CN108646183A - A kind of battery in battery pack method for diagnosing faults - Google Patents
A kind of battery in battery pack method for diagnosing faults Download PDFInfo
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- CN108646183A CN108646183A CN201810278942.4A CN201810278942A CN108646183A CN 108646183 A CN108646183 A CN 108646183A CN 201810278942 A CN201810278942 A CN 201810278942A CN 108646183 A CN108646183 A CN 108646183A
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Abstract
The invention discloses a kind of battery in battery pack method for diagnosing faults further to diagnose fault type by the voltage after standing after carrying out battery pack holistic diagnosis and malfunctioning module positioning by the terminal voltage that charges.The reliable diagnosis of power battery pack failure may be implemented in the present invention, reduces the erroneous judgement of battery failure, avoids battery pack is unnecessary from repairing repeatedly, saves maintenance cost.
Description
Technical field
The present invention relates to Vehicular dynamic battery technical field more particularly to a kind of battery in battery pack method for diagnosing faults.
Background technology
It is run in electric vehicle, the occupation mode of battery is to use to be attached rear shape by single battery with series-parallel system
Meets the needs of power in vehicle operation at a battery pack.And the battery pack containing a large amount of series and parallel battery cells exists
It is influenced in manufacturing process or by many uncontrollable factors in use, the difference between battery cell can be caused, and then reduce
The power performance of battery pack seriously affects battery capacity, energy, pressure difference, course continuation mileage, service life, and then influences user
In the experience using process.
Battery pack single monomer battery voltage exception when charging, to reach charge cutoff condition in advance and terminate to fill
Electricity, other batteries and underfill, in this way impact entire battery pack, reduce the performance of battery pack at this time.Therefore, root at present
Judge power battery pack failure according to the monomer pressure difference of battery pack.Battery management system BMS according only to the collected voltage of institute not
Unanimously report brownout or overtension failure.But this breakdown judge mode has a drawback in that, does not embody
Out of order producing cause cannot effectively instruct subsequent balanced operation.
Invention content
Technical problems based on background technology, the present invention propose a kind of battery in battery pack method for diagnosing faults.
A kind of battery in battery pack method for diagnosing faults proposed by the present invention, includes the following steps：
S1, by the vehicle equipped with battery pack by repeatedly charge with operating mode electric discharge operation after, record remote monitoring data；Far
Range monitoring data include vehicle each module monomer voltage, charging current and discharge current in the process of running；
S2, it is charged to battery pack and obtains each serial module structure voltage value V11 in battery pack charging end, V12 to V1n, n
For the quantity of serial module structure, and maximum voltage value Vmax and minimum voltage value Vmin are screened, and calculates the voltage of each serial module structure
Average value V1；
S3, pressure difference Δ V, Δ V=Vmax-Vmin are obtained；
S4, judge whether pressure difference Δ V is more than preset first voltage threshold value U1；It is no, then judge that the battery pack is normal；
S5, it is then to judge the battery failure, by the maximum voltage value Vmax and minimum voltage value Vmin in the battery pack
It is compared respectively with average voltage V1, positioning failure module；
S6, after battery pack is stood default value at the first time, the standing voltage value of each serial module structure in battery pack is obtained
V21, V22 to V2n, and obtain the standing average voltage V2 of each serial module structure；
S7, by the standing voltage value V2m of malfunctioning module compared with standing average voltage V2,1≤m≤n；
S8, in conjunction with the comparison result failure judgement type of step S5 and step S7.
Preferably, step S5 specifically includes following steps：
S51, default second voltage threshold value U2；
S52, judge whether the difference of maximum voltage value Vmax and average voltage V1 is more than second voltage threshold value U2；It is,
Then judge the corresponding serial module structure failures of maximum voltage value Vmax；
It is S53, no, then judge whether the difference of average voltage V1 and minimum voltage value Vmin is more than second voltage threshold value
U2；It is then to judge the corresponding serial module structure failures of minimum voltage value Vmin.
Preferably, in step S8, if malfunctioning module is the corresponding serial module structures of maximum voltage value Vmax, and the module is quiet
It sets voltage value V2m and is less than standing average voltage V2, then judge the module damage；
Preferably, in step S8, if malfunctioning module is the corresponding serial module structures of maximum voltage value Vmax, and the module is quiet
It sets voltage value V2m and is more than standing average voltage V2, then judge that module SOC states are higher；
Preferably, in step S8, if malfunctioning module is the corresponding serial module structures of minimum voltage value Vmin, and the module is quiet
It sets voltage value V2m and is more than standing average voltage V2, then judge the damage；
Preferably, in step S8, if malfunctioning module is the corresponding serial module structures of minimum voltage value Vmin, and the module is quiet
It sets voltage value V2m and is less than standing average voltage V2, then judge that module SOC states are relatively low.
Preferably, first voltage threshold value U1 and second voltage threshold value U2 is arranged according to battery pack charging current.
It is whole to carry out battery pack by the terminal voltage that charges for a kind of battery in battery pack method for diagnosing faults proposed by the present invention
Body is diagnosed with after malfunctioning module positioning, is further diagnosed to fault type by the voltage after standing.The present invention may be implemented to move
The reliable diagnosis of power battery failure reduces the erroneous judgement of battery failure, avoids battery pack is unnecessary from repairing repeatedly, saves dimension
Accomplish this.
In the present invention, by the maximum voltage value Vmax and minimum voltage value Vmin of battery pack serial module structure to battery pack into
Row holistic diagnosis is conducive to improve battery pack diagnosis efficiency, and screening fail battery group is to carry out Precise Diagnosis.In addition, of the invention
It is run by vehicle, advantageously ensures that the fault detect of battery pack meets actual application environment, by remote monitoring data, favorably
In providing reference frame for the parameter setting in fault detect.
Description of the drawings
Fig. 1 is a kind of battery in battery pack method for diagnosing faults flow chart of proposition proposed by the present invention；
Fig. 2 is a serial module structure in battery pack in charging end and the voltage's distribiuting schematic diagram of standing；
Fig. 3 is another serial module structure in battery pack in charging end and the voltage's distribiuting schematic diagram of standing；
Fig. 4 is another serial module structure in battery pack in charging end and the voltage's distribiuting schematic diagram of standing.
Specific implementation mode
Referring to Fig.1, a kind of battery in battery pack method for diagnosing faults proposed by the present invention, includes the following steps.
S1, by the vehicle equipped with battery pack by repeatedly charge with operating mode electric discharge operation after, record remote monitoring data.Far
Range monitoring data include vehicle each module monomer voltage, charging current and discharge current in the process of running.
It in this step, is run by vehicle, advantageously ensures that the fault detect of battery pack meets actual application environment, pass through
Remote monitoring data is conducive to provide reference frame for the parameter setting in fault detect.
S2, it is charged to battery pack and obtains each serial module structure voltage value V11 in battery pack charging end, V12 to V1n, n
For the quantity of serial module structure, and maximum voltage value Vmax and minimum voltage value Vmin are screened, and calculates the voltage of each serial module structure
Average value V1.
Specifically, in this step, maximum voltage value Vmax and minimum voltage value Vmin are respectively that voltage value V11, V12 are arrived
The maximum value and minimum value of V1n, V1=(V11+V12+ ... V1n)/n.
S3, pressure difference Δ V, Δ V=Vmax-Vmin are obtained.
S4, judge whether pressure difference Δ V is more than preset first voltage threshold value U1；It is no, then judge that the battery pack is normal.The
One voltage threshold U1 is arranged according to battery pack charging current.
S5, it is then to judge the battery failure, by the maximum voltage value Vmax and minimum voltage value Vmin in the battery pack
It is compared respectively with average voltage V1, positioning failure module.
In this way, in present embodiment, pass through the maximum voltage value Vmax and minimum voltage value Vmin of battery pack serial module structure
Holistic diagnosis is carried out to battery pack, is conducive to improve battery pack diagnosis efficiency, screening fail battery group is to carry out Precise Diagnosis.
In present embodiment, the concrete mode of positioning failure module is as follows：
S51, default second voltage threshold value U2.Second voltage threshold value U2 is arranged according to battery pack charging current.
S52, judge whether the difference of maximum voltage value Vmax and average voltage V1 is more than second voltage threshold value U2；It is,
Then judge the corresponding serial module structure failures of maximum voltage value Vmax.
It is S53, no, then judge whether the difference of average voltage V1 and minimum voltage value Vmin is more than second voltage threshold value
U2.It is then to judge the corresponding serial module structure failures of minimum voltage value Vmin.
In this way, in present embodiment, directly from maximum voltage value Vmax and the corresponding serial module structures of minimum voltage value Vmin
Failure is detected, is conducive to improve fault location efficiency, avoids the redundancy of effort for detecting each serial module structure one by one.
S6, after battery pack is stood default value at the first time, the standing voltage value of each serial module structure in battery pack is obtained
V21, V22 to V2n, and obtain the standing average voltage V2 of each serial module structure.
S7, by the standing voltage value V2m of malfunctioning module compared with standing average voltage V2,1≤m≤n.
S8, in conjunction with the comparison result failure judgement type of step S5 and step S7.
In the step S8 of present embodiment, according to preset breakdown judge model failure judgement type, specifically：If therefore
Barrier module is the corresponding serial module structures of maximum voltage value Vmax, and the module stands voltage value V2m and is less than standing average voltage
V2 then judges the module damage, needs to change module；
If malfunctioning module is the corresponding serial module structures of maximum voltage value Vmax, and the module stands voltage value V2m and is more than
Average voltage V2 is stood, then judges that module SOC states are higher, module equilibrium need to be carried out；
If malfunctioning module is the corresponding serial module structures of minimum voltage value Vmin, and the module stands voltage value V2m and is more than
Average voltage V2 is stood, then judges the damage, module replacing need to be carried out；
If malfunctioning module is the corresponding serial module structures of minimum voltage value Vmin, and the module stands voltage value V2m and is less than
Average voltage V2 is stood, then judges that module SOC states are relatively low, module equilibrium need to be carried out.
In this way, in present embodiment, after carrying out battery pack holistic diagnosis and malfunctioning module positioning by the terminal voltage that charges,
Fault type is further diagnosed by the voltage after standing.Present embodiment may be implemented the reliable of power battery pack failure and examine
It is disconnected, the erroneous judgement of battery failure is reduced, avoids battery pack is unnecessary from repairing repeatedly, saves maintenance cost.
The foregoing is only a preferred embodiment of the present invention, but scope of protection of the present invention is not limited thereto,
Any one skilled in the art in the technical scope disclosed by the present invention, according to the technique and scheme of the present invention and its
Inventive concept is subject to equivalent substitution or change, should be covered by the protection scope of the present invention.
Claims (7)
1. a kind of battery in battery pack method for diagnosing faults, which is characterized in that include the following steps：
S1, by the vehicle equipped with battery pack by repeatedly charge with operating mode electric discharge operation after, record remote monitoring data；Long-range prison
It includes vehicle each module monomer voltage, charging current and discharge current in the process of running to control data；
S2, it is charged to battery pack and obtains each serial module structure voltage value V11 in battery pack charging end, V12 to V1n, n is string
The quantity of gang mould block, and maximum voltage value Vmax and minimum voltage value Vmin are screened, and calculate the average voltage of each serial module structure
Value V1；
S3, pressure difference Δ V, Δ V=Vmax-Vmin are obtained；
S4, judge whether pressure difference Δ V is more than preset first voltage threshold value U1；It is no, then judge that the battery pack is normal；
S5, it is then to judge the battery failure, by the maximum voltage value Vmax and minimum voltage value Vmin difference in the battery pack
It is compared with average voltage V1, positioning failure module；
S6, after battery pack is stood default value at the first time, standing voltage value V21, V22 of each serial module structure in battery pack are obtained
To V2n, and obtain the standing average voltage V2 of each serial module structure；
S7, by the standing voltage value V2m of malfunctioning module compared with standing average voltage V2,1≤m≤n；
S8, in conjunction with the comparison result failure judgement type of step S5 and step S7.
2. battery in battery pack method for diagnosing faults as described in claim 1, which is characterized in that step S5 specifically includes following
Step：
S51, default second voltage threshold value U2；
S52, judge whether the difference of maximum voltage value Vmax and average voltage V1 is more than second voltage threshold value U2；It is then to sentence
Break the corresponding serial module structure failure of maximum voltage value Vmax；
It is S53, no, then judge whether the difference of average voltage V1 and minimum voltage value Vmin is more than second voltage threshold value U2；It is,
Then judge the corresponding serial module structure failures of minimum voltage value Vmin.
3. battery in battery pack method for diagnosing faults as claimed in claim 2, which is characterized in that in step S8, if failure
Module is the corresponding serial module structures of maximum voltage value Vmax, and the module stands voltage value V2m and is less than standing average voltage V2,
Then judge the module damage.
4. battery in battery pack method for diagnosing faults as claimed in claim 2, which is characterized in that in step S8, if failure
Module is the corresponding serial module structures of maximum voltage value Vmax, and the module stands voltage value V2m and is more than standing average voltage V2,
Then judge that module SOC states are higher.
5. battery in battery pack method for diagnosing faults as claimed in claim 2, which is characterized in that in step S8, if failure
Module is the corresponding serial module structures of minimum voltage value Vmin, and the module stands voltage value V2m and is more than standing average voltage V2,
Then judge the damage.
6. battery in battery pack method for diagnosing faults as claimed in claim 2, which is characterized in that in step S8, if failure
Module is the corresponding serial module structures of minimum voltage value Vmin, and the module stands voltage value V2m and is less than standing average voltage V2,
Then judge that module SOC states are relatively low.
7. such as claim 1 to 6 any one of them battery in battery pack method for diagnosing faults, which is characterized in that first voltage
Threshold value U1 and second voltage threshold value U2 is arranged according to battery pack charging current.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111562503A (en) * | 2020-04-07 | 2020-08-21 | 天津力神电池股份有限公司 | Method for analyzing and processing failure of lithium ion battery charging and discharging equipment |
| CN111580000A (en) * | 2020-04-14 | 2020-08-25 | 浙江零跑科技有限公司 | Battery SOC calibration method |
| CN111579998A (en) * | 2020-04-14 | 2020-08-25 | 浙江零跑科技有限公司 | Battery SOC calibration method and device and storage medium |
| CN113646648A (en) * | 2019-10-02 | 2021-11-12 | 株式会社Lg新能源 | Method and system for detecting connection failure of parallel battery units |
| CN114114057A (en) * | 2021-10-28 | 2022-03-01 | 合肥国轩高科动力能源有限公司 | New energy electric vehicle battery monomer abnormity prediction method |
| EP3958006A4 (en) * | 2019-09-11 | 2022-06-01 | LG Energy Solution, Ltd. | Battery diagnosis apparatus and method |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101930057A (en) * | 2010-06-13 | 2010-12-29 | 深圳市睿德电子实业有限公司 | Method and system for detecting faults of power batteries |
| CN102565711A (en) * | 2011-12-02 | 2012-07-11 | 毛广甫 | Method for testing voltage condition of battery pack |
| CN104614675A (en) * | 2014-12-31 | 2015-05-13 | 普天新能源车辆技术有限公司 | Power battery group consistency detection method and device |
| CN104916875A (en) * | 2015-04-21 | 2015-09-16 | 合肥国轩高科动力能源股份公司 | Power battery pack fault diagnosis and maintenance method |
| CN105548908A (en) * | 2016-01-25 | 2016-05-04 | 北京华特时代电动汽车技术有限公司 | Internal resistance consistency detection method for power battery pack |
| CN105846483A (en) * | 2015-01-14 | 2016-08-10 | 北京普莱德新能源电池科技有限公司 | Imbalance fault determining and balancing method for battery pack |
| CN107612071A (en) * | 2017-09-24 | 2018-01-19 | 合肥国轩高科动力能源有限公司 | A kind of battery cell fault verification and processing method |
-
2018
- 2018-03-30 CN CN201810278942.4A patent/CN108646183B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101930057A (en) * | 2010-06-13 | 2010-12-29 | 深圳市睿德电子实业有限公司 | Method and system for detecting faults of power batteries |
| CN102565711A (en) * | 2011-12-02 | 2012-07-11 | 毛广甫 | Method for testing voltage condition of battery pack |
| CN104614675A (en) * | 2014-12-31 | 2015-05-13 | 普天新能源车辆技术有限公司 | Power battery group consistency detection method and device |
| CN105846483A (en) * | 2015-01-14 | 2016-08-10 | 北京普莱德新能源电池科技有限公司 | Imbalance fault determining and balancing method for battery pack |
| CN104916875A (en) * | 2015-04-21 | 2015-09-16 | 合肥国轩高科动力能源股份公司 | Power battery pack fault diagnosis and maintenance method |
| CN105548908A (en) * | 2016-01-25 | 2016-05-04 | 北京华特时代电动汽车技术有限公司 | Internal resistance consistency detection method for power battery pack |
| CN107612071A (en) * | 2017-09-24 | 2018-01-19 | 合肥国轩高科动力能源有限公司 | A kind of battery cell fault verification and processing method |
Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP3958006A4 (en) * | 2019-09-11 | 2022-06-01 | LG Energy Solution, Ltd. | Battery diagnosis apparatus and method |
| US11965936B2 (en) | 2019-09-11 | 2024-04-23 | Lg Energy Solution, Ltd. | Battery diagnosis apparatus and method |
| CN113646648A (en) * | 2019-10-02 | 2021-11-12 | 株式会社Lg新能源 | Method and system for detecting connection failure of parallel battery units |
| CN113646648B (en) * | 2019-10-02 | 2024-04-02 | 株式会社Lg新能源 | Method and system for detecting connection failure of parallel battery units |
| CN111562503A (en) * | 2020-04-07 | 2020-08-21 | 天津力神电池股份有限公司 | Method for analyzing and processing failure of lithium ion battery charging and discharging equipment |
| CN111562503B (en) * | 2020-04-07 | 2022-05-03 | 天津力神电池股份有限公司 | Method for analyzing and processing failure of lithium ion battery charging and discharging equipment |
| CN111580000A (en) * | 2020-04-14 | 2020-08-25 | 浙江零跑科技有限公司 | Battery SOC calibration method |
| CN111579998A (en) * | 2020-04-14 | 2020-08-25 | 浙江零跑科技有限公司 | Battery SOC calibration method and device and storage medium |
| CN111579998B (en) * | 2020-04-14 | 2022-05-06 | 浙江零跑科技股份有限公司 | Battery SOC calibration method and device and storage medium |
| CN111580000B (en) * | 2020-04-14 | 2022-05-17 | 浙江零跑科技股份有限公司 | Battery SOC calibration method |
| CN114114057A (en) * | 2021-10-28 | 2022-03-01 | 合肥国轩高科动力能源有限公司 | New energy electric vehicle battery monomer abnormity prediction method |
| CN114114057B (en) * | 2021-10-28 | 2023-11-07 | 合肥国轩高科动力能源有限公司 | New energy electric automobile battery monomer anomaly prediction method |
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