CN110970679B - Battery pack temperature sensor rationality diagnosis method based on thermal symmetry - Google Patents
Battery pack temperature sensor rationality diagnosis method based on thermal symmetryDownload PDFInfo
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- CN110970679B CN110970679BCN201911366109.6ACN201911366109ACN110970679BCN 110970679 BCN110970679 BCN 110970679BCN 201911366109 ACN201911366109 ACN 201911366109ACN 110970679 BCN110970679 BCN 110970679B
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- 238000000034methodMethods0.000titleclaimsabstractdescription11
- 238000003745diagnosisMethods0.000titleclaimsabstractdescription9
- 238000012360testing methodMethods0.000claimsabstractdescription35
- 238000004088simulationMethods0.000claimsabstractdescription13
- 238000007599dischargingMethods0.000claimsabstractdescription4
- 238000012795verificationMethods0.000claimsabstractdescription3
- 230000009897systematic effectEffects0.000claimsdescription12
- 238000002405diagnostic procedureMethods0.000claims2
- 230000002159abnormal effectEffects0.000abstractdescription2
- 238000007726management methodMethods0.000description6
- 238000012544monitoring processMethods0.000description2
- HBBGRARXTFLTSG-UHFFFAOYSA-NLithium ionChemical compound[Li+]HBBGRARXTFLTSG-UHFFFAOYSA-N0.000description1
- 230000005856abnormalityEffects0.000description1
- 238000011161developmentMethods0.000description1
- 239000000446fuelSubstances0.000description1
- 229910001416lithium ionInorganic materials0.000description1
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- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
- H01M10/00—Secondary cells; Manufacture thereof
- H01M10/42—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
- H01M10/48—Accumulators combined with arrangements for measuring, testing or indicating the condition of cells, e.g. the level or density of the electrolyte
- H01M10/486—Accumulators combined with arrangements for measuring, testing or indicating the condition of cells, e.g. the level or density of the electrolyte for measuring temperature
- 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
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02E60/10—Energy storage using batteries
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Abstract
Description
Technical Field
The invention relates to a power battery system of an electric automobile in a new energy automobile, in particular to a battery pack temperature sensor rationality diagnosis method based on thermal symmetry.
Background
The performance of lithium ion power battery systems is deeply affected by temperature. The capacity and the charge-discharge multiplying power of the battery cell can be seriously influenced by over-low temperature; the service life of the battery is rapidly reduced due to overhigh temperature, and even the thermal runaway of a battery core is caused; the power performance of the system is severely restricted by overlarge temperature difference. Along with the requirements of customers on the dynamic property and the charging time of the new energy automobile are higher and higher, the requirements on the capacity and the multiplying power of the battery cell are higher and higher, and the requirements on the battery cell temperature management and control brought along with the requirements are also stricter and stricter. Therefore, it is also increasingly important and urgent to enhance temperature management of the battery system.
In the current battery system temperature management method, the monitoring and diagnosis of some temperatures are mainly carried out on the highest temperature, the lowest temperature, the temperature difference, the average temperature and the like collected in a battery pack. The method is based on data processing, lacks consideration on specific components and structural arrangement forms in the battery system, and has certain limitation on temperature monitoring. For example, a difference value between Tmax and Tmin is used as a temperature control method, Tmax is the highest temperature of the battery assembly, Tmin is the lowest temperature of the battery assembly, and due to the influences of spatial arrangement, heat source distribution and the like of the battery assembly, the difference value even reaches more than 10 ℃ but still cannot be used as a basis for judging an abnormality.
The development of a power battery platform of an electric automobile is the work focus of all current manufacturers. Compared with the traditional fuel vehicle-based battery system, the brand-new platform battery system has the characteristics of simple structure, high modularization degree and the like. Specifically, the platform batteries are usually arranged in order, even symmetrically; the heat source is concentrated, namely the high-voltage box, the main sub-board and the components which are used as the heat source are designed in a concentrated mode, and the influence on the temperature of the module is small. Therefore, the temperature field distribution in the battery pack of the battery system is simple and uniform, and even a plurality of thermally symmetrical modules exist, and based on the characteristics, the temperature management can be further optimized.
Disclosure of Invention
The invention aims to provide a battery pack temperature sensor rationality diagnosis method based on thermal symmetry, which can accurately diagnose the numerical value collection rationality of a temperature sensor and effectively monitor the collection abnormity of the temperature sensor.
The invention relates to a battery pack temperature sensor rationality diagnosis method based on thermal symmetry, which comprises the following steps:
s1, establishing a battery pack thermal simulation analysis model, and preliminarily determining a plurality of groups of thermal symmetry points by analyzing the core group structure arrangement characteristics, the heat source distribution condition and the thermal management system flow channel condition of the battery pack, wherein each group of thermal symmetry points comprises two test points;
s2, verifying the multiple groups of thermal symmetry points obtained in S1 to obtain temperature characteristics of the test points in thermal simulation tests under different charging and discharging working conditions, and if the temperature characteristics of the two test points of the single group of thermal symmetry points are the same or the difference value of the two test points is within a set range, the verification is passed; if the difference value of the two test points of the single group of thermal symmetry points is out of the set range, returning to S1 to re-select the test points;
s3, according to the positions of a plurality of groups of thermal symmetry points in the battery pack thermal simulation analysis model verified by S2, arranging temperature sensors at corresponding positions of the battery pack, calculating a temperature difference value | T1-T2| acquired by two temperature sensors in each group of thermal symmetry points, comparing the temperature difference value | T1-T2| with a difference threshold TBD, and judging the rationality of the temperature sensors in each group of thermal symmetry points.
Further, the fault state is displayed when the temperature difference | T1-T2| is greater than the difference threshold TBD in the S3.
Further, the difference threshold TBD of each group of thermal symmetry points in S3 is determined according to the systematic temperature difference of the arrangement points of the two temperature sensors, the temperature drift deviation of the two temperature sensors, and the acquisition accuracy; the system temperature difference comprises the temperature field distribution difference and the thermal conductivity difference of two temperature sensor arrangement points.
According to the invention, multiple groups of thermal symmetry points are determined through a thermal simulation analysis model and a thermal simulation test, the battery pack arranges temperature sensors according to the obtained thermal symmetry points, compares a temperature difference value | T1-T2| acquired by two temperature sensors in the same group with a difference threshold TBD, judges the rationality of the temperature sensors of each group of thermal symmetry points, and displays a fault state when the temperature difference value | T1-T2| is greater than the difference threshold TBD, so that the rationality of the temperature sensors can be accurately diagnosed, and the abnormal acquisition of the temperature sensors can be effectively monitored.
Drawings
Fig. 1 is a schematic view of the structure of a battery pack according to the present invention.
In the figure, 1-module, 2-high voltage box, 3-main board, 4-test point.
Detailed Description
The present invention will be described in detail with reference to the accompanying drawings.
A battery pack temperature sensor rationality diagnosis method based on thermal symmetry comprises the following steps:
s1, establishing a battery pack thermal simulation analysis model, and preliminarily determining a plurality of groups of thermal symmetry points by analyzing the core group structure arrangement characteristics, the heat source distribution condition and the thermal management system flow channel condition of the battery pack, wherein each group of thermal symmetry points comprises two test points.
And S2, verifying the multiple groups of thermal symmetry points obtained in the S1 to obtain the temperature characteristics of the test points in thermal simulation tests under different charging and discharging working conditions, if the temperature characteristics of the two test points of the single group of thermal symmetry points are the same or the difference value of the two test points is within a set range, verifying the two test points of the same group of thermal symmetry points to pass, wherein the two test points in the same group of thermal symmetry points have symmetry in space and structural arrangement, the two test points have the same thermal performance parameters such as external heat exchange and thermal resistance, and the influence of an external heat source on the two test points is the same, namely the two test points keep the temperature and the temperature change conditions consistent under any working conditions of the battery pack. If the difference value of the two test points of the single group of thermal symmetry points is out of the set range, returning to S1 to select the test point again.
And S3, verifying the positions of five groups of thermal symmetry points in the passed battery pack thermal simulation analysis model according to S2, referring to fig. 1, arranging five groups of temperature sensors on atest point 4 at the corresponding position of abattery pack 1, wherein each group comprises two temperature sensors, the high-voltage box 2 and themain partition plate 3 outside thebattery pack 1 are used as heat sources to have the same influence on the temperature sensors in the same group, and calculating the temperature difference value acquired by the two temperature sensors in each group of thermal symmetry points.
Calculating a temperature difference value | T1-T2| of the first group of temperature sensors, comparing the temperature difference value | T1-T2| with a difference threshold TBD1, and determining a difference threshold TBD1 according to the systematic temperature difference of the arrangement points of the first group of two temperature sensors, the temperature drift deviation of the first group of two temperature sensors and the acquisition precision; the systematic temperature difference comprises a temperature field distribution difference and a thermal conductivity difference of the first set of two temperature sensor arrangement points. If the absolute value of T1-T2 is more than TBD1, a fault state is displayed, and if the absolute value of T1-T2 is less than or equal to TBD1, the two temperature sensors in the first group normally acquire.
Calculating a temperature difference value | T3-T4| of the second group of temperature sensors, comparing the temperature difference value | T3-T4| with a difference threshold TBD2, and determining a difference threshold TBD2 according to the systematic temperature difference of the arrangement points of the second group of two temperature sensors, the temperature drift deviation of the second group of two temperature sensors and the acquisition precision; the systematic temperature difference comprises a temperature field distribution difference and a thermal conductivity difference of the second group of two temperature sensor arrangement points. If the absolute value of T3-T4 is more than TBD2, a fault state is displayed, and if the absolute value of T3-T4 is less than or equal to TBD2, the acquisition of the two temperature sensors in the second group is normal.
Calculating a temperature difference value | T5-T6| of the third group of temperature sensors, comparing the temperature difference value | T5-T6| with a difference threshold TBD3, and determining a difference threshold TBD3 according to the systematic temperature difference of the arrangement points of the third group of two temperature sensors, the temperature drift deviation of the third group of two temperature sensors and the acquisition precision; the systematic temperature difference comprises the temperature field distribution difference and the thermal conductivity difference of the third group of two temperature sensor arrangement points. If the absolute value of T5-T6 is more than TBD3, a fault state is displayed, and if the absolute value of T5-T6 is less than or equal to TBD3, the acquisition of the two temperature sensors in the third group is normal.
Calculating a temperature difference value | T7-T8| of the fourth group of temperature sensors, comparing the temperature difference value | T7-T8| with a difference threshold TBD4, and determining a difference threshold TBD4 according to the systematic temperature difference of arrangement points of the fourth group of two temperature sensors, the temperature drift deviation of the fourth group of two temperature sensors and the acquisition precision; the systematic temperature difference comprises the temperature field distribution difference and the thermal conductivity difference of the fourth group of two temperature sensor arrangement points. If the absolute value of T7-T8 is more than TBD4, a fault state is displayed, and if the absolute value of T7-T8 is less than or equal to TBD4, the acquisition of the two temperature sensors in the fourth group is normal.
Calculating a temperature difference value | T9-T10| of the fifth group of temperature sensors, comparing the temperature difference value | T9-T10| with a difference threshold TBD5, and determining the difference threshold TBD5 according to the systematic temperature difference of the arrangement points of the fifth group of two temperature sensors, the temperature drift deviation of the fifth group of two temperature sensors and the acquisition precision; the systematic temperature difference comprises the temperature field distribution difference and the thermal conductivity difference of the fifth set of two temperature sensor arrangement points. If the absolute value of T9-T10 is more than TBD5, a fault state is displayed, and if the absolute value of T9-T10 is less than or equal to TBD5, the acquisition of the two temperature sensors in the fifth group is normal.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (3)
1. A battery pack temperature sensor rationality diagnosis method based on thermal symmetry is characterized by comprising the following steps:
s1, establishing a battery pack thermal simulation analysis model, and preliminarily determining a plurality of groups of thermal symmetry points by analyzing the core group structure arrangement characteristics, the heat source distribution condition and the thermal management system flow channel condition of the battery pack, wherein each group of thermal symmetry points comprises two test points;
s2, verifying the multiple groups of thermal symmetry points obtained in the S1 to obtain the temperature characteristics of the test points in thermal simulation tests under different charging and discharging working conditions, and if the temperature characteristics of the two test points of the single group of thermal symmetry points are the same or the difference value of the two test points is within a set range, the verification is passed; if the difference value of the two test points of the single group of thermal symmetry points is out of the set range, returning to S1 to re-select the test points;
s3, according to the positions of a plurality of groups of thermal symmetry points in the battery pack thermal simulation analysis model verified by S2, arranging temperature sensors at corresponding positions of the battery pack, calculating a temperature difference value | T1-T2| acquired by two temperature sensors in each group of thermal symmetry points, comparing the temperature difference value | T1-T2| with a difference threshold TBD, and judging the rationality of the temperature sensors in each group of thermal symmetry points.
2. The thermal symmetry-based battery pack temperature sensor rationality diagnostic method according to claim 1, characterized in that: the fault state is displayed when the temperature difference | T1-T2| is greater than the difference threshold TBD in the S3.
3. The thermal symmetry-based battery pack temperature sensor rationality diagnostic method according to claim 1 or 2, characterized in that: the difference threshold TBD of each group of thermal symmetry points in the S3 is determined according to the systematic temperature difference of the arrangement points of the two temperature sensors, the temperature drift deviation of the two temperature sensors and the acquisition precision;
the system temperature difference comprises the temperature field distribution difference and the thermal conductivity difference of two temperature sensor arrangement points.
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Families Citing this family (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113740742B (en)* | 2020-05-29 | 2023-03-14 | 比亚迪股份有限公司 | Battery thermal management method, device, medium and equipment |
| DE102020208556B4 (en)* | 2020-07-08 | 2022-01-20 | Volkswagen Aktiengesellschaft | Thermal runaway detection method and motor vehicle |
| DE102020126639A1 (en) | 2020-10-12 | 2022-04-14 | Vorwerk & Co. Interholding Gesellschaft mit beschränkter Haftung | Method for operating a battery having a plurality of battery cells |
| CN113720874B (en)* | 2021-08-30 | 2023-08-01 | 北京遥测技术研究所 | Microwave product thermal simulation method based on soldering tin thermal conductivity test |
| CN113804252A (en)* | 2021-09-10 | 2021-12-17 | 广州市吉华勘测股份有限公司 | High formwork supporting safety monitoring method, device, equipment and storage medium |
| CN114414082A (en)* | 2022-03-02 | 2022-04-29 | 北京卫星环境工程研究所 | A temperature detection and determination method for electric tools for space on-orbit maintenance |
| CN116298948A (en)* | 2023-03-24 | 2023-06-23 | 中国第一汽车股份有限公司 | Method and device for monitoring safety of vehicle power battery function and storage medium |
| DE102023208528A1 (en) | 2023-09-05 | 2025-03-06 | Robert Bosch Gesellschaft mit beschränkter Haftung | Method and device for evaluating temperature measurements from temperature sensors distributed in a device battery |
| CN117145618B (en)* | 2023-10-30 | 2024-03-15 | 中国第一汽车股份有限公司 | Exhaust gas temperature detection element, control method for exhaust gas temperature detection element, and vehicle |
| CN118258520B (en)* | 2024-05-31 | 2024-08-13 | 杭州协能科技股份有限公司 | Battery temperature sensor falling detection method and battery pack |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE102005004998A1 (en)* | 2005-02-03 | 2006-08-17 | Vb Autobatterie Gmbh & Co. Kgaa | Device and method for determining the temperature in an electric battery |
| WO2009065667A1 (en)* | 2007-11-23 | 2009-05-28 | Robert Bosch Gmbh | Monitoring the temperature sensors of a pulse-controlled inverter |
| GB201404571D0 (en)* | 2014-03-14 | 2014-04-30 | Daimler Ag | Method for checking a multi sensor system of a vehicle |
| CN103900733A (en)* | 2014-03-04 | 2014-07-02 | 清华大学 | Method for measuring temperature field distribution inside battery |
| CN105206888A (en)* | 2015-08-31 | 2015-12-30 | 浙江工业大学之江学院 | Lithium ion battery internal temperature monitoring method |
| JP2018013420A (en)* | 2016-07-21 | 2018-01-25 | 株式会社リコー | Temperature detection sensor abnormality determination device, heating device, image forming system, and detected temperature abnormality determination method |
| CN109145394A (en)* | 2018-07-27 | 2019-01-04 | 北京新能源汽车股份有限公司 | Display method, device and system for temperature field of power battery |
| CN109449518A (en)* | 2018-11-02 | 2019-03-08 | 奇瑞汽车股份有限公司 | Temperature correction method for power battery system |
| CN209029503U (en)* | 2018-12-14 | 2019-06-25 | 东软睿驰汽车技术（沈阳）有限公司 | A kind of battery modules |
| CN110534825A (en)* | 2019-07-26 | 2019-12-03 | 中国电力科学研究院有限公司 | Lithium ion battery thermal runaway early warning method |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6508584B2 (en)* | 1999-02-23 | 2003-01-21 | Intel Corporation | Method and apparatus for testing a temperature sensor |
| JP4916326B2 (en)* | 2007-01-31 | 2012-04-11 | 東京エレクトロン株式会社 | Temperature monitoring substrate inspection apparatus and inspection method |
| US7771113B2 (en)* | 2007-06-29 | 2010-08-10 | Cummins Filtration Ip, Inc | Sensor rationality diagnostic |
- 2019
- 2019-12-26CNCN201911366109.6Apatent/CN110970679B/enactiveActive
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE102005004998A1 (en)* | 2005-02-03 | 2006-08-17 | Vb Autobatterie Gmbh & Co. Kgaa | Device and method for determining the temperature in an electric battery |
| WO2009065667A1 (en)* | 2007-11-23 | 2009-05-28 | Robert Bosch Gmbh | Monitoring the temperature sensors of a pulse-controlled inverter |
| CN103900733A (en)* | 2014-03-04 | 2014-07-02 | 清华大学 | Method for measuring temperature field distribution inside battery |
| GB201404571D0 (en)* | 2014-03-14 | 2014-04-30 | Daimler Ag | Method for checking a multi sensor system of a vehicle |
| CN105206888A (en)* | 2015-08-31 | 2015-12-30 | 浙江工业大学之江学院 | Lithium ion battery internal temperature monitoring method |
| JP2018013420A (en)* | 2016-07-21 | 2018-01-25 | 株式会社リコー | Temperature detection sensor abnormality determination device, heating device, image forming system, and detected temperature abnormality determination method |
| CN109145394A (en)* | 2018-07-27 | 2019-01-04 | 北京新能源汽车股份有限公司 | Display method, device and system for temperature field of power battery |
| CN109449518A (en)* | 2018-11-02 | 2019-03-08 | 奇瑞汽车股份有限公司 | Temperature correction method for power battery system |
| CN209029503U (en)* | 2018-12-14 | 2019-06-25 | 东软睿驰汽车技术（沈阳）有限公司 | A kind of battery modules |
| CN110534825A (en)* | 2019-07-26 | 2019-12-03 | 中国电力科学研究院有限公司 | Lithium ion battery thermal runaway early warning method |
Non-Patent Citations (2)
| Title |
|---|
| HEV动力电池组数据采集系统设计;林如意等;《电子器件》;20111031;第34卷(第5期);第576-579页* |
| structural analysis bassed sensors fault detection and isolation of cylindrical lithium-ion batteries in automotive applications;Liu Zhentong等;《CONTROL ENGINEERING PRACTICE》;20160706;第52卷;第46-58页* |
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