CN116147840A - Multi-station leakage fault diagnosis method based on electric-thermal-gas signal fusion - Google Patents
Multi-station leakage fault diagnosis method based on electric-thermal-gas signal fusion Download PDFInfo
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Abstract
The invention establishes a fault characteristic parameter set by integrating the electric signal parameter, the thermal signal parameter and the gas signal parameter which represent the leakage fault of the battery electrolyte. Dividing the effective action interval of each fault characterization parameter according to the diagnosis time of each characteristic parameter, and formulating diagnosis priority. And combining the characteristic parameters under multiple working conditions according to the priority of the characteristic parameters, and providing a diagnosis method for multi-parameter fusion. The method can improve the reliability and timeliness of battery leakage fault diagnosis.
Description
Technical Field
The invention relates to a method for diagnosing leakage faults of a lithium ion battery, in particular to a multi-condition leakage fault diagnosis method based on 'electric-thermal-gas' signal fusion.
Background
In recent years, with the rapid development of the electric automobile industry, the safety performance of lithium ion batteries has become a focus of attention in the industry. Generally, the main reasons for battery safety accidents are electrical abuse, thermal abuse, mechanical abuse, and defects in the manufacturing process. Electrolyte leakage is one of typical faults of lithium ion batteries, the reliability of the batteries is seriously damaged, and safe and stable operation of the electric automobile is threatened. Therefore, it is necessary to diagnose the leakage failure of the lithium ion battery.
In the leakage process of the electrolyte of the lithium ion battery, the content of the electrolyte of the battery is reduced, the electrolyte continuously reacts with moisture in the air, the self-discharge degree of the battery is deepened, the anode active material is damaged, and lithium deposition occurs in the charging process. In severe cases, a fire explosion of the battery system may be caused. Through long-time standing and charge-discharge testing of the battery, the leakage battery has different performances from the normal battery in voltage, current and temperature and signals based on monitoring of volatile organic compound gas.
The method for diagnosing faults is not clear according to the electric, thermal and gas signal characteristics when the lithium ion battery has the leakage faults. The prior art (application number: 202010862452.6) requires a long time for fault diagnosis based on an electric signal, and there is a risk of misdiagnosis.
Therefore, it is necessary to diagnose the leakage fault based on the differential characterization parameters of the leakage battery on the electric signal, the thermal signal, and the gas signal. In addition, in order to improve the timeliness and reliability of the fault diagnosis result, it is necessary to integrate the parameters of three signals, and a multi-condition leakage fault diagnosis method based on 'electric-heat-gas' signal fusion is provided.
Disclosure of Invention
In order to solve the technical problems, the invention provides a multi-working condition leakage fault diagnosis method based on 'electric-heat-gas' signal fusion, which comprises the following steps:
standing and charging and discharging test are carried out on the normal battery and the liquid leakage battery;
obtaining voltage and current signals of a battery in a constant-current charging stage, a constant-voltage charging stage and a standing stage after charging;
obtaining electric characteristic parameters of the battery and performing leakage fault diagnosis based on the electric signals;
acquiring temperature signals of a constant-current charging stage, a constant-voltage charging stage and a standing stage after charging;
obtaining thermal characteristic parameters of the battery and performing leakage fault diagnosis based on thermal signals;
acquiring volatile organic compound gas signals of the battery in a constant-current charging stage, a constant-voltage charging stage and a standing stage after charging;
obtaining gas characteristic parameters of the battery and performing leakage fault diagnosis based on gas signals;
integrating leakage fault parameters;
dividing effective action intervals of each fault characterization parameter and making diagnosis priority;
combining the electrical characteristic parameter, the thermal characteristic parameter and the gas characteristic parameter under multiple working conditions;
and diagnosing the battery leakage fault.
Based on the scheme, the method for obtaining the electrical characteristic parameters of the battery and performing the leakage fault diagnosis based on the electrical signals comprises the following specific steps:
in the constant current charging stage, the peak characteristic parameters of the normal battery and drain battery IC curves are extracted, including but not limited to: the peak position, peak height, peak area and peak width are diagnosed according to the evolution rule along with the cycle times;
extracting characteristic parameters related to current in the constant voltage charging stage of the drain battery, including but not limited to: the moment when the current starts to rise, the peak current reached after rising, and the characteristic peak position and peak value of the differential curve;
drawing standing voltage and normalized differential curve of a normal battery and a drain battery;
extracting characteristic parameters related to the standing voltage of the drain battery, including but not limited to: characteristic peak and valley positions of the differential voltage curve.
Based on the scheme, the method for obtaining the thermal characteristic parameters of the battery and performing leakage fault diagnosis based on the thermal signals specifically comprises the following steps:
according to a temperature-voltage variation curve (TV) and a differential curve (DTV) of a normal battery and a drain battery in a constant current charging stage in a cyclic aging process, characteristic parameters representing battery faults are obtained, including but not limited to: voltage corresponding to the maximum value and the minimum value in the battery temperature change curve, and temperature differential value symbols at the battery reverse point and the end of charging;
and combining the characteristic parameters related to the standing voltage of the liquid leakage battery, and diagnosing the liquid leakage fault according to the mutation of the characteristic parameters.
Based on the scheme, the gas characteristic parameters of the battery are obtained and the leakage fault diagnosis based on the gas signal is specifically as follows:
and detecting volatile organic gas generated by leakage of the battery electrolyte through the gas sensor, comparing the volatile organic gas with the gas concentration change condition of a normal battery, and judging whether the battery electrolyte is leaked or not.
Based on the scheme, under two environmental conditions of sealing and temperature control, when the battery is in a standing working condition and a charging and discharging working condition, the change curve of the gas concentration of the normal battery and the gas concentration of the liquid leakage battery along with time is obtained, and the diagnosis of the leakage fault of the electrolyte is carried out according to the change of the gas concentration.
Based on the scheme, the integrated leakage fault parameters are specifically as follows:
integrating electrical signal parameters theta characterizing battery electrolyte leakage failure E Parameter θ of thermal signal T And the air signal parameter theta G Establishing a fault characteristic parameter set theta L ：
θ L ＝{θ E ，θ T ，θ G } (1)
On the basis of the scheme, the effective action intervals of the fault characterization parameters are divided, and the diagnosis priority is formulated specifically as follows:
dividing the effective action interval of each fault characterization parameter according to the diagnosis time of each characteristic parameter, and formulating diagnosis priority, wherein the earlier the diagnosis time is, the higher the priority is;
the priority is sequentially from high to low: the characteristic peak I electric signal of the constant-current charging section, the characteristic peak II1 electric signal of the constant-current charging section, the thermal signal, the characteristic peak II2 electric signal of the constant-current charging section, the electric signal characteristic parameter of the constant-voltage charging section and the electric signal characteristic parameter of the standing stage after charging.
Based on the scheme, the characteristic parameters are combined according to the priority of the characteristic parameters, and a multi-parameter fusion electrolyte leakage fault diagnosis method is provided:
diagnosing based on the concentration change of the gas signal, and judging that the electrolyte of the battery leaks once the concentration of the gas increases suddenly;
under the condition that the gas concentration does not change obviously, the leakage diagnosis is carried out through an electric signal and a thermal signal: when the self-discharging degree of the battery is deepened, judging whether the corresponding fault characteristic parameters are suddenly changed or not according to the working condition of the battery;
under the constant current charging condition, if the battery has characteristic peak I electric signal characteristic parameters of a constant current charging section or characteristic peak II1 electric signal characteristic parameters of the constant current charging section, the battery cathode active material is deteriorated, whether the thermal signal characteristic parameters or characteristic peak II2 electric signal characteristic parameters are suddenly changed or not needs to be further determined, and if the thermal signal characteristic parameters or the characteristic peak II2 electric signal characteristic parameters are suddenly changed, the battery electrolyte leaks;
under constant voltage charging or a static condition after charging, if an electrical signal characteristic parameter of a constant voltage charging section or an electrical signal characteristic parameter of a static stage after charging occurs, an electrolyte leakage fault occurs in the battery.
The invention has the beneficial effects that:
electrical signal parameter θ characterizing battery electrolyte leakage failure by integration E Parameter θ of thermal signal T And the air signal parameter theta G Establishing a fault characteristic parameter set theta L 。
Dividing the effective action interval of each fault characterization parameter according to the diagnosis time of each characteristic parameter, and formulating diagnosis priority. And combining the characteristic parameters under multiple working conditions according to the priority of the characteristic parameters, and providing a diagnosis method for multi-parameter fusion.
The method improves the reliability and timeliness of the leakage fault diagnosis.
Drawings
The invention has the following drawings:
FIG. 1 is a flow chart of a multi-station leakage fault diagnosis method based on "electric-thermal-pneumatic" fusion;
FIG. 2 is a graph of electrical signals for a normal cell and a leaky cell;
FIG. 3 is a graph of normal cell and drain cell thermal signals;
FIG. 4 is a graph of normal cell and drain cell gas signals;
FIG. 5 is a multi-condition leakage fault diagnosis method for multi-parameter fusion.
Detailed Description
The present invention will be described in further detail with reference to fig. 1-5 and the detailed description of the invention, in order to make the objects, advantages and features of the invention more apparent.
Referring to fig. 1, the invention provides a multi-station leakage fault diagnosis method based on 'electric-heat-gas' signal fusion, which can effectively identify whether a battery has leakage fault.
The method comprises the steps of performing constant-current and constant-voltage charging test on the battery based on leakage fault diagnosis of an electric signal, and respectively obtaining a voltage curve of the battery in a constant-current charging stage, a current curve of the battery in a constant-voltage charging stage and a voltage curve of the battery in a standing stage after charging. And performing differential processing on the obtained voltage and current curves to obtain corresponding differential curves. The constant current charging voltage curves of the normal battery and the drain battery are shown in fig. 2 (a) and (b). With increasing cycle times, the voltage curve of the normal cell does not change significantly, and only the height of peak i of the IC curve decreases. However, as the number of cycles increases, the voltage curve begins to create a new plateau ii 2. In addition, the IC curve gradually disappears as the characteristic peak II1 and the characteristic peak II2 is formed, except for the decrease in the height of the characteristic peak I. And extracting peak characteristics of the IC curves of the normal battery and the drain battery in the constant current charging stage, including but not limited to peak positions, peak heights, peak areas and peak widths, and diagnosing according to the evolution rule of the normal battery and the drain battery along with the cycle times. Besides the constant current charging phase, the constant voltage charging and the rest phase after charging can also detect lithium deposition. The constant voltage charge current curves of the normal cell and the drain cell are shown in fig. 2 (c), (d). The method comprises the steps that a current characteristic peak appears in a constant voltage charging stage of the drain battery, a current differential curve is obtained according to the constant voltage charging current curve, and characteristic parameters related to the current in the constant voltage charging stage of the drain battery are extracted, wherein the characteristic parameters include, but are not limited to, the moment when the current starts to rise, the peak current reached after rising, and the position and the peak value of the differential curve characteristic peak are used as characteristic parameters for representing lithium deposition of the battery; and drawing a standing voltage curve of the normal battery and the liquid leakage battery, wherein the standing voltage of the liquid leakage battery is a platform as shown in fig. 2 (e) and (f). Differentiating the standing voltage curve, and extracting characteristic parameters related to the standing voltage of the drain battery, including but not limited to characteristic peak positions and valley positions of the differentiated voltage curve. And diagnosing the leakage fault according to the phenomena of mutation of the characteristic parameters and the like. The diagnosis method based on the electric signals combines the voltage and current characteristic parameters of the standing process and the charging process, and has accurate and reliable diagnosis results, but longer diagnosis time.
The invention includes leakage fault diagnosis based on thermal signals. Leakage fault diagnosis based on thermal signals mainly depends on changes in battery temperature. The differential curve of the battery temperature is similar to the IC curve, and can represent the phase change reaction and side reaction of the battery active material. And diagnosing the leakage fault based on a constant-current charging temperature change curve of the battery along with the voltage and a differential curve thereof in the continuous cyclic aging process. In the cyclic aging process, the temperature of the normal battery and the temperature of the drain battery change curve along with the voltage in the constant current charging stage (as shown in fig. 3), the position of the maximum value in the temperature change curve of the drain battery compared with the normal battery starts to deviate along with the increase of the cycle times, and the phenomenon that the temperature rises again in the final charging stage disappears. Characteristic parameters that may characterize a battery fault are obtained, including, but not limited to, voltages corresponding to maxima and minima in the battery temperature profile, and signs of battery reversal points and temperature differential values at the end of charge. And diagnosing the leakage fault according to the characteristic parameters. However, since the weak self-discharge process of the battery is difficult to embody in thermal characteristics, electrolyte leakage cannot be determined depending on a separate thermal signal, and a diagnosis method based on an electrical signal is required.
The invention includes leakage fault diagnosis based on gas signals. Unlike the failure diagnosis principle based on electrical and thermal signals, the diagnosis based on the gas signal does not require long-time standing or continuous charge and discharge to monitor the self-discharge of the battery, the degradation of the anode active material, and the degree of lithium deposition. Normally, the battery does not generate volatile gas, and the electrolyte is leaked and then reacts with moisture in the air to finally generate the volatile gas. According to the fault diagnosis method based on the gas signal, the volatile organic gas (VOC) generated by leakage of the battery electrolyte is detected through the gas sensor, and compared with the gas concentration change condition of a normal battery, whether the battery electrolyte leaks or not is judged. As shown in fig. 4, the gas concentration of the normal cell does not change over a period of time, while the gas concentration of the leaky cell increases significantly over the same period of time. The diagnosis method based on the gas signal is not influenced by the battery operation condition, can rapidly perform liquid leakage diagnosis in a closed environment, but can be developed with time or influenced by the environment condition, and can have the risk of failure. According to the characteristic parameters of the leakage battery on the electric signal, the thermal signal and the air signal, the other characteristic parameters can show obvious variation trend different from that of a normal battery, and the leakage fault diagnosis method based on the electric signal, the thermal signal and the air signal respectively is obtained.
Because the diagnosis method based on the single signal has the defects in timeliness and reliability, in order to improve the timeliness and reliability of fault diagnosis results, the electric signal parameter theta for representing the leakage fault of the battery electrolyte is integrated E Parameter θ of thermal signal T And the air signal parameter theta G Establishing a fault characteristic parameter set theta L ：
θ L ＝{θ E ，θ T ，θ G } (1)
In the continuous development process of electrolyte leakage faults, dividing the effective action interval of each fault characterization parameter according to the diagnosis time of each characteristic parameter, and formulating diagnosis priority. Of all the characteristic parameters, the gas has the earliest diagnostic time and the highest priority. Secondly, the electric signal in the long-time standing stage can be diagnosed through standing for a certain time after electrolyte leaks. The rest electric and thermal characteristic parameters can be mutated only after certain circulation, so that the diagnosis time is relatively late and the priority is relatively low. The priority is sequentially from high to low: the characteristic peak I electric signal of the constant-current charging section, the characteristic peak II1 electric signal of the constant-current charging section, the thermal signal, the characteristic peak II2 electric signal of the constant-current charging section, the electric signal characteristic parameter of the constant-voltage charging section and the electric signal characteristic parameter of the standing stage after charging.
In addition to determining the priority of each characteristic parameter, the combination relation of each characteristic parameter still needs to be determined. Independent parameters based on battery electrical and thermal signals tend to be difficult to diagnose electrolyte leakage faults, such as: the degree of self-discharge of the battery increases, and may be caused by external short-circuiting or internal short-circuiting, in addition to leakage of the electrolyte. Degradation of the battery anode active material or lithium deposition may be caused by low temperature of the battery, high rate charge, long time cycle, and the like. Therefore, according to the priority of each characteristic parameter, each characteristic parameter is combined, and a multi-parameter fusion electrolyte leakage fault diagnosis method is proposed, as shown in fig. 5.
First, a diagnosis is made based on a change in the concentration of the gas signal, and once the gas concentration increases suddenly, it is determined that leakage of the battery electrolyte occurs. Secondly, under the condition that the gas concentration does not change obviously, the leakage diagnosis is carried out through electric and thermal signals. When the self-discharging degree of the battery is monitored to be deepened, judging whether the corresponding fault characteristic parameters are suddenly changed or not according to the working condition of the battery. Under the constant current charging condition, if the battery has the characteristic peak I electric signal characteristic parameter of the constant current charging section or the characteristic peak II1 electric signal characteristic parameter of the constant current charging section, the battery cathode active material is deteriorated, whether the thermal signal characteristic parameter or the characteristic peak II2 electric signal characteristic parameter is suddenly changed or not needs to be further determined, and if the thermal signal characteristic parameter or the characteristic peak II2 electric signal characteristic parameter is suddenly changed, the electrolyte of the battery is leaked. Similarly, under constant voltage charging or a static condition after charging, if an electrical signal characteristic parameter of the constant voltage charging section or an electrical signal characteristic parameter of the static stage after charging occurs, the battery suffers from electrolyte leakage failure. The leakage fault diagnosis method based on the electric-thermal-gas multi-parameter fusion is used for diagnosing according to the priority and the combination relation of the characteristic parameters, is more timely and accurate, and improves the reliability of electrolyte leakage fault diagnosis.
The above embodiments are only for illustrating the present invention and not for limiting the present invention, and various changes and modifications may be made by one skilled in the relevant art without departing from the spirit and scope of the present invention, so that all equivalent technical solutions fall within the scope of the present invention, which is defined by the claims.
What is not described in detail in this specification is prior art known to those skilled in the art.
Claims (8)
1. The multi-station leakage fault diagnosis method based on the electric-thermal-gas signal fusion is characterized by comprising the following steps of:
standing and charging and discharging test are carried out on the normal battery and the liquid leakage battery;
obtaining voltage and current signals of a battery in a constant-current charging stage, a constant-voltage charging stage and a standing stage after charging;
obtaining electric characteristic parameters of the battery and performing leakage fault diagnosis based on the electric signals;
acquiring temperature signals of a constant-current charging stage, a constant-voltage charging stage and a standing stage after charging;
obtaining thermal characteristic parameters of the battery and performing leakage fault diagnosis based on thermal signals;
acquiring volatile organic compound gas signals of the battery in a constant-current charging stage, a constant-voltage charging stage and a standing stage after charging;
obtaining gas characteristic parameters of the battery and performing leakage fault diagnosis based on gas signals;
integrating leakage fault parameters;
dividing effective action intervals of each fault characterization parameter and making diagnosis priority;
combining the electrical characteristic parameter, the thermal characteristic parameter and the gas characteristic parameter under multiple working conditions;
the electrolyte leakage fault diagnosis method with multiple parameter fusion is provided.
2. The multi-station leakage fault diagnosis method based on the electric-thermal-gas signal fusion according to claim 1, wherein the method for obtaining the electric characteristic parameters of the battery and performing the leakage fault diagnosis based on the electric signals is specifically as follows:
in the constant current charging stage, extracting peak characteristic parameters of the IC curves of the normal battery and the drain battery, and diagnosing according to the evolution rule along with the cycle times;
extracting characteristic parameters related to current in a constant voltage charging stage of the drain battery;
drawing standing voltage and normalized differential curve of a normal battery and a drain battery;
and extracting characteristic parameters related to the standing voltage of the drain battery.
3. The multi-condition leakage fault diagnosis method based on the electric-thermal-gas signal fusion according to claim 2, wherein the obtaining of the thermal characteristic parameters of the battery and the leakage fault diagnosis based on the thermal signal are specifically as follows:
according to a temperature-voltage variation curve (TV) and a differential curve (DTV) of a normal battery and a drain battery in a constant current charging stage in a cyclic aging process, obtaining characteristic parameters representing battery faults;
and combining the characteristic parameters related to the standing voltage of the liquid leakage battery, and diagnosing the liquid leakage fault according to the mutation of the characteristic parameters.
4. The multi-condition leakage fault diagnosis method based on the electric-thermal-gas signal fusion according to claim 1, wherein the obtaining of the gas characteristic parameters of the battery and the leakage fault diagnosis based on the gas signal are specifically:
and detecting volatile organic gas generated by leakage of the battery electrolyte through the gas sensor, comparing the volatile organic gas with the gas concentration change condition of a normal battery, and judging whether the battery electrolyte is leaked or not.
5. The multi-condition leakage fault diagnosis method based on 'electric-thermal-pneumatic' signal fusion according to claim 4, wherein,
and under two environment conditions of sealing and temperature control, acquiring a change curve of the gas concentration of the normal battery and the leakage battery along with time when the battery is in a standing working condition and a charging and discharging working condition, and diagnosing the leakage fault of the electrolyte according to the change of the gas concentration.
6. The multi-condition leakage fault diagnosis method based on 'electric-thermal-pneumatic' signal fusion according to claim 1, wherein the integrated leakage fault parameters are specifically:
integrating electrical signal parameters theta characterizing battery electrolyte leakage failure E Parameter θ of thermal signal T And the air signal parameter theta G Establishing a fault characteristic parameter set theta L ：
θ L ＝{θ E ，θ T ，θ G } (1)
7. The multi-condition leakage fault diagnosis method based on the electric-thermal-gas signal fusion according to claim 1, wherein the effective action interval of each fault characterization parameter is divided, and the diagnosis priority is formulated specifically as follows:
dividing the effective action interval of each fault characterization parameter according to the diagnosis time of each characteristic parameter, and formulating diagnosis priority, wherein the earlier the diagnosis time is, the higher the priority is;
the priority is sequentially from high to low: the characteristic peak I electric signal of the constant-current charging section, the characteristic peak II1 electric signal of the constant-current charging section, the thermal signal, the characteristic peak II2 electric signal of the constant-current charging section, the electric signal characteristic parameter of the constant-voltage charging section and the electric signal characteristic parameter of the standing stage after charging.
8. The multi-condition leakage fault diagnosis method based on 'electric-thermal-gas' signal fusion according to claim 1, wherein the multi-parameter fusion electrolyte leakage fault diagnosis method specifically comprises the following steps:
diagnosing based on the concentration change of the gas signal, and judging that the electrolyte of the battery leaks once the concentration of the gas increases suddenly;
under the condition that the gas concentration does not change obviously, the leakage diagnosis is carried out through an electric signal and a thermal signal: when the self-discharging degree of the battery is deepened, judging whether the corresponding fault characteristic parameters are suddenly changed or not according to the working condition of the battery;
under the constant current charging condition, if the battery has characteristic peak I electric signal characteristic parameters of a constant current charging section or characteristic peak II1 electric signal characteristic parameters of the constant current charging section, the battery cathode active material is deteriorated, whether the thermal signal characteristic parameters or characteristic peak II2 electric signal characteristic parameters are suddenly changed or not needs to be further determined, and if the thermal signal characteristic parameters or the characteristic peak II2 electric signal characteristic parameters are suddenly changed, the battery electrolyte leaks;
under constant voltage charging or a static condition after charging, if an electrical signal characteristic parameter of a constant voltage charging section or an electrical signal characteristic parameter of a static stage after charging occurs, an electrolyte leakage fault occurs in the battery.
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| CN116572747A (en) * | 2023-07-13 | 2023-08-11 | 宁德时代新能源科技股份有限公司 | Battery fault detection method, device, computer equipment and storage medium |
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| CN116572747B (en) * | 2023-07-13 | 2023-12-22 | 宁德时代新能源科技股份有限公司 | Battery fault detection method, device, computer equipment and storage medium |
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