Monitoring method and monitoring device for monitoring DC resistance of battery

Abstract

The invention provides a monitoring method for monitoring the direct current resistance of a battery. The monitoring method comprises the following steps of: S1, acquiring a discharge starting voltage and a discharge starting current of the battery before discharging and a discharge ending voltage and a discharge ending current of the battery after discharging; a preliminary determination step S2 of determining a DC resistance measurement value of the battery according to the discharge start voltage, the discharge end voltage, the discharge start current and the discharge end current; and a correction step S3, correcting the DC resistance measurement value according to the discharge end current based on correlation information representing the correlation between the current at the discharge end and the DC resistance so as to determine the corrected DC resistance. The invention further provides a corresponding monitoring device and a computer program product. By means of the application, the direct current resistance of the battery can be monitored more accurately.

Description

Technical Field

[0001] The present application relates to the field of batteries, and particularly to a monitoring method for monitoring the direct current resistance of a battery, a monitoring device, and a computer program product. Background Art

[0002] With the development of energy storage technology, in recent years, batteries have been widely used in various fields. For example, lithium-ion batteries are widely used as power batteries in vehicles. The reliability, stability, and service life of the battery directly affect the performance of the vehicle.

[0003] The direct current resistance (DCR) is a key parameter of the battery, which has a significant impact on the power output, energy efficiency, and other performance indicators of the battery. During the operation of the battery, especially in the case of battery aging, it is particularly important to accurately obtain the DCR. Because the aging process will significantly change the resistance characteristics of the battery, thereby affecting its overall performance. Real-time monitoring and accurate calculation of DCR are one of the core functions of the battery management system (BMS), aiming to ensure the optimal working state of the battery and extend its service life.

[0004] In the existing battery management system, the DCR can be calculated by controlling the battery discharge and measuring the voltage change ΔV and the current change ΔI. Specifically, the DCR can be calculated according to the following formula: DCR = ΔV / ΔI. Using the calculated DCR, the BMS can evaluate the resistance characteristics of the battery in real time, providing an important basis for the health management and performance optimization of the battery. However, in practice, the battery may face variable working conditions. This makes the measured DCR inaccurate or unable to accurately reflect the resistance characteristics of the battery.

[0005] Therefore, there are still deficiencies in the prior art in the monitoring of the direct current resistance of the battery. Summary of the Invention

[0006] The purpose of the present application is to provide an improved monitoring method for monitoring the direct current resistance of a battery, and a corresponding monitoring device and computer program product, so as to at least partially overcome the deficiencies of the prior art.

[0007] According to a first aspect of the present application, there is provided a monitoring method for monitoring the direct current resistance of a battery. The monitoring method includes the following steps: an acquisition step S1 of acquiring the discharge start voltage and discharge start current of the battery before discharge and the discharge end voltage and discharge end current at the end of discharge; a preliminary determination step S2 of determining a measured value of the direct current resistance of the battery according to the discharge start voltage, discharge end voltage, discharge start current, and discharge end current; and a correction step S3 of correcting the measured value of the direct current resistance according to the discharge end current based on the correlation information representing the correlation between the current at the end of discharge and the direct current resistance to determine the corrected direct current resistance.

[0008] By using the correlation information to correct the DC resistance measurement value, the DC resistance of the battery can be monitored more accurately. The corrected DC resistance can be further used to analyze the state of the battery. For example, by comparing the corrected DC resistance based on a unified end-of-discharge current, the state of health of the battery can be evaluated more accurately and / or it can be determined whether the battery is abnormal.

[0009] In an exemplary embodiment, the monitoring method further includes an association step S4. In the association step S4, correlation information can be generated based on multiple sets of monitoring data of the battery, wherein each set of monitoring data includes a DC resistance measurement value determined by means of the discharge process of the battery and the corresponding end-of-discharge current. The multiple sets of monitoring data have at least two different end-of-discharge currents. Thus, the correlation information can be not limited to being pre-calibrated and stored. Instead, for example, the BMS can generate the correlation information in an online manner.

[0010] In an exemplary embodiment, the monitoring method further includes an evaluation step S5. In the evaluation step S5, the effectiveness of the current correlation information is evaluated based on the corrected DC resistance, and it is determined whether it is necessary to execute the association step S4 to generate new correlation information according to the effectiveness. This helps to ensure the adaptability of the correlation information to the battery.

[0011] In an exemplary embodiment, in the evaluation step S5, the effectiveness of the current correlation information is evaluated in the following manner: obtaining a plurality of corrected DC resistances determined based on the current correlation information; determining the deviation between the plurality of corrected DC resistances; and if the deviation is greater than a predetermined deviation threshold, evaluating that the correlation information is no longer effective.

[0012] In an exemplary embodiment, the plurality of corrected DC resistances are the corrected DC resistances determined during the same operating cycle of the battery. Thus, the situation where the correlation information does not match the battery can be identified more accurately.

[0013] Alternatively or additionally, the plurality of corrected DC resistances are the corrected DC resistances determined within a predetermined time period. This also helps to accurately identify the situation where the correlation information does not match the battery.

[0014] In an exemplary embodiment, the plurality of corrected DC resistances are the corrected DC resistances corrected based on the same end-of-discharge current.

[0015] In an exemplary embodiment, if it is determined in the evaluation step S5 that the association step S4 needs to be executed, the association step S4 is executed using the DC resistance measurement values corresponding to the plurality of corrected DC resistances and the end-of-discharge current as at least a part of the multiple sets of monitoring data. Thus, the evaluation step S5 and the association step S4 can be executed using the monitoring data measured during the operation of the battery. There is no need to additionally discharge the battery to execute the association step S4. This enables the association step S4 to be executed immediately after the evaluation step S5. Thus, the association step S4 can be executed conveniently and at low cost.

[0016] In an exemplary embodiment, the association step S4 includes the following sub-steps: a preparation step S41 of obtaining the start-of-discharge voltage and the start-of-discharge current of the battery before discharge; a discharge step S42 of discharging the battery at a predetermined constant current and obtaining the end-of-discharge voltage and the end-of-discharge current of the battery after discharge; and a generation step S43 of determining the DC resistance measurement value of the battery according to the start-of-discharge voltage and the start-of-discharge current of the battery before discharge and the end-of-discharge voltage and the end-of-discharge current of the battery after discharge, so as to generate association information using the DC resistance measurement value and the corresponding end-of-discharge current. In the association step S4, the discharge step S42 is executed at least twice with different end-of-discharge currents to obtain the multiple sets of monitoring data.

[0017] In an exemplary embodiment, the association information is used to represent a negative correlation between the current at the end of discharge and the DC resistance.

[0018] In an exemplary embodiment, the association information is used to represent a linear relationship between the current at the end of discharge and the DC resistance.

[0019] In an exemplary embodiment, the association information is used to represent a quadratic function relationship between the current at the end of discharge and the DC resistance.

[0020] According to a second aspect of the present application, there is provided a monitoring device, which includes a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor can execute the monitoring method according to the present application.

[0021] According to a third aspect of the present application, there is provided a computer program product, which includes computer program instructions, wherein when the computer program instructions are executed by one or more processors, the one or more processors can execute the monitoring method according to the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Next, the present application will be described in more detail by referring to the accompanying drawings, and the principles, features and advantages of the present application can be better understood. The accompanying drawings include:

[0023] Figure 1 Schematically shows a flowchart of a monitoring method for monitoring the DC resistance of a battery according to an exemplary embodiment of the present application;

[0024] Figure 2 Schematically shows the DC resistance and discharge current measured by experiments;

[0025] Figure 3 Schematically shows a vehicle according to an exemplary embodiment of the present application;

[0026] Figure 4 Schematically shows a flowchart of a monitoring method according to an exemplary embodiment of the present application;

[0027] Figure 5 Schematically shows a flowchart of a monitoring method according to an exemplary embodiment of the present application;

[0028] Figure 6 Schematically shows the evaluation steps of a monitoring method according to an exemplary embodiment of the present application; and

[0029] Figure 7 Schematically shows a flowchart of the association step of a monitoring method according to an exemplary embodiment of the present application.

[0030] List of reference numerals

[0031] 1 Vehicle

[0032] 3 Power battery

[0033] 5 Monitoring device

[0034] 7 Voltage sensor

[0035] 9 Current sensor Detailed description of the invention

[0036] In order to make the technical problems to be solved, technical solutions and beneficial technical effects of the present application clearer, the present application will be further described in detail below with reference to the drawings and multiple exemplary embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application, rather than to limit the protection scope of the present application.

[0037] Figure 1 Schematically shows a flowchart of a monitoring method for monitoring the DC resistance of a battery according to an exemplary embodiment of the present application.

[0038] The battery to be monitored is, for example, a lithium-ion battery. The battery is, for example, a power battery for a vehicle. It should be understood, however, that the monitoring method according to the present application can also be applied to batteries of other types and / or for other uses. For example, the battery can be a lead-acid battery. In addition, the battery can also be used to power an aircraft or a ship, etc.

[0039] As Figure 1 shown, the monitoring method includes an acquisition step S1, a preliminary determination step S2, and a correction step S3.

[0040] In the acquisition step S1, the discharge start voltage and discharge start current of the battery before discharge and the discharge end voltage and discharge end current at the end of discharge are acquired.

[0041] In the preliminary determination step S2, a measured value of the DC resistance of the battery is determined based on the discharge start voltage, the discharge end voltage, the discharge start current, and the discharge end current. Optionally, in the preliminary determination step S2, the measured value of the DC resistance of the battery is determined according to DCR_M = (V1 - V0) / (I1 - I0), where DCR_M represents the measured value of the DC resistance, V0 represents the discharge start voltage, V1 represents the discharge end voltage, I0 represents the discharge start current, and I1 represents the discharge end current.

[0042] In the correction step S3, the measured value of the DC resistance is corrected according to the discharge end current based on the correlation information representing the correlation between the current at the end of discharge and the DC resistance to determine the corrected DC resistance.

[0043] By the monitoring method according to the present application, the DC resistance of the battery can be monitored more accurately.

[0044] In the existing monitoring methods, usually the measured value of the DC resistance determined based on the discharge start voltage, the discharge end voltage, the discharge start current, and the discharge end current is directly used as the monitoring result, and the state of the battery is analyzed based on the measured value of the DC resistance. This monitoring method does not consider the influence of the current on the DC resistance, resulting in the monitoring result obtained not being able to accurately reflect the state of the battery.

[0045] The inventor considered that there might be a correlation between the current and the DC resistance, and verified the correlation between the current at the end of discharge and the DC resistance through experiments. The experiment is briefly described below.

[0046] First, the battery to be tested is placed in an environment of 25 °C, and its state of charge (SOC) is adjusted to 15%. The battery is especially left standing for a sufficient long time to ensure the stability of the battery state. The open circuit voltage (OCV) at this time is recorded as V 0 .

[0047] Then, the battery is discharged at different discharge currents. Optionally, the battery is discharged at different discharge rates (also known as discharge C-rates). The discharge duration is, for example, 10 s. Record the discharge current and the voltage at the end of discharge.

[0048] Here, the voltages of the battery are recorded as V 1 and V 10 .

[0049] According to the formula DCR 1 =(V 1 -V 0 ) / I and DCR 10 =(V 10 -V 0 ) / I, calculate the DC resistances for discharge durations of 1 s and 10 s, where I represents the discharge current.

[0050] Figure 2 Schematically shows the DC resistance and the discharge current measured through the above experiment. In Figure 2 , the abscissa represents the discharge current (expressed in discharge C-rates), and the ordinate represents the calculated DC resistance. The square data points represent the data measured at a discharge duration of 1 s. It can be seen that the DC resistance of the battery measured is different at different discharge rates. In this experiment, the DC resistance of the battery decreases with the increase of the discharge rate. The circular data points represent the data measured at a discharge duration of 10 s. This set of data shows a similar trend of change as the data measured at a discharge duration of 1 s.

[0051] Through the above experiment, it can be verified that there is a correlation between DCR and current. Even at the same state of charge and temperature, DCR will change with the change of current. This correlation makes it complicated to accurately determine DCR under operating conditions (such as the working conditions commonly found in electric vehicles).

[0052] In addition, through the above experiment or a similar experiment, the correlation between DCR and the end-of-discharge current can also be calibrated. Thus, the corresponding correlation information can be generated.

[0053] For example, referring to Figure 2 , a linear fit can be performed on the DC resistance and the discharge current measured in the case of a discharge duration of 1 s. Optionally, the least squares method can be used to perform a linear fit on the DC resistance and the discharge current. For example, the ordinary least squares method or the weighted least squares method, etc. can be used. In another embodiment, other linear fitting methods can also be adopted. In Figure 2In it, a linear function obtained by linearly fitting the DC resistance and discharge current measured at a discharge duration of 1 s is depicted by a dotted line, and a linear function obtained by linearly fitting the DC resistance and discharge current measured at a discharge duration of 10 s is depicted by a dashed line.

[0054] Thus, a linear function representing the correlation between the DC resistance and the discharge current can be determined. The linear function can be expressed as DCR = k*I + b. The parameters k and b of the linear function can be calibrated as at least part of the correlation information for use in the monitoring method according to the present application.

[0055] According to the monitoring method of the present application, the correlation information can be used to correct the DC resistance measurement value to determine the corrected DC resistance. The corrected DC resistance can be further used to analyze the state of the battery. For example, by comparing the corrected DC resistances based on a unified discharge end current, the battery health state can be evaluated more accurately and / or it can be determined whether the battery is abnormal.

[0056] For example, according to the correlation information, the DC resistance measurement value can be corrected to the corrected DC resistance at the reference current according to the following formula: DCR_C = DCR_M + f(I_R - I), where DCR_C represents the corrected DC resistance, DCR_M represents the DC resistance measurement value, I_R represents the reference current, and I represents the discharge end current corresponding to the DC resistance measurement value.

[0057] As an example, in the case where the linear function DCR = k*I + b is used to represent the correlation between the DC resistance and the discharge current, the corrected DC resistance can be obtained by the following formula: DCR_C = DCR_M + k*(I_R - I).

[0058] As described above, according to an exemplary embodiment of the present application, the correlation information can be used to represent the linear relationship between the current at the end of discharge and the DC resistance.

[0059] Optionally, the correlation information can be used to represent the quadratic function relationship between the current at the end of discharge and the DC resistance. For some batteries, the quadratic function relationship can more accurately represent the correlation between the current at the end of discharge and the DC resistance. For example, the quadratic function relationship can be expressed as DCR = a*I 2 + b*I + c.

[0060] According to an exemplary embodiment of the present application, the correlation information can be selectively used to represent the linear relationship or the quadratic function relationship between the current at the end of discharge and the DC resistance. For example, according to the goodness of fit of the linear relationship and the quadratic function relationship, one of the linear relationship and the quadratic function relationship can be selected to represent the correlation between the current at the end of discharge and the DC resistance.

[0061] According to an exemplary embodiment of the present application, the correlation information can be used to represent a negative correlation between the current at the end of discharge and the DC resistance.

[0062] Figure 3 Schematically shown is a vehicle 1 according to an exemplary embodiment of the present application. The vehicle 1 is an electric vehicle equipped with a power battery 3. The power battery 3 may include a plurality of battery cells. The vehicle 1 is further provided with a monitoring device 5, which can be used to monitor the state of the power battery 3.

[0063] The monitoring device 5 includes a memory and a processor. Among them, the memory stores a computer program. When the computer program is executed by the processor, the processor can execute the monitoring method according to an exemplary embodiment of the present application. The computer program instructions can be stored in a computer-readable storage medium. The computer-readable storage medium may, for example, include a high-speed random access memory, and may also include a non-volatile memory or a volatile solid-state storage device. The processor may be a central processing unit, or may also be other general-purpose processors, digital signal processors, application-specific integrated circuits, off-the-shelf programmable gate arrays, or other programmable logic devices, etc. It should be understood that the features and advantages described herein for the monitoring method also apply to the monitoring device 5, and vice versa.

[0064] The monitoring method according to the present application can be used to monitor individual battery cells of the power battery 3 separately. This monitoring method can also be used to monitor a battery module or a battery pack including a plurality of battery cells.

[0065] The monitoring device 5 can in particular be implemented as part of a battery management system. For example, the monitoring device 5 can be implemented as a battery monitoring unit (BMU) and / or a main control unit (MCU) of the battery management system or integrated into the battery monitoring unit and / or the main control unit. The battery management system may further include a voltage sensor 7, a current sensor 9, a temperature sensor, a communication interface, etc.

[0066] According to an exemplary embodiment of the present application, the discharge start voltage and the discharge end voltage can be detected by means of the voltage sensor 7, for example. The discharge start current and the discharge end current can be detected by means of the current sensor 9, for example. The detection results of the voltage sensor 7 and / or the current sensor 9 can be transmitted to the monitoring device 5 for calculating the DC resistance measurement value and correcting the DC resistance.

[0067] In an exemplary embodiment according to the present application, the correlation information can be pre-calibrated through experiments and stored, for example, in the memory of the monitoring device 5.

[0068] Figure 4 Schematically shown is a flowchart of the monitoring method according to an exemplary embodiment of the present application. And Figure 1Similar to the embodiments shown, the monitoring method includes an acquisition step S1, a preliminary determination step S2, and a correction step S3. The acquisition step S1, the preliminary determination step S2, and the correction step S3 can be performed in the manner described above and will not be elaborated here.

[0069] In Figure 4 the embodiments shown, the monitoring method may further include an association step S4. In the association step S4, according to multiple sets of monitoring data of the battery, association information is generated, where each set of monitoring data includes a DC resistance measurement value determined by means of the discharge process of the battery and the corresponding end-of-discharge current. The multiple sets of monitoring data have at least two different end-of-discharge currents.

[0070] Thus, the association information may not be limited to being pre-calibrated and stored. Instead, for example, the BMS can generate the association information in an online manner.

[0071] As an example, the association information can be pre-calibrated and stored in a memory before the battery is used in a vehicle. After the battery is used in a vehicle, the association information can also be updated in an online manner. After the battery has been used for a period of time, its characteristics may change. The pre-calibrated association information may no longer accurately adapt to the battery. The updated association information can more accurately represent the characteristics of the battery. Thus, a more accurate corrected DC resistance can be obtained.

[0072] Alternatively, the pre-calibration of the association information can also be omitted, and the association information can be directly generated in an online manner.

[0073] The association step S4 can be performed periodically, for example. The period of the association step S4 can be measured in natural time or in terms of the working time of the battery. For example, one year after the electric vehicle first uses the battery and / or after the cumulative working time of the electric vehicle's battery reaches 500 h, the BMS can determine that the association step S4 needs to be performed to update the association information.

[0074] Figure 5 Schematically shows a flowchart of the monitoring method according to an exemplary embodiment of the present application. Similar to Figure 1 the embodiments shown, the monitoring method includes an acquisition step S1, a preliminary determination step S2, and a correction step S3. The acquisition step S1, the preliminary determination step S2, and the correction step S3 can be performed in the manner described above and will not be elaborated here.

[0075] In Figure 5In the illustrated embodiment, the monitoring method may further include an evaluation step S5 and a correlation step S4. In the evaluation step S5, the effectiveness of the current correlation information is evaluated based on the corrected DC resistance, and it is determined whether it is necessary to execute the correlation step S4 to generate new correlation information according to the effectiveness. This helps to ensure the adaptability of the correlation information to the battery.

[0076] If it is evaluated in the evaluation step S5 that the current correlation information is no longer effective, it is determined that it is necessary to execute the correlation step S4 to generate new correlation information. If it is evaluated in the evaluation step S5 that the current correlation information is effective, it is determined that it is temporarily not necessary to execute the correlation step S4.

[0077] The following Figure 6 further describes the evaluation step S5.

[0078] According to an exemplary embodiment of the present application, in the evaluation step S5, the effectiveness of the current correlation information is evaluated in the following manner: obtaining a plurality of corrected DC resistances determined based on the current correlation information; determining the deviation between the plurality of corrected DC resistances; and if the deviation is greater than a predetermined deviation threshold, evaluating that the correlation information is no longer effective.

[0079] In Figure 6 the correlation between the current at the end of discharge represented by the current correlation information and the DC resistance is schematically shown by a dotted line. The square data points represent the DC resistance measurement values and the corresponding end-of-discharge currents. Here, 4 data points are exemplarily shown, which correspond to 4 different end-of-discharge currents. The triangular data points represent the corrected DC resistances obtained after correcting the DC resistance measurement values according to the end-of-discharge current based on the current correlation information. Here, the correction is made with 5C as the reference current. It can be seen that there is a large deviation between the 4 corrected DC resistances determined based on the current correlation information. If the deviation is greater than the predetermined deviation threshold, the correlation information can be evaluated as no longer effective.

[0080] The multiple corrected DC resistances are, in particular, corrected DC resistances determined during the same operating cycle of the battery. "The same operating cycle of the battery" means a single use process of the battery. For example, in an electric vehicle, one operating cycle of the power battery of the electric vehicle can represent the process from the start to the stop of the operation of the electric vehicle. If the current relevance information has a high degree of compatibility with the battery, the resistance characteristics of the battery usually remain consistent during the same operating cycle of the battery, that is, the multiple corrected DC resistances of the battery should remain consistent. If there is a large deviation between the multiple corrected DC resistances determined based on the current relevance information during the same operating cycle of the battery, then the deviation is likely due to the fact that the relevance information is no longer compatible with the battery. Therefore, it can be evaluated that the relevance information is no longer valid. If there is a large deviation between the multiple corrected DC resistances determined based on the same relevance information during different operating cycles of the battery, then the deviation may also be due to a change in the resistance characteristics of the battery.

[0081] Therefore, in the evaluation step S5, by only using the multiple corrected DC resistances determined during the same operating cycle of the battery, it is possible to more accurately identify the situation where the relevance information is not compatible with the battery. Taking Figure 6 the situation shown as an example, the 4 square data points must be data collected during the same operating cycle of the battery.

[0082] Alternatively or additionally, the multiple corrected DC resistances are corrected DC resistances determined within a predetermined time period. Still taking Figure 6 the situation shown as an example, this means that the 4 square data points must be data collected within a predetermined time period. This also helps to accurately identify the situation where the relevance information is not compatible with the battery.

[0083] The multiple corrected DC resistances can, for example, be corrected DC resistances corrected based on the same end-of-discharge current. If the current relevance information has a high degree of compatibility with the battery, the multiple corrected DC resistances corrected based on the same end-of-discharge current should be approximately equal.

[0084] If it is determined in the evaluation step S5 that the association step S4 needs to be executed, then relevance information can be generated based on multiple sets of monitoring data of the battery, where each set of monitoring data includes a DC resistance measurement value determined by means of the discharge process of the battery and the corresponding end-of-discharge current. The multiple sets of monitoring data have at least two different end-of-discharge currents.

[0085] In particular, the correlation step S4 can be performed using at least a part of the DC resistance measurement values corresponding to the plurality of corrected DC resistances and the end-of-discharge current as the plurality of sets of monitoring data. Thus, the evaluation step S5 and the correlation step S4 can be performed using the monitoring data measured during the operation of the battery. There is no need to additionally discharge the battery to perform the correlation step S4. This enables the correlation step S4 to be performed immediately after the evaluation step S5. Thus, the correlation step S4 can be performed conveniently and at low cost.

[0086] See Figure 6 , after performing the evaluation step S5 using the data points of four triangles (representing a plurality of corrected DC resistances), the correlation step S4 can be performed using the data points of four squares (representing the corresponding DC resistance measurement values and the end-of-discharge current) corresponding to the data points of the four triangles. For example, by fitting the data points of the four squares, a new linear function (depicted by a solid line here) can be obtained.

[0087] Optionally, after performing the correlation step S4, the correction step S3 can be performed again using the new correlation information. When performing the correction step S3 again, the DC resistance measurement values corresponding to the plurality of corrected DC resistances used in the evaluation step S5 can be re-corrected to obtain new and more accurate corrected DC resistances. In Figure 6 , the new corrected DC resistances are schematically shown by circles. It can be seen that the deviation between the four new corrected DC resistances is significantly reduced.

[0088] According to an exemplary embodiment of the present application, the monitoring method may further include a verification step. In the verification step, the new correlation information generated in the correlation step S4 is verified according to the new corrected DC resistances. Only when the deviation between the new corrected DC resistances meets a predetermined condition, the new correlation information passes the verification and can thus be used as effective correlation information in the subsequent correction step S3. The predetermined condition may include, for example: the deviation of the new corrected DC resistances is less than a predetermined threshold; and / or the deviation of the new corrected DC resistances is less than the deviation obtained in the evaluation step S5.

[0089] Figure 7 A flowchart of the correlation step S4 of the monitoring method according to an exemplary embodiment of the present application is schematically shown.

[0090] In this embodiment, the correlation step S4 may include the following sub-steps: a preparation step S41, a discharge step S42, and a generation step S43.

[0091] In the preparation step S41, the discharge start voltage and the discharge start current of the battery before discharge are obtained. Optionally, the current of the battery before discharge may not be zero.

[0092] In the discharging step S42, the battery is discharged at a predetermined constant current, and the end voltage and end current of the battery after discharging are obtained. In the discharging step S42, the discharging duration is, for example, 1 s and / or 10 s. Optionally, the discharging duration is 10 s, and the voltages at 1 s and 10 s after the start of discharging are respectively recorded to calculate the correlation information for the cases where the discharging duration is 1 s and 10 s respectively.

[0093] In the generating step S43, based on the start voltage and start current of the battery before discharging and the end voltage and end current of the battery after discharging, the measured value of the DC resistance of the battery is determined to generate the correlation information by using the measured value of the DC resistance and the corresponding end current.

[0094] In the correlating step S4, the discharging step S42 is performed at least twice with different end currents to obtain the multiple sets of monitoring data.

[0095] Optionally, after the BMS recognizes the need to perform the correlating step S4, it may determine whether a predetermined execution condition is satisfied. The correlating step S4 is performed only after recognizing the need to perform the correlating step S4 and when the predetermined execution condition is satisfied. The execution condition may include, for example: the vehicle is not in a driving state; and / or the temperature of the battery is within a predetermined temperature range; and / or the SOC of the battery is within a predetermined SOC range.

[0096] Although specific embodiments of the present application are described in detail herein, they are given for explanatory purposes only and should not be considered as limiting the scope of the present application. Various substitutions, alterations, and modifications can be conceived without departing from the spirit and scope of the present application.

Claims

1. A method for monitoring the DC resistance of a battery, wherein: The monitoring method comprises the following steps: Acquisition step S1, acquiring a discharge start voltage and a discharge start current of the battery before discharge, and a discharge end voltage and a discharge end current at the end of discharge; Preliminary determination step S2, determining a DC resistance measurement value of the battery according to the discharge start voltage, the discharge end voltage, the discharge start current and the discharge end current; as well as In the correction step S3, the DC resistance measurement value is corrected according to the discharge end current based on the correlation information indicating the correlation between the current at the end of discharge and the DC resistance to determine the corrected DC resistance.

2. The monitoring method according to claim 1, wherein: The monitoring method further comprises an association step S4, in which association information is generated based on multiple sets of monitoring data of the battery, wherein each set of monitoring data comprises a DC resistance measurement value and a corresponding end-of-discharge current determined by means of a discharge process of the battery, and the multiple sets of monitoring data have at least two different end-of-discharge currents.

3. The monitoring method according to claim 1 or 2, wherein: The monitoring method further comprises an evaluation step S5, in which the validity of the current correlation information is evaluated based on the corrected DC resistance, and it is determined whether the correlation step S4 needs to be executed to generate new correlation information based on the validity.

4. The monitoring method according to claim 3, wherein: In the evaluation step S5, the validity of the current relevance information is evaluated in the following manner: Obtaining a plurality of corrected DC resistances determined according to current correlation information; determining deviations between the plurality of modified DC resistances; as well as If the deviation is greater than a predetermined deviation threshold, it is evaluated that the relevance information is no longer valid.

5. The monitoring method according to claim 4, wherein: The plurality of corrected DC resistances are corrected DC resistances determined during a same operating cycle of the battery; and / or The plurality of modified DC resistances are modified DC resistances determined within a predetermined period of time; and / or The plurality of corrected DC resistances are corrected DC resistances that are corrected based on the same discharge end current.

6. The monitoring method according to claim 4 or 5, wherein: If it is determined in the evaluation step S5 that the association step S4 needs to be performed, the association step S4 is performed using the DC resistance measurement values ​​and the discharge end current corresponding to the multiple corrected DC resistances as at least a part of the multiple groups of monitoring data.

7. The monitoring method according to claim 2, wherein: The association step S4 includes the following sub-steps: Preparation step S41, obtaining the discharge start voltage and discharge start current of the battery before discharge; Discharging step S42, discharging the battery at a predetermined constant current, and obtaining the discharge end voltage and discharge end current of the battery after the discharge; as well as Generating step S43, determining the DC resistance measurement value of the battery according to the discharge start voltage and discharge start current of the battery before discharge and the discharge end voltage and discharge end current of the battery after discharge, so as to generate correlation information using the DC resistance measurement value and the corresponding discharge end current, The discharging step S42 is performed at least twice with different discharge end currents to obtain the multiple sets of monitoring data.

8. The monitoring method according to any one of claims 1 to 7, wherein: The correlation information is used to indicate the negative correlation between the current and the DC resistance at the end of discharge; and / or The correlation information is used to represent the linear relationship between the current and the DC resistance at the end of discharge; and / or The correlation information is used to represent the quadratic function relationship between the current and the DC resistance at the end of discharge.

9. A monitoring device comprising a memory and a processor, wherein: The memory stores a computer program. When the computer program is executed by the processor, the processor can perform the monitoring method according to any one of claims 1 to 8.

10. A computer program product comprising computer program instructions, wherein: The computer program instructions, when executed by one or more processors, enable the one or more processors to perform the monitoring method according to any one of claims 1-8.

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