CN114415032A - Power battery safety detection method, system and storage medium - Google Patents
Power battery safety detection method, system and storage medium Download PDFInfo
- Publication number
- CN114415032A CN114415032A CN202210089340.0A CN202210089340A CN114415032A CN 114415032 A CN114415032 A CN 114415032A CN 202210089340 A CN202210089340 A CN 202210089340A CN 114415032 A CN114415032 A CN 114415032A
- Authority
- CN
- China
- Prior art keywords
- power battery
- data
- safety
- module
- voltage
- 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
Links
Images
Classifications
-
- 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
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L58/00—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles
- B60L58/10—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling batteries
- B60L58/16—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling batteries responding to battery ageing, e.g. to the number of charging cycles or the state of health [SoH]
-
- 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]
- G01R31/392—Determining battery ageing or deterioration, e.g. state of health
-
- 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
- G06F17/15—Correlation function computation including computation of convolution operations
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/60—Other road transportation technologies with climate change mitigation effect
- Y02T10/70—Energy storage systems for electromobility, e.g. batteries
Abstract
The invention relates to the technical field of power battery safety detection, and discloses a power battery safety detection method, a system and a storage medium. The method has the advantages of quickly and accurately detecting the health state of the power battery, guaranteeing the use safety of the power battery and improving the driving safety of the electric automobile.
Description
Technical Field
The invention relates to the technical field of power battery safety detection, in particular to a power battery safety detection method, a power battery safety detection system and a storage medium.
Background
The new energy automobile has various reasons for accidents, and may be sudden accidents or results of gradually accumulated risks, but any accident problem is reflected on a data level, that is, the risk of the new energy automobile is certainly reflected on the data level, so that the accident occurrence rate can be greatly reduced if the safety of the automobile can be judged through data. In the running process of the electric automobile, the working condition is extremely complex, more contingencies exist in voltage change, and more noises exist, so that the health state of the power battery in the running process is not easily measured.
For solving this problem, there is a power battery package security monitoring system for new energy automobile among the prior art, including the ambient temperature sensor who is used for detecting the inside temperature of power battery package, the smoke transducer who is used for detecting the inside smog concentration of power battery package, be used for detecting the weeping sensor of power battery package internal cooling liquid level height, be used for detecting the first temperature sensor of liquid cooling system water inlet department coolant temperature and be used for detecting the second temperature sensor of liquid cooling system water outlet department coolant temperature. The power battery pack safety monitoring system for the new energy automobile can detect the temperature, the liquid leakage height and the smoke concentration of a liquid cooling system of the power battery pack in all aspects, improve the safety prevention level of the power battery pack and reduce the operation risk of the power battery pack.
Although the scheme can realize the safety detection of the power battery, the safety detection is obtained by analyzing based on the collected internal electrochemical parameters of the power battery, and in the daily use process of the power battery, the internal electrochemical data cannot be checked due to safety problems, and the whole process is complex and complicated, so that the health state of the power battery cannot be simply and quickly judged.
Disclosure of Invention
The invention aims to provide a method, a system and a storage medium for detecting the safety of a power battery, so as to solve the technical problem that the health state of the power battery is simply and quickly judged.
In order to achieve the purpose, the invention adopts the following technical scheme: a power battery safety detection method comprises the following steps:
step S1, collecting original message data of the power battery to form a first data set, and analyzing the first data set to obtain battery signal data;
step S2, preprocessing the battery signal data to finally obtain effective data of the power battery;
step S3, selecting single voltage data of the power battery in a discharging state from the effective data, and subtracting the minimum voltage from the maximum voltage at each moment to obtain a range voltage;
step S4, filtering the range voltage by using a convolution mean filter, and removing an end point effect at the same time;
step S5, determining the size of a window, and dividing the maximum value of the filtered range voltage by the minimum value in the window to obtain an entropy value;
and step S6, uniformly setting the entropy value of the maximum range voltage value smaller than the standard value as 1, then obtaining the entropy value change condition of the power battery, and evaluating the safety of the power battery.
The principle and the advantages of the scheme are as follows: during actual application, historical operating data of the power battery are collected, the collected data are processed, the range voltage is calculated, the entropy value of the power battery is calculated by utilizing the range voltage, and then the safety of the power battery is evaluated, so that the health state of the power battery is clearly known. Compared with the prior art, the safety detection method has the advantages that the safety detection of the power battery can be rapidly completed, so that a user can know the health state of the power battery in real time, and the driving safety of the electric automobile is guaranteed.
Preferably, as an improvement, the battery signal data is preprocessed by cleaning the battery signal data, deleting abnormal characters and invalid data, and rejecting data with a voltage value greater than 6V or less than 1V.
Has the advantages that: the collected data may contain a plurality of invalid data and abnormal characters, so that the invalid data and the abnormal characters are deleted, the data calculation amount can be reduced, the safety detection speed of the power battery is improved, the data can be cleaned, the reliability of the data can be further improved, and the accuracy of the safety detection of the power battery is ensured.
Preferably, as an improvement, the valid data includes three signals of Time, Charge-discharge state Charge _ Status, and voltage matrix V.
Has the advantages that: through screening, the analysis object that selects these three signal data of time, charge-discharge state and voltage matrix as power battery security and detect not only can accurate analysis go out power battery's health condition, but also can effectively reduce the kind and the quantity of analysis data, reduces the data calculation analysis volume, effectively improves the overall efficiency of analytic process.
Preferably, as a modification, the standard value is 0.05V.
Has the advantages that: through analysis, the standard value is set to be 0.05V, false alarm can be eliminated, the situation that entropy value is abnormal and large due to too small denominator under the condition that the pressure difference is not large originally is avoided, the accuracy of the entropy value result is improved, and therefore the accurate judgment of the health state of the power battery is guaranteed.
Preferably, as an improvement, the safety of the power battery is evaluated by arranging the calculated entropy values at fixed intervals, and if the entropy values are always in a stable state, determining that the safety of the power battery is qualified, and if the entropy values are changed violently, determining that the safety of the power battery is unqualified.
Has the advantages that: the collected voltage data may fluctuate to a certain extent, but after the entropy value is calculated, if the safety of the power battery is qualified, the entropy value is still in a stable state and does not fluctuate as the voltage data, and if the power battery is unqualified, the entropy value will change violently, so that the health state of the power battery can be obviously judged.
Preferably, as a modification, the fixed interval is 10 seconds.
Has the advantages that: the time of the fixed interval is set to 10 seconds, so that the effective quantity of the extremely-poor voltage can be provided, the overlarge data taking quantity is avoided, the accuracy of safety evaluation of the power battery can be guaranteed while the small data calculation and analysis quantity is guaranteed.
The invention also provides a power battery safety detection system, which comprises a processor module, a data acquisition module, a pre-processing module, a filtering module and a display module, wherein the data acquisition module, the pre-processing module, the filtering module and the display module are respectively connected with the processor module;
the data acquisition module is used for acquiring historical operating data of the power battery to form a first data set and sending the first data set to the preprocessing module;
the preprocessing module is used for analyzing the first data set to obtain battery signal data, preprocessing the battery signal data to obtain effective data and sending the effective data to the filtering module;
the filtering module is used for filtering the effective data of the power battery and removing the endpoint effect;
the processor module comprises an entropy calculation unit and a data analysis unit, wherein the entropy calculation unit is used for calculating the monomer voltage data of the power battery in a discharge state to obtain a range voltage, and dividing the maximum value of the range voltage by the minimum value to obtain an entropy; the data analysis unit is used for analyzing the safety state of the power battery according to the entropy change condition of the power battery to obtain a safety evaluation result of the power battery;
and the display module is used for displaying the safety evaluation result of the power battery.
Has the advantages that: by the system, the power battery safety detection method is applied, the acquired historical operation data of the power battery are utilized, the maximum value and the minimum value of the range voltage are utilized to calculate the entropy value after the range voltage is calculated, and the safety of the power battery is evaluated through the stability of the entropy value, so that the health state of the power battery is evaluated quickly and accurately, and the use safety of the electric automobile is guaranteed.
Preferably, as an improvement, the filtering module further includes a convolution mean filter, and the convolution mean filter is used for performing filtering processing on the effective data of the power battery.
Has the advantages that: a convolution mean filter is preset in a filtering module, the filter utilizes a convolution operation principle and adopts a matrix calculation mode, and the speed of data filtering can be effectively guaranteed, so that the data processing efficiency is improved, and the safety of the power battery is quickly evaluated.
Preferably, as an improvement, the system further comprises a reminding module, and the reminding module is used for sending reminding information to a user when the safety of the power battery is detected to be unqualified.
Has the advantages that: through increasing the reminding module, can in time send the assessment result for the user after the power battery security assessment is accomplished, make the user know power battery's health status very first time to can make next step and use the car planning to power battery's health status, guarantee driving safety.
The invention also provides a power battery safety detection storage medium, wherein the storage medium is stored with computer-executable instructions, and the computer-executable instructions are used for enabling a computer to execute the power battery safety detection method.
Has the advantages that: through the arranged storage medium, a computer program for executing the power battery safety evaluation method can be stored, so that the health state of the power battery can be quickly and effectively detected, an accurate safety evaluation result is obtained, the use safety risk of the power battery is reduced, and the safety of using the electric automobile by a user is ensured.
Drawings
Fig. 1 is a schematic view of a testing process of a power battery safety detection method according to a first embodiment of the present invention.
Fig. 2 is a system diagram of a power battery safety detection system according to a first embodiment of the present invention.
Detailed Description
The following is further detailed by way of specific embodiments:
the reference numbers in the drawings of the specification include: the device comprises a processor module 1, a data acquisition module 2, a preprocessing module 3, a filtering module 4, a display module 5, an entropy value calculation unit 6 and a data analysis unit 7.
The first embodiment is as follows:
this embodiment is substantially as shown in figure 1: a power battery safety detection method comprises the following steps:
step S1, collecting original message data of the power battery to form a first data set, and analyzing the first data set to obtain battery signal data;
step S2, preprocessing the battery signal data, cleaning the battery signal data, deleting abnormal characters and invalid data, and eliminating data with a voltage value larger than 6V or smaller than 1V to finally obtain valid data of the power battery, wherein the valid data comprises three signals of Time, Charge-discharge state _ Status and voltage matrix V;
step S3, selecting single voltage data of the power battery in a discharging state from the effective data, and subtracting the minimum voltage from the maximum voltage at each moment to obtain a range voltage;
step S4, filtering the range voltage by using a convolution mean filter, and removing an end point effect at the same time;
step S5, determining the window size, and dividing the maximum value of the filtered range voltage by the minimum value in the window to obtain an entropy value, wherein the entropy value is defined by the formula: svdiff ═ max { v _ max (t) -v _ min (t)) }/min { v _ max (t) -v _ min (t));
step S6, uniformly setting the entropy value of the maximum range voltage value smaller than the standard value as 1, then obtaining the entropy value change condition of the power battery, evaluating the safety of the power battery, arranging the calculated entropy values according to the fixed interval time, judging that the safety of the power battery is qualified if the entropy value is always in a stable state, and judging that the safety of the power battery is unqualified if the entropy value is violently changed (namely the maximum value of the entropy value exceeds 5).
As shown in fig. 2, the invention also provides a power battery safety detection system using the power battery safety detection method, which comprises a processor module 1, and a data acquisition module 2, a pre-processing module 3, a filtering module 4 and a display module 5 which are respectively connected with the processor module 1;
the data acquisition module 2 is used for acquiring historical operating data of the power battery to form a first data set and sending the first data set to the preprocessing module 3;
the preprocessing module 3 is used for analyzing the first data set to obtain battery signal data, preprocessing the battery signal data to obtain effective data, and sending the effective data to the filtering module 4;
the filtering module 4 comprises a convolution mean filter, and the convolution mean filter is mainly responsible for filtering the effective data of the power battery and removing the endpoint effect;
the processor module 1 comprises an entropy calculation unit 6 and a data analysis unit 7, wherein the entropy calculation unit 6 is used for calculating the monomer voltage data of the power battery in a discharge state to obtain a range voltage, and dividing the maximum value of the range voltage by the minimum value to obtain an entropy; the data analysis unit 7 is used for analyzing the safety state of the power battery according to the entropy change condition of the power battery to obtain a safety evaluation result of the power battery;
and the display module 5 is used for displaying the safety evaluation result of the power battery.
The invention also provides a storage medium for detecting the safety of the power battery, wherein the storage medium is stored with computer-executable instructions, the computer-executable instructions are used for enabling a computer to execute the power battery safety detection method, and the storage medium comprises a U disk, a mobile hard disk, an optical disk, a mechanical hard disk, a solid state hard disk and a computer memory. The storage medium is selected to be computer memory in this embodiment.
The specific implementation process of this embodiment is as follows:
firstly, a data acquisition module 2 is used for acquiring historical operating data of a power battery, then the acquired historical operating data is sent to a preprocessing module 3 for processing, the preprocessing module 3 firstly analyzes the historical operating data to obtain corresponding battery signal data, then the battery signal data is cleaned, abnormal characters and invalid data, such as NAN, are deleted, data with a voltage value larger than 6V or smaller than 1V are eliminated, and finally effective data of the power battery, including three signals of Time, Charge-discharge state _ Status and voltage matrix V, are obtained.
And secondly, selecting single voltage data of the power battery in a discharging state from the effective data to calculate, reserving a corresponding Time and a voltage matrix V when the Charge-Status is equal to 3, and subtracting the minimum voltage from the maximum voltage at each moment to obtain the range voltage.
And thirdly, filtering the range voltage by using a convolution mean filter, removing an end effect, determining the size of a window as a charging process, dividing the maximum value of the filtered range voltage by the minimum value of the range voltage to obtain an entropy value according to a definition formula Svdiff ═ max { v _ max (t) -v _ min (t)) }/min { v _ max (t) -v _ min (t)) } of the entropy value.
And fourthly, uniformly setting the entropy values corresponding to the maximum range voltage of less than 0.05V as 1, then obtaining the change condition of the entropy values of the power battery, arranging the calculated entropy values at intervals of 10 seconds, judging that the safety of the power battery is qualified if the entropy values are always in a stable state, and judging that the safety of the power battery is unqualified if the entropy values are severely changed.
With the development of new energy vehicles, the enhancement of environmental awareness of consumers and the improvement of acceptance of new energy vehicles, the amount of new energy vehicles in the market is increasing year by year, and with the popularization and large-area application of new energy vehicles, some corresponding problems are gradually exposed, such as the problem of difficult charging of new energy vehicles, the problem of greatly reduced duration in winter, and the problem of safety of power batteries, wherein the problem of safety of power batteries is most concerned, because power batteries are the most important part of the whole new energy vehicles, once the power batteries are failed, the damage of the vehicles is caused, and dangerous accidents such as fire and explosion are caused, so that the safety detection aiming at the power batteries is a key focus object in the whole industry at present.
The conventional power battery safety detection method in the current market is characterized in that the whole power battery is detached and then detected by using special detection equipment, or a sensor is used for collecting electrochemical parameters inside a power battery pack to analyze, so that the safety of the power battery is detected, although the detection of the power battery can be completed by the two modes, the whole process is more complicated, the spent time is more, and the detection method is not beneficial to users of most electric vehicles.
In the scheme, two key factors of rapidness and convenience of safety detection of the power battery are fully considered, the power battery does not need to be disassembled for detection, electrochemical data in the power battery does not need to be collected for analysis, only daily operation data of the power battery needs to be collected, operations such as cleaning and invalid data removing are carried out on the collected data, then after the extreme difference voltage of the voltage is obtained by using the single voltage data in the discharge state, the maximum value of the extreme difference voltage is divided by the minimum value of the extreme difference voltage to obtain the entropy value, finally, the entropy value change condition of fixed interval time is counted, if the entropy value is always in a stable state, the power battery is free of safety problem at present, and if the entropy value is changed violently, the safety problem of the health state of the power battery is indicated, and further detection is needed. Through the mode, the health state of the power battery can be analyzed quickly and accurately only by analyzing the running data of the power battery by using the set entropy model, so that the majority of electric vehicle users can conveniently adopt the method to carry out daily detection, the detection efficiency can be ensured, the accuracy of the detection result can be ensured, the daily use of the electric vehicle can not be influenced, and the use safety and the use experience of the electric vehicle are greatly improved.
Example two:
this embodiment is basically the same as the first embodiment, except that: the power battery safety detection system further comprises a reminding module, the reminding module is connected with a vehicle machine system of the electric vehicle, and when the power battery safety is detected to be unqualified, reminding information is sent to the vehicle machine system of the electric vehicle, so that the power battery safety detection system plays a role in reminding a user.
The specific implementation process of this embodiment is the same as that of the first embodiment, except that:
and fourthly, uniformly setting the entropy value corresponding to the maximum value of the range voltage smaller than 0.05V to 1, then obtaining the entropy value change condition of the power battery, arranging the calculated entropy values according to the interval time of 10 seconds, judging that the safety of the power battery is qualified if the entropy values are always in a stable state, judging that the safety of the power battery is unqualified if the entropy values are severely changed, and after the detection is finished, sending the reminding information and the detection result to a vehicle-mounted machine system of the electric vehicle by a reminding module if the safety of the power battery is unqualified, so that a user can receive the reminding information in time and take subsequent measures.
Through the warning module that sets up, and remind module and car machine headtotail, can in time send power battery's security testing result for the customer and know, the customer of being convenient for knows power battery's health status in real time, also can in time take corresponding measure when power battery goes out safety problem, guarantee driving safety.
Example three:
this embodiment is basically the same as the first embodiment, except that: the power battery safety detection system also comprises a prediction module which is used for analyzing the collected operation data and predicting the time of the power battery with the safety problem and suggesting the time of the next safety detection to the user by combining the safety detection result of the power battery.
The specific implementation process of this embodiment is the same as that of the first embodiment, except that: adding a step:
and fifthly, after the safety detection result of the power battery is obtained, starting a prediction module, calculating and analyzing the time of the power battery with the safety problem by utilizing the collected operation data and combining the safety detection result of the power battery, and providing the predictive time for the next safety detection to the user.
Through the prediction module that sets up, can calculate the periodic trend that analyzes out power battery safety and stability fast to provide a prediction time point for the user, the user of being convenient for has a definite time to accomplish next detection, fully ensured power battery's security.
The foregoing is merely an example of the present invention and common general knowledge in the art of designing and/or characterizing particular aspects and/or features is not described in any greater detail herein. It should be noted that, for those skilled in the art, without departing from the technical solution of the present invention, several variations and modifications can be made, which should also be regarded as the protection scope of the present invention, and these will not affect the effect of the implementation of the present invention and the practicability of the patent. The scope of the claims of the present application shall be determined by the contents of the claims, and the description of the embodiments and the like in the specification shall be used to explain the contents of the claims.
Claims (10)
1. A power battery safety detection method is characterized in that: the method comprises the following steps:
step S1, collecting original message data of the power battery to form a first data set, and analyzing the first data set to obtain battery signal data;
step S2, preprocessing the battery signal data to finally obtain effective data of the power battery;
step S3, selecting single voltage data of the power battery in a discharging state from the effective data, and subtracting the minimum voltage from the maximum voltage at each moment to obtain a range voltage;
step S4, filtering the range voltage by using a convolution mean filter, and removing an end point effect at the same time;
step S5, determining the size of a window, and dividing the maximum value of the filtered range voltage by the minimum value in the window to obtain an entropy value;
and step S6, uniformly setting the entropy value of the maximum range voltage value smaller than the standard value as 1, then obtaining the entropy value change condition of the power battery, and evaluating the safety of the power battery.
2. The power battery safety detection method according to claim 1, characterized in that: the battery signal data are preprocessed by cleaning the battery signal data, deleting abnormal characters and invalid data, and removing data with the voltage value larger than 6V or smaller than 1V.
3. The power battery safety detection method according to claim 1, characterized in that: the valid data comprises three signals of Time, Charge-discharge state Charge _ Status and voltage matrix V.
4. The power battery safety detection method according to claim 1, characterized in that: the standard value is 0.05V.
5. The power battery safety detection method according to claim 1, characterized in that: and evaluating the safety of the power battery by arranging the calculated entropy values at fixed intervals, judging that the safety of the power battery is qualified if the entropy values are always in a stable state, and judging that the safety of the power battery is unqualified if the entropy values are severely changed.
6. The power battery safety detection method according to claim 5, characterized in that: the fixed interval was 10 seconds.
7. The utility model provides a power battery safety detecting system which characterized in that: the device comprises a processor module, a data acquisition module, a pre-processing module, a filtering module and a display module, wherein the data acquisition module, the pre-processing module, the filtering module and the display module are respectively connected with the processor module;
the data acquisition module is used for acquiring historical operating data of the power battery to form a first data set and sending the first data set to the preprocessing module;
the preprocessing module is used for analyzing the first data set to obtain battery signal data, preprocessing the battery signal data to obtain effective data and sending the effective data to the filtering module;
the filtering module is used for filtering the effective data of the power battery and removing the endpoint effect;
the processor module comprises an entropy calculation unit and a data analysis unit, wherein the entropy calculation unit is used for calculating the monomer voltage data of the power battery in a discharge state to obtain a range voltage, and dividing the maximum value of the range voltage by the minimum value to obtain an entropy; the data analysis unit is used for analyzing the safety state of the power battery according to the entropy change condition of the power battery to obtain a safety evaluation result of the power battery;
and the display module is used for displaying the safety evaluation result of the power battery.
8. The power battery safety detection system according to claim 7, wherein: the filtering module further comprises a convolution mean filter, and the convolution mean filter is used for filtering the effective data of the power battery.
9. The power battery safety detection system according to claim 7, wherein: the power battery safety detection device further comprises a reminding module, and the reminding module is used for sending reminding information to a user when the safety of the power battery is detected to be unqualified.
10. A power battery safety detection storage medium is characterized in that: the storage medium stores computer-executable instructions for causing a computer to execute a power battery safety detection method according to any one of claims 1 to 6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210089340.0A CN114415032A (en) | 2022-01-25 | 2022-01-25 | Power battery safety detection method, system and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210089340.0A CN114415032A (en) | 2022-01-25 | 2022-01-25 | Power battery safety detection method, system and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114415032A true CN114415032A (en) | 2022-04-29 |
Family
ID=81276499
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210089340.0A Pending CN114415032A (en) | 2022-01-25 | 2022-01-25 | Power battery safety detection method, system and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114415032A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115615343A (en) * | 2022-12-05 | 2023-01-17 | 中汽数据有限公司 | Power battery safety monitoring method, electronic equipment and storage medium |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20160018345A1 (en) * | 2014-07-21 | 2016-01-21 | Samsung Electronics Co., Ltd | Method and apparatus for detecting abnormal state of battery |
| CN110045298A (en) * | 2019-05-06 | 2019-07-23 | 重庆大学 | A kind of diagnostic method of power battery pack parameter inconsistency |
| CN110068769A (en) * | 2019-05-07 | 2019-07-30 | 北京长城华冠汽车科技股份有限公司 | The test method and system of power battery |
| CN112038716A (en) * | 2020-08-14 | 2020-12-04 | 合肥国轩高科动力能源有限公司 | Early warning method for thermal runaway of lithium ion battery pack |
| CN112487031A (en) * | 2020-11-27 | 2021-03-12 | 江西江铃集团新能源汽车有限公司 | Single battery fault detection method and device, readable storage medium and electronic equipment |
| CN113030763A (en) * | 2021-02-20 | 2021-06-25 | 武汉云衡智能科技有限公司 | Potential risk diagnosis system for consistency difference of power batteries for vehicles |
| CN113858956A (en) * | 2021-09-29 | 2021-12-31 | 北理新源(佛山)信息科技有限公司 | New energy automobile data acquisition and processing method system |
| CN113933732A (en) * | 2021-10-13 | 2022-01-14 | 中国汽车工程研究院股份有限公司 | New energy automobile power battery health state analysis method, system and storage medium |
-
2022
- 2022-01-25 CN CN202210089340.0A patent/CN114415032A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20160018345A1 (en) * | 2014-07-21 | 2016-01-21 | Samsung Electronics Co., Ltd | Method and apparatus for detecting abnormal state of battery |
| CN110045298A (en) * | 2019-05-06 | 2019-07-23 | 重庆大学 | A kind of diagnostic method of power battery pack parameter inconsistency |
| CN110068769A (en) * | 2019-05-07 | 2019-07-30 | 北京长城华冠汽车科技股份有限公司 | The test method and system of power battery |
| CN112038716A (en) * | 2020-08-14 | 2020-12-04 | 合肥国轩高科动力能源有限公司 | Early warning method for thermal runaway of lithium ion battery pack |
| CN112487031A (en) * | 2020-11-27 | 2021-03-12 | 江西江铃集团新能源汽车有限公司 | Single battery fault detection method and device, readable storage medium and electronic equipment |
| CN113030763A (en) * | 2021-02-20 | 2021-06-25 | 武汉云衡智能科技有限公司 | Potential risk diagnosis system for consistency difference of power batteries for vehicles |
| CN113858956A (en) * | 2021-09-29 | 2021-12-31 | 北理新源(佛山)信息科技有限公司 | New energy automobile data acquisition and processing method system |
| CN113933732A (en) * | 2021-10-13 | 2022-01-14 | 中国汽车工程研究院股份有限公司 | New energy automobile power battery health state analysis method, system and storage medium |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115615343A (en) * | 2022-12-05 | 2023-01-17 | 中汽数据有限公司 | Power battery safety monitoring method, electronic equipment and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110018425B (en) | Power battery fault diagnosis method and system | |
| CN106353687B (en) | Lithium battery health state assessment method | |
| CN110109029B (en) | Battery cell lithium analysis parameter detection method and device, battery cell detection system and computer readable storage medium | |
| CN111823952B (en) | Battery cell temperature diagnosis method, storage medium and electronic equipment | |
| CN114430080B (en) | Power battery cell abnormal self-discharge identification method based on operation data | |
| CN109014544B (en) | Micro resistance spot welding quality on-line monitoring method | |
| CN108521155B (en) | Electric vehicle charging early warning method and system | |
| CN113687234B (en) | Battery abnormality recognition method, apparatus, device, medium, and program product | |
| CN113933732A (en) | New energy automobile power battery health state analysis method, system and storage medium | |
| CN110749829B (en) | Power supply equipment abnormality detection method and device | |
| CN112487031A (en) | Single battery fault detection method and device, readable storage medium and electronic equipment | |
| CN114415032A (en) | Power battery safety detection method, system and storage medium | |
| CN115648944A (en) | Early warning method, device, equipment and storage medium for power battery | |
| CN111157908A (en) | Battery health degree prediction method based on big data machine learning | |
| CN116125300A (en) | Battery pack abnormality monitoring method and device, electronic equipment and storage medium | |
| CN116150572A (en) | Automobile battery monomer consistency defect evaluation method based on cluster analysis | |
| CN108872780A (en) | Charge livewire work detection, system and the terminal device reconnoitred | |
| CN116008820B (en) | Method, device and medium for detecting inconsistency of vehicle battery cells | |
| CN113095739A (en) | Power grid data anomaly detection method and device | |
| CN116923188A (en) | Charging protection system of new energy vehicle | |
| CN111551856B (en) | Vehicle storage battery state detection method and device, computer equipment and storage medium | |
| CN109696635B (en) | Battery charging state judgment method and management system based on Internet of vehicles application | |
| CN115219903A (en) | Battery self-discharge rate abnormity judgment method and device based on Internet of vehicles data analysis | |
| CN115236525A (en) | Echelon battery screening method, device and medium | |
| WO2022155791A1 (en) | Method for analyzing charging status of electric motorcycle on basis of analysis of electrical feature sequence |
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 |
Application publication date: 20220429 |
|
| RJ01 | Rejection of invention patent application after publication |