CN112666473A - Battery detection method and battery detection system - Google Patents
Battery detection method and battery detection system Download PDFInfo
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Abstract
The embodiment of the application discloses a battery detection method and a battery detection system. The battery detection method comprises the following steps: acquiring real-time parameters of a battery, and presetting parameter variables; obtaining a voltage estimation error and first battery state information according to the battery real-time parameter and the preset parameter variable; obtaining second battery state information according to the first battery state information; acquiring third battery state information, and calculating and processing the first battery state information, the second battery state information and the third battery state information according to a preset weight to obtain fourth battery state information; and obtaining the real-time battery capacity according to the fourth battery state information. The battery detection method provided by the embodiment of the application can represent actual battery state information according to the preset weight and a plurality of different battery real-time parameters, so that battery measurement errors caused by representing the battery state information by a single battery parameter are avoided.
Description
Technical Field
The embodiment of the application relates to the field of energy storage device detection, in particular to a battery detection method and a battery detection system.
Background
In the related art, the battery management system detects the battery status in real time to obtain an actual operating status parameter (e.g., remaining battery capacity) of the battery.
However, in the actual use process, the battery parameters may change, and there is a large error between the working state parameters obtained according to the fixed detection equation and the battery parameters and the actual working state parameters.
Disclosure of Invention
The embodiment of the application aims at solving at least one technical problem existing in the prior art. Therefore, the embodiment of the application provides a battery testing method, which can represent actual battery state information according to preset weight and a plurality of different battery real-time parameters, so as to avoid battery measurement errors caused by representing the battery state information by a single battery parameter.
The embodiment of the application also provides a battery detection system for realizing the battery test method.
According to the battery test method of the embodiment of the first aspect of the application, the method comprises the following steps:
acquiring real-time parameters of a battery, and presetting parameter variables;
obtaining a voltage estimation error and first battery state information according to the battery real-time parameter and the preset parameter variable;
obtaining second battery state information according to the first battery state information;
acquiring third battery state information, and calculating and processing the first battery state information, the second battery state information and the third battery state information according to a preset weight to obtain fourth battery state information;
and obtaining the real-time battery capacity according to the fourth battery state information.
The battery testing method provided by the embodiment of the application has at least the following beneficial effects: the actual battery state information can be represented according to the preset weight and a plurality of different battery real-time parameters, so that the battery measurement error caused by representing the battery state information by a single battery parameter is avoided.
According to some embodiments of the present application, the obtaining of the voltage estimation error and the first battery state information according to the battery real-time parameter and the preset parameter variable includes:
performing online parameter observation processing on the battery real-time parameters and the preset parameter variables to obtain first battery parameters to be processed;
carrying out prior estimation processing on the first battery parameter to be processed to obtain the voltage estimation error;
and carrying out posterior estimation processing on the battery real-time parameters, the preset parameter variables and the voltage estimation error to obtain the first battery state information.
According to some of the embodiments of the present application, further comprising:
carrying out state estimation processing on the first battery state information to obtain a second battery parameter to be processed;
and carrying out prior estimation processing on the second battery parameter to be processed to obtain the second battery state information.
According to some embodiments of the present application, the obtaining the first battery state information by performing a posterior estimation process on the battery real-time parameter, the preset parameter variable, and the voltage estimation error includes:
carrying out posterior estimation processing on the battery real-time parameter, the preset parameter variable and the voltage estimation error to obtain an internal resistance value of an aged battery and a current internal resistance value of the battery;
and obtaining the first battery state information according to the internal resistance value of the aged battery, the current internal resistance value of the battery and the initial internal resistance value of the battery.
According to some embodiments of the present application, the second to-be-processed battery parameter includes a maximum current battery capacity, and the performing state estimation processing on the first battery state information to obtain the second to-be-processed battery parameter includes:
carrying out state estimation processing on the first battery state information to obtain the maximum value of the current battery capacity;
the performing prior estimation processing on the second battery parameter to be processed to obtain the second battery state information includes:
and carrying out prior estimation processing on the current battery capacity maximum value and the battery standard capacity maximum value to obtain the second battery state information.
According to some of the embodiments of the present application, the obtaining the third battery state information includes:
and performing offline detection on the battery to obtain offline battery parameters, and performing analysis fitting processing on the offline battery parameters to obtain third battery state information.
According to some embodiments of the present application, the calculating, according to a preset weight, the first battery state information, the second battery state information, and the third battery state information to obtain fourth battery state information includes:
presetting a first weight, a second weight and a third weight, and calculating and processing the first battery state information, the second battery state information and the third battery state information according to the first weight, the second weight and the third weight to obtain fourth battery state information.
According to some of the embodiments of the present application, further comprising: carrying out prior estimation processing on the real-time battery capacity to obtain the third information to be processed; and carrying out posterior estimation processing on the third information to be processed to obtain the real-time electric quantity information of the battery.
According to some of the embodiments of the present application, further comprising:
carrying out prior estimation processing on the first battery state information to obtain a voltage estimation error correction value;
correcting the voltage estimation error according to the voltage estimation error correction value to obtain a corrected voltage estimation error;
carrying out posterior estimation processing on the battery real-time parameter, the preset parameter variable and the corrected voltage estimation error so as to correct the first battery state information;
and/or (c) and/or,
carrying out posterior estimation processing on the third information to be processed to obtain a third information to be processed correction value;
correcting the third information to be processed according to the third information to be processed correction value to obtain corrected third information to be processed;
and carrying out posterior estimation processing on the corrected third information to be processed so as to correct the real-time electric quantity information of the battery.
According to a second aspect of embodiments of the present application, a battery detection system includes: a memory having a computer program stored thereon; a processor for executing the computer program in the memory to implement the battery detection method as in any of the above embodiments.
According to the battery detection system of the embodiment of the application, at least the following beneficial effects are achieved: by implementing the battery detection method in any of the above embodiments, the battery state information is represented by using different battery real-time parameters, so as to avoid battery measurement errors caused by representing the battery state information by using a single battery parameter.
Additional aspects and advantages of embodiments of the present application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
Drawings
Embodiments of the present application will be further described with reference to the accompanying drawings and embodiments, in which:
fig. 1 is a flowchart of a battery testing method according to an embodiment of the present disclosure; (ii) a
FIG. 2 is a schematic signal flow diagram illustrating a method for testing a battery according to an embodiment of the present disclosure;
FIG. 3 is a signal flow diagram of a battery testing method according to another embodiment of the present application
FIG. 4 is a flow chart of a battery testing method according to another embodiment of the present application;
FIG. 5 is a flow chart of a battery testing method according to another embodiment of the present application;
fig. 6 is a flowchart illustrating a battery testing method according to another embodiment of the present application.
Detailed Description
Reference will now be made in detail to embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein like reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are exemplary only for the purpose of explaining the embodiments of the present application, and are not to be construed as limiting the embodiments of the present application.
In the description of the embodiments of the present application, it should be understood that the orientation or positional relationship referred to in the description of the orientation, such as the upper, lower, front, rear, left, right, etc., is based on the orientation or positional relationship shown in the drawings, and is only for convenience of description and simplification of the description, but does not indicate or imply that the device or element referred to must have a specific orientation, be constructed in a specific orientation, and be operated, and thus, should not be construed as limiting the embodiments of the present application.
In the description of the embodiments of the present application, the number of the elements is one or more, the number of the elements is two or more, and the elements larger than, smaller than, larger than, or the like are understood as not including the number, and the elements larger than, smaller than, or the like are understood as including the number. If the first and second are described for the purpose of distinguishing technical features, they are not to be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated or implicitly indicating the precedence of the technical features indicated.
In the description of the embodiments of the present application, unless otherwise explicitly limited, terms such as setting, installing, connecting and the like should be understood in a broad sense, and those skilled in the art can reasonably determine the specific meanings of the terms in the embodiments of the present application by combining the specific contents of the technical solutions.
In the description of the embodiments of the present application, reference to the description of the terms "one embodiment," "some embodiments," "an illustrative embodiment," "an example," "a specific example," or "some examples" or the like means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the embodiments of the present application. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
Referring to fig. 1, fig. 2, and fig. 3, a battery testing method according to an embodiment of the present disclosure includes: step S100, acquiring real-time parameters of the battery, and presetting parameter variables; step S200, obtaining a voltage estimation error and first battery state information according to the battery real-time parameters and preset parameter variables; step S300, obtaining second battery state information according to the first battery state information; step S400, third battery state information is obtained, and the first battery state information, the second battery state information and the third battery state information are calculated according to preset weights to obtain fourth battery state information; and S500, obtaining the real-time battery capacity according to the fourth battery state information.
Further, performing parameter estimation Kalman algorithm processing through the battery real-time parameters and preset parameter variables to obtain voltage estimation errors and first battery state information; and performing state estimation SOC Kalman algorithm processing on the first battery state information to obtain second battery state information.
And respectively acquiring the first battery state information, the second battery state information and the third battery state information, and calculating the first battery state information, the second battery state information and the third battery state information according to a preset weight to obtain fourth battery state information. Further, the preset weight can be adjusted in real time according to the specific types of the first battery state information, the second battery state information and the third battery state information or the aging degree of the battery, so that the fourth battery state information can accurately reflect the real-time state of the battery.
Specifically, the first battery state information, the second battery state information, and the third battery state information may be battery state of health information represented by different battery parameters, and the fourth battery state information is obtained according to the battery state of health information of different battery parameters and corresponding preset weights to accurately reflect the state of health information of the battery.
The first battery state information, the second battery state information and the third battery state information can be obtained by representing basic battery parameters such as capacitance, resistance and battery capacity of the battery. The battery state information is characterized by different basic battery parameters so as to avoid battery measurement errors caused by the fact that a single battery parameter represents the battery state information.
Referring to fig. 4, in some embodiments, the step S200 of obtaining the voltage estimation error and the first battery state information according to the battery real-time parameter and the preset parameter variable includes: step S201, carrying out online parameter observation processing on the battery real-time parameters and preset parameter variables to obtain first battery parameters to be processed; s202, carrying out prior estimation processing on a first battery parameter to be processed to obtain a voltage estimation error; step S203, carrying out posterior estimation processing on the battery real-time parameters, the preset parameter variables and the voltage estimation errors to obtain first battery state information.
The method comprises the steps of carrying out online observation processing on real-time parameters and preset parameter variables of a battery to obtain first battery parameters to be processed for prior estimation processing, and obtaining a voltage estimation error. And updating or correcting the battery detection parameters through the voltage estimation error so as to ensure the accuracy of the battery detection.
Parameters and variables such as battery real-time parameters, preset parameter variables and the like are substituted into a battery parameter state equation set to carry out online observation processing and obtain first battery parameters to be processed. The voltage estimation error and other battery state information are obtained by carrying out prior estimation processing on the first battery parameter to be processed.
Other battery state information may include any of system state estimation parameters, error covariance estimation parameters, error matrix parameters, kalman gain matrix parameters, system state correction parameters, error covariance update parameters.
Whether the battery parameter state equation set can be solved and/or the solved solution has uniqueness is determined by carrying out prior estimation processing on the first battery parameter to be processed.
In some embodiments, the first battery state information is obtained by performing a posteriori estimation processing on the battery real-time parameter, the preset parameter variable, the voltage estimation error, and the first battery parameter to be processed.
It can be understood that parameter correction is performed on the battery parameter state equation set through the voltage estimation error so as to update the parameters in the battery parameter state equation set in real time, thereby avoiding the situation that a large error exists between the measured battery state parameter and the actual battery state parameter due to battery aging. And obtaining first battery state information used for representing the battery health state by carrying out posterior estimation processing on the battery real-time parameters, the preset parameter variables and the first battery parameters to be processed.
Referring to fig. 5, in some embodiments, the step S300 of obtaining the second battery state information according to the first battery state information further includes: s301, performing state estimation processing on the first battery state information to obtain a second battery parameter to be processed; and S302, carrying out prior estimation processing on the second battery parameter to be processed to obtain second battery state information.
And performing state estimation processing on the first battery state information to obtain a second battery parameter to be processed, and performing prior estimation processing on the second battery parameter to be processed to obtain second battery state information used for representing the battery health state.
Referring to fig. 6, in some embodiments, the step S203 of performing a posteriori estimation on the battery real-time parameter, the preset parameter variable, and the voltage estimation error to obtain the first battery state information includes: step S2031, carrying out posterior estimation processing on the real-time parameters of the battery, the preset parameter variables and the voltage estimation error to obtain the internal resistance value of the aged battery and the current internal resistance value of the battery; step S2032, first battery state information is obtained according to the internal resistance value of the aged battery, the current internal resistance value of the battery and the initial internal resistance value of the battery.
In some implementations, the battery aging internal resistance, the battery current internal resistance and the battery standard internal resistance are obtained by performing posterior estimation processing on the battery real-time parameter, the preset parameter variable and the first battery parameter to be processed, and the first battery state information is obtained according to the battery aging internal resistance, the battery current internal resistance and the battery standard internal resistance, so as to represent the battery health state through the battery internal resistance.
Wherein, the first battery state information calculation formula is as follows:
wherein, SOHrIndicating battery state-of-health information (first battery state information) calculated on the basis of the internal resistance; roldThe ohmic internal resistance value of the battery when the battery is aged is shown; rnewThe initial ohmic internal resistance value of the battery is shown when the battery leaves a factory; rrealIndicating the ohmic internal resistance value of the battery in the current state.
First battery state information used for representing the battery state of health is obtained through the variation of the ohmic internal resistance of the battery, so that the state of health of the battery is accurately reflected.
In some embodiments, if the second battery parameter to be processed includes the maximum current battery capacity, then step S301, performing state estimation processing on the first battery state information to obtain the second battery parameter to be processed includes: step S3011, performing state estimation processing on the first battery state information to obtain a current battery capacity maximum value; step S302, performing prior estimation processing on a second battery parameter to be processed to obtain second battery state information, including: and step S3021, carrying out prior estimation processing on the current maximum battery capacity and the maximum standard battery capacity to obtain second battery state information.
In a specific embodiment, a second battery state information used for representing the battery health state is obtained by performing state estimation processing on the first battery state information (such as parameters of battery capacity, ohmic internal resistance, output current, output voltage and the like) to obtain a second battery parameter to be processed, and performing prior estimation processing on the second battery parameter to be processed. The second battery parameter to be processed comprises a battery capacity parameter, the battery capacity parameter variation is obtained according to the battery capacity parameter and the battery state parameter equation set, and the second battery state information is obtained according to the battery capacity parameter and the battery capacity parameter variation.
Specifically, the second battery state information, SOH, is obtained according to the battery capacity parameter and the battery capacity parameter variationCBattery state of health information (second battery state information) calculated on the basis of the capacity is indicated.
Second battery state information (SOH)C) The calculation formula is as follows:
wherein, CrThe maximum use capacity of the battery is shown when the new battery leaves the factory; caRepresents the maximum usage capacity of the current battery; SOHCBattery state of health information (second battery state information) calculated on the basis of the capacity is indicated.
Further, second battery state information (the maximum use capacity of the current battery) for representing the battery health state is obtained by carrying out prior estimation processing on a second battery parameter (battery capacity) to be processed
Calculating the maximum use capacity of the current battery according to the electric quantity of the battery (the second battery parameter to be processed) and obtaining the estimated value of the maximum use capacity of the battery
Maximum capacity estimation for battery
The calculation formula is as follows:
therein, SOC2、SOC1Respectively representing the battery power (SOC values) of the battery at two different times.
In a practical computing scenario, SOC2、SOC1The battery state of charge (SOC value) of the battery at two different moments (the same battery is in a static state) is respectively represented, and the battery is in the static state in the battery measuring process.
The battery is subjected to standing treatment, and the standing interval time of data acquisition exceeds t minutes, so that the relation between the acquired battery power and the battery capacity accumulation is reduced.
Further, the convergence coefficient (rate of change of capacity estimation value) is set for the capacity estimation value
To avoid capacity estimation
There is an excessive error.
The convergence factor δ is calculated as follows:
where, δ represents the convergence coefficient,
indicating the collectable range.
By capacity values estimated for preceding and following moments
Is limited to improve the accuracy of the battery capacity estimation.
In some embodiments, obtaining the third battery state information comprises: and performing offline detection on the battery to obtain offline battery parameters, and performing analysis fitting processing on the offline battery parameters to obtain third battery state information.
Obtaining a third battery state information (SOH) by obtaining battery estimated state calculation values corresponding to different temperatures, different multiplying powers and different battery electric quantity ranges and analyzing and fitting the battery estimated state calculation valuesoff)。
Wherein the third battery state information (SOH)off) The calculation formula is as follows:
SOHoff＝f(rate，T，soc) (5)
the offline battery state information corresponding to different offline parameters is obtained by obtaining the battery offline parameters, and the current third battery state information (offline battery state information) of the battery is obtained according to the battery offline parameters and the battery real-time parameters.
In some embodiments, the obtaining the fourth battery state information by performing calculation processing on the first battery state information, the second battery state information, and the third battery state information according to the preset weight includes: presetting a first weight, a second weight and a third weight, and calculating and processing the first battery state information, the second battery state information and the third battery state information according to the first weight, the second weight and the third weight to obtain fourth battery state information.
The first battery state information SOHr and the second battery state information SOH are subjected to the preset first weight w1, the preset second weight w2 and the preset third weight w3CThird battery state information SOHoffAnd performing calculation processing to obtain fourth battery state information. Wherein the first weight corresponds to the first battery state information, the second weight corresponds to the second battery state information, and the third weight corresponds to the third battery state information.
Specifically, the first weight w1, the second weight w2, and the third weight w3 are adaptively adjusted according to the battery use stage (differentiated according to the battery operating time) of the battery to improve the accuracy of the fourth battery state information.
For example, in the early stage of battery usage, the third weight w3 is greater than the first weight w1, the second weight w 2; the third weight w3 is less than the first weight w1 and/or the second weight w2 during the middle and later stages of battery use or at rest.
In some embodiments, the battery capacity is subjected to feedback correction through the fourth battery state information so as to accurately reflect the real capacity of the battery, and a large error between the actual capacity of the battery and the marked capacity of the battery caused by battery aging is avoided.
In some embodiments, further comprising: carrying out prior estimation processing on the capacity of the real-time battery to obtain third information to be processed; and carrying out posterior estimation processing on the third information to be processed to obtain the real-time electric quantity information of the battery.
Obtaining third information SOH to be processed by carrying out prior estimation processing on real-time battery capacityC(ii) a For the third information SOH to be processedCAnd carrying out posterior estimation processing to obtain the real-time electric quantity information of the battery.
Referring to fig. 1 and fig. 3, in some embodiments, the method further includes: carrying out prior estimation processing on the first battery state information to obtain a voltage estimation error correction value; correcting the voltage estimation error according to the voltage estimation error correction value to obtain a corrected voltage estimation error; carrying out posterior estimation processing on the real-time parameters of the battery, the preset parameter variables and the corrected voltage estimation error so as to correct the first battery state information; and/or, carrying out posterior estimation processing on the third information to be processed to obtain a third information correction value to be processed; correcting the third information to be processed according to the third information to be processed correction value to obtain corrected third information to be processed; and carrying out posterior estimation processing on the corrected third information to be processed so as to correct the real-time electric quantity information of the battery.
It can be understood that the voltage estimation error and the real-time electric quantity information involved in the parameter processing process are corrected in real time to perform adaptive adjustment on the battery detection method, so that the algorithm precision is improved.
Specifically, a voltage estimation error correction value is obtained by carrying out prior estimation processing on first battery state information; correcting the voltage estimation error according to the voltage estimation error correction value to obtain a corrected voltage estimation error; and carrying out posterior estimation processing on the real-time parameters of the battery, the preset parameter variables and the corrected voltage estimation error so as to correct the first battery state information.
The voltage estimation error correction value is obtained through prior estimation processing to correct the first battery state information, so that a battery state information calculation closed loop is constructed, and real-time constraint and iterative operation are performed.
In some embodiments, the battery detection method, which performs real-time estimation processing on part of the initial battery parameters, further includes: acquiring a noise covariance parameter array of the battery; and correcting the battery parameter discrete equation set according to the noise covariance parameter number set.
And correcting the battery parameter discrete equation set through the noise covariance parameter number set so as to reduce the system divergence caused by the mutation of the model error covariance matrix. The measurement error covariance matrix may be determined from the actual voltage current sampling accuracy.
According to factors (temperature, multiplying power, SOC and aging) under different states, the Q is combinedk-1To form searches of different dimensions.
For example, the relative range of the battery operating temperature is within 30 ℃, so three values can be set: t1, T2, T3; the V-SOC interval variation trend of the lithium iron phosphate battery is obvious, so that three values can be set: SOC1, SOC2, SOC 3; the battery working charge-discharge multiplying power range can be set with three interval values: c1, C2, C3, C4. The measurement noise covariance matrix is determined by the actual voltage current sampling accuracy, as shown in table 1.
TABLE 1
And calling the corresponding noise covariance to correct the discrete equation set of the battery parameters under different battery states by establishing a chart relation among the temperature, the battery electric quantity, the charge-discharge multiplying power and the noise covariance.
Specifically, there are two main model parameters to be corrected in the second-order one-state lag model, i.e., Qk-1Is a two-dimensional matrix of 2x 2.
In some embodiments, a battery detection system, comprises: a memory having a computer program stored thereon; a processor for executing a computer program in a memory to implement the battery detection method as provided in any of the above embodiments.
By implementing the battery detection method in any of the above embodiments, the battery state information is represented by using different battery real-time parameters, so as to avoid battery measurement errors caused by representing the battery state information by using a single battery parameter.
Although the embodiments of the present application have been described in detail with reference to the drawings, the embodiments of the present application are not limited to the above embodiments, and various changes can be made without departing from the spirit and scope of the embodiments of the present application within the knowledge of those skilled in the art. Furthermore, the embodiments and features of the embodiments of the present application may be combined with each other without conflict.
Claims (10)
1. A battery testing method, comprising:
acquiring real-time parameters of a battery, and presetting parameter variables;
obtaining a voltage estimation error and first battery state information according to the battery real-time parameter and the preset parameter variable;
obtaining second battery state information according to the first battery state information;
acquiring third battery state information, and calculating and processing the first battery state information, the second battery state information and the third battery state information according to a preset weight to obtain fourth battery state information;
and obtaining the real-time battery capacity according to the fourth battery state information.
2. The battery testing method of claim 1, wherein obtaining a voltage estimation error and first battery state information according to the battery real-time parameter and the preset parameter variable comprises:
performing online parameter observation processing on the battery real-time parameters and the preset parameter variables to obtain first battery parameters to be processed;
carrying out prior estimation processing on the first battery parameter to be processed to obtain the voltage estimation error;
and carrying out posterior estimation processing on the battery real-time parameters, the preset parameter variables and the voltage estimation error to obtain the first battery state information.
3. The battery testing method of claim 2, wherein obtaining second battery state information based on the first battery state information further comprises:
carrying out state estimation processing on the first battery state information to obtain a second battery parameter to be processed;
and carrying out prior estimation processing on the second battery parameter to be processed to obtain the second battery state information.
4. The battery testing method according to any one of claims 2 or 3, wherein the obtaining the first battery state information by performing a posteriori estimation on the battery real-time parameter, the preset parameter variable, and the voltage estimation error includes:
carrying out posterior estimation processing on the battery real-time parameter, the preset parameter variable and the voltage estimation error to obtain an internal resistance value of an aged battery and a current internal resistance value of the battery;
and obtaining the first battery state information according to the internal resistance value of the aged battery, the current internal resistance value of the battery and the initial internal resistance value of the battery.
5. The battery testing method according to claim 3, wherein the second battery parameter to be processed includes a current maximum battery capacity, and performing state estimation processing on the first battery state information to obtain a second battery parameter to be processed includes:
carrying out state estimation processing on the first battery state information to obtain the maximum value of the current battery capacity;
the performing prior estimation processing on the second battery parameter to be processed to obtain the second battery state information includes:
and carrying out prior estimation processing on the current battery capacity maximum value and the battery standard capacity maximum value to obtain the second battery state information.
6. The battery testing method of claim 3, wherein the obtaining third battery status information comprises:
and performing offline detection on the battery to obtain offline battery parameters, and performing analysis fitting processing on the offline battery parameters to obtain third battery state information.
7. The battery testing method according to claim 3, wherein the calculating the first battery state information, the second battery state information, and the third battery state information according to a preset weight to obtain fourth battery state information comprises:
presetting a first weight, a second weight and a third weight, and calculating and processing the first battery state information, the second battery state information and the third battery state information according to the first weight, the second weight and the third weight to obtain fourth battery state information.
8. The battery testing method of claim 3, further comprising:
carrying out prior estimation processing on the capacity of the real-time battery to obtain third information to be processed;
and carrying out posterior estimation processing on the third information to be processed to obtain the real-time electric quantity information of the battery.
9. The battery testing method of claim 8, further comprising:
carrying out prior estimation processing on the first battery state information to obtain a voltage estimation error correction value;
correcting the voltage estimation error according to the voltage estimation error correction value to obtain a corrected voltage estimation error;
carrying out posterior estimation processing on the battery real-time parameter, the preset parameter variable and the corrected voltage estimation error so as to correct the first battery state information;
and/or (c) and/or,
carrying out posterior estimation processing on the third information to be processed to obtain a third information to be processed correction value;
correcting the third information to be processed according to the third information to be processed correction value to obtain corrected third information to be processed;
and carrying out posterior estimation processing on the corrected third information to be processed so as to correct the real-time electric quantity information of the battery.
10. A battery detection system, comprising: a memory having a computer program stored thereon; a processor for executing the computer program in the memory to implement:
the battery detection method according to any one of claims 1 to 9.
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