CN108761338B - Method and device for updating OCV curve of battery on line - Google Patents

Method and device for updating OCV curve of battery on line Download PDF

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CN108761338B
CN108761338B CN201810494224.0A CN201810494224A CN108761338B CN 108761338 B CN108761338 B CN 108761338B CN 201810494224 A CN201810494224 A CN 201810494224A CN 108761338 B CN108761338 B CN 108761338B
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ocv
battery
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internal resistance
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CN108761338A (en
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时玉帅
张巍
王起亮
张建利
方兰兰
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King Long United Automotive Industry Suzhou Co Ltd
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    • 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]
    • G01R31/382—Arrangements for monitoring battery or accumulator variables, e.g. SoC
    • G01R31/3842—Arrangements for monitoring battery or accumulator variables, e.g. SoC combining voltage and current measurements
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R19/00—Arrangements for measuring currents or voltages or for indicating presence or sign thereof
    • G01R19/165—Indicating that current or voltage is either above or below a predetermined value or within or outside a predetermined range of values
    • G01R19/16528—Indicating that current or voltage is either above or below a predetermined value or within or outside a predetermined range of values using digital techniques or performing arithmetic operations
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R27/00—Arrangements for measuring resistance, reactance, impedance, or electric characteristics derived therefrom
    • G01R27/02—Measuring real or complex resistance, reactance, impedance, or other two-pole characteristics derived therefrom, e.g. time constant
    • G01R27/08—Measuring resistance by measuring both voltage and current
    • 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]
    • G01R31/367—Software therefor, e.g. for battery testing using modelling or look-up tables
    • 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]
    • G01R31/396—Acquisition or processing of data for testing or for monitoring individual cells or groups of cells within a battery
    • 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
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/60—Other road transportation technologies with climate change mitigation effect
    • Y02T10/70—Energy storage systems for electromobility, e.g. batteries

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Abstract

The invention discloses a method for updating an OCV curve of a battery on line, which comprises the following steps: designing a battery internal resistance model, setting an SOC (state of charge) change window in a certain range, and setting internal resistance and OCV (open circuit control) as fixed values when the change window is in the range; measuring a traveling crane discharge curve to obtain a current and voltage road spectrum of SOC discharge; and (3) performing least square analysis on data of different currents and corresponding voltages in the SOC change window in the working condition to obtain a group of OCV values of different marks in the SOC change window and the internal resistance value of the battery, and analyzing to obtain an OCV curve. The OCV curve of the battery can be updated on line, and the OCV curve of the aged battery cell of the new energy automobile can be obtained through the method. The detection of the battery capacity and the battery internal resistance attenuation of the new energy automobile is further enhanced, and the method has a positive effect on the detection of a new energy automobile battery system.

Description

Method and device for updating OCV curve of battery on line
Technical Field
The invention belongs to the technical field of power battery management, and particularly relates to a method and a device for updating an OCV curve of a battery on line.
Background
The electric automobile is a vehicle taking an electric motor as a power device and a battery as an energy storage device. The development of electric vehicles is a new strategic industry that is vigorously developed by various countries after energy crisis and financial crisis. Therefore, battery management is extremely important. The remaining battery capacity (SOC) of the battery pack is an important parameter of the battery management system, and is the most important reference for planning a battery usage route, and is also the basis for power management and the like in battery management.
The method for estimating the residual capacity of the power battery generally adopts an estimation method of open-circuit voltage correction plus ampere-hour integral and a Kalman filtering algorithm based on a battery model, wherein the Kalman filtering algorithm can effectively estimate the residual capacity (SOC) of a battery pack on the premise of obtaining an effective open-circuit voltage (OCV) curve. The OCV curve is generally obtained by offline calibration, but the offline calibration method is only for the battery cells which leave the factory soon, and the OCV curve obtained by the aged battery cells on the new energy automobile by offline calibration is not in accordance with the actual use condition. The estimation of the battery SOC after aging depends on the battery OCV after aging, however, a method for updating the battery OCV on line does not exist at present.
Disclosure of Invention
In view of the above technical problems, an object of the present invention is to provide a method for updating an OCV curve of a battery online, which can update the OCV curve of the battery online, and can obtain the OCV curve of an aged cell of a new energy vehicle by using the method.
The technical scheme of the invention is as follows:
a method of updating an OCV curve of a battery online, comprising the steps of:
s01: designing a battery internal resistance model, setting an SOC (state of charge) change window in a certain range, and setting internal resistance and OCV (open circuit control) as fixed values when the change window is in the range;
s02: measuring a traveling discharge curve to obtain a corresponding current and voltage road spectrum when the SOC is discharged to a certain value from a full charge state or any state;
s03: and (3) performing least square analysis on data of different currents and corresponding voltages in the SOC change window in the working condition to obtain a group of OCV values of different marks in the SOC change window and the internal resistance value of the battery, and analyzing to obtain an OCV curve.
In a preferred technical scheme, the battery internal resistance model is as follows: vi(soc)＝OCV(soc)+Ii×R(soc)Internal resistance R(soc)Open circuit voltage OCV(soc)Is a constant value, Vi(soc)Is a voltage, IiIs the current.
In a preferred technical scheme, the certain range is a 1% -2% SOC range.
In a preferred embodiment, after the step S02, a graph with time on the abscissa, current value on the left of the ordinate, and SOC on the right of the ordinate, and a graph with time on the abscissa, voltage value on the left of the ordinate, and SOC on the right of the ordinate are obtained.
In a preferred embodiment, the step of analyzing and obtaining the OCV curve in step S03 includes:
obtaining a linear correlation coefficient of current-voltage;
an OCV-SOC curve graph with the abscissa as SOC and the ordinate as OCV and an R-SOC curve graph with the abscissa as SOC and the ordinate as R are obtained.
The invention also discloses a device for updating the OCV curve of the battery on line, which comprises:
a battery internal resistance model design module: designing a battery internal resistance model, setting an SOC (state of charge) change window in a certain range, and setting internal resistance and OCV (open circuit control) as fixed values when the change window is in the range;
a discharge curve drawing module: measuring a traveling crane discharge curve to obtain a current and voltage road spectrum of SOC discharge;
an OCV curve plotting module: and (3) performing least square analysis on data of different currents and corresponding voltages in the SOC change window in the working condition to obtain a group of OCV values of different marks in the SOC change window and the internal resistance value of the battery, and analyzing to obtain an OCV curve.
In a preferred technical scheme, the battery internal resistance model is as follows: vi(soc)＝OCV(soc)+Ii×R(soc)Internal resistance R(soc)Open circuit voltage OCV(soc)Is a constant value, Vi(soc)Is a voltage, IiIs the current.
In a preferred technical scheme, the certain range is a 1% -2% SOC range.
In a preferred technical solution, the discharge curve drawing module is further configured to obtain a curve graph with an abscissa as time, a left ordinate as a current value, and a right ordinate as an SOC, and a curve graph with an abscissa as time, a left ordinate as a voltage value, and a right ordinate as an SOC.
In a preferred embodiment, the step of obtaining the OCV curve by analyzing in the OCV curve drawing module includes:
obtaining a linear correlation coefficient of current-voltage;
an OCV-SOC curve graph with the abscissa as SOC and the ordinate as OCV and an R-SOC curve graph with the abscissa as SOC and the ordinate as R are obtained.
Compared with the prior art, the invention has the beneficial effects that:
the method provided by the invention does not need to calibrate the OCV curve under the line, but updates the OCV curve of the battery by combining the actual use condition of the battery, and has the advantage of realizing online testing of the OCV curve of the aged battery cell of the new energy automobile. The real-time monitoring of a battery system of a running vehicle is guaranteed, and the battery monitoring system has a positive effect on the detection of the working condition of the battery.
Drawings
The invention is further described with reference to the following figures and examples:
FIG. 1 is a flow chart of a method of updating a battery OCV curve online in accordance with the present invention;
FIG. 2 is a schematic diagram of a current and voltage road spectrum curve for a battery test according to the present invention;
FIG. 3 is a schematic diagram of OCV-SOC and R-SOC of the battery analyzed by the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail with reference to the accompanying drawings in conjunction with the following detailed description. It should be understood that the description is intended to be exemplary only, and is not intended to limit the scope of the present invention. Moreover, in the following description, descriptions of well-known structures and techniques are omitted so as to not unnecessarily obscure the concepts of the present invention.
Example (b):
the invention discloses a device for updating an OCV curve of a battery on line, which comprises:
a battery internal resistance model design module: designing a battery internal resistance model, setting an SOC (state of charge) change window in a certain range, and setting internal resistance and OCV (open circuit control) as fixed values when the change window is in the range;
a discharge curve drawing module: measuring a traveling crane discharge curve to obtain a current and voltage road spectrum of SOC discharge;
an OCV curve plotting module: and (3) performing least square analysis on data of different currents and corresponding voltages in the SOC change window in the working condition to obtain a group of OCV values of different marks in the SOC change window and the internal resistance value of the battery, and analyzing to obtain an OCV curve.
As shown in fig. 1, the apparatus performs a method of updating an OCV curve of a battery on-line, including:
step one, designing a battery internal resistance model as Vi(soc)＝OCV(soc)+Ii×R(soc)Internal resistance R(soc)Open circuit voltage OCV(soc)Is a constant value, Vi(soc)Is a voltage, IiIs the current. Because the internal resistance and the electromotive force of the lithium ion battery are changed along with the SOC, when the SOC change value is small, the internal resistance and the OCV can be approximately constant; the small range variation window can be between 1% and 2%.
Selecting 1% as a change window of the SOC, and approximately considering the internal resistance and the OCV as fixed values in the range of the change window;
step three, in the embodiment, the lithium battery is taken as a research object, and the driving discharge curve is measured, and the whole discharge interval is not limited, and can be 100% to 0% or 90% to 15%. The present embodiment is to obtain the corresponding current and voltage road spectrum from the full charge state 100% to the discharge state 40%, as shown in fig. 2.
Step four, obtaining a curve graph with the abscissa as time (unit: S), the left ordinate as current value (unit: A) and the right ordinate as SOC (unit:%); and a graph with the abscissa as time (in the unit of S), the left ordinate as a voltage value (in the unit of V), and the right ordinate as SOC (in the unit of:%);
and step five, carrying out least square calculation analysis on current and voltage data with the SOC variation range within 1% to obtain a group of OCV values marked by SOC according to 1% and the internal resistance value of the battery:
the OCV calculation method comprises the following steps:
Figure GDA0002390103560000041
the battery internal resistance R calculation method comprises the following steps:
Figure GDA0002390103560000042
where N is the number of change windows.
Step six, correspondingly, a linear correlation coefficient of current-voltage can be obtained;
analyzing a group of different marked OCV values and battery internal resistance values obtained by calculating every 1% of SOC in the fifth step to obtain OCV-SOC and R-SOC curves, so that the average value of the battery internal resistance and the relationship between the OCV and the SOC can be obtained, and the battery electromotive force characteristics are met;
step eight, obtaining a curve graph with the abscissa of SOC (unit:%) and the ordinate of OCV (unit: V); and a graph having SOC (unit:%) on the abscissa and R (unit: m.OMEGA.) on the ordinate, as shown in FIG. 3.
It is to be understood that the above-described embodiments of the present invention are merely illustrative of or explaining the principles of the invention and are not to be construed as limiting the invention. Therefore, any modification, equivalent replacement, improvement and the like made without departing from the spirit and scope of the present invention should be included in the protection scope of the present invention. Further, it is intended that the appended claims cover all such variations and modifications as fall within the scope and boundaries of the appended claims or the equivalents of such scope and boundaries.

Claims (10)

1. A method for updating an OCV curve of a battery on line is characterized by comprising the following steps:
s01: designing a battery internal resistance model, setting an SOC (state of charge) change window in a certain range, and setting internal resistance and OCV (open circuit control) as fixed values when the change window is in the range;
s02: measuring a traveling crane discharge curve to obtain a current and voltage road spectrum of SOC discharge;
s03: taking different currents I in SOC change window in working conditioniAnd corresponding voltage ViThe method comprises the following steps of (1) carrying out least square analysis on data to obtain OCV values and battery internal resistance values of different marks in a group of SOC change windows, wherein the OCV calculation method comprises the following steps:
Figure FDA0002390103550000011
the battery internal resistance R calculation method comprises the following steps:
Figure FDA0002390103550000012
wherein N is the number of the change windows, and the OCV curve is obtained through analysis.
2. The method for updating the OCV curve of the battery online according to claim 1, wherein the internal resistance model of the battery is as follows: vi(soc)＝OCV(soc)+Ii×R(soc)Internal resistance R(soc)Open circuit voltage OCV(soc)Is a constant value, Vi(soc)Is a voltage, IiIs the current.
3. The method for updating the OCV curve of the battery online as recited in claim 1, wherein the certain range is a 1% -2% SOC range.
4. The method for updating the OCV curve of the battery online according to claim 1, wherein the step S02 is followed by obtaining a graph with time on the abscissa and current value on the left of the ordinate and SOC on the right of the ordinate, and a graph with time on the abscissa and voltage value on the left of the ordinate and SOC on the right of the ordinate.
5. The method for updating the OCV curve of the battery online according to claim 1, wherein the step of analyzing the OCV curve in the step S03 includes:
obtaining a linear correlation coefficient of current-voltage;
an OCV-SOC curve graph with the abscissa as SOC and the ordinate as OCV and an R-SOC curve graph with the abscissa as SOC and the ordinate as R are obtained.
6. An apparatus for updating an OCV curve of a battery online, comprising:
a battery internal resistance model design module: designing a battery internal resistance model, setting an SOC (state of charge) change window in a certain range, and setting internal resistance and OCV (open circuit control) as fixed values when the change window is in the range;
a discharge curve drawing module: measuring a traveling crane discharge curve to obtain a current and voltage road spectrum of SOC discharge;
an OCV curve plotting module: taking different currents I in SOC change window in working conditioniAnd corresponding voltage ViThe method comprises the following steps of (1) carrying out least square analysis on data to obtain OCV values and battery internal resistance values of different marks in a group of SOC change windows, wherein the OCV calculation method comprises the following steps:
Figure FDA0002390103550000021
the battery internal resistance R calculation method comprises the following steps:
Figure FDA0002390103550000022
wherein N is the number of the change windows, and the OCV curve is obtained through analysis.
7. The apparatus for updating the OCV curve of the battery online according to claim 6, wherein the internal resistance model of the battery is: vi(soc)＝OCV(soc)+Ii×R(soc)Internal resistance R(soc)Open circuit voltage OCV(soc)Is a constant value, Vi(soc)Is a voltage, IiIs the current.
8. The apparatus for updating the OCV curve of the battery online as recited in claim 6, wherein the certain range is a 1% -2% SOC range.
9. The apparatus for online updating of the OCV curve of the battery according to claim 6, wherein the discharge curve plotting module is further configured to obtain a graph with time on the abscissa and current value on the left of the ordinate and SOC on the right of the ordinate, and a graph with time on the abscissa and voltage value on the left of the ordinate and SOC on the right of the ordinate.
10. The apparatus for online updating of the OCV curve of the battery according to claim 6, wherein the step of analyzing the OCV curve in the OCV curve plotting module to obtain the OCV curve comprises:
obtaining a linear correlation coefficient of current-voltage;
an OCV-SOC curve graph with the abscissa as SOC and the ordinate as OCV and an R-SOC curve graph with the abscissa as SOC and the ordinate as R are obtained.
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