Evaluation method for monitoring battery consistency in real time

Abstract

The invention discloses an evaluation method for monitoring the consistency of batteries in real time. The method comprises the following steps: (1) selecting consistency evaluation parameters of the batteries; (2) establishing an index matrix of consistency evaluation parameters; (3) calculating a weight factor of the consistency evaluation parameter by utilizing an AHP (Analytic Hierarchy Process); (IV) determining boundary values of consistency evaluation parameters of the battery in each state; (V) calculating a consistency comprehensive parameter of the battery in each state; vI, calculating constants of a Cauchy distribution calculation formula; (VII) collecting attribute data of the battery system in real time, and calculating real-time consistency comprehensive parameters; and (VIII) obtaining a Cauchy distribution calculation formula based on the step (VI), and converting a real-time consistency comprehensive parameter into a percentage. Hardware of original equipment does not need to be changed, and the upgrading cost is reduced; the consistency of battery cell modules, clusters and stacks can be calculated in real time; and the consistency state of the current battery cell can be effectively, conveniently and quickly observed.

Description

Technical Field

[0001] The present invention belongs to the technical field of battery management, and in particular relates to an evaluation method for real-time monitoring of battery consistency. Background Art

[0002] With the promotion of new energy technologies, batteries are being used more and more widely. Many photovoltaic and wind power plants need to be equipped with storage, so energy storage systems are developing rapidly. The evaluation of the operating status of power station energy storage systems has been studied by practitioners from all walks of life.

[0003] In actual application, the health status of energy storage power stations is affected by operating conditions and environment, and each single battery will have different degrees of inconsistency, which will seriously affect the safe operation of the power station. There are many factors that affect the consistency of batteries, and there has been a lack of a scientific evaluation method that can systematically integrate various factors and present them to users in an intuitive way. Summary of the invention

[0004] The present invention is proposed to overcome the shortcomings of the prior art, and its purpose is to provide an evaluation method for real-time monitoring of battery consistency.

[0005] The present invention is achieved through the following technical solutions:

[0006] A method for evaluating battery consistency in real time monitoring includes the following steps:

[0007] (I) Select the consistency evaluation parameters of the battery;

[0008] (II) Establish an indicator matrix for consistency assessment parameters;

[0009] (III) Calculating the weight factors of the consistency evaluation parameters using the AHP analytic hierarchy process based on the indicator matrix of the consistency evaluation parameters established in step (II);

[0010] (IV) Determine the boundary values ​​of the consistency assessment parameters under various battery conditions;

[0011] (V) calculating the comprehensive consistency parameters of the battery under various states using the boundary values ​​of the consistency evaluation parameters and the weight factors of the consistency evaluation parameters;

[0012] (VI) When the battery is determined to be in a healthy state, the corresponding percentage of the upper limit value of the consistency comprehensive parameter is 100%; when the battery is determined to be in a sub-healthy state, the corresponding percentage of the upper limit value of the consistency comprehensive parameter is 80%, and the constant of the Cauchy distribution calculation formula is calculated;

[0013] (VII) collecting the attribute data of the battery system in real time, calculating the real-time consistency evaluation parameters according to the attribute data collected in real time, and obtaining the real-time consistency comprehensive parameters by using the consistency comprehensive parameter calculation formula;

[0014] (VIII) Based on the Cauchy distribution calculation formula obtained in step (VI), the real-time consistency comprehensive parameter is converted into a percentage in the range of 0 to 100%, and the current battery consistency level is calculated in real time.

[0015] In the above technical solution, the battery consistency evaluation parameters include the cell extreme SOC, extreme voltage, voltage standard deviation, coefficient of variation, extreme temperature, maximum temperature and cell internal resistance.

[0016] In the above technical solution, the battery status includes healthy, sub-healthy and severe.

[0017] In the above technical solution, the calculation formula of the consistency comprehensive parameter is:

[0018] C=Σx i W i

[0019] Where: C is the consistency comprehensive parameter, X i is the boundary value of the consistency assessment parameter, W i is the weight factor of the consistency assessment parameter, i = extreme SOC, extreme voltage, voltage standard deviation, coefficient of variation, extreme temperature, maximum temperature, and cell internal resistance.

[0020] In the above technical solution, the calculation formula of the Cauchy distribution is as follows:

[0021]

[0022] Where: F(x) is the corresponding percentage of the consistency comprehensive parameter, m and d are constants, and x is the consistency comprehensive parameter.

[0023] In the above technical solution, the calculation method of the constant of the Cauchy distribution calculation formula is specifically as follows:

[0024] Establish the battery status as healthy x 100 and the battery status is sub-healthy boundary x 80 The Cauchy distribution calculation formula is used when the two formulas are combined to obtain the constants m and d in the Cauchy distribution calculation formula;

[0025] The Cauchy distribution calculation formula when the battery state is healthy is:

[0026]

[0027] When the battery state is at the sub-health boundary, the Cauchy distribution calculation formula is:

[0028]

[0029] Where: x 100It is the upper limit value of the consistency comprehensive parameter when the battery status is healthy;

[0030] x 80 It is the upper limit value of the consistency comprehensive parameter when the battery status is sub-healthy;

[0031] m and d are constants.

[0032] In the above technical solution, the attribute data includes voltage, temperature, SOC and internal resistance.

[0033] In the above technical solution, after the step (IV) determines the boundary values ​​of the consistency evaluation parameters under various states of the battery, the boundary values ​​of the consistency evaluation parameters are normalized, and the normalized consistency evaluation parameters are used in the calculation of subsequent steps. The reason for the normalization is: after determining the boundary values ​​of the consistency evaluation parameters under various states of the battery, if the voltage and temperature values ​​included in the consistency evaluation parameters are very different, in order to avoid a large deviation when calculating the consistency comprehensive parameters, resulting in the original parameters with larger weights accounting for a smaller proportion in the comprehensive parameters, it is necessary to normalize the boundary values ​​of the consistency evaluation parameters. Here, the normalization method takes the extreme SOC as an example. The healthy upper limit value is 5, and the sub-healthy upper limit value is 10. Then the healthy upper limit value of the extreme SOC after normalization is 5 / 10=0.5, and the sub-healthy upper limit value is 10 / 10=1.

[0034] The beneficial effects of the present invention are:

[0035] The present invention provides an evaluation method for real-time monitoring of battery consistency. Based on the internal resistance, temperature, voltage and other parameters of the battery cell, the weight of each factor is determined through the evaluation of the AHP hierarchical analysis method system, and then through the Cauchy distribution, the consistency of the battery cell is finally calculated; the present invention is mainly used to estimate the voltage consistency under the current working condition in real time when the working condition changes, and is used to warn the user; the present invention mainly uses the Cauchy distribution to convert the specific value of the battery cell consistency into a range of 0-100%, which is convenient and fast. The present invention does not require changes to the hardware of the original equipment, reducing the upgrade cost; it can be applied to the energy storage system to calculate the consistency of the battery cell module, cluster, and stack in real time; it can effectively, conveniently and quickly observe the current state of battery cell consistency. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 It is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0037] In order to enable those skilled in the art to better understand the technical solution of the present invention, the technical solution of the present invention is further described below with reference to the accompanying drawings and through specific implementation methods.

[0038] The professional terms involved in this application are explained as follows:

[0039] 1. SOC: The full name is State of Charge. SOC refers to the state of charge of the battery, that is, the available state of the remaining power in the battery.

[0040] 2. AHP:

[0041] The analytic hierarchy process breaks down the problem into different components according to the nature of the problem and the overall goal to be achieved, and clusters and combines the factors at different levels according to the interrelationships, influences and affiliations between the factors to form a multi-level analysis structure model, which ultimately reduces the problem to the determination of the relative importance of the lowest level (schemes and measures for decision-making, etc.) relative to the highest level (overall goal) or the ranking of the relative order of merit.

[0042] 3. Cauchy distribution:

[0043] Cauchy distribution is a continuous probability distribution in probability theory and statistics, also known as Lorenz distribution, which is a kind of stable distribution. A stable distribution means that when the random variable undergoes a linear combination, its probability density function remains unchanged. Cauchy distribution is a continuous probability distribution with no mathematical expectation. When the random variable X satisfies its probability density function, X is said to obey Cauchy distribution.

[0044] 4. Coefficient of variation: The ratio of the standard deviation of the original data to the mean of the original data. The coefficient of variation includes the coefficient of variation of voltage, the coefficient of variation of resistance and the coefficient of variation of temperature. One or more of them can be selected when establishing the indicator matrix.

[0045] Example 1

[0046] A method for evaluating battery consistency in real time monitoring includes the following steps:

[0047] (I) Select the consistency evaluation parameters of the battery;

[0048] The battery consistency evaluation parameters include battery cell extreme SOC, extreme voltage, voltage standard deviation, coefficient of variation, extreme temperature, maximum temperature and battery cell internal resistance;

[0049] (II) Establishing the index matrix of consistency assessment parameters

[0050] The index matrix of the consistency evaluation parameters is established based on the importance of various elements determined by actual experience, papers and other data. The index matrix can be adjusted based on different application conditions.

[0051] The establishment of the indicator matrix of this application is based on the document "Jin Wentao, Li Yuyang, Jia Xuecui, et al., Research on Comprehensive Evaluation Method of Battery Consistency of Energy Storage Power Station [J]. Low Voltage Electrical Appliances, 2022(005):000"; the indicator matrix of this embodiment is shown in Table 1;

[0052] Table 1: Indicator matrix for consistency assessment parameters

[0053] Indicator Matrix Very poor SOC Extreme voltage difference Voltage standard deviation Coefficient of variation Extreme temperature Maximum temperature Cell internal resistance Very poor SOC 1 7 7 5 5 3 5 Extreme voltage difference 1 / 7 1 1 1 / 3 1 / 3 1 / 5 1 / 3 Voltage standard deviation 1 / 7 1 1 1 / 3 1 / 3 1 / 5 1 / 3 Voltage variation coefficient 1 / 5 3 3 1 1 1 / 3 1 Extreme temperature 1 / 5 3 3 1 1 1 / 3 1 Maximum temperature 1 / 3 5 5 3 3 1 3 Cell internal resistance 1 / 5 3 3 1 1 1 / 3 1

[0054] (III) According to the index matrix of consistency evaluation parameters established in step (II), the weight factors of consistency evaluation parameters are calculated using AHP. The weight factors of each consistency evaluation parameter are shown in Table 2.

[0055] Table 2: Weighting factors for various consistency assessment parameters

[0056]

[0057] (IV) Determine the boundary values ​​of consistency evaluation parameters under various battery conditions

[0058] The battery status includes healthy, sub-healthy and severe;

[0059] The boundary values ​​of the consistency assessment parameters are mainly derived from the relevant battery specifications, with a small number of references to relevant literature.

[0060] The boundary values ​​of the consistency evaluation parameters of the battery used in this embodiment are shown in Table 3;

[0061] Table 3: Boundary values ​​of consistency assessment parameters

[0062]

[0063]

[0064] In Table 3, the upper limit of health belongs to the healthy state, that is, when it is less than the boundary value, it belongs to the healthy state. Taking the extreme SOC as an example, as long as the value is not greater than 5, it is a healthy state; the lower limit of sub-health belongs to health, and the upper limit of sub-health belongs to sub-health. Taking the extreme SOC as an example, a value greater than 5 and less than or equal to 10 belongs to the sub-health state, and 10 and greater than 10 are all serious states.

[0065] (V) Using the boundary value of the consistency evaluation parameter and the weight factor of the consistency evaluation parameter to calculate the boundary value of the consistency comprehensive parameter under each state of the battery

[0066] The calculation formula of the consistency comprehensive parameter is:

[0067] C=Σx i Wi

[0068] Where: C is the consistency comprehensive parameter, X i is the boundary value of the consistency assessment parameter, W i is the weight factor of the consistency assessment parameter, i = extreme SOC, extreme voltage, voltage standard deviation, voltage variation coefficient, extreme temperature, maximum temperature, cell internal resistance;

[0069] The comprehensive consistency parameters of the battery in each state of this embodiment are shown in Table 4;

[0070] Table 4: Boundary values ​​of consistency comprehensive parameters under various battery conditions

[0071]

[0072] (VI) When the battery is determined to be in a healthy state, the corresponding percentage of the upper limit value of the consistency comprehensive parameter is 100%; when the battery is determined to be in a sub-healthy state, the corresponding percentage of the upper limit value of the consistency comprehensive parameter is 80%, and the constant of the Cauchy distribution calculation formula is calculated;

[0073] The calculation formula of the Cauchy distribution is as follows:

[0074]

[0075] Where: F(x) is the percentage corresponding to the consistency comprehensive parameter, m and d are constants; x is the consistency comprehensive parameter;

[0076] The calculation method of the constant of the Cauchy distribution calculation formula is specifically as follows:

[0077] Establish the battery status as healthy x 100 and battery status is sub-healthy x 80 The Cauchy distribution calculation formula is used when the two formulas are combined to obtain the constants m and d in the Cauchy distribution calculation formula;

[0078] The Cauchy distribution calculation formula when the battery state is healthy is:

[0079]

[0080] The Cauchy distribution calculation formula when the battery state is at the sub-health boundary is:

[0081]

[0082] Where: x 100 It is the upper limit value of the consistency comprehensive parameter when the battery status is healthy;

[0083] x 80 It is the upper limit value of the consistency comprehensive parameter when the battery status is sub-healthy;

[0084] Table 5: Battery status and corresponding percentage comparison table

[0085]

[0086] (VII) collecting the attribute data of the battery system in real time, calculating and obtaining the real-time consistency evaluation parameters according to the attribute data collected in real time, and obtaining the real-time consistency comprehensive parameters by using the consistency comprehensive parameter calculation formula;

[0087] The attribute data includes voltage, temperature, SOC and internal resistance;

[0088] (VIII) Based on the Cauchy distribution calculation formula determined in step (VI), the real-time consistency comprehensive parameter is converted into a percentage within the range of 0 to 100%, and the current battery consistency level is calculated in real time.

[0089] The calculation method of the real-time comprehensive indicators of battery cells (modules, clusters, stacks) is also shown above.

[0090] For the above data, based on the Cauchy distribution, the degree of cell consistency is converted into a range of 0-100%, and the current voltage consistency is calculated in real time.

[0091] The present invention can quantitatively reflect the consistency of single cells, avoid the inconsistency and extensiveness of grading, provide theoretical support for the operation and maintenance analysis of batteries in energy storage power stations, and improve the safe operation of energy storage power stations.

[0092] The applicant declares that the above is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Those skilled in the art should understand that any changes or substitutions that can be easily thought of by those skilled in the art within the technical scope disclosed by the present invention shall fall within the protection scope and disclosure scope of the present invention.

Claims

1. A real-time monitoring and evaluation method for battery consistency, characterized in that: The following steps are involved: (I) Select the consistency evaluation parameters of the battery; (II) Establish an indicator matrix for consistency assessment parameters; (III) Calculating the weight factors of the consistency evaluation parameters using the AHP analytic hierarchy process based on the indicator matrix of the consistency evaluation parameters established in step (II); (IV) Determine the boundary values ​​of the consistency assessment parameters under various battery conditions; (V) calculating the comprehensive consistency parameters of the battery under various states using the boundary values ​​of the consistency evaluation parameters and the weight factors of the consistency evaluation parameters; (VI) When the battery is determined to be in a healthy state, the corresponding percentage of the upper limit value of the consistency comprehensive parameter is 100%; when the battery is determined to be in a sub-healthy state, the corresponding percentage of the upper limit value of the consistency comprehensive parameter is 80%, and the constant of the Cauchy distribution calculation formula is calculated; (VII) collecting the attribute data of the battery system in real time, calculating the real-time consistency evaluation parameters according to the attribute data collected in real time, and obtaining the real-time consistency comprehensive parameters by using the consistency comprehensive parameter calculation formula; (VIII) Based on the Cauchy distribution calculation formula obtained in step (VI), the real-time consistency comprehensive parameter is converted into a percentage in the range of 0 to 100%, and the current battery consistency level is calculated in real time.

2. The method for evaluating battery consistency in real time monitoring according to claim 1, characterized in that: The battery consistency evaluation parameters include the cell extreme SOC, extreme voltage, voltage standard deviation, coefficient of variation, extreme temperature, maximum temperature and cell internal resistance; the coefficient of variation is any one or more of the voltage coefficient of variation, resistance coefficient of variation and coefficient of variation temperature.

3. The method for evaluating battery consistency in real time monitoring according to claim 1, characterized in that: The battery status includes healthy, sub-healthy and severe.

4. The method for evaluating battery consistency in real time monitoring according to claim 1, characterized in that: The calculation formula of the consistency comprehensive parameter is: C=xW Where: C is the consistency comprehensive parameter, X i is the boundary value of the consistency assessment parameter, W i is the weight factor of the consistency assessment parameter, i = extreme SOC, extreme voltage, voltage standard deviation, coefficient of variation, extreme temperature, maximum temperature, and cell internal resistance.

5. The method for evaluating battery consistency in real time monitoring according to claim 1, characterized in that: The calculation formula of the Cauchy distribution is as follows: Where: F(x) is the corresponding percentage of the consistency comprehensive parameter, m and d are constants, and x is the consistency comprehensive parameter.

6. The method for evaluating battery consistency in real time monitoring according to claim 1, characterized in that: The calculation method of the constant of the Cauchy distribution calculation formula is specifically as follows: Establish the Cauchy distribution calculation formulas when the battery state is healthy and when the battery state is at the sub-health boundary, and combine the two formulas to obtain the constants m and d in the Cauchy distribution calculation formula; The Cauchy distribution calculation formula when the battery state is healthy is: When the battery state is at the sub-health boundary, the Cauchy distribution calculation formula is: Where: x 100 It is the upper limit value of the consistency comprehensive parameter when the battery status is healthy; x 80 It is the upper limit value of the consistency comprehensive parameter when the battery status is sub-healthy; m and d are constants.

7. The method for evaluating battery consistency in real time monitoring according to claim 1, characterized in that: The attribute data includes voltage, temperature, SOC and internal resistance.

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