CN110031770B

CN110031770B - A method to quickly get the capacity of all single cells in a battery pack

Info

Publication number: CN110031770B
Application number: CN201910353661.5A
Authority: CN
Inventors: 刘中财; 王东征; 严晓; 黄碧雄; 马非凡; 丁家宝; 郭海龙
Original assignee: Shanghai MS Energy Storage Technology Co Ltd
Current assignee: Shanghai Meikesheng Energy Technology Co.,Ltd.
Priority date: 2019-04-29
Filing date: 2019-04-29
Publication date: 2021-08-17
Anticipated expiration: 2039-04-29
Also published as: CN110031770A

Abstract

The present invention relates to a method for quickly obtaining the capacity of all single cells in a battery pack, comprising the following steps: S1, obtaining target battery reference curve data and battery nominal capacity Cap _initial ; S2, processing the battery reference curve data and recording characteristics The capacity or charging capacity of the battery at the value position; S3, calculate the relationship coefficient between the capacity and the total capacity between the battery characteristic values; S4, process the charging curve of the battery pack, and record the charging capacity of the battery at the characteristic value position; S5, calculate the step S4 to obtain The capacity between the characteristic values of the battery, and according to the relationship coefficient described in step S3, calculate the capacity of all the single cells in the battery pack one by one. The method of the invention is applicable in the normal charging process of the battery pack, does not affect the input and output of the battery operation, only needs to obtain the battery SOC-OCV curve data or a historical charging curve, the nominal capacity of the battery in advance, and does not need to additionally test the battery parameters. The total capacity of all the single cells in the system can be obtained in real time.

Description

Method for rapidly obtaining capacity of all single batteries in battery pack

Technical Field

The invention relates to a method for quickly obtaining the capacity of all single batteries in a battery pack.

Background

The invention relates to the capacity of all single batteries in a battery pack, in particular to the capacity of all single batteries in a battery pack formed by connecting a plurality of single batteries in series. Lithium ion batteries have been widely used in the fields of electric vehicles, electrochemical energy storage, 3C electronic products, and the like, because of their advantages of high energy, high battery voltage, wide operating temperature range, long storage life, and the like. The effective capacity of the battery is related to the continuous working time of the battery, the resistance value of the battery is closely related to the instant charging and discharging capacity of the battery, and in addition, in the battery packs which are connected in series into a group, the capacity distribution of the single batteries is closely related to the consistency of the battery packs.

The capacity of a lithium ion battery is one of important performance indexes for measuring the performance of the battery, and it represents the amount of electricity discharged by the battery (JS-150D can be used for discharge test) under certain conditions (discharge rate, temperature, end voltage, etc.), that is, the capacity of the battery is usually expressed in ampere-hour units (abbreviated as a · H, 1A · H is 3600C). In the lithium ion battery in the actual use process, the situation that the battery is fully charged and discharged basically does not exist, and the total capacity of the battery is difficult to know, so that the estimation of the battery and the nuclear power State (SOC) is influenced, the accurate real-time calculation of the capacity of the battery is realized, and the lithium ion battery has important significance for the safety management of the battery.

The invention discloses a Chinese patent (patent number: CN109342955A, patent name: a method and a system for calculating the capacity of a lithium ion battery). according to the method, the discharge capacity of the lithium ion battery at the experimental temperature is obtained by performing discharge tests on the lithium ion battery at n experimental temperatures, a model is established by combining an Arrhenius formula, and the battery capacity value at any temperature point is calculated. The method needs n discharge tests in advance, is complex to operate, can only calculate the capacity value of the battery at different temperatures, cannot accurately calculate the capacity value of the battery after aging, and is poor in practicability.

The invention discloses a Chinese patent (patent number: CN 108152747A, patent name: detection method and device of storage battery capacity), which is characterized in that the method comprises the steps of obtaining a measured value of a storage battery discharge parameter of a wind generating set in the process of supplying power and changing the pitch by using the storage battery; and detecting the current capacity of the storage battery according to the measured value and a functional relation constructed by the storage battery test by utilizing the discharge parameters. The method needs to carry out a large number of storage battery tests before use to construct a relational database of measured values and battery capacity, calculates the required measured values by capturing appropriate discharge parameters in the actual use process, and evaluates the current capacity of the storage battery by searching the corresponding capacity in the database prepared in advance. The method needs to establish a relational database in advance, and has troublesome actual application and high cost; and due to the nonlinear characteristic of the battery, in the implementation process, whether the corresponding relation between the capacity of the storage battery and the corresponding measured value is established or not is judged, and the accuracy of the result is lack of data support.

The invention patent of China (patent number: CN108732508, patent name: a real-time estimation method of lithium ion battery capacity) obtains a charging data-real-time capacity VS voltage curve in a standard capacity test through a battery durability test, and then performs data fitting on the curve for difference. The peak position and the size in the difference result curve have correlation with the residual capacity of the battery, and the battery capacity can be estimated by comparing the difference curve in the initial condition and the certain time condition. The method requires a durability test for the battery, and the method has poor practical operability; the peak value of the difference result curve is related to a data screening processing method, and the error is large.

Chinese patent (patent No. CN109031153, patent name: a method for estimating the state of health of lithium ion battery online), this method passes the test of short-term cycle life, as the initial parameter of model training, utilize the capacity increment analysis method, extract a plurality of characteristic parameters from the curve of capacity increment, form the characteristic parameter set, carve the state of health of the battery, and regard the value of the characteristic parameter as the model output of the regression model method of the multiple output Gaussian process, finish the online assessment to the capacity of the battery. The method needs to carry out cycle life test, and practical application has difficulty.

Disclosure of Invention

The invention aims to provide a method for calculating the capacity value of all single batteries in a battery pack in real time by extracting characteristic value parameters after processing based on a charging curve in the normal work of the batteries and substituting the characteristic value parameters into a model for calculation.

The purpose of the invention can be realized by the following technical scheme:

a method for rapidly obtaining the capacity of all single batteries in a battery pack comprises the following steps:

s1, aiming at the target lithium ion battery, acquiring battery reference curve data and battery nominal capacity Cap_initial；

S2, processing the lithium ion battery reference curve data, and recording the capacity or charging capacity of the battery at the characteristic value position;

s3, calculating a relation coefficient between the capacity and the total capacity among the characteristic values of the batteries;

s4, processing the battery pack charging curve, and recording the charging capacity of the battery at the characteristic value position;

and S5, calculating the capacities among the battery characteristic values obtained in the step S4, and calculating the capacities of all the single batteries in the battery pack one by one according to the relation coefficient in the step S3.

The battery reference curve data in step S1 may be battery SOC-OCV curve data obtained from a manufacturer, or may be historical charging curve data.

In step S2, the processing is performed on the lithium ion battery reference curve data, and the capacity or the charging capacity of the battery at the characteristic value position is recorded: according to the type of the battery material, data with SOC greater than 20% are obtained for the lithium iron phosphate battery, a capacity increment curve is obtained, and the calculation formula is

Extracting a characteristic value, wherein the position of the characteristic value is the maximum position in the capacity increment curve, and recording the capacity Q or the charging capacity Q' corresponding to the position of the characteristic value; for ternary material battery, data with SOC greater than 20% is taken to obtain d²Q/dV²Curve, the calculation formula is

Extracting the feature value, the position of the feature value is

And recording the capacity Q or the charging capacity Q' corresponding to the characteristic value position; q ═ SOC Cap_initial；

Wherein: q is the battery capacity, Q' is the charge capacity, dQ is the differential of the capacity, d²Q is the second differential of the capacity, Δ Q_kIs the difference in capacity between adjacent samples, V is the voltage of the cell, dV is the differential of the voltage, dV²Is the second order differential of the voltage, Δ V_kIs adjacent toDifference in voltage between sampling points, Δ Q, for each sampling point k_k＝Q_k-Q_k-1，ΔV_k＝V_k-V_k-1，ΔQ_k-1＝Q_k-1-Q_k-2，ΔV_k-1＝V_k-1-V_k-2。

Wherein, the characteristic value of the battery reference curve has 2, namely a first characteristic value and a second characteristic value, and the capacity Q of the 1 st characteristic value position is recorded₁Or charging capacity Q'₁Capacity Q of the 2 nd eigenvalue position₂Or charging capacity Q'₂。

In step S3, a coefficient g of the relationship between the capacity and the total capacity between the battery characteristic values is calculated as Δ Q/Cap_initial(ii) a Where Δ Q is the capacity difference between the 1 st characteristic value and the 2 nd characteristic value, Δ Q ═ Q₂-Q₁L, |; if historical charging curve data is employed, then Δ Q ═ Q'₂-Q‘₁|。

Wherein, the step S4 is to process the battery pack charging curve, and the recording of the battery charging capacity at the characteristic value position specifically includes: and extracting data meeting the condition that delta V is larger than or equal to X in the charging process of the battery pack. According to the type of a battery material, data with SOC greater than 20% are taken for the lithium iron phosphate battery, a capacity increment analysis method is utilized, a characteristic value is extracted from a capacity increment curve, and the charging capacity corresponding to the position of the characteristic value is recorded; for ternary material battery, data with SOC greater than 20% is taken to obtain d²Q/dV²A curve, extracting a characteristic value and recording the charging capacity corresponding to the position of the characteristic value; the charging capacity corresponding to the characteristic value comprises a charging capacity Q 'of the 1 st characteristic value position'_1jAnd a charging capacity Q 'of the 2 nd characteristic value position'_2jWherein: q_1jThe j number of the single battery capacity, Q, of the 1 st characteristic value position_2jIs the No. 2 characteristic value position j single battery capacity, Q'_1jIs the charging capacity of the monomer of No. j of the 1 st characteristic value position, Q'_2jThe charge capacity of the No. j cell at the No. 2 characteristic value position.

Wherein the step of S5 calculates the capacity between the characteristic values of the batteries obtained in the step of S4, and performs the calculation according to the characteristic values of the batteries obtained in the step of S3The specific calculation of the capacities of all the single batteries in the battery pack is as follows: calculating the capacity difference between the 1 st characteristic value and the 2 nd characteristic value of the j single battery, namely delta Q_j＝|Q_2j-Q_1j|＝|Q‘_2j-Q‘_1jAccording to the formula Cap_j＝ΔQ_jThe capacity of the j single battery is obtained, and then the capacities of other single batteries in the battery pack are calculated one by one; wherein, Cap_jThe j-th unit cell capacity g is a coefficient of the relationship between the capacity and the total capacity between the characteristic values of the battery obtained in claim 5.

Wherein the value range of X is more than or equal to 1mV and less than or equal to 10 mV.

The charging curve of the battery pack may be the last charging curve, or may be a last charging curve extracted from the last 10 charging curves and combined with the last charging curve, so that a curve including 2 characteristic value points is formed.

The method comprises the following steps of extracting a charging curve from the charging curve of the last 10 times and combining the charging curve with the last time, firstly selecting a curve which has the same charging current as the charging current of the curve of the last time and has an environmental temperature difference smaller than 5 degrees from the charging curve of the last 10 times, then selecting a curve which can be combined with the curve of the last time to form a curve comprising two characteristic value position curves from the rest curves, and if a plurality of curves meet requirements, preferentially selecting the curve with the closest environmental temperature; if the ambient temperature is the same, the most recent charging profile, i.e. the profile closest in time to the last charging, is preferably selected.

The invention has the beneficial effects that: 1. the method is applicable to the normal charging process of the battery pack, and does not influence the working input and output of the battery; 2. the method only needs to acquire the SOC-OCV curve data of the battery or a historical charging curve and the nominal capacity of the battery in advance, and does not need to additionally test battery parameters; 3. the total capacity of all the single batteries in the battery pack can be obtained in real time; 4. the total capacity of all the single batteries can be obtained without fully charging the batteries.

Drawings

FIG. 1 is a flow chart of the present invention;

FIG. 2 is a capacity increment curve for a lithium iron phosphate lithium ion battery reference curve;

FIG. 3 is a graph of capacity increase for lithium iron phosphate lithium ion battery charging data;

FIG. 4 is a capacity increment curve and d for a ternary lithium ion battery reference curve²Q/dV²A curve;

FIG. 5 is a capacity increment curve for ternary lithium ion battery charging data and d²Q/dV²A curve;

FIG. 6 is a histogram of the capacities of all the cells in the battery pack;

FIG. 7 is a graph of the error of the calculated capacity versus the true capacity of the present invention.

Detailed Description

The invention is described in detail below with reference to the figures and specific embodiments.

As shown in fig. 1, a method for rapidly obtaining the capacity of all the single batteries in a battery pack, the middle battery of the battery pack may be a lithium iron phosphate battery or a ternary material battery; the battery pack can be a battery pack system formed by connecting a plurality of battery cells in parallel and then in series. Acquiring battery reference curve data and battery nominal capacity Cap aiming at a target lithium ion battery_initial. The lithium ion battery reference curve data can be battery SOC-OCV curve data obtained from a manufacturer, and can also be historical charging curve data. The SOC-OCV curve data of the battery is obtained from a manufacturer, and the SOC value density is between 0.1% and 5%, including 0.1% and 5%. Processing curve data, extracting a characteristic value from a capacity increment curve by using a capacity increment analysis method according to the type of a battery material and taking data with SOC (State of Charge) more than 20% of the lithium iron phosphate battery, and recording a capacity Q or a charging capacity Q' corresponding to the position of the characteristic value; for ternary material battery, data with SOC greater than 20% is taken to obtain d²Q/dV²And (5) extracting a characteristic value and recording the capacity Q or the charging capacity Q' corresponding to the position of the characteristic value by a curve. Q ═ SOC Cap_initial。

Processing the data of a reference curve of the lithium iron phosphate battery, and obtaining a capacity increment curve with SOC as an abscissa, wherein the calculation formula is

Extracting a characteristic value, wherein the position of the characteristic value is the position of the maximum value in the capacity increment curve; processing the data of the reference curve of the ternary battery to obtain d with the voltage as the abscissa²Q/dV²Curve, the calculation formula is

Extracting the feature value, the position of the feature value is

The position of (a). For lithium iron phosphate or ternary batteries, in the interval of which the SOC is more than 20% and less than 100%, the characteristic values of the curves are all 2. Capacity Q for recording the 1 st eigenvalue position₁Or charging capacity Q'₁Capacity Q of the 2 nd eigenvalue position₂Or charging capacity Q'₂. Wherein: q is the battery capacity, Q' is the charge capacity, dQ is the differential of the capacity, d²Q is the second differential of the capacity, Δ Q_kIs the difference in capacity between adjacent samples, V is the voltage of the cell, dV is the differential of the voltage, dV²Is the second order differential of the voltage, Δ V_kFor the difference in voltage between adjacent samples, Δ Q for each sample point k_k＝Q_k-Q_k-1，ΔV_k＝V_k-V_k-1，ΔQ_k-1＝Q_k-1-Q_k-2，ΔV_k-1＝V_k-1-V_k-2；

Calculating the relation coefficient of the capacity and the total capacity between the characteristic values of the battery, wherein g is delta Q/Cap_initial(ii) a Where Δ Q is the capacity difference between the 1 st characteristic value and the 2 nd characteristic value, Δ Q ═ Q₂-Q₁L, |; if historical charging curve data is employed, then Δ Q ═ Q'₂-Q‘₁|。

And extracting data meeting the condition that delta V is larger than or equal to X in the charging process of the battery pack. The data includes voltage values of all single batteries, and the batteriesThe charge time of the pack and the charge capacity value of the battery pack, etc. The value range of X is more than or equal to 1mV and less than or equal to 10 mV. According to the type of a battery material, data with SOC greater than 20% are taken for the lithium iron phosphate battery, a capacity increment analysis method is utilized, a characteristic value is extracted from a capacity increment curve, and the charging capacity corresponding to the position of the characteristic value is recorded; for ternary material battery, data with SOC greater than 20% is taken to obtain d²Q/dV²And (5) a curve, extracting the characteristic value and recording the charging capacity corresponding to the position of the characteristic value. Recording charging capacity Q 'of 1 st characteristic value position of all battery curves'_1jRecording the charging capacity Q 'of the 2 nd characteristic value position of all the cell curves'_2jWherein: q_1jThe j number of the single battery capacity, Q, of the 1 st characteristic value position_2jIs the No. 2 characteristic value position j single battery capacity, Q'_1jIs the charging capacity of the monomer of No. j of the 1 st characteristic value position, Q'_2jThe charge capacity of the No. j cell at the No. 2 characteristic value position.

Calculating the capacity difference between the 1 st characteristic value and the 2 nd characteristic value of the j single battery, namely delta Q_j＝|Q_2j-Q_1j|；ΔQ_jAlso equal to the 1 st to 2 nd eigenvalue charge capacity. If a charging curve contains both the 1 st and 2 nd characteristic values, Δ Q_j＝|Q‘_2j-Q‘_1jL. If the single charging curve does not contain two characteristic value positions, the charging curve can be extracted from the charging curve of the last 10 times and combined with the last time to form a curve containing 2 characteristic value points. The two combined curves should meet the requirement that the charging current is the same and the temperature difference of the charging environment is less than 5 degrees, otherwise, the two curves are not combined.

And (3) calculating the total capacity corresponding to the j-th single battery, wherein the calculation formula is as follows:

Cap_j＝ΔQ_j/g；

and calculating the capacity of each single battery in the battery pack one by one.

Example 1:

the target lithium ion battery is a CATL lithium iron phosphate battery with a nominal capacity of Cap_initialThe battery reference curve data is SOC-OCV relationship curve data at 180Ah, and the data interval is Δ SOC of 2%. The capacity value corresponding to each OCV point is represented by the formula: q ═ SOC 180 is calculated;

obtaining a capacity increment curve of SOC-OCV relation data by adopting a five-point cubic smoothing filtering method (2 data before and after the position to be subjected to smoothing filtering are selected, the total number of the data is 5, a 3-order polynomial is adopted for fitting, and the numerical value after smoothing filtering is obtained), wherein the obtained capacity increment curve is shown as a dQ/dV point drawing line in figure 2, the figure 2 takes SOC as an abscissa, the left ordinate is battery open-circuit voltage OCV, the right ordinate is dQ/dV, the 1 st characteristic value position is an A point position in figure 2, the corresponding SOC is 55.6 percent, and the capacity Q is Q₁The 2 nd eigenvalue position in the graph is the B point position in fig. 2, corresponding to an SOC of 84.9%, at 100.08Ah, and the capacity Q₂＝152.82Ah；

Calculating a relation coefficient of capacity and total capacity between the characteristic values of the batteries:

g＝ΔQ/Cap_initial＝|Q₂-Q₁|/Cap_initial＝(152.82-100.08)/180＝0.293

the charging data condition of fig. 3 is that the battery pack performs constant current charging with a current of 0.35C, 63A until the voltage of any single battery reaches 3.6V, i.e. stops charging, and the SOC of the battery pack in the early stage of charging is 20%.

The charging data is extracted under the condition that the delta V is more than or equal to 2mV, and the voltage value and the charging electric quantity value of each single battery are extracted. Obtaining a capacity increment curve by adopting a five-point triple smoothing filter method for the voltage value and the charging electric quantity value of the battery, wherein the capacity increment curve of the No. 1 single battery in the battery pack is shown in fig. 3, the SOC is taken as an abscissa in fig. 3, the left ordinate is the battery voltage, the right ordinate is dQ/dV, the 1 st characteristic value position in the diagram is the C point position in fig. 3, and the corresponding charging capacity value is Q'₁₁67.66Ah, the 2 nd eigenvalue position in the figure is the D point position in figure 3, and the corresponding charge capacity value is Q'₂₁＝119.2Ah；

And (3) calculating the total capacity of the No. 1 single battery of the battery pack:

Cap₁＝ΔQ₁/g＝|Q‘₂₁-Q‘₁₁|/g＝(119.2-67.06)/0.293＝177.9Ah

the same calculation method calculates the total capacity of the number 2 single battery in the battery pack to the total capacity of the number 240 single battery, and draws the total capacity of all the single batteries into a histogram, and fig. 6 is a histogram of the capacity of all the single batteries in the battery pack.

And comparing the capacity value calculated by the method of the present invention with the real capacity value of the battery, the capacity error rate is shown in fig. 7, which shows that the maximum capacity error is 3.86%.

Example 2:

the target lithium ion battery is a 21700 ternary battery with nominal capacity of Cap_initialThe battery reference curve data used was SOC-OCV curve data at 4.5Ah, and the data interval was Δ SOC of 3%. The capacity value corresponding to each OCV point is represented by the formula: q ═ SOC 4.5 was calculated;

solving a capacity increment curve and d of SOC-OCV relation data by adopting a five-point three-time smoothing filtering method²Q/dV²The resulting capacity increase curve is shown in dotted dQ/dV in FIG. 4, d²Q/dV²The curve is shown by the dotted line in FIG. 4, where FIG. 4 is the open circuit voltage OCV on the abscissa, the left ordinate is the battery SOC, the right 1 st ordinate is dQ/dV, and the right 2 nd ordinate is d²Q/dV²In the figure, the 1 st eigenvalue position is the E point position in figure 4, corresponding to the SOC value of 39.8%, the capacity Q₁When the value is 1.791Ah, the 2 nd eigenvalue position in the graph is the F point position in fig. 4, corresponding to the SOC value of 76.4%, and the capacity Q₂＝3.438Ah；

g＝ΔQ/Cap_initial＝|Q²-Q₁|/Cap_initial＝(3.438-1.791)/4.5＝0.336

the target lithium ion battery is charged with a constant current of 1C and 4.5A until the voltage reaches 4.2V, and the charging is stopped, wherein the SOC of the battery pack in the early stage of charging is 15%.

The charging data is extracted under the condition that the delta V is more than or equal to 3mV, and the voltage value and the charging electric quantity value of the battery are extracted. The capacity increment curve and d are obtained by adopting a five-point triple smoothing filtering method for the voltage value and the charging electric quantity value²Q/dV²Curve, capacity increment curve of charge data of the battery and d²Q/dV²The graph is shown in FIG. 5, where FIG. 5 is the voltage on the abscissa, the left ordinate is the battery SOC, the right 1 st ordinate is dQ/dV, and the right 2 nd ordinate is d²Q/dV²Where the 1 st eigenvalue position in the figure is the H point position in figure 5, and the corresponding charge capacity value is Q'₁₁0.945Ah, the 2 nd eigenvalue position in the figure is the M point position in figure 5, and the corresponding charge capacity value is Q'₂₁＝2.601Ah；

Cap₁＝ΔQ₁/g＝|Q‘₂₁-Q‘₁₁|/g＝(2.443-0.945)/0.336＝4.46Ah

the total capacity of other single batteries in the battery pack is calculated by the same calculation method.

Example 3:

the target lithium ion battery is a soft package ternary battery of the high department of the Xuan, 15Ah is connected in series after being connected in parallel, and the nominal capacity is Cap_initialThe battery reference curve data is historical curve data, the charging current is 6A, and the data extraction condition is that delta V is more than or equal to 5 mV;

obtaining a capacity increment curve and d of historical charging curve data by adopting a five-point three-time smoothing filtering method²Q/dV²Curve, and with charging voltage as abscissa, left ordinate is battery SOC, right 1 st ordinate is dQ/dV, right 2 nd ordinate is d²Q/dV²Calculating the charging capacity Q 'corresponding to the 1 st characteristic value position'₁16.53Ah, and a charging capacity Q 'corresponding to the 2 nd characteristic value position'₂＝26.13Ah；

g＝ΔQ/Cap_initial＝|Q‘₂-Q‘₁|/Cap_initial＝(26.13-16.53)/30＝0.32

the battery pack assembled by the target lithium ion battery is formed by connecting 2 batteries and 16 batteries in series, the target lithium ion battery is charged at constant current of 0.5C and 15A until the voltage of any single battery reaches 4.2V, the charging is stopped, and the SOC of the battery pack in the early stage of charging is 13%.

The charging data is extracted under the condition that the delta V is more than or equal to 1mV, the voltage value and the charging electric quantity value of each single battery are extracted, and after the charging is finished, the data with the SOC less than 15 percent are removed. Obtaining a capacity increment curve and d by adopting a five-point triple smoothing filtering method for the voltage value and the charging electric quantity value of each single battery²Q/dV²Recording the charging capacity value of the 1 st characteristic value position and the charging capacity value of the 2 nd characteristic value position of each single battery, wherein the 1 st characteristic value position of the No. 1 single battery corresponds to the charging capacity value of Q'₁₁0.945Ah, and the charge capacity value corresponding to the 2 nd unique value position is Q'₂₁＝2.601Ah；

And (3) calculating the total capacity of the No. 1 single battery in the battery pack:

Cap₁＝ΔQ₁/g＝|Q‘₂₁-Q‘₁₁|/g＝(21.56-11.576)/0.32＝31.2Ah

the total capacity from the No. 2 single battery to the No. 16 single battery in the battery pack is calculated by the same calculation method.

Example 4:

embodiment 4 is similar to embodiment 3, except that, when processing the charging curve, the single charging curve does not include two characteristic value positions, so the charging curve is extracted from the charging curve of the last 10 times and combined with the last time to form a curve including 2 characteristic value points. Firstly, selecting a curve which is the same as the charging current of the last curve in the last 10 charging curves and has the difference of the environmental temperature less than 5 degrees, selecting a curve which can be combined into a curve containing two characteristic value position curves from the last curve, and preferentially selecting the curve with the closest environmental temperature if a plurality of curves meet the requirement; if the ambient temperature is the same, the most recent charging profile (i.e., the profile closest in time to the last charge) is preferably selected. The data extraction conditions may be data for conditions where Δ V is greater than or equal to 10 mV. And calculating the capacity of the single batteries in the battery pack one by using the formula.

The foregoing shows and describes the general principles and broad features of the present invention and advantages thereof. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.

Claims

1. a method for quickly obtaining the capacity of all single cells in the battery pack, characterized in that: comprise the steps:

S1. For the target lithium-ion battery, obtain battery reference curve data and battery nominal capacity Cap _initial ;

S2. Process the reference curve data of the lithium-ion battery, and record the capacity or charging capacity of the battery at the eigenvalue position;

S3. Calculate the relationship coefficient between the battery eigenvalues and the total capacity;

S4. Process the charging curve of the battery pack, and record the charging capacity of the battery at the eigenvalue position;

S5. Calculate the capacity between the battery characteristic values obtained in step S4, and calculate the capacity of all single cells in the battery pack one by one according to the relationship coefficient described in step S3,

In the step S2, the reference curve data of the lithium-ion battery is processed, and the capacity or charging capacity of the battery at the eigenvalue position is recorded: according to the type of battery material, for the lithium iron phosphate battery, the data whose SOC is greater than 20% are obtained, and the SOC is obtained. is the capacity increment curve of the abscissa, and the calculation formula is

Extract the eigenvalue, the position of the eigenvalue is the maximum value position in the capacity increment curve, and record the capacity Q or charging capacity Q′ corresponding to the position of the eigenvalue; for the ternary material battery, take the data with SOC greater than 20% to obtain The d ² Q/dV ² curve with the voltage as the abscissa, the formula is

Extract eigenvalues, the eigenvalue positions are

position, and record the capacity Q or charging capacity Q′ corresponding to the eigenvalue position; Q=SOC*Cap _initial ;

Among them: Q is the capacity of the battery, Q' is the charging capacity, dQ is the differential of the capacity, d ² Q is the second-order differential of the capacity, ΔQ _k is the difference of the capacity between adjacent sampling points, V is the voltage of the battery, dV is the differential of the voltage, dV ² is the second-order differential of the voltage, ΔV _k is the difference between the voltages between adjacent sampling points, for each sampling point k, ΔQ _k =Q _k -Q _k-1 , ΔV _k =V _k -V _k-1 , ΔQ _k-1 =Q _k-1 -Q _k-2 , ΔV _k-1 =V _k-1 -V _k-2 ,

The battery reference curve has two eigenvalues, namely the first eigenvalue and the second eigenvalue, record the capacity Q ₁ or charging capacity Q' ₁ at the position of the first eigenvalue, and the capacity Q at the position of the second eigenvalue ₂ or charging capacity Q' ₂ ,

In the step S3, the relationship coefficient g=ΔQ/Cap _initial between the capacity and the total capacity of the battery eigenvalues is calculated; wherein ΔQ is the capacity difference between the first eigenvalue and the second eigenvalue, ΔQ=|Q ₂ -Q ₁ |; If historical charging curve data is used, then ΔQ=|Q' ₂ -Q' ₁ |.

2. A method for quickly obtaining the capacity of all single cells in a battery pack according to claim 1, wherein the battery reference curve data in the step S1 is obtained from the manufacturer of the battery SOC-OCV curve data , or historical charging curve data.

3. The method for quickly obtaining the capacity of all single cells in the battery pack as claimed in claim 1, wherein the step S4 processes the charging curve of the battery pack, and the battery charging capacity at the record characteristic value position is specifically: Extract the data that satisfies the condition of ΔV≥X during the charging process of the battery pack. According to the type of battery material, for lithium iron phosphate batteries, take the data whose SOC is greater than 20%, and use the capacity increment analysis method to calculate the capacity increment with SOC as the abscissa. Extract the eigenvalue from the curve, and record the charging capacity corresponding to the position of the eigenvalue; for the ternary material battery, take the data with SOC greater than 20% to obtain the d ² Q/dV ² curve with the voltage as the abscissa, extract the eigenvalue, and record The charging capacity corresponding to the eigenvalue position; the charging capacity corresponding to the eigenvalue includes the charging capacity Q' _1j at the first eigenvalue position and the charging capacity Q' _2j at the second eigenvalue position, where: Q _1j is the first characteristic Value position jth single battery capacity, Q _2j is the second eigenvalue position jth single battery capacity, Q' _1j is the first eigenvalue position jth single battery charging capacity, Q' _2j is the jth single battery capacity The charging capacity of the jth monomer at the 2 eigenvalue positions.

4. A method for quickly obtaining the capacity of all single cells in a battery pack as claimed in claim 3, wherein the step S5 calculates the capacity between the battery characteristic values obtained in the step S4, and calculates the capacity according to the step S3. Calculate the capacity of all single cells in the battery pack one by one using the relationship coefficient mentioned above. Specifically: Calculate the capacity difference between the first eigenvalue and the second eigenvalue of the jth single cell, ΔQ _j =|Q _2j -Q _1j |=|Q' _2j -Q' _1j |, then according to the formula Cap _j =ΔQ _j /g to obtain the capacity of the jth single battery, and then calculate the capacity of other single batteries in the battery pack one by one; among them, Cap _j is the capacity of the jth single battery, and g is the relationship coefficient between the capacity and the total capacity between the battery characteristic values obtained in claim 1.

5 . The method for quickly obtaining the capacity of all cells in a battery pack according to claim 3 , wherein the value range of X is 1mV≦X≦10mV. 6 .

6. A method for quickly obtaining the capacity of all single cells in a battery pack according to claim 3, wherein the charging curve of the battery pack is the most recent charging curve, or one of the most recent 10 charging curves The extracted charging curve is combined with the most recent one to make it a curve containing 2 eigenvalue points.

7. A method for quickly obtaining the capacity of all single cells in a battery pack as claimed in claim 6, wherein the charging curve extracted from the most recent 10 charging curves is combined with the most recent one, and the most recent charging curve is selected first. Among the 10 charging curves, the charging current is the same as that of the latest curve and the difference in ambient temperature is less than 5 degrees. From the remaining curves, select the curve which is combined with the most recent curve to form a curve containing two eigenvalue position curves. If the curve meets the requirements, select the one with the closest ambient temperature; if the ambient temperature is the same, select the latest charging curve, that is, the curve closest to the last charging in time.