CN114636930A - Battery self-discharge fault early warning method - Google Patents
Battery self-discharge fault early warning method Download PDFInfo
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Abstract
The invention provides a battery self-discharge fault early warning method, and belongs to the technical field of batteries. The method comprises two judgment conditions, wherein the self-discharge fault of the battery is judged as long as one of the two judgment conditions is met; wherein, the judgment condition is as follows: when the delta SOC value of the battery is larger than or equal to the delta SOC trigger threshold, the delta SOC value of the battery is in an ascending trend within a first set time before reaching the delta SOC trigger threshold; the second judgment condition is as follows: and under the condition that the low-voltage battery cell proportion value is larger than or equal to the low-voltage battery cell proportion triggering threshold value, the low-voltage battery cell proportion value is in an ascending trend within a second set time before the low-voltage battery cell proportion triggering threshold value is reached. According to the method, on the basis of carrying out primary fault judgment by utilizing the low-voltage battery cell ratio and the delta SOC value, further fault identification is carried out based on the change trend in the corresponding set time before the low-voltage battery cell ratio and the delta SOC value reach the corresponding trigger threshold, so that the fault identification accuracy is improved, and the fault identification result has certain advancement.
Description
Technical Field
The invention relates to a battery self-discharge fault early warning method, and belongs to the technical field of batteries.
Background
At present, the self-discharge fault early warning method of the battery mainly comprises two methods: one method is to measure the self-discharge of the battery by an open-circuit voltage attenuation rate measuring method, but the open-circuit voltage attenuation rate measuring method is to estimate the self-discharge result of the battery based on a fitted OCV (open-circuit voltage) -SOC relation, the estimation accuracy of the self-discharge result of the battery depends on an experimental simulation result, and the self-discharge result of the battery is easily influenced by working conditions such as temperature and multiplying power, and is difficult to calculate accurately; one is to perform battery self-discharge measurement by establishing a non-linear model (for example, a fourier fitting model) of discharge voltage and battery capacity through a non-linear fitting method, and although the accuracy of the self-discharge measurement model can be improved, the self-discharge fault identification is performed simply according to the estimated self-discharge rate, so that the accuracy is not sufficient, and the fault severity is difficult to define.
Disclosure of Invention
The invention aims to provide a battery self-discharge fault early warning method, which is used for solving the problem that the battery self-discharge fault recognition accuracy is not enough only by utilizing a self-discharge rate estimated value in the prior art.
In order to achieve the above object, the present invention provides a battery self-discharge fault early warning method, which includes two judgment conditions, wherein a battery is judged to have a self-discharge fault as long as one of the two judgment conditions is satisfied; wherein, the judgment condition is as follows: under the condition that the delta SOC value of the battery is larger than or equal to the delta SOC trigger threshold, the delta SOC value of the battery is in an ascending trend within a first set time before reaching the delta SOC trigger threshold; the second judgment condition is as follows: under the condition that the low-voltage battery cell proportion value is larger than or equal to the low-voltage battery cell proportion trigger threshold value, the low-voltage battery cell proportion value is in an ascending trend within a second set time before the low-voltage battery cell proportion trigger threshold value is reached;
determining a delta SOC value of the battery according to the highest voltage and the lowest voltage of the single body in the battery;
the low-voltage battery cell ratio is obtained through the following steps: calculating the frequency of low-voltage states of each single battery cell in the battery within a third set time based on the voltage data of each single battery cell reported by the battery in real time, taking the battery cell with the highest frequency of low-voltage states as a low-voltage battery cell, and calculating the ratio of the frequency of low-voltage states of the low-voltage battery cell within the third set time to the total frequency of low-voltage states of all the single battery cells within the battery as a low-voltage battery cell ratio; when the voltage of the single battery cell is smaller than the set voltage value, the single battery cell is in a low-voltage state.
The invention has the beneficial effects that: (1) the low-voltage cell ratio and the delta SOC value (delta SOC value for short) of the battery are used as key indexes for identifying the self-discharge fault of the battery, on the basis of carrying out primary fault judgment by using the low-voltage cell ratio and the delta SOC value, the fault is further identified based on the variation trend in corresponding set time before the low-voltage cell ratio and the delta SOC value reach corresponding trigger thresholds, the fault identification accuracy is improved, and the problem that the self-discharge fault identification accuracy is insufficient only by using the self-discharge rate measurement value in the prior art is solved; the fault recognition based on the change trend of the key indexes ensures that the fault recognition result has certain advance, can find the fault problem more than 10 days in advance, and improves the coverage of fault recognition on the premise of ensuring the recognition accuracy; (2) carry out fault identification from 2 dimensions of low voltage electricity core ratio and delta SOC value, the recognition result of 2 dimensions plays the effect of mutual complementation, has further improved model identification's degree of accuracy and coverage.
Further, in the above method, the method further includes a step of performing a grading pre-warning on the self-discharge fault of the battery, where the grading pre-warning includes: when the judgment condition is met, judging that the self-discharge fault of the battery is a serious fault; and when the second judgment condition is met, judging whether the delta SOC value is larger than or equal to the delta SOC trigger threshold, if so, judging that the self-discharge fault of the battery is an important fault, and otherwise, judging that the self-discharge fault of the battery is a common fault.
The beneficial effects of doing so are: and fault early warning grade division is carried out, so that subsequent application management is facilitated.
Further, in the method, the delta SOC value of the battery is calculated according to an established delta SOC nonlinear index calculation model by combining the highest voltage and the lowest voltage of the cell in the battery, and the established delta SOC nonlinear index calculation model is established by using a nonlinear index algorithm based on SOC _ OCV experimental data of different battery materials.
The beneficial effects of doing so are: the delta SOC nonlinear index calculation model is established by adopting a nonlinear index algorithm, so that the simplicity and universality of delta SOC calculation application can be improved.
Further, in the above method, when the battery material is a lithium iron phosphate battery, the Δ SOC nonlinear index calculation model is: and A is the maximum voltage of the monomer A and A is the minimum voltage of the monomer B, wherein A and B are model coefficients obtained by fitting.
Further, in the method, whether the low-voltage battery cell ratio value and the delta SOC value are in an ascending trend within corresponding set time is judged by using a difference function and a median filter algorithm.
Further, in the above method, the number of times that each cell in the battery has a low voltage state is obtained based on statistics of effective data, where the effective data is: and the voltage data of each single battery cell is reported by the battery in real time when the battery is in a driving state and under a stable current.
The beneficial effects of doing so are: the selection of the low-voltage battery core and the calculation of the low-voltage battery core ratio are carried out based on the statistical result of the effective data, so that the calculation of the low-voltage battery core ratio is more accurate, and the accuracy of the follow-up fault identification result is further ensured.
Further, in the above method, multiple sets of the low-voltage battery cell proportion trigger threshold and the Δ SOC trigger threshold may be established according to factors affecting the self-discharge rate of the battery, where the factors affecting the self-discharge rate of the battery include a product type, a temperature, and an operation condition.
The beneficial effects of doing so are: the low-voltage battery cell proportion trigger threshold and the delta SOC trigger threshold are established in groups, so that the objectivity of setting the trigger threshold can be improved, and the fault identification accuracy is further improved.
Further, in the method, the low-voltage battery ratio trigger threshold and the Δ SOC trigger threshold are updated periodically.
The beneficial effects of doing so are: the trigger threshold value is updated regularly, so that the fault identification accuracy can be further improved.
Drawings
FIG. 1 is a graph illustrating the trend of the change in key indicators of a self-discharging failed vehicle battery in an embodiment of the method of the present invention;
FIG. 2 is a flow chart of a battery self-discharge fault pre-warning method in an embodiment of the method of the present invention;
FIG. 3 is a diagram illustrating a variation trend of Δ SOC values according to an embodiment of the method of the present invention;
fig. 4 is a graph of a variation trend of the low-voltage cell percentage value in the embodiment of the method of the present invention.
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.
The method comprises the following steps:
from the self-discharge failure mechanism, the self-discharge behavior of the battery is shown in that the discharge rate of one or more battery cores is large, the difference of delta SOC is large, and the problems of low-voltage alarm, SOC jump, vehicle anchorage and the like are easily caused in the running process of a vehicle due to the capacity loss of spontaneous chemical side reactions in the battery, the micro short-circuit loss in the battery cores, the defect of diaphragms and the like.
Based on the single voltage data of the historical self-discharge fault vehicle battery, the key factors capable of identifying the self-discharge fault of the battery are researched by using a coaxial multi-index time series change trend method to obtain a key index change trend graph shown in fig. 1, and research shows that: before the self-discharge fault occurs, the battery shows the phenomenon that the low-voltage battery cell ratio and the delta SOC value are increased rapidly in a short period, and the delta SOC value change of the battery has certain hysteresis. The low-voltage battery core is the single battery core with the largest number of times of low-voltage states in the set time, the low-voltage battery core proportion value is the ratio of the number of times of low-voltage states of the low-voltage battery core in the set time to the total number of times of low-voltage states of all the single battery cores in the battery, and the delta SOC value of the battery is determined according to the highest voltage and the lowest voltage of the single battery in the battery.
Therefore, based on the above research results, in this embodiment, two indexes, namely, the low-voltage cell ratio and the Δ SOC value of the battery (referred to as Δ SOC value for short), are used as key indexes capable of identifying the self-discharge fault of the battery, and a battery self-discharge fault early-warning method based on the low-voltage cell ratio and the variation trend of the Δ SOC value is provided from two dimensions of the low-voltage cell ratio and the Δ SOC value, so as to identify the self-discharge fault of the battery in advance.
The method for early warning of self-discharge fault of battery in this embodiment is shown in fig. 2, and includes the following steps:
(1) acquiring voltage data of each single battery cell reported by a battery in real time;
(2) screening data in a driving state and a stable current from voltage data of each single battery cell reported by the battery in real time to serve as effective data, counting the times of low-voltage states of each single battery cell in the battery within a third set time (namely set time T3, for example, the current day is taken as set time T3) based on the effective data, taking the battery cell with the most times of low-voltage states as a low-voltage battery cell, and calculating the ratio of the times of low-voltage states of the low-voltage battery cell within the set time T3 to the total times of low-voltage states of all the single battery cells in the battery to serve as a low-voltage battery cell ratio; when the voltage of the single battery cell is smaller than the set voltage value, the single battery cell is in a low-voltage state.
In this embodiment, the stable current refers to a current greater than 5A, so that after voltage data of each single cell core reported by the battery in real time is obtained, the voltage data is screened, the voltage data meeting the driving state and the current greater than 5A at the same time is used as effective data, and selection of the low-voltage cell core and calculation of the low-voltage cell core proportion are performed based on a statistical result of the effective data, so that accuracy of a calculation result of the low-voltage cell core proportion can be improved, and accuracy of subsequent fault identification is further ensured; as another embodiment, the number of times that each single battery cell in the battery appears in a low-voltage state within a third set time may also be obtained by directly counting the voltage data of each single battery cell reported by the battery in real time.
(3) Calculating to obtain a delta SOC value of the battery according to the established delta SOC nonlinear index calculation model by combining the highest voltage of the monomer and the lowest voltage of the monomer in the battery;
in the embodiment, the method is combined with SOC _ OCV experimental data of different battery materials, and a delta SOC nonlinear index calculation model of different battery materials is established by utilizing a nonlinear index algorithm, so that the simplicity and universality of delta SOC calculation application can be improved; taking a lithium iron phosphate battery as an example, a nonlinear index calculation model of the lithium iron phosphate battery delta SOC is as follows: a is the maximum voltage of the monomer A is the minimum voltage of the monomer A, and B is the model coefficient obtained by least square fitting based on experimental data.
As another embodiment, a Δ SOC nonlinear calculation model of different battery materials may be established by using other existing nonlinear fitting algorithms based on SOC _ OCV experimental data of different battery materials, and then a Δ SOC value may be calculated based on the established Δ SOC nonlinear calculation model.
(4) When the delta SOC value of the battery is larger than or equal to the delta SOC trigger threshold value, if the delta SOC value is in an ascending trend within a set time T1 before reaching the delta SOC trigger threshold value, judging that the battery has a self-discharge fault; or when the low-voltage battery cell proportion value is larger than or equal to the low-voltage battery cell proportion triggering threshold, if the low-voltage battery cell proportion value is in an ascending trend within the set time T2 before the low-voltage battery cell proportion value reaches the low-voltage battery cell proportion triggering threshold, the battery is judged to have a self-discharge fault.
That is to say, the method for early warning a self-discharge fault of a battery according to this embodiment first determines whether the Δ SOC value and the low-voltage cell ratio of the battery reach the corresponding trigger threshold, and continues to determine whether the Δ SOC value and the low-voltage cell ratio of the battery are in an ascending trend within the corresponding set time when the Δ SOC value and the low-voltage cell ratio of the battery reach the corresponding trigger threshold, and only when the Δ SOC value and the low-voltage cell ratio of the battery both reach the corresponding trigger threshold and are in an ascending trend within the corresponding set time, it is determined that the self-discharge fault of the battery occurs, where reaching the corresponding trigger threshold is a precondition for determining the ascending trend.
For convenience of description, the first judgment condition "when the Δ SOC value of the battery is greater than or equal to the Δ SOC trigger threshold, the Δ SOC value is in an increasing trend within a set time T1 before reaching the Δ SOC trigger threshold" is used, and the second judgment condition "when the low-voltage cell occupancy ratio is greater than or equal to the low-voltage cell occupancy trigger threshold, the low-voltage cell occupancy ratio is in an increasing trend within a second set time before reaching the low-voltage cell occupancy trigger threshold" is used.
In this embodiment, still carry out hierarchical early warning to battery self discharge trouble, divide self discharge trouble early warning grade into serious failure, important trouble and general trouble 3 grades, the severity is: critical failure > general failure. When the judgment condition is met, judging that the self-discharge fault of the battery is a serious fault; and when the second judgment condition is met, judging whether the delta SOC value is greater than or equal to the delta SOC trigger threshold, if so, judging that the self-discharge fault of the battery is an important fault, otherwise, judging that the self-discharge fault of the battery is a common fault.
The specific values of the first, second and third setting times and the number of the divided fault early warning levels can be set according to actual conditions, for example, the first and second setting times can be set to a short period of time before reaching the corresponding trigger thresholds.
In the embodiment, whether the low-voltage battery cell ratio and the delta SOC value are in an ascending trend within corresponding set time is judged by using a difference function and a median filtering algorithm; and determining a low-voltage battery cell ratio trigger threshold and a delta SOC trigger threshold according to the self-discharge case vehicle failure mode and the experimental result.
As other embodiments, whether the low-voltage battery cell ratio and the Δ SOC value rise within the corresponding set time may also be implemented by using other filtering algorithms; in addition, by analyzing factors (such as product types, temperatures, operation conditions and the like) affecting the self-discharge rate of the battery, multiple groups of low-voltage cell proportion triggering threshold values, multiple groups of delta SOC triggering threshold values, or multiple groups of low-voltage cell proportion triggering threshold values and delta SOC triggering threshold values are established according to the factors affecting the self-discharge rate of the battery, and the triggering threshold values are periodically updated according to actual conditions (for example, the triggering threshold values are periodically updated by using the obtained latest data), so that the objectivity of setting the triggering threshold values is improved, and the fault identification accuracy and the fault identification number are further improved, for example: the trigger threshold corresponding to each product type may be established, or the trigger threshold corresponding to each temperature may be established, or the trigger threshold under each operation condition may be established, or the trigger threshold may also be established by simultaneously combining a plurality of influence factors, for example, the trigger threshold may be established by simultaneously combining two influence factors of the product type and the temperature, or by simultaneously combining three influence factors of the product type, the temperature, and the operation condition. When the device is actually used, the corresponding trigger threshold value is selected according to the actual situation.
Fig. 3 and 4 are graphs showing the change trend of key indexes of identified vehicles (hereinafter referred to as problem vehicles) with a battery self-discharge fault problem, where, taking a fault identification result in a period of time as an example, there are 8 vehicles (hereinafter referred to as problem vehicles) with a battery self-discharge fault problem identified based on a Δ SOC value and a Δ SOC value change trend, there are 5 vehicles with a problem identified based on a low-voltage cell occupancy value and a low-voltage cell occupancy value change trend, and there are 8 vehicles with a problem identified altogether, where 5 vehicles with a serious fault are generally 3 vehicles with a serious fault. Through data verification, the battery self-discharge fault early warning method can be used for identifying faults more than 10 days in advance, and the fault identification result accuracy is more than 90%.
In summary, the embodiment provides a battery self-discharge fault early warning method based on the variation trend of the key indexes of the battery from two dimensions of the low-voltage cell ratio and the Δ SOC value, and has the following advantages:
(1) the method comprises the steps that a low-voltage battery cell ratio and a delta SOC value are used as key indexes for identifying the self-discharge fault of the battery, on the basis of primary fault judgment by using the low-voltage battery cell ratio and the delta SOC value, a difference function and a filtering algorithm are adopted to evaluate the change trend of the key indexes in a short period, and further fault identification is carried out based on the change trend in the short period before the low-voltage battery cell ratio and the delta SOC value reach corresponding trigger thresholds, so that the fault identification accuracy is improved, and the problem that the self-discharge fault identification accuracy of the battery is insufficient only by using a self-discharge rate measurement value in the prior art is solved; the fault recognition based on the change trend of the key indexes ensures that the fault recognition result has certain advance, can find the fault problem more than 10 days in advance, and improves the coverage of fault recognition on the premise of ensuring the recognition accuracy;
(2) fitting the SOC _ OCV curve by adopting a nonlinear exponential algorithm, establishing a nonlinear exponential calculation model of the delta SOC, and improving the simplicity and universality of the delta SOC calculation application;
(3) fault identification is carried out from 2 dimensions of the low-voltage battery cell ratio and the delta SOC value, and the identification results of the 2 dimensions play a role of mutual complementation, so that the accuracy and the coverage of model identification are further improved;
(4) and fault early warning grade division is carried out, so that subsequent application management is facilitated.
The battery self-discharge fault early warning method is suitable for various battery material types such as ternary batteries of new energy vehicles and lithium iron phosphate batteries, is not influenced by the types of pure electric products, the types of batteries and operation conditions, and can be applied to all new energy commercial vehicles and passenger vehicles in the market in an expanded mode.
Claims (8)
1. The battery self-discharge fault early warning method is characterized by comprising two judgment conditions, wherein the self-discharge fault of the battery is judged as long as one of the two judgment conditions is met; wherein, the judgment condition is as follows: under the condition that the delta SOC value of the battery is larger than or equal to the delta SOC trigger threshold, the delta SOC value of the battery is in an ascending trend within a first set time before reaching the delta SOC trigger threshold; the second judgment condition is as follows: under the condition that the low-voltage cell proportion value is larger than or equal to the low-voltage cell proportion trigger threshold value, the low-voltage cell proportion value is in an ascending trend within a second set time before reaching the low-voltage cell proportion trigger threshold value;
determining a delta SOC value of the battery according to the highest voltage and the lowest voltage of the single body in the battery;
the low-voltage battery cell ratio is obtained through the following steps: calculating the frequency of low-voltage states of each single battery cell in the battery within a third set time based on the voltage data of each single battery cell reported by the battery in real time, taking the battery cell with the highest frequency of low-voltage states as a low-voltage battery cell, and calculating the ratio of the frequency of low-voltage states of the low-voltage battery cell within the third set time to the total frequency of low-voltage states of all the single battery cells within the battery as a low-voltage battery cell ratio; when the voltage of the single battery cell is smaller than the set voltage value, the single battery cell is in a low-voltage state.
2. The battery self-discharge fault early warning method according to claim 1, further comprising the step of performing a hierarchical early warning on the battery self-discharge fault, wherein the hierarchical early warning comprises: when the judgment condition is met, judging that the self-discharge fault of the battery is a serious fault; and when the second judgment condition is met, judging whether the delta SOC value is larger than or equal to the delta SOC trigger threshold, if so, judging that the self-discharge fault of the battery is an important fault, and otherwise, judging that the self-discharge fault of the battery is a common fault.
3. The battery self-discharge fault early warning method according to claim 1 or 2, characterized in that a delta SOC value of the battery is calculated according to an established delta SOC nonlinear index calculation model in combination with a highest cell voltage and a lowest cell voltage in the battery, and the established delta SOC nonlinear index calculation model is established by a nonlinear index algorithm based on SOC _ OCV experimental data of different battery materials.
4. The battery self-discharge fault early warning method according to claim 3, wherein when the battery material is a lithium iron phosphate battery, the Δ SOC nonlinear index calculation model is as follows: and A is the maximum voltage of the monomer A and A is the minimum voltage of the monomer B, wherein A and B are model coefficients obtained by fitting.
5. The battery self-discharge fault early warning method according to claim 1 or 2, characterized in that whether the low-voltage cell fraction value and the delta SOC value are in an ascending trend within a corresponding set time is judged by using a difference function and a median filter algorithm.
6. The battery self-discharge fault early-warning method according to claim 1 or 2, wherein the number of times that each single battery cell in the battery appears in a low-voltage state is obtained based on statistics of valid data, and the valid data is as follows: and the voltage data of each single battery cell is reported by the battery in real time when the battery is in a driving state and under a stable current.
7. The battery self-discharge fault early warning method according to claim 1 or 2, wherein the low-voltage cell percentage trigger threshold and the delta SOC trigger threshold are set up in multiple groups according to factors affecting a self-discharge rate of the battery, wherein the factors affecting the self-discharge rate of the battery include a product type, a temperature and an operation condition.
8. The battery self-discharge fault early warning method according to claim 7, wherein the low-voltage cell duty ratio trigger threshold and the delta SOC trigger threshold are updated periodically.
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