WO2023028934A1 - 故障检测方法、装置、电池管理系统和存储介质 - Google Patents

故障检测方法、装置、电池管理系统和存储介质 Download PDF

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WO2023028934A1
WO2023028934A1 PCT/CN2021/116136 CN2021116136W WO2023028934A1 WO 2023028934 A1 WO2023028934 A1 WO 2023028934A1 CN 2021116136 W CN2021116136 W CN 2021116136W WO 2023028934 A1 WO2023028934 A1 WO 2023028934A1
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integral
fault
sampling period
sampling
integration
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PCT/CN2021/116136
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English (en)
French (fr)
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李佳莹
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宁德时代新能源科技股份有限公司
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Priority to PCT/CN2021/116136 priority Critical patent/WO2023028934A1/zh
Priority to CN202180082572.7A priority patent/CN116783495A/zh
Publication of WO2023028934A1 publication Critical patent/WO2023028934A1/zh

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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

Definitions

  • the present application relates to the field of battery technology, in particular to a fault detection method, device, battery management system and storage medium.
  • BMS Battery Management System
  • the usual method is: when the judgment items such as current current, current temperature, current voltage, etc. exceed the corresponding threshold (condition 1) and the duration exceeds the preset diagnosis judgment time (condition 2), set Failure, as shown in Table 1:
  • Fault Condition 1 Condition 2 battery overcurrent fault Current current I>200(A) Duration t>10s battery over temperature fault Current temperature T>65(DegC) Duration t>5s battery overvoltage fault Current voltage V>4.0(V) Duration t>15s
  • the present application provides a fault detection method, device, battery management system and storage medium, which can detect faults in time and help avoid the risk of untimely alarm.
  • the present application provides a fault detection method, including: applied to the battery management system BMS, including: obtaining the sampling value of the fault parameter of the battery cell within the sampling period; integrating the sampling value within the integration time length to obtain the first Integral values corresponding to the i sampling period; wherein, i is an integer and 1 ⁇ i ⁇ M, M corresponds to the type of the fault parameter and M ⁇ 1; the starting point of the integration duration is the sampling period The starting point, the end point of the integration duration is the end point of the i-th sampling period starting from the starting point; when the integral value corresponding to the i-th sampling period is greater than or equal to the corresponding fault parameter When the integration threshold is preset, it is determined that the battery cell is faulty.
  • the starting point of the sampling period is used as the starting point of the integration duration
  • the end point of the i-th sampling period starting from the starting point is the end point of the integration duration
  • the sampling value in the integration duration is calculated. Integrate to obtain the integral value corresponding to the i-th sampling period.
  • the integral value is greater than or equal to the preset integral threshold corresponding to the fault parameter, indicating that the battery may fail if the integral value is too large within a period of time.
  • the integral value corresponding to the i-th sampling period is greater than or equal to the preset integral threshold corresponding to the fault parameter, it is determined that the battery has failed, indicating that the time point when the integral value is greater than or equal to the preset integral threshold corresponding to the fault parameter is set out
  • the time point of the fault that is, the embodiment of the present application does not use the fixed diagnosis and judgment time as the judgment standard when setting the fault, thereby avoiding the risk of untimely alarm when the diagnosis and judgment time is fixed, which is conducive to timely A fault has been detected.
  • the integrating the sampling values within the integration time length to obtain the integration value corresponding to the ith sampling period includes: according to the integration coefficient corresponding to the fault parameter, the sampling value within the integration time length performing integration to obtain an integral value corresponding to the i-th sampling period; wherein, the integral coefficient is used to characterize the degree of influence of the fault parameter on the battery cell.
  • the integral value can be obtained in combination with the degree of influence of the fault parameter on the battery cell, which is beneficial to shorten the settling time of the fault that has a greater influence on the battery cell, that is, it is beneficial to quickly detect the damage to the battery cell. Faults with a large degree of influence.
  • the integral coefficient is calculated by the ratio of the sampling value to the sampling threshold. Since there may be differences in the sampling values in different sampling periods, the integral coefficient can be dynamically changed for different sampling periods. It is beneficial to enable the integral coefficient to reflect the degree of influence of the current sampling value of the fault parameter on the battery cell. The larger the K, the greater the impact of the fault parameter on the cell, and the larger the K, the larger the integral value, so that the integral value can quickly be greater than or equal to the preset integral threshold with the increase of the integral time to detect Battery failure is conducive to quickly detecting failures that have a greater impact on the battery.
  • integrating the sampling value within the integration time length to obtain the integral value corresponding to the i-th sampling period includes: calculating the i-th by the following formula The integral value corresponding to the sampling period:
  • Y is the integral value
  • K is the integral coefficient
  • X is the sampling value
  • N is the order corresponding to the fault parameter.
  • the integral value corresponding to the i-th sampling period can be obtained through accurate, fast and reasonable calculation through the above integral formula.
  • 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 the preset integral threshold corresponding to the fault parameter , determining that the cell is faulty, including: when the integral value corresponding to the ith sampling period is greater than or equal to k integral thresholds among the plurality of integral thresholds, obtaining the largest of the k integral thresholds Integrate the fault level corresponding to the threshold, and determine the obtained fault level as the fault level of the fault in the battery cell; wherein, the k is an integer greater than or equal to 1.
  • different grades of faults can be reflected by configuring multiple integral thresholds, which is conducive to different degrees of fault response and facilitates different degrees of early warning for the same type of fault.
  • M 1000.
  • 1 ⁇ M ⁇ 1000 so that calculation can be performed based on the sampling values sampled in one or more complete sampling periods, so as to ensure the validity of the integration.
  • M ⁇ 1000 that is, the integration time will not be too long to ensure that the integration value exceeds the integration threshold in a short time and improve the accuracy of fault detection.
  • after integrating the sampling values within the integration time length to obtain the integration value corresponding to the i-th sampling period it further includes: predicting the corresponding fault parameter within the integration time length Set the sampling threshold to be integrated to obtain the sampling threshold integral value corresponding to the ith sampling period; calculate the integral value corresponding to the ith sampling period and the sampling threshold integral value corresponding to the i sampling period Integral difference; when the integral value corresponding to the i-th sampling period is greater than or equal to the preset integral threshold corresponding to the fault parameter, it is determined that the cell has a fault, including: when the integral difference is greater than or equal to the preset integral difference threshold corresponding to the fault parameter, it is determined that the battery cell is faulty.
  • the integral difference can reflect the possible fault risk caused by the part of the sampling value exceeding the preset sampling threshold.
  • the integral difference may be positive or negative, and the positive and negative difference are considered at the same time, so that when the sampling value fluctuates above and below the preset sampling threshold, the fault can be reset in time, avoiding the need to continuously exceed a certain threshold for a period of time in the prior art. The failure caused by the fault setting is not timely.
  • the present application provides a fault detection device, including: an acquisition module, used to obtain the sampling value of the fault parameter of the battery cell within the sampling period; an integration module, used to integrate the sampling value within the integration time length, to obtain The integral value corresponding to the i-th sampling period; wherein, i is an integer and 1 ⁇ i ⁇ M, M corresponds to the type of the fault parameter and M ⁇ 1; the starting point of the integration duration is the sampling period The starting point of the integration duration is the ending point of the i-th sampling period starting from the starting point; the determination module is used to determine when the integral value corresponding to the i-th sampling period is greater than or equal to When the fault parameter corresponds to a preset integration threshold, it is determined that the battery cell is faulty.
  • the present application provides a battery management system BMS, including: at least one processor; and a memory connected in communication with the at least one processor; wherein, the memory stores information that can be processed by the at least one processor. instructions executed by the at least one processor, the instructions are executed by the at least one processor, so that the at least one processor can execute the above fault detection method.
  • the present application provides a computer-readable storage medium storing a computer program, and implementing the above fault detection method when the computer program is executed by a processor.
  • FIG. 1 is a schematic flow diagram of a fault detection method mentioned in some embodiments of the present application.
  • Fig. 2 is a schematic diagram of the detection results of overcurrent faults in the general scheme mentioned in some embodiments of the present application;
  • FIG. 3 is a schematic diagram of the detection results of overcurrent fault detection using the integral method mentioned in some embodiments of the present application;
  • Fig. 4 is a schematic diagram of detection results of detecting overcurrent faults using a general scheme in three scenarios with different currents mentioned in some embodiments of the present application;
  • Fig. 5 is a schematic diagram of detection results of detecting overcurrent faults using an integral method under three scenarios with different currents mentioned in some embodiments of the present application;
  • FIG. 6 is a schematic diagram of a fault detection device mentioned in some embodiments of the present application.
  • Fig. 7 is a schematic structural diagram of a BMS mentioned in some embodiments of the present application.
  • Power batteries are not only used in energy storage power systems such as hydraulic, thermal, wind and solar power plants, but also widely used in electric vehicles such as electric bicycles, electric motorcycles, electric vehicles, as well as military equipment and aerospace and other fields .
  • energy storage power systems such as hydraulic, thermal, wind and solar power plants
  • electric vehicles such as electric bicycles, electric motorcycles, electric vehicles, as well as military equipment and aerospace and other fields .
  • the battery cell in the power battery plays a key role in the normal operation of the power battery, so the fault detection of the battery cell is particularly important.
  • an optimization direction for risk 1 is to shorten the diagnosis and judgment time, but this will bring about the problem of frequent or misplaced faults; for risk 2, a This optimization direction is divided into multi-level faults, with different thresholds and diagnostic judgment time, but this can only reduce the risk to a certain extent, no matter how classified it is, it is still difficult to cover all faults, and it cannot fundamentally solve the problem that fault alarms are not timely enough question.
  • the inventor designed a fault detection method after in-depth research, by integrating the sampling value of the fault parameter within a certain integration time, when the integral value is greater than or equal to the predetermined When the set integral threshold is reached, the cell is detected to be faulty. That is to say, the embodiment of the present application does not use a fixed diagnosis and judgment time as the judgment standard when setting a fault, thereby avoiding the risk of untimely alarm when the diagnosis and judgment time is fixed, which is conducive to timely detection of faults.
  • the fault detection method disclosed in the embodiment of the present application is applied to the battery management system BMS.
  • the BMS is a control system for protecting the safety of the power battery, and monitors the use status of the battery at all times to provide guarantee for the use safety of new energy vehicles.
  • the schematic flowchart of the fault detection method can refer to FIG. 1, including:
  • Step 101 Obtain the sampling value of the fault parameter of the cell within the sampling period
  • Step 102 Integrate the sampling values within the integration duration to obtain the integration value corresponding to the i-th sampling period;
  • Step 103 When the integral value corresponding to the i-th sampling period is greater than or equal to the preset integral threshold corresponding to the fault parameter, it is determined that the battery cell is faulty;
  • the BMS can acquire the sampling value of the fault parameter of the cell within the sampling period; wherein, the sampling period can be a sampling period preset according to actual needs, for example, it can be set to 10ms.
  • the fault parameter can be a parameter used to judge whether the cell is faulty, for example, it can include but not limited to: current, voltage, temperature; the fault parameter of current can be used to judge whether the cell has an overcurrent fault, and the fault parameter of voltage can be It is used to judge whether the cell has an overvoltage fault, and the fault parameter temperature can be used to judge whether the cell has an overtemperature fault.
  • the sampled value of the fault parameter may include, but not limited to: a sampled value of current, that is, a current value, a sampled value of voltage, that is, a voltage value, and a sampled value of temperature, that is, a temperature value.
  • the sampling value of the fault parameter of the battery cell can be sampled by a sampling device, and the sampling device can periodically collect the fault parameter of the battery cell according to a preset sampling period, and send the sampled value to the BMS, so that The BMS can acquire the sampled values of the fault parameters of the cells within the sampling period.
  • the BMS can acquire the sampling value of the fault parameter of the battery cell in each sampling period.
  • i is an integer and 1 ⁇ i ⁇ M
  • M corresponds to the type of fault parameter and M ⁇ 1
  • the starting point of the integration duration is the starting point of the sampling period
  • the end point of the integration duration is the period starting from the starting point The end point of the i-th sampling period.
  • the types of fault parameters may be, for example, current, voltage, temperature, etc. Different types of fault parameters have corresponding M values. According to actual needs, the M values corresponding to different types of fault parameters may be the same or different.
  • the duration of the M sampling periods may be the tolerance period corresponding to the fault parameter, and the tolerance period may be the fault tolerance time for the battery cell to maintain safety under the current dangerous working condition. That is to say, different types of fault parameters correspond to their respective tolerance durations.
  • the BMS can take the starting point of each sampling period as the starting point of the integration duration, and take the end point of the i-th sampling period starting from the starting point as the end point of the integration duration, and integrate the sampled values within the integration duration to obtain the i-th The integral value corresponding to the sampling period. That is, the starting point of each sampling period can be used as the starting point of the integration duration, so that the sampling value of each sampling period can be fully utilized.
  • the fault parameter may be a current, and the integrated value of the current within the integration time period may be an electric quantity.
  • the fault parameter may be temperature, and the integrated value of temperature within the integration time period may be heat.
  • step 103 when the BMS determines that the integral value corresponding to the i-th sampling period is greater than or equal to the preset integral threshold corresponding to the fault parameter, it determines that the battery cell is faulty.
  • the integral threshold can be set according to actual needs. Different fault parameters can correspond to different integral thresholds.
  • the integral threshold corresponding to current can be called current integral threshold
  • the integral threshold corresponding to voltage can be called voltage integral threshold
  • the integral threshold corresponding to temperature can be The integration threshold of can be called the temperature integration threshold.
  • the preset integral threshold is used to measure whether the integral value corresponding to the i-th sampling period is a value within a safe range.
  • the integral value corresponding to the i-th sampling period is greater than or equal to the preset integral threshold corresponding to the fault parameter, it means that the The integral value corresponding to the i sampling period is no longer within the safe range, and it can be determined that the battery cell is faulty at this time.
  • the fault parameter is current
  • the integrated value of the current within the integration time period may be electric quantity.
  • the fault parameter is temperature
  • the integrated value of temperature during the integration time period may be heat.
  • the BMS after the BMS determines that the battery cell is faulty, it can output alarm information to the entire vehicle, for example, it can notify the entire vehicle of the current fault through CAN communication or through a unified diagnostic service (Unified Diagnostic Services, referred to as: UDS). Warns that the vehicle cannot support operation at full power at present, so that the next step can be taken to eliminate the fault.
  • UDS Unified Diagnostic Services
  • the integral value corresponding to the i-th sampling period is greater than or equal to the preset integral threshold corresponding to the fault parameter, it is determined that the battery has failed, indicating that the time point when the integral value is greater than or equal to the preset integral threshold corresponding to the fault parameter is set out
  • the time point of the fault that is, the embodiment of the present application does not use the fixed diagnosis and judgment time as the judgment standard when setting the fault, thereby avoiding the risk of untimely alarm when the diagnosis and judgment time is fixed, which is conducive to timely A fault has been detected.
  • integrating the sampled values within the integral duration to obtain the integral value corresponding to the ith sampling period includes: integrating the sampled values within the integral duration according to the integral coefficient corresponding to the fault parameter to obtain The integral value corresponding to the i-th sampling period; where the integral coefficient is used to characterize the degree of influence of the fault parameter on the cell.
  • the integral coefficient is used to characterize the degree of influence of the fault parameter on the cell, which can be understood as: the integral coefficient is used to represent the degree of damage to the cell caused by the fault caused by different fault parameters.
  • the greater the influence of the fault parameter on the cell the greater the integral coefficient corresponding to the fault parameter. For example, if the over-temperature fault caused by temperature is more harmful to the cell than the over-current fault caused by current, the integral coefficient corresponding to temperature can be greater than the integral coefficient corresponding to current.
  • the integral coefficients set for different fault parameters may be pre-stored in the BMS.
  • the preset sampling threshold can be set according to actual needs, and different fault parameters can correspond to different preset sampling thresholds.
  • the preset sampling threshold can be understood as the maximum allowable value, and the maximum allowable value can be understood as: in order to ensure the safety of the battery cell, the maximum value of the fault parameter.
  • the preset sampling threshold corresponding to the current can be: to ensure the safety of the cell, the maximum value of the current, and the preset sampling threshold corresponding to the voltage can be: the maximum value of the voltage to ensure the safety of the cell.
  • the integral coefficient is calculated by the ratio of the sampling value to the sampling threshold. Since the sampling value may be different in different sampling periods, the integral coefficient can be dynamically changed for different sampling periods, which is beneficial to make the integral coefficient reflect the fault parameters.
  • the degree of influence of the current sampling value of the battery on the cell The larger the K, the greater the impact of the fault parameter on the cell, and the larger the K, the larger the integral value, so that the integral value can quickly be greater than or equal to the preset integral threshold with the increase of the integral time to detect Battery failure is conducive to quickly detecting failures that have a greater impact on the battery.
  • the sampling value within the integral duration is integrated to obtain the integral value corresponding to the i-th sampling period, including: calculating the i-th sampling period corresponding to The integral value of :
  • Y is the integral value
  • K is the integral coefficient
  • X is the sampling value
  • N is the order corresponding to the fault parameter.
  • the formula for calculating the integral value can be pre-stored in the BMS.
  • the BMS obtains the sampling value of the fault parameter of the battery cell within the sampling period, the obtained sampling value is substituted into the formula for calculating the integral value, and the i-th The integral value corresponding to the sampling period.
  • N may be the order of the fault parameter when the target parameter is obtained through the fault parameter, and the target parameter may be a parameter directly related to the fault type corresponding to the fault parameter.
  • the fault parameter is the current I
  • the target parameter is the electric quantity q.
  • the number is the power of 1, then the formula for calculating the integral value of the current corresponding to the i-th sampling period can be expressed as follows:
  • the fault parameter is temperature
  • the target parameter is heat
  • cm ⁇ t is specific heat
  • m is mass
  • ⁇ t is the change of temperature. It can be seen that when heat is obtained by temperature The order of temperature is 1, that is, the power of ⁇ t is 1 power.
  • the fault parameter is current I
  • the target parameter is heat Q
  • the order of the fault parameter I is 2 when the target parameter Q is obtained through the fault parameter I, that is, the The number of times is the power of 2.
  • the integral value corresponding to the first sampling period is:
  • the start point of the integration duration is the start point 0 of the first sampling period
  • the end point of the integration duration is 10 ms, the end point of the first sampling period starting from the start point 0.
  • the integral value corresponding to the second sampling period is:
  • the start point of the integration time is the start point 0 of the first sampling period, and the end point of the integration time is 20ms, the end point of the second sampling period starting from the start point 0.
  • K1 and X1 are the integral coefficient and sampling value in the first sampling period respectively
  • K2 and X2 are the integral coefficient and sampling value in the second sampling period respectively.
  • the integral value corresponding to the third sampling period is:
  • the start point of the integration time is the start point 0 of the first sampling period, and the end point of the integration time is 30ms, the end point of the third sampling period starting from the start point 0.
  • K3 and X3 are the integral coefficient and sampling value in the 3rd sampling cycle respectively.
  • the integral value corresponding to the fourth sampling period is:
  • the start point of the integration time is the start point 0 of the first sampling period, and the end point of the integration time is 40ms, the end point of the fourth sampling period starting from the start point 0.
  • K4 and X4 are the integral coefficient and sampling value in the 4th sampling cycle respectively.
  • calculation process is just an example of the starting point of the first sampling period as the starting point of the integration time.
  • the calculation method is similar, and will not be repeated here to avoid repetition.
  • the above integral formula is conducive to accurate, fast and reasonable calculation to obtain the integral value corresponding to the i-th sampling period.
  • the preset integral threshold corresponding to the fault parameter includes multiple integral thresholds; when the integral value corresponding to the i-th sampling period is greater than or equal to the preset integral threshold corresponding to the fault parameter, it is determined that the battery cell is faulty , including: when the integral value corresponding to the i-th sampling period is greater than or equal to k integral thresholds among the plurality of integral thresholds, obtain the fault level corresponding to the largest integral threshold among the k integral thresholds, and determine the obtained fault level is the failure level of the failure of the battery cell; where, k is an integer greater than or equal to 1.
  • the multiple integral thresholds included in the preset integral thresholds can be set according to actual needs, and are used to represent different fault levels.
  • a larger integral threshold represents a higher fault level, and a higher fault level indicates a fault. more serious.
  • the BMS After the BMS determines that the battery cell has failed, it can output an alarm message to the vehicle. For example, it can notify the vehicle of the current failure through CAN communication or UDS, warning that the vehicle cannot support full power operation at present, and can request immediate parking when the failure is serious.
  • the fault parameter is current
  • the preset integral thresholds corresponding to the current include: integral threshold 1 (corresponding to primary fault level), integral threshold 2 (corresponding to intermediate fault level), and integral threshold 3 (corresponding to failure level is high).
  • integral threshold 1 corresponding to primary fault level
  • integral threshold 2 corresponding to intermediate fault level
  • integral threshold 3 corresponding to failure level is high.
  • different grades of faults can be reflected by configuring multiple integral thresholds, which is beneficial to achieve different degrees of fault response, and facilitates different degrees of early warning for the same type of fault according to different fault grades.
  • M corresponds to the type of fault parameter and M ⁇ 1, that is, the minimum value of M is 1, the maximum value is 1000, and M is an integer. Since 1 ⁇ i ⁇ M, the minimum end point of the integration time is: the end point of the first sampling period starting from the start point of the integration time length, and the maximum end point of the integration time length is: the first sampling period starting from the start point of the integration time length The end point of the 1000 sample period. Assuming that the sampling period is 10ms, the minimum integration time is 10ms and the maximum is 10s. It can also be understood that the tolerance time corresponding to the fault parameter is in the interval [10ms, 10s].
  • the tolerance time corresponding to the same fault parameter may be different, and for the same battery core, the tolerance time corresponding to different types of fault parameters may also be different.
  • the endurance time can be determined by comprehensively considering the capability of the battery cell and the corresponding fault tolerance time interval (fault tolerant time interval, FTTI for short).
  • 1 ⁇ M ⁇ 1000 so that the calculation can be performed based on the sampling values sampled in one or more complete sampling periods, so as to ensure the validity of the integration.
  • M ⁇ 1000 that is, the integration time will not be too long to ensure that the integration value exceeds the integration threshold in a short time and improve the accuracy of fault detection.
  • the integration duration after integrating the sampling values within the integration duration to obtain the integration value corresponding to the i-th sampling period, it further includes: integrating the preset sampling threshold corresponding to the fault parameter within the integration duration, Obtain the sampling threshold integral value corresponding to the i-th sampling period; calculate the integral difference between the integral value corresponding to the i-th sampling period and the sampling threshold integral value corresponding to the i-th sampling period; when the i-th sampling period corresponds to When the integral value is greater than or equal to the preset integral threshold corresponding to the fault parameter, it is determined that the battery cell is faulty, including: when the integral difference is greater than or equal to the preset integral difference threshold corresponding to the fault parameter, it is determined that the battery cell is faulty.
  • the preset sampling threshold can be set according to actual needs, and different fault parameters can correspond to different preset sampling thresholds.
  • the preset sampling threshold can be understood as the maximum allowable value, and the maximum allowable value can be understood as: in order to ensure the safety of the battery cell, the maximum value of the fault parameter.
  • the preset sampling threshold corresponding to the current can be: to ensure the safety of the cell, the maximum value of the current, and the preset sampling threshold corresponding to the voltage can be: the maximum value of the voltage to ensure the safety of the cell.
  • Integrating the preset sampling threshold corresponding to the fault parameter within the integration time is similar to integrating the sampled value within the integration time. The difference is that the former integrates the preset sampling threshold, while the latter integrates the sampled value. How to integrate the sampled value has been described above, here a similar method can be used to integrate the preset sampling threshold, to avoid repetition, no more details are given here.
  • the integral difference can be calculated by the following formula:
  • Y' is the integral difference
  • X is the sampling value
  • X max is the preset sampling threshold
  • N is the order corresponding to the fault parameter
  • K is the integral coefficient corresponding to the fault parameter.
  • the preset integral difference thresholds corresponding to the above fault parameters may be set according to actual needs. There is a numerical difference between the preset integral threshold corresponding to the fault parameter and the 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 threshold is used to measure whether the integral difference between the integral value corresponding to the i-th sampling period and the sampling threshold integral value corresponding to the i-th sampling period is a value within a safe range, if the integral difference If it is greater than or equal to the preset integral difference threshold corresponding to the fault parameter, it means that the integral difference is no longer within the safe range, and it can be determined that the battery cell is faulty.
  • the integral difference can reflect the possible fault risk caused by the part of the sampling value exceeding the preset sampling threshold.
  • the integral difference may be positive or negative, and the positive and negative difference are considered at the same time, so that when the sampling value fluctuates above and below the preset sampling threshold, the fault can be reset in time, avoiding the need to continuously exceed a certain threshold for a period of time in the prior art. The failure caused by the reset failure is not timely.
  • the BMS obtains the sampling value of the current of the cell within the sampling period, and then uses the following formula to integrate the difference between the sampling value I within the integration time and the maximum allowable value I max of the current to obtain the integral corresponding to the i-th sampling period Difference q':
  • the above formula is used to calculate the integral difference within a certain integration period, that is, the electric quantity q.
  • the actual electric quantity within a certain integral period is greater than or equal to the integral difference threshold corresponding to the current, it is determined that the cell has an overcurrent fault.
  • the general scheme for detecting overcurrent faults is as follows: if the detected current is greater than the overcurrent threshold and the duration is longer than the preset diagnostic judgment time, then it is determined that the cell has an overcurrent fault.
  • the general solution will fail to report faults when the current repeatedly oscillates, because the condition that the current is greater than the overcurrent threshold cannot be continuously met.
  • the integration method using the method of integrating the current within the integration time in this embodiment (referred to as the integration method), if the integrated power q within a certain period of time exceeds the preset integration difference threshold corresponding to the current, it will be determined that the battery cell has Overcurrent fault.
  • the overcurrent threshold in FIG. 3 can be understood as: the preset integral difference threshold corresponding to the current.
  • the time for setting the overcurrent fault is fixed, that is, the overcurrent fault is detected at the same time, as shown in Figure 4.
  • the damage caused by the greater current in the same time should be greater.
  • the calculation formulas of the integral values corresponding to different fault parameters can be pre-stored in the BMS, including: the calculation formulas of the integral values corresponding to the current, the calculation formulas of the integral values corresponding to the voltage, the calculation formulas of the integral values corresponding to the temperature, etc. .
  • the BMS After the BMS obtains the current sampling value, voltage sampling value, and temperature sampling value of the battery cell within the sampling period, it can be directly brought into the corresponding calculation formula to calculate the integral value, so that different fault types can be judged at the same time.
  • multiple integral thresholds representing different fault levels can be set for the same fault type, which is conducive to different degrees of early warning for the same fault type.
  • a fault detection device includes: an acquisition module 601, used to acquire the sampling value of the fault parameter of the cell within the sampling period; an integration module 602, used to calculate the integration time Integrate the sampled values within to obtain the integral value corresponding to the ith sampling period; wherein, i is an integer and 1 ⁇ i ⁇ M, M corresponds to the type of fault parameter and M ⁇ 1; the starting point of the integral duration is The starting point of the sampling period, the end point of the integration duration is the end point of the i sampling period starting from the starting point; the determination module 603 is used for when the integral value corresponding to the i sampling period is greater than or equal to the corresponding preset value of the fault parameter When the integral threshold is set, it is determined that the cell is faulty.
  • this embodiment is an apparatus embodiment corresponding to the above-mentioned method embodiment, and this embodiment can be implemented in cooperation with the above-mentioned method embodiment.
  • the relevant technical details and technical effects mentioned in the foregoing method embodiments are still valid in this embodiment, and will not be repeated here in order to reduce repetition.
  • the relevant technical details mentioned in this embodiment can also be applied to the above method embodiments.
  • modules involved in this embodiment are logical modules.
  • a logical unit can be a physical unit, or a part of a physical unit, or multiple physical units. Combination of units.
  • units that are not closely related to solving the technical problem proposed by the present invention are not introduced in this embodiment, but this does not mean that there are no other units in this embodiment.
  • a battery management system BMS includes: at least one processor 701; and a memory 702 communicatively connected to the at least one processor 701; wherein, the memory 702 stores instructions executable by the at least one processor 701, and the instructions are executed by the at least one processor 701, so that the at least one processor 701 can execute the fault detection method as described above.
  • the memory 702 and the processor 701 are connected by a bus, and the bus may include any number of interconnected buses and bridges, and the bus connects one or more processors 701 and various circuits of the memory 702 together.
  • the bus may also connect together various other circuits such as peripherals, voltage regulators, and power management circuits, all of which are well known in the art and therefore will not be further described herein.
  • the bus interface provides an interface between the bus and the transceivers.
  • a transceiver may be a single element or multiple elements, such as multiple receivers and transmitters, providing means for communicating with various other devices over a transmission medium.
  • the data processed by the processor 701 is transmitted on the wireless medium through the antenna, further, the antenna also 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 also provide various functions including timing, peripheral interface, voltage regulation, power management and other control functions. And the memory 702 may be used to store data used by the processor 701 when performing operations.
  • a computer-readable storage medium storing a computer program.
  • the above method embodiments are implemented when the computer program is executed by the processor.
  • a storage medium includes several instructions to make a device ( It may be a single-chip microcomputer, a chip, etc.) or a processor (processor) to execute all or part of the steps of the methods described in the various embodiments of the present application.
  • the aforementioned storage media include: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic disk or optical disc, etc., which can store program codes. .

Abstract

本申请实施例提供一种故障检测方法、装置、电池管理系统和存储介质。故障检测方法包括：获取采样周期内电芯的故障参数的采样值；对积分时长内的采样值进行积分，得到第i个所述采样周期对应的积分值；其中，i为整数且1≤i≤M，M与所述故障参数的种类对应且M≥1；所述积分时长的起始点为所述采样周期的起始点，所述积分时长的结束点为以所述起始点开始的第i个所述采样周期的结束点；当第i个所述采样周期对应的积分值大于或等于所述故障参数对应的预设积分阈值时，确定所述电芯出现故障，能够及时检测出故障，有利于避免报警不及时的风险。

Description

故障检测方法、装置、电池管理系统和存储介质 技术领域
本申请涉及电池技术领域，特别是涉及一种故障检测方法、装置、电池管理系统和存储介质。
背景技术
当电池管理系统(Battery Management System，简称：BMS)检测到电芯出现故障时需要及时做出相应的诊断，否则极易引发起火、爆炸等安全事故。为了进行故障检测，通常会采用的方式为：当判定项比如当前电流、当前温度、当前电压等超过对应的阈值(条件1)且持续时间超过预设的诊断判定时长(条件2)，则置出故障，如表1所示：
表1
故障 条件1 条件2
电池过流故障 当前电流I>200(A) 持续时间t>10s
电池过温故障 当前温度T>65(DegC) 持续时间t>5s
电池过压故障 当前电压V>4.0(V) 持续时间t>15s
对于同一类型的故障，无论多严苛，诊断判定时长是固定不变的，容易带来报警不及时的风险。
发明内容
鉴于上述问题，本申请提供一种故障检测方法、装置、电池管理系统和存储介质，能够及时检测出故障，有利于避免报警不及时的风险。
第一方面，本申请提供了一种故障检测方法，包括：应用于电池管理系统BMS，包括：获取采样周期内电芯的故障参数的采样值；对积分时长内的采样值进行积分，得到第i个所述采样周期对应的积分值；其中，i为整数且1≤i≤M，M与所述故障参数的种类对应且M≥1；所述积分时长的起始点为所述采样周期的起始点，所述积分时长的结束点为以所述起始点开始的第i个所述采样周期的结束点；当第i个所述采样周期对应的积分值大于或等于所述故障参数对应的预设积分阈值时，确定所述电芯出现故障。
本申请实施例的技术方案中，以采样周期的起始点为积分时长的起始点，以起始点开始的第i个采样周期的结束点为积分时长的结束点，对积分时长内的采样值进行积分，得到第i个采样周期对应的积分值，积分值大于或等于故障参数对应的预设积分阈值，说明电芯在一段时间内积分值过大可能出现故障。当第i个采样周期对应的积分值大于或等于故障参数对应的预设积分阈值时，确定电芯出现故障，说明积分值大于或等于故障参数对应的预设积分阈值时的时间点为置出故障的时间点，即本申请实施例在置出故障时并不以固定的诊断判定时长为判断标准，从而避免了诊断判定时长固定不变时，容易带来报警不及时的风险，有利于及时检测出故障。
在一些实施例中，所述对积分时长内的采样值进行积分，得到第i个所述采样周期对应的积分值，包括：根据所述故障参数对应的积分系数，对积分时长内的采样值进行积分，得到第i个所述采样周期对应的积分值；其中，所述积分系数用于表征所述故障参数对所述电芯的影响程度。
本申请实施例的技术方案中，能够结合故障参数对电芯的影响程度得到积分值，有利于缩短对电芯的影响程度较大的故障的置出时间，即有 利于快速检测出对电芯的影响程度较大的故障。
在一些实施例中，积分系数通过如下公式计算：K＝X/X max，其中，K为所述积分系数，X为所述采样值，X max为所述故障参数对应的预设采样阈值。
本申请实施例的技术方案中，积分系数通过采样值和采样阈值的比值计算得到，由于不同的采样周期中，采样值可能存在差异，因此对于不同的采样周期，积分系数可以是动态变化的，有利于使得积分系数能够体现故障参数的当前采样值对电芯的影响程度。K越大说明故障参数对电芯的影响程度越大，同时K越大也会使得积分值越大，从而随着积分时长的增加积分值能够快速大于或等于预设的积分阈值，以检测出电芯故障，有利于快速检测出对电芯的影响程度较大的故障。
在一些实施例中，所述根据所述故障参数对应的积分系数，对积分时长内的采样值进行积分，得到第i个所述采样周期对应的积分值，包括：通过如下公式计算得到第i个所述采样周期对应的积分值：
Y＝∫K*X Ndt
其中，Y为所述积分值，K为所述积分系数，X为所述采样值，N为所述故障参数对应的阶数。
本申请实施例的技术方案中，通过上述的积分公式有利于准确、快速、合理的计算得到第i个所述采样周期对应的积分值。
在一些实施例中，所述故障参数对应的预设积分阈值包括多个积分阈值；所述当第i个所述采样周期对应的积分值大于或等于所述故障参数对应的预设积分阈值时，确定所述电芯出现故障，包括：当第i个所述采样周期对应的积分值大于或等于所述多个积分阈值中的k个积分阈值，则获取所述k个积分阈值中最大的积分阈值对应的故障等级，并将获取的故障等级确定为所述电芯出现的故障的故障等级；其中，所述k为大于或等 于1的整数。
本申请实施例的技术方案中，通过配置多个积分阈值能够体现不同等级的故障，有利于实现不同程度的故障响应，方便了对同一类型的故障进行不同程度的预警。
在一些实施例中，M≤1000。
本申请实施例的技术方案中，1≤M≤1000，使得能够基于一个或多个完整的采样周期采样的采样值进行计算，确保积分的有效性。M≤1000，即积分时长不会太大，确保积分值是在短时间内超过积分阈值，提高故障检测的准确性。
在一些实施例中，在所述对积分时长内的采样值进行积分，得到第i个所述采样周期对应的积分值之后，还包括：在所述积分时长内对所述故障参数对应的预设采样阈值进行积分，得到第i个所述采样周期对应的采样阈值积分值；计算第i个所述采样周期对应的积分值与第i个所述采样周期对应的采样阈值积分值之间的积分差值；所述当第i个所述采样周期对应的积分值大于或等于所述故障参数对应的预设积分阈值时，确定所述电芯出现故障，包括：当所述积分差值大于或等于所述故障参数对应的预设积分差值阈值时，确定所述电芯出现故障。
本申请实施例的技术方案中，积分差值能够反映采样值超出预设采样阈值的部分可能带来的故障风险。而且积分差值可能有正有负，同时考虑正负差值，使得采样值在预设采样阈值上下波动时，也能及时置出故障，避免现有技术中需要连续超出某个阈值一段时间才置出故障造成的故障置出不及时。
第二方面，本申请提供了一种故障检测装置，包括：获取模块，用于获取采样周期内电芯的故障参数的采样值；积分模块，用于对积分时长 内的采样值进行积分，得到第i个所述采样周期对应的积分值；其中，i为整数且1≤i≤M，M与所述故障参数的种类对应且M≥1；所述积分时长的起始点为所述采样周期的起始点，所述积分时长的结束点为以所述起始点开始的第i个所述采样周期的结束点；确定模块，用于当第i个所述采样周期对应的积分值大于或等于所述故障参数对应的预设积分阈值时，确定所述电芯出现故障。
第三方面，本申请提供了一种电池管理系统BMS，包括：至少一个处理器；以及，与所述至少一个处理器通信连接的存储器；其中，所述存储器存储有可被所述至少一个处理器执行的指令，所述指令被所述至少一个处理器执行，以使所述至少一个处理器能够执行上述的故障检测方法。
第四方面，本申请提供了一种计算机可读存储介质，存储有计算机程序，所述计算机程序被处理器执行时实现上述的故障检测方法。
上述说明仅是本申请技术方案的概述，为了能够更清楚了解本申请的技术手段，而可依照说明书的内容予以实施，并且为了让本申请的上述和其它目的、特征和优点能够更明显易懂，以下特举本申请的具体实施方式。
附图说明
为了更清楚地说明本申请实施例的技术方案，下面将对本申请实施例中所需要使用的附图作简单地介绍，显而易见地，下面所描述的附图仅仅是本申请的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据附图获得其他的附图。
图1为本申请一些实施例提到的故障检测方法的流程示意图；
图2为本申请一些实施例提到的一般方案中过流故障的检测结果示意图；
图3为本申请一些实施例提到的采用积分方式检测过流故障的检测结果示意图；
图4为本申请一些实施例提到的在电流不同的三个场景下采用一般方案检测过流故障的检测结果示意图；
图5为本申请一些实施例提到的在电流不同的三个场景下采用积分方式检测过流故障的检测结果示意图；
图6为本申请一些实施例提到的故障检测装置的示意图；
图7为本申请一些实施例提到的BMS的结构示意图。
具体实施方式
下面结合附图和实施例对本申请的实施方式作进一步详细描述。以下实施例的详细描述和附图用于示例性地说明本申请的原理，但不能用来限制本申请的范围，即本申请不限于所描述的实施例。
在本申请的描述中，需要说明的是，除非另有说明，“多个”的含义是两个以上；术语“上”、“下”、“左”、“右”、“内”、“外”等指示的方位或位置关系仅是为了便于描述本申请和简化描述，而不是指示或暗示所指的装置或元件必须具有特定的方位、以特定的方位构造和操作，因此不能理解为对本申请的限制。此外，术语“第一”、“第二”、“第三”等仅用于描述目的，而不能理解为指示或暗示相对重要性。“垂直”并不是严格意义上的垂直，而是在误差允许范围之内。“平行”并不是严格意义上的平行，而是在误差允许范围之内。
下述描述中出现的方位词均为图中示出的方向，并不是对本申请的具体结构进行限定。在本申请的描述中，还需要说明的是，除非另有明确的规定和限定，术语“安装”、“相连”、“连接”应做广义理解，例如，可以是固定连接，也可以是可拆卸连接，或一体地连接；可以是直接相连，也 可以通过中间媒介间接相连。对于本领域的普通技术人员而言，可视具体情况理解上述术语在本申请中的具体含义。
目前，从市场形势的发展来看，动力电池的应用越加广泛。动力电池不仅被应用于水力、火力、风力和太阳能电站等储能电源系统，而且还被广泛应用于电动自行车、电动摩托车、电动汽车等电动交通工具，以及军事装备和航空航天等多个领域。随着动力电池应用领域的不断扩大，其市场的需求量也在不断地扩增。动力电池中的电芯对动力电池的正常工作起到关键性作用，因此，电芯的故障检测也就显得尤为重要。
本发明人注意到，目前为了进行电芯的故障检测采用的方案多为：当判定项比如当前电流、当前温度、当前电压等超过对应的预设阈值且持续时间超过预设的诊断判定时长，则置出故障，可以参考上述表1。但是如果遇到工况频繁抖动的情况，可能会存在漏报故障的风险(风险1)。并且对于同一类型的故障，无论多严苛，诊断判定时长是固定不变的，这会带来故障报警不够及时的风险(风险2)。
针对上述风险1和风险2，发明人还发现了，针对风险1的一种优化方向是缩小诊断判定时长，但这又会带来故障频繁置出或者误置出的问题；针对风险2的一种优化方向是分多级故障，配不同的阈值和诊断判定时长，但这只能够在一定程度上减小风险，再怎么分级仍然难以囊括所有的故障，不能从根本上解决故障报警不够及时的问题。
基于以上考虑，为了避免上述风险1和风险2，发明人经过深入研究，设计了一种故障检测方法，通过在一定的积分时长内对故障参数的采样值进行积分，当积分值大于或等于预设的积分阈值时，检测出电芯出现故障。即本申请实施例在置出故障时并不以固定的诊断判定时长为判断标准，从而避免了诊断判定时长固定不变时，容易带来报警不及时的风险，有利于及时检测出故障。
本申请实施例公开的故障检测方法，应用于电池管理系统BMS，BMS为一套保护动力电池使用安全的控制系统，时刻监控电池的使用状态，为新能源车辆的使用安全提供保障。
根据本申请的一些实施例，故障检测方法的流程示意图可以参照图 1，包括：
步骤101：获取采样周期内电芯的故障参数的采样值；
步骤102：对积分时长内的采样值进行积分，得到第i个采样周期对应的积分值；
步骤103：当第i个采样周期对应的积分值大于或等于故障参数对应的预设积分阈值时，确定电芯出现故障；
在步骤101中，BMS可以获取采样周期内电芯的故障参数的采样值；其中，采样周期可以为根据实际需要预设的采样周期，比如可以设置为10ms。故障参数可以为用于判断电芯是否故障的参数，比如可以包括但不限于：电流、电压、温度；电流这一故障参数可以用于判断电芯是否出现过流故障，电压这一故障参数可以用于判断电芯是否出现过压故障，温度这一故障参数可以用于判断电芯是否出现过温故障。对应的，故障参数的采样值可以包括但不限于：电流的采样值即电流值、电压的采样值即电压值、温度的采样值即温度值。
电芯的故障参数的采样值可以由一采样装置采样得到，该采样装置可以根据预设的采样周期，对电芯的故障参数进行周期性采集，并将采样得到的采样值发送给BMS，使得BMS可以获取到采样周期内电芯的故障参数的采样值。在具体实现中，BMS可以获取到每个采样周期内电芯的故障参数的采样值。
在步骤102中，i为整数且1≤i≤M，M与故障参数的种类对应且M≥1；积分时长的起始点为采样周期的起始点，积分时长的结束点为以起始点开始的第i个采样周期的结束点。其中，故障参数的种类比如可以为电流类、电压类、温度类等，不同种类的故障参数均对应有M值，根据实际需要，不同种类的故障参数对应的M值可以相同也可以不同。M个采样周期的持续时长可以为故障参数对应的耐受时长，耐受时长可以为在当前危险工况下电芯能够维持安全的容错时间。也就是说，不同种类的故障参数均对应有各自的耐受时长。
BMS可以以每个采样周期的起始点为积分时长的起始点，以起始点开始的第i个采样周期的结束点为积分时长的结束点，对积分时长内的采 样值进行积分，得到第i个采样周期对应的积分值。即每个采样周期的起始点均可以作为积分时长的起始点，使得每个采样周期的采样值都能被充分利用。
在一些实施例中，故障参数可以为电流，在积分时长内对电流的积分值可以为电量。在一些实施例中，故障参数可以为温度，在积分时长内对温度的积分值可以为热量。
在步骤103中，当BMS判定第i个采样周期对应的积分值大于或等于故障参数对应的预设积分阈值时，确定电芯出现故障。其中，积分阈值可以根据实际需要进行设置，不同的故障参数可以对应不同的积分阈值，比如，电流对应的积分阈值可以称为电流积分阈值，电压对应的积分阈值可以称为电压积分阈值，温度对应的积分阈值可以称为温度积分阈值。预设积分阈值用于衡量第i个采样周期对应的积分值是否为一个在安全范围内的值，如果第i个采样周期对应的积分值大于或等于故障参数对应的预设积分阈值，说明第i个采样周期对应的积分值已经不在安全范围内，此时即可确定出电芯出现故障。
在一些实施例中，故障参数为电流，在积分时长内对电流的积分值可以为电量。当BMS判定第i个采样周期对应的电流的积分值(即电量)大于或等于故障参数(电流)对应的预设积分阈值时，确定电芯出现过流故障。
在一些实施例中，故障参数为温度，在积分时长内对温度的积分值可以为热量。当BMS判定第i个采样周期对应的温度的积分值(即热量)大于或等于故障参数(温度)对应的预设积分阈值时，确定电芯出现过温故障。
在一些实施例中，BMS在确定电芯出现故障后，可以向整车输出报警信息，比如可以通过CAN通讯或者通过统一的诊断服务(Unified Diagnostic Services，简称：UDS)通知整车当前出现故障，警示整车当前无法全功率支持运行，以便采取下一步的措施以解除故障。
以采样周期的起始点为积分时长的起始点，以起始点开始的第i个采样周期的结束点为积分时长的结束点，对积分时长内的采样值进行积分， 得到第i个采样周期对应的积分值，积分值大于或等于故障参数对应的预设积分阈值，说明电芯在一段时间内积分值过大可能出现故障。当第i个采样周期对应的积分值大于或等于故障参数对应的预设积分阈值时，确定电芯出现故障，说明积分值大于或等于故障参数对应的预设积分阈值时的时间点为置出故障的时间点，即本申请实施例在置出故障时并不以固定的诊断判定时长为判断标准，从而避免了诊断判定时长固定不变时，容易带来报警不及时的风险，有利于及时检测出故障。
根据本申请的一些实施例，对积分时长内的采样值进行积分，得到第i个采样周期对应的积分值，包括：根据故障参数对应的积分系数，对积分时长内的采样值进行积分，得到第i个采样周期对应的积分值；其中，积分系数用于表征故障参数对电芯的影响程度。
积分系数用于表征故障参数对电芯的影响程度可以理解为：积分系数用来代表不同的故障参数所导致的故障对电芯的危害程度。故障参数对电芯的影响程度越大，该故障参数对应的积分系数可以越大。比如，如果温度所导致的过温故障对电芯的危害程度大于电流所导致的过流故障对电芯的危害程度，则温度对应的积分系数可以大于电流对应的积分系数。
在一些实施例中，针对不同故障参数设置的积分系数可以预先存储在BMS中。
通过结合故障参数对电芯的影响程度即积分系数得到积分值，有利于缩短对电芯的影响程度较大的故障的置出时间，即有利于快速检测出对电芯的影响程度较大的故障。
根据本申请的一些实施例，积分系数通过如下公式计算：K＝X/X max，其中，K为积分系数，X为采样值，X max为故障参数对应的预设采样阈值。
其中，预设采样阈值可以根据实际需要进行设置，不同的故障参数可以对应不同的预设采样阈值。预设采样阈值可以理解为最大允许值，最大允许值可以理解为：为保证电芯安全，故障参数的最大值。比如，电流对应的预设采样阈值可以为：为保证电芯安全，电流的最大值，电压对应的预设采样阈值可以为：为保证电芯安全，电压的最大值。
X max可以预先存储在BMS中，从而当BMS获取到采样值X后，直 接利用上述公式计算得到积分系数。可以理解的是：由于BMS可以获取每个采样周期内电芯的故障参数的采样值，每个采样周期内的采样值大小可能存在波动，因此计算的积分系数可以根据采样值的变化而变化。以过流故障为例，可选择制定K＝I/I max，即K与I成正比例相关，说明采样的电流值越大，对电芯的危害程度越大。
积分系数通过采样值和采样阈值的比值计算得到，由于不同的采样周期中，采样值可能存在差异，因此对于不同的采样周期，积分系数可以是动态变化的，有利于使得积分系数能够体现故障参数的当前采样值对电芯的影响程度。K越大说明故障参数对电芯的影响程度越大，同时K越大也会使得积分值越大，从而随着积分时长的增加积分值能够快速大于或等于预设的积分阈值，以检测出电芯故障，有利于快速检测出对电芯的影响程度较大的故障。
根据本申请的一些实施例，根据故障参数对应的积分系数，对积分时长内的采样值进行积分，得到第i个采样周期对应的积分值，包括：通过如下公式计算得到第i个采样周期对应的积分值：
Y＝∫K*X Ndt
其中，Y为积分值，K为积分系数，X为采样值，N为故障参数对应的阶数。
其中，计算积分值的公式可以预先存储在BMS中，当BMS获取到采样周期内电芯的故障参数的采样值时，将获取到的采样值代入计算积分值的公式中，即可得到第i个采样周期对应的积分值。
N可以为通过故障参数得到目标参数时故障参数的阶数，目标参数可以为故障参数对应的故障类型直接关联的参数。
在一些实施例中，故障参数为电流I，目标参数为电量q，根据公式q＝It，可以看出通过故障参数I得到目标参数q时故障参数I的阶数为1，即I的次方数为1次方，则计算第i个采样周期对应的电流的积分值的公式可以表示如下：
q＝∫K*I 1dt
在一些实施例中，故障参数为温度，目标参数为热量，根据热量的计算公式cm△t，c为比热，m为质量，△t为温度的变化，可以看出，通过温度得到热量时温度的阶数为1，即△t的次方数为1次方。
在一些实施例中，故障参数为电流I，目标参数为热量Q，根据公式Q＝I 2Rt，可以看出通过故障参数I得到目标参数Q时故障参数I的阶数为2，即I的次方数为2次方。
下面以M＝4，采样周期为10ms，N取2为例说明得到第i个采样周期对应的积分值的方式：
第1个采样周期对应的积分值为：
Figure PCTCN2021116136-appb-000001
即，积分时长的起始点为第1个采样周期的起始点0，积分时长的结束点为以起始点0开始的第1个采样周期的结束点10ms。
第2个采样周期对应的积分值为：
Figure PCTCN2021116136-appb-000002
即，积分时长的起始点为第1个采样周期的起始点0，积分时长的结束点为以起始点0开始的第2个采样周期的结束点20ms。K1和X1分别是第1个采样周期中的积分系数和采样值，K2和X2分别是第2个采样周期中的积分系数和采样值。
第3个采样周期对应的积分值为：
Figure PCTCN2021116136-appb-000003
即积分时长的起始点为第1个采样周期的起始点0，积分时长的结束点为以起始点0开始的第3个采样周期的结束点30ms。K3和X3分别是第3个采样周期中的积分系数和采样值。
第4个采样周期对应的积分值为：
Figure PCTCN2021116136-appb-000004
即积分时长的起始点为第1个采样周期的起始点0，积分时长的结束点为 以起始点0开始的第4个采样周期的结束点40ms。K4和X4分别是第4个采样周期中的积分系数和采样值。
需要说明的是，上述计算过程只是以积分时长的起始点为第1个采样周期的起始点为例进行的说明，在具体实现中，以其他时间点作为积分时长的起始点的计算方式与上述计算方式类似，为避免重复，此处不再赘述。
通过上述的积分公式有利于准确、快速、合理的计算得到第i个所述采样周期对应的积分值。
根据本申请的一些实施例，故障参数对应的预设积分阈值包括多个积分阈值；当第i个采样周期对应的积分值大于或等于故障参数对应的预设积分阈值时，确定电芯出现故障，包括：当第i个采样周期对应的积分值大于或等于多个积分阈值中的k个积分阈值，则获取k个积分阈值中最大的积分阈值对应的故障等级，并将获取的故障等级确定为电芯出现的故障的故障等级；其中，k为大于或等于1的整数。
其中，预设积分阈值包括的多个积分阈值可以根据实际需要设定，用于表征不同的故障等级，多个积分阈值中越大的积分阈值表征的故障等级越高，故障等级越高即表明故障越严重。BMS在确定电芯出现故障后，可以向整车输出报警信息，比如可以通过CAN通讯或者通过UDS通知整车当前出现故障，警示整车当前无法全功率支持运行，故障严重时可以要求立即停车。
比如，故障参数为电流，电流对应的预设积分阈值包括：依次增大的积分阈值1(对应的故障等级为初级)、积分阈值2(对应的故障等级为中级)、积分阈值3(对应的故障等级为高级)。当第i个采样周期对应的积分值大于或等于3个积分阈值中的2个积分阈值(比如为积分阈值2和积分阈值3)，则获取积分阈值2和积分阈值3中最大的积分阈值对应的故障等级，即获取积分阈值3对应的故障等级，将积分阈值3对应的故障等级确定为电芯出现的故障的故障等级，也就是说，检测出电芯出现了高级的过流故障。
本实施例中，通过配置多个积分阈值能够体现不同等级的故障，有 利于实现不同程度的故障响应，方便了对同一类型的故障根据不同的故障等级进行不同程度的预警。
根据本申请的一些实施例，M≤1000。
M与故障参数的种类对应且M≥1，即M的最小取值为1，最大取值为1000，M为整数。由于1≤i≤M，即积分时长的结束点最小为：以积分时长的起始点开始的第1个采样周期的结束点，积分时长的结束点最大为：以积分时长的起始点开始的第1000个采样周期的结束点。假设，采样周期为10ms，则积分时长最小为10ms，最大为10s。还可以理解为，故障参数对应的耐受时长处于区间[10ms，10s]。在具体实现中，对于不同种类的电芯来说，同一种故障参数对应的耐受时长可能存在差异，对于同一种电芯来说，不同种类的故障参数对应的耐受时长也可能存在差异，耐受时长可以综合考虑电芯的能力和对应的故障容忍时间间隔(fault tolerant time interval，简称：FTTI)来确定。
本实施例中，1≤M≤1000，使得能够基于一个或多个完整的采样周期采样的采样值进行计算，确保积分的有效性。M≤1000，即积分时长不会太大，确保积分值是在短时间内超过积分阈值，提高故障检测的准确性。
根据本申请的一些实施例，在对积分时长内的采样值进行积分，得到第i个采样周期对应的积分值之后，还包括：在积分时长内对故障参数对应的预设采样阈值进行积分，得到第i个采样周期对应的采样阈值积分值；计算第i个采样周期对应的积分值与第i个采样周期对应的采样阈值积分值之间的积分差值；当第i个采样周期对应的积分值大于或等于故障参数对应的预设积分阈值时，确定电芯出现故障，包括：当积分差值大于或等于故障参数对应的预设积分差值阈值时，确定电芯出现故障。
其中，预设采样阈值可以根据实际需要进行设置，不同的故障参数可以对应不同的预设采样阈值。预设采样阈值可以理解为最大允许值，最大允许值可以理解为：为保证电芯安全，故障参数的最大值。比如，电流对应的预设采样阈值可以为：为保证电芯安全，电流的最大值，电压对应的预设采样阈值可以为：为保证电芯安全，电压的最大值。
在积分时长内对故障参数对应的预设采样阈值进行积分，与对积分 时长内的采样值进行积分的方式类似，区别在于，前者对预设采样阈值进行积分，后者对采样值进行积分。上文中已经描述过如何对采样值进行积分，这里可以采用类似的方式对预设采样阈值进行积分，为避免重复，此处不再赘述。
在一些实施例中，可以通过如下公式计算积分差值：
Y′＝∫K*(X-X max) Ndt
其中，Y′为积分差值，X为采样值，X max为预设采样阈值，N为故障参数对应的阶数，K为故障参数对应的积分系数。
上述的故障参数对应的预设积分差值阈值，可以根据实际需要进行设定。故障参数对应的预设积分阈值和故障参数对应的预设积分差值阈值之间存在数值上的差异，预设积分阈值大于预设积分差值阈值。预设积分差值阈值用于衡量第i个采样周期对应的积分值与第i个采样周期对应的采样阈值积分值之间的积分差值是否为一个在安全范围内的值，如果积分差值大于或等于故障参数对应的预设积分差值阈值，说明积分差值已经不在安全范围内，此时即可确定出电芯出现故障。
积分差值能够反映采样值超出预设采样阈值的部分可能带来的故障风险。而且积分差值可能有正有负，同时考虑正负差值，使得采样值在预设采样阈值上下波动时，也能及时置出故障，避免现有技术中需要连续超出某个阈值一段时间才置出故障造成的故障置出不及时。
下面以故障参数是电流为例，对本申请一些实施例中的故障检测方法进行说明：
BMS获取采样周期内电芯的电流的采样值，然后采用如下公式对积分时长内的采样值I和电流的最大允许值I max之间的差值进行积分，得到第i个采样周期对应的积分差值q'：
q′＝∫K*(I-I max) 1dt
本实施例中通过上述公式计算在一定积分时长内的积分差值即电量q，当一定积分时长内的实际电量大于或等于电流对应的积分差值阈值，则确定电芯出现过流故障。检测过流故障的一般方案为：检测到电流大于过流阈值，且持续时间大于预设的诊断判定时长，则确定电芯出现过流故 障。而一般方案针对电流反复震荡的情况会漏报故障，因为无法持续满足电流大于过流阈值这个条件。而本实施例中通过积分的方式则不存在漏报故障的问题。
参考图2，当电流在过流阈值附近震荡，由于无法持续满足电流大于过流阈值这个条件，一般方案不会检测出过流故障。
参考图3，采用本实施例中在积分时长内对电流积分的方式(简称积分方式)，在一定时间内积分得到的电量q超过电流对应的预设积分差值阈值，就会确定电芯出现过流故障。图3中的过流阈值即可以理解为：电流对应的预设积分差值阈值。
另外，上述一般方案中，在电流不同的三个场景即I1、I2、I3下，置出过流故障的时间是固定的，即均在同一个时间检测出过流故障，可参考图4。但实际上，越大的电流在相同的时间内带来的损害应该是更大的。本实施例中，在积分时，还考虑到积分系数K，K代表电流对电芯的影响程度、危害程度，设定K＝I/I max，即K与I成正比例相关，侧面说明当前的电流越大，K越大，则对电芯的危害程度越大。参考图5，采用本实施例中的积分方式进行故障检测，在电流不同的三个场景即I1、I2、I3下，电流带来的损害越大，置出故障的时间越短。图5中，电流最大的I3带来的损害最大，因此最早在T3时刻被检测出过流故障，电流为I2的场景下在T2时刻被检测出过流故障，电流为I1的场景下在T1时刻被检测出过流故障。
在一些实施例中，BMS中可以预存不同故障参数对应的积分值的计算公式，包括：电流对应的积分值的计算公式、电压对应的积分值的计算公式、温度对应的积分值的计算公式等。BMS在获取到采样周期内电芯的电流采样值、电压采样值、温度采样值后，可以直接带入对应的计算公式中计算积分值，从而可以同时进行不同故障类型的判断。并且，同一故障类型还可以设置多个表征不同故障等级的积分阈值，从而有利于对同一故障类型进行不同程度的预警。
根据本申请的一些实施例，提供了一种故障检测装置，参考图6，包括：获取模块601，用于获取采样周期内电芯的故障参数的采样值；积 分模块602，用于对积分时长内的采样值进行积分，得到第i个所述采样周期对应的积分值；其中，i为整数且1≤i≤M，M与故障参数的种类对应且M≥1；积分时长的起始点为采样周期的起始点，积分时长的结束点为以起始点开始的第i个采样周期的结束点；确定模块603，用于当第i个采样周期对应的积分值大于或等于故障参数对应的预设积分阈值时，确定电芯出现故障。
不难发现，本实施例为与上述方法实施例相对应的装置实施例，本实施例可与上述方法实施例互相配合实施。上述方法实施例中提到的相关技术细节和技术效果在本实施例中依然有效，为了减少重复，这里不再赘述。相应地，本实施例中提到的相关技术细节也可应用在上述方法实施例中。
值得一提的是，本实施例中所涉及到的各模块均为逻辑模块，在实际应用中，一个逻辑单元可以是一个物理单元，也可以是一个物理单元的一部分，还可以以多个物理单元的组合实现。此外，为了突出本发明的创新部分，本实施例中并没有将与解决本发明所提出的技术问题关系不太密切的单元引入，但这并不表明本实施例中不存在其它的单元。
根据本申请的一些实施例，提供了一种电池管理系统BMS，参考图7，包括：至少一个处理器701；以及，与所述至少一个处理器701通信连接的存储器702；其中，所述存储器702存储有可被所述至少一个处理器701执行的指令，所述指令被所述至少一个处理器701执行，以使所述至少一个处理器701能够执行如上述的故障检测方法。
其中，存储器702和处理器701采用总线方式连接，总线可以包括任意数量的互联的总线和桥，总线将一个或多个处理器701和存储器702的各种电路连接在一起。总线还可以将诸如外围设备、稳压器和功率管理电路等之类的各种其他电路连接在一起，这些都是本领域所公知的，因此，本文不再对其进行进一步描述。总线接口在总线和收发机之间提供接口。
收发机可以是一个元件，也可以是多个元件，比如多个接收器和发送器，提供用于在传输介质上与各种其他装置通信的单元。经处理器701处理的 数据通过天线在无线介质上进行传输，进一步，天线还接收数据并将数据传送给处理器701。
处理器701负责管理总线和通常的处理，还可以提供各种功能，包括定时，外围接口，电压调节、电源管理以及其他控制功能。而存储器702可以被用于存储处理器701在执行操作时所使用的数据。
根据本申请的一些实施例，提供了一种计算机可读存储介质，存储有计算机程序。计算机程序被处理器执行时实现上述方法实施例。
即，本领域技术人员可以理解，实现上述实施例方法中的全部或部分步骤是可以通过程序来指令相关的硬件来完成，该程序存储在一个存储介质中，包括若干指令用以使得一个设备(可以是单片机，芯片等)或处理器(processor)执行本申请各个实施例所述方法的全部或部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(ROM，Read-Only Memory)、随机存取存储器(RAM，Random Access Memory)、磁碟或者光盘等各种可以存储程序代码的介质。
最后应说明的是：以上各实施例仅用以说明本申请的技术方案，而非对其限制；尽管参照前述各实施例对本申请进行了详细的说明，本领域的普通技术人员应当理解：其依然可以对前述各实施例所记载的技术方案进行修改，或者对其中部分或者全部技术特征进行等同替换；而这些修改或者替换，并不使相应技术方案的本质脱离本申请各实施例技术方案的范围，其均应涵盖在本申请的权利要求和说明书的范围当中。尤其是，只要不存在结构冲突，各个实施例中所提到的各项技术特征均可以任意方式组合起来。本申请并不局限于文中公开的特定实施例，而是包括落入权利要求的范围内的所有技术方案。

Claims (10)

  1. 一种故障检测方法，应用于电池管理系统BMS，包括：
    获取采样周期内电芯的故障参数的采样值；
    对积分时长内的采样值进行积分，得到第i个所述采样周期对应的积分值；其中，i为整数且1≤i≤M，M与所述故障参数的种类对应且M≥1；所述积分时长的起始点为所述采样周期的起始点，所述积分时长的结束点为以所述起始点开始的第i个所述采样周期的结束点；
    当第i个所述采样周期对应的积分值大于或等于所述故障参数对应的预设积分阈值时，确定所述电芯出现故障。
  2. 根据权利要求1所述的故障检测方法，其中，所述对积分时长内的采样值进行积分，得到第i个所述采样周期对应的积分值，包括：
    根据所述故障参数对应的积分系数，对积分时长内的采样值进行积分，得到第i个所述采样周期对应的积分值；其中，所述积分系数用于表征所述故障参数对所述电芯的影响程度。
  3. 根据权利要求2所述的故障检测方法，其中，所述积分系数通过如下公式计算：
    K＝X/X max，其中，K为所述积分系数，X为所述采样值，X max为所述故障参数对应的预设采样阈值。
  4. 根据权利要求2或3所述的故障检测方法，其中，所述根据所述故障参数对应的积分系数，对积分时长内的采样值进行积分，得到第i个所述采样周期对应的积分值，包括：
    通过如下公式计算得到第i个所述采样周期对应的积分值：
    Y＝∫K*X Ndt
    其中，Y为所述积分值，K为所述积分系数，X为所述采样值，N为 所述故障参数对应的阶数。
  5. 根据权利要求1至4任一项所述的故障检测方法，其中，所述故障参数对应的预设积分阈值包括多个积分阈值；
    所述当第i个所述采样周期对应的积分值大于或等于所述故障参数对应的预设积分阈值时，确定所述电芯出现故障，包括：
    当第i个所述采样周期对应的积分值大于或等于所述多个积分阈值中的k个积分阈值，则获取所述k个积分阈值中最大的积分阈值对应的故障等级，并将获取的故障等级确定为所述电芯出现的故障的故障等级；其中，所述k为大于或等于1的整数。
  6. 根据权利要求1至5任一项所述的故障检测方法，其中，M≤1000。
  7. 根据权利要求1所述的故障检测方法，其中，在所述对积分时长内的采样值进行积分，得到第i个所述采样周期对应的积分值之后，还包括：
    在所述积分时长内对所述故障参数对应的预设采样阈值进行积分，得到第i个所述采样周期对应的采样阈值积分值；
    计算第i个所述采样周期对应的积分值与第i个所述采样周期对应的采样阈值积分值之间的积分差值；
    所述当第i个所述采样周期对应的积分值大于或等于所述故障参数对应的预设积分阈值时，确定所述电芯出现故障，包括：
    当所述积分差值大于或等于所述故障参数对应的预设积分差值阈值时，确定所述电芯出现故障。
  8. 一种故障检测装置，包括：
    获取模块，用于获取采样周期内电芯的故障参数的采样值；
    积分模块，用于对积分时长内的采样值进行积分，得到第i个所述采样周期对应的积分值；其中，i为整数且1≤i≤M，M与所述故障参数的种类对应且M≥1；所述积分时长的起始点为所述采样周期的起始点，所述积 分时长的结束点为以所述起始点开始的第i个所述采样周期的结束点；
    确定模块，用于当第i个所述采样周期对应的积分值大于或等于所述故障参数对应的预设积分阈值时，确定所述电芯出现故障。
  9. 一种电池管理系统BMS，包括：
    至少一个处理器；以及，
    与所述至少一个处理器通信连接的存储器；其中，
    所述存储器存储有可被所述至少一个处理器执行的指令，所述指令被所述至少一个处理器执行，以使所述至少一个处理器能够执行如权利要求1至7中任一所述的故障检测方法。
  10. 一种计算机可读存储介质，存储有计算机程序，所述计算机程序被处理器执行时实现权利要求1至7中任一项所述的故障检测方法。
PCT/CN2021/116136 2021-09-02 2021-09-02 故障检测方法、装置、电池管理系统和存储介质 WO2023028934A1 (zh)

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