CN111381169B - Power battery thermal runaway early warning method - Google Patents

Power battery thermal runaway early warning method Download PDF

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CN111381169B
CN111381169B CN202010146786.3A CN202010146786A CN111381169B CN 111381169 B CN111381169 B CN 111381169B CN 202010146786 A CN202010146786 A CN 202010146786A CN 111381169 B CN111381169 B CN 111381169B
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battery
thermal runaway
power battery
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CN111381169A (en
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周雅夫
孙宵宵
马建刚
仪坤
连静
李琳辉
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Dalian University of Technology
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/367—Software therefor, e.g. for battery testing using modelling or look-up tables
    • 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]
    • G01R31/382—Arrangements for monitoring battery or accumulator variables, e.g. SoC
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/385—Arrangements for measuring battery or accumulator variables

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Abstract

The invention belongs to the technical field of new energy automobile power batteries, and relates to a power battery thermal runaway early warning method. Firstly, establishing an initial five-dimensional data security model of the power battery; then acquiring five-dimensional data of the power battery in real time, comparing the difference between the real-time five-dimensional data and the five-dimensional data in the safety model, judging the number and the deviation degree of thermal runaway points of the battery, and updating the five-dimensional data safety model of the power battery in real time; and finally, comprehensively analyzing to obtain the thermal runaway grade of the power battery according to the number and the deviation degree of the thermal runaway points. The power battery thermal runaway early warning method provided by the invention is suitable for the full working condition of a vehicle and the full life cycle of a battery, can effectively detect the thermal runaway phenomenon of the battery in advance, and avoids the generation of malignant accidents.

Description

Power battery thermal runaway early warning method
Technical Field
The application belongs to the technical field of new energy automobile power batteries, and relates to a power battery thermal runaway early warning method.
Background
In order to alleviate the huge problems of energy crisis and environmental pollution, the vigorous development of new energy automobiles has become an inevitable trend in the automobile industry. The lithium ion power battery has the advantages of high specific energy, high specific power, high charge-discharge rate, long cycle life and the like, and thus, the lithium ion power battery becomes the most commonly used energy source in new energy automobiles.
However, with the increasing driving range of new energy vehicles, the energy density of the lithium ion power battery is increased, the safety of the lithium ion power battery is reduced, and safety accidents of the lithium ion power battery mainly caused by thermal runaway often occur. The thermal runaway accident of the lithium ion power battery is represented by the phenomena of sudden temperature rise, smoke, fire and even explosion caused by battery heat release, and huge casualties and property loss are caused. The thermal runaway accident of the lithium ion power battery can seriously attack the confidence that consumers accept new energy automobiles and hinder the development of the new energy automobile industry.
The relevant literature shows that no completely stable and reliable method is available for avoiding the thermal runaway phenomenon of the lithium ion power battery. Therefore, in order to reduce the loss caused by the thermal runaway of the battery, it is necessary to explore an effective method for realizing early warning before the thermal runaway of the battery occurs, so that a user can escape in time and take flame-retardant measures. The existing battery thermal runaway early warning method has the following problems: (1) the applicable battery working conditions are not comprehensive, and many thermal runaway early warning methods are early warning methods for researching the thermal runaway of the battery under specific working conditions in a laboratory, and are difficult to adapt to the real vehicle environment; (2) the life cycle of the covered battery is narrow, and many thermal runaway early warning methods only work in the fixed life cycle of the battery and are difficult to be applied to the full life cycle of the battery.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a brand-new thermal runaway early warning method based on a power battery five-dimensional data (SOH, T, SOC, I and V) safety model, so as to detect the thermal runaway phenomenon of the battery in advance and avoid the generation of malignant accidents.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows:
a power battery thermal runaway early warning method comprises the following steps:
the method comprises the following steps: acquiring a group of state parameter values (SOH) of the power battery at the same moment every N seconds*,T*,SOC*,I*,V*) Wherein, SOH*At this time, the battery state of health value, T*For the battery temperature value at that time, SOC*At this time, the state of charge value of the battery, I*The current value of the battery at this time, V*The battery voltage value at the moment;
step two: preliminarily establishing a voltage value corresponding to each group of state parameter values in a five-dimensional data safety model of the power battery;
five-dimensional data security model of power batteryThe SOH value of the power battery stored in the five-dimensional data safety model of the power battery is in a normal SOH interval (80%, 100%)]The average number of the SOH points is n _ SOH, and the corresponding SOH points are as follows: SOH1,SOH2,...,SOHn_SOH(ii) a Setting the value T of the power battery stored in the model in a normal temperature range [ Tmin，Tmax]Is n _ T on average, and the corresponding T point is T1,T2,...,Tn_T(ii) a The SOC value of the power battery stored in the model is in a normal SOC interval (20%, 100%)]Is averaged to obtain n _ SOC, and the corresponding SOC point is the SOC1,SOC2,...,SOCn_SOC(ii) a Setting the value of the power battery I stored in the model in a normal current interval [ Imin，Imax]Is n _ I on average, and the corresponding I point is I1,I2,...,In_I(ii) a Before the SOH, T, SOC, I and V parameters of the power battery are not collected, the five-dimensional data safety model of the power battery is an empty model, and after the SOH, T, SOC, I and V parameters of the power battery are collected, the five-dimensional data safety model of the power battery is continuously updated.
The specific process of preliminarily establishing the voltage value corresponding to the state parameter value in the five-dimensional data safety model of the power battery is as follows: state parameter value (SOH) for current battery*,T*,SOC*,I*,V*) And a power battery five-dimensional data safety model for respectively judging SOH*,T*,SOC*With SOH in five-dimensional data security model1,SOH2,...,SOHn_SOH、T1,T2,...,Tn_T、SOC1,SOC2,...,SOCn_SOCThe more close SOH point, T point and SOC point are judged as
Figure BDA0002401034590000021
Judgment of I*In five-dimensional data security model I1,I2,...,In_IBetween the two points I, the judgment result is I 'and I';
viewing five-dimensional data in the Security model: (
Figure BDA0002401034590000022
I') and (
Figure BDA0002401034590000023
I') whether the voltage value corresponding to the voltage V is null, and if one is null, the voltage V is set*Respectively stored in a five-dimensional data security model (
Figure BDA0002401034590000024
I') and (
Figure BDA0002401034590000025
I'), judging that the current state parameter value is a battery safety point in the voltage value corresponding to the current state parameter value, and entering the step five; and if the data is not empty, entering the step three.
Step three: judging a thermal runaway point of the battery by utilizing a five-dimensional data safety model of the power battery;
setting comparison threshold value delta V of different deviation degrees of battery voltage1 *，ΔV2 *，...,ΔVn *The number of the comparison threshold values is determined according to the number of response measures with different levels of the thermal runaway of the lithium battery, if the thermal runaway of the lithium battery has n response measures with different levels of the thermal runaway, n comparison threshold values are set, the size of the comparison threshold values is calibrated according to a large amount of experimental data of the type of the battery, and the delta V is calculated according to the number of the response measures with different levels of the thermal runaway of the lithium battery1 *＜ΔV2 *＜..＜ΔVn *；
(in five-dimensional data security model) by data interpolation method
Figure BDA0002401034590000026
I′,V′)、(
Figure BDA0002401034590000027
I ', V') are interpolated to obtain
Figure BDA0002401034590000028
I*) Corresponding voltage value
Figure BDA0002401034590000029
Comparison
Figure BDA00024010345900000210
And V*And a threshold value Δ V1 *，ΔV2 *，...,ΔVn *Judging whether the set of state parameter values are thermal runaway points and the grade of the thermal runaway points: if Δ Vs-1` *＜ΔV≤ΔVs *Wherein s is 2,3, and n, and the state parameter value is judged to be an s-1 level thermal runaway point; if Δ Vn *If the current state parameter value is less than delta V, judging that the current state parameter value is an n-level thermal runaway point, and entering a fifth step; if Δ V is less than or equal to Δ V1 *And judging that the current state parameter value is a battery safety point, and entering the step four.
Step four: updating a five-dimensional data security model of the power battery;
value of state parameter (SOH) for which it is determined that battery is safe*,T*,SOC*,I*,V*) A mixture of (I ', V') and (I)*,V*) Interpolation is performed to obtain (I ",
Figure BDA0002401034590000031
) The compounds (I ', V') and (I)*,V*) Interpolation is carried out to obtain the (I',
Figure BDA0002401034590000032
) Voltage of the handle
Figure BDA0002401034590000033
Restored into five-dimensional data security model
Figure BDA0002401034590000034
I′)、(
Figure BDA0002401034590000035
I') correspond toIn the voltage value of (a), the corresponding (in the five-dimensional data security model) is completed
Figure BDA0002401034590000036
I′)、(
Figure BDA0002401034590000037
I'), and entering a step five.
Step five: judging whether the current power battery is out of control due to thermal runaway and the early warning level of the out of control due to thermal runaway according to the number and the properties of the battery out of control points in unit time;
counting the state parameter values (SOH) of M groups of batteries nearest to the current moment*,T*,SOC*,I*,V*) Judging that the thermal runaway points of different grades account for the proportion of all the points, wherein miA ratio of i-class thermal runaway points (i ═ 1, 2.. times.n); setting different thermal runaway grades to compare threshold value r1,r2,...,rnM and r1,r2,...,rnIs calibrated according to a large amount of experimental data of the battery with the model. If m1+m2+,...,+mn≤r1Judging that the power battery is in a safe state; if mi+mi+1+,...,+mn＞riAnd m isi+1+,...,+mn≤ri+1(i-1, 2.., n-1), judging that the thermal runaway early warning grade of the power battery is i-level thermal runaway; if mn＞rnAnd judging that the thermal runaway early warning grade of the power battery is n-grade thermal runaway, and finishing the thermal runaway early warning of the power battery.
The invention has the beneficial effects that: the invention provides a brand-new thermal runaway early warning method based on a power battery five-dimensional data (SOH, T, SOC, I and V) safety model, which comprises the steps of firstly establishing an initial power battery five-dimensional data safety model; then acquiring five-dimensional data of the power battery in real time, comparing the difference between the real-time five-dimensional data and the five-dimensional data in the safety model, judging the number and the deviation degree of thermal runaway points of the battery, and updating the five-dimensional data safety model of the power battery in real time; and finally, comprehensively analyzing to obtain the thermal runaway grade of the power battery according to the number and the deviation degree of the thermal runaway points. The power battery thermal runaway early warning method is suitable for the full working condition of a vehicle and the full life cycle of a battery, and can effectively detect the thermal runaway phenomenon of the battery in advance so as to avoid the generation of malignant accidents.
Drawings
Fig. 1 is a flowchart of a power battery thermal runaway early warning method according to an embodiment of the invention.
Detailed Description
The present invention is further illustrated by the following specific examples.
The flow chart of the power battery thermal runaway early warning method provided by the invention is shown in figure 1. The five-dimensional data safety model of the power battery is stored with data of five parameters of SOH (battery health state), T (temperature), SOC (battery state of charge), I (current) and V (voltage) of the power battery, and the SOH value of the power battery stored in the model is in a normal SOH interval (80%, 100%)]Takes 11 on average in the range of (1), and the corresponding SOH points are as follows: SOH1＝80％,SOH2＝82％,...,SOH10＝98％,SOH11100 percent; the T value of the power battery stored in the model is within a normal temperature range of minus 20 ℃ and 50 DEG C]Is 15 on average, and the corresponding T point is T1＝-20℃,T2＝-15℃,...,T14＝45℃,T15The temperature is 50 ℃; the SOC value of the power battery stored in the model is in a normal SOC interval (20%, 100%)]Is 17 on average in the range of (1), and the corresponding SOC point is the SOC1＝20％,SOC2＝25％,...,SOC16＝95％,SOC17100 percent; the value of the power battery I stored in the model is in a normal current range [ -70A, 190A [ -70A [ ]]Is 27 on average, and the corresponding I point is I1＝-70A,I2＝-60A,...,I26＝180A,I27190A; before the SOH, T, SOC, I and V parameters of the power battery are not collected, the five-dimensional data safety model of the power battery is an empty model, and after the SOH, T, SOC, I and V parameters of the power battery are collected, the five-dimensional data safety model of the power battery is continuously updated.
The power battery thermal runaway early warning method comprises the following steps:
the method comprises the following steps: acquiring a group of state parameter values (SOH) of the power battery at the same moment every 1 second*,T*,SOC*,I*,V*)，SOH*At this time, the battery state of health value, T*For the battery temperature value at that time, SOC*At this time, the state of charge value of the battery, I*The current value of the battery at this time, V*The battery voltage value at the moment;
step two: preliminarily establishing a voltage value corresponding to each group of state parameter values in a five-dimensional data safety model of the power battery; for said current battery state parameter value (SOH)*,T*,SOC*,I*,V*) And a power battery five-dimensional data safety model for respectively judging SOH*,T*,SOC*With SOH in five-dimensional data security model1,SOH2,...,SOHn_SOH、T1,T2,...,Tn_T、SOC1,SOC2,...,SOCn_SOCThe more close SOH point, T point and SOC point are judged as
Figure BDA0002401034590000041
Judgment of I*In five-dimensional data security model I1,I2,...,In_IBetween the two points I, the judgment results are I 'and I', and (in a five-dimensional data security model) is checked
Figure BDA0002401034590000042
I') and (
Figure BDA0002401034590000043
I') whether the voltage value corresponding to the voltage V is null, and if one is null, the voltage V is set*Respectively stored in a five-dimensional data security model (
Figure BDA0002401034590000044
I') and (
Figure BDA0002401034590000045
I'), judging that the current state parameter value is a battery safety point in the voltage value corresponding to the current state parameter value, and entering the step five; and if the data is not empty, entering the step three.
Step three: judging a thermal runaway point of the battery by utilizing a five-dimensional data safety model of the power battery; setting comparison threshold value delta V of different deviation degrees of battery voltage1 *＝0.3V，ΔV2 *＝0.5V，ΔV3 *0.7V, (V) in five-dimensional data security model
Figure BDA0002401034590000046
I′,V′)、(
Figure BDA0002401034590000047
I ', V') are fitted to form a linear fit
Figure BDA0002401034590000048
I*) Corresponding voltage value
Figure BDA0002401034590000049
Comparison
Figure BDA00024010345900000410
And
Figure BDA00024010345900000411
and a threshold value Δ V1 *，ΔV2 *，ΔV3 *If Δ V1 *＜ΔV≤ΔV2 *Judging as a first-level thermal runaway point, if so
Figure BDA0002401034590000058
Judging as a secondary thermal runaway point if
Figure BDA0002401034590000059
Judging the thermal runaway point to be a third-level thermal runaway point, and entering the step five; if Δ V is less than or equal to Δ V1 *And judging that the current state parameter value is a battery safety point, and entering the step four.
Step four: updating a five-dimensional data security model of the power battery: for said state parameter value (SOH) judged as the battery safety point*,T*,SOC*,I*,V*) A mixture of (I ', V') and (I)*,V*) Linear interpolation is performed to obtain (I ",
Figure BDA0002401034590000051
) The compounds (I ', V') and (I)*,V*) Linear interpolation is performed to obtain (I',
Figure BDA0002401034590000052
) Voltage of the handle
Figure BDA0002401034590000053
Restored into five-dimensional data security model
Figure BDA0002401034590000054
I′)、(
Figure BDA0002401034590000055
I') in the corresponding voltage value, finishing the corresponding (in the five-dimensional data security model)
Figure BDA0002401034590000056
I′)、(
Figure BDA0002401034590000057
I ") updating of the voltage value.
Step five: judging whether the current power battery is out of control due to thermal runaway and the early warning level of the out of control due to thermal runaway according to the number and the properties of the battery out of control points in unit time; counting the state parameter value (SOH) of the latest 200 groups of batteries*,T*,SOC*,I*,V*) And judging the ratio of the thermal runaway points of the batteries with different grades, and assuming that the ratio of the primary runaway point is m1, the ratio of the secondary runaway point is m2 and the ratio of the tertiary runaway point is m 3. If m3 is more than 50%, judging that the three-stage thermal runaway is realized; if m3 is less than or equal to 50% and m2+ m3 is more than 50%, judging that the thermal runaway is secondary thermal runaway; if m2+ m3 is less than or equal to 50 percentAnd m1+ m2+ m3 is more than 50%, and the three-stage thermal runaway is judged. And finally, making corresponding response measures according to the judged thermal runaway danger level, wherein for example, the first-level thermal runaway response measure is that the vehicle runs at the power limit of 60% and reports a first-level thermal runaway warning, the second-level thermal runaway response measure is that the vehicle runs at the power limit of 20% and reports a second-level thermal runaway warning, and the third-level thermal runaway response measure is that the vehicle stops immediately and reports a third-level thermal runaway warning.
The above-mentioned embodiments only express the embodiments of the present invention, but not should be understood as the limitation of the scope of the invention patent, it should be noted that, for those skilled in the art, many variations and modifications can be made without departing from the concept of the present invention, and these all fall into the protection scope of the present invention.

Claims (1)

1. A power battery thermal runaway early warning method is characterized by comprising the following steps:
the method comprises the following steps: acquiring a group of state parameter values (SOH) of the power battery at the same moment every N seconds*,T*,SOC*,I*,V*) Wherein, SOH*At this time, the battery state of health value, T*For the battery temperature value at that time, SOC*At this time, the state of charge value of the battery, I*The current value of the battery at this time, V*The battery voltage value at the moment;
step two: preliminarily establishing a voltage value corresponding to each group of state parameter values in a five-dimensional data safety model of the power battery;
storing data of five parameters including SOH, temperature T, SOC, current I and voltage V of the power battery in a five-dimensional data safety model of the power battery, and enabling the SOH value of the power battery stored in the five-dimensional data safety model of the power battery to be within a normal SOH interval (80%, 100%)]The average number of the SOH points is n _ SOH, and the corresponding SOH points are as follows: SOH1,SOH2,...,SOHn_SOH(ii) a Setting the value T of the power battery stored in the model in a normal temperature range [ Tmin，Tmax]Is n _ T on average, and the corresponding T point is T1,T2,...,Tn_T(ii) a The SOC value of the power battery stored in the model is in a normal SOC interval (20%, 100%)]Is averaged to obtain n _ SOC, and the corresponding SOC point is the SOC1,SOC2,...,SOCn_SOC(ii) a Setting the value of the power battery I stored in the model in a normal current interval [ Imin，Imax]Is n _ I on average, and the corresponding I point is I1,I2,...,In_I(ii) a Before the SOH, T, SOC, I and V parameters of the power battery are not collected, the five-dimensional data safety model of the power battery is an empty model, and after the SOH, T, SOC, I and V parameters of the power battery are collected, the five-dimensional data safety model of the power battery is continuously updated;
the specific process of preliminarily establishing the voltage value corresponding to the state parameter value in the five-dimensional data safety model of the power battery is as follows: state parameter value (SOH) for current battery*,T*,SOC*,I*,V*) And a power battery five-dimensional data safety model for respectively judging SOH*,T*,SOC*With SOH in five-dimensional data security model1,SOH2,...,SOHn_SOH、T1,T2,...,Tn_T、SOC1,SOC2,...,SOCn_SOCThe more close SOH point, T point and SOC point are judged as
Figure FDA0002776518560000011
Judgment of I*In five-dimensional data security model I1,I2,...,In_IBetween the two points I, the judgment result is I 'and I';
in a security model for viewing five-dimensional data
Figure FDA0002776518560000012
And
Figure FDA0002776518560000013
whether the corresponding voltage value is empty or not, and if there is one empty, the voltage V is set*Respectively stored in a five-dimensional data security model
Figure FDA0002776518560000014
And
Figure FDA0002776518560000015
judging that the current state parameter value is a battery safety point in the corresponding voltage value, and entering the step five; if the number of the channels is not null, entering a third step;
step three: judging a thermal runaway point of the battery by utilizing a five-dimensional data safety model of the power battery;
setting comparison threshold value delta V of different deviation degrees of battery voltage1 *，ΔV2 *，...,ΔVn *The number of the comparison threshold values is determined according to the number of response measures with different levels of the thermal runaway of the lithium battery, if the thermal runaway of the lithium battery has n response measures with different levels of the thermal runaway, n comparison threshold values are set, the size of the comparison threshold values is calibrated according to a large amount of experimental data of the type of the battery, and the delta V is calculated according to the number of the response measures with different levels of the thermal runaway of the lithium battery1 *＜ΔV2 *＜..＜ΔVn *(ii) a In a five-dimensional data security model using data interpolation
Figure FDA0002776518560000021
Figure FDA0002776518560000022
Do interpolation, interpolate out
Figure FDA0002776518560000023
Corresponding voltage value
Figure FDA0002776518560000024
Comparison
Figure FDA0002776518560000025
And V*And a threshold value Δ V1 *，ΔV2 *，...,ΔVn *Is largeAnd if so, judging whether the set of state parameter values are the thermal runaway point and the grade of the thermal runaway point: if Δ Vs-1` *＜ΔV≤ΔVs *Wherein s is 2,3, n, judging that the state parameter value is an s-1 level thermal runaway point, and if delta V is adoptedn *If the current state parameter value is less than delta V, judging that the current state parameter value is an n-level thermal runaway point, and entering a fifth step; if Δ V is less than or equal to Δ V1 *Judging that the current state parameter value is a battery safety point, and entering the step four;
step four: updating a five-dimensional data security model of the power battery;
value of state parameter (SOH) for which it is determined that battery is safe*,T*,SOC*,I*,V*) A mixture of (I ', V') and (I)*,V*) Interpolation is carried out to obtain
Figure FDA0002776518560000026
Mixing (I ', V') and (I)*,V*) Interpolation is carried out to obtain
Figure FDA0002776518560000027
Voltage of the handle
Figure FDA0002776518560000028
Restore into five-dimensional data security model
Figure FDA0002776518560000029
Corresponding in the five-dimensional data security model is completed in the corresponding voltage value
Figure FDA00027765185600000210
The voltage value is updated, and the step five is entered;
step five: judging whether the current power battery is out of control due to thermal runaway and the early warning level of the out of control due to thermal runaway according to the number and the properties of the battery out of control points in unit time;
counting the state parameter values (SOH) of M groups of batteries nearest to the current moment*,T*,SOC*,I*,V*) Judging that the thermal runaway points of different grades account for the proportion of all the points, wherein miA ratio of i-class thermal runaway points (i ═ 1, 2.. times.n); setting different thermal runaway grades to compare threshold value r1,r2,...,rnM and r1,r2,...,rnThe size of the battery is calibrated according to a large amount of experimental data of the battery with the model; if m1+m2+,...,+mn≤r1Judging that the power battery is in a safe state; if mi+mi+1+,...,+mn＞riAnd m isi+1+,...,+mn≤ri+1(i-1, 2.., n-1), judging that the thermal runaway early warning grade of the power battery is i-level thermal runaway; if mn＞rnAnd judging that the thermal runaway early warning grade of the power battery is n-grade thermal runaway, and finishing the thermal runaway early warning of the power battery.
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