Battery short circuit online prediction method, controller, automobile and storage medium

Abstract

The application provides a battery short circuit online prediction method, comprising: selecting at least one same voltage change interval during the n-th and n+1-th charging processes of a battery, wherein the voltage difference of the battery in the voltage change interval is ΔV; obtaining the charging electric quantity ΔQ of the battery in the voltage change interval during the n-th charging process n , and obtaining the charging electric quantity ΔQ of the battery in the voltage change interval during the n+1-th charging process n+1 ; wherein n is a non-zero natural number; if ΔQ n+1 ≤ ΔQ n or ΔV / ΔQ n+1 ≥ ΔV / ΔQ n , the battery does not have a short circuit; if ΔQ n+1 > ΔQ n or ΔV / ΔQ n+1 < ΔV / ΔQ n , the battery has a short circuit. The application can accurately and reliably predict whether the battery has a short circuit or a micro short circuit in real time, and improves the safety performance of the battery. The application also provides a controller, a vehicle and a computer readable storage medium.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of battery, in particular to a battery short circuit online prediction method, a controller, an automobile and a computer readable storage medium. BACKGROUND

[0002] With the development of electronic technology, lithium ion batteries have the advantages of high specific power, long cycle life, good safety performance and no pollution, etc., and the safety performance of the battery is one of the most important indicators.

[0003] Internal short circuit and micro short circuit are the main reasons for the frequent safety problems of batteries and battery systems in actual application. In order to screen out short-circuited or micro short-circuited batteries, the current main method is to judge the voltage drop of the battery during long-term storage, in addition, the voltage drop, charge and discharge efficiency and equivalent internal resistance can also be used to judge whether the battery is short-circuited. The above methods have one or several defects such as long time consumption, insufficient accuracy, and cannot be monitored online. SUMMARY

[0004] The purpose of the present application is to provide a battery short circuit online prediction method, which aims to solve or at least partially solve the problems in the background art, can predict whether the battery is short-circuited or micro short-circuited in real time, accurately and reliably, and improve the safety performance of the battery.

[0005] The present application provides a battery short circuit online prediction method, comprising:

[0006] At least one same voltage change interval is selected in the n th and n+1 th charging processes of the battery respectively, and the voltage difference of the battery in the voltage change interval is ΔV; the charging capacity ΔQ n of the battery in the voltage change interval in the n th charging process is obtained n+1 , and the charging capacity ΔQ n of the battery in the voltage change interval in the n+1 th charging process is obtained n+1 ; wherein n is a non-zero natural number;

[0007] If ΔQ n+1 ≤ ΔQ n or ΔV / ΔQ n+1 ≥ ΔV / ΔQ n , the battery does not have a short circuit; if ΔQ n+1 > ΔQ n or ΔV / ΔQ n+1 < ΔV / ΔQ n , the battery has a short circuit.

[0008] In one feasible approach, the calculation of the voltage difference ΔV includes:

[0009] Obtain the charging voltage V of the battery during the charging process. W The charging voltage V W Including the charging voltage V located at the beginning of the voltage variation range W1 and the charging voltage V located at the end of the voltage variation range W2 The voltage difference ΔV = V W2 -V W1 .

[0010] In one feasible approach, the calculation of the voltage difference ΔV includes:

[0011] Obtain the open-circuit voltage V of the battery during the charging process. Y The open-circuit voltage V Y Including the open-circuit voltage V located at the beginning of the voltage variation range Y1 and the open-circuit voltage V located at the end of the voltage variation range Y2 The voltage difference ΔV = V Y2 -V Y1 .

[0012] In one feasible manner, the open-circuit voltage V Y The calculation methods include:

[0013] Obtain the charging voltage V of the battery during the charging process. W Then the open-circuit voltage V Y =V W -I*R; where I and R are the battery at the charging voltage V, respectively. W The charging current and DC internal resistance are as follows.

[0014] In one possible implementation, the DC internal resistance R is the rated DC internal resistance of the battery.

[0015] In one possible implementation, the DC internal resistance R corresponds one-to-one with the SOC value of the battery, and the DC internal resistance R corresponding to each SOC value is R = (Vw″-Vw′) / I; where Vw′ is the charging voltage of the battery before charging for the corresponding SOC value, Vw″ is the charging voltage of the battery after charging for the corresponding SOC value, and I is the charging current of the battery for the corresponding SOC value.

[0016] In one feasible manner, the voltage sampling interval between Vw′ and Vw″ is less than or equal to 1 second.

[0017] In an implementable manner, the voltage sampling interval time of the Vw' and the Vw" is 100-500 ms.

[0018] In an implementable manner, the method for obtaining the direct current resistance R comprises:

[0019] The direct current resistance R corresponding to each SOC value is (Vw"-Vw') / I; wherein the Vw' is the charging voltage before the battery corresponding to the SOC value is charged, the Vw" is the charging voltage after the battery corresponding to the SOC value is charged, and the I is the charging current of the battery corresponding to the SOC value; the direct current resistance R corresponding to the SOC value of the battery is pre-calculated and stored according to the R=(Vw"-Vw') / I, and a SOC-R mapping relationship corresponding table is formed, and the direct current resistance R is obtained through the SOC-R mapping relationship corresponding table.

[0020] In an implementable manner, the open circuit voltage V Y is obtained by a method comprising:

[0021] The charging voltage V W of the battery in the charging process is obtained, the charging voltage V W corresponds to the SOC value of the battery in a one-to-one manner, and the open circuit voltage V Y =V W -I*R; wherein I and R are the charging current and the direct current resistance of the battery under the charging voltage V W , respectively; the open circuit voltage V Y corresponding to the SOC value of the battery is pre-calculated and stored according to the V W =V Y -I*R, and a SOC-V Y mapping table database is formed, and the open circuit voltage V Y is obtained through the SOC-V Y mapping table database.

[0022] In an implementable manner, the charging process of the battery is constant current charging, and the charging capacity ΔQ of the battery in the voltage variation interval is (T2-T1)*I0; wherein T1 and T2 are the charging time at the start end of the voltage variation interval and the charging time at the end of the voltage variation interval, respectively, and I0 is the charging current in the constant current charging process.

[0023] In an implementable manner, the charging process of the battery is non-constant current charging, and the charging capacity ΔQ of the battery in the voltage variation interval is wherein T1 and T2 are the charging time at the start end of the voltage variation interval and the charging time at the end of the voltage variation interval, respectively, and I XThe charging current at any time during the non-constant current charging process.

[0024] In an implementable manner, the voltage variation interval is located in a voltage interval range corresponding to the SOC value of 0-10% and / or 90%-100% of the battery.

[0025] In an implementable manner, the voltage variation interval is far away from a voltage interval range corresponding to an inflection point of a charging curve of the battery.

[0026] In an implementable manner, the range of the voltage variation interval is greater than or equal to a voltage interval range corresponding to the SOC value of 3% of the battery.

[0027] In an implementable manner, when ΔQ n+1 >ΔQ n or ΔV / ΔQ n+1 <ΔV / ΔQ n , the BMS sends corresponding alarm information.

[0028] The application further provides a controller, comprising:

[0029] a memory in which instructions are stored;

[0030] a processor, when the instructions are executed by the processor, the battery short circuit online prediction method described above is realized.

[0031] The application further provides an automobile comprising the controller described above.

[0032] The application further provides a computer readable storage medium, instructions are stored on the computer readable storage medium, when the instructions are executed by the processor, the battery short circuit online prediction method described above is realized.

[0033] The battery short circuit online prediction method provided by the application, by collecting the voltage, current and other information of the battery during the charging process, and calculating the ratio of the voltage variation value in the selected voltage variation interval to the actual charging capacity, i.e. ΔV / ΔQ, the variation value at the n th charging is recorded as ΔV / ΔQ n , and the variation value at the n+1 th charging is recorded as ΔV / ΔQ n+1 ; if ΔV / ΔQ n+1 ≥ΔV / ΔQ n , it is considered that the battery state is normal and no short circuit or micro short circuit occurs; if ΔV / ΔQ n+1 <ΔV / ΔQ n , it is judged that the battery appears short circuit or micro short circuit; or ΔQ n+1 and ΔQ n are directly compared, if ΔQ n+1 ≤ΔQ nIf ΔQ is normal, the battery is considered to be in normal condition and no short circuit or micro-short circuit has occurred; if ΔQ n+1 >ΔQ n If the signal is clear, it indicates that the battery has experienced a short circuit or micro-short circuit. This online short circuit prediction method for batteries is simple, convenient, efficient, and accurate. It can predict whether a battery will experience a short circuit or micro-short circuit online, providing early warning of potential safety hazards and improving battery safety performance. Attached Figure Description

[0034] Figure 1 This is a charging curve diagram of the battery in Embodiment 1 of the present invention.

[0035] Figure 2 This is a charging curve diagram of the battery in Embodiment 2 of the present invention.

[0036] Figure 3 This is a charging curve diagram of the battery in Embodiment 3 of the present invention.

[0037] Figure 4 This is a charging curve diagram of the battery in Embodiment 4 of the present invention. Detailed Implementation

[0038] The specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples. The following examples are for illustrative purposes only and are not intended to limit the scope of the invention.

[0039] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and claims of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0040] The directional terms such as "up," "down," "left," "right," "front," "back," "top," and "bottom" (if present) used in the specification and claims of this invention are defined by the position of the structures in the drawings and the relative positions of the structures, and are only for the clarity and convenience of expressing the technical solution. It should be understood that the use of directional terms should not limit the scope of protection claimed by this invention.

[0041] The battery short-circuit online prediction method provided in this embodiment of the invention includes:

[0042] During the nth and (n+1)th charging processes of the battery, at least one identical voltage change interval is selected, and the voltage difference within this interval is ΔV (i.e., the endpoint values ​​and voltage difference of the selected voltage change intervals are the same in both charging processes); the charging capacity ΔQ of the battery within this voltage change interval during the nth charging process is obtained. n And obtain the charge amount ΔQ of the battery during the (n+1)th charge in the voltage change range. n+1 Calculate ΔV / ΔQ n and ΔV / ΔQn+1 ; wherein n is a non-zero natural number;

[0043] Comparing the size relationship of AQ n+1 and AQ n or AV / AQ n and AV / AQ n+1 , if AQ n+1 ≤ AQ n or AV / AQ n+1 ≥ AV / AQ n , it is considered that the battery does not have a short circuit or a micro short circuit (i.e. the battery does not have an internal short circuit or the internal short circuit is negligible); if AQ n+1 > AQ n or AV / AQ n+1 < AV / AQ n , it is considered that the battery has a short circuit or a micro short circuit, at which time the BMS (Battery Management System) sends corresponding alarm information.

[0044] Specifically, the charging curve trend of the battery mainly depends on the positive and negative electrode materials, electrolyte and battery structure and other factors of the battery. In an ideal case, if the capacity and internal resistance of the battery remain unchanged during the charging cycle, the charging curve of the battery will also not change, and the AQ and AV / AQ values of any same voltage change interval will not change each time the battery is charged. However, in actual situations, as the number of cycles of the battery increases, the capacity of the battery will decrease (i.e. AQ decreases) and the internal resistance will increase, causing the charging curve to rise and the slope to increase, i.e. AV / AQ becomes larger. As can be seen, when the battery does not have a short circuit or a micro short circuit, the AQ value of the n+1th charging in a certain voltage change interval will be less than or equal to the AQ value of the nth charging, i.e. AQ n+1 ≤ AQ n , and the AV / AQ value of the n+1th charging will be greater than or equal to the AV / AQ value of the nth charging, i.e. AV / AQ n+1 ≥ AV / AQ n .

[0045] When the battery has an internal short circuit, the trend of the charging curve changing with the number of cycles will be different. Assuming that the n th charging of the battery is normal and an internal short circuit occurs at the n+1th charging, at the n+1th charging, a part of the charging capacity will be dissipated in the form of Joule heat, so the actual charging capacity of the n+1th charging will increase, making AQ become larger. Therefore, under the condition of selecting the same voltage change interval (AV does not change, i.e. AV n+1 = AV n ), the AQ value of the n+1th charging will be greater than the AQ value of the nth charging, i.e. AQ n+1 > AQn Furthermore, the ΔV / ΔQ will decrease during the (n+1)th charge, i.e., ΔV / ΔQ n+1 <ΔV / ΔQ n .

[0046] Therefore, the internal short circuit condition of the battery can be determined based on the change of ΔQ value or ΔV / ΔQ value with the number of cycles. If ΔQ n+1 ≤ΔQ n or ΔV / ΔQ n+1 ≥ΔV / ΔQ n If the battery has no internal short circuit or the internal short circuit is negligible; if ΔQ n+1 >ΔQ n or ΔV / ΔQ n+1 <ΔV / ΔQ n If this is the case, then the battery has an internal short circuit. In practical applications, calculating the ΔQ value or ΔV / ΔQ value over the entire charging range is impractical. Therefore, a more appropriate method is to select one or more specific voltage variation ranges and monitor the charging capacity change within these ranges.

[0047] As one implementation method, the voltage difference ΔV (including ΔV) n+1 and ΔV n One method for calculating ) includes:

[0048] Obtain the charging voltage V of the battery during the charging process. W (the charging voltage V) W This refers to the voltage value that changes during battery charging, not the voltage value of the power source used to charge the battery. Charging voltage V W This can be obtained from the battery charging curve. Charging voltage V W Including the charging voltage V located at the beginning of the voltage variation range W1 and the charging voltage V located at the end of the voltage variation range W2 Voltage difference ΔV = V W2 -V W1 .

[0049] As another implementation, the voltage difference ΔV (including ΔV) n+1 and ΔV n Another method for calculating ) includes:

[0050] Obtain the open-circuit voltage (i.e., the supply voltage after removing the voltage divider from the battery's internal resistance) V during the charging process. Y Open circuit voltage V Y Including the open-circuit voltage V at the beginning of the voltage variation range Y1 and the open-circuit voltage V located at the end of the voltage variation range Y2 Voltage difference ΔV = V Y2 -V Y1 .

[0051] As one implementation method, the above-mentioned open-circuit voltage V Y (including V) Y2 and V Y1 The calculation methods for ) include:

[0052] Obtain the charging voltage V of the battery during the charging process. W Then the open-circuit voltage V Y =V W -I*R; where I and R are the battery voltages at the charging voltage V, respectively. W Below (i.e., corresponding to the charging voltage V) W The charging current I and DC internal resistance (when the battery charging process is constant current charging, this charging current I is the same as the charging current I0 described below; when the battery charging process is non-constant current charging, this charging current I is the same as the charging current I0 described below) X (Equivalent)

[0053] As one implementation method, the open-circuit voltage V Y Each voltage corresponds one-to-one with the battery's SOC (state of charge) value, and the open-circuit voltage V. Y The methods for obtaining it include:

[0054] Record the open-circuit voltage V corresponding to the battery's SOC value. Y And form SOC-V Y Mapping table database, open circuit voltage V Y Through SOC-V Y Retrieve mapping table from database.

[0055] Specifically, because the SOC value of the battery is related to the charging voltage V W One-to-one correspondence, open-circuit voltage V Y and charging voltage V W There is a one-to-one correspondence, therefore the SOC value of the battery is also related to the open-circuit voltage V. Y One-to-one correspondence (i.e., SOC, V) W V Y (The three correspond one-to-one), and the BMS calculates and records each charging voltage V. W The corresponding open-circuit voltage V Y (open circuit voltage V) Y Through the above V Y =V W The SOC value of the battery is calculated using the formula -I*R, and the charging voltage V is also considered. W A one-to-one correspondence is obtained to obtain the SOC value and the open-circuit voltage V. Y Data correspondence and form SOC-V Y Mapping table database.

[0056] As an embodiment, the BMS records the SOC-V of at least three adjacent charging processes Y The mapping table database, especially the data of the voltage interval range corresponding to the SOC value of 0-10% and / or 90%-100% of the battery (the voltage variation interval is preferably within the above two ranges).

[0057] As an embodiment, the above direct current resistance R is the rated direct current resistance of the battery (i.e. the internal resistance data measured when the battery is shipped).

[0058] As another embodiment, the direct current resistance R corresponds to the SOC value of the battery one by one, and the method for obtaining the direct current resistance R comprises:

[0059] The direct current resistance R corresponding to the SOC value of the battery is recorded and a SOC-R mapping relationship corresponding table is formed, and the direct current resistance R is obtained through the SOC-R mapping relationship corresponding table.

[0060] Specifically, since the SOC value of the battery corresponds to the charging voltage V W one by one, the direct current resistance R and the charging voltage V W correspond to each other one by one, so the SOC value of the battery also corresponds to the direct current resistance R one by one (i.e. SOC, V W , R correspond to each other one by one), the BMS calculates and records the direct current resistance R corresponding to each charging voltage V W , and simultaneously the SOC value of the battery and the charging voltage V W correspond to each other one by one, so as to obtain the data corresponding relationship of the SOC value and the direct current resistance R and form a SOC-R mapping relationship corresponding table; when calculating the open circuit voltage V Y , the corresponding SOC value can be selected through the charging voltage V W , and then the corresponding direct current resistance R is selected through the corresponding SOC value, so as to calculate the open circuit voltage V Y according to the direct current resistance R.

[0061] As an embodiment, the direct current resistance R corresponding to each SOC value is (Vw"-Vw') / I; wherein Vw' is the charging voltage before the battery is charged to the corresponding SOC value (the SOC value corresponds to the charging voltage V W value), Vw" is the charging voltage after the battery is charged to the corresponding SOC value, and I is the charging current of the battery to the corresponding SOC value. Therefore, when the charging process of the battery is constant current charging, the above formula can also be converted to: the open circuit voltage V Y =V W -I*R=V W -I*(Vw"-Vw') / I=V W -(Vw"-Vw').

[0062] Since the DC internal resistance R of the battery will change during use, in order to calculate more accurately, a more accurate DC internal resistance R can be calculated according to the jump of the charging voltage V W of the battery at the moment of charging. Since the battery will be in a continuous charging and discharging cycle, the SOC value (corresponding to the charging voltage V W value) can be collected during the charging process of the battery, and the charging voltage V W and the charging current I before and after charging (the sampling interval is less than or equal to 1s) are calculated to obtain the DC internal resistance R, thereby forming a one-to-one mapping relationship between the DC internal resistance R and the SOC value, and being corrected during continuous charging. For example: the SOC-R mapping relationship corresponding table is formed by calculation during the n-th charging process of the battery; during the n+1-th charging process of the battery, the SOC-R mapping relationship corresponding table calculated during the n-th charging process can be directly called (the change interval of the SOC value is the same or overlaps, for example, the charging is from 20% SOC to 80% SOC), and the DC internal resistance R is obtained through the SOC-R mapping relationship corresponding table, so that repeated calculation is not required. At the same time, after the battery is charged for many times, the DC internal resistance R is recalculated and a new SOC-R mapping relationship corresponding table is formed, thereby correcting the SOC-R mapping relationship corresponding table calculated last time to ensure the accuracy of the data (for example, the SOC-R mapping relationship corresponding table is obtained during the first charging process of the battery, and the SOC-R mapping relationship corresponding table calculated during the first charging process can be directly called during the second charging process of the battery; the DC internal resistance R is recalculated and a new SOC-R mapping relationship corresponding table is formed during the 10th charging process of the battery, thereby correcting the SOC-R mapping relationship corresponding table calculated for the first time).

[0063] Specifically, during actual use of the vehicle, the battery will be charged at different SOC values, and R corresponding to the SOC value (corresponding to the charging voltage V W value) during charging can be calculated by R=(Vw"-Vw') / I, Vw' is the charging voltage before charging at the SOC value (corresponding to the charging voltage V W value), Vw" is the charging voltage after charging at the SOC value (corresponding to the charging voltage V W value), and I is the charging current at the SOC value (corresponding to the charging voltage V W value); and a mapping relationship corresponding table of the SOC value and R is established. In this way, the relevant data of the SOC-R mapping relationship corresponding table can be called at any time when needed (when the open circuit voltage V W corresponding to the SOC value (corresponding to the charging voltage V Y value) is calculated, the DC internal resistance R in the SOC-R mapping relationship corresponding table can be directly selected, and V Y =V WIR calculation of open circuit voltage V Y Then, the open circuit voltage V Y is selected again, and the voltage variation interval calculation of ΔV n / ΔQ n is compared with the ΔV n+1 / ΔQ n+1 calculated in the same open circuit voltage interval in the next charging process); in addition, the direct current resistance R is calculated again at each charging of the vehicle (or after a certain number of charging intervals) for correction of the data, and the correction is made to the latest charging data.

[0064] As an embodiment, at the above-mentioned specific SOC value position, the voltage sampling interval time of Vw' and Vw" (i.e. the voltage sampling interval time before and after charging at the SOC value) is less than or equal to 1 s (second).

[0065] As an embodiment, at the above-mentioned specific SOC value position, the voltage sampling interval time of Vw' and Vw" is 100-500 ms (millisecond).

[0066] It should be noted that the above-mentioned two calculation methods of voltage difference ΔV are applicable to both constant current charging and non-constant current charging (e.g. constant voltage charging).

[0067] As an embodiment, the charging process of the battery is constant current charging, and the charging electric quantity ΔQ of the battery in the voltage variation interval is (T2-T1)*I0; wherein T1 and T2 are the charging time at the start and end of the voltage variation interval respectively, and I0 is the charging current in the constant current charging process.

[0068] As another embodiment, the charging process of the battery is non-constant current charging, and the charging electric quantity ΔQ of the battery in the voltage variation interval is (i.e. the integral of charging time t with respect to charging current I X ); wherein T1 and T2 are the charging time at the start and end of the voltage variation interval respectively, and I X is the charging current at any time in the non-constant current charging process. Of course, the above-mentioned integral formula is also applicable to the case of constant current charging of the battery.

[0069] As an embodiment, the voltage variation interval is far away from the voltage interval range corresponding to the inflection point of the charging curve of the battery (i.e. the charging voltage corresponding to the inflection point of the charging curve is not in the selected voltage variation interval range).

[0070] The inflection point of the charging current is a point where the sign of the rate of change (second derivative) of the slope (first derivative) of the tangent of the curve of the charging current changes. Specifically, in mathematics, the inflection point, also known as the point of contraflexure, refers to a point where the curve changes direction, that is, the point where the concave arc and the convex arc of the continuous curve are separated, or the point where the second derivative changes sign, or the point where the monotonicity of the first derivative changes, etc. In the charging curve described in the embodiment, the inflection point refers to a point where the trend of the charging curve changes obviously or bends, as shown in FIG. 8. Figure 1

[0071] As an implementation, the voltage variation interval is located in the voltage interval range corresponding to the SOC value of 0-10% and / or 90%-100% of the battery (that is, the voltage variation interval is selected from the voltage interval range corresponding to the SOC value of 0-10% and / or 90%-100% of the battery). Since the slope of the charging curve in this SOC range is large, the voltage variation in the voltage interval in this range is more obvious, and the data error can be reduced. Of course, in other embodiments, the voltage variation interval can also be selected from the voltage interval range corresponding to the SOC value of 10%-90%.

[0072] As an implementation, the range of the voltage variation interval is greater than or equal to the voltage interval range corresponding to the SOC value of 3% of the battery, so as to ensure that the voltage variation is obvious and improve the detection accuracy (if the voltage interval is too small, the voltage variation is small, which affects the detection accuracy).

[0073] The embodiment of the present application also provides a controller, comprising:

[0074] a memory, wherein instructions are stored in the memory;

[0075] a processor, wherein when the instructions are executed by the processor, the battery short circuit online prediction method described above is realized.

[0076] The embodiment of the present application also provides an automobile, comprising the controller described above.

[0077] The embodiment of the present application also provides a computer readable storage medium, wherein instructions are stored on the computer readable storage medium, and when the instructions are executed by the processor, the battery short circuit online prediction method described above is realized.

[0078] The battery short circuit online prediction method provided by the embodiment of the present application calculates the ratio of the voltage variation value in the selected voltage variation interval to the actual charging capacity, that is, ΔV / ΔQ, according to the voltage, current and other information of the battery in the charging process. The change value at the n th charging is recorded as ΔV / ΔQ n , and the change value at the n+1 th charging is recorded as ΔV / ΔQ n+1 .If ΔV / ΔQn+1 ≥ΔV / ΔQ n If the battery is in normal condition and no short circuit or micro-short circuit has occurred, then the battery is considered to be in normal condition; if ΔV / ΔQ n+1 <ΔV / ΔQ n If the signal is clear, it indicates that the battery has experienced a short circuit or micro-short circuit. This online short circuit prediction method for batteries is simple, convenient, efficient, and accurate. It can predict whether a battery will experience a short circuit or micro-short circuit online, providing early warning of potential safety hazards and improving battery safety performance.

[0079] Example 1

[0080] like Figure 1 As shown, the working steps of Embodiment 1 are as follows:

[0081] (1) During the first charge of the battery (taking a ternary lithium battery as an example), a range of charging voltage variation is selected within the SOC value of 0-10%. The range of the selected voltage variation range is greater than or equal to the voltage range corresponding to 3% SOC. The charging voltage at the beginning of this voltage variation range is obtained by the BMS as V. W1 The charging voltage at the end of this voltage variation range is V. W2 Calculate the voltage difference ΔV1 = V over this voltage variation range. W2 -V W1 .

[0082] (2) The battery is charged with constant current. The charging time at the beginning of the voltage change interval is T1, and the charging time at the end of the voltage change interval is T2. The charging current is I0. Calculate the charging capacity ΔQ1=(T2-T1)*I0 for the voltage change interval.

[0083] (3) Calculate ΔV1 / ΔQ1 based on (1) and (2).

[0084] (4) Using the same method as (1) to (3), calculate ΔV2 / ΔQ2 (ΔV1=ΔV2) within the same voltage change range (within the range of SOC of 0 to 10%) during the second charging cycle of the battery.

[0085] (5) Compare the changes in ΔV / ΔQ. If ΔV2 / ΔQ2 < ΔV1 / ΔQ1, it is determined that the battery has a short circuit or micro short circuit, and the BMS will issue an alarm message.

[0086] Example 2

[0087] like Figure 2 As shown, the voltage variation range is selected from the voltage range corresponding to the SOC value of 90%-100%. The remaining steps of Example 2 are the same as those of Example 1.

[0088] Example 3

[0089] As shown in Figure 3 , the voltage variation interval selects the voltage interval range corresponding to the SOC value of 10%-90%, and the remaining steps of Example Three are the same as those of Example One.

[0090] Example Four

[0091] As shown in Figure 4 , the voltage variation interval selects the voltage interval range corresponding to the SOC value of 1%-4%, and the remaining steps of Example Four are the same as those of Example One.

[0092] Example Five

[0093] Example Five and Example One are basically the same in working steps, and the difference lies in the different calculation methods of the charging capacity ΔQ (i.e., different from step (2) in Example One).

[0094] Specifically, in this embodiment, the battery is charged at a non-constant current, and the BMS obtains the charging time at the start of the voltage variation interval as T1, the charging time at the end of the voltage variation interval as T2, and the charging current at any time as I X , and calculates the charging capacity of the voltage variation interval

[0095] Example Six

[0096] As shown in the following table, the working steps of Example Six are as follows:

[0097] (1) The BMS records the charging voltage V W in the first entire charging process, and each charging voltage V W corresponds to an open circuit voltage V Y , i.e., V Y = V W -I*R, where I is the charging current at the charging voltage V W (battery is charged at a constant current, I is the charging current during constant current charging), and R is the rated DC internal resistance. The BMS records the open circuit voltage V W corresponding to the charging voltage V Y , and establishes a mapping table database of the open circuit voltage V Y and the SOC.

[0098] (2) Select a charging voltage variation interval in the first charging process within the SOC value of 0-10% through the above mapping table database, and the selected voltage variation interval range is greater than or equal to the voltage interval range corresponding to 3% SOC, the start of the voltage variation interval is V Y1 , the end of the voltage variation interval is V Y2 , and the voltage difference ΔV1 of the voltage variation interval is calculated as ΔV1=V Y2-V Y1 .

[0099] (3) The battery is charged with constant current, and the charging time at the beginning of the above voltage variation range is T1, the charging time at the end of the above voltage variation range is T2, and the charging current is I0. The charging capacity of the voltage variation range is calculated as ΔQ1 = (T2-T1)*I0.

[0100] (4) ΔV1 / ΔQ1 is calculated according to (2) and (3).

[0101] (5) ΔV2 / ΔQ2 (ΔV1 = ΔV2) in the same voltage variation range during the second charging cycle of the battery is calculated according to the same method of (1)-(4).

[0102] (6) The change of ΔV / ΔQ is compared. If ΔV2 / ΔQ2 < ΔV1 / ΔQ1, it is judged that the battery has a short circuit or a micro short circuit, and the BMS sends an alarm message.

[0103]

[0104] Example Seven

[0105] The working steps of Example Seven and Example Six are basically the same, and the difference lies in the different calculation methods of the direct current resistance R.

[0106] As shown in the following table, in this embodiment, the direct current resistance R is read through the SOC-R mapping relationship corresponding table established by the SOC value and the direct current resistance R.

[0107] Since the direct current resistance R of the battery will change during use, in order to calculate more accurately, the more accurate direct current resistance R is calculated according to the jump of the charging voltage V W at the moment of constant current charging of the battery. Since the battery will be in continuous charging and discharging cycle, the charging voltage V W and the charging current I before and after charging (the sampling interval is 500ms) of the SOC value (corresponding to the charging voltage V W value) can be collected during the charging of the battery, so as to calculate the direct current resistance R, thereby forming a one-to-one mapping relationship between the direct current resistance R and the SOC value, and being corrected in the continuous charging process. Specifically, during the actual use of the vehicle, the battery will be charged at different SOC values. R corresponding to the SOC value (corresponding to the charging voltage V W value) can be calculated at the moment of charging, V′ is the charging voltage before charging at the SOC value (corresponding to the charging voltage V W value), V″ is the charging voltage after charging at the SOC value (corresponding to the charging voltage V W value), and I is the charging current at the SOC value (corresponding to the charging voltage V WThe charging current (the battery is charged with constant current, I is the charging current during the constant current charging process) corresponding to the SOC value) is calculated, and a mapping relationship table of the SOC value and R is established. In addition, the DC internal resistance R is calculated again at each charging of the vehicle (or after a certain number of charging intervals) to correct the data to the latest charging data.

[0108]

[0109] The above merely illustrates the specific embodiments of the present application, but the protection scope of the present application is not limited thereto, any person skilled in the art can easily think of changes or replacements within the technical range disclosed by the present application, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A battery short circuit online prediction method, characterized in that, The method comprises: at least one same voltage variation interval is selected in the n-th and the n+1-th charging processes of the battery respectively, and the voltage difference of the battery in the voltage variation interval is ΔV; the charging electric quantity of the battery in the n-th charging process in the voltage variation interval is acquired as ΔQ n , and the charging electric quantity of the battery in the n+1-th charging process in the voltage variation interval is acquired as ΔQ n+1 ; wherein n is a non-zero natural number. If ΔQ n+1 ≤ ΔQ n or ΔV / ΔQ n+1 ≥ ΔV / ΔQ n , then the battery is not shorted; if ΔQ n+1 > ΔQ n or ΔV / ΔQ n+1 < ΔV / ΔQ n , then the battery is shorted. The method for calculating the voltage difference AV comprises: acquiring an open circuit voltage V of the battery during charging Y , the open circuit voltage V Y comprises an open circuit voltage V Y1 at a start of the voltage variation interval Y2 and an open circuit voltage V Y2 at an end of the voltage variation interval Y1 ; The open circuit voltage V Y The acquisition method comprises: obtaining a charging voltage V of the battery during charging W , the charging voltage V W corresponds to the SOC value of the battery, then the open circuit voltage V Y =V W -I*R; wherein I and R are the charging current and DC internal resistance of the battery under the charging voltage V W , respectively; according to the V Y =V W -I*R, the open circuit voltage V Y corresponding to the SOC value of the battery is calculated and stored in advance, and a SOC-V Y mapping table database is formed, and the open circuit voltage V Y is obtained through the SOC-V Y mapping table database.

2. A battery short circuit online prediction method, characterized in that, The method comprises: at least one same voltage variation interval is selected in the n-th and the n+1-th charging processes of the battery respectively, and the voltage difference of the battery in the voltage variation interval is ΔV; the charging electric quantity of the battery in the n-th charging process in the voltage variation interval is acquired as ΔQ n , and the charging electric quantity of the battery in the n+1-th charging process in the voltage variation interval is acquired as ΔQ n+1 ; wherein n is a non-zero natural number. if ΔQ n+1 ≤ ΔQ n or ΔV / ΔQ n+1 ≥ ΔV / ΔQ n then the battery is not shorted; if ΔQ n+1 > ΔQ n or ΔV / ΔQ n+1 < ΔV / ΔQ n then the battery is shorted. The direct current resistance R corresponds to the SOC value of the battery one by one, and the direct current resistance R corresponding to each SOC value is (Vw"-Vw') / I; wherein, the Vw' is the charging voltage of the battery before charging corresponding to the SOC value, the Vw" is the charging voltage of the battery after charging corresponding to the SOC value, and the I is the charging current of the battery corresponding to the SOC value. Obtain the open-circuit voltage V of the battery during the charging process. Y The open-circuit voltage V Y Including the open-circuit voltage V located at the beginning of the voltage variation range Y1 and the open-circuit voltage V located at the end of the voltage variation range Y2 The voltage difference ΔV = V Y2 -V Y1 ; The open circuit voltage V Y The calculation method comprises: acquiring a charging voltage V of the battery during charging W , the open circuit voltage V Y = V W - I * R; wherein I and R are a charging current and a direct current internal resistance of the battery respectively under the charging voltage V W ​ The voltage sampling interval time of the Vw' and the Vw" is less than or equal to 1s.

3. The battery short circuit online prediction method of claim 2, wherein, The voltage sampling interval time of the Vw' and the Vw" is 100-500ms.

4. The battery short circuit online prediction method of claim 3, wherein, The method for obtaining the direct current resistance R comprises:

5. The battery short circuit online prediction method of claim 2, wherein, The SOC value corresponding to the direct current resistance R of the battery is calculated and stored in advance according to the R=(Vw"-Vw') / I, and a SOC-R mapping relationship corresponding table is formed, and the direct current resistance R is obtained through the SOC-R mapping relationship corresponding table. The charging process of the battery is constant current charging, and the charging capacity AQ of the battery in the voltage variation interval is (T2-T1)*I0; wherein, T1 and T2 are the charging time of the voltage variation interval start and the voltage variation interval end respectively, and I0 is the charging current in the constant current charging process.

6. The battery short circuit online prediction method of any one of claims 1-5, wherein, The voltage variation interval is located in the voltage interval range corresponding to the SOC value of 0-10% and / or 90%-100% of the battery.

7. The battery short circuit online prediction method of any one of claims 1-5, wherein, The charging process of the battery is non-constant current charging, and the charging electric quantity ΔQ of the battery in the voltage variation interval is = ; wherein, T1 and T2 are the charging time at the beginning and the end of the voltage variation interval respectively, I X is the charging current at any time during the non-constant current charging process.

8. The battery short circuit online prediction method of any one of claims 1-5, wherein, The voltage variation interval is far away from the voltage interval range corresponding to the inflection point of the charging curve of the battery.

9. The battery short circuit online prediction method of any one of claims 1-5, wherein, The range of the voltage variation interval is greater than or equal to the voltage interval range corresponding to the SOC value of 3% of the battery.

10. The battery short circuit online prediction method of any one of claims 1-5, wherein, The method comprises:

11. The battery short circuit online prediction method of any one of claims 1-5, wherein, When ΔQ n+1 > ΔQ n or ΔV / ΔQ n+1 < ΔV / ΔQ n , the BMS issues a corresponding alarm message.

12. A controller characterized by comprising: The memory has instructions stored therein; The processor, when the instructions are executed by the processor, realizes the battery short circuit online prediction method as claimed in any one of claims 1 to 11. The controller as claimed in claim 12 is included.

13. An automobile characterized by comprising: When the instructions are executed by the processor, the battery short circuit online prediction method as claimed in any one of claims 1 to 11 is realized.

14. A computer-readable storage medium having stored thereon instructions, ​

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