CN116783495A - Fault detection method, device, battery management system and storage medium - Google Patents

Fault detection method, device, battery management system and storage medium Download PDF

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Publication number
CN116783495A
CN116783495A CN202180082572.7A CN202180082572A CN116783495A CN 116783495 A CN116783495 A CN 116783495A CN 202180082572 A CN202180082572 A CN 202180082572A CN 116783495 A CN116783495 A CN 116783495A
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fault
integral
sampling period
integration
sampling
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李佳莹
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Contemporary Amperex Technology Co Ltd
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Contemporary Amperex Technology Co Ltd
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere

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Abstract

The embodiment of the application provides a fault detection method, a fault detection device, a battery management system and a storage medium. The fault detection method comprises the following steps: acquiring a sampling value of a fault parameter of the battery cell in a sampling period; integrating the sampling value in the integration time length to obtain an integration value corresponding to the ith sampling period; wherein i is an integer, i is more than or equal to 1 and less than or equal to M, M corresponds to the type of the fault parameter, and M is more than or equal to 1; the starting point of the integration time length is the starting point of the sampling period, and the ending point of the integration time length is the ending point of the ith sampling period starting from the starting point; when the integral value corresponding to the ith sampling period is larger than or equal to a preset integral threshold value corresponding to the fault parameter, determining that the battery cell has faults, and timely detecting the faults is facilitated, so that risks of untimely alarm are avoided.

Description

Fault detection method, device, battery management system and storage medium Technical Field
The present application relates to the field of battery technologies, and in particular, to a fault detection method, a fault detection device, a battery management system, and a storage medium.
Background
When the battery management system (Battery Management System, BMS for short) detects that the battery core fails, corresponding diagnosis needs to be made in time, otherwise, safety accidents such as fire and explosion are extremely easy to cause. For fault detection, the following methods are generally adopted: when a decision item such as the present current, the present temperature, the present voltage, etc. exceeds a corresponding threshold (condition 1) and the duration exceeds a preset diagnostic decision duration (condition 2), a fault is set as shown in table 1:
TABLE 1
Failure of Condition 1 Condition 2
Battery overcurrent fault Current I>200(A) Duration t>10s
Over-temperature fault of battery Current temperature T>65(DegC) Duration t>5s
Overvoltage fault of battery Current voltage V>4.0(V) Duration t>15s
For faults of the same type, the diagnosis judging time length is fixed no matter how severe, and the risk of untimely alarm is easily brought.
Disclosure of Invention
In view of the above problems, the present application provides a fault detection method, a fault detection device, a battery management system and a storage medium, which can detect faults in time, and are beneficial to avoiding risks of untimely alarm.
In a first aspect, the present application provides a fault detection method, including: applied to a battery management system BMS, comprising: acquiring a sampling value of a fault parameter of the battery cell in a sampling period; integrating the sampling value in the integration time length to obtain an integration value corresponding to the ith sampling period; wherein i is an integer, i is more than or equal to 1 and less than or equal to M, M corresponds to the type of the fault parameter, and M is more than or equal to 1; the starting point of the integration time length is the starting point of the sampling period, and the ending point of the integration time length is the ending point of the ith sampling period starting from the starting point; and when the integral value corresponding to the ith sampling period is larger than or equal to a preset integral threshold value corresponding to the fault parameter, determining that the battery cell has faults.
In the technical scheme of the embodiment of the application, the starting point of the sampling period is taken as the starting point of the integration time length, the ending point of the ith sampling period started by the starting point is taken as the ending point of the integration time length, and the sampling value in the integration time length is integrated to obtain the integral value corresponding to the ith sampling period, wherein the integral value is larger than or equal to the preset integral threshold value corresponding to the fault parameter, so that the possible fault of the battery cell is indicated when the integral value is overlarge within a period of time. When the integral value corresponding to the ith sampling period is greater than or equal to a preset integral threshold value corresponding to the fault parameter, determining that the battery cell has faults, and indicating that the time point when the integral value is greater than or equal to the preset integral threshold value corresponding to the fault parameter is the time point when the fault is set, namely, the embodiment of the application does not take the fixed diagnosis judgment time length as a judgment standard when the fault is set, thereby avoiding the risk of untimely alarm easily caused when the diagnosis judgment time length is fixed and being beneficial to timely detecting the fault.
In some embodiments, the integrating the sampling value in the integration period to obtain an integrated value corresponding to the ith sampling period includes: integrating the sampling value in the integration time length according to the integration coefficient corresponding to the fault parameter to obtain an integration value corresponding to the ith sampling period; the integral coefficient is used for representing the influence degree of the fault parameter on the battery cell.
According to the technical scheme, the integrated value can be obtained by combining the influence degree of the fault parameters on the battery cell, so that the setting time of the fault with the larger influence degree on the battery cell is shortened, namely the fault with the larger influence degree on the battery cell is detected quickly.
In some embodiments, the integral coefficient is calculated by the following formula: k=x/X max Wherein K is the integral coefficient, X is the sampling value, X max And a preset sampling threshold value corresponding to the fault parameter is set.
In the technical scheme of the embodiment of the application, the integral coefficient is obtained by calculating the ratio of the sampling value to the sampling threshold value, and the sampling value can be different in different sampling periods, so that the integral coefficient can be dynamically changed in different sampling periods, and the influence degree of the current sampling value of the fault parameter on the battery cell can be reflected by the integral coefficient. The greater K indicates that the greater the influence degree of the fault parameters on the battery cell is, the greater K also enables the greater the integral value, so that the integral value can be rapidly greater than or equal to a preset integral threshold value along with the increase of the integral duration, the battery cell fault can be detected, and the rapid detection of the fault with the greater influence degree on the battery cell is facilitated.
In some embodiments, the integrating the sampling value in the integration duration according to the integration coefficient corresponding to the fault parameter to obtain an integrated value corresponding to the ith sampling period includes: and calculating to obtain an integrated value corresponding to the ith sampling period by the following formula:
Y＝∫K*X N dt
wherein Y is the integral value, K is the integral coefficient, X is the sampling value, and N is the order corresponding to the fault parameter.
According to the technical scheme, the integral value corresponding to the ith sampling period is obtained through the integral formula, so that the integral value can be accurately, quickly and reasonably calculated.
In some embodiments, the preset integral threshold corresponding to the fault parameter includes a plurality of integral thresholds; and when the integral value corresponding to the ith sampling period is greater than or equal to a preset integral threshold value corresponding to the fault parameter, determining that the battery cell has a fault comprises: when the integral value corresponding to the ith sampling period is greater than or equal to k integral thresholds in the multiple integral thresholds, acquiring a fault grade corresponding to the largest integral threshold in the k integral thresholds, and determining the acquired fault grade as the fault grade of the fault of the battery cell; wherein k is an integer greater than or equal to 1.
According to the technical scheme, the faults of different levels can be embodied by configuring the integration thresholds, so that fault responses of different degrees can be realized, and the faults of the same type can be conveniently pre-warned of different degrees.
In some embodiments, M.ltoreq.1000.
In the technical scheme of the embodiment of the application, M is more than or equal to 1 and less than or equal to 1000, so that the calculation can be performed based on the sampling value sampled in one or more complete sampling periods, and the effectiveness of integration is ensured. M is less than or equal to 1000, namely the integral time length is not too long, the integral value is ensured to exceed the integral threshold value in a short time, and the fault detection accuracy is improved.
In some embodiments, after integrating the sampling value in the integration period to obtain an integrated value corresponding to the ith sampling period, the method further includes: integrating a preset sampling threshold value corresponding to the fault parameter in the integration time length to obtain a sampling threshold value integrated value corresponding to the ith sampling period; calculating an integral difference value between an integral value corresponding to the ith sampling period and a sampling threshold integral value corresponding to the ith sampling period; and when the integral value corresponding to the ith sampling period is greater than or equal to a preset integral threshold value corresponding to the fault parameter, determining that the battery cell has a fault comprises: and when the integral difference value is larger than or equal to a preset integral difference value threshold value corresponding to the fault parameter, determining that the battery cell has a fault.
In the technical scheme of the embodiment of the application, the integral difference value can reflect the possible fault risk caused by the fact that the sampling value exceeds the preset sampling threshold value. And the integral difference value can be positive or negative, and the positive difference value and the negative difference value are considered, so that the fault can be set timely when the sampling value fluctuates up and down at a preset sampling threshold value, and the problem that the fault is set untimely because the fault is set continuously beyond a certain threshold value for a period of time in the prior art is avoided.
In a second aspect, the present application provides a fault detection device, comprising: the acquisition module is used for acquiring sampling values of fault parameters of the battery cell in a sampling period; the integration module is used for integrating the sampling value in the integration time length to obtain an integration value corresponding to the ith sampling period; wherein i is an integer, i is more than or equal to 1 and less than or equal to M, M corresponds to the type of the fault parameter, and M is more than or equal to 1; the starting point of the integration time length is the starting point of the sampling period, and the ending point of the integration time length is the ending point of the ith sampling period starting from the starting point; and the determining module is used for determining that the battery cell fails when the integral value corresponding to the ith sampling period is larger than or equal to a preset integral threshold value corresponding to the fault parameter.
In a third aspect, the present application provides a battery management system BMS, comprising: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the fault detection method described above.
In a fourth aspect, the present application provides a computer readable storage medium storing a computer program which when executed by a processor implements the fault detection method described above.
The foregoing description is only an overview of the present application, and is intended to be implemented in accordance with the teachings of the present application in order that the same may be more clearly understood and to make the same and other objects, features and advantages of the present application more readily apparent.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments of the present application will be briefly described below, and it is obvious that the drawings described below are only some embodiments of the present application, and other drawings may be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a fault detection method according to some embodiments of the present application;
FIG. 2 is a schematic diagram of the detection result of an overcurrent fault in a general scheme according to some embodiments of the present application;
FIG. 3 is a schematic diagram illustrating detection results of detecting an overcurrent fault by an integrating method according to some embodiments of the present application;
FIG. 4 is a schematic diagram of detection results of detecting an overcurrent fault by adopting a general scheme under three scenes of different currents according to some embodiments of the application;
FIG. 5 is a schematic diagram of detection results of detecting an overcurrent fault in an integrated manner under three scenarios with different currents according to some embodiments of the present application;
FIG. 6 is a schematic diagram of a fault detection device according to some embodiments of the present application;
fig. 7 is a schematic structural view of a BMS according to some embodiments of the present application.
Detailed Description
Embodiments of the present application are described in further detail below with reference to the accompanying drawings and examples. The following detailed description of the embodiments and the accompanying drawings are provided to illustrate the principles of the application and are not intended to limit the scope of the application, i.e., the application is not limited to the embodiments described.
In the description of the present application, it is to be noted that, unless otherwise indicated, the meaning of "plurality" is two or more; the terms "upper," "lower," "left," "right," "inner," "outer," and the like are merely used for convenience in describing the present application and to simplify the description, and do not denote or imply that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus are not to be construed as limiting the present application. Furthermore, the terms "first," "second," "third," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. The "vertical" is not strictly vertical but is within the allowable error range. "parallel" is not strictly parallel but is within the tolerance of the error.
The directional terms appearing in the following description are those directions shown in the drawings and do not limit the specific structure of the application. In the description of the present application, it should also be noted that, unless explicitly specified and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be either fixedly connected, detachably connected, or integrally connected, for example; can be directly connected or indirectly connected through an intermediate medium. The specific meaning of the above terms in the present application can be understood as appropriate by those of ordinary skill in the art.
Currently, the application of power batteries is more widespread from the development of market situation. The power battery is not only applied to energy storage power supply systems such as hydraulic power, firepower, wind power and solar power stations, but also widely applied to electric vehicles such as electric bicycles, electric motorcycles, electric automobiles, and the like, and a plurality of fields such as military equipment, aerospace, and the like. With the continuous expansion of the application field of the power battery, the market demand of the power battery is also continuously expanding. The battery core in the power battery plays a key role in the normal operation of the power battery, so that the fault detection of the battery core is particularly important.
The inventor notes that the current solutions adopted for fault detection of the battery cells are as follows: when a decision item such as the present current, the present temperature, the present voltage, etc. exceeds a corresponding preset threshold value and the duration exceeds a preset diagnostic decision period, a fault is set, which may be referred to above in table 1. However, if frequent jitter conditions are encountered, there may be a risk of false negatives (risk 1). And for the same type of faults, the diagnosis decision duration is fixed, no matter how severe, which brings the risk of not giving an alarm of the fault in time (risk 2).
For the risks 1 and 2, the inventor also found that one optimization direction for the risks 1 is to shorten the diagnosis decision time, but this brings about the problem of frequent or misplacement of faults; one optimization direction aiming at the risk 2 is to divide the faults into multiple stages, and different thresholds and diagnosis judging time periods are matched, but the risk can be reduced to a certain extent, and then the faults are still difficult to be covered by the classification, so that the problem that the fault alarm is not timely enough can not be fundamentally solved.
Based on the above consideration, in order to avoid the above risks 1 and 2, the inventors have conducted intensive studies and devised a fault detection method for detecting that a cell fails by integrating sampling values of fault parameters for a certain integration period, when the integration value is greater than or equal to a preset integration threshold value. That is, the embodiment of the application does not take the fixed diagnosis and judgment time length as the judgment standard when the fault is set, thereby avoiding the risk of untimely alarm easily caused when the diagnosis and judgment time length is fixed and being beneficial to timely detecting the fault.
The fault detection method disclosed by the embodiment of the application is applied to a Battery Management System (BMS), and the BMS is a set of control system for protecting the use safety of the power battery, monitors the use state of the battery at any time and provides guarantee for the use safety of the new energy vehicle.
According to some embodiments of the present application, a schematic flow chart of a fault detection method may refer to fig. 1, including:
step 101: acquiring a sampling value of a fault parameter of the battery cell in a sampling period;
step 102: integrating the sampling value in the integration time length to obtain an integration value corresponding to the ith sampling period;
step 103: when the integral value corresponding to the ith sampling period is greater than or equal to a preset integral threshold value corresponding to the fault parameter, determining that the battery cell fails;
in step 101, the BMS may obtain a sampling value of a fault parameter of the battery cell in a sampling period; the sampling period may be a sampling period preset according to actual needs, for example, may be set to 10ms. The fault parameters may be parameters for determining whether the power core is faulty, such as may include, but are not limited to: current, voltage, temperature; the fault parameter of current can be used for judging whether the power core has an overcurrent fault, the fault parameter of voltage can be used for judging whether the power core has an overvoltage fault, and the fault parameter of temperature can be used for judging whether the power core has an overtemperature fault. Correspondingly, the sampled values of the fault parameters may include, but are not limited to: the sampled values of the current, voltage, temperature and temperature are the current value, the voltage value and the temperature value.
The sampling value of the fault parameters of the battery cell can be obtained by sampling by a sampling device, the sampling device can periodically collect the fault parameters of the battery cell according to a preset sampling period and send the sampling value obtained by sampling to the BMS, so that the BMS can obtain the sampling value of the fault parameters of the battery cell in the sampling period. In a specific implementation, the BMS may obtain a sampled value of the fault parameter of the battery cell in each sampling period.
In step 102, i is an integer, i is not less than 1 and not more than M, M corresponds to the type of fault parameters, and M is not less than 1; the start point of the integration period is the start point of the sampling period, and the end point of the integration period is the end point of the ith sampling period starting from the start point. The fault parameters may be, for example, current, voltage, and temperature, and the M values corresponding to the different fault parameters may be the same or different according to actual needs. The duration of the M sampling periods can be tolerance duration corresponding to the fault parameters, and the tolerance duration can be fault tolerance time capable of maintaining safety of the battery cell under the current dangerous working condition. That is, different kinds of fault parameters each correspond to a respective tolerance period.
The BMS may integrate the sampling values in the integration period with a start point of each sampling period as a start point of the integration period and an end point of the i-th sampling period from the start point as an end point of the integration period, to obtain an integrated value corresponding to the i-th sampling period. That is, the starting point of each sampling period can be used as the starting point of the integration time length, so that the sampling value of each sampling period can be fully utilized.
In some embodiments, the fault parameter may be current and the integral value of the current over the duration of the integration may be an electrical quantity. In some embodiments, the fault parameter may be temperature and the integral value of temperature over the duration of the integration may be heat.
In step 103, when the BMS determines that the integrated value corresponding to the ith sampling period is greater than or equal to the preset integrated threshold value corresponding to the fault parameter, it is determined that the cell fails. The integration threshold may be set according to actual needs, and different fault parameters may correspond to different integration thresholds, for example, an integration threshold corresponding to a current may be referred to as a current integration threshold, an integration threshold corresponding to a voltage may be referred to as a voltage integration threshold, and an integration threshold corresponding to a temperature may be referred to as a temperature integration threshold. The preset integral threshold is used for measuring whether the integral value corresponding to the ith sampling period is a value within a safety range, and if the integral value corresponding to the ith sampling period is greater than or equal to the preset integral threshold corresponding to the fault parameter, the integral value corresponding to the ith sampling period is not within the safety range, and the fault of the battery cell can be determined.
In some embodiments, the fault parameter is current and the integral value of the current over the duration of the integration may be an electrical quantity. And when the BMS judges that the integral value (namely the electric quantity) of the current corresponding to the ith sampling period is larger than or equal to a preset integral threshold value corresponding to the fault parameter (current), determining that the battery cell has an overcurrent fault.
In some embodiments, the fault parameter is temperature and the integral value of temperature over the duration of the integration may be heat. When the BMS determines that the integral value (i.e., heat) of the temperature corresponding to the ith sampling period is greater than or equal to a preset integral threshold value corresponding to the fault parameter (temperature), the battery cell is determined to have an over-temperature fault.
In some embodiments, after determining that the battery cell fails, the BMS may output an alarm message to the whole vehicle, for example, may notify that the whole vehicle is currently failed through CAN communication or through a unified diagnostic service (Unified Diagnostic Services, abbreviated as UDS), and alert that the whole vehicle is currently unable to support operation with full power, so as to take a next step to relieve the failure.
And integrating the sampling value in the integration time length by taking the starting point of the sampling period as the starting point of the integration time length and the ending point of the ith sampling period from the starting point as the ending point of the integration time length to obtain an integral value corresponding to the ith sampling period, wherein the integral value is larger than or equal to a preset integral threshold value corresponding to the fault parameter, and the fact that the integral value of the battery cell is overlarge in a period of time is indicated to possibly cause faults. When the integral value corresponding to the ith sampling period is greater than or equal to a preset integral threshold value corresponding to the fault parameter, determining that the battery cell has faults, and indicating that the time point when the integral value is greater than or equal to the preset integral threshold value corresponding to the fault parameter is the time point when the fault is set, namely, the embodiment of the application does not take the fixed diagnosis judgment time length as a judgment standard when the fault is set, thereby avoiding the risk of untimely alarm easily caused when the diagnosis judgment time length is fixed and being beneficial to timely detecting the fault.
According to some embodiments of the present application, integrating the sampling value in the integration period to obtain an integrated value corresponding to the ith sampling period includes: integrating the sampling value in the integration time length according to the integration coefficient corresponding to the fault parameter to obtain an integration value corresponding to the ith sampling period; the integral coefficient is used for representing the influence degree of the fault parameters on the battery cell.
The integral coefficient is used for representing the influence degree of the fault parameter on the battery cell, and can be understood as follows: the integral coefficient is used for representing the damage degree of faults caused by different fault parameters to the battery cells. The greater the degree of influence of the fault parameter on the battery cell, the greater the integral coefficient corresponding to the fault parameter can be. For example, if the damage degree of the over-temperature fault caused by the temperature to the battery cell is greater than the damage degree of the over-current fault caused by the current to the battery cell, the integral coefficient corresponding to the temperature may be greater than the integral coefficient corresponding to the current.
In some embodiments, the integration coefficients set for different fault parameters may be pre-stored in the BMS.
The integral value is obtained by combining the influence degree of the fault parameters on the battery core, namely the integral coefficient, so that the setting time of faults with larger influence degree on the battery core is shortened, namely the faults with larger influence degree on the battery core are detected quickly.
According to some embodiments of the application, the integral coefficient is calculated by the following formula: k=x/X max Wherein K is an integral coefficient, X is a sampling value, and X max And a preset sampling threshold value corresponding to the fault parameter is set.
The preset sampling threshold value can be set according to actual needs, and different fault parameters can correspond to different preset sampling threshold values. The preset sampling threshold may be understood as a maximum allowable value, which may be understood as: to ensure cell safety, the maximum value of the fault parameters. For example, the preset sampling threshold corresponding to the current may be: in order to ensure the safety of the battery cell, the maximum value of the current and the preset sampling threshold corresponding to the voltage can be: to ensure the safety of the cell, the maximum value of the voltage is used.
X max Can be stored in the BMS in advance, so that the integral coefficient is calculated directly by using the above formula after the BMS acquires the sampling value X. It will be appreciated that: since the BMS can acquire sampling values of fault parameters of the battery cells in each sampling period, there may be fluctuation in the size of the sampling values in each sampling period, and thus the calculated integration coefficients may vary according to the variation of the sampling values. Taking an overcurrent fault as an example, K=I/I can be selectively formulated max I.e., K is directly proportional to I, the greater the sampled current value, the greater the degree of damage to the cell.
The integral coefficient is obtained by calculating the ratio of the sampling value to the sampling threshold value, and the sampling value may have differences in different sampling periods, so that the integral coefficient can be dynamically changed for different sampling periods, and the influence degree of the current sampling value of the fault parameter on the battery cell can be reflected by the integral coefficient. The greater K indicates that the greater the influence degree of the fault parameters on the battery cell is, the greater K also enables the greater the integral value, so that the integral value can be rapidly greater than or equal to a preset integral threshold value along with the increase of the integral duration, the battery cell fault can be detected, and the rapid detection of the fault with the greater influence degree on the battery cell is facilitated.
According to some embodiments of the present application, integrating the sampling value in the integration period according to the integration coefficient corresponding to the fault parameter to obtain the integration value corresponding to the ith sampling period, including: the integral value corresponding to the ith sampling period is calculated by the following formula:
Y＝∫K*X N dt
wherein Y is an integral value, K is an integral coefficient, X is a sampling value, and N is an order corresponding to a fault parameter.
The formula for calculating the integral value can be stored in the BMS in advance, and when the BMS acquires the sampling value of the fault parameter of the battery cell in the sampling period, the acquired sampling value is substituted into the formula for calculating the integral value, so that the integral value corresponding to the ith sampling period can be obtained.
N can be the order of the fault parameters when the target parameters are obtained through the fault parameters, and the target parameters can be the parameters directly related to the fault types corresponding to the fault parameters.
In some embodiments, the fault parameter is a current I, the target parameter is an electric quantity q, according to the formula q=it, it can be seen that when the target parameter q is obtained by the fault parameter I, the order of the fault parameter I is 1, i.e. the power of I is 1, and then the formula for calculating the integral value of the current corresponding to the I-th sampling period can be expressed as follows:
q＝∫K*I 1 dt
in some embodiments, the fault parameter is temperature, the target parameter is heat, cm Δt, c is specific heat, m is mass, Δt is the change in temperature, and it can be seen that the temperature is obtained by temperature with an order of 1, i.e., the Δt is to the power of 1.
In some embodiments, the fault parameter is current I, the target parameter is heat Q, according to the formula q=i 2 Rt, can be seen through the fault parametersAnd when the target parameter Q is obtained by the I, the order of the fault parameter I is 2, namely the power of the I is 2.
The following describes a manner of obtaining an integrated value corresponding to the i-th sampling period, taking m=4, the sampling period being 10ms, and n being 2 as an example:
the integral value corresponding to the 1 st sampling period is:
that is, the start point of the integration period is the start point 0 of the 1 st sampling period, and the end point of the integration period is the end point 10ms of the 1 st sampling period starting with the start point 0.
The integration value corresponding to the 2 nd sampling period is:
that is, the start point of the integration period is the start point 0 of the 1 st sampling period, and the end point of the integration period is the end point 20ms of the 2 nd sampling period starting with the start point 0. K1 and X1 are the integration coefficient and the sampling value in the 1 st sampling period, respectively, and K2 and X2 are the integration coefficient and the sampling value in the 2 nd sampling period, respectively.
The integration value corresponding to the 3 rd sampling period is:
i.e., the start point of the integration period is the start point 0 of the 1 st sampling period, and the end point of the integration period is the end point 30ms of the 3 rd sampling period starting with the start point 0. K3 and X3 are the integration coefficient and the sample value, respectively, in the 3 rd sample period.
The integration value corresponding to the 4 th sampling period is:
i.e., the start point of the integration period is the start point 0 of the 1 st sampling period, and the end point of the integration period is the end point 40ms of the 4 th sampling period starting with the start point 0. K4 and X4 are the integration coefficient and the sample value, respectively, in the 4 th sample period.
It should be noted that, the above calculation process is only described by taking the starting point of the integration time period as the starting point of the 1 st sampling period as an example, and in a specific implementation, the calculation manner using other time points as the starting point of the integration time period is similar to the calculation manner described above, so that repetition is avoided and no description is repeated here.
The integral value corresponding to the ith sampling period is obtained by the integral formula, which is favorable for accurate, quick and reasonable calculation.
According to some embodiments of the application, the preset integral threshold corresponding to the fault parameter includes a plurality of integral thresholds; when the integral value corresponding to the ith sampling period is greater than or equal to a preset integral threshold value corresponding to the fault parameter, determining that the battery cell has a fault comprises: when the integral value corresponding to the ith sampling period is greater than or equal to k integral thresholds in the multiple integral thresholds, acquiring a fault grade corresponding to the largest integral threshold in the k integral thresholds, and determining the acquired fault grade as the fault grade of the fault of the battery cell; wherein k is an integer greater than or equal to 1.
The multiple integral thresholds included in the preset integral threshold can be set according to actual needs and used for representing different fault levels, and the higher the fault level represented by the integral threshold with the larger integral threshold in the multiple integral thresholds is, the more serious the fault is indicated. After determining that the battery cell fails, the BMS CAN output alarm information to the whole vehicle, for example, the BMS CAN inform the whole vehicle that the whole vehicle fails currently through CAN communication or through UDS, and warn that the whole vehicle cannot support running at full power currently, and the vehicle CAN stop immediately when the failure is serious.
For example, the fault parameter is a current, and the preset integral threshold corresponding to the current includes: the integration threshold 1 (corresponding failure level is primary), the integration threshold 2 (corresponding failure level is intermediate), and the integration threshold 3 (corresponding failure level is high) which are sequentially increased. When the integral value corresponding to the ith sampling period is greater than or equal to 2 integral thresholds (such as integral threshold 2 and integral threshold 3) in the 3 integral thresholds, the fault level corresponding to the largest integral threshold in the integral threshold 2 and integral threshold 3 is obtained, that is, the fault level corresponding to the integral threshold 3 is obtained, and the fault level corresponding to the integral threshold 3 is determined as the fault level of the fault occurring in the battery cell, that is, the fault level of the fault occurring in the battery cell is detected.
In the embodiment, the faults of different levels can be reflected by configuring a plurality of integral thresholds, so that fault response of different levels can be realized, and the faults of the same type can be conveniently pre-warned of different levels according to different fault levels.
According to some embodiments of the application, M.ltoreq.1000.
M corresponds to the type of the fault parameter and is more than or equal to 1, namely the minimum value of M is 1, the maximum value of M is 1000, and M is an integer. Since 1.ltoreq.i.ltoreq.M, the end point of the integration period is at least: the end point of the 1 st sampling period starting with the start point of the integration period is at most: the end point of the 1000 th sampling period starting with the start point of the integration period. Assuming a sampling period of 10ms, the integration duration is 10ms at a minimum and 10s at a maximum. It is also understood that the tolerance period corresponding to the fault parameter is in the interval [10ms,10s ]. In a specific implementation, tolerance durations corresponding to the same fault parameter may be different for different types of battery cells, and tolerance durations corresponding to different types of fault parameters may also be different for the same battery cell, where the tolerance durations may be determined by comprehensively considering the capability of the battery cell and the corresponding fault tolerance time interval (fault tolerant time interval, abbreviated as FTTI).
In this embodiment, M is 1-1000, so that the calculation can be performed based on the sampled values sampled in one or more complete sampling periods, and the effectiveness of integration is ensured. M is less than or equal to 1000, namely the integral time length is not too long, the integral value is ensured to exceed the integral threshold value in a short time, and the fault detection accuracy is improved.
According to some embodiments of the present application, after integrating the sampling values in the integration period to obtain the integrated value corresponding to the ith sampling period, the method further includes: integrating a preset sampling threshold value corresponding to the fault parameter in the integration time length to obtain a sampling threshold value integral value corresponding to the ith sampling period; calculating an integral difference value between an integral value corresponding to the ith sampling period and a sampling threshold integral value corresponding to the ith sampling period; when the integral value corresponding to the ith sampling period is greater than or equal to a preset integral threshold value corresponding to the fault parameter, determining that the battery cell has a fault comprises: and when the integral difference value is greater than or equal to a preset integral difference value threshold value corresponding to the fault parameter, determining that the battery cell has faults.
The preset sampling threshold value can be set according to actual needs, and different fault parameters can correspond to different preset sampling threshold values. The preset sampling threshold may be understood as a maximum allowable value, which may be understood as: to ensure cell safety, the maximum value of the fault parameters. For example, the preset sampling threshold corresponding to the current may be: in order to ensure the safety of the battery cell, the maximum value of the current and the preset sampling threshold corresponding to the voltage can be: to ensure the safety of the cell, the maximum value of the voltage is used.
The integration of the preset sampling threshold corresponding to the fault parameter in the integration time period is similar to the integration of the sampling value in the integration time period, except that the former integrates the preset sampling threshold and the latter integrates the sampling value. How the sampled values are integrated has been described above, where the preset sampling threshold values may be integrated in a similar manner, and no further description is given here for avoiding repetition.
In some embodiments, the integral difference may be calculated by the following formula:
Y′＝∫K*(X-X max ) N dt
wherein Y' is an integral difference value, X is a sampling value, and X max For a preset sampling threshold valueN is the order corresponding to the fault parameter, and K is the integral coefficient corresponding to the fault parameter.
The preset integral difference threshold corresponding to the fault parameter can be set according to actual needs. There is a numerical difference between a preset integral threshold corresponding to the fault parameter and a preset integral difference threshold corresponding to the fault parameter, and the preset integral threshold is greater than the preset integral difference threshold. The preset integral difference value threshold is used for measuring whether the integral difference value between the integral value corresponding to the ith sampling period and the sampling threshold integral value corresponding to the ith sampling period is a value within a safety range, and if the integral difference value is greater than or equal to the preset integral difference value threshold corresponding to the fault parameter, the integral difference value is not within the safety range, and the fault of the battery cell can be determined at the moment.
The integral difference value can reflect the possible fault risk caused by the fact that the sampling value exceeds a preset sampling threshold value. And the integral difference value can be positive or negative, and the positive difference value and the negative difference value are considered, so that the fault can be set timely when the sampling value fluctuates up and down at a preset sampling threshold value, and the problem that the fault is set untimely because the fault is set continuously beyond a certain threshold value for a period of time in the prior art is avoided.
The fault detection method in some embodiments of the present application will be described below by taking the fault parameter as an example of current:
the BMS obtains the sampling value of the current of the battery cell in the sampling period, and then adopts the following formula to obtain the sampling value I in the integration time period and the maximum allowable value I of the current max Integrating the difference value to obtain an integrated difference value q' corresponding to the ith sampling period:
q′＝∫K*(I-I max ) 1 dt
in this embodiment, the integrated difference value, i.e., the electric quantity q, in a certain integrated time period is calculated by the above formula, and when the actual electric quantity in the certain integrated time period is greater than or equal to the integrated difference value threshold corresponding to the current, it is determined that the overcurrent fault occurs in the battery cell. The general scheme for detecting overcurrent faults is as follows: and if the detected current is larger than the overcurrent threshold and the duration is longer than the preset diagnosis judging duration, determining that the battery cell has an overcurrent fault. The general scheme can fail to report the fault under the condition that the current repeatedly oscillates, because the condition that the current is larger than the overcurrent threshold cannot be continuously met. In this embodiment, the problem of failure missing is not existed in the integrating mode.
Referring to fig. 2, when the current oscillates around the overcurrent threshold, the general scheme does not detect an overcurrent fault because the condition that the current is greater than the overcurrent threshold cannot be continuously satisfied.
Referring to fig. 3, in this embodiment, by integrating the current during the integration period (abbreviated as an integration manner), the electric quantity q obtained by integrating in a certain period exceeds a preset integration difference threshold corresponding to the current, so as to determine that the battery cell has an overcurrent fault. The overcurrent threshold in fig. 3 can be understood as: the current corresponds to a preset integral difference threshold.
In the general scheme, the time for setting the overcurrent fault is fixed in three scenes I1, I2, I3 where the currents are different, that is, the overcurrent fault is detected at the same time, and fig. 4 is referred to. In practice, however, the larger the current, the greater the damage that will be done during the same time. In this embodiment, in the integration, the k=i/I is set in consideration of the integration coefficient K, where K represents the influence degree and the damage degree of the current on the battery cell max I.e. K is directly proportional to I, the greater the current the side indicates, the greater the K, the greater the extent of damage to the cell. Referring to fig. 5, the integration method in the present embodiment is used to detect faults, and the greater the damage caused by the current, the shorter the fault setting time under three scenarios I1, I2, I3 with different currents. In fig. 5, since the damage caused by I3 having the largest current is largest, the overcurrent fault is detected at the earliest time T3, the overcurrent fault is detected at the time T2 in the case of the current I2, and the overcurrent fault is detected at the time T1 in the case of the current I1.
In some embodiments, a calculation formula of integral values corresponding to different fault parameters may be pre-stored in the BMS, including: a calculation formula of an integrated value corresponding to a current, a calculation formula of an integrated value corresponding to a voltage, a calculation formula of an integrated value corresponding to a temperature, and the like. After the BMS acquires the current sampling value, the voltage sampling value and the temperature sampling value of the battery cell in the sampling period, the BMS can be directly brought into a corresponding calculation formula to calculate the integral value, so that the judgment of different fault types can be simultaneously carried out. And the same fault type can be provided with a plurality of integral thresholds representing different fault levels, so that the same fault type can be warned in different degrees.
According to some embodiments of the present application, there is provided a fault detection apparatus, referring to fig. 6, including: the acquiring module 601 is configured to acquire a sampling value of a fault parameter of the battery cell in a sampling period; an integrating module 602, configured to integrate sampling values in an integration duration to obtain an integrated value corresponding to an ith sampling period; wherein i is an integer, i is more than or equal to 1 and less than or equal to M, M corresponds to the type of fault parameters, and M is more than or equal to 1; the starting point of the integration time length is the starting point of the sampling period, and the ending point of the integration time length is the ending point of the ith sampling period starting from the starting point; a determining module 603, configured to determine that the battery cell fails when the integrated value corresponding to the ith sampling period is greater than or equal to a preset integrated threshold corresponding to the failure parameter.
It is to be noted that this embodiment is an embodiment of the apparatus corresponding to the above-described method embodiment, and this embodiment may be implemented in cooperation with the above-described method embodiment. The related technical details and technical effects mentioned in the above method embodiments are still valid in this embodiment, and in order to reduce repetition, they are not repeated here. Accordingly, the related technical details mentioned in the present embodiment can also be applied in the above-described method embodiments.
It should be noted that, each module involved in this embodiment is a logic module, and in practical application, one logic unit may be one physical unit, or may be a part of one physical unit, or may be implemented by a combination of multiple physical units. In addition, in order to highlight the innovative part of the present application, units less closely related to solving the technical problem presented by the present application are not introduced in the present embodiment, but it does not indicate that other units are not present in the present embodiment.
According to some embodiments of the present application, there is provided a battery management system BMS, referring to fig. 7, including: at least one processor 701; and a memory 702 communicatively coupled to the at least one processor 701; wherein the memory 702 stores instructions executable by the at least one processor 701 to enable the at least one processor 701 to perform a fault detection method as described above.
Where memory 702 and processor 701 are connected by a bus, the bus may comprise any number of interconnected buses and bridges, the buses connecting the various circuits of the one or more processors 701 and memory 702 together. The bus may also connect various other circuits such as peripherals, voltage regulators, and power management circuits, which are well known in the art, and therefore, will not be described any further herein. The bus interface provides an interface between the bus and the transceiver.
The transceiver may be one element or may be a plurality of elements, such as a plurality of receivers and transmitters, providing a means for communicating with various other apparatus over a transmission medium. The data processed by the processor 701 is transmitted over a wireless medium via an antenna, which further receives the data and transmits the data to the processor 701.
The processor 701 is responsible for managing the bus and general processing and may provide various functions including timing, peripheral interfaces, voltage regulation, power management, and other control functions. And memory 702 may be used to store data used by processor 701 in performing operations.
According to some embodiments of the present application, there is provided a computer-readable storage medium storing a computer program. The computer program implements the above-described method embodiments when executed by a processor.
That is, it will be understood by those skilled in the art that all or part of the steps in implementing the methods of the embodiments described above may be implemented by a program stored in a storage medium, where the program includes several instructions for causing a device (which may be a single-chip microcomputer, a chip or the like) or a processor (processor) to perform all or part of the steps in the methods of the embodiments of the application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present application, and not for limiting the same; although the application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the application, and are intended to be included within the scope of the appended claims and description. In particular, the technical features mentioned in the respective embodiments may be combined in any manner as long as there is no structural conflict. The present application is not limited to the specific embodiments disclosed herein, but encompasses all technical solutions falling within the scope of the claims.

Claims (10)

  1. A fault detection method applied to a battery management system BMS, comprising:
    acquiring a sampling value of a fault parameter of the battery cell in a sampling period;
    integrating the sampling value in the integration time length to obtain an integration value corresponding to the ith sampling period; wherein i is an integer, i is more than or equal to 1 and less than or equal to M, M corresponds to the type of the fault parameter, and M is more than or equal to 1; the starting point of the integration time length is the starting point of the sampling period, and the ending point of the integration time length is the ending point of the ith sampling period starting from the starting point;
    and when the integral value corresponding to the ith sampling period is larger than or equal to a preset integral threshold value corresponding to the fault parameter, determining that the battery cell has faults.
  2. The fault detection method as claimed in claim 1, wherein integrating the sampling value in the integration period to obtain the integration value corresponding to the ith sampling period includes:
    integrating the sampling value in the integration time length according to the integration coefficient corresponding to the fault parameter to obtain an integration value corresponding to the ith sampling period; the integral coefficient is used for representing the influence degree of the fault parameter on the battery cell.
  3. The fault detection method of claim 2, wherein the integral coefficient is calculated by the formula:
    K＝X/X max wherein K is the integral coefficient, X is the sampling value, X max And a preset sampling threshold value corresponding to the fault parameter is set.
  4. The fault detection method according to claim 2 or 3, wherein integrating the sampling value in the integration duration according to the integration coefficient corresponding to the fault parameter to obtain the integration value corresponding to the ith sampling period includes:
    and calculating to obtain an integrated value corresponding to the ith sampling period by the following formula:
    Y＝∫K*X N dt
    wherein Y is the integral value, K is the integral coefficient, X is the sampling value, and N is the order corresponding to the fault parameter.
  5. The fault detection method according to any one of claims 1 to 4, wherein the preset integral threshold corresponding to the fault parameter includes a plurality of integral thresholds;
    and when the integral value corresponding to the ith sampling period is greater than or equal to a preset integral threshold value corresponding to the fault parameter, determining that the battery cell has a fault comprises:
    when the integral value corresponding to the ith sampling period is greater than or equal to k integral thresholds in the multiple integral thresholds, acquiring a fault grade corresponding to the largest integral threshold in the k integral thresholds, and determining the acquired fault grade as the fault grade of the fault of the battery cell; wherein k is an integer greater than or equal to 1.
  6. The failure detection method according to any one of claims 1 to 5, wherein m.ltoreq.1000.
  7. The fault detection method according to claim 1, wherein after integrating the sampling values in the integration period to obtain an integration value corresponding to the ith sampling period, further comprising:
    integrating a preset sampling threshold value corresponding to the fault parameter in the integration time length to obtain a sampling threshold value integrated value corresponding to the ith sampling period;
    calculating an integral difference value between an integral value corresponding to the ith sampling period and a sampling threshold integral value corresponding to the ith sampling period;
    and when the integral value corresponding to the ith sampling period is greater than or equal to a preset integral threshold value corresponding to the fault parameter, determining that the battery cell has a fault comprises:
    and when the integral difference value is larger than or equal to a preset integral difference value threshold value corresponding to the fault parameter, determining that the battery cell has a fault.
  8. A fault detection device comprising:
    the acquisition module is used for acquiring sampling values of fault parameters of the battery cell in a sampling period;
    the integration module is used for integrating the sampling value in the integration time length to obtain an integration value corresponding to the ith sampling period; wherein i is an integer, i is more than or equal to 1 and less than or equal to M, M corresponds to the type of the fault parameter, and M is more than or equal to 1; the starting point of the integration time length is the starting point of the sampling period, and the ending point of the integration time length is the ending point of the ith sampling period starting from the starting point;
    And the determining module is used for determining that the battery cell fails when the integral value corresponding to the ith sampling period is larger than or equal to a preset integral threshold value corresponding to the fault parameter.
  9. A battery management system BMS, comprising:
    at least one processor; the method comprises the steps of,
    a memory communicatively coupled to the at least one processor; wherein,
    the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the fault detection method of any one of claims 1 to 7.
  10. A computer readable storage medium storing a computer program which, when executed by a processor, implements the fault detection method of any one of claims 1 to 7.
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