CN113777501A - SOH estimation method of battery module - Google Patents
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- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
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Abstract
The invention discloses a method for estimating SOH of a battery module, which relates to the technical field of new energy, and comprises a step of establishing an SOC-OCV table of a single battery in a tested battery module, a step of estimating the SOC of the tested battery module, a step of calculating the SOH of the battery module, a step of establishing an internal resistance aging curve of the battery module and a step of calculating the final SOH, wherein the method fully considers the internal actual condition of the battery module, selects a corresponding strategy to combine an ampere-hour integration method, an open-circuit voltage method and a Kalman filtering method in the SOC calculation process, can more accurately estimate the SOC of the battery module, fully considers the change of the internal resistance after the battery is aged, finally obtains the accurate SOH of the module through the two aspects of the SOC and the internal resistance, and can relieve the problem of overcharge and overdischarge of the battery module.
Description
Technical Field
The invention relates to the technical field of new energy, in particular to a method for estimating SOH of a battery module.
Background
In the field of battery management technology, in order to achieve accurate management of a battery, various battery state estimations are often required, including battery state of charge estimation (SOC), battery state of health estimation (SOH), battery power state estimation (SOP), battery state of energy (SOE), and the like, and the estimation of these states often requires acquisition of real-time critical parameters of the battery.
The battery power management is one of core contents of the battery management, has important significance on the control of the whole battery state and the prediction and estimation of the driving range of the electric vehicle, and simultaneously, because the non-linearity of the residual power estimation (SOC) of the power battery is influenced by various factors, the battery power estimation and prediction method is complex, and the accurate estimation of the SOC is difficult.
Because SOC prevents that the power battery from overcharging and overdischarging main foundation, only can the SOC of accurate estimation group battery effectively improve the utilization efficiency of power battery group, the life of group battery can be guaranteed to the SOH of accurate estimation battery module, and the qualitative law of influence factor of SOC estimation precision is as follows:
charging and discharging current is relative to rated charging and discharging working condition. The power battery generally shows that the large-current chargeable and dischargeable capacity is lower than the rated capacity, and the small-current chargeable and dischargeable capacity is larger than the rated capacity.
② temperature. The capacity of the battery pack at different temperatures changes to a certain extent, and the selection of the temperature section and the correction factor directly influence the performance and the available electric quantity of the battery.
And thirdly, battery capacity attenuation. The capacity of the battery gradually decreases during the cycling. Therefore, the correction condition for the electric quantity needs to be changed continuously, which is also an important factor affecting the accuracy of the model.
And fourthly, self-discharge. The chemical reaction in the battery produces the self-discharge phenomenon, makes it when placing, and the electric quantity loses, and the size of self-discharge mainly is relevant with ambient temperature, needs to carry out the correction according to the experimental data.
Consistency. The modeling and capacity estimation of the battery pack are different from those of single batteries, and the consistency difference of the battery pack has an important influence on the estimation of electric quantity. The charge of the battery pack is estimated and corrected according to the voltage of the overall battery, and if the battery difference is large, the estimation accuracy error is large.
In the prior art, the SOC estimation method for a single cell includes a discharge test method, an ampere-hour integration method, a kalman filter method, a neural network method, and the like, but each of the prior art methods has its own drawbacks: the discharge test method requires the battery pack to be in a constant-current discharge state and takes a large amount of measurement time; the accumulated error of the ampere-hour integral method along with the aging of the battery is larger, the data demand of the neural network method is large, the calculation is complex, and the practical application is poor; the Kalman filtering method is high in accuracy and high in practical applicability. The SOC estimation method of the module battery generally is characterized in that a module is equivalent to a large battery, the average SOC of the battery is taken as the SOC of the module, but the SOC of the module can be effectively estimated only under the condition of very good battery consistency by considering comparison of one surface, but the condition of large difference of single batteries in the module is ignored, and the actual estimation precision is poor; in addition, the SOC of all the single batteries in the module is calculated by adopting a single battery SOC estimation mode, the calculation amount is large, and the efficiency is low. That is, a method for effectively and accurately estimating the SOC of the battery module is needed to obtain an accurate SOH according to the SOC.
Disclosure of Invention
The invention aims to provide a method for estimating the SOH of a battery module aiming at the defects of the prior art, which fully considers the internal actual condition of the battery module, selects a corresponding strategy to combine an ampere-hour integral method, an open-circuit voltage method and a Kalman filtering method in the SOC calculation process, can estimate the SOC of the battery module more accurately, fully considers the change of internal resistance after the battery is aged, finally obtains the accurate SOH of the module through the two aspects of the SOC and the internal resistance, and can relieve the problem of overcharge and overdischarge of the battery module.
The invention provides a method for estimating SOH of a battery module, which comprises the following steps:
and a step of establishing an SOC-OCV table of the single batteries in the tested battery module, wherein the SOC-OCV table is established by fitting according to SOC-OCV measurement results of all the single batteries in the SOC point range in the battery module, and the SOC-OCV table comprises OCV and SOC values of each single battery, namely, the current SOC value of each single battery can be obtained in the SOC-OCV table by a table look-up method according to the current OCV value of each single battery.
Multiple experiments prove that the current of the single battery during long-time stable operation is selected within the range of 0.5-1C, which can better reflect the real characteristics of the battery, wherein C is the rated capacity of the battery, the standing time range of the single battery during long-time stable operation is 3-7 hours, the sampling interval time range is 0.05-1 second, the SOC taking interval is 1-10%, namely, a measuring point is selected at intervals of 1-10% of SOC; and fitting and establishing an SOC-OCV table according to SOC-OCV measurement results in all SOC point ranges of the battery.
More preferably, the current rate at which the battery under test stably operates for a long time is 0.5C.
SOC estimation step of the tested battery module, namely obtaining the monomer voltage of each single battery, sequencing all the single batteries according to the monomer voltages of the single batteries, and setting the OCV of the maximum single battery of the monomer voltages in the battery module as UmaxOCV of the cell having the minimum cell voltage is UminAnd calculating the average OCV of all the single cells in the battery module as Uave(ii) a And according to said Umax、UminAnd UaveSelecting a table lookup method to obtain the SOC corresponding to the tested battery module from the SOC-OCV table and updating the obtained SOC of the tested battery module by using a Kalman filtering method; or calculating the maximum sum of the single batteries in the tested battery module by an ampere-hour integration methodCalculating the minimum SOC by combining the SOC of the tested battery module which is updated by Kalman filtering and is obtained by a table look-up method to obtain the final SOC of the tested battery module;
the SOC estimation step of the tested battery module is specifically carried out if UaAnd UiAre all lower than the threshold voltage w, according to UaveAnd searching U from the SOC-OCV table by a table look-up methodave(i.e., current OCV) and set the SOC as SOCaveSOC at this timeaveThe SOC of the module is obtained, and the SOC of the battery pack is continuously updated through Kalman filtering; when U is turnedaAnd UiThe SOC corresponding to the average voltage corresponding to the monocells in the module is considered to be the SOC of the module when the consistency of the battery is good, and the SOC of the single battery obtained through table lookup of the average voltage also represents the SOC of the module.
The SOC estimation step of the tested battery module comprises the following specific steps: if U isaAnd UiIf any one of the voltage values is larger than the threshold voltage w, the SOC estimation is carried out according to the following steps:
step a, according to the maximum single voltage U of the single battery in the battery modulemaxMinimum cell voltage UminAnd an average voltage UaveAnd searching the corresponding SOC from the SOC-OCV table by a table look-up methodmax、SOCminAnd SOCave(ii) a I.e. when U is presentaAnd/or UiWhen the voltage is higher than the set threshold voltage w, the single battery with the largest module is selected first, and the voltage of the single battery is set to be UmaxThe corresponding SOC at this time can be found by a table look-up method and is set as SOCmaxThe upper limit of the module SOC, and the second step of selecting the minimum cell voltage in the module, and setting the voltage as SOCminThe corresponding SOC at this time can be found by a table look-up method and is set as SOCminIt is the lower limit of the module SOC.
Preferably, the threshold voltage w is a certain voltage value between 1 mv and 15 mv.
Further, the voltage of each single battery in the module is obtained through detection equipment.
Step b, by an ampere-hour integration method (AH integration method)
Continuously updating the SOCmax、SOCminWherein x is the current sampling point, (x +1) is the next time sampling point, I (x) represents the current charging and discharging current, Δ represents the size of the adopted interval, T represents the current temperature of the battery cell, and η (T) represents the temperature correction coefficient,
25℃Crefers to the capacity, C, of a single cell at 25 degrees CelsiusTThe capacity of the single battery under the actual temperature T under the current test environment is used as a temperature correction coefficient according to the ratio of the capacity to the actual temperature T; the SOC of the battery module output at the time of K is SOC1Then SOC is determined1(K)＝SOC1(K-1)·SOCmax(K)+(1-SOC1(K-1))·SOCmin(K) I.e. (K-1) is the last time, SOCmax(K)、SOCmin(K) The maximum and minimum SOC at the moment K are obtained by a table look-up method according to the maximum and minimum voltage at the moment K;
and, preferably, when Δ SOC>The system can generate fault alarm at 50 percent, wherein, the delta SOC is equal to the SOCmax-SOCmin；
Step c, considering that an ampere-hour integration method (AH integration method) can generate accumulated errors, calculating the SOC of the battery module by combining the Kalman filter and weighting the SOC and the SOC, thereby improving the estimation precision of the module, and according to the U, calculating the SOC of the battery module by using the battery moduleaveAnd searching the corresponding SOC from the SOC-OCV table by a table look-up methodaveContinuously updating the externally output lookup table SOC of the battery module by Kalman filtering as the externally output lookup table SOC of the battery module, wherein the externally output lookup table SOC of the battery module at the moment K is the SOC2Then, the final SOC of the battery module under test is SOC (k) ═ ω · SOC1(K)+(1-ω)·SOC2(K) Wherein, omega represents a weight factor, and the value range of omega is 0-1.
Battery module SOH calculationStep of calculating the SOH of the battery module according to the final SOC of the tested battery module obtained in the SOC estimation step1Δ AH is the SOC of the battery module to be externally output calculated from the time (K-1) to the time K by an ampere-hour integration method (AH integration method), specifically, the ampere-hour integration method (AH integration method) is the method described in step b in the SOC estimation step for the battery module under test, and Δ SOC is the SOC difference between the time (K-1) and the time K (K-1) -SOC (K);
establishing an internal resistance aging curve of the battery module, and calculating the direct-current internal resistance R of the battery module under the set SOC before an aging experimentnew(n)Then carrying out aging test on the battery module and carrying out periodic mixed pulse power test on the battery module to obtain the direct current internal resistance value R of the battery module after the aging testnow(n)R is to benow(n)、Rnew(n)Performing polynomial fitting (namely curve fitting) to obtain an aging curve (namely an SOC-direct current internal resistance curve) of the internal resistance of the tested battery module;
the method comprises the following steps of establishing an internal resistance aging curve of the battery module, specifically, carrying out a primary mixed pulse power test, carrying out pulse discharge on all single batteries in the tested battery module under a set SOC (state of charge), wherein the multiplying power of pulse current I is 0.5-1C, the discharge duration is 5-15 seconds, standing for 30-60 seconds after discharge, then starting pulse charge on the batteries with the pulse current I, the charge duration is 5-15 seconds, and circularly operating the step until all the single batteries are completely tested under the set SOC;
recording voltage values of the battery module in each pulse charging and pulse discharging process in the primary mixed pulse power test, and calculating direct-current internal resistance R of the battery module under the set SOC before the aging experimentnew(n)Value, in particular, Rnew(n)＝[(u(n)-u(n+1))/I+(u(n+3)-u(n+2))/I]/2 wherein u(n)The voltage of the battery module before the start of pulse discharge u(n+1)The voltage u of the battery module after the voltage drop at the instant of pulse discharge(n+2)For the battery module at the end of pulse dischargeVoltage of u(n+3)The battery module is the rebound voltage after the pulse is finished, and as mentioned above, I is the pulse current;
and then carrying out an aging test on the battery module, wherein the aging test mainly adopts a cycle test, and the battery module is subjected to a periodic mixed pulse power test in the aging test process until the direct current internal resistance R of the battery module at the moment Know(n)(K) And the direct current internal resistance R at the time of (K-1)now(n)Ratio R of (K-1)now(n)(K)/Rnow(n)(K-1)<Delta. time stop test, Rnow(n)Value calculation mode and Rnew(n)The values are the same, wherein delta is the value range [ 0-1 ]]Setting prior threshold value, and obtaining direct current internal resistance value R of the battery modulenow(n)、Rnew(n)Performing polynomial fitting (namely curve fitting) to obtain an aging curve (namely an SOC-direct current internal resistance curve) of the internal resistance of the tested battery module;
according to the current SOC value of the module (namely, the current SOC value of the module is calculated according to the strategy), R under the corresponding SOC is searched in the internal resistance aging curve of the battery modulenewAnd RnowCalculating to obtain SOH2＝1-(Rnow-Rnew)/RnewI.e. RnewDirect current internal resistance R of the front module of the aging experimentnowIs the direct current internal resistance of the module after the aging experiment.
A final SOH calculation step for avoiding obtaining the SOH in the SOH calculation step of the battery module1Obtaining SOH in the step of establishing the aging curve of the internal resistance of the battery module2So that the SOH obtained in the SOH calculation step of the battery module is calculated1And the SOH obtained in the step of establishing the internal resistance aging curve of the battery module2Adding weight to calculate the final SOH (x SOH) of the tested battery module1+(1-x)*SOH2Wherein x represents a weight factor, and the value range of x is 0-1.
Drawings
The foregoing and following detailed description of the invention will be apparent when read in conjunction with the following drawings, in which:
fig. 1 is a schematic diagram of a direct current internal resistance curve of a battery module under a set SOC before an aging experiment;
fig. 2 is a schematic diagram of the battery module after the aging experiment in direct current internal resistance fitting.
Detailed Description
The technical solutions for achieving the objects of the present invention are further illustrated by the following specific examples, and it should be noted that the technical solutions claimed in the present invention include, but are not limited to, the following examples.
Example 1
As a specific embodiment of the present invention, this embodiment discloses a method for estimating the SOH of a battery module, including the following steps:
and a step of establishing an SOC-OCV table of the single batteries in the tested battery module, wherein the SOC-OCV table is established by fitting according to SOC-OCV measurement results of all the single batteries in the SOC point range in the battery module, and the SOC-OCV table comprises OCV and SOC values of each single battery, namely, the current SOC value of each single battery can be obtained in the SOC-OCV table by a table look-up method according to the current OCV value of each single battery.
SOC estimation step of the tested battery module, namely obtaining the monomer voltage of each single battery, sequencing all the single batteries according to the monomer voltages of the single batteries, and setting the OCV of the maximum single battery of the monomer voltages in the battery module as UmaxOCV of the cell having the minimum cell voltage is UminAnd calculating the average OCV of all the single cells in the battery module as Uave(ii) a And according to said Umax、UminAnd UaveSelecting a table lookup method to obtain the SOC corresponding to the tested battery module from the SOC-OCV table and updating the obtained SOC of the tested battery module by using a Kalman filtering method; or calculating the maximum SOC and the minimum SOC of the single battery in the tested battery module by an ampere-hour integration method, and calculating the final SOC of the tested battery module by combining the SOC of the tested battery module which is updated by Kalman filtering and searched by a table look-up method;
a battery module SOH calculation step, wherein the final battery module to be tested is obtained according to the SOC estimation step of the battery module to be testedSOH of SOC (System on chip) calculation battery module1Δ AH is the SOC of the battery module to be externally output calculated from the time (K-1) to the time K by an ampere-hour integration method (AH integration method), specifically, the ampere-hour integration method (AH integration method) is the method described in step b in the SOC estimation step for the battery module under test, and Δ SOC is the SOC difference between the time (K-1) and the time K (K-1) -SOC (K);
establishing an internal resistance aging curve of the battery module, and calculating the direct-current internal resistance R of the battery module under the set SOC before an aging experimentnew(n)Then carrying out aging test on the battery module and carrying out periodic mixed pulse power test on the battery module to obtain the direct current internal resistance value R of the battery module after the aging testnow(n)R is to benow(n)、Rnew(n)Performing polynomial fitting (namely curve fitting) to obtain an aging curve (namely an SOC-direct current internal resistance curve) of the internal resistance of the tested battery module;
a final SOH calculation step for avoiding obtaining the SOH in the SOH calculation step of the battery module1Obtaining SOH in the step of establishing the aging curve of the internal resistance of the battery module2So that the SOH obtained in the SOH calculation step of the battery module is calculated1And the SOH obtained in the step of establishing the internal resistance aging curve of the battery module2Adding weight to calculate the final SOH (x SOH) of the tested battery module1+(1-x)*SOH2Wherein x represents a weight factor, and the value range of x is 0-1.
Example 2
As a specific implementation scheme of the present invention, the present embodiment discloses a method for estimating the SOH of a battery module, which includes a step of establishing an SOC-OCV table of a single battery in a tested battery module, a step of estimating the SOC of the tested battery module, a step of calculating the SOH of the battery module, a step of establishing an internal resistance aging curve of the battery module, and a step of calculating the final SOH.
The SOC-OCV table building method comprises the steps of building an SOC-OCV table of each single battery in the tested battery module, fitting and building the SOC-OCV table according to SOC-OCV measurement results of all the single batteries in the SOC point range in the battery module, wherein the SOC-OCV table comprises OCV and SOC values of each single battery, namely, the current SOC value of each single battery can be obtained in the SOC-OCV table through a table look-up method according to the current OCV value of each single battery. Multiple experiments prove that the real characteristics of the battery can be better reflected when the current of the single battery stably working for a long time is selected within the range of 0.5-1C, and more preferably, the current multiplying power of the battery stably working for a long time in the test is 0.5C; wherein C is the rated capacity of the battery, the standing time range of the single battery for long-time stable work is 3-7 hours, the sampling interval time range is 0.05-1 second, the SOC taking interval is 1-10%, namely, a measuring point is selected every 1-10% of SOC; and fitting and establishing an SOC-OCV table according to SOC-OCV measurement results in all SOC point ranges of the battery.
And SOC estimation step of the tested battery module, namely acquiring the single voltage of each single battery, sequencing all the single batteries according to the single voltages of the single batteries, and setting the OCV of the maximum single battery of the single voltages in the battery module as UmaxOCV of the cell having the minimum cell voltage is UminAnd calculating the average OCV of all the single cells in the battery module as Uave(ii) a And according to said Umax、UminAnd UaveDeviation value between:
if U isaAnd UiAre all lower than the threshold voltage w, according to UaveAnd searching U from the SOC-OCV table by a table look-up methodave(i.e., current OCV) and set the SOC as SOCaveSOC at this timeaveThe SOC of the module is obtained, and the SOC of the battery pack is continuously updated through Kalman filtering; when U is turnedaAnd UiWhen the cell voltage is lower than the threshold voltage w, the current consistency of the battery is better proved, namely when the battery consistency is good, the SOC corresponding to the average voltage corresponding to the monocells in the module can be considered as the SOC of the module, and the SOC of the single cell obtained by looking up the table through the average voltage also represents the SOC of the module;
if U isaAnd UiIf any one of the voltage values is larger than the threshold voltage w, the SOC estimation is carried out according to the following steps:
step a, according to electricityMaximum cell voltage U of cell in cell modulemaxMinimum cell voltage UminAnd an average voltage UaveAnd searching the corresponding SOC from the SOC-OCV table by a table look-up methodmax、SOCminAnd SOCave(ii) a I.e. when U is presentaAnd/or UiWhen the voltage is higher than the set threshold voltage w, the single battery with the largest module is selected first, and the voltage of the single battery is set to be UmaxThe corresponding SOC at this time can be found by a table look-up method and is set as SOCmaxThe upper limit of the module SOC, and the second step of selecting the minimum cell voltage in the module, and setting the voltage as SOCminThe corresponding SOC at this time can be found by a table look-up method and is set as SOCminIt is the lower limit of the module SOC.
By ampere-hour integration (AH integration)
Continuously updating the SOCmax、SOCminWherein x is the current sampling point, (x +1) is the next time sampling point, I (x) represents the current charging and discharging current, Δ represents the size of the adopted interval, T represents the current temperature of the battery cell, and η (T) represents the temperature correction coefficient,
25℃Crefers to the capacity, C, of a single cell at 25 degrees CelsiusTThe capacity of the single battery under the actual temperature T under the current test environment is used as a temperature correction coefficient according to the ratio of the capacity to the actual temperature T; the SOC of the battery module output at the time of K is SOC1Then SOC is determined1(K)＝SOC1(K-1)·SOCmax(K)+(1-SOC1(K-1))·SOCmin(K) I.e. (K-1) is the last time, SOCmax(K)、SOCmin(K) The maximum and minimum SOC at K are obtained by a table lookup method according to the maximum and minimum voltage at K, and preferably, when Δ SOC is>The system can generate fault alarm at 50 percent, wherein, the delta SOC is equal to the SOCmax-SOCmin；
Step c, taking account of ampere-hour integralsThe method (AH integration method) can generate accumulated error, so that the SOC of the battery module is calculated by combining with the Kalman filter and weighted, thereby improving the estimation precision of the module according to the UaveAnd searching the corresponding SOC from the SOC-OCV table by a table look-up methodaveContinuously updating the externally output lookup table SOC of the battery module by Kalman filtering as the externally output lookup table SOC of the battery module, wherein the externally output lookup table SOC of the battery module at the moment K is the SOC2Then, the final SOC of the battery module under test is SOC (k) ═ ω · SOC1(K)+(1-ω)·SOC2(K) Wherein, omega represents a weight factor, and the value range of omega is 0-1.
And, more preferably, the threshold voltage w is a certain voltage value between 1 mv and 15mv, and the voltage of each single battery in the module is obtained by the detection device.
The SOH calculation step of the battery module calculates the SOH of the battery module according to the final SOC of the tested battery module obtained in the SOC estimation step of the tested battery module1Δ AH is the SOC of the battery module to be externally output calculated from the time (K-1) to the time K by an ampere-hour integration method (AH integration method), specifically, the ampere-hour integration method (AH integration method) is the method described in step b in the SOC estimation step for the battery module under test, and Δ SOC is the SOC difference between the time (K-1) and the time K (K-1) -SOC (K);
establishing an internal resistance aging curve of the battery module, and calculating direct-current internal resistance R of the battery module under a set SOC before an aging experimentnew(n)Then carrying out aging test on the battery module and carrying out periodic mixed pulse power test on the battery module to obtain the direct current internal resistance value R of the battery module after the aging testnow(n)R is to benow(n)、Rnew(n)Performing polynomial fitting (namely curve fitting) to obtain an aging curve (namely an SOC-direct current internal resistance curve) of the internal resistance of the tested battery module; specifically, firstly, a primary mixed pulse power test is carried out, firstly, pulse discharge is carried out on all single batteries in a tested battery module under a set SOC (state of charge), the multiplying power of the pulse current I is 0.5-1C, and the discharge lastsStanding for 30-60 seconds after discharging for 5-15 seconds, then starting pulse charging on the battery by using pulse current I, wherein the charging time lasts for 5-15 seconds, and circularly operating the step until all the single batteries are completely tested under the set SOC;
recording voltage values of the battery module in each pulse charging and pulse discharging process in the primary mixed pulse power test, and calculating direct-current internal resistance R of the battery module under the set SOC before the aging experimentnew(n)Values, in particular, R as shown in FIG. 1new(n)＝[(u(n)-u(n+1))/I+(u(n+3)-u(n+2))/I]/2 wherein u(n)The voltage of the battery module before the start of pulse discharge u(n+1)The voltage u of the battery module after the voltage drop at the instant of pulse discharge(n+2)The voltage u of the battery module at the end of pulse discharge(n+3)The battery module is the rebound voltage after the pulse is finished, and as mentioned above, I is the pulse current;
and then carrying out an aging test on the battery module, wherein the aging test mainly adopts a cycle test, and the battery module is subjected to a periodic mixed pulse power test in the aging test process until the direct current internal resistance R of the battery module at the moment Know(n)(K) And the direct current internal resistance R at the time of (K-1)now(n)Ratio R of (K-1)now(n)(K)/Rnow(n)(K-1)<Delta. time stop test, Rnow(n)Value calculation mode and Rnew(n)The values are the same, wherein delta is the value range [ 0-1 ]]The prior threshold value is set, as shown in fig. 2, and the direct current internal resistance value R of the battery module is obtainednow(n)、Rnew(n)Performing polynomial fitting (namely curve fitting) to obtain an aging curve (namely an SOC-direct current internal resistance curve) of the internal resistance of the tested battery module;
according to the current SOC value of the module (namely, the current SOC value of the module is calculated according to the strategy), R under the corresponding SOC is searched in the internal resistance aging curve of the battery modulenewAnd RnowCalculating to obtain SOH2＝1-(Rnow-Rnew)/RnewI.e. RnewDirect current internal resistance R of the front module of the aging experimentnowFor aging and compactingAnd testing the direct current internal resistance of the module.
The final SOH calculation step is used for avoiding obtaining the SOH in the SOH calculation step of the battery module1Obtaining SOH in the step of establishing the aging curve of the internal resistance of the battery module2So that the SOH obtained in the SOH calculation step of the battery module is calculated1And the SOH obtained in the step of establishing the internal resistance aging curve of the battery module2Adding weight to calculate the final SOH (x SOH) of the tested battery module1+(1-x)*SOH2Wherein x represents a weight factor, and the value range of x is 0-1.
Claims (9)
1. A method for estimating SOH of a battery module is characterized in that: the method comprises the following steps:
establishing an SOC-OCV table of the single batteries in the tested battery module, fitting and establishing the SOC-OCV table according to SOC-OCV measurement results of all the single batteries in the SOC point taking range in the battery module, wherein the SOC-OCV table comprises an OCV value and an SOC value of each single battery;
SOC estimation step of the tested battery module, namely obtaining the monomer voltage of each single battery, sequencing all the single batteries according to the monomer voltages of the single batteries, and setting the OCV of the maximum single battery of the monomer voltages in the battery module as UmaxOCV of the cell having the minimum cell voltage is UminAnd calculating the average OCV of all the single cells in the battery module as Uave(ii) a And according to said Umax、UminAnd UaveSelecting a table lookup method to obtain the SOC corresponding to the tested battery module from the SOC-OCV table and updating the obtained SOC of the tested battery module by using a Kalman filtering method; or calculating the maximum SOC and the minimum SOC of the single battery in the tested battery module by an ampere-hour integration method, and calculating the final SOC of the tested battery module by combining the SOC of the tested battery module which is updated by Kalman filtering and searched by a table look-up method;
a battery module SOH calculation step for calculating the battery module according to the final SOC of the tested battery module obtained in the tested battery module SOC estimation stepSOH1Δ AH is the SOC of the external output of the battery module calculated by the ampere-hour integration method from the time (K-1) to the time K, and Δ SOC is the SOC difference between the time (K-1) and the time K (K-1) -SOC (K);
establishing an internal resistance aging curve of the battery module, and calculating the direct-current internal resistance R of the battery module under the set SOC before an aging experimentnew(n)Then carrying out aging test on the battery module and carrying out periodic mixed pulse power test on the battery module to obtain the direct current internal resistance value R of the battery module after the aging testnow(n)R is to benow(n)、Rnew(n)Performing polynomial fitting to obtain an aging curve of the internal resistance of the tested battery module;
a final SOH calculation step of calculating the SOH of the battery module1And the SOH obtained in the step of establishing the internal resistance aging curve of the battery module2Adding weight to calculate the final SOH (x SOH) of the tested battery module1+(1-x)*SOH2Wherein x represents a weight factor, and the value range of x is 0-1.
2. The method of estimating the SOH of a battery module according to claim 1, wherein: the current of the single battery during long-time stable work is selected within the range of 0.5-1C, wherein C is the rated capacity of the battery, the standing time range of the single battery during long-time stable work is 3-7 hours, the sampling interval time range is 0.05-1 second, and the SOC sampling interval is 1-10%.
3. The method of estimating the SOH of a battery module according to claim 2, wherein: more preferably, the current rate at which the battery under test stably operates for a long time is 0.5C.
4. The method of estimating the SOH of a battery module according to claim 1, wherein: the SOC estimation step of the tested battery module is specifically carried out if UaAnd UiAre all lower than the threshold voltage w, according to UaveBy means of a table look-up methodLooking up U from the SOC-OCV tableave(i.e., current OCV) and set the SOC as SOCaveSOC at this timeaveNamely the SOC of the module, and the SOC of the battery pack is continuously updated through Kalman filtering.
5. The method of claim 4, wherein the SOC of the battery module under test is estimated if U is greater than UaAnd UiIf any one of the voltage values is larger than the threshold voltage w, the SOC estimation is carried out according to the following steps:
step a, according to the maximum single voltage U of the single battery in the battery modulemaxMinimum cell voltage UminAnd an average voltage UaveAnd searching the corresponding SOC from the SOC-OCV table by a table look-up methodmax、SOCminAnd SOCave；
Step b, by ampere-hour integration method
Continuously updating the SOCmax、SOCminWherein x is the current sampling point, (x +1) is the next time sampling point, I (x) represents the current charging and discharging current, Δ represents the size of the adopted interval, T represents the current temperature of the battery cell, and η (T) represents the temperature correction coefficient,
refers to the capacity, C, of a single cell at 25 degrees CelsiusTIs the capacity of the single cell at the actual temperature T in the current test environment; the SOC of the battery module output at the time of K is SOC1Then, then
SOC1(K)＝SOC1(K-1)·SOCmax(K)+(1-SOC1(K-1))·SOCmin(K)；
Step c, according to the UaveFrom the SO by table look-upFinding out corresponding SOC from C-OCV tableaveContinuously updating the externally output lookup table SOC of the battery module by Kalman filtering as the externally output lookup table SOC of the battery module, wherein the externally output lookup table SOC of the battery module at the moment K is the SOC2Then, the final SOC of the battery module under test is SOC (k) ═ ω · SOC1(K)+(1-ω)·SOC2(K) Wherein, omega represents a weight factor, and the value range of omega is 0-1.
6. The method of estimating the SOH of a battery module according to claim 5, wherein: the threshold voltage w is a certain voltage value between 1 mv and 15 mv.
7. The method of estimating the SOH of a battery module according to claim 5, wherein: the voltage of each single battery in the module is obtained through detection equipment.
8. The method of estimating the SOH of a battery module according to claim 5, wherein: when Δ SOC>The system can generate fault alarm at 50 percent, wherein, the delta SOC is equal to the SOCmax-SOCmin。
9. The method of estimating the SOH of a battery module according to claim 5, wherein: the method comprises the following steps of establishing an internal resistance aging curve of the battery module, specifically, carrying out a primary mixed pulse power test, carrying out pulse discharge on all single batteries in the tested battery module under a set SOC (state of charge), wherein the multiplying power of pulse current I is 0.5-1C, the discharge duration is 5-15 seconds, standing for 30-60 seconds after discharge, then starting pulse charge on the batteries with the pulse current I, the charge duration is 5-15 seconds, and circularly operating the step until all the single batteries are completely tested under the set SOC;
recording voltage values of the battery module in each pulse charging and pulse discharging process in the primary mixed pulse power test, and calculating direct-current internal resistance R of the battery module under the set SOC before the aging experimentnew(n)The value of the one or more of the one,
Rnew(n)＝[(u(n)-u(n+1))/I+(u(n+3)-u(n+2))/I]/2 wherein u(n)The voltage of the battery module before the start of pulse discharge u(n+1)The voltage u of the battery module after the voltage drop at the instant of pulse discharge(n+2)The voltage u of the battery module at the end of pulse discharge(n+3)The voltage is the rebound voltage of the battery module after the pulse is finished;
then carrying out an aging test on the battery module, and carrying out a periodic mixed pulse power test on the battery module in the aging test process until the direct current internal resistance R of the battery module at the moment Know(n)(K) And the direct current internal resistance R at the time of (K-1)now(n)Ratio R of (K-1)now(n)(K)/Rnow(n)(K-1)<Stopping the test when delta is larger than the value range [ 0-1 ]]Setting prior threshold value, and obtaining direct current internal resistance value R of the battery modulenow(n)、Rnew(n)Performing polynomial fitting to obtain an aging curve of the internal resistance of the tested battery module;
according to the current SOC value of the module (namely, the current SOC value of the module is calculated according to the strategy), R under the corresponding SOC is searched in the internal resistance aging curve of the battery modulenewAnd RnowCalculating to obtain SOH2＝1-(Rnow-Rnew)/Rnew。
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114325431A (en) * | 2021-12-31 | 2022-04-12 | 北京西清能源科技有限公司 | Method and device for measuring and calculating direct current internal resistance of battery |
| CN114883701A (en) * | 2022-03-01 | 2022-08-09 | 东方电气集团科学技术研究院有限公司 | Method for controlling temperature of lithium ion battery in charging and discharging process in balanced manner |
| US11448703B2 (en) * | 2018-02-07 | 2022-09-20 | Lg Energy Solution, Ltd. | Device and method for estimating SOC via open-circuit voltage of battery |
| WO2024036432A1 (en) * | 2022-08-15 | 2024-02-22 | 宁德时代新能源科技股份有限公司 | Direct current resistance measurement method for battery, system, device, and storage medium |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103529393A (en) * | 2013-10-22 | 2014-01-22 | 南京汽车集团有限公司 | SOC (start of charge) estimation method of automobile power lithium battery |
| CN105676134A (en) * | 2016-01-08 | 2016-06-15 | 中国第一汽车股份有限公司 | SOH estimation method for vehicle lithium-ion power battery |
| CN109061511A (en) * | 2018-09-20 | 2018-12-21 | 苏州艾思控科技有限公司 | The method of battery cell SOH is calculated in a kind of battery management system in real time |
| CN109870655A (en) * | 2019-03-26 | 2019-06-11 | 上海工程技术大学 | A kind of evaluation method for lithium battery SOC |
| US20190207397A1 (en) * | 2017-12-29 | 2019-07-04 | Gogoro Inc. | Systems and methods for managing batteries based on usage |
| CN110632528A (en) * | 2019-11-04 | 2019-12-31 | 桂林电子科技大学 | Lithium battery SOH estimation method based on internal resistance detection |
| CN111337832A (en) * | 2019-12-30 | 2020-06-26 | 南京航空航天大学 | Power battery multidimensional fusion SOC and SOH online joint estimation method |
| CN113009367A (en) * | 2021-02-19 | 2021-06-22 | 哈尔滨理工大学 | Online testing device and method for battery health degree |
-
2021
- 2021-09-29 CN CN202111153311.8A patent/CN113777501A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103529393A (en) * | 2013-10-22 | 2014-01-22 | 南京汽车集团有限公司 | SOC (start of charge) estimation method of automobile power lithium battery |
| CN105676134A (en) * | 2016-01-08 | 2016-06-15 | 中国第一汽车股份有限公司 | SOH estimation method for vehicle lithium-ion power battery |
| US20190207397A1 (en) * | 2017-12-29 | 2019-07-04 | Gogoro Inc. | Systems and methods for managing batteries based on usage |
| CN109061511A (en) * | 2018-09-20 | 2018-12-21 | 苏州艾思控科技有限公司 | The method of battery cell SOH is calculated in a kind of battery management system in real time |
| CN109870655A (en) * | 2019-03-26 | 2019-06-11 | 上海工程技术大学 | A kind of evaluation method for lithium battery SOC |
| CN110632528A (en) * | 2019-11-04 | 2019-12-31 | 桂林电子科技大学 | Lithium battery SOH estimation method based on internal resistance detection |
| CN111337832A (en) * | 2019-12-30 | 2020-06-26 | 南京航空航天大学 | Power battery multidimensional fusion SOC and SOH online joint estimation method |
| CN113009367A (en) * | 2021-02-19 | 2021-06-22 | 哈尔滨理工大学 | Online testing device and method for battery health degree |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US11448703B2 (en) * | 2018-02-07 | 2022-09-20 | Lg Energy Solution, Ltd. | Device and method for estimating SOC via open-circuit voltage of battery |
| CN114325431A (en) * | 2021-12-31 | 2022-04-12 | 北京西清能源科技有限公司 | Method and device for measuring and calculating direct current internal resistance of battery |
| CN114325431B (en) * | 2021-12-31 | 2024-03-08 | 北京西清能源科技有限公司 | Method and device for measuring and calculating direct current internal resistance of battery |
| CN114883701A (en) * | 2022-03-01 | 2022-08-09 | 东方电气集团科学技术研究院有限公司 | Method for controlling temperature of lithium ion battery in charging and discharging process in balanced manner |
| CN114883701B (en) * | 2022-03-01 | 2024-05-10 | 东方电气集团科学技术研究院有限公司 | Method for controlling temperature of lithium ion battery in charging and discharging processes in balanced mode |
| WO2024036432A1 (en) * | 2022-08-15 | 2024-02-22 | 宁德时代新能源科技股份有限公司 | Direct current resistance measurement method for battery, system, device, and storage medium |
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