Battery lithium precipitation detection method, device and equipment, medium and vehicle

Abstract

The invention relates to a battery lithium precipitation detection method, device and equipment, a medium and a vehicle in the technical field of vehicles. The detection method comprises the following steps: determining the actual direct current internal resistance of a battery in each charging sub-stage in a stepped charging process; the stepped charging process comprises at least two charging sub-stages, and constant-current charging is carried out on the battery at a target charging rate in each charging sub-stage; determining the target direct-current internal resistance of the battery in the corresponding charging sub-stage; the target direct-current internal resistance is a predicted value of the direct-current internal resistance obtained through a preset mathematical model; and when the difference value between the actual direct-current internal resistance and the target direct-current internal resistance is greater than a preset difference threshold value, determining that the battery is in a lithium precipitation state. Therefore, when the difference value between the actual direct-current internal resistance and the target direct-current internal resistance is larger than the preset difference threshold value, the deviation degree between the actual direct-current internal resistance and the target direct-current internal resistance is large, the battery is determined to be in the lithium precipitation state and is not interfered by current change in the stepped charging process of the battery, lithium precipitation misjudgment is avoided, and rapid and accurate online lithium precipitation detection is achieved.

Description

Technical Field

[0001] The present disclosure relates to the field of vehicle technology, and in particular to a battery lithium deposition detection method, device, equipment, medium and vehicle. Background Art

[0002] During the charging process of lithium-ion batteries, lithium ions will be deintercalated from the positive electrode and embedded in the negative electrode. However, when some abnormal conditions occur, the lithium ions deintercalated from the positive electrode cannot be embedded in the negative electrode. Then the lithium ions can only be precipitated on the surface of the negative electrode, forming a layer of gray material. This phenomenon is called lithium deposition. Lithium deposition is a loss condition of lithium-ion batteries. After lithium deposition occurs, the life of lithium-ion batteries will be accelerated, and continued use will also pose safety risks.

[0003] Related art discloses a lithium-ion battery charging method to avoid lithium plating. By superimposing a weak disturbance signal during constant current charging, the battery impedance corresponding to different state of charge (SOC) at different frequencies is measured, and the change law of the real part of the impedance at a specific frequency is extracted. If the real part or the imaginary part of the impedance decreases rapidly at the set charge capacity as charging proceeds, indicating that lithium plating has occurred, the charging current is reduced until the charging is completed. However, if the sudden decrease in impedance during charging is used as a criterion for lithium plating and applied to step charge (STC), the change in charging current will also cause a sudden change in impedance, which is easy to cause misjudgment of lithium plating. Summary of the invention

[0004] In order to solve the above technical problems, the present disclosure provides a battery lithium plating detection method, device, equipment, medium and vehicle.

[0005] In a first aspect, the present disclosure provides a battery lithium deposition detection method, comprising:

[0006] Determine the actual DC internal resistance of the battery in each charging sub-stage during the step-charging process; wherein the step-charging process includes at least two charging sub-stages, and the battery is charged with a constant current at a target charging rate in each charging sub-stage;

[0007] Determining a target DC internal resistance of the battery in a corresponding charging sub-stage; wherein the target DC internal resistance is a predicted value of the DC internal resistance obtained by a preset mathematical model;

[0008] When the difference between the actual DC internal resistance and the target DC internal resistance is greater than a preset difference threshold, it is determined that the battery is in a lithium deposition state.

[0009] Optionally, determining the actual DC internal resistance of the battery in each charging sub-stage during the step-by-step charging process includes:

[0010] Get the voltage and current values ​​of the battery during charging;

[0011] According to the voltage value and the current value, obtaining a voltage change amount and a current change amount corresponding to a first preset time length;

[0012] An actual DC internal resistance is determined, where the actual DC internal resistance is equal to a ratio of the voltage value change to the current value change.

[0013] Optionally, the battery lithium deposition detection method further includes:

[0014] An average value of the current actual DC internal resistance and a previously preset number of actual DC internal resistances is calculated, and the average value is determined to be the current actual DC internal resistance.

[0015] Optionally, determining a target DC internal resistance of the battery in a corresponding charging sub-stage includes:

[0016] Obtain the current charge capacity of the battery and the charge capacity and actual DC internal resistance at the initial moment of the charging sub-stage to which the current moment belongs;

[0017] Substituting the current charge capacity, the charge capacity at the initial moment of the charging sub-stage to which the current moment belongs, and the actual DC internal resistance into a preset mathematical model to obtain the target DC internal resistance corresponding to the current moment;

[0018] Wherein, in the preset mathematical model, the target DC internal resistance is exponentially related to the charge capacity.

[0019] Optionally, the preset mathematical model includes characteristic parameters, and the battery lithium deposition detection method further includes:

[0020] Substituting the current charge capacity and actual DC internal resistance as well as the charge capacity and actual DC internal resistance at the initial moment of the charging sub-stage to which the current moment belongs into the preset mathematical model, to obtain the actual value of the characteristic parameter corresponding to the current moment;

[0021] Based on the actual value of the characteristic parameter corresponding to the current moment, the characteristic parameter in the preset mathematical model is corrected; wherein the corrected preset mathematical model is used to calculate the target DC internal resistance at the next moment.

[0022] Optionally, the battery lithium deposition detection method further includes:

[0023] According to the current charge capacity of the battery and the preset charging table, determine the current charging sub-stage and the corresponding target charging rate;

[0024] Determine the charging rate of the battery, which is equal to the target charging rate corresponding to the charging sub-stage at the current moment

[0025] Among them, in the preset charging table, the step-by-step charging process is divided into at least two charging sub-stages according to the charge capacity from low to high, each charging sub-stage corresponds to a target charging rate, different charging sub-stages correspond to different target charging rates, and the target charging rate decreases step by step with the increase of the charge capacity.

[0026] Optionally, before determining the target DC internal resistance of the battery in the corresponding charging sub-stage, the battery lithium deposition detection method further includes:

[0027] When the charging rate of the battery remains stable within the second preset time period, performing the step of determining the target DC internal resistance of the battery in the corresponding charging sub-stage;

[0028] When the charging sub-stage is switched, the charging rate of the battery is adjusted to a target charging rate corresponding to the charging sub-stage after the switch.

[0029] Optionally, the battery lithium deposition detection method further includes:

[0030] In each charging sub-phase, a square wave pulse excitation of a preset frequency is superimposed on the charging current.

[0031] In a second aspect, the present disclosure further provides a battery lithium deposition detection device, comprising:

[0032] A first determination module is used to determine the actual DC internal resistance of the battery in each charging sub-stage during a step-charging process; wherein the step-charging process includes at least two charging sub-stages, and the battery is charged with a constant current at a target charging rate in each charging sub-stage;

[0033] A second determination module is used to determine a target DC internal resistance of the battery in a corresponding charging sub-stage; wherein the target DC internal resistance is a predicted value of the DC internal resistance obtained by a preset mathematical model;

[0034] The third determination module is used to determine that the battery is in a lithium deposition state when the difference between the actual DC internal resistance and the target DC internal resistance is greater than a preset difference threshold.

[0035] In a third aspect, the present disclosure further provides an electronic device, comprising: a memory and a processor;

[0036] The memory stores executable programs or instructions;

[0037] The processor runs the program or instruction to implement any of the above-mentioned battery lithium deposition detection methods.

[0038] In a fourth aspect, the present disclosure further provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program is executed by a processor to implement any of the above-mentioned battery lithium plating detection methods.

[0039] In a fifth aspect, the present disclosure also provides a vehicle, comprising: the above-mentioned electronic device.

[0040] Compared with the prior art, the technical solution provided by the present invention has the following advantages:

[0041] In the technical solution provided by the present invention, the difference between the actual DC internal resistance and the target DC internal resistance of the battery in each charging sub-stage during the step-type charging process is compared with a preset difference threshold; when the difference between the two is greater than the preset difference threshold, it indicates that the actual DC internal resistance deviates greatly from the target DC internal resistance, and it is determined that the battery is in a lithium deposition state. It is not affected by the current changes during the step-type charging process of the battery, avoids misjudgment of lithium deposition, and realizes fast and accurate online lithium deposition detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0043] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0044] Figure 1 A schematic diagram of a process for detecting lithium deposition in a battery provided by an embodiment of the present disclosure;

[0045] Figure 2 A schematic diagram of a charging rate-time variation curve during a step-type charging process provided in an embodiment of the present disclosure;

[0046] Figure 3 A schematic diagram of an actual DC internal resistance-time variation curve drawn based on original data provided in an embodiment of the present disclosure;

[0047] Figure 4 for Figure 1 A detailed flow chart of S110 in the battery lithium deposition detection method shown;

[0048] Figure 5 A schematic diagram of a smoothed actual DC internal resistance-time variation curve shown in an embodiment of the present disclosure;

[0049] Figure 6 for Figure 1 A detailed flow chart of S120 in the battery lithium deposition detection method shown;

[0050] Figure 7A schematic diagram of another battery lithium deposition detection method provided in an embodiment of the present disclosure;

[0051] Figure 8 A schematic diagram of a negative electrode potential change curve of a battery in different states provided by an embodiment of the present disclosure;

[0052] Fig. 9 A schematic diagram of the structure of a battery lithium deposition detection device provided in an embodiment of the present disclosure;

[0053] Fig.10 A schematic diagram of the structure of an electronic device provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0054] In order to more clearly understand the above-mentioned objectives, features and advantages of the present disclosure, the scheme of the present disclosure will be further described below. It should be noted that the embodiments of the present disclosure and the features in the embodiments can be combined with each other without conflict.

[0055] In the following description, many specific details are set forth to facilitate a full understanding of the present disclosure, but the present disclosure may also be implemented in other ways different from those described herein; it is obvious that the embodiments in the specification are only part of the embodiments of the present disclosure, rather than all of the embodiments.

[0056] In order to solve the technical problems raised in the background technology section, the embodiments of the present disclosure provide a battery lithium deposition detection method, device, equipment, medium and vehicle. Among them, the battery lithium deposition detection method includes: determining the actual DC internal resistance of the battery in each charging sub-stage during the step-by-step charging process; wherein the step-by-step charging process includes at least two charging sub-stages, and the battery is charged with a constant current at a target charging rate in each charging sub-stage; determining the target DC internal resistance of the battery in the corresponding charging sub-stage; wherein the target DC internal resistance is a predicted value of the DC internal resistance obtained by a preset mathematical model; when the difference between the actual DC internal resistance and the target DC internal resistance is greater than a preset difference threshold, it is determined that the battery is in a lithium deposition state. Thus, by comparing the difference between the actual DC internal resistance and the target DC internal resistance of the battery in each charging sub-stage during the step-by-step charging process with the preset difference threshold; when the difference between the two is greater than the preset difference threshold, it indicates that the actual DC internal resistance is more deviated from the target DC internal resistance, and the battery is determined to be in a lithium deposition state, which is not disturbed by the current change during the step-by-step charging process of the battery, avoiding misjudgment of lithium deposition, and realizing fast and accurate online lithium deposition detection.

[0057] Combination Figure 1-10 , the battery lithium deposition detection method, device, equipment, medium and vehicle provided in the embodiments of the present disclosure are exemplified.

[0058] Figure 1A schematic diagram of a battery lithium deposition detection method provided by an embodiment of the present disclosure. Figure 1 , the battery lithium deposition detection method comprises:

[0059] S110: Determine the actual DC internal resistance of the battery in each charging sub-stage during the step-by-step charging process.

[0060] The step-charging process includes at least two charging sub-stages, and the battery is charged at a constant current at a target charging rate in each charging sub-stage. The charging rate is used to characterize the charging speed, which refers to the current value required for the battery to be charged to its rated capacity within a specified time.

[0061] During the charging process, the battery's charge capacity gradually increases, and the step-by-step charging process is divided into at least two charging sub-stages according to the charge capacity from low to high. The charging sub-stages correspond to the charge capacity intervals one by one, and each charging sub-stage corresponds to a target charging rate. For example, Figure 2 , which is a schematic diagram of a charging rate-time variation curve during a step-type charging process provided by an embodiment of the present disclosure. Figure 2 In order to maximize the fast charging capability of the battery, the step-by-step charging method is used. In the charging sub-stage corresponding to the lower charge capacity interval, the battery is charged at a higher charge rate. As the charge capacity increases, the charge rate is reduced in a step-by-step manner. In the charging sub-stage corresponding to the higher charge capacity interval, the battery is charged at a lower charge rate.

[0062] Among them, the actual DC internal resistance can be a measured value directly obtained by a measuring instrument or device, such as the real part of impedance obtained by an electrochemical workstation; it can also be a calculated value obtained indirectly, such as by obtaining the voltage and current values ​​of the battery in the charging sub-stage, and taking the ratio of the battery voltage change to the corresponding current change as the actual DC internal resistance.

[0063] Optionally, in each charging sub-phase, a square wave pulse excitation of a preset frequency is superimposed on the charging current.

[0064] The outline of the square wave pulse is approximately rectangular, and its rise time and fall time are much shorter than the pulse duration. In each charging sub-stage, the battery is charged with a constant current. After the square wave pulse excitation of a preset frequency is superimposed on the charging current, the current value of the corresponding charging current fluctuates, and the voltage value also fluctuates. By obtaining the voltage and current values ​​of the battery during the square wave pulse excitation process, the ratio of the voltage value change to the current change within the preset time length is used as the actual DC internal resistance.

[0065] It is understood that the embodiment of the present disclosure only exemplarily shows the use of square wave pulse excitation, but does not constitute a limitation on the battery lithium deposition detection method provided in the embodiment of the present disclosure. In other embodiments, other waveform excitations, such as sine pulse excitation and cosine pulse excitation, may also be used, which are not limited here.

[0066] S120: Determine a target DC internal resistance of the battery in a corresponding charging sub-stage.

[0067] The target DC internal resistance is the predicted value of the DC internal resistance obtained by the preset mathematical model, which is the ideal DC internal resistance when the battery is charged with a constant current. The preset mathematical model is established based on the correlation between the target DC internal resistance and the charge capacity. By inputting the charge capacity of the corresponding charging sub-stage into the preset mathematical model, the corresponding target DC internal resistance can be obtained.

[0068] S130: When the difference between the actual DC internal resistance and the target DC internal resistance is greater than a preset difference threshold, it is determined that the battery is in a lithium deposition state.

[0069] The battery state includes the lithium deposition state and the non-lithium deposition state. Figure 3 , which is a schematic diagram of an actual DC internal resistance-time variation curve drawn based on original data provided by an embodiment of the present disclosure, wherein the solid line represents the actual DC internal resistance-time variation curve when the battery is in a lithium deposition state, and the dotted line represents the actual DC internal resistance-time variation curve when the battery is in a non-lithium deposition state. Figure 3 Compared with the case where there is no lithium deposition, the actual DC internal resistance of the battery in the lithium deposition state decreases, and the corresponding difference between the actual DC internal resistance and the target DC increases; therefore, the difference between the actual DC internal resistance and the target DC internal resistance is used to represent the degree of deviation between the actual DC internal resistance and the target DC internal resistance, and further judge whether the battery is in the lithium deposition state; when the difference between the actual DC internal resistance and the target DC internal resistance is greater than the preset difference threshold, it is determined that the battery is in the lithium deposition state; when the difference between the actual DC internal resistance and the target DC internal resistance is not greater than the preset difference threshold, it is determined that the battery is in the non-lithium deposition state.

[0070] Among them, the difference between the actual DC internal resistance and the target DC internal resistance includes at least one of an absolute difference, a relative difference and a ratio. For example, when the absolute difference between the actual DC internal resistance and the target DC internal resistance is greater than the preset absolute difference, that is, |actual DC internal resistance-target DC internal resistance|>preset absolute difference, the deviation between the actual DC internal resistance and the target DC internal resistance is large, and it is determined that the battery is in a lithium deposition state. For another example, when the relative difference between the actual DC internal resistance and the target DC internal resistance is greater than the preset relative difference, that is, |actual DC internal resistance-target DC internal resistance|÷target DC internal resistance×100%>preset relative difference, the deviation between the actual DC internal resistance and the target DC internal resistance is large, and it is determined that the battery is in a lithium deposition state. For another example, when the ratio of the actual DC internal resistance to the target DC internal resistance is less than the preset ratio, that is, the actual DC internal resistance÷target DC internal resistance<preset ratio, the deviation between the actual DC internal resistance and the target DC internal resistance is large, and it is determined that the battery is in a lithium deposition state.

[0071] It should be noted that the embodiment of the present disclosure divides the step charging process into at least two charging sub-stages. In each charging sub-stage, the difference between the actual DC internal resistance and the target DC internal resistance is compared with the preset difference value, that is, lithium plating detection and analysis is performed. This is different from the related art in which a sudden decrease in battery impedance is used as the basis for judging lithium plating. The detection result is not affected by current changes during the step charging process.

[0072] The present disclosure provides a method for detecting lithium deposition in a battery, including: determining the actual DC internal resistance of the battery in each charging sub-stage during a step-by-step charging process; wherein the step-by-step charging process includes at least two charging sub-stages, and the battery is charged with a constant current at a target charging rate in each charging sub-stage; determining the target DC internal resistance of the battery in the corresponding charging sub-stage; wherein the target DC internal resistance is a predicted value of the DC internal resistance obtained by a preset mathematical model; when the difference between the actual DC internal resistance and the target DC internal resistance is greater than a preset difference threshold, it is determined that the battery is in a lithium deposition state. Thus, by comparing the difference between the actual DC internal resistance and the target DC internal resistance in each charging sub-stage of the battery during the step-by-step charging process with the preset difference threshold; when the difference between the two is greater than the preset difference threshold, it indicates that the actual DC internal resistance deviates greatly from the target DC internal resistance, and the battery is determined to be in a lithium deposition state, and is not disturbed by the current change during the step-by-step charging process of the battery, avoiding misjudgment of lithium deposition, and realizing fast and accurate online lithium deposition detection.

[0073] In one embodiment, Figure 4 As shown, Figure 1 A detailed flow chart of S110 in the battery lithium deposition detection method shown in FIG. Figure 4 , S110 “Determining the actual DC internal resistance of the battery in each charging sub-stage during the step-by-step charging process” includes:

[0074] S411. Obtain the voltage and current values ​​of the battery during the charging process.

[0075] The voltage and current values ​​may be acquired in real time or at preset intervals.

[0076] S412: Obtain a voltage change and a current change corresponding to a first preset time length according to the voltage value and the current value.

[0077] Among them, the voltage change is the difference between the voltage value at the end of the first preset time period and the voltage value at the start of the first preset time period, and the current change is the difference between the current value at the end of the first preset time period and the current value at the start of the first preset time period; the first preset time period can be set to N time steps or preset time intervals for obtaining voltage values / current values, N is an integer and N≥1.

[0078] S413. Determine an actual DC internal resistance, where the actual DC internal resistance is equal to a ratio of a voltage value change to a current value change.

[0079] In this way, calculating the actual DC internal resistance by the ratio of the voltage value change to the current value change can simplify the DC internal resistance analysis process and can reflect the change of the battery internal resistance.

[0080] In one embodiment, the battery lithium deposition detection method further includes:

[0081] The average value of the current actual DC internal resistance and the actual DC internal resistance of a preset number of times is calculated, and the average value is determined as the current actual DC internal resistance.

[0082] in, Figure 3 The actual DC internal resistance-time variation curve is drawn based on the original data. The calculated actual DC internal resistance generates jitter due to sampling error and test environment. In order to filter out noise, the actual DC internal resistance-time variation curve needs to be smoothed.

[0083] The smoothing method of the actual DC internal resistance-time variation curve is: select the current actual DC internal resistance and a preset number (M-1) of actual DC internal resistances before it, calculate the average value of the selected M actual DC internal resistances, and the average value is the current actual DC internal resistance after smoothing; that is, in is the current actual DC internal resistance after smoothing, and k is the sequence number of the current DC internal resistance.

[0084] For example, Figure 5 , which is a schematic diagram of a smoothed actual DC internal resistance-time variation curve shown in an embodiment of the present disclosure. Figure 5, the preset number is set to 39, that is, M is equal to 40, select the current actual DC internal resistance (whose sequence number is k, k is an integer greater than or equal to 40) and the 39 actual DC internal resistances before it (the corresponding sequence numbers are: k-39, k-38, k-37, ..., k-1), calculate the average value of the selected 40 actual DC internal resistances (the corresponding sequence numbers are k-39 to k), select and calculate the average value of each 40 actual DC internal resistances in sequence, that is, calculate the average value of the 1st to 40th actual DC internal resistances, calculate the average value of the 2nd to 41st actual DC internal resistances, and so on to obtain the smoothed actual DC internal resistance-time variation curve.

[0085] It should be noted that, in the initial stage of battery lithium plating detection, when the number of actual DC internal resistances determined is less than or equal to the preset number (i.e., k is less than or equal to 39), the actual DC internal resistance corresponding to this period is equal to 0; when the number of actual DC internal resistances to be determined is greater than the preset number (i.e., k is greater than or equal to 40), the first smoothed actual DC internal resistance can be obtained.

[0086] In one embodiment, Figure 6 As shown, Figure 1 A detailed flow chart of S120 in the battery lithium deposition detection method shown in FIG. Figure 6 S120 “determining the target DC internal resistance of the battery in the corresponding charging sub-stage” includes:

[0087] S621, obtaining the current charge capacity of the battery and the charge capacity and actual DC internal resistance at the initial time of the charging sub-stage to which the current time belongs.

[0088] S622, substituting the current charge capacity and the charge capacity at the initial time of the charging sub-stage to which the current time belongs and the actual DC internal resistance into a preset mathematical model to obtain a target DC internal resistance corresponding to the current time;

[0089] Among them, in the preset mathematical model, the target DC internal resistance is exponentially related to the charge capacity; as the charge capacity increases, the target DC internal resistance tends to decrease.

[0090] Exemplarily, the formula of the preset mathematical model is set as:

[0091] Where Z is the target DC internal resistance, Z 0 The actual DC internal resistance at the initial moment of the charging sub-stage to which the current moment belongs; SOC 0 is the charge capacity at the initial moment of the charging sub-stage to which the current moment belongs; SOC is the charge capacity at the current moment; A and m are characteristic parameters in the preset mathematical model.

[0092] In one embodiment, the preset mathematical model includes characteristic parameters, and the battery lithium deposition detection method further includes:

[0093] Substitute the current charge capacity and actual DC internal resistance as well as the charge capacity and actual DC internal resistance at the initial moment of the charging sub-stage to which the current moment belongs into the preset mathematical model to obtain the actual value of the characteristic parameter corresponding to the current moment;

[0094] Based on the actual value of the characteristic parameter corresponding to the current moment, the characteristic parameter in the preset mathematical model is corrected.

[0095] The modified preset mathematical model is used to calculate the target DC internal resistance at the next moment.

[0096] In this embodiment, the charge capacity and actual DC internal resistance at the current moment and the charge capacity and actual DC internal resistance at the initial moment of the charging sub-stage to which the current moment belongs are brought into a preset mathematical model, and the actual values ​​of the characteristic parameters (for example, including A and m) corresponding to the current moment are identified using an extended Kalman filter (EKF) algorithm; then, based on the actual values ​​of the characteristic parameters, the characteristic parameters in the preset mathematical model used to calculate the target DC internal resistance at the current moment are corrected, so that the corrected characteristic parameters are equal to the actual values ​​of the characteristic parameters corresponding to the current moment; the target DC internal resistance at the next moment is predicted using the corrected preset mathematical model; or the charge capacity and actual DC internal resistance at the previous moment and the charge capacity and actual DC internal resistance at the initial moment of the charging sub-stage to which the previous moment belongs are brought into a preset mathematical model, and the actual values ​​of the characteristic parameters A and m corresponding to the current moment are identified using an EKF algorithm, and then the characteristic parameters in the preset mathematical model are corrected, so that the corrected characteristic parameters are equal to the actual values ​​of the characteristic parameters corresponding to the previous moment, and the target DC internal resistance at the current moment is calculated using the corrected preset mathematical model. In this way, the accuracy of the target DC internal resistance is improved by real-time identification and correction of the characteristic parameters A and m in the preset mathematical model.

[0097] In one embodiment, the battery lithium deposition detection method further includes:

[0098] According to the current charge capacity of the battery and the preset charging table, determine the current charging sub-stage and the corresponding target charging rate;

[0099] Determine the charging rate of the battery, which is equal to the target charging rate corresponding to the charging sub-stage at the current moment.

[0100] Among them, in the preset charging table, the step-by-step charging process is divided into at least two charging sub-stages according to the charge capacity from low to high, each charging sub-stage corresponds to a target charging rate, and different charging sub-stages correspond to different target charging rates, and the target charging rate decreases step by step as the charge capacity increases. The preset charging table is saved in the battery management system (BMS); when the battery charge capacity is equal to 100%, the battery management system cuts off the charging path between the external power supply and the battery to prevent the battery from overcharging; when the battery charge capacity is lower than the set minimum charge capacity, the battery management system cuts off the discharge path between the battery and the external power device to prevent the battery from over-discharging, thereby extending the battery life.

[0101] For example, in the preset charging table, the step-by-step charging process is divided into five charging sub-stages according to the charge capacity from low to high. The first charge capacity interval is [0, 20%), and the corresponding target charging rate is K 1 ; The second charge capacity interval is [20%, 40%), and the corresponding target charge rate is K 2 ; The third charge capacity interval is [40%, 60%), and the corresponding target charge rate is K 3 ; The fourth charge capacity interval is [60%, 80%), and the corresponding target charge rate is K 4 ; The fifth charge capacity interval is [80%, 100%), and the corresponding target charge rate is K 5 ; Among them, the size relationship of the target charging rate corresponding to the five charging sub-stages is: K 1 >K 2 >K 3 >K 4 >K 5 >0.

[0102] It can be understood that the embodiment of the present disclosure only exemplarily shows that the step-type charging process includes five charging sub-stages and the corresponding relationship between the five charging sub-stages and the charge capacity interval, but does not constitute a limitation on the battery lithium deposition detection method provided by the embodiment of the present disclosure. In other embodiments, the step-type charging sub-stages can be divided according to the requirements of the battery lithium deposition detection method, and the number of charging sub-stages can be two, three, four, six or more, which is not limited here.

[0103] In one embodiment, before “determining the target DC internal resistance of the battery in the corresponding charging sub-stage”, the battery lithium deposition detection method further includes:

[0104] When the charging rate of the battery remains stable within the second preset time period, performing the step of determining the target DC internal resistance of the battery in the corresponding charging sub-stage;

[0105] When the charging sub-stage is switched, the charging rate of the battery is adjusted to a target charging rate corresponding to the charging sub-stage after the switch.

[0106] During the charging process, the charge capacity of the battery gradually increases. When the charge capacity exceeds the current charge capacity interval and enters the next charge capacity interval, the corresponding charging sub-stage is switched, and the charging rate of the battery is also switched to the target charging rate corresponding to the charging sub-stage after the switch; the charging rate after the switch is less than the charging rate before the switch, and the reduction in the charging rate will cause the charging current to decrease, that is, the current change increases, so that the calculated actual DC internal resistance decreases, and the corresponding difference between the actual DC internal resistance and the target internal resistance is likely to exceed the preset difference threshold, but the battery does not necessarily undergo lithium deposition at this time, thereby Leading to misjudgment of lithium plating; therefore, in order to avoid the misjudgment of lithium plating caused by the above situation, the charging rate of the battery is obtained, and when the charging rate of the battery remains stable within the second preset time period, that is, the charging rate of the battery has not switched, the step of "determining the target DC internal resistance of the battery in the corresponding charging sub-stage" and subsequent steps are executed; when the charging rate of the battery changes within the second preset time period, that is, the battery enters the next charging sub-stage, the charging rate of the battery is switched (the corresponding charging current is also switched), the step of "determining the target DC internal resistance of the battery in the corresponding charging sub-stage" and subsequent steps are not executed, and lithium plating detection is not performed.

[0107] For example, Figure 3 or Figure 5 As shown, compared with the state without lithium deposition, the actual DC internal resistance corresponding to a, b, c and d is abnormally reduced when the battery is in the lithium deposition state; wherein, a, c and d are the abnormal reduction of the actual DC internal resistance caused by lithium deposition of the battery, and b is the abnormal reduction of the actual DC internal resistance caused by the switching of the charging rate (or charging current). This embodiment can exclude the situation where the actual DC internal resistance is abnormally reduced due to the switching of the charging rate (or charging current), thereby avoiding the misjudgment of lithium deposition.

[0108] For example, Figure 7 FIG. 1 is a flow chart of another method for detecting lithium deposition in a battery provided by an embodiment of the present disclosure. Figure 7 , the battery lithium deposition detection method comprises:

[0109] S710: Obtain current value and voltage value of the battery during the step-by-step charging process, wherein the current value and voltage value change periodically over time.

[0110] Among them, in each charging sub-stage of step charging, the battery is charged with a constant current; by superimposing a pulse wave of a preset frequency on the charging current for excitation, the frequency of the current value and voltage value pulse wave changes periodically, and the pulse wave can be selected from all waveforms known to technical personnel in this field, such as square wave pulses, which are not limited here.

[0111] S720: Calculate the actual DC internal resistance according to the current value and the voltage value.

[0112] In this step, the voltage change and current change corresponding to the preset time length are calculated based on the current value and the voltage value and the corresponding time, and the ratio of the voltage change to the current change is used as the actual DC internal resistance.

[0113] S730: Do you want to switch the current?

[0114] In this step, the current charging current (or charging rate) of the battery is compared with the charging current (or charging rate) of the previous acquisition cycle. If the deviation between the current charging current (or charging rate) and the charging current (or charging rate) of the previous acquisition cycle does not exceed the preset deviation threshold, that is, no current switching is performed, the judgment result is no, and S750 is executed; if the deviation between the current charging current (or charging rate) and the charging current (or charging rate) of the previous acquisition cycle exceeds the preset deviation threshold, that is, current switching is performed, the judgment result is yes, and S740 is executed.

[0115] S740: No lithium plating test is performed.

[0116] S750: Calculate the target DC internal resistance of the battery based on a preset mathematical model.

[0117] In this step, the charge capacity and actual DC internal resistance at the previous moment and the charge capacity and actual DC internal resistance at the initial moment of the charging sub-stage to which the previous moment belongs are brought into the preset mathematical model to determine the characteristic parameters corresponding to the previous moment; then the charge capacity at the current moment and the charge capacity and actual DC internal resistance at the initial moment of the charging sub-stage to which the current moment belongs are substituted into the preset mathematical model, the characteristic parameters in the preset mathematical model are the characteristic parameters corresponding to the previous moment determined in the previous step, and the target DC internal resistance corresponding to the current moment is calculated.

[0118] S760: When the deviation between the actual DC internal resistance and the target DC internal resistance exceeds a preset threshold, determine that the battery is in a lithium deposition state.

[0119] In this step, when the deviation between the actual DC internal resistance and the target DC internal resistance exceeds the preset threshold, it is determined that the battery is in a lithium deposition state; when the deviation between the actual DC internal resistance and the target DC internal resistance does not exceed the preset threshold, it is determined that the battery is in a non-lithium deposition state.

[0120] The disclosed embodiment also verifies the detection results of the above-mentioned battery lithium deposition detection method, and compares the negative electrode potential change curves of batteries in different states, such as Figure 8 As shown, the negative electrode potential of the battery in the non-lithium deposition state is above 0V, while the negative electrode potential of the battery in the lithium deposition state drops below 0V at a, c, and d, indicating that lithium deposition occurs in the battery, verifying the accuracy of the lithium deposition detection results.

[0121] Based on the same inventive concept, an embodiment of the present disclosure also provides a battery lithium deposition detection device, which is used to execute the steps of any of the above-mentioned battery lithium deposition detection methods and has corresponding beneficial effects. The similarities can be understood by referring to the above and will not be repeated in the following text.

[0122] In one embodiment, Fig. 9 FIG. 1 is a schematic diagram of a battery lithium deposition detection device provided by an embodiment of the present disclosure. Fig. 9 The battery lithium deposition detection device 900 includes: a first determination module 901, used to determine the actual DC internal resistance of the battery in each charging sub-stage during the step-by-step charging process; wherein the step-by-step charging process includes at least two charging sub-stages, and the battery is charged with a constant current at a target charging rate in each charging sub-stage; a second determination module 902, used to determine the target DC internal resistance of the battery in the corresponding charging sub-stage; wherein the target DC internal resistance is a predicted value of the DC internal resistance obtained by a preset mathematical model; and a third determination module 903, used to determine that the battery is in a lithium deposition state when the difference between the actual DC internal resistance and the target DC internal resistance is greater than a preset difference threshold.

[0123] In one embodiment, the first determination module is used to determine the actual DC internal resistance of the battery in each charging sub-stage during the step-by-step charging process, including: obtaining the voltage value and current value of the battery during the charging process; obtaining the voltage change and current change corresponding to the first preset time length based on the voltage value and the current value; and determining that the actual DC internal resistance is equal to the ratio of the voltage value change to the current value change.

[0124] In one embodiment, the first determination module is further used to: calculate an average value of the current actual DC internal resistance and a previously preset number of actual DC internal resistances, and determine the average value as the current actual DC internal resistance.

[0125] In one embodiment, the second determination module is used to determine the target DC internal resistance of the battery in the corresponding charging sub-stage, including: obtaining the charge capacity of the battery at the current moment and the charge capacity and the actual DC internal resistance at the initial moment of the charging sub-stage to which the current moment belongs; substituting the charge capacity at the current moment and the charge capacity and the actual DC internal resistance at the initial moment of the charging sub-stage to which the current moment belongs into a preset mathematical model to obtain the target DC internal resistance corresponding to the current moment; wherein, in the preset mathematical model, the target DC internal resistance is exponentially related to the charge capacity.

[0126] In one embodiment, the preset mathematical model includes characteristic parameters, and the second determination module is also used to: bring the charge capacity and actual DC internal resistance at the previous moment and the charge capacity and actual DC internal resistance at the initial moment of the charging sub-stage to which the previous moment belongs into the preset mathematical model to determine the characteristic parameters corresponding to the previous moment; wherein the characteristic parameters corresponding to the previous moment are used to calculate the target DC internal resistance at the current moment.

[0127] In one embodiment, the battery lithium plating detection device also includes: a fourth determination module; the fourth determination module is used to determine the charging sub-stage and the corresponding target charging rate at the current moment according to the charge capacity of the battery at the current moment and a preset charging table, and determine that the charging rate of the battery is equal to the target charging rate corresponding to the charging sub-stage at the current moment; wherein, in the preset charging table, the step-by-step charging process is divided into at least two charging sub-stages from low to high according to the charge capacity, each charging sub-stage corresponds to a target charging rate, different charging sub-stages correspond to different target charging rates, and the target charging rate decreases step by step with the increase of the charge capacity.

[0128] In one embodiment, before determining the target DC internal resistance of the battery in the corresponding charging sub-stage, the fourth determination module is also used to: when the charging rate of the battery remains stable within a second preset time period, execute the step of determining the target DC internal resistance of the battery in the corresponding charging sub-stage; wherein, when the charging sub-stage switches, the charging rate of the battery is adjusted to the target charging rate corresponding to the charging sub-stage after the switch.

[0129] Optionally, the battery lithium deposition detection device further includes: an excitation module; the excitation module is used to superimpose a square wave pulse excitation of a preset frequency on the charging current in each charging sub-stage.

[0130] The device can be implemented by software and / or hardware, and can be integrated on any processor or electronic device with computing capability. For contents not described in detail in the device embodiment of the present disclosure, reference can be made to the description in any method embodiment of the present disclosure.

[0131] Based on the above implementation, Fig.10 FIG. 1 is a schematic diagram of the structure of an electronic device provided by an embodiment of the present disclosure. Fig.10 The electronic device 1000 includes: a memory 1001 and a processor 1002; the memory 1001 stores executable programs or instructions; the processor 1002 runs the programs or instructions to implement any of the above-mentioned deceleration and anti-skid control methods, which have corresponding beneficial effects. To avoid repeated description, they will not be repeated here.

[0132] The processor 1002 may be a central processing unit (CPU) or other forms of processing units having data processing capabilities and / or instruction execution capabilities, and may control other components in the computer to perform desired functions.

[0133] The memory 1001 may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and / or cache memory (cache), etc. Non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 1002 may execute the program instructions to implement the method steps of the various embodiments of the present application described above and / or other desired functions.

[0134] In addition to the above-mentioned methods and apparatus, embodiments of the present application may also be a computer program product, which includes computer program instructions, and when the computer program instructions are executed by a processor, the processor executes the method steps of various embodiments of the present application.

[0135] The computer program product may be written in any combination of one or more programming languages ​​to write program code for performing the operations of the embodiments of the present invention, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0136] On the basis of the above-mentioned implementation manner, the embodiment of the present disclosure further provides a computer-readable storage medium on which a computer program or instruction is stored. When the computer program or instruction is executed by the processor, the processor executes the method steps of various embodiments of the present disclosure to implement any of the above-mentioned deceleration and anti-skid control methods, which has corresponding beneficial effects. To avoid repeated description, it will not be repeated here.

[0137] The computer-readable medium may be included in the electronic device, or may exist independently without being incorporated into the electronic device.

[0138] Computer readable storage media may take any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may include, for example, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or devices, or any combination of the above. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0139] Based on the above implementation, the embodiment of the present disclosure further provides a vehicle. The vehicle includes: the above electronic device.

[0140] In other embodiments, the vehicle also includes all other vehicle-mounted equipment or devices known to those skilled in the art, such as a vehicle control unit and a storage unit, etc., which are not limited here.

[0141] It should be noted that, in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0142] The above description is only a specific embodiment of the present disclosure, so that those skilled in the art can understand or implement the present disclosure. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present disclosure. Therefore, the present disclosure will not be limited to the embodiments described herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A battery lithium deposition detection method, characterized in that: include: Determine the actual DC internal resistance of the battery in each charging sub-stage during the step-charging process; wherein the step-charging process includes at least two charging sub-stages, and the battery is charged with a constant current at a target charging rate in each charging sub-stage; Determining a target DC internal resistance of the battery in a corresponding charging sub-stage; wherein the target DC internal resistance is a predicted value of the DC internal resistance obtained by a preset mathematical model; When the difference between the actual DC internal resistance and the target DC internal resistance is greater than a preset difference threshold, it is determined that the battery is in a lithium deposition state.

2. The battery lithium deposition detection method according to claim 1, characterized in that: The method of determining the actual DC internal resistance of the battery in each charging sub-stage during the step-by-step charging process includes: Get the voltage and current values ​​of the battery during charging; According to the voltage value and the current value, obtaining a voltage change amount and a current change amount corresponding to a first preset time length; An actual DC internal resistance is determined, where the actual DC internal resistance is equal to a ratio of the voltage value change to the current value change.

3. The battery lithium deposition detection method according to claim 2, characterized in that: Also includes: An average value of the current actual DC internal resistance and a previously preset number of actual DC internal resistances is calculated, and the average value is determined to be the current actual DC internal resistance.

4. The battery lithium deposition detection method according to any one of claims 1 to 3, characterized in that: The determining of the target DC internal resistance of the battery in the corresponding charging sub-stage includes: Obtain the current charge capacity of the battery and the charge capacity and actual DC internal resistance at the initial moment of the charging sub-stage to which the current moment belongs; Substituting the current charge capacity, the charge capacity at the initial moment of the charging sub-stage to which the current moment belongs, and the actual DC internal resistance into a preset mathematical model to obtain the target DC internal resistance corresponding to the current moment; Wherein, in the preset mathematical model, the target DC internal resistance is exponentially related to the charge capacity.

5. The battery lithium deposition detection method according to claim 4, characterized in that: The preset mathematical model includes characteristic parameters, and the battery lithium deposition detection method further includes: Substituting the current charge capacity and actual DC internal resistance as well as the charge capacity and actual DC internal resistance at the initial moment of the charging sub-stage to which the current moment belongs into the preset mathematical model, to obtain the actual value of the characteristic parameter corresponding to the current moment; Based on the actual value of the characteristic parameter corresponding to the current moment, the characteristic parameter in the preset mathematical model is corrected; wherein the corrected preset mathematical model is used to calculate the target DC internal resistance at the next moment.

6. The battery lithium deposition detection method according to claim 4, characterized in that: Also includes: According to the current charge capacity of the battery and the preset charging table, determine the current charging sub-stage and the corresponding target charging rate; Determine a charging rate of the battery, where the charging rate is equal to a target charging rate corresponding to the charging sub-stage at the current moment; Among them, in the preset charging table, the step-by-step charging process is divided into at least two charging sub-stages according to the charge capacity from low to high, each charging sub-stage corresponds to a target charging rate, different charging sub-stages correspond to different target charging rates, and the target charging rate decreases step by step with the increase of the charge capacity.

7. The battery lithium deposition detection method according to claim 6, characterized in that: Before determining the target DC internal resistance of the battery in the corresponding charging sub-stage, the battery lithium deposition detection method further includes: When the charging rate of the battery remains stable within the second preset time period, performing the step of determining the target DC internal resistance of the battery in the corresponding charging sub-stage; When the charging sub-stage is switched, the charging rate of the battery is adjusted to a target charging rate corresponding to the charging sub-stage after the switch.

8. The battery lithium deposition detection method according to claim 1, characterized in that: Also includes: In each charging sub-phase, a square wave pulse excitation of a preset frequency is superimposed on the charging current.

9. A battery lithium deposition detection device, characterized in that: include: A first determination module is used to determine the actual DC internal resistance of the battery in each charging sub-stage during a step-charging process; wherein the step-charging process includes at least two charging sub-stages, and the battery is charged with a constant current at a target charging rate in each charging sub-stage; A second determination module is used to determine a target DC internal resistance of the battery in a corresponding charging sub-stage; wherein the target DC internal resistance is a predicted value of the DC internal resistance obtained by a preset mathematical model; The third determination module is used to determine that the battery is in a lithium deposition state when the difference between the actual DC internal resistance and the target DC internal resistance is greater than a preset difference threshold.

10. An electronic device, characterized in that: include: Memory and processor; The memory stores executable programs or instructions; The processor runs the program or instruction to implement the battery lithium deposition detection method according to any one of claims 1 to 8.

11. A computer readable medium having a computer program or instruction stored thereon, characterized in that: The computer program is executed by a processor to implement the battery lithium deposition detection method as described in any one of claims 1 to 8.

12. A vehicle, characterized in that: include: The electronic device as claimed in claim 10.

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