CN110879367A - Method for screening echelon recycling scenes of power lithium batteries - Google Patents
Method for screening echelon recycling scenes of power lithium batteries Download PDFInfo
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- CN110879367A CN110879367A CN201910958760.6A CN201910958760A CN110879367A CN 110879367 A CN110879367 A CN 110879367A CN 201910958760 A CN201910958760 A CN 201910958760A CN 110879367 A CN110879367 A CN 110879367A
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- lithium battery
- battery
- internal resistance
- soc
- power
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- 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
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- 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]
- G01R31/367—Software therefor, e.g. for battery testing using modelling or look-up tables
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- 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
Abstract
The invention discloses a power lithium battery echelon recycling scene screening method based on application scene data collection, and aims at the problems that a retired lithium battery is in an off-line state and performance difference exists among single batteries, and the like, by taking ohmic internal resistance of the lithium battery as a basic parameter, a lithium battery performance test working condition suitable for echelon utilization lithium batteries is designed, and by means of health characteristic data extraction based on a lithium battery first-order RC equivalent circuit model and an incremental autoregressive model (I-ARX), three health factors including mean internal resistance, minimum internal resistance and internal resistance state of charge (SOC) are constructed, a health service life model is established, and a lithium battery SOH detection method based on a multi-model data fusion technology is adopted. And the measurement of contact type is not relied on, and the internal structure of the battery can be damaged. The problems that the power lithium battery is difficult to screen, long in detection period and hung upside down in recycling economic benefits due to the fact that the complexity of an energy storage system and the complexity of a power system are not matched at present are solved.
Description
Technical Field
The invention relates to the technical field of gradient utilization of power lithium batteries, in particular to a gradient reuse scene screening method of a power lithium battery based on application scene data collection.
Background
The recovery of the power battery is mainly divided into two cyclic processes of echelon utilization and disassembly recovery, and the recovery cycle of the power battery is started from the echelon utilization. The disassembly and recovery refers to the steps of crushing, disassembling, smelting and the like of the completely scrapped power battery, so that the resources such as nickel, cobalt, lithium and the like are recycled. The life cycle of a power cell typically includes production, use, scrapping, disassembly, and reuse. After the battery capacity of the power battery for the vehicle is reduced to 80%, the charge and discharge performance of the power battery cannot meet the requirement of vehicle driving, and the power battery needs to be scrapped, except that the chemical activity of the power battery is reduced, the chemical components in the battery are not changed, wherein 20% of the capacity can be used in the field with smaller electric quantity requirement, namely the battery capacity is lower than 60% and no longer has use value, so that the battery capacity used by the electric vehicle only accounts for 50% of the available capacity of the power battery in the whole life cycle, if the battery disassembled from the electric vehicle is directly disassembled and recycled, 50% of energy is wasted, and after the battery is recombined, the battery is applied to the occasions with lower electric energy requirement than the vehicle in a gradient manner, so that the full utilization of the battery; the power battery with shorter recycling life and less than 60 percent of capacity does not have use value any more, the battery needs to be disassembled and recycled, valuable metals and materials are extracted, and then the recycled metals and materials are applied to the production of a battery core, a module and a system, so that the whole life cycle of the power battery forms a closed loop state.
Firstly, in the product structure and production process design of the power battery, in order to improve the working reliability of the battery pack, a plurality of enterprises adopt a laser welding process to connect the batteries in series or adopt a bolt fastening method. The difficulty of the gradient utilization of the power battery is formed by the connecting joint, and the cost of a user for reassembling the battery pack by adopting an old battery is overlarge, so that the gradient utilization of the power battery is hindered.
Secondly, the echelon utilization field of the power lithium battery is relatively complex, the quality of the retired battery is different, and various problems of safety, consistency, technical performance, economical efficiency and the like of the power lithium battery need to be solved.
Finally, the energy storage battery and the power battery applied to echelon utilization have different attention points in the aspect of technical performance, and the system complexity faced by the energy storage system and the power system is different, particularly after long-term use, the battery consistency is reduced in a nonlinear way, so that the utilization of the power echelon battery is more similar to a false proposition, a large amount of screening work is carried out on the batteries with different consistencies, and the economy of the power lithium battery used in echelon utilization is questioned in the industry.
Disclosure of Invention
The invention aims to provide a power lithium battery echelon recycling scene screening method based on application scene data collection, and aims to solve the problems in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme: a power lithium battery echelon recycling scene screening method based on application scene data collection comprises the following specific steps:
the method comprises the following steps that firstly, the intelligent matching algorithm function of a server side is carried through the data collection function (detailed in figure 1) of a BMS chip in a battery pack and a charge-discharge control algorithm;
secondly, a lithium battery SOH off-line detection means is utilized in a gradient manner, the designed lithium battery testing working condition takes a dynamic internal resistance test as a target, the testing working condition is short in time, and the detection and screening work can be completed on the batch of retired lithium battery packs within 20 minutes; three health factors including mean internal resistance, minimum internal resistance and internal resistance-SOC curves are constructed by adopting a performance test method based on a designed lithium battery, and then three health life models are established.
Thirdly, controlling the SOCvs OCV curve of the power battery in use to be about 2-3mV in the SOC range from 70% to 95%, wherein the measurement error of the voltage sensor has 3-4 mV;
and fourthly, intentionally enabling the initial SOC to have 20% of errors in batch lithium battery algorithm matching, and correcting the 20% of errors through intelligent matching and collection of battery use historical data. Without error correction, the SOC follows the SOCI curve. The SOC output by the algorithm is CombinedSOC, i.e., the blue solid line in the figure. The callated SOC is the true SOC that is back-inferred from the last verification. (see FIG. 2 for details)
Compared with the prior art, the invention has the beneficial effects that: screening methods used in the prior art are more or less related to contact measurement of electrical parameters of power lithium batteries, such as detection of open-circuit voltage and internal resistance, and require a long charging and discharging process for the batteries; on one hand, the measurement of the parameters may cause the change and damage of the internal structure of the lithium battery, and on the other hand, the charging and discharging processes of the lithium battery can be completed only in several hours, so that the consumed time and labor cost are high, and the economic benefit of the recycling and echelon utilization of the commercial lithium battery is limited.
The invention aims to provide a screening method for gradient utilization of a power lithium battery based on practical dimensionality, and solve the problems that the traditional contact type measurement of the capacity and internal resistance parameters of the lithium battery in the prior art causes secondary loss to the lithium battery and the screening efficiency is low. The evaluation method based on the multi-model data fusion technology is beneficial to ensuring the reliability and accuracy of predicting the SOH of the lithium battery by utilizing the gradient, and compared with the traditional prediction method, the evaluation method does not depend on contact measurement any more and possibly damages the internal structure of the battery on the premise of risk. The problems that the power lithium battery is difficult to screen, long in detection period and hung upside down in recycling economic benefits due to the fact that the complexity of an energy storage system and the complexity of a power system are not matched at present are solved.
Drawings
FIG. 1 is a schematic view of the structure of the inspection apparatus of the present invention;
FIG. 2 is a SOCvs OCV graph of the present invention;
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious 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 and 2, the present invention provides: a power lithium battery echelon recycling scene screening method based on application scene data collection comprises the following specific steps:
the method comprises the following steps that firstly, the intelligent matching algorithm function of a server side is carried through the data collection function (detailed in figure 1) of a BMS chip in a battery pack and a charge-discharge control algorithm;
secondly, a lithium battery SOH off-line detection means is utilized in a gradient manner, the designed lithium battery testing working condition takes a dynamic internal resistance test as a target, the testing working condition is short in time, and the detection and screening work can be completed on the batch of retired lithium battery packs within 20 minutes; by adopting the performance test method based on the designed lithium battery, the method constructsMean internal resistance, minimum internal resistance and internal resistance-SOC curveThree health factors, and then three health life models are established.
Thirdly, controlling the SOCvs OCV curve of the power battery in use to be about 2-3mV in the SOC range from 70% to 95%, wherein the measurement error of the voltage sensor has 3-4 mV;
and fourthly, intentionally enabling the initial SOC to have 20% of errors in batch lithium battery algorithm matching, and correcting the 20% of errors through intelligent matching and collection of battery use historical data. Without error correction, the SOC follows the SOCI curve. The SOC output by the algorithm is CombinedSOC, i.e., the blue solid line in the figure. The callated SOC is the true SOC that is back-inferred from the last verification. (see FIG. 2 for details)
The working principle is as follows: the invention provides a power lithium battery echelon recycling scene screening method based on application scene data collection, aiming at the problems that a retired lithium battery is in an off-line state and performance difference exists among single batteries, and the like, the lithium battery is designed to be suitable for a echelon utilization lithium battery performance test working condition by taking ohmic internal resistance of a lithium battery as a basic parameter, and a health characteristic data extraction method based on a lithium battery first-order RC equivalent circuit model and an incremental autoregressive model (I-ARX) is used for constructing three health factors of mean internal resistance, minimum internal resistance and internal resistance state of charge (SOC), establishing a health service life model and a lithium battery SOH detection method based on a multi-model data fusion technology.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (1)
1. The method for screening the power lithium battery echelon recycling scene is characterized by comprising the following specific steps of:
the method comprises the following steps that firstly, an intelligent matching algorithm function of a server side is carried through a data collection function and a charge-discharge control algorithm of a BMS chip in a battery pack;
secondly, a lithium battery SOH off-line detection means is utilized in a gradient manner, the designed lithium battery testing working condition takes a dynamic internal resistance test as a target, the testing working condition is short in time, and the detection and screening work can be completed on the batch of retired lithium battery packs within 20 minutes; three health factors including mean internal resistance, minimum internal resistance and an internal resistance-SOC curve are constructed by adopting a performance test method based on a designed lithium battery, and then three health life models are established;
thirdly, controlling the SOCvs OCV curve of the power battery in use to be about 2-3mV in the SOC range from 70% to 95%, wherein the measurement error of the voltage sensor has 3-4 mV;
fourthly, in batch lithium battery algorithm matching, the initial SOC intentionally has an error of 20%, and the error of 20% is corrected through intelligent matching and collection of battery use historical data; if the error correction function is not available, the SOC can follow the curve of the SOCI; the SOC output by the algorithm is CombinedSOC, namely a blue solid line in the graph; the callated SOC is the true SOC that is back-inferred from the last verification.
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| CN201910958760.6A CN110879367A (en) | 2019-10-10 | 2019-10-10 | Method for screening echelon recycling scenes of power lithium batteries |
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| CN201910958760.6A CN110879367A (en) | 2019-10-10 | 2019-10-10 | Method for screening echelon recycling scenes of power lithium batteries |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111812538A (en) * | 2020-07-22 | 2020-10-23 | 兰州兰石恩力微电网有限公司 | Power battery evaluation system |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111812538A (en) * | 2020-07-22 | 2020-10-23 | 兰州兰石恩力微电网有限公司 | Power battery evaluation system |
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Application publication date: 20200313 |
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| WW01 | Invention patent application withdrawn after publication |