CN111044927B - Power battery service life evaluation method and system - Google Patents
Power battery service life evaluation method and system Download PDFInfo
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Abstract
The invention discloses a method and a system for evaluating the service life of a power battery. The battery life evaluation method adopts a test working condition curve composed of constant power segments as a test reference, and predicts the life of the power battery through the capacity attenuation corresponding to each constant power segment, and comprises the following steps: establishing a charge capacity attenuation model and a discharge capacity attenuation model of the battery under different powers; establishing a test working condition, wherein the test working condition consists of a plurality of groups of characteristic segments, and each group of characteristic segments corresponds to one power and one duration; and calculating the proportion of each power in the test working condition, and predicting the service life of the power battery according to the charging capacity attenuation model and the discharging capacity attenuation model corresponding to each power. The battery life evaluation method provided by the invention adopts the test working condition curve composed of the constant power segments as the test reference, and predicts the service life of the power battery through the capacity attenuation corresponding to each constant power segment, thereby reducing the test complexity and improving the test efficiency.
Description
Technical Field
The embodiment of the invention relates to a battery testing technology, in particular to a method and a system for evaluating the service life of a power battery.
Background
At present, the technology and scale of the pure electric vehicle are greatly developed, but the corresponding test standards are not comprehensive enough, for example, the service life test of the power battery of the electric vehicle is generally evaluated by adopting the national standard working condition, but the characteristic values of the national standard working condition and the actual working condition are not consistent, so the service life test result is not accurate.
In order to enable the test condition to be closer to the use working condition, the standard NEDC working condition can be adopted for discharge test, the NEDC is mainly used for rack test of the whole vehicle, and for the test of the whole vehicle, the indexes for measuring the service life of the battery are mainly the driving mileage and the service life, wherein the driving mileage corresponds to the cycle life of the battery, and the service life corresponds to the calendar life of the battery. The testing under the NEDC working condition consumes a long testing time, and a life test needs about one year. For the evaluation of the service life of the power battery, a model method can also be adopted, for example, a model for predicting the service life of the power battery by quantitatively researching the attenuation of the capacity of the power battery by taking the battery SOC and the SEI film resistance as parameters, or a power battery service life prediction model designed based on an artificial neural network. However, the prediction model requires fine model parameters and has high model complexity.
Therefore, a method and a system for evaluating the service life of a battery, which are convenient to test and have a test result close to the actual driving condition of the electric vehicle, are urgently needed.
Disclosure of Invention
The invention provides a method and a system for evaluating the service life of a power battery, which aim to simplify the test process and enable the test result to be closer to the actual driving condition of an electric automobile.
In a first aspect, an embodiment of the present invention provides a method for evaluating a service life of a power battery, where a test condition curve composed of constant power segments is used as a test reference, and the service life of the power battery is predicted through a capacity attenuation corresponding to each constant power segment, where the method includes: establishing a charge capacity attenuation model and a discharge capacity attenuation model of the battery under different powers; establishing a test working condition, wherein the test working condition consists of a plurality of groups of characteristic segments, and each group of characteristic segments corresponds to one power and one duration; and calculating the proportion of each power in the test working condition, and predicting the service life of the power battery according to the charging capacity attenuation model and the discharging capacity attenuation model corresponding to each power.
Further, the charge capacity fade model is:
ln YC＝K1Tln XC+B1T
in the formula, YCFor charge capacity fade, K1T、B1TIs the coefficient, X, of the charge capacity decay model at temperature TCIs the set charging energy throughput.
Further, the discharge capacity decay model is as follows:
ln YD＝K2Tln XD+B2T
in the formula, YDFor charge capacity fade, K2T、B2TIs the coefficient of the decay model of the discharge capacity at temperature T, XDIs the set discharge energy throughput.
Further, the test condition is reconstructed from the original condition, and the reconstruction includes:
calculating the charge time ratio, the discharge time ratio and the standing time ratio of the original working condition;
dividing the original working condition into charging segments, discharging segments and standing segments by taking a first threshold and a second threshold as boundary points, and recording the duration of each charging segment, each discharging segment and each standing segment, the average power of each charging segment and the average power of each discharging segment;
performing primary classification on the charging segments, the discharging segments and the standing segments according to power through clustering analysis, and performing secondary classification on each type of the charging segments, each type of the discharging segments and each type of the standing segments according to duration through clustering analysis to obtain a group of charging characteristic segments, a group of discharging characteristic segments and a group of standing characteristic segments;
and forming the test working condition by using the group of charging characteristic segments, the group of discharging characteristic segments and the group of standing characteristic segments, wherein the charging time ratio, the discharging time ratio and the standing time ratio in the test working condition are the same as those in the original working condition.
Further, the first threshold is 1KW, and the second threshold is-1 KW.
Further, the segment with the power larger than the first threshold and the duration larger than 1S in the original working condition is a charging segment; the segment with the power smaller than the second threshold value and the duration longer than 1S in the original working condition is a charging segment; and the segment with the power smaller than the first threshold and longer than the second threshold and the duration longer than 1S in the original working condition is a standing segment.
And further, screening the charging characteristic segments and the discharging characteristic segments, if the power of one charging characteristic segment or one discharging characteristic segment is less than 5KW and the duration is less than 10S, classifying the charging segment or the discharging segment corresponding to the charging characteristic segment or the discharging characteristic segment as a standing segment, and performing primary classification and secondary classification on the charging segment, the discharging segment and the standing segment again through clustering analysis to obtain a group of charging characteristic segments, a group of discharging characteristic segments and a group of standing characteristic segments.
Further, when the secondary classification is performed, the classification number of the charging segment and the discharging segment with the minimum power and the maximum power is 1.
In a second aspect, an embodiment of the present invention further provides a system for evaluating a service life of a power battery, where a test condition curve composed of constant power segments is used as a test reference, and the service life of the power battery is predicted through a capacity attenuation corresponding to each constant power segment.
The system comprises a constant power cycle test unit, a test condition construction unit and a battery life prediction unit, wherein the constant power test unit is used for carrying out cycle test under different powers so as to establish a charging capacity attenuation model and a discharging capacity attenuation model of the battery under different powers; the test working condition construction unit is used for establishing a test working condition, wherein the test working condition consists of a plurality of groups of characteristic segments, and each group of characteristic segments corresponds to one type of power and one type of duration; the battery life prediction unit is used for calculating the proportion of each power in the test working condition and predicting the life of the power battery according to the charging capacity attenuation model and the discharging capacity attenuation model corresponding to each power.
Further, the device also comprises a temperature control unit used for adjusting the temperature of the test environment when the cycle test is carried out.
The battery life evaluation method provided by the invention adopts the test working condition curve composed of constant power segments as a test reference, and predicts the life of the power battery through the capacity attenuation corresponding to each constant power segment.
Drawings
FIG. 1 is a flowchart of a battery life evaluation method according to a first embodiment;
FIG. 2 is a flowchart of a test condition construction method in the first embodiment;
FIG. 3 is a diagram illustrating curves of original operating conditions used in the first embodiment;
FIG. 4 is a graph showing the characteristic curves of the discharge segment in the first embodiment;
FIG. 5 is a graph showing the characteristic curves of the discharge segments in the first embodiment;
FIG. 6 is a schematic diagram of the stationary segment characteristic curve in the first embodiment;
FIG. 7 is a graph illustrating test conditions according to the first embodiment;
fig. 8 is a schematic diagram of a battery life evaluation system according to the second embodiment.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
Example one
Fig. 1 is a flowchart of a battery life evaluation method according to an embodiment, and referring to fig. 1, the battery life evaluation method includes the steps of:
s1, establishing a charging capacity attenuation model and a discharging capacity attenuation model of the battery under different powers.
In the step, the result data of battery charging and discharging is collected in a cycle test mode, and a charging capacity attenuation model and a discharging capacity attenuation model are constructed in a data fitting mode. Specifically, before the test, the charging power, the charging throughput under the charging power, the discharging throughput under the discharging power, and the experimental temperature are determined. During the test, the battery is placed in a constant temperature test box, the test can be carried out from the upper limit of the SOC (State of Charge) of the battery, the battery is discharged until the residual electric quantity of the battery reaches a set lower limit value or a specified value provided by a battery supplier, then the battery is charged until the residual electric quantity of the battery reaches the set upper limit value, and after the cycle test is carried out according to the discharging and charging processes, the battery is kept still for a certain time to acquire the test data of the battery. The acquired test data includes capacity fade, and the exemplary acquisition process of the capacity fade is to periodically record the fading change of the capacity from the Beginning value of the Life to a certain time point later, and the capacity fade is expressed as a percentage of the initial BOL (initial Life) capacity by the following formula:
in the formula, txRepresents the 1C capacity measurement time, t, at the time of the test0Representing the initial lifetime 1C capacity nominal time. The test may also be performed starting from the lower limit of the battery SOC, the test procedure being the reverse of the above.
For a power battery, time and temperature are two important factors influencing the service life of the battery, for accurately representing an attenuation model and simultaneously reducing the time for carrying out the test, different test environment temperatures are respectively set based on an Arrhenius equation to carry out an accelerated life test, and the actual failure time of the battery can be calculated by a linear epitaxy method by using the capacity attenuation obtained by the test.
Illustratively, the charge capacity decay model is constructed in the form of:
yC＝f(Tc，xc)
in the formula, yCFor charge capacity decay, TcTo test the ambient temperature, xcA charge capacity throughput corresponding to the charging power.
The form of the discharge capacity decay model constructed is as follows:
yD＝f(TD，xD)
in the formula, yDFor decay of discharge capacity, TDTo test the ambient temperature, xcA charge capacity throughput corresponding to the discharge power.
S2, establishing a test working condition, wherein the test working condition consists of a plurality of groups of characteristic segments, and each group of characteristic segments corresponds to one power and one duration.
In the step, the adopted test working condition is not an irregular working condition curve similar to the national standard working condition, but a test working condition consisting of a plurality of constant power characteristic segments. Wherein, the characteristic segments are divided into a charging characteristic segment, a discharging characteristic segment and a standing characteristic segment, the charging characteristic segment at least comprises three power characteristics and three durations, for example, the power and time characteristics of one charging characteristic segment are expressed by (P, T), then the characteristics of the charging characteristic segment adopted in the test working condition comprise (3.6kW, 5s), (11.6kW, 7s), (21.8kW, 10s), correspondingly, the charging characteristic segment at least comprises three power characteristics and three durations, the power of the standing characteristic segment is zero, and the standing characteristic segment at least comprises three durations.
For example, the test condition may be constructed by reconstructing a typical power battery test condition, for example, reconstructing the typical power battery test condition by using a cluster analysis method, or constructing the power battery test condition by acquiring rack test data and actual road driving data, segmenting the constructed power battery test condition according to power, calculating an average power, a power root-mean-square, a maximum power, a minimum power and a peak-to-average ratio coefficient of each power segment, and calculating a power representative value of each power segment according to the values. Dividing the power range into L grades from large to small, judging the sub-interval of the power representative value of each segment, and taking the typical power segment as a constant power segment to further form a test working condition.
And S3, calculating the proportion of each power in the test working condition, and predicting the service life of the power battery according to the charging capacity attenuation model and the discharging capacity attenuation model corresponding to each power.
Combining the step S1 and the step S2, in the step S1, each attenuation model corresponds to one power and one ambient temperature, and the test condition in the step S2 is composed of a plurality of constant power characteristic segments, so that the life attenuation can be superimposed according to the proportion of the battery used under different powers based on the test condition, and then the result of life evaluation is obtained.
The battery life evaluation method shown in fig. 1 adopts a test working condition curve composed of constant power segments as a test reference, and predicts the life of the power battery through the capacity attenuation corresponding to each constant power segment.
As a preferable scheme, the charge capacity fade model constructed in step S1 is:
ln YC＝K1Tln XC+B1T
in the formula, YCFor charge capacity fade, K1T、B1TCoefficient of charge capacity decay model at temperature T, XCIs the set charging energy throughput. The discharge capacity decay model constructed was:
ln YD＝K2Tln XD+B2T
in the formula, YDFor charge capacity fade, K2T、B2TCoefficient of discharge capacity decay model, X, at temperature TDIs the set discharge energy throughput.
A direct functional relation is established between the energy throughput and the capacity attenuation, the complexity of a charging capacity attenuation model and the complexity of a discharging capacity attenuation model are reduced, and the charging capacity attenuation model and the discharging capacity attenuation model are easy to be matched with a test working condition for use.
Fig. 2 is a flowchart of a test condition construction method in the first embodiment, and referring to fig. 2, as a preferred solution, in step S2, the test condition is reconstructed from an original condition, and the reconstruction includes:
s201, analyzing curve characteristics of original working conditions.
In this step, analyzing the curve characteristics includes calculating a charge time ratio, a discharge time ratio, a rest time ratio, an average charge power, and an average discharge power of the original operating condition.
S202, segmenting the original working condition according to power to obtain a charging segment, a discharging segment and a standing segment.
In the step, a first threshold and a second threshold are used as demarcation points, an original working condition is divided into a charging segment, a discharging segment and a standing segment, the duration of each charging segment, each discharging segment and each standing segment, the average power of each charging segment and each discharging segment are recorded, wherein the first threshold is 1KW, and the second threshold is-1 KW. Specifically, the segment with the power greater than the first threshold and the duration greater than 1S in the original working condition is the charging segment, the segment with the power less than the second threshold and the duration greater than 1S in the original working condition is the charging segment, and the segment with the power less than the first threshold and the duration greater than 1S in the original working condition is the standing segment. Fig. 3 is a schematic diagram of an original operating condition curve adopted in the first embodiment, fig. 4 is a schematic diagram of a discharge segment characteristic curve in the first embodiment, fig. 5 is a schematic diagram of a discharge segment characteristic curve in the first embodiment, and fig. 6 is a schematic diagram of a standing segment characteristic curve in the first embodiment, referring to fig. 3 to fig. 6, after segmentation, 61 charging segments, 56 discharging segments, and 24 standing segments are obtained.
S203, classifying the charging segment, the discharging segment and the standing segment through twice clustering analysis to form a charging characteristic segment, a discharging characteristic segment and a standing characteristic segment.
In this step, the charging segments, the discharging segments and the standing segments are classified once according to power through clustering analysis, for example, a K-means clustering method, and each charging segment, each discharging segment and each standing segment are classified twice according to duration time through clustering analysis, so as to obtain a group of charging characteristic segments, a group of discharging characteristic segments and a group of standing characteristic segments.
For example, in the first classification, the charging segments are clustered according to the average power, the charging segments are clustered into three classes, the central value of each cluster is the power of the charging feature segment, in the second classification, each class of charging segments is clustered according to the duration, and the central value of each cluster is the duration of the class of charging feature segment. When the optional secondary classification is performed, the classification number of the charging segment with the minimum power and the maximum power is 1. For example, after primary classification, the power of three types of charging fragments is 3.6KW, 11.6KW, 21.8KW, then the number of classes is 1 when performing secondary classification according to duration for the charging fragment with power of 3.6KW and the charging fragment with power of 21.8KW, the number of classes is greater than 1 when performing secondary classification according to duration for the charging fragment with power of 11.6KW, for example, 2, finally, 4 types of charging feature fragments can be obtained, that is, fragment 1(3.6KW, 5S), fragment 2(11.6KW, 7S), fragment 3(11.6KW, 15S), fragment 4(21.8KW, 10S). The clustering principle that the section of discharging adopted is unanimous with the section of charging, it is optional, during once classification, the section of discharging is clustered into four types, the power of four types of section of discharging is 3.2KW respectively, 9.6KW, 16.7KW, 31.1KW, the power is minimum, the classification number of the section of discharging of power maximum is 1, when carrying out secondary classification according to duration to the section of discharging that the power is 9.6KW, 16.7KW, the classification number is 2, can obtain 6 types of section of discharging characteristic finally, namely section 5(3.2KW, 6S), section 6(9.6KW, 13S), section 7(9.6KW, 42S), section 8(16.7KW, 123S), section 9(16.7KW, 19S), section 10(31.1KW, 58S). The power of the standing segments is zero, when the secondary classification is carried out, the classification number is 3, and three types of standing characteristic segments, namely segment 11(0, 4S), segment 12(0, 18S) and segment 13(0, 48S), can be finally obtained.
Optionally, the step further includes screening the charging characteristic segments and the discharging characteristic segments, if the power of one charging characteristic segment or one discharging characteristic segment is less than 5KW and the duration is less than 10S, classifying the charging segment or the discharging segment corresponding to the charging characteristic segment or the discharging characteristic segment as a standing segment, and performing primary classification and secondary classification on the charging segment, the discharging segment and the standing segment through clustering analysis to obtain a group of charging characteristic segments, a group of discharging characteristic segments and a group of standing characteristic segments. The precision of the test working condition can be improved through screening of the special diagnosis fragments.
And S204, forming a test working condition by using the charging characteristic segment, the discharging characteristic segment and the standing characteristic segment.
Fig. 7 is a schematic diagram of a test condition curve in the first embodiment, and referring to fig. 7, in this step, a test condition is formed by using a set of charging characteristic segments, a set of discharging characteristic segments, and a set of standing characteristic segments, where a charging time ratio, a discharging time ratio, and a standing time ratio in the test condition are the same as those in an original condition. When a test working condition is specifically established, the use frequency of each type of characteristic segment is not fixed, and the charging time ratio, the discharging time ratio and the standing time ratio in the test working condition are the same as those in the original working condition. Preferably, when the characteristic segments are used for constructing the test working condition, the average charging power and the average discharging power of the original working condition can be simultaneously referred to, so that the charging time ratio, the discharging time ratio, the standing time ratio, the average charging power and the average discharging power in the test working condition are the same as those in the original working condition.
The test condition construction method shown in fig. 2 performs twice clustering with average power and duration, ensures the feature integrity of the working condition segments, and checks the average power of the whole test condition and the proportions of standing, charging and discharging, and the like, thereby ensuring the precision of the test condition.
Example two
Fig. 8 is a schematic diagram of a battery life evaluation system in the second embodiment, and referring to fig. 8, the life evaluation system predicts the life of the power battery by using a test condition curve composed of constant power segments as a test reference and by using a capacity attenuation corresponding to each constant power segment.
The service life evaluation system comprises a constant power cycle test unit 1, a test working condition construction unit 2 and a battery service life prediction unit 3.
The constant power test unit 1 is used for performing cycle tests under different powers to establish a charging capacity attenuation model and a discharging capacity attenuation model of the battery under different powers. The test condition construction unit 2 is configured to establish a test condition, where the test condition is composed of a plurality of groups of feature segments, and each group of feature segments corresponds to one power and one duration. The battery life prediction unit 3 is used for calculating the proportion of each power in a test working condition, and predicting the service life of the power battery according to a charging capacity attenuation model and a discharging capacity attenuation model corresponding to each power.
The preferred constant power test unit 1 constructs a charge capacity decay model as follows:
ln YC＝K1Tln XC+B1T
in the formula, YCFor charge capacity fade, K1T、B1TCoefficient of charge capacity decay model at temperature T, XCIs the set charging energy throughput. The discharge capacity decay model constructed was:
ln YD＝K2Tln XD+B2T
in the formula, YDFor charge capacity fade, K2T、B2TCoefficient of discharge capacity decay model, X, at temperature TDIs the set discharge energy throughput.
Preferably, the test condition constructing unit 2 obtains the test condition by reconstructing the original condition, wherein the reconstructing includes:
and calculating the charge time ratio, the discharge time ratio and the standing time ratio of the original working condition.
Dividing an original working condition into charging segments, discharging segments and standing segments by taking a first threshold and a second threshold as demarcation points, recording the duration of each charging segment, each discharging segment and each standing segment, and the average power of each charging segment and each discharging segment, wherein the first threshold is 1KW, the second threshold is-1 KW, and the segments with the power larger than the first threshold and the duration larger than 1S in the original working condition are charging segments; in the original working condition, the segment with the power smaller than the second threshold and the duration longer than 1S is a charging segment; and in the original working condition, the section with the power smaller than the first threshold and larger than the second threshold and the duration larger than 1S is a standing section.
The method comprises the steps of classifying charging segments, discharging segments and standing segments according to power respectively through clustering analysis, classifying each type of charging segments, each type of discharging segments and each type of standing segments secondarily according to duration time respectively through clustering analysis to obtain a group of charging characteristic segments, a group of discharging characteristic segments and a group of standing characteristic segments, wherein when secondary classification is carried out, the classification number of the charging segments and the discharging segments with the minimum power and the maximum power is 1.
And screening the charging characteristic segments and the discharging characteristic segments, classifying the charging segments or the discharging segments corresponding to the charging characteristic segments or the discharging characteristic segments as static segments if the power of one charging characteristic segment or one discharging characteristic segment is less than 5KW and the duration is less than 10S, and performing primary classification and secondary classification on the charging segments, the discharging segments and the static segments through clustering analysis to obtain a group of charging characteristic segments, a group of discharging characteristic segments and a group of static characteristic segments.
And forming a test working condition by using the group of charging characteristic segments, the group of discharging characteristic segments and the group of standing characteristic segments, wherein the charging time ratio, the discharging time ratio and the standing time ratio in the test working condition are the same as those in the original working condition.
The life evaluation system further comprises a temperature control unit 4 for adjusting the temperature of the test environment when the cycle test is performed.
In this embodiment, the constant power cycle testing unit 1, the testing condition constructing unit 2, the battery life predicting unit 3, and the temperature control unit 4 may be implemented in a software manner, and the units may be configured in an electronic device, such as a server or a terminal device, where a typical terminal device includes a computer.
The beneficial effects of the battery life evaluation system provided in this embodiment are the same as the battery life evaluation method described in the embodiment, and are not described herein again.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (9)
1. A method for evaluating the service life of a power battery is characterized in that a test working condition curve composed of constant power segments is used as a test reference, and the service life of the power battery is predicted through capacity attenuation corresponding to each constant power segment, and comprises the following steps:
establishing a charge capacity attenuation model and a discharge capacity attenuation model of the battery under different powers;
establishing a test working condition, wherein the test working condition consists of a plurality of groups of characteristic segments, and each group of characteristic segments corresponds to one power and one duration;
calculating the proportion of each power in the test working condition, and predicting the service life of a power battery according to the charging capacity attenuation model and the discharging capacity attenuation model corresponding to each power;
wherein, the test working condition is obtained by reconstructing the original working condition, and the reconstruction comprises the following steps:
calculating the charge time ratio, the discharge time ratio and the standing time ratio of the original working condition;
dividing the original working condition into a charging segment, a discharging segment and a standing segment by taking a first threshold and a second threshold as boundary points, and recording the duration of each charging segment, each discharging segment and each standing segment, the average power of each charging segment and each discharging segment;
performing primary classification on the charging segments, the discharging segments and the standing segments according to power through clustering analysis, and performing secondary classification on each type of the charging segments, each type of the discharging segments and each type of the standing segments according to duration through clustering analysis to obtain a group of charging characteristic segments, a group of discharging characteristic segments and a group of standing characteristic segments;
and forming the test working condition by using the group of charging characteristic segments, the group of discharging characteristic segments and the group of standing characteristic segments, wherein the charging time ratio, the discharging time ratio and the standing time ratio in the test working condition are the same as those in the original working condition.
2. The life evaluation method according to claim 1, wherein the charge capacity fade model is:
lnYC＝K1TlnXC+B1T
in the formula, YCFor charge capacity fade, K1T、B1TIs the coefficient, X, of the charge capacity decay model at temperature TCIs the set charging energy throughput.
3. The life evaluation method according to claim 1, wherein the discharge capacity decay model is:
lnYD＝K2TlnXD+B2T
in the formula, YDFor charge capacity fade, K2T、B2TIs the coefficient of the decay model of the discharge capacity at temperature T, XDIs the set discharge energy throughput.
4. The life evaluation method according to claim 1, wherein the first threshold value is 1KW, and the second threshold value is-1 KW.
5. The life evaluation method of claim 1, wherein the segment with power greater than the first threshold and duration greater than 1S in the original working condition is a charging segment;
the segment with the power smaller than the second threshold value and the duration longer than 1S in the original working condition is a charging segment;
and the segment with the power smaller than the first threshold and longer than the second threshold and the duration longer than 1S in the original working condition is a standing segment.
6. The method of evaluating lifetime of claim 1, further comprising screening said charging signature segment, said discharging signature segment,
if the power of one charging characteristic segment or one discharging characteristic segment is less than 5KW and the duration is less than 10S, classifying the charging segment or the discharging segment corresponding to the charging characteristic segment or the discharging characteristic segment as a standing segment,
and performing the primary classification and the secondary classification on the charging fragments, the discharging fragments and the standing fragments through clustering analysis to obtain a group of charging characteristic fragments, a group of discharging characteristic fragments and a group of standing characteristic fragments.
7. The method of evaluating lifetime as claimed in claim 1, wherein the secondary classification is performed such that the classification number of charging segments and discharging segments having the smallest power and the largest power is 1.
8. A power battery life evaluation system is characterized in that a test working condition curve composed of constant power segments is used as a test reference, the life of a power battery is predicted through the capacity attenuation corresponding to each constant power segment,
the system comprises a constant power cycle test unit, a test condition construction unit and a battery life prediction unit,
the constant power test unit is used for carrying out cycle test under different powers so as to establish a charging capacity attenuation model and a discharging capacity attenuation model of the battery under different powers;
the test working condition construction unit is used for establishing a test working condition, wherein the test working condition consists of a plurality of groups of characteristic segments, and each group of characteristic segments corresponds to one type of power and one type of duration;
the battery life prediction unit is used for calculating the proportion of each power in the test working condition and predicting the life of the power battery according to the charging capacity attenuation model and the discharging capacity attenuation model corresponding to each power;
the test condition constructing unit obtains a test condition by reconstructing an original condition, wherein the reconstruction comprises:
calculating the charge time ratio, the discharge time ratio and the standing time ratio of the original working condition;
dividing the original working condition into a charging segment, a discharging segment and a standing segment by taking a first threshold and a second threshold as boundary points, and recording the duration of each charging segment, each discharging segment and each standing segment, the average power of each charging segment and each discharging segment;
performing primary classification on the charging segments, the discharging segments and the standing segments according to power through clustering analysis, and performing secondary classification on each type of the charging segments, each type of the discharging segments and each type of the standing segments according to duration through clustering analysis to obtain a group of charging characteristic segments, a group of discharging characteristic segments and a group of standing characteristic segments;
and forming the test working condition by using the group of charging characteristic segments, the group of discharging characteristic segments and the group of standing characteristic segments, wherein the charging time ratio, the discharging time ratio and the standing time ratio in the test working condition are the same as those in the original working condition.
9. The life evaluation system of claim 8, further comprising a temperature control unit for adjusting a temperature of a test environment when performing the cycle test.
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