Battery direct current internal resistance and battery capacity data preprocessing method, system and program product

Abstract

The invention discloses a battery direct-current internal resistance and battery capacity data preprocessing method and system and a program product, and the method comprises the steps: judging the current state of a time period between a current moment and a previous moment according to the current change values of the current moment and the previous moment; calculating the direct-current internal resistance of the battery at the current moment and the true value interval of the direct-current internal resistance of the battery corresponding to the current moment according to the current state of the time interval between the current moment and the previous moment and the charging and discharging state of the battery; judging whether the battery DC internal resistance is a true value according to the true value interval; and if the direct-current internal resistance of the battery is not the true value, correcting the direct-current internal resistance of the battery. According to the method, authenticity judgment is carried out on the battery data, meanwhile, the false value is corrected, the data quality is improved, the battery SOH prediction time can be shortened to a certain extent, and the battery SOH prediction precision can be improved.

Description

Technical Field

[0001] The present invention relates to the field of power batteries, and in particular to a method, system and program product for preprocessing battery DC internal resistance and battery capacity data. Background Art

[0002] Battery SOH (State of Healthy) is a key parameter of power batteries. It is a measure of the available energy of the battery and an important reference for predicting the remaining life of the battery. Therefore, the estimation of SOH is very important. The SOH of power batteries cannot be measured directly and needs to be estimated based on relevant parameters during the use of the battery.

[0003] At present, the estimation method based on big data is the most commonly used battery SOH estimation method. The technical solution of the power battery SOH estimation method based on big data is generally as follows: first, obtain massive battery data and process the data; then extract features from the data and divide the data into a training set and a validation set; finally, build a data-based startup model, substitute the training set data into the model operation, output the predicted value, and compare the output layer result with the validation set, adjust the model parameters according to the comparison difference, and then continuously train the model and iterate the model parameters to achieve the final expected prediction result.

[0004] However, the big data-based estimation method does not consider the authenticity of the data itself when preprocessing the battery data. In this way, the battery data that has not been refined and preprocessed is imported into the data-driven model, which will increase the prediction time and affect the robustness of the model. On the other hand, it will also increase the estimation error and reduce the estimation accuracy. Summary of the invention

[0005] The purpose of the present invention is to provide a battery DC internal resistance and battery capacity data preprocessing method, system and program product, aiming to solve the problem that the estimation method based on big data in the prior art does not consider the authenticity judgment of the data itself when preprocessing the battery data.

[0006] In order to solve the above technical problems, the present invention is achieved through the following technical solutions:

[0007] In one aspect, the present invention provides a method for preprocessing battery DC internal resistance data, comprising:

[0008] Determine the current state of the period between the current moment and the previous moment according to the current change value between the current moment and the previous moment;

[0009] Calculate the battery DC internal resistance at the current moment and the true value interval of the battery DC internal resistance corresponding to the current moment according to the current state and the battery charge and discharge state during the period between the current moment and the previous moment;

[0010] Determining whether the battery DC internal resistance is a true value according to the true value interval;

[0011] If the battery DC internal resistance is not a true value, the battery DC internal resistance is corrected.

[0012] Further, judging the current state in the period between the current moment and the previous moment according to the current change value between the current moment and the previous moment includes:

[0013] Determining the current state of the time period according to whether the current change value is greater than a preset change value;

[0014] If yes, then the period is a variable flow period;

[0015] If not, the period is a constant current period;

[0016] Among them, the current value at the current moment is I t , the current value at the previous moment is I t-1 , the current change value is |I t -I t-1 |.

[0017] Furthermore, the battery DC internal resistance at the current moment and the true value interval of the battery DC internal resistance corresponding to the current moment are calculated according to the current state and the battery charge and discharge state in the period between the current moment and the previous moment, including:

[0018] When the period is a constant current period, the battery DC internal resistance R CC =ΔU / I;

[0019] In the charging state, ΔU=U t-1 -U t , R CC =(U t-1 -U t ) / I, maximum DC internal resistance

[0020] In the discharge state, ΔU=U t -U t-1 , R CC =(U t -U t-1 ) / I, maximum DC internal resistance

[0021] When the time period is a variable current time period, the battery DC internal resistance R RC =ΔU / ΔI;

[0022] In the charging state, ΔU=U t-1 -U t , ΔI=It-1 -I t , R RC =(U t-1 -U t ) / (I t-1 -I t ), maximum DC internal resistance R max =(U t-1 -U max ) / (I t -I t-1 );

[0023] In the discharge state, ΔU=U t -U t-1 , ΔI=I t -I t-1 , R RC =(U t -U t-1 ) / (I t -I t-1 ), maximum DC internal resistance R max =(U min -U t-1 ) / (I t -I t-1 );

[0024] The true value interval of the battery DC internal resistance is [0, R max ];

[0025] Among them, ΔU is the voltage change, U t is the voltage value at the current moment, U t-1 is the voltage value at the previous moment, I is the geometric mean current during the constant current period, that is, ΔI is the current change, U max When charging U t Maximum battery voltage upper limit, U min U is the discharge time t The lower limit of the maximum battery voltage, U max and U min Related to the material of the battery.

[0026] Furthermore, if the battery DC internal resistance is not a true value, the battery DC internal resistance is corrected, including:

[0027] According to the SOC-OCV curve, obtain the corresponding open circuit voltage OCV at the current moment SOC，t ;

[0028] According to U t =OCV SOC，t -I t R t Get the current internal resistance value Rt =(OCV SOC，t -U t ) / I t ;

[0029] The battery DC internal resistance true value R at the previous moment t-1 As a priori value, the current internal resistance value R t As the observed value, the battery DC corrected internal resistance BR at the current moment is calculated according to the Kalman filter method. t .

[0030] On the other hand, the present invention also provides a battery capacity data preprocessing method, comprising:

[0031] Calculating a capacity difference between a battery capacity at a first moment and a battery capacity at a second moment after a preset time, and a theoretical maximum change value of the battery capacity between the first moment and the second moment;

[0032] Determining whether the battery capacity at the second moment is a true value according to the capacity difference and the theoretical maximum change value of the battery capacity;

[0033] If the battery capacity at the second moment is not a true value, the battery capacity at the second moment is corrected.

[0034] Further, the calculating of the capacity difference between the battery capacity at the first moment and the battery capacity at the second moment after a preset time, and the theoretical maximum change value of the battery capacity between the first moment and the second moment, includes:

[0035] The battery capacity value at the first moment is C t , the battery capacity value at the second moment is C t+Δt The capacity difference between the second moment and the first moment is (C t+Δt -C t );

[0036] The theoretical maximum change value ΔC of the battery capacity between the first moment and the second moment max =I max *Δt;

[0037] The first time is t, the preset time is Δt, the second time is t+Δt, I max is the maximum current value within the preset time.

[0038] Furthermore, if the battery capacity at the second moment is not a true value, correcting the battery capacity at the second moment includes:

[0039] Obtain the battery SOC at the first moment and the second moment tand battery SOC t+Δt ;

[0040] According to the battery SOC t With the battery SOC t+Δt Get the battery SOC change (SOC t+Δt -SOC t );

[0041] The battery capacity change ΔC within the preset time is obtained according to the battery SOC change t+Δt -SOC t )*C N ;

[0042] Obtain the battery capacity correction value C at the second moment according to the battery capacity change t+Δt =C t +ΔC;

[0043] Among them, C N is the rated capacity of the battery.

[0044] The present invention also provides a battery DC internal resistance data preprocessing system, comprising:

[0045] A first judgment unit, used to judge the current state of the period between the current moment and the previous moment according to the current change value between the current moment and the previous moment;

[0046] A first calculation unit, used to calculate the DC internal resistance of the battery at the current moment and the true value interval of the DC internal resistance of the battery corresponding to the current moment according to the current state in the period between the current moment and the previous moment and the charge and discharge state of the battery;

[0047] A second judgment unit, configured to judge whether the battery DC internal resistance is a true value according to the true value interval;

[0048] The first correction unit is used to correct the battery DC internal resistance if the battery DC internal resistance is not a true value.

[0049] The present invention also provides a battery capacity data preprocessing system, comprising:

[0050] a second calculation unit, configured to calculate a capacity difference between a battery capacity at a first moment and a battery capacity at a second moment after a preset time, and a theoretical maximum change value of the battery capacity between the first moment and the second moment;

[0051] a third judging unit, configured to judge whether the battery capacity at the second moment is a true value according to the capacity difference and the theoretical maximum change value of the battery capacity;

[0052] The second correction unit is used to correct the battery capacity at the second moment if the battery capacity at the second moment is not a true value.

[0053] The present invention also provides a computer program product, including a computer program, which implements the steps of the above-mentioned battery DC internal resistance data preprocessing method or battery capacity data preprocessing method when executed by a processor.

[0054] The embodiment of the present invention provides a method, system and computer program product for preprocessing the DC internal resistance and battery capacity data of a battery, wherein the DC internal resistance data preprocessing method of the battery comprises: judging the current state of the time period between the current moment and the previous moment according to the current change value between the current moment and the previous moment; calculating the DC internal resistance of the battery at the current moment and the true value interval of the DC internal resistance of the battery corresponding to the current moment according to the current state of the time period between the current moment and the previous moment and the charge and discharge state of the battery; judging whether the DC internal resistance of the battery is a true value according to the true value interval; if the DC internal resistance of the battery is not a true value, correcting the DC internal resistance of the battery. The present invention judges the authenticity of the battery data and corrects the false value at the same time, thereby improving the data quality, and can reduce the battery SOH prediction time and improve the prediction accuracy of the battery SOH to a certain extent. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying any creative work.

[0056] Figure 1 A schematic diagram of a flow chart of a method for preprocessing battery DC internal resistance data provided by an embodiment of the present invention;

[0057] Figure 2 A schematic diagram of a flow chart of a battery capacity data preprocessing method provided by an embodiment of the present invention;

[0058] Figure 3 A schematic diagram of a sub-process of a battery DC internal resistance data preprocessing method provided by an embodiment of the present invention;

[0059] Figure 4 A schematic diagram of a sub-process of a battery DC internal resistance data preprocessing method provided by an embodiment of the present invention;

[0060] Figure 5 A schematic diagram of a sub-process of a battery DC internal resistance data preprocessing method provided by an embodiment of the present invention;

[0061] Figure 6A schematic diagram of a sub-process of a battery DC internal resistance data preprocessing method provided by an embodiment of the present invention;

[0062] Figure 7 A schematic diagram of a sub-process of a battery capacity data preprocessing method provided by an embodiment of the present invention;

[0063] Figure 8 A schematic diagram of a sub-process of a battery capacity data preprocessing method provided by an embodiment of the present invention;

[0064] Fig. 9 A schematic diagram of a sub-process of a battery capacity data preprocessing method provided by an embodiment of the present invention;

[0065] Fig.10 A structural block diagram of a battery DC internal resistance data preprocessing system provided in an embodiment of the present invention;

[0066] Fig.11 This is a structural block diagram of a battery capacity data preprocessing system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0067] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0068] It should be understood that when used in this specification and the appended claims, the terms "include" and "comprises" indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0069] It should also be understood that the terms used in this specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the specification of the present invention and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0070] It should be further understood that the term "and / or" used in the present description and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0071] The coasting of the car in the present invention does not include coasting under braking, because braking triggers brake energy recovery. At this time, safety should be considered first. Energy recovery is carried out under the premise of safety. The size of energy recovery depends on many aspects, such as the structure of the braking system, the torque distribution relationship between mechanical braking and electric braking, and the user's braking torque demand corresponding to the corresponding brake pedal opening, etc. These are not within the setting range of the present invention. The present invention only considers the energy recovery intensity setting during the coasting process, that is, when the brake pedal is not pressed.

[0072] Combination Figure 1 As shown, on the one hand, the present invention provides a battery DC internal resistance data preprocessing method, comprising steps S10 to S40:

[0073] S10, judging the current state of the period between the current moment and the previous moment according to the current change value between the current moment and the previous moment;

[0074] S20, calculating the battery DC internal resistance at the current moment and the true value interval of the battery DC internal resistance corresponding to the current moment according to the current state and the charge and discharge state of the battery in the time period between the current moment and the previous moment;

[0075] S30, judging whether the DC internal resistance of the battery is a true value according to the true value interval;

[0076] S40: If the battery DC internal resistance is not a true value, the battery DC internal resistance is corrected.

[0077] In the embodiment of the present invention, when performing the battery SOH estimation method, the working data of the battery is divided into multiple time periods, and the beginning and end of each time period are respectively the current moment and the previous moment. When the battery DC internal resistance data at the current moment is refined and preprocessed, first, the current state of the time period is judged to be in a constant current state or a variable current state according to the current change value between the current moment and the previous moment, and the battery state is obtained according to the battery DC at the current moment. The state of the battery is in a charging state or a discharging state. Different current states and battery states will lead to different calculation formulas for the battery DC internal resistance. The battery DC internal resistance at this moment is calculated according to Ohm's law; secondly, the true value interval of the battery DC internal resistance corresponding to the moment is calculated according to the current state and the battery state, so as to judge whether the battery DC internal resistance is a true value; finally, when the battery DC internal resistance is not a true value, that is, when the battery DC internal resistance is a false value, the battery DC internal resistance is corrected. By judging the authenticity of the battery DC internal resistance and correcting the false value at the same time, the quality of the battery DC internal resistance data is improved, and the battery SOH prediction time can be reduced to a certain extent and the prediction accuracy of the battery SOH can be improved.

[0078] Specifically, the battery state is determined based on whether the current is less than zero; if so, the battery is in a charging state; if not, the battery is in a discharging state.t <0, the battery is in charging state, I t When >0, the battery is in discharge state.

[0079] Combination Figure 3 As shown, in some embodiments, the current state of the period between the current moment and the previous moment is determined according to the current change value between the current moment and the previous moment, that is, step S10 includes steps S101 to S103:

[0080] S101, judging the current state of the time period according to whether the current change value is greater than a preset change value;

[0081] S102: If yes, the time period is a variable flow time period;

[0082] S103, if not, the period is a constant current period;

[0083] Among them, the current value at the current moment is I t , the current value at the previous moment is I t-1 , the current change value is |I t -I t-1 |.

[0084] In this embodiment, the current value I is obtained at the current moment. t The current value I at the previous moment t-1 , then the current change value is |I t -I t-1 |, in a specific embodiment, the preset change value is 1A, |I t -I t-1 When |>1A, this period is the current conversion period, |I t -I t-1 |≤1A, then the period is a constant current period. It is understandable that the preset change value can be set according to the accuracy of different battery SOH estimation. Judging the current state of the period by the current change value makes the value of the battery DC internal resistance more accurate, preventing the calculated battery DC internal resistance from being misjudged due to errors in its authenticity, thereby improving the accuracy of battery SOH estimation.

[0085] Combination Figure 4 As shown, in some embodiments, the DC internal resistance of the battery at the current moment and the true value interval of the DC internal resistance of the battery corresponding to the current moment are calculated according to the current state and the charge and discharge state of the battery in the time period between the current moment and the previous moment, that is, step S20 includes steps S201 to S203:

[0086] S201, when the period is the constant current period, the battery DC internal resistance R CC =ΔU / I;

[0087] In the charging state, ΔU=Ut-1 -U t , R CC =(U t-1 -U t ) / I, maximum DC internal resistance

[0088] In the discharge state, ΔU=U t -U t-1 , R CC =(U t -U t-1 ) / I, maximum DC internal resistance

[0089] S202, when the time period is the current conversion period, the battery DC internal resistance R RC =ΔU / ΔI;

[0090] In the charging state, ΔU=U t-1 -U t , ΔI=I t-1 -I t , R RC =(U t-1 -U t ) / (I t-1 -I t ), maximum DC internal resistance R max =(U t-1 -U max ) / (I t -I t-1 );

[0091] In the discharge state, ΔU=U t -U t-1 , ΔI=I t -I t-1 , R RC =(U t -U t-1 ) / (I t -I t-1 ), maximum DC internal resistance R max =(U min -U t-1 ) / (I t -I t-1 );

[0092] S203, the true value interval of the battery DC internal resistance is [0, R max ];

[0093] Among them, ΔU is the voltage change, U t is the voltage value at the current moment, U t-1is the voltage value at the previous moment, I is the geometric mean current during the constant current period, that is, ΔI is the current change, U max When charging U t Maximum battery voltage upper limit, U min U is the discharge time t The lower limit of the maximum battery voltage, U max and U min Related to the material of the battery.

[0094] In this embodiment, during the constant current period, the current I hardly changes, and the geometric mean value of the current is taken. In the charging state, the voltage gradually decreases, ΔU = U t-1 -U t , R CC =(U t-1 -U t ) / I, in the discharge state, the voltage gradually increases, ΔU=U t -U t-1 , R CC =(U t -U t-1 ) / I; During the variable current period, the current changes gradually, R RC =ΔU / ΔI. The battery DC internal resistance is accurately calculated according to different formulas based on the change of current and different battery states, thus improving the accuracy of battery SOH estimation. max and U min Regarding the battery materials, the commonly used battery materials in the prior art include ternary lithium batteries, lithium manganese oxide batteries and lithium iron phosphate batteries. max and U min They are 4.3V and 2.8V respectively, and the U of lithium manganate battery max and U min 4.2V and 2.7V respectively, the U of the iron phosphate battery max and U min The upper and lower limits of the battery voltage are obtained according to different lithium batteries, so as to calculate the maximum DC internal resistance R under the corresponding state. max , more accurately obtain the true value interval of the battery DC internal resistance, and then accurately determine whether the battery DC internal resistance is a true value.

[0095] Combination Figure 5 As shown, in some embodiments, whether the DC internal resistance of the battery is a true value is determined according to the true value interval, that is, step S30 includes steps S301 to S303:

[0096] S301, judging whether the DC internal resistance of the battery is a true value according to whether the DC internal resistance of the battery is within its corresponding true value interval;

[0097] S302: If yes, the DC internal resistance of the battery is true;

[0098] S303: If not, the battery DC internal resistance is a false value.

[0099] In this embodiment, if the DC internal resistance of the battery is within its corresponding true value interval, it is a true value, otherwise it is a false value. The true value interval determination method can more accurately and quickly determine the authenticity of the DC internal resistance of the battery.

[0100] Combination Figure 6 As shown, in some embodiments, if the battery DC internal resistance is not a true value, the battery DC internal resistance is corrected, that is, step S40 includes steps S401 to S403:

[0101] S401, obtain the corresponding open circuit voltage OCV at the current moment according to the SOC-OCV curve SOC，t ;

[0102] S402, according to U t =OCV SOC，t -I t R t Get the current internal resistance value R t =(OCV SOC，t -U t ) / I t ;

[0103] S403, the battery DC internal resistance true value R t-1 As a priori value, the current internal resistance value R t As the observed value, the battery DC corrected internal resistance BR at the current moment is calculated according to the Kalman filter method. t .

[0104] In this embodiment, during the use of the battery, the state of charge (SOC) is the ratio of the actual power provided in the current state to the power provided in the fully charged state. The open circuit voltage (OCV) refers to the voltage measured by the battery without load. The open circuit voltage changes with the SOC. Therefore, the corresponding open circuit voltage OCV at the current moment can be obtained according to the SOC-OCV curve. SOC，t , according to the actual voltage U t And according to U t =OCV SOC，t -I t R t The internal resistance value R of the battery can be calculated tKalman filtering is a recursive algorithm used to estimate the state of a dynamic system. The prior value refers to the state prediction obtained based on the system's dynamic model and the current state estimation before the current state estimation is performed. The observed value refers to the actual measurement data obtained at the current moment, which reflects the actual system state. The battery DC corrected internal resistance BR at the current moment is calculated according to the Kalman filtering method. t The response is fast and the error is small, thus improving the accuracy of battery SOH estimation.

[0105] Combination Figure 2 As shown, on the other hand, the present invention also provides a battery capacity data preprocessing method, comprising steps S50 to S70:

[0106] S50, calculating the capacity difference between the battery capacity at the first moment and the battery capacity at the second moment after a preset time, and the theoretical maximum change value of the battery capacity between the first moment and the second moment;

[0107] S60, judging whether the battery capacity at the second moment is a true value according to the capacity difference and the theoretical maximum change value of the battery capacity;

[0108] S70: If the battery capacity at the second moment is not a true value, correct the battery capacity at the second moment.

[0109] In the embodiment of the present invention, when preprocessing the battery capacity data at the second moment, that is, when judging the authenticity of the battery capacity at the second moment, it is necessary to judge based on the capacity difference between the second moment and the first moment before the predetermined time. If the capacity difference does not exceed the maximum capacity change value, the battery capacity data at the second moment is a true value, otherwise it is a false value, and the battery capacity at the second moment needs to be corrected. By judging the authenticity of the battery capacity and correcting the false value at the same time, the quality of the battery capacity data is improved, which not only reduces the battery SOH prediction time and avoids affecting the robustness of the battery SOH estimation model, but also improves the prediction accuracy of the battery SOH and reduces the estimation error of the battery SOH.

[0110] Combination Figure 7 As shown, in some embodiments, the capacity difference between the battery capacity at the first moment and the battery capacity at the second moment after a preset time, and the theoretical maximum change value of the battery capacity between the first moment and the second moment are calculated, that is, step S50 includes steps S501-S502:

[0111] S501, the battery capacity value at the first moment is C t , the battery capacity value at the second moment is C t+Δt The capacity difference between the second moment and the first moment is (C t+Δt -C t );

[0112] S502: Theoretical maximum change value ΔC of battery capacity between the first moment and the second moment max =I max *Δt;

[0113] The first moment is t, the preset time is Δt, the second moment is t+Δt, I max It is the maximum current value within the preset time.

[0114] In this embodiment, the preset time Δt is set according to the working environment of the battery. When judging the authenticity of the battery capacity at the second moment, it is necessary to judge based on the capacity difference between the second moment and the first moment before the preset time Δt. In the actual application scenario, the battery capacity value C at the first moment t is true to ensure that the battery capacity value C at the second moment t+Δt The accuracy of authenticity judgment. Battery capacity is usually expressed in ampere-hours (Ah) or milliampere-hours (mAh), which reflects the amount of charge that the battery can store and release. The maximum capacity change value ΔC within a preset time Δt max =I max *Δt.

[0115] Combination Figure 8 As shown, in some embodiments, whether the battery capacity at the second moment is a true value is determined according to the capacity difference and the theoretical maximum change value of the battery capacity, that is, step S60 includes steps S601 to S603:

[0116] S601, judging whether the battery capacity is a true value according to whether the capacity difference is less than the maximum capacity change value;

[0117] S602: If yes, the battery capacity is a true value;

[0118] S603: If not, the battery capacity is a false value.

[0119] In this embodiment, the capacity difference is less than the maximum capacity change value, that is, the battery capacity value does not exceed the theoretical change, and the battery capacity value at the second moment is a true value. The capacity difference is greater than the maximum capacity change value, and the battery capacity value at the second moment is a false value. By judging the authenticity of the battery capacity value at the second moment, it is possible to avoid the false value affecting the accuracy of the battery SOH estimation, thereby improving the accuracy of the battery SOH estimation.

[0120] Combination Fig. 9 As shown, in some embodiments, if the battery capacity value at the second moment is not a true value, the battery capacity value at the second moment is corrected, that is, step S70 includes steps S701 to S704:

[0121] S701: Obtaining the battery SOC at the first moment and the second moment t and battery SOCt+Δt ;

[0122] S702: According to the battery SOC t and battery SOC t+Δt Get the battery SOC change (SOC t+Δt -SOC t );

[0123] S703, obtain the battery capacity change ΔC within a preset time according to the battery SOC change t+Δt -SOC t )*C N ;

[0124] S704, obtaining a battery capacity correction value C at the second moment according to the battery capacity change t+Δt =C t +ΔC;

[0125] Among them, C N is the rated capacity of the battery.

[0126] In this embodiment, the battery SOC change (SOC t+Δt -SOC t ) is the proportional change value of the battery's energy storage capacity, C N is the rated capacity of the battery, (SOC t+Δt -SOC t )*C N That is, the battery capacity change ΔC, ΔC is actually the battery capacity change from the first moment to the second moment, so the corrected battery capacity correction value C at the second moment t+Δt =C t +ΔC, by correcting the pseudo value, improves the quality of battery capacity data, which not only reduces the battery SOH prediction time and avoids affecting the robustness of the battery SOH estimation model, but also improves the prediction accuracy of the battery SOH and reduces the estimation error of the battery SOH.

[0127] Combination Fig.10 As shown, the present invention also provides a battery DC internal resistance data preprocessing system, comprising:

[0128] The first judgment unit 100 is used to judge the current state of the period between the current moment and the previous moment according to the current change value between the current moment and the previous moment;

[0129] The first calculation unit 200 is used to calculate the DC internal resistance of the battery at the current moment and the true value interval of the DC internal resistance of the battery corresponding to the current moment according to the current state and the charge and discharge state of the battery in the period between the current moment and the previous moment;

[0130] The second judgment unit 300 is used to judge whether the DC internal resistance of the battery is a true value according to the true value interval;

[0131] The first correction unit 400 is used to correct the battery DC internal resistance if the battery DC internal resistance is not a true value.

[0132] In the embodiment of the present invention, the quality of the battery DC internal resistance data is improved by judging the authenticity of the battery DC internal resistance and correcting the false value, which can reduce the battery SOH prediction time and improve the battery SOH prediction accuracy to a certain extent.

[0133] Combination Fig.11 As shown, the present invention also provides a battery capacity data preprocessing system, comprising:

[0134] The second calculation unit 500 is used to calculate the capacity difference between the battery capacity at the first moment and the battery capacity at the second moment after a preset time, and the theoretical maximum change value of the battery capacity between the first moment and the second moment;

[0135] The third judgment unit 600 is used to judge whether the battery capacity at the second moment is a true value according to the capacity difference and the theoretical maximum change value of the battery capacity;

[0136] The second correction unit 700 is used to correct the battery capacity at the second moment if the battery capacity at the second moment is not a true value.

[0137] In the embodiment of the present invention, the quality of the battery capacity data is improved by judging the authenticity of the battery capacity and correcting the false value, which not only reduces the battery SOH prediction time and avoids affecting the robustness of the battery SOH estimation model, but also improves the prediction accuracy of the battery SOH and reduces the estimation error of the battery SOH.

[0138] The present invention also provides a computer program product, including a computer program, which implements the steps of the above-mentioned battery DC internal resistance data preprocessing method or battery capacity data preprocessing method when executed by a processor.

[0139] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A battery DC internal resistance data preprocessing method, characterized in that: include: Determine the current state of the period between the current moment and the previous moment according to the current change value between the current moment and the previous moment; Calculate the battery DC internal resistance at the current moment and the true value interval of the battery DC internal resistance corresponding to the current moment according to the current state and the battery charge and discharge state during the period between the current moment and the previous moment; Determining whether the battery DC internal resistance is a true value according to the true value interval; If the battery DC internal resistance is not a true value, the battery DC internal resistance is corrected.

2. A battery capacity data preprocessing method, characterized in that: include: Calculating a capacity difference between a battery capacity at a first moment and a battery capacity at a second moment after a preset time, and a theoretical maximum change value of the battery capacity between the first moment and the second moment; Determining whether the battery capacity at the second moment is a true value according to the capacity difference and the theoretical maximum change value of the battery capacity; If the battery capacity at the second moment is not a true value, the battery capacity at the second moment is corrected.

3. The battery DC internal resistance data preprocessing method according to claim 1, characterized in that: The step of judging the current state in the period between the current moment and the previous moment according to the current change value between the current moment and the previous moment includes: Determining the current state of the time period according to whether the current change value is greater than a preset change value; If yes, then the period is a variable flow period; If not, the period is a constant current period; Among them, the current value at the current moment is I t , the current value at the previous moment is I t-1 , the current change value is |I t -I t-1 |.

4. The battery SOH data preprocessing method according to claim 3, characterized in that: The battery DC internal resistance at the current moment is calculated according to the current state and the battery charge and discharge state between the current moment and the previous moment, as well as the true value interval of the battery DC internal resistance corresponding to the current moment, including: When the period is a constant current period, the battery DC internal resistance R CC =ΔU / I; In the charging state, ΔU=U t-1 -U t , R CC =(U t-1 -U t ) / I, maximum DC internal resistance In the discharge state, ΔU=U t -U t-1 , R CC =(U t -U t-1 ) / I, maximum DC internal resistance When the time period is a variable current time period, the battery DC internal resistance R RC =ΔU / ΔI; In the charging state, ΔU=U t-1 -U t , ΔI=I t-1 -I t , R RC =(U t-1 -U t ) / (I t-1 -I t ), maximum DC internal resistance R max =(U t-1 -U max ) / (I t -I t-1 ); In the discharge state, ΔU=U t -U t-1 , ΔI=I t -I t-1 , R RC =(U t -U t-1 ) / (I t -I t-1 ), maximum DC internal resistance R max =(U min -U t-1 ) / (I t -I t-1 ); The true value interval of the battery DC internal resistance is [0, R max ]; Among them, ΔU is the voltage change, U t is the voltage value at the current moment, U t-1 is the voltage value at the previous moment, I is the geometric mean current during the constant current period, that is, ΔI is the current change, U max When charging U t Maximum battery voltage upper limit, U min U is the discharge time t The lower limit of the maximum battery voltage, U max and U min Related to the material of the battery.

5. The battery SOH data preprocessing method according to claim 4, characterized in that: If the battery DC internal resistance is not a true value, correcting the battery DC internal resistance includes: Get the corresponding open circuit voltage OCV at the current moment according to the SOC-OCV curve SOC，t ; According to U t =OCV SOC，t -I t R t Get the current internal resistance value R t =(OCV SOC，t -U t ) / I t ; The battery DC internal resistance true value R at the previous moment t-1 As a priori value, the current internal resistance value R t As the observed value, the battery DC corrected internal resistance BR at the current moment is calculated according to the Kalman filter method. t .

6. The battery capacity data preprocessing method according to claim 2, characterized in that: The calculating the capacity difference between the battery capacity at the first moment and the battery capacity at the second moment after a preset time, and the theoretical maximum change value of the battery capacity between the first moment and the second moment, includes: The battery capacity value at the first moment is C t , the battery capacity value at the second moment is C t+Δt The capacity difference between the second moment and the first moment is (C t+Δt -C t ); The theoretical maximum change value ΔC of the battery capacity between the first moment and the second moment max =I max *Δt; The first time is t, the preset time is Δt, the second time is t+Δt, I max is the maximum current value within the preset time.

7. The battery capacity data preprocessing method according to claim 6, characterized in that: If the battery capacity at the second moment is not a true value, correcting the battery capacity at the second moment includes: Obtain the battery SOC at the first moment and the second moment t and battery SOC t+Δt ; According to the battery SOC t With the battery SOC t+Δt Get the battery SOC change (SOC t+Δt -SOC t ); The battery capacity change ΔC within the preset time is obtained according to the battery SOC change t+Δt -SOC t )*C N ; Obtain the battery capacity correction value C at the second moment according to the battery capacity change t+Δt =C t +ΔC; Among them, C N is the rated capacity of the battery.

8. A battery DC internal resistance data preprocessing system, characterized in that: include: A first judgment unit, used to judge the current state of the period between the current moment and the previous moment according to the current change value between the current moment and the previous moment; A first calculation unit, used to calculate the DC internal resistance of the battery at the current moment and the true value interval of the DC internal resistance of the battery corresponding to the current moment according to the current state in the period between the current moment and the previous moment and the charge and discharge state of the battery; A second judgment unit, configured to judge whether the battery DC internal resistance is a true value according to the true value interval; The first correction unit is used to correct the battery DC internal resistance if the battery DC internal resistance is not a true value.

9. A battery capacity data preprocessing system, characterized in that: include: a second calculation unit, configured to calculate a capacity difference between a battery capacity at a first moment and a battery capacity at a second moment after a preset time, and a theoretical maximum change value of the battery capacity between the first moment and the second moment; a third judging unit, configured to judge whether the battery capacity at the second moment is a true value according to the capacity difference and the theoretical maximum change value of the battery capacity; The second correction unit is used to correct the battery capacity at the second moment if the battery capacity at the second moment is not a true value.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the battery DC internal resistance data preprocessing method described in claim 1 or the battery capacity data preprocessing method described in claim 2 are implemented.

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