CN113536235A - Charge state prediction feedback system of mining power battery pack - Google Patents

Charge state prediction feedback system of mining power battery pack Download PDF

Info

Publication number
CN113536235A
CN113536235A CN202110801923.7A CN202110801923A CN113536235A CN 113536235 A CN113536235 A CN 113536235A CN 202110801923 A CN202110801923 A CN 202110801923A CN 113536235 A CN113536235 A CN 113536235A
Authority
CN
China
Prior art keywords
data
power battery
battery pack
unit
signal
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.)
Withdrawn
Application number
CN202110801923.7A
Other languages
Chinese (zh)
Inventor
封居强
孙业国
张星
黄凯峰
伍龙
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.)
Huainan Normal University
Original Assignee
Huainan Normal University
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 Huainan Normal University filed Critical Huainan Normal University
Priority to CN202110801923.7A priority Critical patent/CN113536235A/en
Publication of CN113536235A publication Critical patent/CN113536235A/en
Withdrawn legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/06—Electricity, gas or water supply

Abstract

The invention discloses a charge state prediction feedback system of a mining power battery pack, which relates to the technical field of power batteries and comprises a data acquisition unit, a data processing unit, a signal calibration unit, a data verification unit, a data cache unit, a data feedback unit and a display screen; the data processing unit is used for sending the first total estimated characteristic quantity Y' to the data verification unit and sending the O of the power battery pack with the equal interval duration in the second time level to the data processing unitjAnd O'jThe signal is sent to a signal calibration unit; the invention can be used for complex engineeringMoreover, the SOC is accurately predicted, specific verification and feedback processes are involved, and the safety and stability of the power battery pack are greatly improved.

Description

Charge state prediction feedback system of mining power battery pack
Technical Field
The invention relates to the technical field of power batteries, in particular to a charge state prediction feedback system of a mining power battery pack.
Background
The SOC is the ratio of the residual capacity of the storage battery after being used for a period of time or being left unused for a long time to the capacity of the storage battery in a full charge state, the value range of the SOC is 0-1, when the SOC is 0, the storage battery is completely discharged, when the SOC is 1, the storage battery is completely charged, in a new energy automobile, the SOC is taken as the internal parameter of the storage battery and has important significance to a battery management system, the SOC of a power battery pack is equivalent to the oil meter of a common fuel automobile, and the SOC of the storage battery is taken as one of important decision factors of energy management and plays an important role in optimizing the energy management of the whole automobile, improving the utilization of power capacitance and capacity, controlling the overcharge and the overdischarge of the power battery and ensuring the safety of the power battery in the use process;
the SOC is an important parameter for measuring the safety coefficient of the power battery pack, but in the prior art, the calculation of the SOC is mostly directly obtained through an algorithm or is obtained through single factor acquisition and comparison, the SOC under a complex working condition is difficult to accurately predict, specific verification and feedback processes are not provided, only the rough estimation content of the SOC is provided, and the safety and stability of the power battery pack are greatly influenced;
in order to solve the above-mentioned drawbacks, a technical solution is now provided.
Disclosure of Invention
The invention aims to provide a system for predicting and feeding back the state of charge of a mining power battery pack, aiming at solving the problems that in the prior art, the state of charge SOC is mostly calculated by directly obtaining the state of charge through an algorithm or is obtained by acquiring and comparing single factors, the accurate prediction of the state of charge SOC under a complex working condition is difficult, no specific verification and feedback process exists, only the rough estimation content of the state of charge SOC greatly influences the safety and stability of the power battery pack.
The purpose of the invention can be realized by the following technical scheme:
a charge state prediction feedback system of a mining power battery pack comprises a data acquisition unit, a data processing unit, a signal calibration unit, a data verification unit, a data cache unit, a data feedback unit and a display screen;
the data acquisition unit is used for capturing and acquiring internal cause parameters and external cause parameters of the power battery pack and sending the internal cause parameters and the external cause parameters to the data processing unit;
the data processing unit carries out the following estimation and characterization quantity calculation operation on the received intrinsic parameters and extrinsic parameters:
s1: acquiring internal cause parameters of the power battery pack in each equal time period in the first time level, wherein the internal cause parameters comprise current data, voltage data, internal resistance data and working temperature data, and respectively marking the internal cause parameters as Ii、Ui、RiAnd TiAccording to the formula
Figure BDA0003165009400000021
Determining internal data O of a power battery pack for equal time periods within a first time classiWherein a is1、a2、a3And a4Respectively expressed as the bias coefficients of current data, voltage data, internal resistance data and operating temperature data, and a3＞a4＞a2＞a1＞0；
S2: acquiring external factor parameters of the power battery pack in each equal time period in the first time level, wherein the external factor parameters comprise aging degree data, new rate data and environment temperature data, and respectively marking the external factor parameters as Pi、KiAnd Ti', according to the formula
Figure BDA0003165009400000022
Determining external data O of the power battery pack for each equal time interval within a first time classi', wherein, b1、b2And b3Conversion factors expressed as aging degree data, new rate data and environment temperature data respectivelySub-coefficients, and b1＞b2＞b3＞0；
S3: according to the formula
Figure BDA0003165009400000023
Determining a first total estimated variable Y' of the power battery at a first time level, wherein c1And c2Error coefficients expressed as internal data and external data, respectively, and c1＞c2＞0；
The data processing unit sends the first total estimated characteristic quantity Y' to a data verification unit;
the data processing unit also compares the O of the power battery pack with each equal interval duration in the second time leveljAnd Oj' the signal is sent to a signal calibration unit;
the signal calibration unit receives internal data O of the power battery pack with equal interval duration in the second time leveljAnd external data OjPerforming quantitative calibration, and sending the calibrated signal data to a data verification unit;
the data verification unit verifies and compares the first total estimated characteristic quantity Y 'obtained at the first time level and the second total estimated characteristic quantity X' obtained at the second time level, and sends a comparison result after verification to the data feedback unit;
and the data feedback unit outputs the received verification result and sends the output data to a display screen in a text mode.
Further, the aging degree data includes a power-skip rate, a capacity loss amount and a power circulation amount, and are respectively designated as Tdi、RhiAnd PsiAccording to the formula
Figure BDA0003165009400000031
Determining aging data P for each equal time segment of the power battery pack within a first time leveliWherein h is1、h2And h3Aging factor coefficients respectively representing the power-skip rate, the capacity loss amount and the electric quantity circulation amount, and h2＞h1＞h3＞0。
Further, the signal calibration unit receives internal data O of the power battery pack with equal interval duration in the second time leveljAnd external data O'jAnd carrying out quantitative calibration, wherein the specific signal calibration operation steps are as follows:
step 1: acquiring data values of internal cause parameters of the power battery pack with equal interval duration in a second time level, and carrying out materialization calibration on the data values;
step 2: acquiring data values of external cause parameters of the power battery pack within each equal interval time length in a second time level, and carrying out hierarchical calibration on the data values;
step 3: respectively extracting and identifying the current signal, the voltage signal, the internal resistance signal and the working temperature signal data calibrated in Step1, and dividing gears according to the degree of conversion;
step 4: respectively identifying the aging degree signal, the new rate signal and the environment temperature signal data calibrated in Step2, and carrying out level division according to the level degree;
step 5: scaling the sum of the quantized and scaled good signals over all equal interval durations in the second time stage to G and the sum of the quantized and scaled difference signals to G' according to a formula
Figure BDA0003165009400000041
Determining a second total estimated variable X' of the power battery at a second time level, wherein d1And d2Coefficient of conversion factor expressed as a good semaphore and a difference semaphore, respectively, and d1＞d2＞0；
And the signal calibration unit sends the second total estimated quantity X' of the power battery pack with the second time level to the data verification unit.
Further, the data verification unit performs verification comparison on the first total estimated quantity Y 'in the first time level obtained by the same power battery pack and the second total estimated quantity X' in the second time level obtained by the same power battery pack, and specific data verification operations are as follows:
carrying out goodness of fit verification on the data of the first total estimated characteristic quantity Y 'and the second total estimated characteristic quantity X', and verifying the goodness of fit according to a formula
Figure BDA0003165009400000042
Calculating the matching value Z and the preset range W thereof1Comparing and outputting very accurate, generally accurate and differential results;
the data verification unit respectively sends a very accurate result, a general accurate result and a difference result of the verification to the data feedback unit.
Further, the data verification unit is electrically connected with a data caching unit, and the data caching unit is used for temporarily storing the difference result data.
Further, the sum of the best signals is scaled to be G equal to (the sum of the numbers of the first gear, the second gear, the third gear, the first order and the second order in the materialization scaling and the grading scaling)/(the total number of all the gears + the total number of all the steps), and the sum of the difference signals is scaled to be G' equal to (the sum of the numbers of the fourth gear and the third order in the materialization scaling and the grading scaling)/(the total number of all the gears + the total number of all the steps).
Compared with the prior art, the invention has the beneficial effects that:
1. the method comprises the steps that data influencing the SOC estimated value in multiple aspects of a first time level are collected and subjected to data calibration and formulation processing, so that the estimated value with very accurate SOC is obtained, and the SOC of a battery pack is predicted and estimated in all directions under complex working conditions;
2. the state of charge estimation data is influenced in multiple aspects of the second time level, signal calibration and quantization processing are carried out on the state of charge estimation data, so that state of charge estimation verification data is obtained, the verification data is compared with the estimation data with very accurate state of charge, the state of charge is fed back, and the safety and stability of the mining power battery pack are greatly improved while the effective accurate state of charge is obtained.
Drawings
In order to facilitate understanding for those skilled in the art, the present invention will be further described with reference to the accompanying drawings;
FIG. 1 is a block diagram of the system of the present invention;
FIG. 2 is a diagram illustrating a first time level and a second time level according to the present invention;
FIG. 3 is a schematic diagram of the stratification steps of the present invention;
FIG. 4 is a diagram illustrating the grading level division according to the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-4, a system for predicting and feeding back a state of charge of a mining power battery pack includes a data acquisition unit, a data processing unit, a signal calibration unit, a data verification unit, a data cache unit, a data feedback unit, and a display screen;
the data acquisition unit captures and acquires internal cause parameters and external cause parameters of the power battery pack, wherein the internal cause parameters comprise current data, voltage data, internal resistance data and working temperature data, the external cause parameters comprise aging degree data, new rate data and environment temperature data, and the acquired data parameters are transmitted to the data processing unit, wherein the internal cause parameters represent parameter data influencing internal factors of the power battery pack, the external cause parameters represent parameter data influencing external factors of the power battery pack, and the internal cause parameters and the external cause parameters jointly determine the state of charge (SOC) of the power battery pack;
the data processing unit carries out the following estimation and characterization quantity calculation operation on the received internal cause parameters and external cause parameters:
s1: acquiring intrinsic parameters of the power battery pack in each equal time period in a first time level, and respectively marking current data, voltage data, internal resistance data and working temperature data as Ii、Ui、RiAnd TiAccording to the formula
Figure BDA0003165009400000061
n is a positive integer greater than or equal to 1, and internal data O of the power battery pack in each equal time slot in the first time level is obtainediWherein a is1、a2、a3And a4Respectively expressed as the bias coefficients of current data, voltage data, internal resistance data and operating temperature data, and a3＞a4＞a2＞a1＞0，a1+a2+a3+a49.82, wherein the current data, the voltage data and the internal resistance data are all represented as mean value data obtained when the power battery pack in each equal time period operates in a first time level, the working temperature data is represented as an average temperature when the power battery pack operates, the current data, the voltage data, the internal resistance data and the working temperature data are acquired by detection equipment such as a sensor, the first time level is represented as a time interval of 3 months, and the deviation coefficient is represented as the magnitude of correction degree of the current data, the voltage data, the internal resistance data and the working temperature data on the internal factor parameter;
s2: acquiring external factor parameters of the power battery pack in each equal time period in the first time level, wherein the external factor parameters comprise aging degree data, new rate data and environment temperature data, and respectively marking the external factor parameters as Pi、KiAnd Ti', according to the formula
Figure BDA0003165009400000071
n is a positive integer of 1 or more, and external data O 'of the power battery pack in each equal time slot in the first time level is obtained'iWherein b is1、b2And b3Respectively expressed as conversion factor coefficients of aging degree data, new rate data and ambient temperature data, and b1＞b2＞b3＞0，b1+b2+b31.5, wherein the conversion factor coefficient is expressed as the influence degree of aging degree data, new rate data and environment temperature data on the extrinsic parameter, and the aging degree dataThe aging degree data is used for measuring the variable quantity of the performance of the power battery pack, the freshness rate is used for reflecting the old and new degree of the power battery pack, and specifically, the freshness rate is [ rated service time of the battery pack/(rated service time of the battery pack + used time of the battery pack)]100%, the ambient temperature data representing an average of ambient temperatures at which the power cell stack is located;
wherein the aging degree data includes a power-skip rate, a capacity loss amount and a power circulation amount, and is respectively designated as Tdi、RhiAnd PsiAccording to the formula
Figure BDA0003165009400000072
n is a positive integer greater than or equal to 1, and aging degree data P of the power battery pack in each equal time period in the first time level is obtainediWherein h is1、h2And h3Aging factor coefficients respectively representing the power-skip rate, the capacity loss amount and the electric quantity circulation amount, and h2＞h1＞h3＞0，h1+h2+h3The aging factor coefficient is expressed as the influence degree of the electricity skipping rate, the capacity loss amount and the electricity circulation amount on the aging weight, wherein the electricity skipping rate represents the percentage of the change amount of the electricity of the power battery pack in each equal time period to the unit time, and for example: taking the time period t as 50min, measuring the variation W of the electric quantity of the power battery pack of 50min as 33W, and obtaining the power jump rate
Figure BDA0003165009400000073
The capacity loss amount represents the sum of the charging times and the using times, and the electric quantity circulation amount represents the percentage of the total discharging quantity and the total charging quantity of the power battery pack in each equal time period;
s3: according to the formula
Figure BDA0003165009400000074
n is a positive integer greater than or equal to 1, and first total estimated characteristic quantity data Y' of the power battery pack at a first time level is obtained, wherein the first total estimated characteristic quantity Y is' for measuring the total state of charge accuracy of a battery at a first time level, wherein c1And c2Error coefficients expressed as internal data and external data, respectively, and c1＞c2＞0，c1+c23.2, and the error coefficient is expressed as the influence degree of the internal data and the external data on the first certain feature quantity data;
the first total evaluation quantity Y' of the data processing unit is sent to the data verification unit,
and the data processing unit also compares the O of the power battery pack with each equal interval duration in the second time leveljAnd O'jThe signal is sent to a signal calibration unit;
the signal calibration unit receives internal data O of the power battery pack with equal interval duration in the second time leveljAnd external data O'jCarrying out quantitative calibration and sending the calibrated signal data to a data verification unit, wherein the second time level is represented by the total interval duration adjacent to each equal time period in the first time level, the adjacent interval durations are equal and are the same as the time lengths of the equal time periods, and the signal calibration unit receives internal data O of the power battery pack with the equal interval durations in the second time leveljAnd external data O'jAnd carrying out quantitative calibration, wherein the specific signal calibration operation steps are as follows:
step 1: acquiring data values of internal cause parameters of the power battery pack with equal interval duration in a second time level, comparing current data, voltage data, internal resistance data and working temperature data with preset values of the internal cause parameters respectively, and carrying out mass calibration on the internal cause parameters, wherein when current data I is obtainediGreater than or equal to a preset value q1Then, it is calibrated as the current quality signal, when the current data IiLess than a predetermined value q1Then, it is calibrated as the current poor signal, when the voltage data UiWhen the voltage data U is larger than the maximum value of the preset range or smaller than the minimum value of the preset range, the voltage data U is calibrated to be a voltage inferior signaliWhen the voltage is within the preset range, the voltage is calibrated to be a high-quality voltage signal, and when the voltage is within the preset range, the voltage is calibrated to be a high-quality voltage signalInternal resistance data RiLess than or equal to a preset value q2When the internal resistance data R is high, the internal resistance data R is calibrated to be an internal resistance high-quality signaliGreater than a predetermined value q2Then, the signal is calibrated as the internal resistance poor signal, and when the working temperature data TiWhen the temperature is larger than the maximum value of the preset range or smaller than the minimum value of the preset range, the signal is calibrated to be a working temperature poor signal, and when the working temperature data T isiWhen the signal is within the preset range, the signal is calibrated as a working temperature high-quality signal;
step 2: acquiring data values of external factors of the power battery pack with equal interval duration in a second time level, comparing the aging degree data, the new rate data and the environmental temperature data with preset values respectively, and carrying out grading calibration on the aging degree data, the new rate data and the environmental temperature data, wherein when the aging degree data PiGreater than or equal to a preset value v1When it is, it is calibrated as an aged low-level signal, and when the aged degree data P isiLess than a predetermined value v1Then, it is calibrated as an aging high-grade signal, when the new rate data KiLess than a predetermined value v2Then, it is calibrated as a new low-level signal, when the new rate data K is reachediGreater than or equal to a preset value v2Then it is calibrated as a new high level signal, when the ambient temperature data T'iWhen the data is larger than the maximum value of the preset range or smaller than the minimum value of the preset range, the data is calibrated to be an environment temperature low-level signal, and when the data is the environment temperature data T'iWhen the signal is within the preset range, the signal is calibrated to be an environment temperature advanced signal;
step 3: respectively extracting and identifying the current signal, the voltage signal, the internal resistance signal and the working temperature signal data in Step1, dividing gears according to the degree of conversion, classifying the four signals into a first gear when the four signals extracted and identified at the same time are all high-quality signals, classifying the signals into a second gear when the three signals extracted and identified at the same time are high-quality signals, classifying the signals into a third gear when the two signals extracted and identified at the same time are high-quality signals, and classifying the signals into a fourth gear under other conditions;
step 4: respectively identifying the aging degree signal, the new rate signal and the environment temperature signal data in Step2, and carrying out level division according to the level degree, classifying the signals into a first level when three signals are extracted and identified simultaneously as high-level signals, classifying the signals into a second level when two signals are extracted and identified simultaneously as high-level signals, and classifying the signals into a third level under other conditions;
step 5: scaling the sum of the quantized and scaled good signals over all equal interval durations in the second time stage to G and the sum of the quantized and scaled difference signals to G' according to a formula
Figure BDA0003165009400000091
Determining a second total estimated variable X' of the power battery at a second time level, wherein d1And d2Coefficient of conversion factor expressed as a good semaphore and a difference semaphore, respectively, and d1＞d2＞0，d1+d22.3, the conversion factor coefficient is expressed as the influence degree of the optimal semaphore and the difference semaphore on the second total estimated semaphore;
wherein, the total optimal signal quantity is calibrated to be G equal to (the sum of the numbers of the first gear, the second gear, the third gear, the first gear and the second gear in the materialization calibration and the grading calibration)/(the total number of all the gears + the total number of all the stages), and the total differential signal quantity is calibrated to be G' equal to (the sum of the numbers of the fourth gear and the third gear in the materialization calibration and the grading calibration)/(the total number of all the gears + the total number of all the stages);
the signal calibration unit sends a second total estimated quantity X' of the power battery pack with the second time level to the data verification unit;
the data verification unit verifies and compares the first total estimated quantity Y 'in the first time level obtained by the same power battery pack with the second total estimated quantity X' in the second time level obtained by the same power battery pack, and the specific data verification operation is as follows:
carrying out goodness of fit verification on the data of the first total estimated characteristic quantity Y 'and the second total estimated characteristic quantity X', and verifying the goodness of fit according to a formula
Figure BDA0003165009400000101
When the coincidence value is larger than the preset range W1When the maximum value is less than the preset range W, correct text contents are sequentially generated and transmitted to the data feedback unit, and when the coincidence value is less than the preset range W, the correct text contents are transmitted to the data feedback unit1When the matching value is within the preset range W, the difference text content is generated in sequence and transmitted to the data feedback unit, and when the matching value is within the preset range W, the difference text content is transmitted to the data feedback unit1In the meantime, error text contents are sequentially generated and transmitted to the data feedback unit, wherein correct text contents indicate that the first total estimated feature quantity estimated value is very accurate, difference text contents indicate that the first total estimated feature quantity estimated value has a difference and are temporarily stored in the data cache unit, the data cache unit is used for temporarily storing difference result data and is matched with the data processing unit, the signal calibration unit and the data verification unit for multiple calls, the difference result data indicate abnormal data with large result deviation, and the error text contents indicate that the first total estimated feature quantity estimated value is generally accurate;
the data verification unit respectively sends a very accurate result, a general accurate result and a difference result of the verification to the data feedback unit;
the data feedback unit outputs the received verification result, the output data is sent to a display screen in a text mode, and the text content is very accurate, generally accurate and difference judgment of the estimated value data of the first total estimated characteristic quantity Y', so that researchers can accurately predict the SOC of the mining power battery pack, and the potential safety hazard prediction efficiency of the mining power battery pack is improved;
the above formulas are obtained by collecting a large amount of data and performing software simulation, and the coefficients in the formulas are set by those skilled in the art according to actual conditions.
When the invention is used, the sensor is used for collecting the factor parameters of the power battery pack in various aspects under different time levels and different working conditions, the data obtained in the first time level are subjected to data calibration and formulaic processing, a quantized value first total estimated quantity Y 'of which the state of charge is accurately estimated is obtained, then the data obtained in the second time level are subjected to data calibration, fine division and formulaic processing, a quantized value second total estimated quantity X' of which the state of charge is accurately estimated is obtained, the first total estimated quantity Y 'and the second total estimated quantity X' are compared and verified, the accuracy of the double-quantization state of charge estimation is fed back, and the data result is sent to the display screen, so that researchers can predict and analyze the state of charge of the battery pack, and the comprehensive accurate estimation of the state of charge of the power battery pack is realized under the complicated working conditions, the safety and stability of the mining power battery pack are greatly improved.
The preferred embodiments of the invention disclosed above are intended to be illustrative only. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise forms disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims (6)

1. The system for predicting and feeding back the state of charge of the mining power battery pack is characterized by comprising a data acquisition unit, a data processing unit, a signal calibration unit, a data verification unit, a data cache unit, a data feedback unit and a display screen;
the data acquisition unit is used for capturing and acquiring internal cause parameters and external cause parameters of the power battery pack and sending the internal cause parameters and the external cause parameters to the data processing unit;
the data processing unit carries out the following estimation and characterization quantity calculation operation on the received intrinsic parameters and extrinsic parameters:
s1: acquiring internal cause parameters of the power battery pack in each equal time period in the first time level, wherein the internal cause parameters comprise current data, voltage data, internal resistance data and working temperature data, and respectively marking the internal cause parameters as Ii、Ui、RiAnd TiAccording to the formula
Figure FDA0003165009390000011
Determining internal data O of a power battery pack for equal time periods within a first time classiWherein a is1、a2、a3And a4Respectively expressed as the bias coefficients of current data, voltage data, internal resistance data and operating temperature data, and a3＞a4＞a2＞a1＞0；
S2: acquiring external factor parameters of the power battery pack in each equal time period in the first time level, wherein the external factor parameters comprise aging degree data, new rate data and environment temperature data, and respectively marking the external factor parameters as Pi、KiAnd Ti', according to the formula
Figure FDA0003165009390000012
Obtaining external data O 'of the power battery pack of each equal time slot in the first time level'iWherein b is1、b2And b3Respectively expressed as conversion factor coefficients of aging degree data, new rate data and ambient temperature data, and b1＞b2＞b3＞0；
S3: according to the formula
Figure FDA0003165009390000013
Determining a first total estimated variable Y' of the power battery at a first time level, wherein c1And c2Error coefficients expressed as internal data and external data, respectively, and c1＞c2＞0；
The data processing unit sends the first total estimated characteristic quantity Y' to a data verification unit;
the data processing unit also compares the O of the power battery pack with each equal interval duration in the second time leveljAnd O'jThe signal is sent to a signal calibration unit;
the signal calibration unit receives internal data O of the power battery pack with equal interval duration in the second time leveljAnd external data O'jCarrying out quantitative calibration and calibratingThe calibrated signal data is sent to a data verification unit;
the data verification unit verifies and compares the first total estimated characteristic quantity Y 'obtained at the first time level and the second total estimated characteristic quantity X' obtained at the second time level, and sends a comparison result after verification to the data feedback unit;
and the data feedback unit outputs the received verification result and sends the output data to a display screen in a text mode.
2. The system of claim 1, wherein the aging data comprises a power-skip rate, a capacity loss amount and a power circulation amount, and are respectively designated as Tdi、RhiAnd PsiAccording to the formula
Figure FDA0003165009390000021
Determining aging data P for each equal time segment of the power battery pack within a first time leveliWherein h is1、h2And h3Aging factor coefficients respectively representing the power-skip rate, the capacity loss amount and the electric quantity circulation amount, and h2＞h1＞h3＞0。
3. The system of claim 1, wherein the signal calibration unit is configured to calibrate the internal data O received by the power battery pack for each equal interval duration in the second time stagejAnd external data O'jAnd carrying out quantitative calibration, wherein the specific signal calibration operation steps are as follows:
step 1: acquiring data values of internal cause parameters of the power battery pack with equal interval duration in a second time level, and carrying out materialization calibration on the data values;
step 2: acquiring data values of external cause parameters of the power battery pack within each equal interval time length in a second time level, and carrying out hierarchical calibration on the data values;
step 3: respectively extracting and identifying the current signal, the voltage signal, the internal resistance signal and the working temperature signal data calibrated in Step1, and dividing gears according to the degree of conversion;
step 4: respectively identifying the aging degree signal, the new rate signal and the environment temperature signal data calibrated in Step2, and carrying out level division according to the level degree;
step 5: scaling the sum of the quantized and scaled good signals over all equal interval durations in the second time stage to G and the sum of the quantized and scaled difference signals to G' according to a formula
Figure FDA0003165009390000031
Determining a second total estimated variable X' of the power battery at a second time level, wherein d1And d2Coefficient of conversion factor expressed as a good semaphore and a difference semaphore, respectively, and d1＞d2＞0；
And the signal calibration unit sends the second total estimated quantity X' of the power battery pack with the second time level to the data verification unit.
4. The system of claim 1, wherein the data verification unit verifies and compares the first total estimated quantity Y 'in the first time level and the second total estimated quantity X' in the second time level of the same power battery pack, and the specific data verification operation is as follows:
carrying out goodness of fit verification on the data of the first total estimated characteristic quantity Y 'and the second total estimated characteristic quantity X', and verifying the goodness of fit according to a formula
Figure FDA0003165009390000032
Calculating the matching value Z and the preset range W thereof1Comparing and outputting very accurate, generally accurate and differential results;
the data verification unit respectively sends a very accurate result, a general accurate result and a difference result of the verification to the data feedback unit.
5. The system according to claim 4, wherein the data verification unit is electrically connected to a data cache unit, and the data cache unit is configured to temporarily store the difference result data.
6. The system of claim 3, wherein the sum of the good signals is scaled to G equal to (sum of the numbers of first, second, third, first and second stages in the materialization and classification scale)/(total number of all stages + total number of all stages), and the sum of the difference signals is scaled to G' equal to (sum of the numbers of fourth and third stages in the materialization and classification scale)/(total number of all stages + total number of all stages).
CN202110801923.7A 2021-07-15 2021-07-15 Charge state prediction feedback system of mining power battery pack Withdrawn CN113536235A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202110801923.7A CN113536235A (en) 2021-07-15 2021-07-15 Charge state prediction feedback system of mining power battery pack

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202110801923.7A CN113536235A (en) 2021-07-15 2021-07-15 Charge state prediction feedback system of mining power battery pack

Publications (1)

Publication Number Publication Date
CN113536235A true CN113536235A (en) 2021-10-22

Family

ID=78099546

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202110801923.7A Withdrawn CN113536235A (en) 2021-07-15 2021-07-15 Charge state prediction feedback system of mining power battery pack

Country Status (1)

Country Link
CN (1) CN113536235A (en)

Similar Documents

Publication Publication Date Title
CN111707951B (en) Battery pack consistency evaluation method and system
CN107991623B (en) Battery ampere-hour integral SOC estimation method considering temperature and aging degree
CN108089133B (en) Battery pack consistency detection method and detection device for energy storage system
CN108732510B (en) Lithium ion battery consistency screening and grouping method based on internal characteristics
CN107132481B (en) Method and system for identifying monomer consistency in battery pack
CN108037462A (en) Storage battery health status quantization method and system
CN112180274B (en) Rapid detection and evaluation method for power battery pack
CN111974709B (en) Retired power lithium battery screening method and system based on temperature change cluster analysis
CN110045291B (en) Lithium battery capacity estimation method
CN113109729B (en) Vehicle power battery SOH evaluation method based on accelerated aging test and real vehicle working condition
WO2023124220A1 (en) Vehicle detection method and device
CN115494400B (en) Lithium battery lithium separation state online monitoring method based on ensemble learning
CN115184831B (en) Early warning method for echelon lithium battery pack
CN112051512A (en) Echelon utilization sorting method and energy storage system
Jiang et al. Sorting and grouping optimization method for second-use batteries considering aging mechanism
CN105738828A (en) Battery capacity accurate measurement method
CN114879066A (en) Battery pack consistency evaluation method and system
CN113866655A (en) Power battery capacity assessment method fusing vehicle networking operation data and test data
CN114545275A (en) Indirect prediction method for remaining service life of lithium ion battery
CN109782182A (en) A kind of series-connected cell group energy state On-line Estimation method and apparatus
CN110208717B (en) Power battery service life prediction method based on big data
CN110376527B (en) Estimation method for SOH (state of health) of power battery and electric vehicle
CN113536235A (en) Charge state prediction feedback system of mining power battery pack
CN116826887A (en) Battery equalization method and equalization device
CN116047339A (en) Lithium ion battery pack SOC estimation method and device based on thermoelectric coupling model

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
WW01 Invention patent application withdrawn after publication
WW01 Invention patent application withdrawn after publication

Application publication date: 20211022