CN112698218B - Battery health state acquisition method and device and storage medium - Google Patents

Abstract

The embodiment of the invention relates to a battery health state acquisition method and device and a storage medium, wherein the method comprises the following steps: when the vehicle is powered on, judging whether a capacity change amount calculation condition is satisfied; calculating a capacity variation when the capacity variation calculation condition is judged to be satisfied; judging whether the capacity calculation condition is satisfied; calculating capacity when judging that the capacity calculation condition is satisfied; and calculating the health state of the battery according to the capacity variation and the capacity. By the method, the device and the storage medium, the corresponding relation between the total life cycle number of the battery and the SOH does not need to be measured, and test resources and time are saved; the aging degree of the actual capacity of the battery is reflected more truly, the charge state and the driving range estimation precision are improved, and good driving experience is provided for users.

Description

Battery health state acquisition method and device and storage medium

Technical Field

The invention relates to the technical field of batteries, in particular to a battery health state acquisition method and device and a storage medium.

Background

For new energy automobiles, especially pure electric automobiles, lithium ion power batteries are a main power source. SOH (State Of Health) Of a battery is an important parameter Of a power battery, and characterizes the aging degree Of the battery, that is, the capacity degradation and the increase Of internal resistance. SOH is an important issue for a pure electric vehicle as it relates to estimation of other important states of the battery, such as estimation of SOC (State of charge) and allowable power, which directly affect the range and driving experience.

The SOH estimation of the existing new energy automobile lithium ion power battery generally adopts the method of measuring the cycle number of the battery, and the SOH of the battery health state is obtained by inquiring a corresponding table of the cycle number and the SOH measured in advance. In practice, due to different temperatures of the batteries on different vehicles, different experienced working conditions, different batteries and other reasons, even the same cycle times, the SOH of different batteries are different, so that the method cannot truly reflect the actual SOH of the batteries, further inaccurate estimation of SOC, driving range and the like is caused, and the driving experience of a user is seriously affected.

Disclosure of Invention

The embodiment of the invention discloses a method and a device for acquiring the state of health of a battery and a storage medium, which can improve the calculation accuracy of the state of health of the battery.

The embodiment of the invention discloses a method for acquiring the health state of a battery, which comprises the following steps:

when the vehicle is powered on, judging whether a capacity change amount calculation condition is satisfied;

calculating a capacity variation when the capacity variation calculation condition is judged to be satisfied;

judging whether the capacity calculation condition is satisfied;

calculating capacity when judging that the capacity calculation condition is satisfied;

And calculating the health state of the battery according to the capacity variation and the capacity.

The second aspect of the embodiment of the invention discloses a battery health status acquisition device, which comprises:

the capacity change amount calculation condition judgment module is used for judging whether the capacity change amount calculation condition is met when the vehicle is electrified;

a capacity change amount calculation module for calculating a capacity change amount;

the capacity calculation condition judging module is used for judging whether the capacity calculation condition is met when the vehicle is electrified;

the capacity calculation module is used for calculating capacity;

the health state calculating module is used for calculating the health state according to the capacity variation and the capacity;

the health state adjusting module is used for acquiring historical battery health state data meeting preset conditions and adjusting the current battery health state according to the historical battery health state data.

A third aspect of the embodiment of the present invention discloses a computer-readable storage medium storing a computer program, wherein the computer program causes a computer to execute the battery state of health acquisition method disclosed in the first aspect of the embodiment of the present invention.

Compared with the prior art, the embodiment of the invention has the following beneficial effects: the corresponding relation between the cycle number of the whole life cycle of the battery and SOH does not need to be measured, so that the testing resources and time are saved; the aging degree of the actual capacity of the battery is reflected more truly, the charge state and the driving range estimation precision are improved, and good driving experience is provided for users.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

Fig. 1 is a schematic flow chart of an embodiment of a method for acquiring a battery state of health according to an embodiment of the present invention;

FIG. 2 is a flow chart of another embodiment of a method for acquiring battery state of health according to an embodiment of the present invention;

FIG. 3 is a flow chart of a method for acquiring a state of health of a battery according to an embodiment of the present invention;

fig. 4 is a schematic block diagram of an embodiment of a battery state of health acquisition device according to an embodiment of the present invention.

Detailed Description

The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

It should be noted that the terms "first," "second," "third," and "fourth," etc. in the description and claims of the present invention are used for distinguishing between different objects and not for describing a particular sequential order. The terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed or inherent to such process, method, article, or apparatus.

The embodiment of the invention provides a battery health state acquisition method, which mainly finds two SOC points corresponding to an OCV-SOC curve according to the OCV (open circuit voltage) in the use process of a vehicle according to the OCV-SOC curve of the battery, accumulates capacity variation between the two points, and divides the capacity variation by the SOC difference between the two points to obtain the actual capacity of the current battery. The ratio of the actual capacity of the current battery to the nominal capacity of the battery when leaving the factory is a percentage, namely SOH. The following description is made with reference to specific embodiments.

Fig. 1 is a schematic flow chart of an embodiment of a method for obtaining a battery state of health according to an embodiment of the present invention, including:

101. when the vehicle is powered on, judging whether a capacity change amount calculation condition is satisfied;

the capacity change amount calculation condition includes:

capacity change amount calculation condition a: the parking time is more than or equal to S1;

the parking time is the time from last power-down to the interval of power-up;

s1 is a preset capacity variation calculating condition parking time threshold, preferably, S1 can be the time required for removing the polarized terminal voltage to reach stability under the static state of the battery;

capacity change amount calculation condition B: the SOC value SOC1 of the OCV-SOC curve of the battery corresponding to the current voltage of the battery with the minimum monomer voltage is less than or equal to SOC_judge1;

the battery corresponding to the minimum single battery voltage is the battery with the lowest voltage among all single batteries in the current battery; the SOC value corresponding to the current voltage can be obtained through the OCV-SOC curve of the battery, and the value is recorded as SOC1;

the soc_judge1 is a preset capacity change amount calculation condition state of charge threshold, preferably, it may be set as the SOC lowest point of a plateau region of the OCV-SOC curve, where the plateau region of the OCV-SOC curve refers to a region where the slope of the OCV-SOC curve is smaller than a certain value, such as smaller than 8mV per 1% SOC;

When both the above conditions are satisfied, then the capacity change amount calculation condition is considered to be satisfied;

102. if the capacity variation amount calculation condition is satisfied, calculating the capacity variation amount;

and (3) respectively calculating:

wherein,

t1 is a time point when the capacity change amount calculation condition is judged to be satisfied;

the RTC is the time for calculating the delta Cap or the delta DchaCap, and can be acquired by internal timing of the BMS or acquired by the outside;

i is the current of the battery;

I _d a current in a discharge direction of the battery;

Δcap is the amount of change in the cumulative capacity from T1 as the time start;

Δdchacap is the cumulative amount of change in discharge direction capacity from T1 as the time start point;

103. judging whether the capacity calculation condition is satisfied;

the capacity calculation conditions include:

capacity calculation condition a: the parking time is more than or equal to S2;

the parking time is the time from last power-down to the interval of power-up;

s2 is a preset capacity calculation condition time threshold, preferably, S2 can be the time required for removing the polarized terminal voltage to reach stability under the static state of the battery;

capacity calculation condition B: the voltage value of the battery corresponding to the maximum single voltage is equal to or less than the SOC value SOC2 and equal to or less than SOC_judg2 in the OCV-SOC curve;

the battery corresponding to the maximum single voltage is the battery with the highest voltage among all single batteries; the SOC value corresponding to the current voltage can be obtained through the OCV-SOC curve of the battery, and the value is recorded as SOC2;

The soc_judge2 is a preset capacity calculation condition state of charge threshold, preferably, it may be set as the highest SOC point of a plateau region of the OCV-SOC curve, where the plateau region of the OCV-SOC curve refers to a region where the slope of the OCV-SOC curve is smaller than a certain value, such as less than 8mV per 1% SOC;

capacity calculation condition C: CT-T1 is less than or equal to T_Judge

Wherein:

CT is the time when the capacity calculation condition is judged;

t1 is a time point when the capacity change amount calculation condition is judged to be satisfied;

t_judge is a preset time difference threshold, which represents the maximum allowable value of the time difference between SOC1 and SOC2, and this value is not usually too large, because too large would cause long-term self-discharge of the battery not to be accumulated in Δcap, so that the final result accuracy is reduced, and in some embodiments, this threshold may be set to 5 days, for example;

capacity calculation condition D: ΔDchaCap is less than or equal to ΔDchacap_Judge

Wherein:

Δdchacap is the cumulative amount of change in discharge direction capacity from T1 as the time start point;

Δdchacap_judge is a preset capacity change threshold, which represents the maximum allowable discharge between SOC1 and SOC2, and prevents excessive discharge condition current sampling errors from being large so that Δcap inaccuracy leads to reduced accuracy of the result, and in some embodiments, this threshold may be set to 0.5×cap_rate, where cap_rate is the nominal capacity;

When all the four conditions are met, the capacity calculation condition is considered to be met;

104. if the capacity calculation condition is met, calculating the capacity;

the method specifically comprises the following steps:

wherein,

cap_cal is the actual capacity of the battery;

Δcap is the amount of change in the cumulative capacity from T1 as the time start;

105. calculating SOH according to the capacity variation and capacity

Wherein,

soh_c is the state of health (SOH) of the battery;

cap_rate is the nominal capacity of the battery factory.

From the above description, it can be seen that the embodiments of the present invention have at least the following advantages:

the optimal selection modes of the SOC1 and the SOC2 are adopted, so that the accumulation of the capacity variation delta Cap and the discharge direction capacity variation delta DchaCap is accurate, and the calculation precision of the current actual capacity of the battery and the SOH of the battery state reflecting the capacity is high;

the corresponding relation between the cycle number of the whole life cycle of the battery and SOH does not need to be measured, so that the testing resources and time are saved;

the aging degree of the actual capacity of the battery is reflected more truly, the charge state and the driving range estimation precision are improved, and good driving experience is provided for users.

Further, the soh_c data obtained by this calculation may also be adjusted by historical soh_c data, which is described in detail below with reference to the accompanying drawings.

Fig. 2 is a schematic flow chart of another embodiment of a method for obtaining a battery state of health according to an embodiment of the present invention, including:

201. when the vehicle is powered on, judging whether a capacity change amount calculation condition is satisfied;

the capacity change amount calculation condition includes:

capacity change amount calculation condition a: the parking time is more than or equal to S1;

the parking time is the time from last power-down to the interval of power-up;

s1 is a preset capacity variation calculating condition parking time threshold, preferably, S1 can be the time required for removing the polarized terminal voltage to reach stability under the static state of the battery;

capacity change amount calculation condition B: the SOC value SOC1 of the OCV-SOC curve of the battery corresponding to the current voltage of the battery with the minimum monomer voltage is less than or equal to SOC_judge1;

the battery corresponding to the minimum single battery voltage is the battery with the lowest voltage among all single batteries in the current battery; the SOC value corresponding to the current voltage can be obtained through the OCV-SOC curve of the battery, and the value is recorded as SOC1;

the soc_judge1 is a preset capacity change amount calculation condition state of charge threshold, preferably, it may be set as the SOC lowest point of a plateau region of the OCV-SOC curve, where the plateau region of the OCV-SOC curve refers to a region where the slope of the OCV-SOC curve is smaller than a certain value, such as smaller than 8mV per 1% SOC;

When both the above conditions are satisfied, then the capacity change amount calculation condition is considered to be satisfied;

202. if the capacity variation amount calculation condition is satisfied, calculating the capacity variation amount;

and (3) respectively calculating:

wherein,

t1 is a time point when the capacity change amount calculation condition is judged to be satisfied;

the RTC is the time for calculating the delta Cap or the delta DchaCap, and can be acquired by internal timing of the BMS or acquired by the outside;

i is the current of the battery;

I _d a current in a discharge direction of the battery;

Δcap is the amount of change in the cumulative capacity from T1 as the time start;

Δdchacap is the cumulative amount of change in discharge direction capacity from T1 as the time start point;

203. judging whether the capacity calculation condition is satisfied;

the capacity calculation conditions include:

capacity calculation condition a: the parking time is more than or equal to S2;

the parking time is the time from last power-down to the interval of power-up;

s2 is a preset capacity calculation condition time threshold, preferably, S2 can be the time required for removing the polarized terminal voltage to reach stability under the static state of the battery;

capacity calculation condition B: the voltage value of the battery corresponding to the maximum single voltage is equal to or less than the SOC value SOC2 and equal to or less than SOC_judg2 in the OCV-SOC curve;

the battery corresponding to the maximum single voltage is the battery with the highest voltage among all single batteries; the SOC value corresponding to the current voltage can be obtained through the OCV-SOC curve of the battery, and the value is recorded as SOC2;

The soc_judge2 is a preset capacity calculation condition state of charge threshold, preferably, it may be set as the highest SOC point of a plateau region of the OCV-SOC curve, where the plateau region of the OCV-SOC curve refers to a region where the slope of the OCV-SOC curve is smaller than a certain value, such as less than 8mV per 1% SOC;

capacity calculation condition C: CT-T1 is less than or equal to T_Judge

Wherein:

CT is the time when the capacity calculation condition is judged;

t1 is a time point when the capacity change amount calculation condition is judged to be satisfied;

t_judge is a preset time difference threshold, which represents the maximum allowable value of the time difference between SOC1 and SOC2, and this value is not usually too large, because too large would cause long-term self-discharge of the battery not to be accumulated in Δcap, so that the final result accuracy is reduced, and in some embodiments, this threshold may be set to 5 days, for example;

capacity calculation condition D: ΔDchaCap is less than or equal to ΔDchacap_Judge

Wherein:

Δdchacap is the cumulative amount of change in discharge direction capacity from T1 as the time start point;

Δdchacap_judge is a preset capacity change threshold, which represents the maximum allowable discharge between SOC1 and SOC2, and prevents excessive discharge condition current sampling errors from being large so that Δcap inaccuracy leads to reduced accuracy of the result, and in some embodiments, this threshold may be set to 0.5×cap_rate, where cap_rate is the nominal capacity;

When all the four conditions are met, the capacity calculation condition is considered to be met;

204. if the capacity calculation condition is met, calculating the capacity;

the method specifically comprises the following steps:

wherein,

cap_cal is the actual capacity of the battery;

Δcap is the amount of change in the cumulative capacity from T1 as the time start;

205. calculating SOH according to the capacity variation and the capacity;

wherein,

soh_c is the state of health (SOH) of the battery;

cap_rate is the nominal capacity of the battery factory;

206. acquiring historical SOH data meeting preset conditions, and adjusting the SOH according to the historical SOH data;

specifically, a preset number of historical SOH data meeting a preset time interval condition and a preset SOH difference condition can be obtained, and then the current SOH is adjusted according to the historical SOH data;

in the embodiment of the present invention, there may be various ways to obtain historical SOH data meeting preset conditions and adjust the current SOH according to the historical SOH data, which is described in the following specific details:

a mode one,

The historical SOH data meeting the preset conditions specifically comprises the following steps:

recent historical SOH data satisfying the following two conditions simultaneously:

condition a: SOH acquisition time interval is less than or equal to S3;

the SOH acquisition time interval is the difference between the current SOH acquisition time and the historical SOH acquisition time; the S3 is a preset time difference threshold, which may be set to 2 months, for example;

Condition B: SOH_C-SOH_C_Targe2I is less than or equal to SOH_Judge;

wherein, the soh_c_target2 is a historical SOH value, and the soh_j-age is a preset SOH difference threshold, for example, may be set to 1%;

after the historical SOH data meeting the preset conditions is obtained, the mode of adjusting the current SOH according to the historical SOH data may be specifically as follows:

calculate soh_n= (soh_c+soh_c_target2)/2

Wherein, the SOH_N is the adjusted SOH, and is used and stored as the result value of the current SOH;

a second mode,

The historical SOH data meeting the preset conditions specifically comprises the following steps:

a preset number of historical SOH data satisfying the following three conditions simultaneously:

condition a: SOH acquisition time interval is less than or equal to S3;

the SOH acquisition time interval is the difference between the current SOH acquisition time and the historical SOH acquisition time; the S3 is a preset time difference threshold, which may be set to 2 months, for example;

condition B: SOH_C-SOH_C_Targe2I is less than or equal to SOH_Judge;

wherein, the soh_c_target2 is a historical SOH value, and the soh_j-age is a preset SOH difference threshold, for example, may be set to 1%;

condition C: if the number of the historical SOH data meeting the condition A and the condition B simultaneously exceeds the preset number, selecting a preset number of historical SOH data which is more recent to the current SOH acquisition time;

After the historical SOH data meeting the preset conditions is obtained, the specific mode of adjusting the current SOH according to the historical SOH data may be specifically as follows:

calculate soh_n= (soh_c + Σsoh_c_target 2_m)/(m+1)

Wherein, the SOH_N is the adjusted SOH, and is used and stored as the result value of the current SOH; the sigma SOH_C_target2_M is the sum of the preset number of history SOH meeting the condition, and the preset number is specifically M;

mode III,

The historical SOH data meeting the preset conditions specifically comprises the following steps:

all historical SOH data satisfying the following two conditions simultaneously:

condition a: SOH acquisition time interval is less than or equal to S3;

the SOH acquisition time interval is the difference between the current SOH acquisition time and the historical SOH acquisition time; the S3 is a preset time difference threshold, which may be set to 2 months, for example;

condition B: SOH_C-SOH_C_Targe2I is less than or equal to SOH_Judge;

wherein, the soh_c_target2 is a historical SOH value, and the soh_j-age is a preset SOH difference threshold, for example, may be set to 1%;

after the historical SOH data of the preset condition is obtained, the specific mode of adjusting the current SOH according to the historical SOH data may be specifically:

calculate soh_n= (soh_c + Σsoh_c_target 2_n)/(n+1)

Wherein, the SOH_N is the adjusted SOH, and is used and stored as the result value of the current SOH; the sigma SOH_C_target2_N is the sum of all the history SOH meeting the condition, and the number of the history SOH meeting the condition is specifically N;

207. storing the SOH_N obtained after the adjustment;

the soh_n is used and stored as a result of the current calculation of the SOH, and the soh_n obtained at this time is used as history data when the SOH is calculated after power-up.

Compared with an embodiment of the battery state of health acquisition method of the present invention, the above embodiment adds the step of adjusting the current SOH data according to the historical SOH data meeting the preset conditions, so that the obtained result has better continuity, is closer to the real situation, and has better effect.

The embodiments of the method for estimating SOH are described above in a logically forward manner, and in fact, since the estimation of SOH is not typically performed in a power-up-down process, in actual implementation, the embodiments implemented in a time forward manner may not look exactly the same as the above schemes, and the embodiments implemented in a time forward manner are described below.

Fig. 3 is a schematic flow chart of another embodiment of a method for obtaining a battery state of health according to an embodiment of the present invention, including:

301. When the vehicle is powered on, judging whether a capacity change amount calculation process in progress exists;

when an ongoing capacity change amount calculation process exists, there is generally a corresponding record in the battery management system, from which it can be known whether an ongoing capacity change amount calculation process exists;

if yes, judging whether the capacity change amount calculation process is out of date;

because each capacity change amount calculation process has a certain period, whether the capacity change amount calculation condition is met or not is judged again after the period is exceeded;

if not, judging whether the capacity change amount calculation condition is satisfied;

302. judging whether the capacity change amount calculation process has expired;

the capacity change amount calculation process generally has a certain time limit, for example, in some embodiments of the present invention, may be limited to not more than 5 days from the time when the capacity change amount calculation condition is satisfied;

if not, calculating the capacity variation;

if the capacity change amount calculation condition is out of date, judging whether the capacity change amount calculation condition is met or not;

303. judging whether a capacity change amount calculation condition is satisfied;

the capacity change amount calculation condition includes:

capacity change amount calculation condition a: the parking time is more than or equal to S1;

The parking time is the time from last power-down to the interval of power-up;

s1 is a preset capacity variation calculating condition parking time threshold, preferably, S1 can be the time required for removing the polarized terminal voltage to reach stability under the static state of the battery;

capacity change amount calculation condition B: the SOC value SOC1 of the OCV-SOC curve of the battery corresponding to the current voltage of the battery with the minimum monomer voltage is less than or equal to SOC_judge1;

the battery corresponding to the minimum single battery voltage is the battery with the lowest voltage among all single batteries in the current battery; the SOC value corresponding to the current voltage can be obtained through the OCV-SOC curve of the battery, and the value is recorded as SOC1;

the soc_judge1 is a preset capacity change amount calculation condition state of charge threshold, preferably, it may be set as the SOC lowest point of a plateau region of the OCV-SOC curve, where the plateau region of the OCV-SOC curve refers to a region where the slope of the OCV-SOC curve is smaller than a certain value, such as smaller than 8mV per 1% SOC;

when both the above conditions are satisfied, then the capacity change amount calculation condition is considered to be satisfied;

304. calculating the capacity variation;

and (3) respectively calculating:

wherein,

t1 is a time point when the capacity change amount calculation condition is judged to be satisfied;

the RTC is the time for calculating the delta Cap or the delta DchaCap, and can be acquired by internal timing of the BMS or acquired by the outside;

I is the current of the battery;

I _d a current in a discharge direction of the battery;

Δcap is the amount of change in the cumulative capacity from T1 as the time start;

Δdchacap is the cumulative amount of change in discharge direction capacity from T1 as the time start point;

305. judging whether the capacity calculation condition is satisfied;

the capacity calculation conditions include:

capacity calculation condition a: the parking time is more than or equal to S2;

the parking time is the time from last power-down to the interval of power-up;

s2 is a preset capacity calculation condition time threshold, preferably, S2 can be the time required for removing the polarized terminal voltage to reach stability under the static state of the battery;

capacity calculation condition B: the voltage value of the battery corresponding to the maximum single voltage is equal to or less than the SOC value SOC2 and equal to or less than SOC_judg2 in the OCV-SOC curve;

the battery corresponding to the maximum single voltage is the battery with the highest voltage among all single batteries; the SOC value corresponding to the current voltage can be obtained through the OCV-SOC curve of the battery, and the value is recorded as SOC2;

the soc_judge2 is a preset capacity calculation condition state of charge threshold, preferably, it may be set as the highest SOC point of a plateau region of the OCV-SOC curve, where the plateau region of the OCV-SOC curve refers to a region where the slope of the OCV-SOC curve is smaller than a certain value, such as less than 8mV per 1% SOC;

Capacity calculation condition C: CT-T1 is less than or equal to T_Judge

Wherein:

CT is the time when the capacity calculation condition is judged;

t1 is a time point when the capacity change amount calculation condition is judged to be satisfied;

t_judge is a preset time difference threshold, which represents the maximum allowable value of the time difference between SOC1 and SOC2, and this value is not usually too large, because too large would cause long-term self-discharge of the battery not to be accumulated in Δcap, so that the final result accuracy is reduced, and in some embodiments, this threshold may be set to 5 days, for example;

capacity calculation condition D: ΔDchaCap is less than or equal to ΔDchacap_Judge

Wherein:

Δdchacap is the cumulative amount of change in discharge direction capacity from T1 as the time start point;

Δdchacap_judge is a preset capacity change threshold, which represents the maximum allowable discharge between SOC1 and SOC2, and prevents excessive discharge condition current sampling errors from being large so that Δcap inaccuracy leads to reduced accuracy of the result, and in some embodiments, this threshold may be set to 0.5×cap_rate, where cap_rate is the nominal capacity;

when all the four conditions are met, the capacity calculation condition is considered to be met;

306. calculating the actual capacity of the current battery;

the method comprises the following steps:

wherein Δcap is the amount of change in the cumulative capacity from T1 as the time start point;

SOC2 is the SOC value of the battery corresponding to the maximum monomer voltage obtained when judging whether the capacity calculation condition is met or not in an OCV-SOC curve;

SOC1 is the SOC value of the OCV-SOC curve of the battery corresponding to the current voltage of the minimum cell voltage when judging whether the capacity variation calculation condition is satisfied;

307. calculating SOH according to the capacity and the capacity variation;

wherein,

soh_c is the state of health (SOH) of the battery;

cap_rate is the nominal capacity of the battery factory;

308. acquiring historical SOH data meeting preset conditions, and adjusting the SOH according to the historical SOH data;

specifically, a preset number of historical SOH data meeting a preset time interval condition and a preset SOH difference condition can be obtained, and then the current SOH is adjusted according to the historical SOH data;

in the embodiment of the present invention, there may be various ways to obtain historical SOH data meeting preset conditions and adjust the current SOH according to the historical SOH data, which is described in the following specific details:

a mode one,

The historical SOH data meeting the preset conditions specifically comprises the following steps:

recent historical SOH data satisfying the following two conditions simultaneously:

condition a: SOH acquisition time interval is less than or equal to S3;

the SOH acquisition time interval is the difference between the current SOH acquisition time and the historical SOH acquisition time; the S3 is a preset time difference threshold, which may be set to 2 months, for example;

Condition B: SOH_C-SOH_C_Targe2I is less than or equal to SOH_Judge;

wherein, the soh_c_target2 is a historical SOH value, and the soh_j-age is a preset SOH difference threshold, for example, may be set to 1%;

after the historical SOH data meeting the preset conditions is obtained, the mode of adjusting the current SOH according to the historical SOH data may be specifically as follows:

calculate soh_n= (soh_c+soh_c_target2)/2

Wherein, the SOH_N is the adjusted SOH, and is used and stored as the result value of the current SOH;

a second mode,

The historical SOH data meeting the preset conditions specifically comprises the following steps:

a preset number of historical SOH data satisfying the following three conditions simultaneously:

condition a: SOH acquisition time interval is less than or equal to S3;

the SOH acquisition time interval is the difference between the current SOH acquisition time and the historical SOH acquisition time; the S3 is a preset time difference threshold, which may be set to 2 months, for example;

condition B: SOH_C-SOH_C_Targe2I is less than or equal to SOH_Judge;

wherein, the soh_c_target2 is a historical SOH value, and the soh_j-age is a preset SOH difference threshold, for example, may be set to 1%;

condition C: if the number of the historical SOH data meeting the condition A and the condition B simultaneously exceeds the preset number, selecting a preset number of historical SOH data which is more recent to the current SOH acquisition time;

After the historical SOH data meeting the preset conditions is obtained, the specific mode of adjusting the current SOH according to the historical SOH data may be specifically as follows:

calculate soh_n= (soh_c + Σsoh_c_target 2_m)/(m+1)

Wherein, the SOH_N is the adjusted SOH, and is used and stored as the result value of the current SOH; the sigma SOH_C_target2_M is the sum of the preset number of history SOH meeting the condition, and the preset number is specifically M;

mode III,

The historical SOH data meeting the preset conditions specifically comprises the following steps:

all historical SOH data satisfying the following two conditions simultaneously:

condition a: SOH acquisition time interval is less than or equal to S3;

the SOH acquisition time interval is the difference between the current SOH acquisition time and the historical SOH acquisition time; the S3 is a preset time difference threshold, which may be set to 2 months, for example;

condition B: SOH_C-SOH_C_Targe2I is less than or equal to SOH_Judge;

wherein, the soh_c_target2 is a historical SOH value, and the soh_j-age is a preset SOH difference threshold, for example, may be set to 1%;

after the historical SOH data of the preset condition is obtained, the specific mode of adjusting the current SOH according to the historical SOH data may be specifically:

calculate soh_n= (soh_c + Σsoh_c_target 2_n)/(n+1)

Wherein, the SOH_N is the adjusted SOH, and is used and stored as the result value of the current SOH; the sigma SOH_C_target2_N is the sum of all the history SOH meeting the condition, and the number of the history SOH meeting the condition is specifically N;

309. storing the SOH_N obtained after the adjustment;

the soh_n is used and stored as a result of the current calculation of the SOH, and the soh_n obtained at this time is used as history data when the SOH is calculated after power-up.

The embodiment of the invention also provides a battery health status acquisition device, as shown in fig. 4, which is a schematic block diagram of the battery health status acquisition device provided by the invention, comprising:

a capacity variation calculation condition judgment module 401 for judging whether a capacity variation calculation condition is satisfied when the vehicle is powered on;

the capacity change amount calculation condition includes:

capacity change amount calculation condition a: the parking time is more than or equal to S1;

the parking time is the time from last power-down to the interval of power-up;

s1 is a preset capacity variation calculating condition parking time threshold, preferably, S1 can be the time required for removing the polarized terminal voltage to reach stability under the static state of the battery;

Capacity change amount calculation condition B: the SOC value SOC1 of the OCV-SOC curve of the battery corresponding to the current voltage of the battery with the minimum monomer voltage is less than or equal to SOC_judge1;

the battery corresponding to the minimum single battery voltage is the battery with the lowest voltage among all single batteries in the current battery; the SOC value corresponding to the current voltage can be obtained through the OCV-SOC curve of the battery, and the value is recorded as SOC1;

the soc_judge1 is a preset capacity change amount calculation condition state of charge threshold, preferably, it may be set as the SOC lowest point of a plateau region of the OCV-SOC curve, where the plateau region of the OCV-SOC curve refers to a region where the slope of the OCV-SOC curve is smaller than a certain value, such as smaller than 8mV per 1% SOC;

when both the above conditions are satisfied, then the capacity change amount calculation condition is considered to be satisfied;

a capacity change amount calculation module 402 for calculating a capacity change amount;

specifically, the method comprises the following steps of:

wherein,

t1 is a time point when the capacity change amount calculation condition is judged to be satisfied;

the RTC is the time for calculating the delta Cap or the delta DchaCap, and can be acquired by internal timing of the BMS or acquired by the outside;

i is the current of the battery;

I _d a current in a discharge direction of the battery;

Δcap is the amount of change in the cumulative capacity from T1 as the time start;

Δdchacap is the cumulative amount of change in discharge direction capacity from T1 as the time start point;

a capacity calculation condition judgment module 403, configured to judge whether a capacity calculation condition is satisfied when the vehicle is powered on;

the capacity calculation conditions include:

capacity calculation condition a: the parking time is more than or equal to S2;

the parking time is the time from last power-down to the interval of power-up;

s2 is a preset capacity calculation condition time threshold, preferably, S2 can be the time required for removing the polarized terminal voltage to reach stability under the static state of the battery;

capacity calculation condition B: the voltage value of the battery corresponding to the maximum single voltage is equal to or less than the SOC value SOC2 and equal to or less than SOC_judg2 in the OCV-SOC curve;

the battery corresponding to the maximum single voltage is the battery with the highest voltage among all single batteries; the SOC value corresponding to the current voltage can be obtained through the OCV-SOC curve of the battery, and the value is recorded as SOC2;

the soc_judge2 is a preset capacity calculation condition state of charge threshold, preferably, it may be set as the highest SOC point of a plateau region of the OCV-SOC curve, where the plateau region of the OCV-SOC curve refers to a region where the slope of the OCV-SOC curve is smaller than a certain value, such as less than 8mV per 1% SOC;

capacity calculation condition C: CT-T1 is less than or equal to T_Judge

Wherein:

CT is the time when the capacity calculation condition is judged;

t1 is a time point when the capacity change amount calculation condition is judged to be satisfied;

t_judge is a preset time difference threshold, which represents the maximum allowable value of the time difference between SOC1 and SOC2, and this value is not usually too large, because too large would cause long-term self-discharge of the battery not to be accumulated in Δcap, so that the final result accuracy is reduced, and in some embodiments, this threshold may be set to 5 days, for example;

capacity calculation condition D: ΔDchaCap is less than or equal to ΔDchacap_Judge

Wherein:

Δdchacap is the cumulative amount of change in discharge direction capacity from T1 as the time start point;

Δdchacap_judge is a preset capacity change threshold, which represents the maximum allowable discharge between SOC1 and SOC2, and prevents excessive discharge condition current sampling errors from being large so that Δcap inaccuracy leads to reduced accuracy of the result, and in some embodiments, this threshold may be set to 0.5×cap_rate, where cap_rate is the nominal capacity;

when all the four conditions are met, the capacity calculation condition is considered to be met;

a capacity calculation module 404 for calculating capacity;

the method is specifically used for calculation:

wherein,

cap_cal is the actual capacity of the battery;

Δcap is the amount of change in the cumulative capacity from T1 as the time start;

a state of health calculation module 405 for calculating a state of health (SOH) according to the capacity variation and the capacity

Wherein,

soh_c is the state of health (SOH) of the battery;

cap_rate is the nominal capacity of the battery factory;

the health state adjusting module 406 is configured to obtain historical SOH data that meets a preset condition, and adjust the current SOH according to the historical SOH data;

specifically, a preset number of historical SOH data meeting a preset time interval condition and a preset SOH difference condition can be obtained, and then the current SOH is adjusted according to the historical SOH data;

in the embodiment of the present invention, there may be various ways to obtain historical SOH data meeting preset conditions and adjust the current SOH according to the historical SOH data, which is described in the following specific details:

a mode one,

The historical SOH data meeting the preset conditions specifically comprises the following steps:

recent historical SOH data satisfying the following two conditions simultaneously:

condition a: SOH acquisition time interval is less than or equal to S3;

the SOH acquisition time interval is the difference between the current SOH acquisition time and the historical SOH acquisition time; the S3 is a preset time difference threshold, which may be set to 2 months, for example;

Condition B: SOH_C-SOH_C_Targe2I is less than or equal to SOH_Judge;

wherein, the soh_c_target2 is a historical SOH value, and the soh_j-age is a preset SOH difference threshold, for example, may be set to 1%;

after the historical SOH data meeting the preset conditions is obtained, the mode of adjusting the current SOH according to the historical SOH data may be specifically as follows:

calculate soh_n= (soh_c+soh_c_target2)/2

Wherein, the SOH_N is the adjusted SOH, and is used and stored as the result value of the current SOH;

a second mode,

The historical SOH data meeting the preset conditions specifically comprises the following steps:

a preset number of historical SOH data satisfying the following three conditions simultaneously:

condition a: SOH acquisition time interval is less than or equal to S3;

the SOH acquisition time interval is the difference between the current SOH acquisition time and the historical SOH acquisition time; the S3 is a preset time difference threshold, which may be set to 2 months, for example;

condition B: SOH_C-SOH_C_Targe2I is less than or equal to SOH_Judge;

wherein, the soh_c_target2 is a historical SOH value, and the soh_j-age is a preset SOH difference threshold, for example, may be set to 1%;

condition C: if the number of the historical SOH data meeting the condition A and the condition B simultaneously exceeds the preset number, selecting a preset number of historical SOH data which is more recent to the current SOH acquisition time;

After the historical SOH data meeting the preset conditions is obtained, the specific mode of adjusting the current SOH according to the historical SOH data may be specifically as follows:

calculate soh_n= (soh_c + Σsoh_c_target 2_m)/(m+1)

Wherein, the SOH_N is the adjusted SOH, and is used and stored as the result value of the current SOH; the sigma SOH_C_target2_M is the sum of the preset number of history SOH meeting the condition, and the preset number is specifically M;

mode III,

The historical SOH data meeting the preset conditions specifically comprises the following steps:

all historical SOH data satisfying the following two conditions simultaneously:

condition a: SOH acquisition time interval is less than or equal to S3;

the SOH acquisition time interval is the difference between the current SOH acquisition time and the historical SOH acquisition time; the S3 is a preset time difference threshold, which may be set to 2 months, for example;

condition B: SOH_C-SOH_C_Targe2I is less than or equal to SOH_Judge;

wherein, the soh_c_target2 is a historical SOH value, and the soh_j-age is a preset SOH difference threshold, for example, may be set to 1%;

after the historical SOH data of the preset condition is obtained, the specific mode of adjusting the current SOH according to the historical SOH data may be specifically:

calculate soh_n= (soh_c + Σsoh_c_target 2_n)/(n+1)

Wherein, the SOH_N is the adjusted SOH, and is used and stored as the result value of the current SOH; the sigma SOH_C_target2_N is the sum of all the history SOH meeting the condition, and the number of the history SOH meeting the condition is specifically N;

a storage module 407, configured to store the soh_n obtained after the adjustment;

the soh_n is used and stored as a result of the current calculation of the SOH, and the soh_n obtained at this time is used as history data when the SOH is calculated after power-up.

From the above description, it can be seen that the embodiments of the present invention have at least the following advantages:

the optimal selection modes of the SOC1 and the SOC2 are adopted, so that the accumulation of the capacity variation delta Cap and the discharge direction capacity variation delta DchaCap is accurate, and the calculation precision of the current actual capacity of the battery and the SOH of the battery state reflecting the capacity is high;

the corresponding relation between the cycle number of the whole life cycle of the battery and SOH does not need to be measured, so that the testing resources and time are saved;

the aging degree of the actual capacity of the battery is reflected more truly, the charge state and the driving range estimation precision are improved, and good driving experience is provided for users;

the step of adjusting the SOH data according to the historical SOH data meeting the preset conditions is added, so that the obtained result has better continuity, is closer to the real situation and has better effect. .

The embodiment of the invention also discloses a vehicle which comprises the battery health state acquisition device.

The embodiment of the invention also discloses a computer readable storage medium which stores a computer program, wherein the computer program enables a computer to execute any one of the battery health state acquisition methods.

The embodiments of the present invention also disclose a computer program product, wherein the computer program product, when run on a computer, causes the computer to perform some or all of the steps of the method as in the method embodiments above.

The embodiment of the invention also discloses an application release platform which is used for releasing a computer program product, wherein when the computer program product runs on a computer, the computer is enabled to execute part or all of the steps of the method in the method embodiments.

Those of ordinary skill in the art will appreciate that all or part of the steps of the various methods of the above embodiments may be implemented by a program that instructs associated hardware, the program may be stored in a computer readable storage medium including Read-Only Memory (ROM), random access Memory (Random Access Memory, RAM), programmable Read-Only Memory (Programmable Read-Only Memory, PROM), erasable programmable Read-Only Memory (Erasable Programmable Read Only Memory, EPROM), one-time programmable Read-Only Memory (OTPROM), electrically erasable programmable Read-Only Memory (EEPROM), compact disc Read-Only Memory (Compact Disc Read-Only Memory, CD-ROM) or other optical disk Memory, magnetic disk Memory, tape Memory, or any other medium that can be used for carrying or storing data that is readable by a computer.

The above describes in detail a method and apparatus for acquiring a battery state of health and a storage medium disclosed in the embodiments of the present invention, and specific examples are applied herein to illustrate the principles and embodiments of the present invention, where the above description of the embodiments is only for helping to understand the method and core idea of the present invention; meanwhile, as those skilled in the art will have variations in the specific embodiments and application scope in accordance with the ideas of the present invention, the present description should not be construed as limiting the present invention in view of the above.

Claims (10)

1. A battery state of health acquisition method, comprising:

when the vehicle is powered on, judging whether a capacity change amount calculation condition is satisfied;

calculating a capacity variation when the capacity variation calculation condition is judged to be satisfied;

judging whether the capacity calculation condition is satisfied;

calculating capacity when judging that the capacity calculation condition is satisfied;

calculating the state of health of the battery according to the capacity variation and the capacity;

acquiring historical battery health state data meeting preset conditions, and adjusting the current battery health state according to the historical battery health state data;

the obtaining the historical battery health state data meeting the preset conditions specifically comprises the following steps:

And acquiring a preset number of historical battery health state data which accords with a preset time interval condition and a preset battery health state difference condition.

2. The battery state of health acquisition method according to claim 1, wherein:

the determining whether the capacity variation amount calculation condition is satisfied further includes:

when the vehicle is powered on, judging whether a capacity change amount calculation process in progress exists currently;

if yes, the step of judging whether the capacity calculation condition is met or not is carried out;

and if not, performing the step of judging whether the capacity change amount calculation condition is satisfied.

3. The battery state of health acquisition method according to claim 1, wherein:

the determining whether the capacity variation amount calculation condition is satisfied further includes:

when the vehicle is powered on, judging whether a capacity change amount calculation process in progress exists currently;

if the capacity variation calculation process in progress is judged, judging whether the capacity variation calculation process in progress is out of date or not;

if judging that the capacity variation calculation process is not in progress, carrying out the step of judging whether the capacity variation calculation condition is met or not;

if the result of judging whether the running capacity change amount calculating process is out of date, the step of judging whether the capacity change amount calculating condition is met is carried out;

And if the result of judging whether the running capacity change amount calculating process is outdated is not outdated, carrying out the step of judging whether the capacity calculating condition is met.

4. A battery state of health acquisition method as set forth in any one of claims 1 to 3, wherein:

the capacity change amount calculation condition includes simultaneously satisfying the following two conditions:

capacity change amount calculation condition a: the parking time is more than or equal to S1;

the S1 is a preset capacity change amount calculation condition parking time threshold;

capacity change amount calculation condition B: SOC1 is less than or equal to SOC_judge1;

the SOC1 is the SOC value of the OCV-SOC curve of the battery corresponding to the current voltage of the minimum single voltage;

and the SOC_judge1 is a preset capacity change amount calculation condition state-of-charge threshold.

5. The battery state of health acquisition method as set forth in claim 4, wherein:

the calculation of the capacity variation includes:

and (3) calculating:

wherein,

t1 is a time point when the capacity change amount calculation condition is judged to be satisfied;

the RTC is the time for calculating the delta Cap or the delta DchaCap, and can be acquired by internal timing of the BMS or acquired by the outside;

i is the current of the battery;

I _d a current in a discharge direction of the battery;

Δcap is the amount of change in the cumulative capacity from T1 as the time start;

Δdchacap is the amount of change in capacity in the discharge direction accumulated from T1 as the time start point.

6. The battery state of health acquisition method according to claim 5, wherein:

the capacity calculation conditions include satisfying the following four conditions:

capacity calculation condition a: the parking time is more than or equal to S2;

the parking time is the time from last power-down to the interval of power-up;

s2 is a preset capacity calculation condition time threshold;

capacity calculation condition B: SOC2 is less than or equal to SOC_judg2;

the SOC2 is the SOC value of an OCV-SOC curve of the battery corresponding to the maximum single voltage; the SOC_judg2 is a preset capacity calculation condition state-of-charge threshold;

capacity calculation condition C: CT-T1 is less than or equal to T_Judge

Wherein:

the CT is the time when the capacity calculation condition is judged;

the T1 is a time point when the capacity change amount calculation condition is judged to be satisfied;

T_Judge is a preset time difference threshold;

capacity calculation condition D: ΔDchaCap is less than or equal to ΔDchacap_Judge

Wherein:

the Δdchacap is the cumulative amount of change in the discharge direction capacity from T1 as the time start point; and the DeltaDchaCap_Judge is a preset upper limit of the capacity change amount threshold.

7. The battery state of health acquisition method as set forth in claim 6, wherein:

The computing capacity includes:

wherein,

the Cap_cal is the actual capacity of the battery;

the Δcap is the amount of change in the cumulative capacity from T1 to the time start point.

8. The battery state of health acquisition method according to claim 7, wherein:

the calculating the battery health status according to the capacity variation and the capacity comprises:

and (3) calculating:

wherein,

the SOH_C is the state of health of the battery;

the Cap_rate is the nominal capacity of the battery factory.

9. A battery state of health acquisition device, characterized by comprising:

the capacity change amount calculation condition judgment module is used for judging whether the capacity change amount calculation condition is met when the vehicle is electrified;

a capacity change amount calculation module for calculating a capacity change amount;

the capacity calculation condition judging module is used for judging whether the capacity calculation condition is met when the vehicle is electrified;

the capacity calculation module is used for calculating capacity;

the health state calculating module is used for calculating the health state according to the capacity variation and the capacity;

a health state adjusting module for obtaining historical battery health state data meeting preset conditions and adjusting the current battery health state according to the historical battery health state data,

The obtaining the historical battery health state data meeting the preset conditions specifically comprises the following steps:

and acquiring a preset number of historical battery health state data which accords with a preset time interval condition and a preset battery health state difference condition.

10. A computer-readable storage medium storing a computer program, wherein the computer program causes a computer to execute the battery state of health acquisition method according to any one of claims 1 to 8.