CN113206508A - Prediction-based active equalization method for energy storage battery of micro-grid - Google Patents

Prediction-based active equalization method for energy storage battery of micro-grid Download PDF

Info

Publication number
CN113206508A
CN113206508A CN202110438917.XA CN202110438917A CN113206508A CN 113206508 A CN113206508 A CN 113206508A CN 202110438917 A CN202110438917 A CN 202110438917A CN 113206508 A CN113206508 A CN 113206508A
Authority
CN
China
Prior art keywords
battery
battery pack
grid
micro
calculating
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202110438917.XA
Other languages
Chinese (zh)
Inventor
孔江涛
于世超
孙海宁
王聪聪
王欣
刘少波
巩志伟
王建
焦可清
任昆
李玉峰
杨天佳
武翔洋
王震
韩雪飞
谷旭阳
李昱龙
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Shijiazhuang Kelin Electric Co Ltd
Original Assignee
Shijiazhuang Kelin Electric Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Shijiazhuang Kelin Electric Co Ltd filed Critical Shijiazhuang Kelin Electric Co Ltd
Priority to CN202110438917.XA priority Critical patent/CN113206508A/en
Publication of CN113206508A publication Critical patent/CN113206508A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/28—Arrangements for balancing of the load in a network by storage of energy
    • H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/371—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC] with remote indication, e.g. on external chargers
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/385—Arrangements for measuring battery or accumulator variables
    • G01R31/387—Determining ampere-hour charge capacity or SoC
    • G01R31/388—Determining ampere-hour charge capacity or SoC involving voltage measurements
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/389—Measuring internal impedance, internal conductance or related variables
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/396—Acquisition or processing of data for testing or for monitoring individual cells or groups of cells within a battery
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
    • H02J7/0013—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries acting upon several batteries simultaneously or sequentially
    • H02J7/0014—Circuits for equalisation of charge between batteries
    • H02J7/0016—Circuits for equalisation of charge between batteries using shunting, discharge or bypass circuits
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
    • H02J7/0013—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries acting upon several batteries simultaneously or sequentially
    • H02J7/0014—Circuits for equalisation of charge between batteries
    • H02J7/0019—Circuits for equalisation of charge between batteries using switched or multiplexed charge circuits
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
    • H02J7/0068—Battery or charger load switching, e.g. concurrent charging and load supply
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
    • H02J7/007—Regulation of charging or discharging current or voltage
    • H02J7/00712—Regulation of charging or discharging current or voltage the cycle being controlled or terminated in response to electric parameters
    • H02J7/00714—Regulation of charging or discharging current or voltage the cycle being controlled or terminated in response to electric parameters in response to battery charging or discharging current
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
    • H02J7/007—Regulation of charging or discharging current or voltage
    • H02J7/00712—Regulation of charging or discharging current or voltage the cycle being controlled or terminated in response to electric parameters
    • H02J7/007182—Regulation of charging or discharging current or voltage the cycle being controlled or terminated in response to electric parameters in response to battery voltage

Landscapes

  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Charge And Discharge Circuits For Batteries Or The Like (AREA)

Abstract

A prediction-based active balancing method for a micro-grid energy storage battery pack relates to the battery management technology, in particular to management of the energy storage battery pack of a micro-grid, and particularly relates to a prediction-based active balancing method for the micro-grid energy storage battery pack. By adopting the method and the device, the impending state is predicted, the balance environment is prepared in advance, and when the next time period is reached, the charging and discharging current is set according to the specific parameters of each battery cell, so that accurate and active balance is realized.

Description

Prediction-based active equalization method for energy storage battery of micro-grid
Technical Field
The invention relates to a battery management technology, in particular to management of an energy storage battery pack of a microgrid, and particularly relates to a method for actively balancing the energy storage battery pack of the microgrid based on prediction.
Background
The energy storage battery is an important component of the micro-grid, the service life of the energy storage battery is an important factor for restricting the development of the micro-grid, and how to prolong the service life of the energy storage battery is a difficult problem.
In the prior art, a management method of passive equalization is mostly adopted for battery charge and discharge equalization, generally, a battery with higher voltage is discharged in a resistance discharge mode, and electric quantity is released in a form of heat, so that the electric quantity of the whole system is limited by the battery with the least capacity, if the capacities of the batteries connected in series are the same, the situation can be avoided, in fact, even if the initial capacities of the batteries are the same, the capacities are different gradually along with the increase of charge and discharge times and the aging degree of the batteries are different, and the difference is larger and larger, which is caused by the property difference of the batteries and is amplified along with the increase of working time, and at present, the situation cannot be avoided, and the service life of the whole system can only be prolonged by an equalization means.
The higher voltage battery wastes most of the energy in the form of heat, which is not allowed for a large capacity energy storage battery.
There is also a scheme of active equalization by parallel capacitors, i.e. each battery is connected with a super capacitor in parallel, the capacitor can be connected with its own battery and its adjacent battery in parallel by a switch, when the voltage of a certain battery is too high, 1, the current of the series loop is consistent, but a parallel branch is added to a certain battery, this branch will separate the current passing through the battery, i.e. the condition of adjusting a single battery under the condition of integral consistency, 2, the battery will age along with the working time, and the battery ages differently, showing that the voltages at two ends are different under the same working condition, firstly connecting the capacitor in parallel to the battery with high voltage, discharging the battery, switching the capacitor to the adjacent battery after the voltage of the capacitor is consistent with the voltage of the battery, charging the battery by the capacitor, realizing the electric quantity transfer, but the capacitor does not consume the electric quantity, realizing the transfer with the energy consumption, however, the method is complex to control, requires a huge switch array, is complex in structure, high in assembly difficulty and low in efficiency, and the cost of the super capacitor is not lower than that of a battery.
With the development of the technology, the active equalization technology in the field also has application.
Chinese patent 201811187147.0 discloses a battery active equalization method based on battery state of health and state of charge, and chinese patent 201710077127.7 discloses a battery active equalization circuit and method, similar applications all focus on the state of the battery itself, but do not basically consider environmental factors.
Disclosure of Invention
The invention aims to design a micro-grid energy storage battery charging and discharging control system which can be accurately controlled, has low energy loss, simple structure, low cost and high efficiency and is easy to realize.
In order to achieve the purpose, the invention adopts the following technical scheme: a prediction-based active equalization method for a micro-grid energy storage battery pack,mthe battery cells are connected in series to form a unit,pthe units are connected in parallel to form a micro-grid energy storage battery pack, the balancing method is completed by a control circuit connected with the battery pack,
the equalization method comprises the following steps:
and step A, acquiring voltage information and charge-discharge states of all battery cells in the battery pack every T minutes, and storing the acquired information and time.
And B, acquiring the daily generated energy data, daily load data and power grid scheduling data of the micro-grid in the latest Q hours.
Step C, carrying out comprehensive analysis and calculation according to the voltage information of each battery cell in the battery pack, the daily generated energy data of the microgrid, the daily load data of the microgrid and the scheduling data of the microgrid, predicting the electric quantity demand condition in the next time period T, and comprising the following steps:
step C1, calculating
Figure 562146DEST_PATH_IMAGE001
。
Wherein the content of the first and second substances,tthe value range is as follows: 1-Q60/T, representing a certain moment in Q hours, xis(t) istThe degree of association of the time of day,sthe values of 1-3 are taken as follows,x 0 (t)for all cellstThe average voltage at a moment in time is,ρin order to be a resolution factor, the resolution factor,ρ∈[0,1]，x 1 (t)is composed oftThe daily generated energy data of the micro-grid at the moment,x 2 (t)is composed oftThe daily load data of the micro-grid at the moment,x 3 (t)is composed oftAnd scheduling data of the power grid at the moment.
Step C2, calculating
Figure 824500DEST_PATH_IMAGE002
。
Wherein the content of the first and second substances,r s n = Q60/T as the number of correlations.
Step C3, calculating
Figure 817864DEST_PATH_IMAGE003
Figure 837772DEST_PATH_IMAGE004
。
Wherein the content of the first and second substances,σ 0 is a correlation factor of the cell voltage,σ 1 is a correlation factor of daily power generation of the micro-grid,σ 2 is a correlation factor of daily load of the micro-grid,σ 3 and (4) a correlation factor for power grid dispatching.
Step C4, ifσ 0 Andσ s opposite sign, thenr s =–r s ，sThe value 1-3.
And C5, calculating the charge and discharge state of the battery pack in the next time period T.
Figure 778046DEST_PATH_IMAGE005
。
0<N<n，t=n，Y t+1 Is the predicted battery charge and discharge current.
Step C6, calculating
Figure 567011DEST_PATH_IMAGE006
。
S N Standard error is indicated.
Get the smallestS N Value is corresponded toY t+1 And obtaining the charging and discharging current of the battery pack in the next time period T.
And D, calculating the SOC of each battery cell according to the battery cell voltage information.
And E, calculating and analyzing by combining the charging and discharging current of the battery pack and the SOC information of each electric core to obtain a balance control strategy, wherein the balance control strategy comprises the following steps:
step E1, calculating the mean value and standard deviation of all the current battery cell SOC:
Figure 996855DEST_PATH_IMAGE007
Figure 317109DEST_PATH_IMAGE008
。
wherein the content of the first and second substances,mis the total number of cells in a unit,V i is the first in the first unitiThe current voltage of each of the cells is,
Figure 857812DEST_PATH_IMAGE009
is a mean value, σsocIs the standard deviation.
Step E2, withVi–
Figure 501283DEST_PATH_IMAGE010
And σsocCalculating the required adjustment of each cell for the threshold valueThe magnitude of the charging/discharging current is adjusted,
Figure 39712DEST_PATH_IMAGE011
。
in the formula: i isTune iThe current size required to be adjusted for the ith cell, τ =0.0128, is a battery balance constant,I t+1 for the predicted charge-discharge current of the ith cell,I t+1 =Y t+1 /p，C i the capacity of the ith cell.
Step F, according to ITune iAndI t+1 and generating a PWM control waveform and adjusting the current capacity of an IBGT device in the control circuit.
Further, the balancing method is completed by connecting a control circuit of the battery pack, wherein the control circuit comprises a switch circuit, a balancing module, a voltage detection circuit, a control module and a communication module.
In each time period T, the control module controls the switching circuit to gate the single battery cells in the battery pack in batches one by one, is connected with the voltage detection circuit, detects the voltages at two ends of each battery cell in the battery pack through the voltage detection circuit, and uploads the voltage data of the battery cells to the control module; the communication module is communicated with a superior system to acquire daily generated energy data of the micro-grid, daily load data of the micro-grid and scheduling data of the power grid within a certain time, and the control module outputs PWM pulse waveforms through the balancing module after analysis and calculation according to the data to control the switch circuit to be gated and connected with the battery cell, so that the purpose of controlling the charging/discharging current of the battery cell in the battery pack is achieved, and battery balance is achieved.
Has the advantages that: 1. the method comprises the steps of (1) gating the cells in batches each time for measurement, improving execution speed, and further selecting the length of a time period for processing in a wider range, 2) using daily generated energy data of a micro-grid, daily load data of the micro-grid and power grid scheduling data to predict an impending state, preparing a balanced environment in advance, actively balancing a battery pack according to a prediction result when the next time period is reached, 3) setting charge and discharge currents according to specific parameters of each cell to realize accurate control, ensuring that the electric quantity of each cell in the battery pack is basically the same at the same time, 4, adopting modes of resistance discharge or parallel super capacitor and the like in the prior art, having large energy loss, and neglecting energy loss in the application.
Drawings
Figure 1 is a schematic diagram of the hardware connections of the present invention,
fig. 2 is a cell real-time OVC-SOC curve.
Detailed Description
Micro-grid energy storage battery packm×pThe battery cell consists of a plurality of battery cells,mthe battery cells are connected in series to form a unit,pthe units are connected in parallel. The purpose of series connection is to increase the battery voltage and the purpose of parallel connection is to increase the battery capacity.
The equalization method is completed by connecting a control circuit of the battery pack, as shown in fig. 1, the control circuit includes a switch circuit, an equalization module, a voltage detection circuit, a control module and a communication module.
The switch circuit is similar to a common switch circuit in structure, and is distinguished in that a switch device is formed by combining IGBTs, so that the circuit can be separated or connected, and the current in the circuit can be controlled in response to a PWM control signal.
The whole battery pack can realize active equalization by using one control circuit; for convenience of capacity expansion, each series-connected unit can be matched with a control circuit.
The control method of each unit is the same, and one unit is taken as an example for explanation.
And step A, acquiring voltage information and charge-discharge states of all battery cells in the battery pack every T minutes, and storing the acquired information and time.
The charging and discharging of the battery is a relatively slow process, and the sampling interval adopted in the embodiment is T =5 minutes; and the sampling interval can be adjusted according to different charging and discharging multiplying powers of the battery, so that the battery is controlled to be balanced and does not do more useless work.
In the step A, the control module controls the switch circuit to gradually gate the connection of the voltage detection circuit and the battery cell in batches to acquire the voltage information of the battery cell in the battery pack.
In this embodiment, the voltage detection circuit mainly includes a switch selection chip, a sampling resistor, and a metering chip, and each switch selection chip can control the switches at the two ends of 8 electric cores to be switched on and off.
According to the chip capacity, for example, to improve the working efficiency, in this embodiment, the battery cells connected in series into a unit are divided into 8 groups, and 8 battery cells are gated for measurement each time. If a unit contains 200 cells, the cells can be divided into 25 groups; in order to improve the measurement accuracy, the voltage detection time is 20ms each time, and the time required by all the cells in the measurement unit is 20 × 25=500 ms. This time fully meets the requirement of T =5 minutes.
And B, acquiring the daily generated energy data, daily load data and power grid scheduling data of the micro-grid in the latest Q hours.
And B, while the step A is carried out, communicating with an upper-level system through a communication module to obtain related data in a latest period of time. For the micro-grid system, the related data comprises micro-grid daily power generation data, micro-grid daily load data and power grid scheduling data.
In this example, the prediction calculation was performed using the data of the last 24 hours, i.e., Q = 24.
Step C, performing comprehensive analysis and calculation according to the voltage information of each battery cell in the battery pack, the daily generated energy data of the micro-grid, the daily load data of the micro-grid and the scheduling data of the power grid, and predicting the electric quantity demand condition in the next time period T; and meanwhile, calculating the electric quantity (SOC) condition of the battery cell in the battery pack according to the voltage information of the battery cell.
Step C1, analyzing the relevance between the cell voltage and the related data, and calculating
Figure 34212DEST_PATH_IMAGE001
。
Wherein the content of the first and second substances,tthe value range is as follows: 1-Q60/T, representing a certain moment in Q hours, xis(t) istThe degree of association of the time of day,sthe values of 1-3 are taken as follows,x 0 (t)for all cellstOf time of dayThe average voltage is then calculated by taking the average voltage,ρin order to be a resolution factor, the resolution factor,ρ∈[0,1]the larger the resolution factor, the larger the resolution, the smaller the resolution factor, and the smaller the resolution.
x 1 (t)Is composed oftThe daily generated energy data of the micro-grid at the moment,x 2 (t)is composed oftThe daily load data of the micro-grid at the moment,x 3 (t)is composed oftAnd scheduling data of the power grid at the moment. minute min viable countx 0 (t)-x s (t) | and max-x 0 (t)-x s (t) And | is the minimum difference and the maximum difference of two levels respectively.
If tmax is 3, two equations are developed:
min min|x 0 (t)-x s (t)|=min( min(|x 0 (1)-x 1 (1)|，|x 0 (2)-x 1 (2)|，|x 0 (3)-x 1 (3)|)，min(|x 0 (1)-x 2 (1)|，|x 0 (2)-x 2 (2)|，|x 0 (3)-x 2 (3)|)，min(|x 0 (1)-x 3 (1)|，|x 0 (2)-x 3 (2)|，|x 0 (3)-x 3 (3)|) )。
max max|x 0 (t)-x s (t)|=max( max(|x 0 (1)-x 1 (1)|，|x 0 (2)-x 1 (2)|，|x 0 (3)-x 1 (3)|)，max(|x 0 (1)-x 2 (1)|，|x 0 (2)-x 2 (2)|，|x 0 (3)-x 2 (3)|)，max(|x 0 (1)-x 3 (1)|，|x 0 (2)-x 3 (2)|，|x 0 (3)-x 3 (3)|) )。
the calculation result is an index describing the correlation degree of the average voltage of the battery core, the daily generated energy data of the micro-grid, the daily load data of the micro-grid and the scheduling data of the power grid at a certain time (t).
Step C2, integrating the indexes and calculating
Figure 440923DEST_PATH_IMAGE002
。
Wherein the content of the first and second substances,r s n = Q60/T as the number of correlations.
Step C3, calculating xisThe absolute value is used in the formula of (t), and therefore it is not possible to distinguish whether the correlation is positive or negative, and this embodiment adopts the following formula to solve this problem.
Computing
Figure 938900DEST_PATH_IMAGE003
Figure 976127DEST_PATH_IMAGE004
。
Wherein the content of the first and second substances,σ 0 is a correlation factor of the cell voltage,σ 1 is a correlation factor of daily power generation of the micro-grid,σ 2 is a correlation factor of daily load of the micro-grid,σ 3 and (4) a correlation factor for power grid dispatching.
Step C4, ifσ 0 Andσ s opposite sign, thenr s =–r s ，sThe value 1-3.
When sign (σ 0 )=sign(σ s ) Indicating a positive association between the two; when sign (σ 0 )=–sign(σ s ) Indicates a negative relationship between the two, so thatr s =–r s 。
In the case of positive association, the higher the number of associations, the higher the priority, and the lower the number of associations, the lower the priority; similarly, in the case of negative correlation, the higher the priority is as the number of correlations is smaller (as the absolute value is larger), the lower the priority is as the number of correlations is larger.
And step C5, calculating the charge-discharge state of the battery pack for the next time period T, namely T minutes from the moment T + 1.
The operation condition in the microgrid has periodicity, and the battery charging and discharging condition at the next moment can be predicted by the following formula:
Figure 130027DEST_PATH_IMAGE012
。
0<N<n, t represents the time of the current time period, t +1 represents the time at which the next time period starts,Y t+1 the predicted next time period T is the battery pack charging and discharging current.
The prediction value is based on data of N-1 time periods ahead from the current time t.
In this example, Q =24 hours of data, T =5, data collected every 5 minutes, T =24 × 60/5=288, was obtained.
Because N has different values and has different influences on the prediction result, the standard error of the prediction result needs to be calculated.
Step C6, calculating
Figure 278112DEST_PATH_IMAGE006
。
S N Indicating the standard error of N taking different values.
Minimum sizeS N The value indicates the highest prediction accuracy. Get the smallestS N Value is corresponded toY t+1 And obtaining the charging and discharging current of the battery pack in the next time period T.
And D, calculating the SOC of each battery cell according to the battery cell voltage information.
As shown in fig. 2, the cell voltage is used to search the real-time VOC-SOC curve of the cell, so as to obtain the current SOC of the cell. If the cell voltage is 3.2V, the corresponding SOC is 83%, that is, 83% of the remaining electric quantity of the current cell. This step requires only a table lookup: when the voltage is known, the corresponding battery capacity can be found according to the VOC-SCO of the battery core.
And calculating the charging and discharging current of the battery pack in the next time period T.
Step E, combining the charging and discharging current of the battery pack in the next time period T (T +1)Y t+1 And calculating and analyzing the SOC information of the battery cell in the battery pack to obtain the balance control strategy.
And E1, calculating the mean value and the standard deviation of all the current battery cell SOC.
Figure 630596DEST_PATH_IMAGE007
Figure 648843DEST_PATH_IMAGE008
。
Wherein the content of the first and second substances,mis the total number of cells in a unit,V i is the first in the first unitiThe current voltage of each of the cells is,
Figure 352357DEST_PATH_IMAGE013
is a mean value, σsocIs the standard deviation.
The above is data for calculating the cells in one unit. And performing the calculation for all the units to obtain the data of all the battery cores.
All cells can also be calculated as the base number:
Figure 976236DEST_PATH_IMAGE014
Figure 714385DEST_PATH_IMAGE015
。
wherein the content of the first and second substances,m×pthe total number of cells of the battery pack.
Step E2, withVi–
Figure 827834DEST_PATH_IMAGE010
And σsocAnd calculating the value of the charging/discharging current of each battery cell, which is a threshold value.
Figure 80961DEST_PATH_IMAGE011
。
In the formula: i isTune iThe current size required to be adjusted for the ith cell, τ =0.0128, is a battery balance constant,I t+1 for the predicted charge-discharge current of the ith cell,C i the capacity of the ith cell.
Predicted total charge and discharge current of battery packY t+1 There are a total of p units in parallel. And (3) considering the difference of the parallel branches, the charging and discharging current of each branch is as follows:I t+1 =Y t+1 /p。
step F, when the starting time (t +1) of the next time period is reached, aiming at each electric core I, according to the ITune iAndI t+1 and generating a PWM control waveform, connecting the PWM control waveform with a control pin of an IGBT in a switch circuit, adjusting the through-current capacity of the IBGT device, and controlling the charging/discharging current of the battery cell to achieve the purpose of actively balancing each battery cell.
And repeating the steps, taking T as a time interval, and adjusting in real time according to a prediction result to realize active equalization of the battery pack and achieve the aim of battery equalization control.
The following is the effect contrast data after 1000 charges and discharges of two sets of group battery, and the standard is 3.2V, 0.5A/h's lithium cell electricity core is all selected for use to the electric core, and every group adopts 100 electric cores to establish ties to constitute.
The original capacity table/capacity mean value after the detection of 200 electric cores is 0.504 (A/h), which is similar to the nominal capacity:
0.503 0.503 0.504 0.499 0.500 0.504 0.502 0.504
0.501 0.504 0.504 0.499 0.498 0.505 0.502 0.508
0.508 0.499 0.510 0.509 0.499 0.500 0.502 0.510
0.506 0.510 0.501 0.499 0.508 0.498 0.500 0.503
0.506 0.507 0.500 0.502 0.507 0.503 0.507 0.500
0.509 0.502 0.500 0.505 0.508 0.499 0.509 0.504
0.506 0.501 0.502 0.503 0.507 0.501 0.506 0.510
0.501 0.508 0.500 0.510 0.507 0.507 0.510 0.501
0.499 0.502 0.508 0.505 0.502 0.498 0.507 0.504
0.501 0.502 0.508 0.499 0.507 0.499 0.500 0.500
0.506 0.501 0.504 0.507 0.506 0.506 0.504 0.506
0.501 0.503 0.498 0.499 0.506 0.509 0.499 0.508
0.507 0.502 0.501 0.509 0.501 0.502 0.505 0.509
0.505 0.506 0.501 0.502 0.499 0.501 0.503 0.508
0.503 0.503 0.504 0.498 0.502 0.501 0.503 0.498
0.506 0.501 0.500 0.500 0.500 0.506 0.510 0.503
0.502 0.509 0.498 0.502 0.502 0.507 0.508 0.510
0.504 0.505 0.508 0.508 0.499 0.499 0.509 0.500
0.505 0.498 0.507 0.509 0.499 0.506 0.506 0.508
0.499 0.509 0.506 0.509 0.501 0.500 0.510 0.501
0.500 0.499 0.505 0.507 0.509 0.503 0.506 0.510
0.508 0.504 0.501 0.508 0.509 0.503 0.509 0.506
0.505 0.504 0.503 0.505 0.510 0.504 0.501 0.502
0.504 0.500 0.504 0.503 0.501 0.499 0.505 0.500
0.503 0.502 0.505 0.502 0.510 0.507 0.500 0.499
the 200 battery cores are randomly divided into two groups, a mode that 100 battery cores in each group are connected in series is adopted, the group A adopts a battery equalization scheme (a resistance discharge equalization mode) provided by a battery manufacturer, the group B adopts the equalization scheme, after 1000 times of charging and discharging, the battery is subjected to nuclear capacity detection (the detection mode is an ampere-hour integral method as the upper detection mode), and the detection results are as follows.
After 1000 times of charge and discharge of the group A, the average value of the cell capacity is 0.493A/h
0.497 0.501 0.489 0.492
0.499 0.490 0.491 0.495
0.501 0.491 0.501 0.498
0.489 0.498 0.495 0.491
0.501 0.495 0.491 0.494
0.496 0.497 0.489 0.489
0.495 0.498 0.499 0.493
0.497 0.489 0.497 0.487
0.491 0.491 0.500 0.489
0.492 0.489 0.491 0.498
0.498 0.498 0.499 0.488
0.497 0.489 0.493 0.493
0.487 0.488 0.493 0.468
0.489 0.487 0.499 0.490
0.491 0.501 0.493 0.500
0.495 0.487 0.500 0.495
0.494 0.456 0.498 0.494
0.492 0.493 0.495 0.498
0.487 0.488 0.498 0.497
0.490 0.493 0.501 0.501
0.497 0.492 0.499 0.492
0.492 0.492 0.489 0.490
0.501 0.496 0.491 0.498
0.494 0.489 0.488 0.501
0.494 0.491 0.494 0.495
0.495 0.488 0.498 0.497
After 1000 times of charge and discharge in group B, the average value of the cell capacity is 0.497A/h
0.493 0.497 0.499 0.500
0.492 0.492 0.497 0.500
0.497 0.502 0.502 0.496
0.496 0.502 0.501 0.496
0.497 0.496 0.502 0.499
0.502 0.499 0.495 0.502
0.498 0.497 0.496 0.502
0.496 0.499 0.502 0.493
0.494 0.499 0.494 0.498
0.495 0.500 0.495 0.495
0.500 0.496 0.501 0.497
0.492 0.495 0.497 0.500
0.493 0.496 0.498 0.498
0.501 0.500 0.501 0.492
0.497 0.494 0.498 0.495
0.501 0.502 0.495 0.496
0.494 0.497 0.492 0.497
0.497 0.493 0.500 0.496
0.499 0.502 0.494 0.497
0.492 0.499 0.495 0.492
0.497 0.499 0.495 0.492
0.492 0.500 0.498 0.492
0.496 0.493 0.495 0.499
0.501 0.498 0.502 0.498
0.498 0.496 0.500 0.502
0.494 0.498 0.497 0.497。
The comparison of the above tables shows that the capacity derating of the group A battery is larger than that of the group B battery, namely the battery life consumption is larger; and the standard deviation of the battery capacity in the group A is smaller than that of the battery capacity in the group B, which shows that the service life condition of the group A battery is more different and is more difficult in the later maintenance process.
Looking carefully at A, B both groups, it was found that there were two cells in group A that had a faster drop in capacity (0.456, 0,468). Because the number of samples is relatively large, the occurrence of the situation can be basically excluded to be caused by the individual difference of the battery cells. It can be expected that with the increase of the charging and discharging times, the difference between the capacities of the two battery cells and the capacities of other battery cells will be further increased, thereby affecting the use of the whole battery pack and even scrapping the battery pack.
The measurement results after 1000 times of re-charging and discharging are as follows.
After 2000 times of charging and discharging of group A
0.485 0.488 0.471 0.477
0.483 0.473 0.475 0.477
0.490 0.484 0.489 0.481
0.482 0.487 0.487 0.473
0.482 0.484 0.477 0.476
0.482 0.482 0.470 0.477
0.483 0.486 0.479 0.480
0.488 0.473 0.478 0.467
0.480 0.482 0.486 0.477
0.484 0.475 0.485 0.480
0.489 0.480 0.488 0.473
0.480 0.476 0.479 0.477
0.477 0.478 0.482 0.449
0.475 0.470 0.491 0.483
0.478 0.492 0.486 0.482
0.490 0.470 0.487 0.480
0.478 0.417 0.491 0.476
0.484 0.483 0.478 0.486
0.473 0.481 0.487 0.481
0.472 0.481 0.486 0.486
0.492 0.478 0.487 0.479
0.487 0.485 0.480 0.480
0.494 0.490 0.476 0.481
0.487 0.470 0.477 0.487
0.478 0.475 0.475 0.484
0.483 0.474 0.488 0.487
After the B group battery is charged and discharged for 2000 times
0.487 0.494 0.488 0.494
0.481 0.488 0.494 0.489
0.482 0.496 0.490 0.483
0.485 0.489 0.493 0.484
0.484 0.490 0.496 0.495
0.489 0.486 0.483 0.488
0.490 0.484 0.490 0.495
0.492 0.489 0.498 0.482
0.488 0.490 0.484 0.491
0.484 0.489 0.487 0.484
0.497 0.487 0.493 0.485
0.489 0.488 0.490 0.493
0.480 0.488 0.492 0.486
0.490 0.486 0.486 0.482
0.484 0.481 0.494 0.486
0.488 0.489 0.480 0.490
0.481 0.486 0.489 0.493
0.487 0.486 0.492 0.489
0.491 0.491 0.485 0.490
0.484 0.490 0.481 0.481
0.487 0.485 0.484 0.485
0.482 0.489 0.485 0.483
0.483 0.490 0.482 0.487
0.487 0.488 0.496 0.486
0.492 0.482 0.492 0.489
0.490 0.486 0.491 0.488。
In group a, the capacity of two cells decreased rapidly (second measurements of 0.449, 0.417); in group B, the change is substantially consistent.
In summary, the equalization method adopted by the group a is obviously not as good as the equalization method adopted by the group B.

Claims (4)

1. A prediction-based active equalization method for a micro-grid energy storage battery pack,mthe battery cells are connected in series to form a unit,pthe units are connected in parallel to form a micro-grid energy storage battery pack, the balancing method is completed by a control circuit connected with the battery pack,
the method is characterized by comprising the following steps:
step A, acquiring voltage information and charge-discharge states of all battery cells in a battery pack every T minutes, and storing the acquired information and time;
b, acquiring daily generated energy data, daily load data and power grid scheduling data of the micro-grid in the latest Q hours;
step C, carrying out comprehensive analysis and calculation according to the voltage information of each battery cell in the battery pack, the daily generated energy data of the microgrid, the daily load data of the microgrid and the scheduling data of the microgrid, predicting the electric quantity demand condition in the next time period T, and comprising the following steps:
step C1, calculating
Figure 276213DEST_PATH_IMAGE001
Wherein the content of the first and second substances,tthe value range is as follows: 1-Q60/T, representing a certain moment in Q hours, xis(t) istThe degree of association of the time of day, x 0 (t)for all cellstThe average voltage at a moment in time is,ρin order to be a resolution factor, the resolution factor,ρ∈[0,1]，sthe values of 1-3 are taken as follows,x 1 (t)is composed oftThe daily generated energy data of the micro-grid at the moment,x 2 (t)is composed oftThe daily load data of the micro-grid at the moment,x 3 (t)is composed oftThe time of day is the power grid dispatching data,
step C2, calculating
Figure 380435DEST_PATH_IMAGE002
Wherein the content of the first and second substances,r s n = Q60/T as the number of correlations,
step C3, calculating
Figure 5451DEST_PATH_IMAGE003
Figure 802506DEST_PATH_IMAGE004
Wherein the content of the first and second substances,σ 0 is a correlation factor of the cell voltage,σ 1 is a correlation factor of daily power generation of the micro-grid,σ 2 is a correlation factor of daily load of the micro-grid,σ 3 the relevance factor of the power grid dispatching is,
step C4, ifσ 0 Andσ s opposite sign, thenr s =–r s ，sThe values of 1-3 are taken as follows,
step C5, calculating the charge and discharge state of the battery pack in the next time period T,
Figure 880183DEST_PATH_IMAGE005
0<N<n，t=n，Y t+1 for the predicted charge and discharge currents of the battery,
step C6, calculating
Figure 53676DEST_PATH_IMAGE006
S N Represents the standard error;
get the smallestS N Value is corresponded toY t+1 Obtaining the charging and discharging current of the battery pack in the next time period T;
step D, calculating the SOC of each battery cell according to the battery cell voltage information,
and E, calculating and analyzing by combining the charging and discharging current of the battery pack and the SOC information of each electric core to obtain a balance control strategy, wherein the balance control strategy comprises the following steps:
step E1, calculating the mean value and standard deviation of all the current battery cell SOC:
Figure 798778DEST_PATH_IMAGE007
Figure 750422DEST_PATH_IMAGE008
wherein the content of the first and second substances,mis the total number of cells in a unit,V i is the first in the first unitiThe current voltage of each of the cells is,
Figure 580975DEST_PATH_IMAGE009
is a mean value, σsocIs the standard deviation;
step E2, withVi–
Figure 292579DEST_PATH_IMAGE010
And σsocIs a threshold value which is a threshold value,calculating the size of the charging/discharging current required to be adjusted for each battery cell,
Figure 892188DEST_PATH_IMAGE011
in the formula: i isTune iThe current size required to be adjusted for the ith cell, τ =0.0128, is a battery balance constant,I t+1 for the predicted charge-discharge current of the ith cell,I t+1 =Y t+1 /p，C i the capacity of the ith cell;
step F, according to ITune iAndI t+1 and generating a PWM control waveform and adjusting the current capacity of an IBGT device in the control circuit.
2. The microgrid energy storage battery pack active equalization method based on prediction of claim 1,
step E1, calculating the mean value and standard deviation of all the current battery cell SOC:
Figure 765466DEST_PATH_IMAGE012
Figure 83314DEST_PATH_IMAGE013
wherein the content of the first and second substances,m×pis the total number of the battery cells of the battery pack,V i is the first in the first unitiThe current voltage of the individual cell is,
Figure 333030DEST_PATH_IMAGE009
is a mean value, σsocIs the standard deviation.
3. The microgrid energy storage battery pack active equalization method based on prediction as claimed in claim 1, characterized in that the control circuit comprises a switching circuit, an equalization module, a voltage detection circuit, a control module and a communication module;
in the step A, the control module controls the switch circuit to gradually gate the connection of the voltage detection circuit and the battery cell in batches to acquire the voltage information of the battery cell in the battery pack.
4. The microgrid energy storage battery pack active equalization method based on prediction as claimed in claim 3, characterized in that each series-connected unit is associated with a control circuit.
CN202110438917.XA 2021-04-23 2021-04-23 Prediction-based active equalization method for energy storage battery of micro-grid Pending CN113206508A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202110438917.XA CN113206508A (en) 2021-04-23 2021-04-23 Prediction-based active equalization method for energy storage battery of micro-grid

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202110438917.XA CN113206508A (en) 2021-04-23 2021-04-23 Prediction-based active equalization method for energy storage battery of micro-grid

Publications (1)

Publication Number Publication Date
CN113206508A true CN113206508A (en) 2021-08-03

Family

ID=77028034

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202110438917.XA Pending CN113206508A (en) 2021-04-23 2021-04-23 Prediction-based active equalization method for energy storage battery of micro-grid

Country Status (1)

Country Link
CN (1) CN113206508A (en)

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113962468A (en) * 2021-10-29 2022-01-21 杭州青橄榄网络技术有限公司 Energy consumption monitoring and statistics-based energy consumption carbon emission management method and system
CN114460470A (en) * 2022-01-26 2022-05-10 上海玫克生智能科技有限公司 Battery pack state analysis method and system based on voltage and terminal
CN117559614A (en) * 2024-01-11 2024-02-13 西安奇点能源股份有限公司 Charging and discharging balance control method for serial battery PACK

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113962468A (en) * 2021-10-29 2022-01-21 杭州青橄榄网络技术有限公司 Energy consumption monitoring and statistics-based energy consumption carbon emission management method and system
CN114460470A (en) * 2022-01-26 2022-05-10 上海玫克生智能科技有限公司 Battery pack state analysis method and system based on voltage and terminal
CN117559614A (en) * 2024-01-11 2024-02-13 西安奇点能源股份有限公司 Charging and discharging balance control method for serial battery PACK
CN117559614B (en) * 2024-01-11 2024-04-02 西安奇点能源股份有限公司 Charging and discharging balance control method for serial battery PACK

Similar Documents

Publication Publication Date Title
Han et al. Estimation of cell SOC evolution and system performance in module-based battery charge equalization systems
CN109031145B (en) Series-parallel battery pack model considering inconsistency and implementation method
CN102324582B (en) Intelligent maintenance device of multifunctional lead-acid battery and capacity prediction method
CN113206508A (en) Prediction-based active equalization method for energy storage battery of micro-grid
CN105449740B (en) A kind of energy-storage lithium battery active equalization control system and control method
US11292360B2 (en) Battery equalization method and system, vehicle, storage medium, and electronic device
US10230248B2 (en) Maintenance method of power battery pack
CN109687548B (en) Supplementary electric formula of storage battery initiative balancing unit
Huang et al. Wireless smart battery management system for electric vehicles
Yildirim et al. Evaluation and comparison of battery cell balancing methods
CN112350400A (en) Lithium battery pack non-hierarchical active and passive equalization circuit and method
Ekanayake et al. Active and passive based hybrid cell balancing approach to series connected lithium-ion battery pack
Turksoy et al. A fast and energy-efficient nonnegative least square-based optimal active battery balancing control strategy for electric vehicle applications
CN111762059A (en) Multivariable fusion battery pack balancing method considering battery charging and discharging working conditions
CN110707788A (en) System and method for quickly equalizing energy storage battery array in distributed energy storage power station
Li et al. Design of an active battery equalization circuit with DC-DC converter
Li et al. Evaluation and analysis of circuit model for lithium batteries
Hong et al. A battery management system with two-stage equalization
CN214124859U (en) Battery management system for lithium battery
CN114938049A (en) Method and system for charging and discharging balance protection detection management of battery pack
CN112054575B (en) LC energy storage based series-parallel battery pack integrated equalization method
CN110739747B (en) Equalization control method of battery pack
Yan et al. Development status of balanced technology of battery management system of electric vehicle
Zhang et al. Research on Series-Parallel Connection Switching Charging Method for Lithium Battery of Autonomous Underwater Vehicles
Sun et al. Quick Evaluation of the State-of-Health of Spent Lithium-Ion Battery Modules

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
RJ01 Rejection of invention patent application after publication
RJ01 Rejection of invention patent application after publication

Application publication date: 20210803