CN114312319B - Battery safety monitoring method based on voltage accumulation value, storage medium and vehicle - Google Patents
Battery safety monitoring method based on voltage accumulation value, storage medium and vehicle Download PDFInfo
- Publication number
- CN114312319B CN114312319B CN202111532891.1A CN202111532891A CN114312319B CN 114312319 B CN114312319 B CN 114312319B CN 202111532891 A CN202111532891 A CN 202111532891A CN 114312319 B CN114312319 B CN 114312319B
- Authority
- CN
- China
- Prior art keywords
- battery
- value
- voltage
- data
- vehicle
- 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.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 24
- 238000012544 monitoring process Methods 0.000 title claims abstract description 21
- 238000009825 accumulation Methods 0.000 title claims abstract description 17
- 230000002159 abnormal effect Effects 0.000 claims abstract description 26
- 230000005856 abnormality Effects 0.000 claims abstract description 11
- 239000000178 monomer Substances 0.000 claims description 14
- 230000001186 cumulative effect Effects 0.000 claims description 11
- 238000004140 cleaning Methods 0.000 claims description 6
- 230000001174 ascending effect Effects 0.000 claims description 3
- 238000007599 discharging Methods 0.000 claims description 3
- 238000007781 pre-processing Methods 0.000 claims description 3
- 238000012163 sequencing technique Methods 0.000 abstract description 2
- 238000005516 engineering process Methods 0.000 description 7
- 238000005111 flow chemistry technique Methods 0.000 description 4
- HBBGRARXTFLTSG-UHFFFAOYSA-N Lithium ion Chemical compound [Li+] HBBGRARXTFLTSG-UHFFFAOYSA-N 0.000 description 2
- 229910001416 lithium ion Inorganic materials 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 230000017525 heat dissipation Effects 0.000 description 1
- 230000020169 heat generation Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
Images
Classifications
-
- 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 discloses a battery safety monitoring method based on a voltage accumulation value, a storage medium and a vehicle. And the abnormal strategy is judged by sequencing the voltage of the battery cells, so that the abnormality of the battery cells of the vehicle is found in real time in advance, and the thermal runaway and other battery safety accidents of the battery of the vehicle are avoided.
Description
Technical Field
The present invention relates to a battery safety monitoring technology, and in particular, to a battery safety monitoring method based on a voltage integrated value, a storage medium, and a vehicle.
Background
The lithium ion battery becomes the first choice battery of the electric automobile due to the factors of high energy density, long cycle life and the like. But high energy densities also present significant thermal safety issues, often manifested as thermal runaway. Thermal runaway of lithium ion batteries is mainly due to the fact that internal heat generation is far higher than heat dissipation rate, a large amount of heat is accumulated in the battery, and therefore chain reaction is caused, and the battery fires and explodes. In recent years, a problem of ignition of a plurality of electric vehicles has occurred, and most of the problems are related to thermal safety of batteries.
Since many factors affect the thermal safety of the battery, both internal and external factors of the battery may be affected. At present, aiming at the existing thermal safety monitoring system of the electric automobile, the data condition of the battery monomer is not monitored in real time, so that the early warning delay on the thermal safety problem of the battery is caused to be common. The battery is in a dangerous state, and safety accidents such as fire of the electric automobile are likely to happen. Therefore, early, rapid and accurate early warning of the safety of the battery is of great significance to safety accidents, personal safety and property safety.
Disclosure of Invention
The battery safety monitoring method based on the voltage accumulation value disclosed by the invention utilizes a big data real-time flow processing and distributed computing technology to monitor, calculate and analyze the characteristic performance related to the thermal safety of the battery in real time, finds out the battery cell which is about to be abnormal in real time through a battery cell voltage accumulation abnormality judgment strategy, and sends out early warning information in advance before the battery cell has abnormal thermal safety problems, thereby realizing the monitoring and early warning of the thermal safety of each battery cell.
The storage medium disclosed by the invention is stored with one or more programs, the one or more programs can be executed by one or more processors to realize the steps of a battery abnormality real-time monitoring method based on voltage accumulation, and the characteristic performance related to the thermal safety of the battery is monitored and calculated and analyzed in real time by utilizing big data real-time flow processing and distributed computing technology, the abnormal battery cells which are about to be abnormal are found in real time through a battery cell voltage accumulation abnormality judgment strategy, and early warning information is sent in advance before the abnormal problem of the thermal safety of the battery cells occurs, so that the monitoring and early warning of the thermal safety of each cell are realized.
The vehicle disclosed by the invention adopts the storage medium, utilizes the big data real-time flow processing and distributed computing technology to monitor, calculate and analyze the characteristic performance related to the thermal safety of the battery in real time, and finds out the battery cell which is about to be abnormal in real time through the battery cell voltage accumulation abnormality judgment strategy, and sends out early warning information in advance before the thermal safety problem abnormality of the battery cell occurs, thereby realizing the monitoring and early warning of the thermal safety of each battery cell.
The technical scheme of the invention is as follows:
the invention discloses a battery safety monitoring method based on a voltage accumulation value, which comprises the following steps:
step S1: and collecting the voltage and the number data of each single cell of the vehicle battery in real time.
Step S2: preprocessing battery monomer data; and cleaning the data of the collected real-time battery cell voltage data to remove abnormal data.
Step S3: and extracting the differential pressure data of the battery cells in real time according to the differential pressure value of the battery cells and the comprehensive battery cells of the vehicle.
Step S4: and a certain sliding time window range is reserved before the current moment, and the accumulated data of the differential pressure of the battery cells are accumulated and calculated.
Step S5: and calculating the current accumulated differential pressure drop value of the battery monomer, and judging that the battery is abnormal if the accumulated differential pressure drop value exceeds a set value.
Step S6: and according to the result of the step S5, finding out the vehicle with abnormal battery.
Further, the step S2 specifically includes the following steps:
s2-1: and (3) cleaning the data of the collected real-time battery cell voltage data to remove null value, value exceeding normal interval, repeated value and redundant value abnormal value data.
S2-2: and (3) carrying out ascending order on the real-time battery cell voltage data processed in the step (S2-1) according to a time sequence.
S2-3: and (3) carrying out travel judgment on the data processed in the step S2-2, marking a complete charging and discharging process as a travel, increasing the travel number of the corresponding voltage data of the vehicle by 1, and marking the travel number of the first voltage data of the vehicle as the travel 1.
Further, the step S3 specifically includes the following steps:
s3-1: and (3) reading in the real-time battery cell voltage data processed in the step (2).
S3-2: calculating the voltage data differential of the real-time battery cells:
wherein ,
for the pressure difference of the battery cell i at time t, +.>
For the voltage value of cell i at time t, < >>
For the vehicle, the battery cell voltage is integrated, +.>
The voltage median of all the battery cells of the vehicle at the time t, which represents the current time, can be selected.
Further, the step S4 specifically includes the following steps:
s4-1: a sliding time window M of the range of the number of the battery cell voltage data is set.
S4-2: it is checked whether the number of voltage data per battery cell exceeds the size of the sliding time window M at time t.
S4-3: and (3) exceeding the sliding time window M, and accumulating and calculating the accumulated data of the cell differential pressure:
wherein ,
for the accumulated pressure difference of the battery cell i at the time t-M+1 to t,
the differential pressure of the vehicle battery cell i at the times t, t-1, t-2 to t-M+1 is represented, and M represents the size of the sliding time window.
Further, the step S5 specifically includes the following steps:
s5-1: and judging whether the stroke number of the battery monomer i at the moment t exceeds a stroke threshold N.
S5-2: if S5-1 is satisfied, judging the accumulated pressure difference value p of the battery cell i at the moment t t i Whether or not it is smaller than the local minimum value of the cumulative differential pressure value of the battery cells i
S5-3: if the S5-2 condition is satisfied, calculating a cumulative differential pressure drop value:
if it is
If the voltage is larger than the set value Q, judging that the voltage of the battery cell is abnormal; wherein, the set value Q is a positive value.
Further, the step S5-2 accumulates the local minimum value of the differential pressure value
Obtained as follows: />
S5-2-1: recording the lowest value of the accumulated pressure differences of the battery monomers in each stroke
S5-2-2: acquiring the lowest value of the accumulated pressure differences of all the single batteries of N strokes before the moment t
Wherein i is the number of the battery cell, and j is the number of the current journey at the moment t.
S5-2-3: calculating the local minimum value of the accumulated pressure difference value of the battery cell i at the moment t:
further, M is more than or equal to 5 and less than or equal to 100, N is more than or equal to 2 and less than or equal to 10, Q is more than or equal to 0.01 and less than or equal to 0.5, and the unit of Q is V.
The invention also discloses a storage medium storing computer executable instructions, the storage medium storing one or more programs, the one or more programs being executable by one or more processors to implement the steps of a method for monitoring battery anomalies based on voltage accumulation as set forth in claims 1-6.
The invention also discloses a vehicle employing a storage medium storing computer executable instructions as claimed in claim 8.
The invention has the beneficial technical effects that: and the voltage of the battery cell of the vehicle is monitored by utilizing a big data real-time flow processing technology and collecting signal data on a T-BOX in the vehicle in real time, and the battery cell voltage data is filtered and sequenced by utilizing a distributed real-time calculation technology. And the abnormal strategy is judged by sequencing the voltage of the battery cells, so that the abnormality of the battery cells of the vehicle is found in real time in advance, and the thermal runaway and other battery safety accidents of the battery of the vehicle are avoided.
Drawings
Fig. 1 is a schematic diagram of a battery safety monitoring method based on a voltage integrated value according to the present invention.
Detailed Description
The present invention will be described in detail with reference to the accompanying drawings.
As shown in fig. 1, the battery safety monitoring method based on the voltage accumulation value disclosed by the invention comprises the following steps:
step S1: and collecting the voltage and the number data of each single cell of the vehicle battery in real time.
In the step, data transmitted by the T-BOX of the vehicle are collected in real time through a big data distributed data stream reading method. The method for reading the data stream can be realized by using technical frameworks such as a Flink, spark Streaming and the like. Besides collecting the voltage and the number data of each single cell of the battery, a frame number, a total voltage and the like can be added.
Step S2: preprocessing battery monomer data; and cleaning the data of the collected real-time battery cell voltage data to remove abnormal data.
The step S2 specifically comprises the following steps:
s2-1: and (3) cleaning the data of the collected real-time battery cell voltage data to remove null value, value exceeding normal interval, repeated value and redundant value abnormal value data.
For example, the voltage value of the single battery collected at a certain moment is not in the interval range of the voltage value, which belongs to the value exceeding the normal interval and should be removed. Also for example, the data collected within 10 seconds are all identical, which belongs to the repeated redundancy value, which should be removed. These abnormal data may interfere with the determination of the abnormal cell voltage, eventually resulting in a decrease in the accuracy of the determination result, and therefore, it is necessary to check these abnormal data.
S2-2: and (3) carrying out ascending order on the real-time battery cell voltage data processed in the step (S2-1) according to a time sequence.
S2-3: and (3) carrying out travel judgment on the data processed in the step S2-2, marking a complete charging and discharging process as a travel, increasing the travel number of the corresponding voltage data of the vehicle by 1, and marking the travel number of the first voltage data of the vehicle as the travel 1.
Step S3: and extracting the differential pressure data of the battery cells in real time according to the differential pressure value of the battery cells and the comprehensive battery cells of the vehicle.
The step S3 specifically comprises the following steps:
the method comprises the steps of performing trending treatment on battery cell voltage data by using a distributed real-time computing technology to reduce the influence of cell charge-discharge voltage change on a judgment result, and specifically comprises the following steps:
s3-1: and (3) reading in the real-time battery cell voltage data processed in the step (2).
S3-2: calculating the voltage data differential of the real-time battery cells:
wherein ,
for the pressure difference of the battery cell i at time t, +.>
For the voltage value of cell i at time t, < >>
For the vehicle, the battery cell voltage is integrated, +.>
The voltage median of all the battery cells of the vehicle at the time t, which represents the current time, can be selected.
Step S4: and a certain sliding time window range is reserved before the current moment, and the accumulated data of the differential pressure of the battery cells are accumulated and calculated.
The step S4 specifically comprises the following steps:
s4-1: setting a sliding time window M of the range of the number of the single battery voltage data; the value range can be: m is more than or equal to 5 and less than or equal to 100.
S4-2: it is checked whether the number of voltage data per battery cell exceeds the size of the sliding time window M at time t.
S4-3: and (3) exceeding the sliding time window M, and accumulating and calculating the accumulated data of the cell differential pressure:
wherein ,
for the accumulated pressure difference of the battery cell i at the time t-M+1 to t,
the differential pressure of the vehicle battery cell i at the times t, t-1, t-2 to t-M+1 is represented, and M represents the size of the sliding time window.
Step S5: and calculating the current accumulated differential pressure drop value of the battery monomer, and judging that the battery is abnormal if the accumulated differential pressure drop value exceeds a set value. The step S5 specifically comprises the following steps:
s5-1: judging whether the stroke number of the battery monomer i exceeds a stroke threshold value N at the moment t, wherein the value range of N is more than or equal to 2 and less than or equal to 10.
S5-2: if S5-1 is satisfied, judging the accumulated pressure difference value p of the battery cell i at the moment t t i Whether or not it is smaller than the local minimum value of the cumulative differential pressure value of the battery cells i
Local minimum value of cumulative differential pressure value
Obtained as follows:
s5-2-1: recording the lowest value of the accumulated pressure differences of the battery monomers in each stroke
S5-2-2: acquiring the lowest value of the accumulated pressure differences of all the single batteries of N strokes before the moment t
Wherein i is the cell numberJ is the travel number of the current travel at the time t.
S5-2-3: calculating the local minimum value of the accumulated pressure difference value of the battery cell i at the moment t:
s5-3: if the S5-2 condition is satisfied, calculating a cumulative differential pressure drop value:
if it is
If the voltage is larger than the set value Q, judging that the voltage of the battery cell is abnormal; wherein, the set value Q is positive, the unit of the set value Q is V, and the value range of the set value Q is more than or equal to 0.01 and less than or equal to 0.5.
Step S6: and according to the result of the step S5, finding out the vehicle with abnormal battery.
The invention also discloses a storage medium storing computer executable instructions, the storage medium storing one or more programs, the one or more programs being executable by one or more processors to implement the steps of the method for monitoring battery abnormality in real time based on voltage accumulation. The storage medium may be Random Access Memory (RAM), memory, read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
The invention also discloses a vehicle, which adopts the storage medium with the computer executable instructions.
The foregoing describes in detail preferred embodiments of the present invention. It should be understood that numerous modifications and variations can be made in accordance with the concepts of the invention by one of ordinary skill in the art without undue burden. Therefore, all technical solutions which can be obtained by logic analysis, reasoning or limited experiments based on the prior art by the person skilled in the art according to the inventive concept shall be within the scope of protection defined by the claims.
Claims (6)
1. The battery safety monitoring method based on the voltage accumulation value is characterized by comprising the following steps of: comprises the steps of,
step S1: collecting the voltage and the number data of each single cell of the vehicle battery in real time;
step S2: preprocessing battery monomer data; carrying out data cleaning on the collected real-time battery cell voltage data to remove abnormal data;
step S3: according to the voltage difference value between the battery cell voltage and the comprehensive battery cell voltage of the vehicle, extracting the voltage difference data of the battery cell in real time, and specifically comprising the following steps:
s3-1: reading in real-time battery cell voltage data processed in the step 2;
s3-2: calculating the voltage data differential of the real-time battery cells:
wherein ,
for the pressure difference of the battery cell i at time t, +.>
For the voltage value of cell i at time t, < >>
For the vehicle, the battery cell voltage is integrated, +.>
The voltage median of all the battery monomers of the vehicle at the time t which represents the current time can be selected;
step S4: the method for cumulatively calculating the cumulative data of the differential pressure of the battery cells within a certain sliding time window range before the current moment specifically comprises the following steps:
s4-1: setting a sliding time window M of the range of the number of the single battery voltage data;
s4-2: checking whether the number of the single battery voltage data of each vehicle exceeds the size of a sliding time window M at the moment t;
s4-3: and (3) exceeding the sliding time window M, and accumulating and calculating the accumulated data of the cell differential pressure:
wherein ,
for the cumulative pressure difference of the battery cells i at the times t-M+1 to t, +.>
Representing the pressure difference of the vehicle battery unit i at the moments t, t-1, t-2 and t-M+1, wherein M represents the size of a sliding time window;
step S5: calculating the current cumulative differential pressure reduction value of the battery monomer, and judging that the battery is abnormal if the current cumulative differential pressure reduction value exceeds a set value, wherein the method specifically comprises the following steps of:
s5-1: judging whether the stroke number of the battery monomer i at the moment t exceeds a stroke threshold N;
s5-2: if S5-1 is satisfied, judging the accumulated pressure difference value of the battery cell i at the moment t
Whether it is smaller than the local minimum value of the cumulative differential pressure value of the battery cells i +.>
S5-3: if the S5-2 condition is satisfied, calculating a cumulative differential pressure drop value:
if it is
If the voltage is larger than the set value Q, judging that the voltage of the battery cell is abnormal; wherein, the set value Q is a positive value;
step S6: and according to the result of the step S5, finding out the vehicle with abnormal battery.
2. The method for monitoring the battery abnormality in real time based on the voltage accumulation according to claim 1, wherein: the step S2 specifically includes the following steps,
s2-1: data cleaning is carried out on the collected real-time battery cell voltage data, and null value, value exceeding normal interval, repeated value and redundant value abnormal value data are removed;
s2-2: the real-time battery cell voltage data processed in the step S2-1 are sequenced in an ascending order according to the time sequence;
s2-3: and (3) carrying out travel judgment on the data processed in the step S2-2, marking a complete charging and discharging process as a travel, increasing the travel number of the corresponding voltage data of the vehicle by 1, and marking the travel number of the first voltage data of the vehicle as the travel 1.
3. The method for monitoring the battery abnormality in real time based on the voltage accumulation according to claim 1, wherein: the step S5-2 is to accumulate the local minimum value of the differential pressure value
Obtained as follows:
s5-2-1: recording the lowest value of the accumulated pressure differences of the battery monomers in each stroke
S5-2-2: acquiring the lowest value of the accumulated pressure differences of all the single batteries of N strokes before the moment t
Wherein i is the number of the battery cell, j is the number of the current travel where the moment t is;
s5-2-3: calculating the local minimum value of the accumulated pressure difference value of the battery cell i at the moment t:
4. the method for monitoring the battery abnormality in real time based on voltage accumulation according to claim 3, wherein: m is more than or equal to 5 and less than or equal to 100, N is more than or equal to 2 and less than or equal to 10, Q is more than or equal to 0.01 and less than or equal to 0.5, and the unit of Q is V.
5. A storage medium storing computer-executable instructions, wherein the storage medium stores one or more programs, the one or more programs being executable by one or more processors to implement the steps of a voltage accumulation based battery anomaly real-time monitoring method as recited in any one of claims 1-4.
6. A vehicle, characterized in that: a storage medium storing computer-executable instructions as recited in claim 5 is employed.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111532891.1A CN114312319B (en) | 2021-12-15 | 2021-12-15 | Battery safety monitoring method based on voltage accumulation value, storage medium and vehicle |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111532891.1A CN114312319B (en) | 2021-12-15 | 2021-12-15 | Battery safety monitoring method based on voltage accumulation value, storage medium and vehicle |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114312319A CN114312319A (en) | 2022-04-12 |
| CN114312319B true CN114312319B (en) | 2023-06-02 |
Family
ID=81052724
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111532891.1A Active CN114312319B (en) | 2021-12-15 | 2021-12-15 | Battery safety monitoring method based on voltage accumulation value, storage medium and vehicle |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114312319B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115588244A (en) * | 2022-09-29 | 2023-01-10 | 重庆长安新能源汽车科技有限公司 | Internet of vehicles big data real-time analysis method, device, equipment and medium |
| CN116834606B (en) * | 2023-08-09 | 2024-02-23 | 力高(山东)新能源技术股份有限公司 | Processing method for monomer voltage during AFE monomer acquisition disconnection |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2005108543A (en) * | 2003-09-29 | 2005-04-21 | Yuasa Corp | Storage battery monitoring system, and method of monitoring storage battery |
| WO2016006462A1 (en) * | 2014-07-07 | 2016-01-14 | 日立オートモティブシステムズ株式会社 | Battery control device |
| WO2018051885A1 (en) * | 2016-09-13 | 2018-03-22 | パナソニックＩｐマネジメント株式会社 | Management device, and power storage system |
| CN110794305A (en) * | 2019-10-14 | 2020-02-14 | 北京理工大学 | Power battery fault diagnosis method and system |
| CN112514138A (en) * | 2018-07-25 | 2021-03-16 | 松下知识产权经营株式会社 | Management device and power supply system |
| CN112526376A (en) * | 2020-12-01 | 2021-03-19 | 江西江铃集团新能源汽车有限公司 | Method and device for estimating abnormity of single automobile battery |
| CN112946485A (en) * | 2021-02-09 | 2021-06-11 | 江西江铃集团新能源汽车有限公司 | Vehicle battery detection method, storage medium and device |
| CN112937303A (en) * | 2021-02-08 | 2021-06-11 | 重庆长安新能源汽车科技有限公司 | Real-time online early warning method and system after battery overheating |
| CN112986834A (en) * | 2021-02-26 | 2021-06-18 | 重庆长安新能源汽车科技有限公司 | Battery safety monitoring method and system based on voltage sequencing |
| CN113777515A (en) * | 2021-09-13 | 2021-12-10 | 国网江西省电力有限公司供电服务管理中心 | Electric vehicle charging safety early warning method |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20200143019A (en) * | 2019-06-14 | 2020-12-23 | 현대자동차주식회사 | Apparatus for diagnosing battery for vehicle and method for diagnosing battery thereof and vehicle including the same |
-
2021
- 2021-12-15 CN CN202111532891.1A patent/CN114312319B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2005108543A (en) * | 2003-09-29 | 2005-04-21 | Yuasa Corp | Storage battery monitoring system, and method of monitoring storage battery |
| WO2016006462A1 (en) * | 2014-07-07 | 2016-01-14 | 日立オートモティブシステムズ株式会社 | Battery control device |
| WO2018051885A1 (en) * | 2016-09-13 | 2018-03-22 | パナソニックＩｐマネジメント株式会社 | Management device, and power storage system |
| CN112514138A (en) * | 2018-07-25 | 2021-03-16 | 松下知识产权经营株式会社 | Management device and power supply system |
| CN110794305A (en) * | 2019-10-14 | 2020-02-14 | 北京理工大学 | Power battery fault diagnosis method and system |
| CN112526376A (en) * | 2020-12-01 | 2021-03-19 | 江西江铃集团新能源汽车有限公司 | Method and device for estimating abnormity of single automobile battery |
| CN112937303A (en) * | 2021-02-08 | 2021-06-11 | 重庆长安新能源汽车科技有限公司 | Real-time online early warning method and system after battery overheating |
| CN112946485A (en) * | 2021-02-09 | 2021-06-11 | 江西江铃集团新能源汽车有限公司 | Vehicle battery detection method, storage medium and device |
| CN112986834A (en) * | 2021-02-26 | 2021-06-18 | 重庆长安新能源汽车科技有限公司 | Battery safety monitoring method and system based on voltage sequencing |
| CN113777515A (en) * | 2021-09-13 | 2021-12-10 | 国网江西省电力有限公司供电服务管理中心 | Electric vehicle charging safety early warning method |
Non-Patent Citations (3)
| Title |
|---|
| 基于大数据的电动汽车动力电池系统故障诊断方法研究;赵洋;中国优秀硕士学位论文全文数据库工程科技Ⅱ辑(第07期);全文 * |
| 基于数据驱动的纯电动汽车动力电池故障诊断方法研究;孙振宇;中国优秀硕士学位论文全文数据库工程科技Ⅱ辑(第07期);全文 * |
| 基于运行数据的异常电池诊断及实现;李欢;中国优秀硕士学位论文全文数据库工程科技Ⅱ辑(第12期);全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114312319A (en) | 2022-04-12 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN114312319B (en) | Battery safety monitoring method based on voltage accumulation value, storage medium and vehicle | |
| CN112986834B (en) | Battery safety monitoring method and system based on voltage sequencing | |
| CN112937303B (en) | Real-time online early warning method and system after battery overheating | |
| CN105789716B (en) | A kind of broad sense battery management system | |
| CN110828915B (en) | Early warning method for explosion of power lithium ion battery | |
| CN110376530B (en) | Device and method for detecting short circuit in battery | |
| CN112038716B (en) | Early warning method for thermal runaway of lithium ion battery pack | |
| CN113721156A (en) | Multi-time scale comprehensive early warning method for lithium iron phosphate battery | |
| CN111554066A (en) | Fire early warning device and method for energy storage battery compartment | |
| CN114942387B (en) | Real data-based power battery fault online detection method and system | |
| CN114487856A (en) | Thermal runaway early warning method and system for battery replacement station | |
| CN114290954A (en) | Battery consistency monitoring method and system based on differential pressure analysis and vehicle | |
| CN115384311A (en) | Method, system, vehicle and storage medium for diagnosing insulation fault of power battery | |
| CN113219353A (en) | BMS-based thermal runaway control method and system | |
| CN113295296A (en) | Battery thermal runaway detection method and battery management system | |
| CN114274777A (en) | Battery abnormity monitoring method and system and vehicle | |
| CN114361616A (en) | Battery thermal runaway early warning method and system and storage medium | |
| CN114734873A (en) | Power battery unit thermal runaway early warning method based on cloud online data | |
| Hong et al. | Collision-Caused thermal runaway investigation of li-ion battery in Real-World electric vehicles | |
| CN115958957B (en) | Method and system for predicting charging overheat faults of power battery of electric automobile | |
| CN105730270B (en) | The method and system of safe prediction is carried out according to the variation of battery status amount and external environment | |
| Zhang et al. | Multi-dimension fault diagnosis of battery system in electric vehicles based on real-world thermal runaway vehicle data | |
| CN116565354A (en) | Fault grading diagnosis early warning method, system and equipment for electrochemical energy storage system | |
| CN111474491A (en) | Satellite power supply abnormity detection method based on pattern analysis | |
| CN115128473A (en) | Lithium analysis monitoring method and device for lithium battery |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CP01 | Change in the name or title of a patent holder | ||
| CP01 | Change in the name or title of a patent holder |
Address after: 401133 room 208, 2 house, 39 Yonghe Road, Yu Zui Town, Jiangbei District, Chongqing Patentee after: Deep Blue Automotive Technology Co.,Ltd. Address before: 401133 room 208, 2 house, 39 Yonghe Road, Yu Zui Town, Jiangbei District, Chongqing Patentee before: CHONGQING CHANGAN NEW ENERGY AUTOMOBILE TECHNOLOGY Co.,Ltd. |