V is reduced D Increasing;
based on the formula (1), the loss voltage V D Voltage response V through internal short-circuit fault battery SC And relaxation voltage V FR Calculated, wherein the voltage response V of the internal short-circuit fault battery SC The voltage of the internal short-circuit fault battery is directly measured; the relaxation voltage V of formula (1) FR Replacement by relaxation voltage V of normal battery NR To evaluate the internal short fault level, as shown in equation (2):
V SC ＝V NR +V D (2)
step 3, obtaining the relaxation voltage V of the normal battery NR ：
Within a certain current interval, the overpotential of the battery is linearly related to the current, namely the magnitude of the relaxation voltage is linearly related to the current;
during the loss process, the amount of power lost by the short circuit resistance is calculated by equation (3):
W＝UIt (3)
wherein, W is the power loss, U and I are the battery voltage and the current flowing through the short-circuit resistor, respectively, and t is the standing time after the battery stops working; in order to evaluate the battery ISC degree, the discharge cutoff voltage before the battery stops operating is set to a constant value, i.e., the battery voltage U is a constant value; setting the standing time t after the battery stops working as a fixed value, and calculating the electric energy consumed in the same time after the battery stops working through a formula (3);
short-circuit resistance r for different internal short-circuit degrees 1 ,r 2 The current and the loss electric energy flowing through the short-circuit resistance loop are expressed as follows:
wherein r is 2 ＝kr 1 Subscripts 1 and 2 represent different degrees of internal short-circuiting, k is a constant representing the numerical relationship of internal short-circuiting resistance at different degrees of ISC, I 1 And I 2 Respectively representing the current, W, flowing through the short-circuit internal resistance at different ISC levels 1 And W 2 Respectively representing the electric quantity consumed by the short-circuit internal resistance of different ISC degrees;
from the formula (4)It follows that the product of the power loss and the short-circuit resistance is a constant value, defined herein as C 0 Namely:
W 2 r 2 ＝W 1 r 1 ＝C 0 (5)
based on equation (5), the battery short circuit resistance is calculated according to equation (6):
wherein W is the electric energy of the short-circuit resistance loss, and since the relation between the loss voltage and the loss electric energy is constant, W in the formula (6) is the loss voltage V D Instead of; the constant C in equation (7) represents the product of the loss voltage and the short-circuit resistance:
and finally, calculating the short-circuit resistance based on the equation (7) and the voltage response of the loss process, and judging the severity of the internal short-circuit fault according to the magnitude of the short-circuit resistance.
Has the beneficial effects that:
(1) The invention does not need additional hardware equipment: the existing internal short circuit fault detection technology is more dependent on the temperature and the impedance value of the battery, and the detection of the temperature and the impedance requires additional hardware equipment, such as a thermocouple and an additional circuit board. This increases the cost of the battery management system and also requires more space. The method provided by the invention can diagnose the internal short-circuit fault only by analyzing the electric signal, namely the voltage change of the battery.
(2) The invention has low calculation complexity: at present, a detection method only depending on an electric signal usually depends on a battery model, such as an equivalent circuit model, and a model-based algorithm introduces a higher-complexity algorithm example, such as Kalman filtering. The method provided by the invention can realize the diagnosis of the internal short circuit fault only by fitting the unique coefficient in the inverse proportion function of the internal short circuit resistance and the loss voltage obtained by calibration, and is beneficial to being realized in an embedded battery management system.
(3) The invention has high prediction precision: after experimental verification, the method provided by the invention can realize high-precision early warning in short-circuit fault levels of 5 omega, 10 omega, 20 omega, 30 omega, 50 omega and 100 omega, and the prediction precision of the method is consistent with an algorithm with higher calculation complexity.
Drawings
FIG. 1 is a schematic illustration of polarization versus relaxation;
FIG. 2 is a diagram of an equivalent circuit model; wherein, the diagram (a) is a normal battery; fig. (b) shows an ISC battery;
FIG. 3 is a schematic diagram of relaxation voltages after stopping operation of a normal battery and an ISC battery;
FIG. 4 is a voltage diagram; wherein, the graph (a) is a discharge voltage schematic diagram; FIG. b is a graph showing the loss process and loss voltage;
FIG. 5 is a schematic view of a battery test platform;
FIG. 6 is a graph showing normal cell relaxation voltage versus current change; wherein, graph (a) is the relaxation voltage of a normal battery at different discharge currents; graph (b) is a linear relationship of normal battery relaxation voltage versus current;
FIG. 7 is a schematic view of ISC fault battery voltage response; wherein, graph (a) is a relaxation voltage of a normal battery and a voltage response diagram of a battery with different ISC fault levels; fig. (b) is a graph of the depletion voltage for different ISC level cells;
FIG. 8 is a graph illustrating relaxation voltage results obtained in various ways; wherein, the diagram (a) is a schematic diagram of the fault relaxation voltage obtained by direct experimental measurement and calculation according to the formula (2); graph (b) is a graph of the difference in fault relaxation voltages obtained in two different ways;
FIG. 9 is a graph showing the loss voltages obtained by equation (2) for different short-circuit resistances; wherein, the resistance of the graph (a) is 5 omega; graph (b) resistance is 10 Ω; graph (c) resistance is 20 Ω; graph (d) resistance is 30 Ω; graph (e) resistance is 50 Ω;
graph (f) resistance is 100 Ω; graph (g) resistance is 200 Ω;
FIG. 10 is a graph showing the fitting results of loss voltages for different short circuit resistances; wherein, the resistance of graph (a) is 5 omega; graph (b) resistance is 10 Ω; graph (c) resistance is 20 Ω; graph (d) resistance is 30 Ω; graph (e) resistance is 50 Ω; graph (f) resistance is 100 Ω; graph (g) resistance is 200 Ω;
FIG. 11 is a diagram illustrating the relationship between loss voltage and short-circuit resistance;
FIG. 12 is a schematic of the inverse proportional function obtained from 7 pairs of data and fitting to all data, respectively; wherein, the graph (a) is a 3D graph; fig. (b) is a front view of the 3D map.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. In addition, the technical features involved in the embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
The invention introduces the theoretical basis of a relaxation process-based lithium ion battery internal short-circuit fault diagnosis method, establishes the correlation between internal short-circuit resistance and voltage drop caused by the internal short-circuit resistance in the relaxation process, and clarifies the feasibility of the method. In addition, the effects of different discharge conditions on the present invention will be discussed to demonstrate its applicability. Finally, the effectiveness of the method is verified through experiments, and the advantages of the method are highlighted.
As shown in fig. 1 to 4, the method for diagnosing a short-circuit fault in a lithium ion battery based on a relaxation process of the present invention specifically includes the following steps:
the phenomenon of the electrode potential (or cell potential) deviating from the equilibrium potential due to the faraday current passing through the electrochemical system is called polarization, the magnitude of which is expressed as an overpotential, which increases with increasing current intensity. Relaxation can be viewed as the reverse process of polarization, i.e., the process by which the cell returns to equilibrium potential after it has been charged and discharged, and can also be referred to as depolarization. When an Internal Short Circuit (ISC) occurs in the battery, the Short Circuit current consumes electric energy, and the state of charge of the battery decreases, causing a drop in battery voltage. The present invention is centered on this idea, identifying ISC faults by analyzing the voltage response after battery discharge. Fig. 1 shows the relationship between polarization and relaxation.
Step 2, analyzing the relaxation process of the ISC fault battery:
for a normal battery without ISC failure, the separator can prevent a current loop from being generated inside the battery. However, abuse of the battery can degrade separator performance, resulting in short circuits inside the battery. In terms of electrical characteristics, the internal short Circuit can be explained by an Equivalent Circuit Model (ECM) as shown in fig. 2. Unlike the ECM of a normal battery, the ECM of an ISC battery includes a closed current loop, which may present a short circuit resistance in parallel. In this closed loop, after the battery stops operating, there is still a short-circuit current flowing through the battery, the intensity of which depends on the value of the short-circuit resistance, which is related to the degree of degradation of the separator. In the initial stage of the ISC, the short-circuit resistance is large and the short-circuit current intensity is low. From step 1 (the overpotential increases with the increase of the current intensity), it can be known that the overpotential caused by the small short-circuit current is much lower than the overpotential generated by the current when the battery normally works. Therefore, it is considered that an overpotential caused by the short-circuit current can be ignored. On this basis, when the ISC battery stops discharging, the ISC battery is approximately restored to the equilibrium potential, as shown in fig. 3. And as a part of overpotential, ohm disappears immediately after overpotential discharge, response speed is very fast, and short-circuit current does not influence the overvoltage. Therefore, the variation tendency of the relaxation voltage after the discharge of the ISC battery is the same as that of the normal battery, as shown in fig. 3. From the above description, the ISC battery has a similar trend of change and end value of the relaxation process to the normal battery, and on this basis, it can be inferred that the ISC battery has a relaxation process highly consistent with the normal battery.
Although the short circuit does not have a significant effect on the relaxation process, the effect of the short circuit-induced electrical energy loss on the voltage is significant. Unlike a normal battery, after the ISC battery stops operating, the short-circuit current continues to pass through the battery. Even a small short-circuit current, i.e., an initial ISC stage with a large short-circuit resistance, results in a significant voltage drop, especially when the Depth of Discharge (DOD) is large, as shown in graph (a) of fig. 4. In the present invention, the effect of the short-circuit current induced voltage drop is defined as a loss process, and the voltage drop is defined as a loss voltage, as shown in diagram (b) of fig. 4.
In summary, for the ISC battery, the relaxation process and the depletion process both affect the voltage after the battery stops working, but the action mechanism is different. During the depletion process, the short-circuit resistance induces a faraday current due to the insertion and extraction of lithium ions, resulting in a decrease in the state of charge (SOC) and, ultimately, a voltage drop. While the relaxation process affects the voltage by redistribution of lithium ions in the electrode, where there is no faraday current. The effects of relaxation and depletion processes are independent of each other under different mechanisms. Therefore, after the ISC battery is discharged, the relaxation voltage V to the ISC battery FR And loss voltage V D Summing to obtain voltage response V of ISC battery SC As shown in formula (1):
V SC ＝V FR +V D (8)
it is to be noted that the loss voltage V in the formula (1) D Related to the short circuit resistance. The short-circuit resistance value decreases, the short-circuit current increases, and the state of charge SOC further decreases, so that the loss voltage increases. Since the loss voltage is related to the short-circuit resistance, it can be used to evaluate the ISC fault level of the battery.
Based on equation (1), the loss voltage V D Voltage response V through ISC battery is required SC And relaxation voltage V FR Calculated, wherein voltage response V of the ISC battery SC Can be obtained directly by measuring the ISC battery voltage. The relaxation process of the ISC battery is similar to that of a normal battery, and the relaxation voltage V of the normal battery NR The relaxation voltage V of the formula (1) is easy to measure FR Replacement by relaxation voltage V of normal battery NR To evaluate the ISC fault level, as shown in equation (2):
V SC ＝V NR +V D (9)
and evaluating the ISC degree of the lithium battery by using the relaxation voltage of the normal battery.
Step 3, obtaining the relaxation voltage of the normal battery:
as described in step 1, relaxation is the inverse of polarization, indicating that overpotential is related to relaxation voltage amplitude. Therefore, by studying the relationship between the overpotential and the current, the relationship between the magnitude of the relaxation voltage and the current can be clarified.
The overpotential of an electrochemical cell is composed of three main components, including ohmic overpotential, concentration overpotential, and activation overpotential. When the battery is discharged at a medium rate (about 1C), the ohmic overpotential has a large proportion, and the relationship between the ohmic overpotential and the current conforms to ohm law, namely, the ohmic overpotential and the current are linearly related. From this, it is known that the overpotential of the battery is linearly related to the current in a certain current interval, that is, the magnitude of the relaxation voltage is linearly related to the current.
during the loss process, the electrical quantity of the short circuit resistance loss is calculated by the formula (3):
W＝UIt (10)
where W is the power dissipated, U and I are the battery voltage and the current flowing through the short circuit resistor, respectively, and t is the rest time after the battery has stopped operating. In order to evaluate the battery ISC degree, the discharge cutoff voltage before the battery stops operating is set to a constant value, i.e., the battery voltage U is a constant value. Further, since the standing time t after the battery stops operating is set to a constant value, the equation (3) can calculate the electric energy consumed in the same time after the battery stops operating.
Based on the above setting, the short-circuit resistance r for different ISC degrees 1 ,r 2 The current flowing through the short-circuit resistance loop (as shown in diagram (b) of fig. 2) and the loss power can be expressed as follows:
wherein r is 2 ＝kr 1 Subscripts 1 and 2 represent different degrees of ISC, k is a constant representing the numerical relationship of the internal short-circuit resistance at different degrees of ISC, I 1 And I 2 Respectively representing the current, W, flowing through the short-circuit internal resistance at different ISC levels 1 And W 2 Respectively, the amounts of power consumed by the short-circuit internal resistances of different ISC degrees.
As can be seen from equation (4), the product of the power loss and the short-circuit resistance is a constant value, defined herein as C 0 That is to say that,
W 2 r 2 ＝W 1 r 1 ＝C 0 (12)
based on equation (5), the battery short circuit resistance can be calculated according to equation (6):
wherein, W is the electric energy of the short-circuit resistance loss; further, since the discharge cut-off voltage is not changed, it is explained that the loss process starts at the same voltage, and therefore the relation between the loss voltage and the loss electric energy is also constant, and based on this invariable relation, the loss voltage V for W in the expression (6) D Instead of this. Accordingly, the constant C in equation (7) is used to represent the product of the loss voltage and the short-circuit resistance:
finally, based on equation (7) and the voltage response of the loss process, the short-circuit resistance can be calculated, and the severity of the fault can be determined by the short-circuit resistance.
As shown in fig. 5, the battery test platform adopted by the present invention comprises the following components: battery charging and discharging equipment, the voltage and current ranges are respectively 20V and 10A, and the measurement precision of the voltage and the current are 0.1 percent FS; the constant temperature box maintains constant environmental temperature in the charging and discharging process, the adjustable temperature interval is 15-60 ℃, and the temperature control precision is 2 ℃; the upper computer is used for acquiring data and controlling battery charging and discharging equipment; the specific parameters of the lithium iron phosphate batteries used for the test are shown in table 1.
As described above, calculating the short-circuit resistance requires the relaxation voltage of a normal battery. In order to obtain and verify the linear relationship with the current, the current meter is provided withThe battery relaxes after discharging to 2.5V at different currents, and the voltage during relaxation is recorded as V NR . Different levels of ISC failure were simulated by connecting external resistors of 5 Ω,10 Ω,20 Ω,30 Ω,50 Ω,100 Ω, and 200 Ω, respectively, in parallel to the battery under test. The battery is also discharged to 2.5V and then relaxed to obtain a voltage V SC The method comprises the following specific steps:
step 1: discharging the battery to 2.5V and standing for 2 hours;
step 2: charging to an upper cutoff voltage at 1C;
and step 3: standing for 10 minutes;
and 4, step 4: discharging to 2.5V under the conditions of 0.5C,0.75C,1C,1.25C,1.5C,1.75C and 2C respectively;
and 5: and standing for 10 minutes.
To avoid the effects of internal resistance and capacity differences, steps 1-5 were performed with the same cell.
TABLE 1
It is noted that the validity of equation (2) is the basis for the short-circuit resistance calculation, and therefore, in addition to the relaxation voltages of the normal battery and the ISC battery, the loss voltage also needs to be measured to verify equation (2). Due to loss of voltage V D The SOC reduction is induced, and during the measurement, the same amount of reduction in battery SOC as during the depletion is achieved. For this purpose, the battery was discharged to 2.5V and then discharged at constant resistance (5 Ω,10 Ω,20 Ω,30 Ω,50 Ω,100 Ω,200 Ω) to simulate power consumption at different ISC levels during consumption. The specific measurement scheme is shown in steps 6-7:
and 6: discharging with constant resistances of 5 Ω,10 Ω,20 Ω,30 Ω,50 Ω,100 Ω,200 Ω;
and 7: and standing for 10 minutes.
The relaxation voltage curves of the normal cell at different rates are shown in fig. 6. In the graph (a) of fig. 6, the voltage curve is the relaxation voltage curve of the battery after discharging to 2.5V at 2C to 0.5C, respectively, from top to bottom. The end point value of each curve in graph (a) of fig. 6 is selected and fitted to the current multiplying factor, and the fitting result is shown in graph (b) of fig. 6. The battery relaxation voltage and the discharge rate are in linear relation, and the battery relaxation voltage and the discharge rate can be calculated according to the linear relation after the battery is discharged at different rates, so that the possibility is provided for ISC fault evaluation under different discharge scenes. To facilitate the validation of the method proposed by the present invention, the following analysis develops the experimental results obtained for the 1C discharge rate.
V SC ，V NR And V D The experimental results of (a) are shown in fig. 7. In the graph (a) of FIG. 7, the voltage curves correspond to the normal relaxation voltages V from the top to the bottom, respectively NR And V at 200 Ω to 5 Ω short-circuit resistance SC . In the graph (b) of fig. 7, the voltage curves respectively correspond to V under 200 Ω -5 Ω short-circuit resistance from top to bottom D . In addition, as can be seen from the graph (a) of fig. 7, the voltage responses of the batteries of different ISC fault levels can be clearly distinguished within 300 seconds, which provides a possibility for the ISC rapid test. For this purpose, in the present invention, a data trophy within 300 seconds after stopping discharge is used to perform ISC fault level assessment.
V in formula (2) NR And V D Is obtained by superimposing the normal relaxation voltage curve in the graph (a) of fig. 7 and each curve in the graph (b) of fig. 7, and comparing the superimposed result with the curve of the corresponding resistance level in the graph (a) of fig. 7, the comparison result being shown in fig. 8. In the graph (a) of fig. 8, the voltage curves respectively correspond to V under 200 Ω -5 Ω short-circuit resistance from top to bottom SC Wherein the dotted line is obtained by superimposing the formula (2), and the solid line is directly measured experimentally. FIG. 8 is a graph (b) showing V obtained by two ways of experimental measurement and superposition of the formula (2) SC The error therebetween can be seen from the fact that V obtained by direct measurement through experiments and V obtained by the formula (2) SC The height is consistent, and the error between the short-circuit resistance and the resistance is less than 5 millivolts except for the partial interval when the short-circuit resistance is 5 omega and 200 omega. These results verify the correctness of equation (2), so V D Can be obtained through calculation, thereby further realizing quantitative evaluation of the ISC fault level. In the case of different short-circuit resistances, based on formula(2) Obtained V D As shown in fig. 9, it can be seen from the graph that as the short-circuit resistance increases, noise of the voltage value becomes more significant as shown in graphs (a), (b), (c), (d), (e), (f) and (g) of fig. 9, which directly affects the evaluation of the ISC. For this purpose, a method of function fitting is used to obtain a smooth V D Curve line. According to V D Curve characteristic of (1), V in formula (8) D (t) fitting of V D Wherein a, b, c, p 1 And p 2 The fitting result is shown in fig. 10 (a), (b), (c), (d), (e), (f), and (g).
From determining the coefficient R 2 It can be seen that a better fitting result can be obtained when the short-circuit resistance is less than 100 Ω. When the short-circuit resistance reaches 100 omega, V D Is significantly reduced, resulting in a reduced signal-to-noise ratio, which directly affects R 2 Therefore relatively low R 2 Is acceptable. As can be seen from the graphs (f) and (g) of fig. 10, the fitting result still obtains an accurate variation trend.
V at a specific time according to the fitting result D Values can be obtained and used to explore its relationship to short circuit resistance as shown in equation (7). In the present invention, V at 300 seconds after the battery stops discharging D The values are used to explore the relationship in equation (7). Seven different short-circuit resistance values (5 Ω,10 Ω,20 Ω,30 Ω,50 Ω,100 Ω,200 Ω), and corresponding V D Was used to fit an inverse proportional function, as shown in FIG. 11, which demonstrates the short circuit resistance vs. V D In an inverse proportional relationship.
As shown in equation (7), the inverse proportional function has only one coefficient C 0 Therefore, after the inverse proportional relationship is proved, only one pair of short-circuit resistors and corresponding V are needed D The relationship between the two can be determined. Based on seven sets of data (5 Ω,10 Ω,20 Ω,30 Ω,50 Ω,100 Ω,200 Ω and corresponding V in fig. 11 D ) Seven, sevenThe inverse scale functions are plotted in fig. 12, respectively, and the inverse scale functions obtained by fitting all seven sets of data in fig. 9 are also plotted in fig. 12 for comparison (middle data number 8 (coordinate point 8 of diagram (a) of fig. 12)). As can be seen from diagram (b) of fig. 12, except for 200 Ω and the corresponding V D In addition, the remaining seven function curves in the graph all show high consistency, which indicates that a relationship can be effectively established by one pair of data, meaning that the evaluation of the ISC fault can be realized by little data.
It will be understood by those skilled in the art that the foregoing is only a preferred embodiment of the present invention, and is not intended to limit the invention, and that any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (1)
1. A lithium ion battery short-circuit fault diagnosis method based on a relaxation process is characterized in that: the method comprises the following steps of judging whether the battery to be detected has an internal short circuit fault by comparing the voltages of a fault battery with a normal battery in the relaxation process, and calculating the size of a short circuit resistor to judge the severity of the fault, wherein the method specifically comprises the following steps:
step 1, establishing a relation between polarization and relaxation: the magnitude of the polarization is expressed as an overpotential, which increases with increasing current intensity; the relaxation is the inverse process of polarization, namely the process that the battery returns to the equilibrium potential after the battery finishes charging and discharging; once the internal short circuit occurs in the battery, the short-circuit current consumes electric energy, the SOC of the battery is reduced, and the voltage of the battery is reduced; identifying an ISC fault by analyzing a voltage response after battery discharge;
step 2, analyzing the relaxation process of the internal short-circuit fault battery:
the relaxation process and the loss process of the internal short-circuit fault battery both influence the voltage of the battery after the battery stops working, and the influence of the relaxation process and the loss process are independent; relaxation voltage V for internal short-circuit fault battery after discharging FR And a loss voltage V D Summing to obtain voltage response V of internal short-circuit fault battery SC As shown in formula (1):
V SC ＝V FR +V D (1)
loss voltage V in formula (1) D Related to the short circuit resistance for evaluating an internal short circuit fault level of the battery; the short-circuit resistance value is reduced, the short-circuit current is increased, the charge state is further reduced, and the loss voltage V is reduced D Increasing;
based on the formula (1), the loss voltage V D Voltage response V through internal short-circuit fault battery SC And relaxation voltage V FR Calculated, wherein the voltage response V of the internal short-circuit fault battery SC The voltage of the internal short-circuit fault battery is directly measured; the relaxation voltage V of formula (1) FR Replacement by relaxation voltage V of normal battery NR To evaluate the internal short-circuit fault level, as shown in equation (2):
V SC ＝V NR +V D (2)
step 3, obtaining the relaxation voltage V of the normal battery NR : within a certain current interval, the overpotential of the battery is linearly related to the current, namely the magnitude of the relaxation voltage is linearly related to the current;
step 4, calculating the short-circuit resistance:
during the loss process, the amount of power lost by the short circuit resistance is calculated by equation (3):
W＝UIt (3)
wherein, W is the power loss, U and I are the battery voltage and the current flowing through the short-circuit resistor, respectively, and t is the standing time after the battery stops working; in order to evaluate the battery ISC degree, the discharge cutoff voltage before the battery stops operating is set to a constant value, i.e., the battery voltage U is a constant value; setting the standing time t after the battery stops working as a fixed value, and calculating the electric energy consumed in the same time after the battery stops working through a formula (3);
short-circuit resistance r for different internal short-circuit degrees 1 ,r 2 The current and the loss power flowing through the short-circuit resistance loop are expressed as follows:
wherein r is 2 ＝kr 1 Subscripts 1 and 2 represent different degrees of internal short-circuiting, k is a constant representing the numerical relationship of internal short-circuiting resistance at different degrees of ISC, I 1 And I 2 Respectively representing the current, W, flowing through the short-circuit internal resistance at different ISC levels 1 And W 2 Respectively representing the electric quantity consumed by the short-circuit internal resistance of different ISC degrees;
the product of the power loss and the short-circuit resistance, which is a constant value and is defined as C in this case, is obtained from equation (4) 0 Namely:
W 2 r 2 ＝W 1 r 1 ＝C 0 (5)
based on equation (5), the battery short-circuit resistance is calculated according to equation (6):
wherein W is the electric energy of the short-circuit resistance loss, and since the relation between the loss voltage and the loss electric energy is constant, the loss voltage V is used for W in the formula (6) D Instead of this; the constant C in equation (7) represents the product of the loss voltage and the short-circuit resistance:
and finally, calculating the short-circuit resistance based on the equation (7) and the voltage response of the loss process, and judging the severity of the internal short-circuit fault according to the magnitude of the short-circuit resistance.
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| CN116338501A (en) * | 2022-12-19 | 2023-06-27 | 哈尔滨工业大学 | Lithium ion battery health detection method based on neural network prediction relaxation voltage |
| CN116577674A (en) * | 2023-07-13 | 2023-08-11 | 国仪量子(合肥)技术有限公司 | Method, device and storage medium for detecting battery performance |
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| CN116338501A (en) * | 2022-12-19 | 2023-06-27 | 哈尔滨工业大学 | Lithium ion battery health detection method based on neural network prediction relaxation voltage |
| CN116338501B (en) * | 2022-12-19 | 2023-09-12 | 哈尔滨工业大学 | Lithium ion battery health detection method based on neural network prediction relaxation voltage |
| CN116577674A (en) * | 2023-07-13 | 2023-08-11 | 国仪量子(合肥)技术有限公司 | Method, device and storage medium for detecting battery performance |
| CN116577674B (en) * | 2023-07-13 | 2023-10-10 | 国仪量子(合肥)技术有限公司 | Method, device and storage medium for detecting battery performance |
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