CN117172028A

CN117172028A - Efficient balance calculation method based on lithium iron phosphate cell unbalance model

Info

Publication number: CN117172028A
Application number: CN202311273581.1A
Authority: CN
Inventors: 杨麒麟; 俞峰; 刘斌生; 杨庆宏; 邓通杭
Original assignee: Fujian Scud Power Technology Co Ltd
Current assignee: Fujian Scud Power Technology Co Ltd
Priority date: 2023-09-28
Filing date: 2023-09-28
Publication date: 2023-12-05

Abstract

The invention discloses a high-efficiency balance calculation method based on a lithium iron phosphate cell unbalance model. A plurality of battery packs are connected in series, and the capacities of the batteries in the battery packs are distributed according to the actual situation; analyzing the reason of unbalance of the batteries in the battery pack based on the capacity allocation of each battery; based on the analysis result of the cell unbalance reason, estimating the real-time total discharge capacity of the battery cell; based on estimation and adjustment, single-section discharge equalization is carried out when the discharge capacity difference of different battery cells is large; so as to achieve the balance of the total discharge quantity of each battery and realize the simultaneous filling of each battery in the battery pack. According to the invention, through introducing an unbalance model of the lithium iron phosphate battery core, each battery core is estimated, the unbalanced battery core can be balanced when the capacity is more than 30%, and the battery core is balanced in full time when the battery core is charged, and the battery core has extremely high balance efficiency when the battery core is discharged and is idle. The discharge capacity of the lithium iron phosphate battery pack is greatly improved.

Description

Efficient balance calculation method based on lithium iron phosphate cell unbalance model

Technical Field

The invention belongs to the field of batteries, and particularly relates to a high-efficiency balance calculation method based on a lithium iron phosphate cell unbalance model.

Background

The lithium ion battery pack is generally formed by connecting a plurality of small-capacity single battery cells in parallel and then expanding the battery cells to target capacity, connecting the battery cells in series to required high voltage to form a high-voltage high-capacity module, and adding the BMS and a corresponding structure to form the lithium ion battery pack. The individual cells may have an inconsistent capacity, inconsistent self-current consumption, or unbalanced cell strings caused by inconsistent leakage current per BMS section. This imbalance may result in insufficient discharge capacity of the battery pack during charge and discharge. At this time, the BMS is required to control the balancing circuit to perform balancing, and the unbalanced cells are pulled to a balanced state. The equalization generally adopts passive discharge, and an equalization circuit among the battery cells is controlled to carry out passive discharge of the single battery, so that the battery with higher voltage is independently discharged to be consistent with other battery cells. And then charging is carried out, and finally, all the battery cells are uniformly filled, so that the maximum dischargeable capacity is achieved. The non-uniform cells are all filled to the primary goal of equalization.

The prior art generally adopts voltage equalization in the standing or charging process, such as ternary cell voltage >3.8V voltage difference >50mV start equalization and <20mV stop equalization. The lithium iron phosphate battery cell generally adopts a battery cell voltage of >3.4V, a voltage difference of >50mV for starting equalization, and a voltage difference of <20mV for stopping equalization. The balancing mode has a certain effect on the ternary battery cell, because the voltage for balancing starting is 3.8V, the corresponding SOC is not more than 70%, and longer balancing time is provided, but if the lithium iron phosphate is too smooth because the middle curve, referring to fig. 1, when the lithium iron phosphate is below 98 capacity, the voltage is almost stable, the balancing can not be performed in the interval through the voltage, the electric quantity exceeding 3.4V is more than 99%, the balancing is performed for a small section of capacity, the balancing can not be performed continuously, the balancing interval and time are too short, meanwhile, for some products with very high operation speed such as a battery replacement market, the battery is taken out to be continuously put into the market for operation when the battery is always full or close to full, the effective balancing time is very short, the balancing effect is very poor, and the capacity of the battery pack can not be fully released after long-term use. Aiming at the defects, the invention mainly solves the problems that only the tail end is balanced during balancing, the time is short, and the balancing effect is poor,

disclosure of Invention

The invention provides a high-efficiency equalization calculation method based on an unbalance model of a lithium iron phosphate battery cell, which is characterized in that the unbalance model of the lithium iron phosphate battery cell is introduced to estimate the capacity, charging and discharging current, self-power consumption and the like of each battery cell, so that the unbalanced battery cell can be equalized when the capacity is more than 30 percent, and the battery cell can be fully equalized when the battery cell is charged, and the battery cell has extremely high equalization efficiency when the battery cell is discharged and is idle. The discharge capacity of the lithium iron phosphate battery pack is greatly improved.

The invention is realized by the following technical scheme:

an efficient balance calculation method based on a lithium iron phosphate cell unbalance model comprises the following steps:

step 1: a plurality of battery packs are connected in series, and the capacities of the batteries in the battery packs are distributed according to the actual situation;

step 2: analyzing the reason of unbalance of the batteries in the battery pack based on the capacity allocation of each battery in the step 1;

step 3: based on the analysis result of the cell unbalance reason in the step 2, estimating the real-time total discharge capacity of the battery cell;

step 4: based on the estimation adjustment in the step 3, single-section discharge equalization is carried out when the discharge capacity difference of different electric cores is large; so as to achieve the balance of the total discharge quantity of each battery and realize the simultaneous filling of each battery in the battery pack.

Further, in the step 1, specifically, the first battery in the battery pack is the base capacity, and the two batteries Bao Nadi are 3% more electric quantity than the battery with the lowest capacity in the battery pack; the third cell in the pack was 5% more charged than the lowest capacity cell of the pack.

Further, the reason for unbalance of the battery in the battery pack in the step 2 is specifically that,

the single battery cells assembled into the battery pack have the capacity difference of the battery cells;

the battery pack is continuously used, and different attenuation degrees of different capacities of the battery cells can appear.

Further, the reason for the unbalance of the battery in the battery pack in the step 2 further includes uneven self-power consumption of the battery cells.

Further, the reason for the unbalance of the battery in the battery pack in the step 2 further includes that the current power consumption of the single cell on the BMS board is inconsistent.

Further, the step 3 is to estimate the real-time total discharge capacity of the battery cell in real time by estimating the full capacity of each section of single body, and simultaneously estimating the charge and discharge accumulated current, the self-consumption current of each battery cell in real time, and performing coulomb accumulation on the two currents.

Further, the step 3 is to estimate the real-time total discharge capacity of the battery cell specifically,

step 3.1: setting an initial value of a full capacity value AFCCx of each battery cell;

step 3.2: setting an initial value of a self-consumption current value I (K) x of each battery cell;

step 3.3: setting an initial value of accumulated charge-discharge capacity QC (CD) x of each battery cell;

step 3.4: based on the initial value of the I (K) x set in the step 3.2 and the initial value of the QC (CD) x set in the step 3.3, after the software is operated, the QC (CD) x and the QC (Ik) x are accumulated with real-time working parameters;

step 3.5: based on the accumulation of the working parameters in the step 3.4, carrying out equalization by adopting an SOC algorithm;

step 3.6: when AFCCx and I (K) x of the single cell change continuously along with the degradation cycle of the cell, the AFCCx and I (K) x also perform real-time tracking calibration.

Further, the step 3.5 of balancing using the SOC algorithm is specifically that when the total SOC of the battery pack is greater than 30% and the maximum QCx-arbitrary QCx is greater than 2% of the AFCC of the total battery, the string of battery cells exceeding the parameter needs to be balanced, and meanwhile, I (band) x is calculated during balancing, and meanwhile, the value of QC (CD) x accumulated to QC (ibaance) x is also increased continuously until the equation is not satisfied, and balancing is stopped.

Further, in the step 3.6, the AFCCx real-time tracking calibration specifically includes that if enough time exists before charging, standing to obtain the OCV, and meanwhile, the OCV is also in one of three intervals, if the OCV is considered to be valid, software obtains the corresponding SOCx1 according to the OCV/SOC table, records the QC (CD) x1 at the moment, enters the charging process, and then stops;

if the OCV after charging can be obtained as well, and the OCV also falls in any one of the three sections, the OCV is considered to be valid, and software obtains the corresponding SOCx2 according to the OCV/SOC table and records QC (CD) x2 at the moment;

if SOCx2-SOCx1>30%, then it is considered that real-time calibration is possible;

the calibration formula is given by the following formula,

AFCCx calibration = Δqc (CD)/Δsoc= (QC (CD) x1-QC (CD) x 2)/(SOCx 2-SOCx 1);

the three intervals are interval 1: SOC 0% -26%;

interval 2: SOC 58-62%;

region 3: SOC 98-100%.

Further, the real-time tracking calibration of I (K) x in step 3.6 is specifically that the OCV calibration will obtain the corresponding SOCx, at which time QCx can be calculated,

QCx＝AFCC*(100％-SOCx)；

QCx＝QC(CD)x+QC(Ik)x，

wherein QC (CD) x is the exact discharge capacity accumulation, QCx also gets calibrated;

can be pushed out

QC(Ik)x1＝QCx-QC(CD)x

And records the QC (Ik) x1, and clears the cumulative run time of QC (Ik) x to 0, i.e. T (Ik) x=0,

continuing to run if a second OCV calibration is obtained, T (Ik) x >48 hours,

the corresponding QC (Ik) x2 can be deduced using calibration,

(QC (Ik) x2-QC (Ik) x 1) to obtain accumulated DeltaQC (Ik) x in unit time,

differentiating DeltaQC (Ik) x to obtain

I (K) x calibration = dΔqc (Ik) x/dT (Ik) x;

after the calibration is finished, T (Ik) x is clear of 0, accumulation is carried out again, the current I (K) x is recorded and calibrated to be QC (Ik) x1, and the next round of calibration links is carried out.

The beneficial effects of the invention are as follows:

1. the equalization algorithm is modeled based on the imbalance cause of the lithium iron phosphate battery. The reasons for imbalance include single-segment capacity non-uniformity and single-segment power consumption non-uniformity.

2. The invention carries out software modeling on each single battery cell to introduce single battery cell capacity AFCCx, single battery cell leakage I (K) x parameters, single battery cell total charge-discharge capacity QC (CD) x and single battery cell total leakage capacity QC (Ik) x parameters. The single total charge-discharge capacity QC (CD) x includes a capacity formed by charge-discharge of the battery pack, a single equilibrium capacity, and a capacity of BMS power consumption.

3. The invention uses a software algorithm real-time operation flow on the basis of 1 to perform cumulative calculation on the charge-discharge capacity QC (CD) x and the self-consumption capacity QC (Ik) x of the monomer, wherein QCx =QC (CD) x+QC (Ik) x, and real-time equalization is performed on the monomer which satisfies the total SOC of more than 30% and the largest QCx-any QCx of more than 2% of total AFCC.

4. According to the invention, on the basis of 2, real-time calibration is carried out on AFCCx, lithium iron phosphate OCV is divided into 3 sections of platforms, and when two OCV calibrations meeting the flow of FIG. 5 and meeting delta SOC >30%, real-time degradation calibration of AFCCx is carried out, and a calibration formula AFCCx calibrates= (QC (CD) x1-QC (CD) x 2)/(SOCx 2-SOCx 1). Long-term tracking of AFCCx degradation due to battery cycling.

5. The invention carries out real-time calibration on I (K) x on the basis of 2, and carries out calibration conforming to the flow of figure 6. The formula I (K) x calibration = d (QC (Ik) x2-QC (Ik) x 1)/dT (Ik) x. The I (K) x degradation due to battery cycling is tracked over time.

6. The invention can greatly improve the balance efficiency of the lithium iron phosphate battery, and can balance the lithium iron phosphate battery in real time after the electric quantity is more than 30%, ensure consistency filling, reduce charging time, improve the discharge capacity of the battery and prolong the cycle life of the battery.

Drawings

FIG. 1 is a schematic diagram of the comparison of the cell SOC voltage with the cell OCV voltage of the present invention.

Fig. 2 is an explanatory diagram of the cause of unbalance of the battery pack analyzed by the present invention.

Fig. 3 is a schematic diagram of the voltage variation interval of the lithium iron phosphate according to the present invention.

Fig. 4 is a flow chart of the method of the present invention.

Fig. 5 is an AFCCx calibration flow chart of the present invention.

FIG. 6 is a flow chart of the I (K) x calibration of the present invention.

Detailed Description

The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

The AFCC is: the battery charged according to the standard condition (standard temperature, voltage, current) and discharged according to the standard condition (standard temperature, voltage, current) has the capacity which is the standard capacity of the battery. This standard capacity is referred to herein as AFCC (Absolute Full Charge Capacity).

AFCCx is the full capacity of a single cell, where x represents the corresponding cell, e.g. AFCC1 represents the absolute full capacity of the first string of cells

SOC is the percentage of total charge of the battery pack.

SOCx is the percentage of charge of a single string of cells in the battery pack.

I (K) in I (K) x represents the self-consumption current of the battery cell, and comprises the sum of the self-discharge current of the battery cell and the single-section power consumption of the BMS. I (K) x represents the sum of the self-consumed currents of a single cell.

I (BMS) is the total operational power consumption of the BMS, including the operational power consumption values in the respective modes.

I (balance) x is an equilibrium current value of a single BMS, I (balance) x=current battery voltage/equilibrium resistance in actual operation

QC (Ibms) is the coulomb integral of the total discharge current of the BMS operation. I.e., QC (Ibms) = ≡ti (bms). When the battery cell is full, the parameter is cleared to 0, and the rest is accumulated forward.

QC (ibaance) x is the coulomb integral of the single-node total equilibrium current of the BMS. Namely QC (ibaance) x= ≡ti (balance) x. When the battery cell is full, the parameter is cleared to 0, and the rest is accumulated forward.

QC (CD) x represents the total charge-discharge current accumulated by a single battery (positive discharge current and negative charge current), the total power consumption current of BMS, and the integrated coulomb of the current of cell equalization, in mAh. QC (CD) x=total charge-discharge current accumulation capacity+qc (Ibms) +qc (ibalan) x. When the battery cell is full, the parameter is cleared to 0, and the rest is accumulated forward.

QC (K) x in QC (Ik) x is the accumulated capacity of the self-consumed current of a single battery, and the unit is mAh. QC (Ik) x is positive. I.e., QC (ibaance) = ≡ti (K) x. When the battery cell is full, the parameter is cleared to 0, and the rest is accumulated forward.

QCx is the total coulomb summation of the electric quantities of the single batteries. Accumulating the current in unit time to finally form capacity, wherein the unit is mAh. Positive accumulation is carried out during discharging, and negative accumulation is carried out during charging. QCx has a value of 0 at full power and a maximum value of AFCCx at empty. QCx =qc (CD) x+qc (Ik) x. The total discharging coulombs comprise charging and discharging electric coulombs, the electric coulombs of BMS working current, the electric coulombs of balanced current and the electric coulombs of single-energy self-consumption coulombs. This value represents the accumulation of all the consumed power of the battery after being full.

An example of a battery pack having a rated capacity of 10Ah and a rated voltage of 9.6V was used, and it was assumed that the battery pack was formed by connecting 3 lithium iron phosphate batteries having a rated capacity of 10Ah in series. The actual capacity of the first string of cells is 10Ah, the actual capacity of the second string of cells is 10.3Ah (3% more power than the lowest capacity cell of the present battery pack), and the actual capacity of the third string of cells is 10.5Ah (5% more power than the lowest capacity cell of the present battery pack).

the single battery cells assembled into the battery pack have the capacity difference of the battery cells; in the above example, the first string of low-capacity cells is preferably charged to 3.4V or more, and the other cells are in the capacity plateau region of 3.34V or less. Unbalance occurs at this time;

the battery pack is continuously used, and different battery cores can have different attenuation degrees of capacity; for example, lithium iron phosphate typically has a capacity of 2000 cycles decaying to less than 80%, and there may be cases where cell 1 decays to 80% and cell 2 decays to 85%, resulting in an increase in the capacity imbalance during use.

Further, the reason for the unbalance of the battery in the battery pack in the step 2 further includes uneven self-power consumption of the battery cells. The battery core can also generate self-power consumption when the battery core is not used in static storage, so that the capacity is reduced, the self-power consumption current is inconsistent due to the fact that different battery cores cannot be completely consistent in production and manufacturing, and the residual capacity is different after long-term storage. The greater the difference in self-power consumption levels can lead to increasingly severe cell imbalances after prolonged storage. The battery cells after continuous cyclic use have different self-consumption levels because of different use environments (positions where the battery packs are not connected, different heating levels and the like), and the self-consumption parameters can be unchanged and offset along with use.

Further, the reason for the unbalance of the battery in the battery pack in the step 2 further includes that the current power consumption of the single cell on the BMS board is inconsistent. The BMS needs to collect the voltage of each battery, and if there is inconsistent power consumption on the board, the remaining capacity of the battery will be inconsistent for a long time, and finally unbalance will be caused. This degree of difference in power consumption is controlled at the time of BMS design, but there is still a certain difference. The unbalance is also the increase of the power consumption of a single battery cell, and the parameter is classified into the power consumption parameters of the battery cell for simplifying a software model.

step 3.1: setting an initial value of a full capacity value AFCCx of each battery cell; the default value of the parameter may be extracted from data provided by the cell manufacturer. The battery cell manufacturer has the associated production aging capacity record of each battery cell, and the full capacity of each battery cell can be written into the software by an automatic means during production;

step 3.2: setting an initial value of a self-consumption current value I (K) x of each battery cell; the numerical value can be calculated through a long-term standing experiment of the battery cell, or a fixed reasonable estimated value is written in, and software can be corrected in real time in actual operation;

step 3.3: setting an initial value of accumulated charge-discharge capacity QC (CD) x of each battery cell; this value is the full capacity value of the cell-the factory capacity value, i.e. QC (CD) x=afccx-the factory capacity. The factory capacity is the equivalent capacity value of the battery cell manufacturer charged in the completely emptied battery. If the battery cell is stored for a long time after leaving the factory, the self-consumption capacitance can be deducted according to the self-consumption K value parameter, and then the value is written into QC (CD) x. The value is a discharge capacity value from a full power state;

step 3.4: the I (bms) value of the software is a plurality of groups of fixed values, the power consumption value under each mode is tested in the development process, and real-time working parameter accumulation is carried out on QC (CD) x and QC (Ik) x after the software is operated based on the I (K) x initial value set in the step 3.2 and the QC (CD) x initial value set in the step 3.3;

step 3.6: with continuous cyclic use, AFCCx and I (K) x perform real-time tracking calibration when AFCCx and I (K) x of the single cell also change continuously along with the degradation cycle of the cell. Referring to fig. 3, although the overall OCV curve of lithium iron phosphate is relatively smooth, there are three distinct voltage variation intervals, interval 1 in this example: the corresponding voltage range of SOC 0% -26% is 3140 mV-3273 mV, the voltage change amplitude is 133mV, and the corresponding accurate SOC can be found out by using an OCV table look-up method in the range. The voltage range of 58-62% of SOC 2 ranges from 3317mV to 3296mV, and the variation amplitude is 21mV. It is sufficient to use an OCV lookup table to find the corresponding precise SOC in this interval. The region 3SOC 98% -100% corresponds to a voltage range of 3331 mV-3431 mV with a conversion amplitude of 100mV, which is sufficient to use OCV table look-up to find the corresponding exact SOCx.

Further, the step 3.5 of balancing using the SOC algorithm is specifically that when the total SOC of the battery pack is greater than 30% and the maximum QCx-arbitrary QCx is greater than 2% of the AFCC of the total battery, the string of battery cells exceeding the parameter needs to be balanced, and meanwhile, I (band) x is calculated during balancing, and meanwhile, the value of QC (CD) x accumulated to QC (ibaance) x is also increased continuously until the equation is not satisfied, and balancing is stopped. The equalization is not limited by charge and discharge conditions; since no error is avoided when the parameter calculation is accumulated, 2% calculation error is reserved. The unbalance of more than 2% can be balanced in real time and high efficiency, the balance within 2% is realized by the single-string cell voltage of the traditional mode of >3.4V, and the balance is started after the voltage difference (the cell voltage exceeding 3.4V-the lowest cell voltage) exceeds 20mV, and the time required by the end balance can be greatly shortened because the unbalance is greatly reduced when the battery is not fully charged, so that all the cells can be fully charged uniformly.

Furthermore, in the step 3.6, the AFCCx real-time tracking calibration is specifically performed during the charging process, so as to ensure the calibration accuracy, and the charging current during the charging process is more stable and more continuous than that during the discharging process. If enough time is left for standing (generally more than 15 min) before charging to acquire OCV, and the OCV is also in one of the three intervals as shown in FIG. 3, the OCV is considered to be valid, software acquires corresponding SOCx1 according to an OCV/SOC table, records QC (CD) x1 at the moment, enters a charging process, and then stops;

the calibration formula is given by the following formula,

AFCCx calibration = Δqc (CD)/Δsoc= (QC (CD) x1-QC (CD) x 2)/(SOCx 2-SOCx 1);

the three intervals are interval 1: the corresponding voltage range of SOC 0% -26% is 3140 mV-3273 mV, the voltage change amplitude is 133mV, and the corresponding accurate SOC can be detected by using an OCV table look-up method in the interval;

interval 2: the voltage range of 58-62% of SOC is 3317 mV-3296 mV, and the variation range is 21mV. The corresponding accurate SOC is sufficiently detected by using an OCV table look-up method in the interval;

region 3: SOC 98% -100% corresponds to voltage range 3331 mV-3431 mV, the conversion amplitude is 100mV, and the corresponding accurate SOCx can be found out by using OCV table look-up method in the interval.

QCx＝AFCC*(100％-SOCx)；

QCx＝QC(CD)x+QC(Ik)x，

can be pushed out

QC(Ik)x1＝QCx-QC(CD)x

continuing to run if a second OCV calibration is obtained, T (Ik) x >48 hours,

the corresponding QC (Ik) x2 can be deduced using calibration,

(QC (Ik) x2-QC (Ik) x 1) to obtain accumulated DeltaQC (Ik) x in unit time,

differentiating DeltaQC (Ik) x to obtain

I (K) x calibration = dΔqc (Ik) x/dT (Ik) x;

Note in particular that between two calibrations, or when an overfill conductance occurs before calibration has been obtained, causing QCx, QC (CD) x, QC (Ik) x to clear 0, QC (Ik) x1, QC (Ik) x2, T (Ik) x should also clear 0, restarting the corrective procedure.

The change of I (K) x in the time course is slow, the newly calibrated I (K) x can be subjected to expanding accumulation time of accumulated QC (Ik) x in the software processing process, and meanwhile, the method of limiting the change amplitude and the average value of a plurality of times can be adopted for the obtained results, so that the accuracy and the reliability of the calibration are ensured.

An efficient balance computing system based on a lithium iron phosphate cell unbalance model, which uses the efficient balance computing system based on the lithium iron phosphate cell unbalance model, and comprises an estimation module and a calculation control module;

the estimation module is used for estimating the real-time total discharge capacity of the battery core based on the analysis result of the battery unbalance reason;

the calculation control module is used for carrying out single-section discharge equalization when the discharge capacity difference of different electric cores is large based on the estimation adjustment of the estimation module; so as to achieve the balance of the total discharge quantity of each battery and realize the simultaneous filling of each battery in the battery pack.

Claims

1. The efficient balance calculation method based on the lithium iron phosphate cell unbalance model is characterized by comprising the following steps of:

2. The method for efficient balance calculation based on lithium iron phosphate cell unbalance model according to claim 1, wherein in the step 1, a first battery in a battery pack is a base capacity, and two batteries Bao Nadi are 3% more than a battery with the lowest capacity in the battery pack; the third cell in the pack was 5% more charged than the lowest capacity cell of the pack.

3. The method for efficient balance calculation based on lithium iron phosphate cell unbalance model of claim 1, wherein the reason for the unbalance of the battery in the battery pack in step 2 is specifically,

4. The efficient balance calculation method based on the lithium iron phosphate cell unbalance model of claim 1, wherein the step 2 further comprises the step of causing the cell unbalance in the battery pack to have uneven power consumption of the cell.

5. The efficient balance calculation method based on the lithium iron phosphate cell unbalance model of claim 1, wherein the step 2 further includes that the current power consumption of a single cell on a BMS board is inconsistent for the reason of the cell unbalance in the battery pack.

6. The method for efficient balance calculation based on lithium iron phosphate cell unbalance model according to claim 1, wherein the step 3 is to estimate the real-time total discharge capacity of the cell by estimating the full capacity of each cell in real time, and simultaneously estimating the charge-discharge accumulated current, the self-consumed current of each cell in real time, and performing coulomb accumulation on the two currents.

7. The method of claim 6, wherein the step 3 is implemented to estimate the real-time total discharge capacity of the battery cell specifically,

8. The efficient equalization calculation method based on the lithium iron phosphate cell imbalance model according to claim 7, wherein the step 3.5 adopts the SOC algorithm to perform equalization, specifically, when the total SOC of the battery pack is greater than 30%, and the maximum QCx-arbitrary QCx is greater than 2% of the AFCC of the total battery, the string of cells exceeding the parameter needs to perform equalization, and at the same time, calculate I (band) x, and at the same time, the value of QC (CD) x accumulated to QC (Ibalance) x will also increase continuously until the equation is not satisfied, and the equalization is stopped.

9. The method of claim 7, wherein the real-time AFCCx tracking calibration in step 3.6 is specifically that if enough time is allowed to stand for obtaining OCV before charging, and the OCV is also in one of three intervals, the OCV is considered to be valid, the software obtains the corresponding SOCx1 according to the OCV/SOC table, records the QC (CD) x1 at the moment, enters the charging process, and then stops;

the calibration formula is given by the following formula,

AFCCx calibration = Δqc (CD)/Δsoc= (QC (CD) x1-QC (CD) x 2)/(SOCx 2-SOCx 1); the three intervals are interval 1: SOC 0% -26%;

interval 2: SOC 58-62%;

region 3: SOC 98-100%.

10. The method for efficient balance calculation based on lithium iron phosphate cell unbalance model according to claim 7, wherein the real-time tracking calibration of I (K) x in step 3.6 is specifically that the OCV calibration will obtain the corresponding SOCx, at which time QCx can be calculated,

QCx＝AFCC*(100％-SOCx)；

QCx＝QC(CD)x+QC(Ik)x，

can be pushed out

QC(Ik)x1＝QCx-QC(CD)x

continuing to run if a second OCV calibration is obtained, T (Ik) x >48 hours,

the corresponding QC (Ik) x2 can be deduced using calibration,

(QC (Ik) x2-QC (Ik) x 1) to obtain accumulated DeltaQC (Ik) x in unit time,

differentiating DeltaQC (Ik) x to obtain

I (K) x calibration = dΔqc (Ik) x/dT (Ik) x;