WO2024099011A1 - 电池直流阻抗估算方法及装置 - Google Patents

电池直流阻抗估算方法及装置 Download PDF

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Publication number
WO2024099011A1
WO2024099011A1 PCT/CN2023/123616 CN2023123616W WO2024099011A1 WO 2024099011 A1 WO2024099011 A1 WO 2024099011A1 CN 2023123616 W CN2023123616 W CN 2023123616W WO 2024099011 A1 WO2024099011 A1 WO 2024099011A1
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Prior art keywords
battery
sampling
current
impedance
time period
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PCT/CN2023/123616
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English (en)
French (fr)
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李华鹏
杜明树
林文煜
赵微
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宁德时代新能源科技股份有限公司
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Publication of WO2024099011A1 publication Critical patent/WO2024099011A1/zh

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
    • G01D21/00—Measuring or testing not otherwise provided for
    • G01D21/02—Measuring two or more variables by means not covered by a single other subclass
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/385—Arrangements for measuring battery or accumulator variables
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/389—Measuring internal impedance, internal conductance or related variables
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/392—Determining battery ageing or deterioration, e.g. state of health
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02E60/10—Energy storage using batteries

Definitions

  • the present application relates to the field of batteries, and in particular to a method and device for estimating a battery DC impedance.
  • Energy storage systems usually require batteries to store excess power, and the batteries can be lithium batteries.
  • the battery life is generally required to reach 20 to 25 years.
  • SOH state of health
  • the battery will age after long-term use, and the state of health (SOH) of the aged battery will decrease.
  • DCR direct current resistance
  • the equivalent circuit method can usually be used to estimate the DC impedance of the battery.
  • this estimation method has low accuracy in estimating the DC impedance of the battery.
  • the present application provides a battery DC impedance estimation method and device, which can solve the problem of low accuracy of battery DC impedance estimation in related technologies.
  • a method for estimating a battery DC impedance comprising:
  • the battery operation data includes sampling time, sampling voltage, sampling current and sampling temperature
  • the battery DC impedance estimation value is determined based on the first impedance estimation value and the impedance compensation value.
  • the battery DC impedance estimation method provided by the embodiment of the present disclosure has higher accuracy than the DC impedance estimation value obtained by the definition method and the equivalent circuit method, and has better portability than the method of estimating DC impedance by equivalent circuit. It is suitable for DC impedance estimation in most operating scenarios in the entire life cycle of the battery, and can solve the problem that DC impedance estimation values under different operating conditions cannot be directly compared.
  • determining the first time period and the second time period according to the sampling time and the sampling current includes:
  • the first time period and the second time period are determined according to the current step starting point.
  • determining the current step starting point according to the sampling time and the sampled current includes:
  • the previous sampling moment at which the sampling current change value between two adjacent sampling moments is greater than the preset current threshold is taken as the current step starting point, thereby achieving the determination of the current step starting point.
  • the preset current threshold is determined according to the minimum current that causes the external polarization change of the battery cell, thereby improving the accuracy of the determined current step starting point.
  • the first time period is a time period after the current step starting point
  • the second time period is a time period before the current step starting point, thereby ensuring the reliability of the first time period and the second time period determined. sex.
  • obtaining a first impedance estimation value according to a sampled voltage and a sampled current in a first time period includes:
  • the product of the sampled voltage and the sampled current in the first time period is accumulated to obtain a first estimated value, and the square of the sampled current in the first time period is accumulated to obtain a second estimated value; the first impedance estimated value is determined based on the first estimated value and the second estimated value, thereby ensuring the reliability of the determined first impedance estimated value.
  • the first impedance estimate is calculated according to the following formula:
  • DCRO is the first impedance estimation value
  • Ui is the difference between the sampling voltage at the i-th sampling moment of the first period and the sampling voltage at the starting point of the current step
  • Ii is the sampling current at the i-th sampling moment of the first period
  • i is an integer greater than or equal to 0 and less than or equal to t.
  • the first impedance estimation value determined by this formula has high accuracy.
  • obtaining the impedance compensation value according to the sampled voltage, the sampled current, and the sampled temperature during the second period includes:
  • the sampled voltage, sampled current and sampled temperature of the second period and the second period are input into the impedance estimation model to obtain an impedance compensation value.
  • the use of the impedance estimation model can improve the efficiency and accuracy of determining the impedance compensation value.
  • the method further includes:
  • a preprocessing operation is performed on the battery operation data, wherein the preprocessing operation includes one or more of a null removal operation, a duplicate removal operation, an abnormal filtering operation, and a time sorting operation.
  • the quality of the data used to estimate the battery DC impedance is ensured, thereby improving the accuracy of determining the battery DC impedance estimation value.
  • the method further includes:
  • One or more of a battery cell aging state, a battery cell real-time power, a battery cell heat generation, and a battery cell consistency is determined based on the battery DC impedance estimation value.
  • the aging trajectory of the battery cell can be accurately reflected and the aging direction of the battery cell can be accurately predicted. It can also accurately estimate the real-time power capacity of the battery cell based on the estimated value of the battery DC impedance, accurately evaluate the heat generation of the battery cell, and accurately evaluate the consistency of the battery cell.
  • a computer-readable storage medium on which a computer program is stored.
  • the computer device implements the battery DC impedance estimation method according to the above aspect.
  • a battery management system including a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the battery management system implements the battery DC impedance estimation method according to the above aspects.
  • a cloud server comprising a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the cloud server implements the battery DC impedance estimation method according to the above aspects.
  • a battery DC impedance estimation device comprising:
  • An acquisition module is used to acquire battery operation data, wherein the battery operation data includes sampling time, sampling voltage, sampling current and sampling temperature;
  • a determination module used to determine a current step starting point according to a sampling moment and a sampling current, and to determine a first time period and a second time period according to the current step starting point;
  • An estimation module is used to obtain a first impedance estimation value according to a sampled voltage and a sampled current in a first time period, and to obtain an impedance compensation value according to a sampled voltage, a sampled current and a sampled temperature in a second time period, and to determine a battery DC impedance estimation value according to the first impedance estimation value and the impedance compensation value.
  • FIG1 is a flow chart of a method for estimating a battery DC impedance provided by an embodiment of the present disclosure
  • FIG2 is a flow chart of another method for estimating a DC impedance of a battery provided by an embodiment of the present disclosure
  • FIG3 is a block diagram of a battery DC impedance estimation method provided by an embodiment of the present disclosure.
  • FIG4 is a block diagram of another battery DC impedance estimation method provided by an embodiment of the present disclosure.
  • FIG5 is a schematic diagram of the structure of a battery management system provided by an embodiment of the present disclosure.
  • FIG6 is a schematic diagram of the structure of a cloud server provided in an embodiment of the present disclosure.
  • batteries are usually required in energy storage systems to store excess electricity.
  • the batteries can be lithium batteries.
  • the battery life is generally required to reach 20 to 25 years. However, the battery will age after long-term use, and the health of the aged battery will decrease. In order to ensure that the energy storage system can operate safely and stably, it is necessary to estimate the battery DC impedance and determine the battery aging degree based on the battery DC impedance.
  • the DC impedance of the battery is estimated by using an equivalent circuit method or a definition method.
  • ⁇ U is the change in voltage
  • ⁇ I is the change in discharge current.
  • the equivalent circuit method is used to estimate the battery DC impedance, the accuracy of the battery DC impedance estimated by this estimation method is low and the transferability is poor.
  • the definition method is used to estimate the battery DC impedance, the battery must be stationary for a long enough time before the current step, the step current must be large enough, the step current must last for a certain period of time without current switching in the middle, the data must have no update delay, and the voltage and current data must have good synchronization. It can be seen that this estimation method has high requirements on data quality, strict calculation conditions, and less available operating data.
  • the battery DC impedance is related to temperature, state of charge, and step current size, the DC impedance of the battery calculated under different operating conditions is quite different and cannot be directly compared.
  • the disclosed embodiment provides a method for estimating the DC impedance of a battery, in which the battery management system can estimate the DC impedance of the battery by using an equivalent heat-generating internal resistance method based on the sampling time, sampling voltage, sampling current, and sampling temperature in the battery operation data.
  • This method has a higher accuracy than the DC impedance estimation value obtained by the definition method and the equivalent circuit method.
  • it has better portability and is suitable for estimating DC impedance in most operating scenarios in the entire life cycle of the battery, and can solve the problem that the DC impedance estimation values under different operating conditions cannot be directly compared.
  • FIG1 is a flow chart of a battery DC impedance estimation method provided by an embodiment of the present disclosure, which is applied to a battery management system or a cloud server.
  • the following is an example of the method being applied to a battery management system. As shown in FIG1 , the method includes:
  • Step 101 Obtain battery operation data.
  • the battery operation data may be pre-stored in the battery management system, and the battery management system may obtain the pre-stored battery operation data after receiving the battery DC impedance estimation instruction.
  • the battery management system may generate the battery DC impedance estimation instruction after receiving the DC impedance estimation operation for the battery, or may periodically generate the battery DC impedance estimation instruction.
  • the battery operation data may include sampling time, sampling voltage, sampling current and sampling temperature.
  • Step 102 Determine a first time period and a second time period according to a sampling time and a sampling current.
  • the battery management system can determine the first time period and the second time period according to the sampling time and the sampling current.
  • Step 103 Obtain a first impedance estimation value according to the sampled voltage and the sampled current in the first time period, and obtain an impedance compensation value according to the sampled voltage, the sampled current and the sampled temperature in the second time period.
  • the battery management system can also obtain a first impedance estimation value according to the sampled voltage and sampled current in the first period, and obtain an impedance compensation value according to the sampled voltage, sampled current and sampled temperature in the second period.
  • Step 104 Determine a battery DC impedance estimation value according to the first impedance estimation value and the impedance compensation value.
  • the battery management system may determine the battery DC impedance estimation value according to the first impedance estimation value and the impedance compensation value.
  • the battery management system may determine the sum of the first impedance estimation value and the impedance compensation value as the battery DC impedance estimation value.
  • an embodiment of the present disclosure provides a battery DC impedance estimation method, in which the battery management system can determine the first time period and the second time period according to the sampling time and the sampling current in the battery operation data, obtain a first impedance estimation value according to the sampling voltage and the sampling current of the first time period, and obtain an impedance compensation value according to the sampling voltage, the sampling current and the sampling temperature of the second time period, and then determine the battery DC impedance estimation value according to the first impedance estimation value and the impedance compensation value.
  • the battery management system can estimate the battery DC impedance using the equivalent heat generation internal resistance method based on the sampling time, sampling voltage, sampling current and sampling temperature in the battery operation data.
  • This method has higher accuracy than the DC impedance estimation value obtained by the definition method and the equivalent circuit method.
  • it Compared with the method of estimating DC impedance by equivalent circuit, it has better portability and is suitable for DC impedance estimation in most operating scenarios throughout the battery life cycle, and can solve the problem that DC impedance estimation values under different operating conditions cannot be directly compared.
  • FIG2 is a flow chart of another battery DC impedance estimation method provided by an embodiment of the present disclosure, which is applied to a battery management system or a cloud server.
  • the following is an example of the method being applied to a battery management system. As shown in FIG2 , the method may include:
  • Step 201 Obtain battery operation data.
  • the battery operation data may be pre-stored in the battery management system, and the battery management system may obtain the pre-stored battery operation data after receiving the battery DC impedance estimation instruction.
  • the battery management system may generate the battery DC impedance estimation instruction after receiving the DC impedance estimation operation for the battery, or may also periodically generate the battery DC impedance estimation instruction.
  • the battery operation data may include sampling time, sampling voltage, sampling current and sampling temperature.
  • the sampling time refers to the time of sampling the sampling voltage, sampling current and sampling temperature of the battery.
  • the sampling voltage refers to the voltage of the battery at a sampling time
  • the sampling current refers to the current of the battery at a sampling time
  • the sampling temperature refers to the temperature of the battery at a sampling time.
  • the battery operation data may include multiple sampling times, and the sampling voltage, sampling current and sampling temperature at each sampling time in the multiple sampling times.
  • Step 202 pre-process the battery operation data.
  • the battery management system may also perform preprocessing operations on the battery operation data, wherein the preprocessing operations may include one or more of a null removal operation, a duplicate removal operation, an abnormal filtering operation, and a time sorting operation.
  • the battery management system can detect whether the sampled voltage, sampled battery, and sampled temperature at the sampling moment are null. If any of the sampled voltage, sampled battery, and sampled temperature at the sampling moment is null, the sampling moment, as well as the sampled voltage, sampled battery, and sampled temperature at the sampling moment can be removed. If the sampled voltage, sampled battery, and sampled temperature at the sampling moment are not empty, the sampling moment, as well as the sampled voltage, sampled battery, and sampled temperature at the sampling moment can be retained.
  • the battery management system can detect whether multiple frames of data are collected at the sampling moment, and each frame of data includes a sampled voltage, a sampled battery, and a sampled temperature. If multiple frames of data are collected at the sampling moment, the target frame data in the multiple frames of data can be retained, and other frame data except the target frame data can be deleted. Optionally, the target frame data can be the first frame of data in the multiple frames of data. If one frame of data is collected at the sampling moment, the one frame of data can be retained.
  • the battery management system can detect whether the sampled voltage, sampled battery, and sampled temperature at the sampling moment are abnormal values. If any of the sampled voltage, sampled battery, and sampled temperature at the sampling moment is an abnormal value, the sampling moment, as well as the sampled voltage, sampled battery, and sampled temperature at the sampling moment can be removed. If the sampled voltage, sampled battery, and sampled temperature at the sampling moment are not abnormal values, the sampling moment, as well as the sampled voltage, sampled battery, and sampled temperature at the sampling moment can be retained.
  • the battery management system may pre-store the current threshold range, the temperature threshold range and the voltage threshold range, which may be determined based on empirical values or based on rated parameters of the battery.
  • the battery management system For each sampled current, if the battery management system detects that the sampled current is within the current threshold range, it can be determined that the sampled current is not an abnormal value. If the battery management system detects that the sampled current is outside the current threshold range, it can be determined that the sampled current is an abnormal value.
  • the battery management system For each sampled voltage, if the battery management system detects that the sampled voltage is within the voltage threshold range, it can be determined that the sampled voltage is not an abnormal value. If the battery management system detects that the sampled voltage is outside the voltage threshold range, it can be determined that the sampled voltage is an abnormal value.
  • the battery management system For each sampled temperature, if the battery management system detects that the sampled temperature is within the temperature threshold range, it can be determined that the sampled temperature is not an abnormal value. If the battery management system detects that the sampled temperature is outside the temperature threshold range, it can be determined that the sampled temperature is an abnormal value.
  • the battery management system can also perform a time sorting operation on multiple sampling moments to sort the sampled voltages, sampled currents, and sampled temperatures at the multiple sampling moments.
  • the time sorting operation can be an ascending operation or a descending operation. The embodiment of the present disclosure takes the ascending operation as an example for explanation.
  • the quality of the data used to estimate the battery DC impedance is ensured, thereby improving the accuracy of determining the battery DC impedance estimation value.
  • Step 203 According to the sampling time and the sampling current, the previous sampling time at which the sampling current change value between two adjacent sampling times is greater than the preset current threshold is taken as the current step starting point.
  • the battery management system can also determine the current step starting point according to the sampling time and the sampling current.
  • the battery management system can use the previous sampling moment when the sampling current change value between two adjacent sampling moments is greater than a preset current threshold as the starting point of the current step according to the sampling moment and the sampling current.
  • the preset current threshold can be determined according to the minimum current that causes the external polarization change of the battery cell.
  • the battery management system can determine the change value of the sampled current at any two adjacent sampling moments among the multiple sampling moments. If the change value of the sampled current at the two adjacent sampling moments is greater than the preset current threshold, the sampling moment before the two adjacent sampling moments can be used as the starting point of the current step. If the change value of the sampled current at the two adjacent sampling moments is not greater than the preset current threshold, there is no need to use the sampling moment before the two adjacent sampling moments as the starting point of the current step.
  • Step 204 Determine a first time period and a second time period according to the current step starting point.
  • the battery management system can determine the The first time period and the second time period are determined.
  • the first time length and the second time length may both be the shortest time length that can cause the battery cell temperature to change under the action of a certain current, thereby ensuring the accuracy of the determination of the first time length and the second time length.
  • Step 205 Accumulate the product of the sampled voltage and the sampled current in the first time period to obtain a first estimated value, and accumulate the square of the sampled current in the first time period to obtain a second estimated value.
  • the battery management system can accumulate the product of the sampled voltage and the sampled current in the first time period to obtain a first estimated value, and can accumulate the square of the sampled current in the first time period to obtain a second estimated value.
  • the battery management system may determine the difference between each sampled voltage in the first time period and the sampled voltage at the starting point of the current step, and accumulate the product of the difference in the first time period and the sampled current to obtain a first estimated value.
  • This first estimate satisfies:
  • This second estimate can satisfy: U i is the difference between the sampling voltage at the i-th sampling moment in the first time period and the sampling voltage at the starting point of the current step, I i is the sampling current at the i-th sampling moment in the first time period, t is an integer less than the total number of sampling moments in the first time period, and i is an integer greater than or equal to 0 and less than or equal to t.
  • Step 206 Determine a first impedance estimation value according to the first estimation value and the second estimation value.
  • the battery management system can The impedance estimate is determined by combining the impedance value and the second estimate.
  • the battery management system may determine the ratio of the first estimated value to the second estimated value as a first impedance estimated value.
  • the first impedance estimated value may be calculated according to the following formula:
  • the DCRO may be a first impedance estimation value.
  • Step 207 Determine a pre-configured impedance estimation model.
  • the battery management system can also determine a preconfigured impedance estimation model, wherein the impedance estimation model can be pre-stored in the battery management system, and the impedance estimation model can be trained using multiple sample data, each of which can include a sample period, a sample sampling voltage of the sample period, a sample sampling current, a sample sampling temperature, and a sample impedance compensation value.
  • Step 208 Input the sampled voltage, sampled current and sampled temperature of the second time period and the second time period into an impedance estimation model to obtain an impedance compensation value.
  • the battery management system can input the sampled voltage, sampled current and sampled temperature of the second period and the second period into the pre-configured impedance estimation model, and the value output by the impedance estimation model is the impedance compensation value, thereby obtaining the impedance compensation value.
  • the use of the impedance estimation model can improve the efficiency and accuracy of determining the impedance compensation value.
  • Step 209 Determine a battery DC impedance estimation value according to the first impedance estimation value and the impedance compensation value.
  • the battery management system can determine the battery DC impedance estimation value according to the first impedance estimation value and the impedance compensation value.
  • the battery management system can determine the sum of the first impedance estimation value and the impedance compensation value as the battery DC impedance estimation value, that is, the battery DC impedance estimation value can satisfy: DCRO+DCRO sup , where DCRO sup is the impedance compensation value.
  • Step 210 Determine the battery cell aging state and battery cell actual value according to the battery DC impedance estimation value. One or more of power, heat generation of the battery cells, and consistency of the battery cells.
  • the battery management system can also determine one or more of the battery cell aging state, the battery cell real-time power, the battery cell heat generation and the battery cell consistency according to the estimated value of the battery DC impedance.
  • the real-time power of the battery cell may refer to the real-time power state (state of power, SOP) of the battery cell.
  • the battery management system may also send the battery DC impedance estimation value to the scheduling unit, and the scheduling unit may determine one or more of the battery cell aging state, the battery cell real-time power, the battery cell heat generation, and the battery cell consistency according to the battery DC impedance estimation value.
  • the scheduling unit may also send the battery DC impedance to other devices that require the battery DC impedance.
  • an embodiment of the present disclosure provides a battery DC impedance estimation method, in which the battery management system can determine the current step starting point according to the sampling time and sampling current in the battery operation data, and determine the first time period and the second time period according to the current step starting point, obtain the first impedance estimation value according to the sampling voltage and sampling current of the first time period, and obtain the impedance compensation value according to the sampling voltage, sampling current and sampling temperature of the second time period, and then determine the battery DC impedance estimation value according to the first impedance estimation value and the impedance compensation value.
  • the method provided by the embodiment of the present disclosure has a higher accuracy than the DC impedance estimation value obtained by the definition method and the equivalent circuit method. It has better portability than the method of estimating DC impedance by equivalent circuit, and does not need to model different cells separately. In addition, it does not have high requirements on the quality of the model input data, and is not sensitive to the pre-stationary polarization state and step current conditions. Therefore, it is suitable for estimating DC impedance in most operating scenarios in the entire life cycle of the battery cell, and can solve the problem that the DC impedance estimation values under different operating conditions cannot be directly compared. question.
  • FIG3 is a block diagram of a battery DC impedance estimation device provided by an embodiment of the present disclosure.
  • the device may be applied to a battery management system or a cloud server. As shown in FIG3 , the device may include:
  • the acquisition module 301 is used to acquire battery operation data.
  • the battery operation data includes sampling time, sampling voltage, sampling current and sampling temperature.
  • the determination module 302 is used to determine the first time period and the second time period according to the sampling time and the sampling current.
  • the estimation module 303 is used to obtain a first impedance estimation value according to the sampled voltage and the sampled current in the first time period, and to obtain an impedance compensation value according to the sampled voltage, the sampled current and the sampled temperature in the second time period, and to determine a battery DC impedance estimation value according to the first impedance estimation value and the impedance compensation value.
  • the embodiments of the present disclosure provide a battery DC impedance estimation device, in which the battery management system can determine the first time period and the second time period according to the sampling time and the sampling current in the battery operation data, and obtain the first impedance estimation value according to the sampling voltage and the sampling current of the first time period, and obtain the impedance compensation value according to the sampling voltage, the sampling current and the sampling temperature of the second time period, and then determine the battery DC impedance estimation value according to the first impedance estimation value and the impedance compensation value. That is, the battery management system can estimate the battery DC impedance by using the equivalent heat generation internal resistance method according to the sampling time, the sampling voltage, the sampling current and the sampling temperature in the battery operation data.
  • This method has higher accuracy than the DC impedance estimation value obtained by the definition method and the equivalent circuit method, and has better portability than the method of estimating DC impedance by the equivalent circuit. It is suitable for DC impedance estimation in most operating scenarios in the entire life cycle of the battery, and can solve the problem that DC impedance estimation values under different operating conditions cannot be directly compared.
  • the determination module 302 is used to:
  • the starting point of the current step is determined according to the sampling time and the sampling current.
  • the first time period and the second time period are determined according to the current step starting point.
  • the determination module 302 is used to:
  • the previous sampling time at which the sampling current change value between two adjacent sampling times is greater than the preset current threshold is taken as the starting point of the current step.
  • the preset current threshold is determined according to a minimum current that causes a change in external polarization of the battery cell.
  • the first time period is a time period after the starting point of the current step
  • the second time period is a time period before the starting point of the current step
  • the estimation module 303 is used to:
  • the product of the sampled voltage and the sampled current in the first period is accumulated to obtain a first estimated value, and the square of the sampled current in the first period is accumulated to obtain a second estimated value.
  • a first impedance estimate is determined based on the first estimate and the second estimate.
  • the first impedance estimate is calculated according to the following formula:
  • DCRO is the first impedance estimation value
  • Ui is the difference between the sampling voltage at the i-th sampling moment in the first period and the sampling voltage at the starting point of the current step
  • Ii is the sampling current at the i-th sampling moment in the first period
  • i is an integer greater than or equal to 0 and less than or equal to t.
  • the estimation module 303 is used to:
  • the sampled voltage, sampled current and sampled temperature of the second period and the second period are input into the impedance estimation model to obtain an impedance compensation value.
  • the apparatus may further include a processing module 304, wherein the processing module 304 is configured to:
  • a preprocessing operation is performed on the battery operation data, wherein the preprocessing operation includes one or more of a null removal operation, a duplicate removal operation, an abnormal filtering operation, and a time sorting operation.
  • the determination module 302 is further used for:
  • one or more of the battery cell aging state, the battery cell real-time power, the battery cell heat generation and the battery cell consistency are determined according to the estimated value of the battery DC impedance.
  • the embodiments of the present disclosure provide a battery DC impedance estimation device, in which the battery management system can determine the first time period and the second time period according to the sampling time and the sampling current in the battery operation data, obtain the first impedance estimation value according to the sampling voltage and the sampling current of the first time period, and obtain the impedance compensation value according to the sampling voltage, the sampling current and the sampling temperature of the second time period, and then determine the battery DC impedance estimation value according to the first impedance estimation value and the impedance compensation value. That is, the battery management system can estimate the battery DC impedance by using the equivalent heat generation internal resistance method according to the sampling time, the sampling voltage, the sampling current and the sampling temperature in the battery operation data.
  • This method has higher accuracy than the DC impedance estimation value obtained by the definition method and the equivalent circuit method, and has better portability than the method of estimating DC impedance by the equivalent circuit. It is suitable for DC impedance estimation in most operating scenarios in the entire life cycle of the battery, and can solve the problem that DC impedance estimation values under different operating conditions cannot be directly compared.
  • An embodiment of the present disclosure provides a computer-readable storage medium, on which a computer program is stored.
  • the computer program is executed by a computer device, the computer device implements the battery DC impedance estimation method described in the above embodiment.
  • FIG. 5 is a schematic diagram of the structure of a battery management system provided in an embodiment of the present disclosure, including a memory 501 and a processor 502.
  • the memory 502 stores a computer program.
  • the battery management system 50 implements the battery DC impedance estimation method described in the above embodiment.
  • FIG6 is a schematic diagram of the structure of a cloud server provided in an embodiment of the present disclosure, including a memory 601 and a processor 602.
  • the memory 601 stores a computer program.
  • the cloud server 60 implements the battery DC impedance estimation method described in the above embodiment.
  • computer-readable media include the following: an electrical connection portion with one or more wirings (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM).
  • the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways if necessary, and then stored in a computer memory.
  • the terms “first”, “second”, etc. used in the embodiments of the present disclosure are only used for descriptive purposes and should not be understood as indicating or implying relative importance, or implicitly indicating the number of technical features indicated in the present embodiment. Therefore, the features defined by the terms “first”, “second”, etc. in the embodiments of the present disclosure may explicitly or implicitly indicate that at least one of the features is included in the embodiment.
  • the word “multiple” means at least two or two or more, such as two, three, four, etc., unless otherwise clearly and specifically defined in the embodiments.
  • connection can be a fixed connection, a detachable connection, or an integrated connection. It can be understood that it can also be a mechanical connection, an electrical connection, etc.; of course, it can also be a direct connection, or an indirect connection through an intermediate medium, or it can be the internal connection of two elements, or the interaction relationship between two elements.
  • connection can be a fixed connection, a detachable connection, or an integrated connection. It can be understood that it can also be a mechanical connection, an electrical connection, etc.; of course, it can also be a direct connection, or an indirect connection through an intermediate medium, or it can be the internal connection of two elements, or the interaction relationship between two elements.

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Abstract

本申请公开了一种电池直流阻抗估算方法及装置，电池管理系统能够根据电池运行数据中的采样时刻和采样电流确定第一时段和第二时段，根据该第一时段的采样电压和采样电流获得第一阻抗估算值，并根据该第二时段的采样电压、采样电流和采样温度获得阻抗补偿值，进而根据第一阻抗估算值和阻抗补偿值确定电池直流阻抗估算值。由于电池管理系统能够根据电池运行数据中的采样时间、采样电压、采样电流和采样温度，采用等效产热内阻方式来估算电池直流阻抗。该方法具有比等效电路法所得直流阻抗估算值更高的精度，相比等效电路估算直流阻抗的方法具有更好的可迁移性。

Description

电池直流阻抗估算方法及装置
相关申请的交叉引用
本申请基于申请号为202211407306.X、申请日为2022年11月10日的中国专利申请提出，并要求上述中国专利申请的优先权，上述中国专利申请的全部内容在此引入本申请作为参考。
技术领域
本申请涉及电池领域，具体涉及一种电池直流阻抗估算方法及装置。
背景技术
储能系统中通常需要设置电池来储存多余的电量，该电池可以为锂电池。一般要求电池的寿命需达到20年至25年。但是电池在长期使用后会发生老化，老化后的电池的健康状态(state of health，SOH)降低。为了确保储能系统能够安全稳定的运行，需要估算电池直流阻抗(directive current resistance，DCR)，并基于该电池直流阻抗估算电池的老化程度。
相关技术中，通常可以采用等效电路法估算电池直流阻抗。但是该种估算方法对电池直流阻抗估算的精度较低。
发明内容
鉴于上述问题，本申请提供一种电池直流阻抗估算方法及装置，能够解决相关技术中对电池直流阻抗估算的精度较低的问题。
第一方面，提供了一种电池直流阻抗估算方法，包括：
获取电池运行数据，其中，电池运行数据包括采样时刻、采样电压、采样电流和采样温度；
根据采样时刻和采样电流确定确定第一时段和第二时段；
根据第一时段的采样电压和采样电流获得第一阻抗估算值，并根据第二时段的采样电压、采样电流和采样温度获得阻抗补偿值；
根据第一阻抗估算值和阻抗补偿值确定电池直流阻抗估算值。
本公开实施例提供了的电池直流阻抗估算方法，具有比定义法和等效电路法所得直流阻抗估算值更高的精度，相比等效电路估算直流阻抗的方法具有更好的可迁移性。适用于电池全生命周期中大部分工况场景的直流阻抗估算，以及能够解决不同工况下直流阻抗估算值无法直接比较的问题。
在一些实施例中，根据采样时刻和采样电流确定第一时段和第二时段，包括：
根据采样时刻和采样电流确定电流阶跃起始点；
根据电流阶跃起始点确定第一时段和第二时段。
在一些实施例中，根据采样时刻和采样电流确定电流阶跃起始点，包括：
根据采样时刻和采样电流，将相邻两个采样时刻的采样电流变化值大于预设电流阈值的前一采样时刻作为电流阶跃起始点，由此实现确定电流阶跃起始点。
在一些实施例中，预设电流阈值根据引起电池电芯外部极化变化的最小电流确定。由此提高确定的电流阶跃起始点的准确性。
在一些实施例中，第一时段为电流阶跃起始点之后的时间段，第二时段为电流阶跃起始点之前的时间段，由此确保确定的第一时段和第二时段的可靠 性。
在一些实施例中，根据第一时段的采样电压和采样电流获得第一阻抗估算值，包括：
对第一时段的采样电压与采样电流的乘积进行累加，获得第一估算值，并对第一时段的采样电流的平方进行累加，获得第二估算值；根据第一估算值和第二估算值确定第一阻抗估算值，由此确保确定的第一阻抗估算值的可靠性。
在一些实施例中，第一阻抗估算值根据以下公式计算：
其中，DCRO为第一阻抗估算值，Ui为第一时段的第i个采样时刻的采样电压与电流阶跃起始点的采样电压的差值，Ii为第一时段的第i个采样时刻的采样电流，i为大于或等于0，且小于或等于t的整数。通过该公式确定的第一阻抗估算值的准确性较高。
在一些实施例中，根据第二时段的采样电压、采样电流和采样温度获得阻抗补偿值，包括：
将第二时段的采样电压、采样电流和采样温度以及第二时段输入阻抗估算模型，获得阻抗补偿值。
采用该阻抗估算模型能够提高对阻抗补偿值确定的效率以及准确性。
在一些实施例中，在获取电池运行数据之后，方法还包括：
对电池运行数据进行预处理操作，其中，预处理操作包括去空处理操作、去重处理操作、异常过滤操作和时间排序操作中的一种或多种。
通过对电池运行数据进行预处理操作，确保了用于估算电池直流阻抗所采用的的数据的质量，由此提高了对电池直流阻抗估算值确定的准确性。
在一些实施例中，在确定电池直流阻抗估算值之后，方法还包括：
根据电池直流阻抗估算值确定电池电芯老化状态、电池电芯实时功率、电池电芯产热量和电池电芯一致性中的一种或多种。
通过确定电池电芯老化状态，由此可以准确体现电芯的老化轨迹，并准确预测电芯的老化方向。且能够根据电池直流阻抗估算值实现准确估算电芯的实时功率能力，准确评估电池电芯产热量以及准确评估电池电芯一致性。
第二方面，提供了一种计算机可读存储介质，计算机可读存储介质上存储有计算机程序，计算机程序被计算机设备执行时，使得计算机设备实现根据上述方面所述的电池直流阻抗估算方法。
第三方面，提供了一种电池管理系统，包括存储器和处理器，存储器存储有计算机程序，计算机程序被处理器执行时，使得电池管理系统实现根据上述方面所述的电池直流阻抗估算方法。
第四方面，提供了一种云服务器，包括存储器和处理器，存储器存储有计算机程序，计算机程序被处理器执行时，使得云服务器实现根据上述方面所述的电池直流阻抗估算方法。
第五方面，提供了一种电池直流阻抗估算装置，包括：
获取模块，用于获取电池运行数据，其中，电池运行数据包括采样时刻、采样电压、采样电流和采样温度；
确定模块，用于根据采样时刻和采样电流确定电流阶跃起始点，并根据电流阶跃起始点确定第一时段和第二时段；
估算模块，用于根据第一时段的采样电压和采样电流获得第一阻抗估算值，并根据第二时段的采样电压、采样电流和采样温度获得阻抗补偿值，以及根据第一阻抗估算值和阻抗补偿值确定电池直流阻抗估算值。
本公开附加的方面和优点将在下面的描述中部分给出，部分将从下面的描述中变得明显，或通过本公开的实践了解到。
附图说明
图1是本公开实施例提供的一种电池直流阻抗估算方法的流程图；
图2是本公开实施例提供的另一种电池直流阻抗估算方法的流程图；
图3是本公开实施例提供的一种电池直流阻抗估算方法的框图；
图4是本公开实施例提供的另一种电池直流阻抗估算方法的框图；
图5是本公开实施例提供的一种电池管理系统的结构示意图；
图6是本公开实施例提供的一种云服务器的结构示意图。
具体实施方式
下面详细描述本公开的实施例，所述实施例的示例在附图中示出，其中自始至终相同或类似的标号表示相同或类似的元件或具有相同或类似功能的元件。下面通过参考附图描述的实施例是示例性的，旨在用于解释本公开，而不能理解为对本公开的限制。
目前，储能系统中通常需要设置电池来储存多余的电量，该电池可以为锂电池。一般要求电池的寿命需达到20年至25年。但是电池在长期使用后会发生老化，老化后的电池的健康状态会降低。为了确保储能系统能够安全稳定的运行，需要估算电池直流阻抗，并基于该电池直流阻抗确定电池的老化程度。
相关技术中，通过采用等效电路法估算电池直流阻抗，或者采用定义法估算电池直流阻抗，采用该定义法估算的电池直流阻抗该ΔU为电压的变化量，ΔI为放电电流的变化量。
但是，若采用等效电路法估算电池直流阻抗，则该种估算方式所估算的电池直流阻抗的精度较低，且可迁移性较差。若采用定义法估算电池直流阻抗，则要求电流阶跃前电池要有足够长时间的静置，要求阶跃电流足够大，要求阶跃电流持续一定的时长且中间不能有电流切换，要求数据没有更新延迟，以及要求电压电流数据同步性较好。可见，该种估算方式对数据的质量要求较高，计算条件较为严苛，且可用的工况数据较少。此外，由于电池直流阻抗与温度、荷电状态以及阶跃电流大小均有关，因此导致不同工况下计算所得电池直流阻抗之间差距较大，无法直接比较。
本公开实施例提供了一种电池直流阻抗估算方法，该方法中电池管理系统能够根据电池运行数据中的采样时间、采样电压、采样电流和采样温度，采用等效产热内阻方式来估算电池直流阻抗，该方法具有比定义法和等效电路法所得直流阻抗估算值更高的精度。相比等效电路估算直流阻抗的方法具有更好的可迁移性，适用于电池全生命周期中大部分工况场景的直流阻抗估算，以及能够解决不同工况下直流阻抗估算值无法直接比较的问题。
图1是本公开实施例提供的一种电池直流阻抗估算方法的流程图，应用于电池管理系统或者云服务器中，以下以该方法应用于电池管理系统为例进行说明。如图1所示，该方法包括：
步骤101、获取电池运行数据。
电池管理系统中可以预先存储该电池运行数据，电池管理系统可以在接收到电池直流阻抗估算指令后，获取预先存储的电池运行数据。其中，电池管理系统可以在接收针对电池的直流阻抗估算操作后，生成电池直流阻抗估算指令，或者，也可以周期性生成该电池直流阻抗估算指令。该电池运行数据可以包括采样时刻、采样电压、采样电流和采样温度。
步骤102、根据采样时刻和采样电流确定第一时段和第二时段。
电池管理系统在获取电池运行数据之后，可以根据采样时刻和采样电流确定确定第一时段和第二时段。
步骤103、根据第一时段的采样电压和采样电流获得第一阻抗估算值，并根据第二时段的采样电压、采样电流和采样温度获得阻抗补偿值。
电池管理系统在获取电池运行数据之后，还可以根据第一时段的采样电压和采样电流获得第一阻抗估算值，并根据第二时段的采样电压、采样电流和采样温度获得阻抗补偿值。
步骤104、根据第一阻抗估算值和阻抗补偿值确定电池直流阻抗估算值。
电池管理系统在确定第一阻抗估算值和阻抗补偿值之后，可以根据第一阻抗估算值和阻抗补偿值确定电池直流阻抗估算值。可选的，该电池管理系统可以将第一阻抗估算值和阻抗补偿值之和确定为电池直流阻抗估算值。
综上所述，本公开实施例提供了一种电池直流阻抗估算方法，该方法中电池管理系统能够根据电池运行数据中的采样时刻和采样电流确定第一时段和第二时段，根据第一时段的采样电压和采样电流获得第一阻抗估算值，并根据第二时段的采样电压、采样电流和采样温度获得阻抗补偿值，进而根据第一阻抗估算值和阻抗补偿值确定电池直流阻抗估算值。
也即是，电池管理系统能够根据电池运行数据中的采样时间、采样电压、采样电流和采样温度，采用等效产热内阻方式来估算电池直流阻抗，该方法具有比定义法和等效电路法所得直流阻抗估算值更高的精度。相比等效电路估算直流阻抗的方法具有更好的可迁移性，适用于电池全生命周期中大部分工况场景的直流阻抗估算，以及能够解决不同工况下直流阻抗估算值无法直接比较的问题。
图2是本公开实施例提供的另一种电池直流阻抗估算方法的流程图，应用于电池管理系统或者云服务器中，以下以该方法应用于电池管理系统为例进行说明。如图2所示，该方法可以包括：
步骤201、获取电池运行数据。
在本公开实施例中，电池管理系统中可以预先存储该电池运行数据，电池管理系统可以在接收到电池直流阻抗估算指令后，获取该预先存储的电池运行数据。可选的，电池管理系统可以在接收针对电池的直流阻抗估算操作后，生成该电池直流阻抗估算指令，或者，也可以周期性生成该电池直流阻抗估算指令。
其中，该电池运行数据可以包括采样时刻、采样电压、采样电流和采样温度。该采样时刻指的是采样电池的采样电压、采样电流和采样温度的时刻。该采样电压指的是该电池的在一个采样时刻的电压，该采样电流指的是该电池在一个采样时刻的电流，该采样温度指的是该电池在一个采样时刻的温度。该电池运行数据可以包括多个采样时刻，以及在该多个采样时刻中的每个采样时刻的采样电压、采样电流和采样温度。
步骤202、对电池运行数据进行预处理操作。
电池管理系统在获取该电池运行数据之后，还可以对电池运行数据进行预处理操作。其中，该预处理操作可以包括去空处理操作、去重处理操作、异常过滤操作和时间排序操作中的一种或多种。
若该预处理操作包括去空处理操作，则对于每个采样时刻，电池管理系统可以分别检测在该采样时刻的采样电压、采样电池和采样温度是否为空。若在该采样时刻的采样电压、采样电池和采样温度中的任一数据为空，则可以去除该采样时刻，以及在该采样时刻的采样电压、采样电池和采样温度。若在该采 样时刻的采样电压、采样电池和采样温度均不为空，则可以保留该采样时刻，以及在该采样时刻的采样电压、采样电池和采样温度。
若该预处理操作包括去重处理操作，则对于每个采样时刻，电池管理系统可以检测在该采样时刻是否采集到多帧数据，每帧数据包括一个采样电压、一个采样电池和一个采样温度。若在该采样时刻采集到多帧数据，则可以保留该多帧数据中的目标帧数据，并删除除该目标帧数据之外的其他帧数据。可选的，该目标帧数据可以是该多帧数数据中的第一帧数据。若在该采样时刻采集到一帧数据，则可以保留该一帧数据。
若该预处理操作包括异常过滤操作，则对于每个采样时刻，电池管理系统可以检测在该采样时刻的采样电压、采样电池和采样温度是否为异常值。若在该采样时刻的采样电压、采样电池和采样温度中的任一数据为异常值，则可以去除该采样时刻，以及在该采样时刻的采样电压、采样电池和采样温度。若在该采样时刻的采样电压、采样电池和采样温度均不为异常值，则可以保留该采样时刻，以及在该采样时刻的采样电压、采样电池和采样温度。
其中，该电池管理系统中可以预先存储该电流阈值范围、温度阈值范围和电压阈值范围。该电流阈值范围、电压阈值范围和温度阈值范围可以是根据经验值确定，或者也可以是根据电池的额定参数确定。
对于每个采样电流，电池管理系统若检测到该采样电流位于该电流阈值范围内，则可以确定该采样电流不为异常值。若检测到该采样电流位于该电流阈值范围之外，则可以确定该采样电流为异常值。
对于每个采样电压，电池管理系统若检测到该采样电压位于该电压阈值范围内，则可以确定该采样电压不为异常值。若检测到该采样电压位于该电压阈值范围之外，则可以确定该采样电压为异常值。
对于每个采样温度，电池管理系统若检测到该采样温度位于该温度阈值范围内，则可以确定该采样温度不为异常值。若检测到该采样温度位于该温度阈值范围之外，则可以确定该采样温度为异常值。
若该预处理操作包括时间排序操作，则电池管理系统还可以对多个采样时刻进行时间排序操作，以实现对多个采样时刻的采样电压、采样电流和采样温度进行排序。可选的，该时间排序操作可以是升序操作，也可以是降序操作，本公开实施例以该时间排序操作为升序操作为例进行说明。
通过对电池运行数据进行预处理操作，确保了用于估算电池直流阻抗所采用的数据的质量，由此提高了对电池直流阻抗估算值确定的准确性。
步骤203、根据采样时刻和采样电流，将相邻两个采样时刻的采样电流变化值大于预设电流阈值的前一采样时刻作为电流阶跃起始点。
电池管理系统在对电池运行数据进行预处理操作之后，还可以根据采样时刻和采样电流确定电流阶跃起始点。
可选的，电池管理系统可以根据采样时刻和采样电流，将相邻两个采样时刻的采样电流变化值大于预设电流阈值的前一采样时刻作为电流阶跃起始点。其中，该预设电流阈值可以根据引起电池电芯外部极化变化的最小电流确定。
可选的，对于多个采样时刻，电池管理系统可以确定该多个采样时刻中任意相邻两个采样时刻的采样电流的变化值。若该相邻两个采样时刻的采样电流变化值大于预设电流阈值，则可以将该相邻两个采样时刻的前一采样时刻作为电流阶跃起始点。若该相邻两个采样时刻的采样电流变化值不大于预设电流阈值，则无需将该相邻两个采样时刻的前一采样时刻作为电流阶跃起始点。
步骤204、根据电流阶跃起始点确定第一时段和第二时段。
电池管理系统在确定电流阶跃起始点之后，可以根据该电流阶跃起始点确 定第一时段和第二时段。其中，该第一时段可以为电流阶跃起始点之后的时间段，该第一时段可以为以电流阶跃起始点为起始点向后截取第一时长的时段，该第一时段t1可以满足：t1＝t0+Δt1，该t0为电流阶跃起始点，该Δt1可以为第一时长。该第二时段可以为电流阶跃起始点之前的时间段，该第二时段可以为以电流阶跃起始点为起始点向前截取第二时长的时段，该第二时段t2可以满足：t2＝t0-Δt2，该Δt2可以为第二时长。
在本公开实施例中，该第一时长和第二时长均可以是在某一电流的作用下，能够引起电池电芯温度变化的最短时长，由此确保对第一时长和第二时长确定的准确性。
步骤205、对第一时段的采样电压与采样电流的乘积进行累加，获得第一估算值，并对第一时段的采样电流的平方进行累加，获得第二估算值。
电池管理系统在确定第一时段和第二时段之后，可以对第一时段的采样电压与采样电流的乘积进行累加，获取第一估算值，并可以对第一时段的采样电流的平方进行累加，获得第二估算值。
可选的，电池管理系统可以确定第一时段中每个采样电压与电流阶跃起始点的采样电压的差值，并将第一时段的差值与采样电流的乘积进行累加，获得第一估算值。
该第一估算值可以满足：该第二估算值可以满足：该Ui为第一时段的第i个采样时刻的采样电压与电流阶跃起始点的采样电压的差值，该Ii为第一时段的第i个采样时刻的采样电流，该t为小于第一时段内的采样时刻的总个数的整数，该i为大于或等于0，且小于或等于t的整数。
步骤206、根据第一估算值和第二估算值确定第一阻抗估算值。
电池管理系统在获取第一估算值和第二估算值之后，可以根据该第一估算 值和第二估算值确定第一阻抗估算值。
可选的，电池管理系统可以将第一估算值和第二估算值的比值确定为第一阻抗估算值。其中，该第一阻抗估算值可以根据以下公式计算：
该DCRO可以为第一阻抗估算值。
步骤207、确定预先配置的阻抗估算模型。
电池管理系统在确定第一阻抗估算值之后，还可以确定预先配置的阻抗估算模型，其中，该阻抗估算模型可以预先存储在电池管理系统中，且该阻抗估算模型可以是采用多个样本数据训练得到的，该每个样本数据可以包括样本时段、该样本时段的样本采样电压、样本采样电流、样本采样温度以及样本阻抗补偿值。
步骤208、将第二时段的采样电压、采样电流和采样温度以及第二时段输入阻抗估算模型，获得阻抗补偿值。
电池管理系统在确定预先配置的阻抗估算模型之后，可以将第二时段的采样电压、采样电流和采样温度以及第二时段输入该预先配置的阻抗估算模型，该阻抗估算模型输出的值即为该阻抗补偿值，由此获得阻抗补偿值。采用该阻抗估算模型能够提高对阻抗补偿值确定的效率以及准确性。
步骤209、根据第一阻抗估算值和阻抗补偿值确定电池直流阻抗估算值。
电池管理系统在获取第一阻抗估算值和阻抗补偿值之后，可以根据该第一阻抗估算值和阻抗补偿值确定电池直流阻抗估算值。可选的，该电池管理系统可以将该第一阻抗估算值和阻抗补偿值之和确定为电池直流阻抗估算值，即该电池直流阻抗估算值可以满足：DCRO+DCROsup，该DCROsup为阻抗补偿值。
步骤210、根据电池直流阻抗估算值确定电池电芯老化状态、电池电芯实 时功率、电池电芯产热量和电池电芯一致性中的一种或多种。
电池管理系统在确定电池直流阻抗估算值之后，还可以根据电池直流阻抗估算值确定电池电芯老化状态、电池电芯实时功率、电池电芯产热量和电池电芯一致性中的一种或多种。其中，该电池电芯实时功率可以是指电池电芯的实时功率状态(state of power，SOP)。通过确定电池电芯老化状态，由此可以准确体现电芯的老化轨迹，并准确预测电芯的老化方向。且能够根据电池直流阻抗估算值实现准确估算电芯的实时功率能力，准确评估电池电芯产热量以及准确评估电池电芯一致性。
电池管理系统还可以将该电池直流阻抗估算值发送至调度单元，该调度单元可以根据该电池直流阻抗估算值确定电池电芯老化状态、电池电芯实时功率、电池电芯产热量和电池电芯一致性中的一种或多种。该调度单元还可以将该电池直流阻抗发送至其他需要电池直流阻抗的设备。
综上所述，本公开实施例提供了一种电池直流阻抗估算方法，该方法中电池管理系统能够根据电池运行数据中的采样时刻和采样电流确定电流阶跃起始点，并根据该电流阶跃起始点确定第一时段和第二时段，根据该第一时段的采样电压和采样电流获得第一阻抗估算值，并根据第二时段的采样电压、采样电流和采样温度获得阻抗补偿值，进而根据第一阻抗估算值和阻抗补偿值确定电池直流阻抗估算值。
本公开实施例提供的方法具有比定义法、等效电路法所得直流阻抗估算值更高的精度，相比等效电路估算直流阻抗的方法具有更好的可迁移性，不需要针对不同电芯分别建模。并且对模型输入数据的质量要求不高，对静置前极化状态、阶跃电流情况不敏感，因此适用于电芯全生命周期中大部分工况场景的直流阻抗估算，以及能够解决不同工况下直流阻抗估算值无法直接比较的问 题。
图3是本公开实施例提供的一种电池直流阻抗估算装置的框图，该装置可以应用于电池管理系统或者云服务器中，如图3所示，该装置可以包括：
获取模块301，用于获取电池运行数据。
其中，电池运行数据包括采样时刻、采样电压、采样电流和采样温度。
确定模块302，用于根据采样时刻和采样电流确定第一时段和第二时段。
估算模块303，用于根据第一时段的采样电压和采样电流获得第一阻抗估算值，并根据第二时段的采样电压、采样电流和采样温度获得阻抗补偿值，以及根据第一阻抗估算值和阻抗补偿值确定电池直流阻抗估算值。
综上所述，本公开实施例提供了一种电池直流阻抗估算装置，该装置中电池管理系统能够根据电池运行数据中的采样时刻和采样电流确定第一时段和第二时段，并根据该第一时段的采样电压和采样电流获得第一阻抗估算值，根据第二时段的采样电压、采样电流和采样温度获得阻抗补偿值，进而根据第一阻抗估算值和阻抗补偿值确定电池直流阻抗估算值。也即是，电池管理系统能够根据电池运行数据中的采样时间、采样电压、采样电流和采样温度，采用等效产热内阻方式来估算电池直流阻抗。该方法具有比定义法和等效电路法所得直流阻抗估算值更高的精度，相比等效电路估算直流阻抗的方法具有更好的可迁移性，适用于电池全生命周期中大部分工况场景的直流阻抗估算，以及能够解决不同工况下直流阻抗估算值无法直接比较的问题。
可选的，确定模块302，用于：
根据采样时刻和采样电流确定电流阶跃起始点。
根据电流阶跃起始点确定第一时段和第二时段。
可选的，确定模块302，用于：
根据采样时刻和采样电流，将相邻两个采样时刻的采样电流变化值大于预设电流阈值的前一采样时刻作为电流阶跃起始点。
可选的，预设电流阈值根据引起电池电芯外部极化变化的最小电流确定。
可选的，第一时段为电流阶跃起始点之后的时间段，第二时段为电流阶跃起始点之前的时间段。
可选的，估算模块303，用于：
对第一时段的采样电压与采样电流的乘积进行累加，获得第一估算值，并对第一时段的采样电流的平方进行累加，获得第二估算值。
根据第一估算值和第二估算值确定第一阻抗估算值。
可选的，第一阻抗估算值根据以下公式计算：
其中，DCRO为第一阻抗估算值，Ui为第一时段的第i个采样时刻的采样电压与电流阶跃起始点的采样电压的差值，Ii为第一时段的第i个采样时刻的采样电流，i为大于或等于0，且小于或等于t的整数。
可选的，估算模块303，用于：
将第二时段的采样电压、采样电流和采样温度以及第二时段输入阻抗估算模型，获得阻抗补偿值。
参考图3，该装置还可以包括处理模块304，该处理模块304，用于：
在获取电池运行数据之后，对电池运行数据进行预处理操作，其中，预处理操作包括去空处理操作、去重处理操作、异常过滤操作和时间排序操作中的一种或多种。
该确定模块302，还用于：
在确定电池直流阻抗估算值之后，根据电池直流阻抗估算值确定电池电芯老化状态、电池电芯实时功率、电池电芯产热量和电池电芯一致性中的一种或多种。
综上所述，本公开实施例提供了一种电池直流阻抗估算装置，该装置中电池管理系统能够根据电池运行数据中的采样时刻和采样电流确定第一时段和第二时段，根据该第一时段的采样电压和采样电流获得第一阻抗估算值，并根据第二时段的采样电压、采样电流和采样温度获得阻抗补偿值，进而根据第一阻抗估算值和阻抗补偿值确定电池直流阻抗估算值。也即是，电池管理系统能够根据电池运行数据中的采样时间、采样电压、采样电流和采样温度，采用等效产热内阻方式来估算电池直流阻抗。该方法具有比定义法和等效电路法所得直流阻抗估算值更高的精度，相比等效电路估算直流阻抗的方法具有更好的可迁移性，适用于电池全生命周期中大部分工况场景的直流阻抗估算，以及能够解决不同工况下直流阻抗估算值无法直接比较的问题。
本公开实施例提供了一种计算机可读存储介质，该计算机可读存储介质上存储有计算机程序，该计算机程序被计算机设备执行时，使得计算机设备实现上述实施例所述的电池直流阻抗估算方法。
图5是本公开实施例提供的一种电池管理系统的结构示意图，包括存储器501和处理器502，存储器502存储有计算机程序，计算机程序被处理器502执行时，使得电池管理系统50实现上述实施例所述的电池直流阻抗估算方法。
图6是本公开实施例提供的一种云服务器的结构示意图，包括存储器601和处理器602，存储器601存储有计算机程序，计算机程序被处理器602执行时，使得云服务器60实现根据上述实施例所述的电池直流阻抗估算方法。
需要说明的是，在流程图中表示或在此以其他方式描述的逻辑和/或步骤，例如，可以被认为是用于实现逻辑功能的可执行指令的定序列表，可以具体实现在任何计算机可读介质中，以供指令执行系统、装置或设备(如基于计算机的系统、包括处理器的系统或其他可以从指令执行系统、装置或设备取指令并执行指令的系统)使用，或结合这些指令执行系统、装置或设备而使用。就本说明书而言，“计算机可读介质”可以是任何可以包含、存储、通信、传播或传输程序以供指令执行系统、装置或设备或结合这些指令执行系统、装置或设备而使用的装置。计算机可读介质的更具体的示例(非穷尽性列表)包括以下：具有一个或多个布线的电连接部(电子装置)，便携式计算机盘盒(磁装置)，随机存取存储器(RAM)，只读存储器(ROM)，可擦除可编辑只读存储器(EPROM或闪速存储器)，光纤装置，以及便携式光盘只读存储器(CDROM)。另外，计算机可读介质甚至可以是可在其上打印所述程序的纸或其他合适的介质，因为可以例如通过对纸或其他介质进行光学扫描，接着进行编辑、解译或必要时以其他合适方式进行处理来以电子方式获得所述程序，然后将其存储在计算机存储器中。
应当理解，本公开的各部分可以用硬件、软件、固件或它们的组合来实现。在上述实施方式中，多个步骤或方法可以用存储在存储器中且由合适的指令执行系统执行的软件或固件来实现。例如，如果用硬件来实现，和在另一实施方式中一样，可用本领域公知的下列技术中的任一项或他们的组合来实现：具有用于对数据信号实现逻辑功能的逻辑门电路的离散逻辑电路，具有合适的组合逻辑门电路的专用集成电路，可编程门阵列(PGA)，现场可编程门阵列(FPGA)等。
在本说明书的描述中，参考术语“可选的”、“一些实施例”、“示例”、 “具体示例”、或“一些示例”等的描述意指结合该实施例或示例描述的具体特征、结构、材料或者特点包含于本公开的至少一个实施例或示例中。在本说明书中，对上述术语的示意性表述不一定指的是相同的实施例或示例。而且，描述的具体特征、结构、材料或者特点可以在任何的一个或多个实施例或示例中以合适的方式结合。
此外，本公开实施例中所使用的“第一”、“第二”等术语，仅用于描述目的，而不可以理解为指示或者暗示相对重要性，或者隐含指明本实施例中所指示的技术特征数量。由此，本公开实施例中限定有“第一”、“第二”等术语的特征，可以明确或者隐含地表示该实施例中包括至少一个该特征。在本公开的描述中，词语“多个”的含义是至少两个或者两个及以上，例如两个、三个、四个等，除非实施例中另有明确具体的限定。
在本公开中，除非实施例中另有明确的相关规定或者限定，否则实施例中出现的术语“安装”、“相连”、“连接”和“固定”等应做广义理解，例如，连接可以是固定连接，也可以是可拆卸连接，或成一体，可以理解的，也可以是机械连接、电连接等；当然，还可以是直接相连，或者通过中间媒介进行间接连接，或者可以是两个元件内部的连通，或者两个元件的相互作用关系。对于本领域的普通技术人员而言，能够根据具体的实施情况理解上述术语在本公开中的具体含义。
尽管上面已经示出和描述了本公开的实施例，可以理解的是，上述实施例是示例性的，不能理解为对本公开的限制，本领域的普通技术人员在本公开的范围内可以对上述实施例进行变化、修改、替换和变型。

Claims (14)

  1. 一种电池直流阻抗估算方法，包括：
    获取电池运行数据，其中，所述电池运行数据包括采样时刻、采样电压、采样电流和采样温度；
    根据所述采样时刻和所述采样电流确定第一时段和第二时段；
    根据所述第一时段的采样电压和采样电流获得第一阻抗估算值，并根据所述第二时段的采样电压、采样电流和采样温度获得阻抗补偿值；
    根据所述第一阻抗估算值和所述阻抗补偿值确定电池直流阻抗估算值。
  2. 根据权利要求1所述的电池直流阻抗估算方法，根据所述采样时刻和所述采样电流确定第一时段和第二时段，包括：
    根据所述采样时刻和所述采样电流确定电流阶跃起始点；
    根据所述电流阶跃起始点确定所述第一时段和所述第二时段。
  3. 根据权利要求2所述的电池直流阻抗估算方法，根据所述采样时刻和所述采样电流确定电流阶跃起始点，包括：
    根据所述采样时刻和所述采样电流，将相邻两个采样时刻的采样电流变化值大于预设电流阈值的前一采样时刻作为所述电流阶跃起始点。
  4. 根据权利要求3所述的电池直流阻抗估算方法，所述预设电流阈值根据引起电池电芯外部极化变化的最小电流确定。
  5. 根据权利要求2至4任一所述的电池直流阻抗估算方法，所述第一时段为所述电流阶跃起始点之后的时间段，所述第二时段为所述电流阶跃起始点之前的时间段。
  6. 根据权利要求2至4任一所述的电池直流阻抗估算方法，根据所述第一 时段的采样电压和采样电流获得第一阻抗估算值，包括：
    对所述第一时段的采样电压与采样电流的乘积进行累加，获得第一估算值，并对所述第一时段的采样电流的平方进行累加，获得第二估算值；
    根据所述第一估算值和所述第二估算值确定所述第一阻抗估算值。
  7. 根据权利要求6所述的电池直流阻抗估算方法，所述第一阻抗估算值根据以下公式计算：
    其中，DCRO为所述第一阻抗估算值，Ui为所述第一时段的第i个采样时刻的采样电压与所述电流阶跃起始点的采样电压的差值，Ii为所述第一时段的第i个采样时刻的采样电流，i为大于或等于0，且小于或等于t的整数。
  8. 根据权利要求1-7中任一项所述的电池直流阻抗估算方法，根据所述第二时段的采样电压、采样电流和采样温度获得阻抗补偿值，包括：
    将所述第二时段的采样电压、采样电流和采样温度以及所述第二时段输入阻抗估算模型，获得所述阻抗补偿值。
  9. 根据权利要求1-8中任一项所述的电池直流阻抗估算方法，在获取电池运行数据之后，所述方法还包括：
    对所述电池运行数据进行预处理操作，其中，所述预处理操作包括去空处理操作、去重处理操作、异常过滤操作和时间排序操作中的一种或多种。
  10. 根据权利要求1-9中任一项所述的电池直流阻抗估算方法，在确定电池直流阻抗估算值之后，所述方法还包括：
    根据所述电池直流阻抗估算值确定电池电芯老化状态、电池电芯实时功率、电池电芯产热量和电池电芯一致性中的一种或多种。
  11. 一种计算机可读存储介质，所述计算机可读存储介质上存储有计算机程序，所述计算机程序被计算机设备执行时，使得所述计算机设备实现根据权利要求1-10中任一项所述的电池直流阻抗估算方法。
  12. 一种电池管理系统，包括存储器和处理器，所述存储器存储有计算机程序，所述计算机程序被所述处理器执行时，使得所述电池管理系统实现根据权利要求1-10中任一项所述的电池直流阻抗估算方法。
  13. 一种云服务器，包括存储器和处理器，所述存储器存储有计算机程序，所述计算机程序被所述处理器执行时，使得所述云服务器实现根据权利要求1-10中任一项所述的电池直流阻抗估算方法。
  14. 一种电池直流阻抗估算装置，包括：
    获取模块，用于获取电池运行数据，其中，所述电池运行数据包括采样时刻、采样电压、采样电流和采样温度；
    确定模块，用于根据所述采样时刻和所述采样电流确定第一时段和第二时段；
    估算模块，用于根据所述第一时段的采样电压和采样电流获得第一阻抗估算值，并根据所述第二时段的采样电压、采样电流和采样温度获得阻抗补偿值，以及根据所述第一阻抗估算值和所述阻抗补偿值确定电池直流阻抗估算值。
PCT/CN2023/123616 2022-11-10 2023-10-09 电池直流阻抗估算方法及装置 WO2024099011A1 (zh)

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