CN116087767A

CN116087767A - Method, device, equipment and medium for reliability test and life prediction of generator

Info

Publication number: CN116087767A
Application number: CN202211661169.2A
Authority: CN
Inventors: 刘正全; 吴晟
Original assignee: Zhejiang Zero Run Technology Co Ltd; Zhejiang Lingsheng Power Technology Co Ltd
Current assignee: Zhejiang Zero Run Technology Co Ltd; Zhejiang Lingsheng Power Technology Co Ltd
Priority date: 2022-12-21
Filing date: 2022-12-21
Publication date: 2023-05-09

Abstract

The application discloses a method, a device, equipment and a medium for reliability test and life prediction of a generator, wherein the method comprises the following steps: determining a first life model and a second life model of the insulated winding; based on the first life model and the first operation duration and the insulation winding temperature in the target data in the temperature dimension, predicting the first equivalent test duration at the reliability test temperature and predicting the second equivalent test duration at the reliability test speed/torque combination; and controlling the insulated winding of the generator to work under the voltage of the insulated winding based on the first equivalent test duration and/or the second equivalent test duration, and controlling the rotor assembly of the target generator to operate at the reliability test temperature and/or the reliability test rotating speed/torque combination to obtain the reliability test result of the target generator. According to the scheme, the test sample size and the test times can be reduced, and the test time is shortened; and the stress state of the motor after assembly can be well simulated, and the accuracy of the reliability test of the motor is improved.

Description

Method, device, equipment and medium for reliability test and life prediction of generator

Technical Field

The application relates to the technical field of reliability tests, in particular to a method, a device, equipment and a medium for reliability test and life prediction of a generator.

Background

The reliability of the motor is critical to the safety of the motor operation, and in general, an accelerated life test is adopted for the reliability test of the motor at the present stage, namely life data is obtained under the stress condition higher than the normal working condition of the motor, and the life under the normal condition is extrapolated according to an accelerated model.

The existing reliability accelerated life test generally carries out a single experiment on parts, and carries out multiple experiments, each experiment sets different temperatures, voltages and the like, a large number of test samples and test time are needed, and the whole stress state of the motor after assembly cannot be simulated, so that the accuracy of the test is reduced.

Therefore, the current reliability accelerated life test needs a large test sample amount, a long test time and low test accuracy, and is a problem to be solved urgently.

Disclosure of Invention

The technical problem that this application mainly solves is to provide a generator reliability test and life-span prediction method, device, equipment and medium, can reduce test sample volume, the test time that the reliability accelerated life test required, simulate the whole stress state after the motor assembly, improve test accuracy.

In order to solve the above problems, a first aspect of the present application provides a reliability test method of a vehicle generator, including: acquiring operation data of vehicle generators of a plurality of target users in various dimensions; wherein the various dimensions include a temperature dimension, a mechanical dimension, and a voltage dimension; screening operation data covering a target proportion in each dimension respectively to serve as target data corresponding to the dimension, determining a first life model of the insulated winding based on first test data of the insulated winding in the temperature dimension, and determining a second life model of the rotor assembly based on second test data of the rotor assembly in the mechanical dimension; predicting a first equivalent test duration at a reliability test temperature based on the first life model and the insulation winding temperature and first operation duration in the target data in the temperature dimension, and predicting a second equivalent test duration at a reliability test speed/torque combination based on the second life model and the speed/torque combination and second operation duration in the target data in the mechanical dimension; and controlling an insulated winding of a target generator to work under the voltage of the insulated winding in the target data under the voltage dimension based on the first equivalent test duration and/or the second equivalent test duration, and controlling a rotor assembly of the target generator to operate at the reliability test temperature and/or the reliability test rotating speed/torque combination to obtain a reliability test result of the target generator.

Wherein, based on the first equivalent test duration and/or the second equivalent test duration, controlling an insulation winding of a target generator to work under an insulation winding voltage in the target data in the voltage dimension, and controlling a rotor assembly of the target generator to operate at the reliability test temperature and/or the reliability test speed/torque combination, so as to obtain a reliability test result of the target generator, including: monitoring a real-time temperature of an insulated winding of the target generator during the second equivalent test period by controlling the insulated winding of the target generator to work at the voltage of the insulated winding in the target data in the voltage dimension and controlling a rotor assembly of the target generator to operate at the reliability test speed/torque combination; adjusting at least one of a coolant temperature and a coolant flow based on whether the real-time temperature reaches an equivalent damage temperature of the first two equivalent test durations; and responding to the second equivalent test duration of the target generator, controlling the target generator to stop running, and obtaining a reliability test result of the target generator.

Wherein, based on whether the real-time temperature reaches the equivalent damage temperature of the first two equivalent test durations, adjusting at least one of the cooling liquid temperature and the cooling liquid flow, including at least one of the following: in response to the real-time temperature not reaching the equivalent damage temperature for the first two equivalent test durations, performing at least one of increasing the coolant temperature, decreasing the coolant flow; and in response to the real-time temperature exceeding the equivalent damage temperature for the first two equivalent test durations, performing at least one of reducing the coolant temperature and increasing the coolant flow.

Wherein, when the various dimensions include the temperature dimension, the screening operation data covering a target proportion in the various dimensions respectively includes: for each operation data in the temperature dimension, predicting the equivalent time length of the insulation winding at the target temperature based on a preset life model of the insulation winding and the insulation winding temperature and the first operation time length in the operation data; sequencing the operation data in the temperature dimension according to the sequence of the equivalent time length from small to large; and selecting the operation data covering the target proportion as the target data of the temperature dimension based on the operation data sequenced in the temperature dimension.

Wherein, when the various dimensions include the mechanical dimension, the screening the operation data covering the target proportion in the various dimensions, as the target data corresponding to the dimensions, includes: selecting one of the operation data of the mechanical dimension as reference data; predicting, for each of the operational data in the mechanical dimension, a pseudo-damage value of the operational data relative to the reference data based on a preset life model of the rotor assembly; sequencing the operation data in the mechanical dimension according to the sequence of the pseudo damage values from small to large; and selecting the operation data covering the target proportion as the target data of the mechanical dimension based on the operation data sequenced in the mechanical dimension.

Wherein the determining a first life model of the insulated winding based on the first test data of the insulated winding in the temperature dimension comprises: acquiring at least three first test data of the insulated winding in the temperature dimension; wherein the first test data comprises a component failure duration when operating at a test temperature; performing function fitting on a preset life model of the insulated winding based on the at least three first test data to obtain a predicted value of an experience parameter in the preset life model; and updating the preset life model based on the predicted value of the experience parameter in the preset life model of the insulated winding to obtain the first life model.

Wherein said determining a second life model of the rotor assembly based on second test data of the rotor assembly in the mechanical dimension comprises: acquiring at least three of the second test data for the rotor assembly in the mechanical dimension; wherein the second test data comprises a component failure duration when operating at a test speed/torque combination; performing function fitting on a preset life model of the rotor assembly based on the at least three second test data to obtain a predicted value of an experience parameter in the preset model; and updating the preset life model based on the predicted value of the experience parameter in the preset life model of the rotor assembly to obtain the second life model.

In order to solve the above-mentioned problem, a second aspect of the present application provides a lifetime prediction method of a vehicle generator, including: acquiring a rotating speed/torque combination, an insulating winding temperature and an operated time length of a rotor assembly of a generator to be tested, and acquiring a first service life model of the insulating winding and a second service life model of the rotor assembly; the first life model and the second life model are obtained based on the reliability test method of the vehicle generator; predicting and obtaining a first service life duration based on the first service life model and the temperature of an insulating winding of the generator to be tested, and predicting and obtaining a second service life duration based on the second service life model and the rotating speed/torque combination of the generator to be tested; and obtaining the residual life duration of the generator to be tested based on the first life duration, the second life duration and the operated duration.

Wherein the first life model comprises a first functional relationship between confidence and life time under different temperatures of the insulated winding, and the second life model comprises a second functional relationship between confidence and life time under different rotational speed/torque combinations.

The predicting, based on the first life model and the insulation winding temperature of the generator to be tested, a first life duration includes: selecting a first functional relation matched with the temperature of the insulated winding of the generator to be tested based on the first life model, and predicting first life time lengths under a plurality of target confidence degrees respectively based on the matched first functional relation; the predicting a second life duration based on the second life model and the rotation speed/torque combination of the generator to be tested includes: selecting a second function relation matched with the rotating speed/torque combination of the generator to be tested based on the second life model, and predicting second life time lengths under the plurality of target confidence degrees respectively based on the matched second function relation; the obtaining the remaining life duration of the generator to be tested based on the first life duration, the second life duration and the operated duration includes: and for the plurality of target confidence degrees, obtaining the residual life time of the generator to be tested under the corresponding target confidence degrees based on the first life time and the second life time under the same target confidence degrees and the operated time.

In order to solve the above-mentioned problem, a third aspect of the present application provides a reliability test apparatus for a vehicle generator, comprising: the acquisition module is used for acquiring operation data of the vehicle generators of a plurality of target users in various dimensions; wherein the various dimensions include a temperature dimension, a mechanical dimension, and a voltage dimension; the screening module is used for screening the operation data covering the target proportion in the various dimensions respectively to serve as target data corresponding to the dimensions; a determining module for determining a first life model of the insulated winding based on first test data of the insulated winding in the temperature dimension and a second life model of the rotor assembly based on second test data of the rotor assembly in the mechanical dimension; the prediction module is used for predicting a first equivalent test duration at a reliability test temperature based on the first life model and the insulation winding temperature and the first operation duration in the target data in the temperature dimension, and predicting a second equivalent test duration at a reliability test speed/torque combination based on the second life model and the speed/torque combination and the second operation duration in the target data in the mechanical dimension; the control module is used for controlling the insulated winding of the target generator to work under the voltage of the insulated winding in the target data under the voltage dimension and controlling the rotor assembly of the target generator to operate at the reliability test rotating speed/torque combination based on the first equivalent test duration and the second equivalent test duration, so as to obtain a reliability test result of the target generator.

In order to solve the above-described problems, a fourth aspect of the present application provides a life prediction apparatus of a vehicle generator, comprising: the acquisition module is used for acquiring the rotating speed/torque combination, the temperature of the insulated winding and the running time of the rotor assembly in the generator to be tested, and acquiring a first service life model of the insulated winding and a second service life model of the rotor assembly; the first life model and the second life model are obtained based on the reliability test device of the vehicle generator; the prediction module is used for predicting and obtaining a first service life duration based on the first service life model and the temperature of the insulating winding of the generator to be detected, and predicting and obtaining a second service life duration based on the second service life model and the rotating speed/torque combination of the generator to be detected; the determining module is used for obtaining the residual life duration of the generator to be tested based on the first life duration, the second life duration and the operated duration.

In order to solve the above-mentioned problem, a fifth aspect of the present application provides an electronic device, including a memory and a processor coupled to each other, where the memory stores program instructions, and the processor is configured to execute the program instructions to implement the reliability test method of a vehicle generator or the lifetime prediction method of a vehicle generator.

In order to solve the above-described problems, a sixth aspect of the present application provides a computer-readable storage medium storing program instructions executable by a processor for implementing the above-described reliability test method of a vehicle generator or lifetime prediction method of a vehicle generator.

According to the scheme, the reliability acceleration test is carried out on the insulating winding and the rotor of the motor, and the motor assembly is enabled to work at the temperature, the rotating speed/torque and the voltage of the reliability acceleration test, so that the test sample size and the test times can be reduced, and the test time is shortened; and the stress state of the motor after assembly can be well simulated, and the accuracy of the reliability test of the motor is improved.

Drawings

FIG. 1 is a flow chart of an embodiment of a method of reliability testing of a vehicle generator of the present application;

FIG. 2 is a flow chart of another embodiment of a method of reliability testing of a vehicle generator of the present application;

FIG. 3 is a flow chart of yet another embodiment of a method of reliability testing of a vehicle generator of the present application;

FIG. 4 is a flow chart of yet another embodiment of a method of reliability testing of a vehicle generator of the present application;

FIG. 5 is a flow chart of yet another embodiment of a method of reliability testing of a vehicle generator of the present application;

FIG. 6 is a flow chart of yet another embodiment of a method of reliability testing of a vehicle generator of the present application;

FIG. 7 is a flow chart of yet another embodiment of a method of reliability testing of a vehicle generator of the present application;

FIG. 8 is a schematic representation of a data fitting analysis of first test data;

FIG. 9 is a schematic representation of a Weibull distribution fit to three first test data;

FIG. 10 is a schematic frame diagram of an embodiment of a reliability test apparatus for a vehicle generator of the present application;

FIG. 11 is a schematic diagram of a frame of an embodiment of a life prediction apparatus of a vehicle generator of the present application;

FIG. 12 is a schematic diagram of a frame of an embodiment of an electronic device of the present application;

FIG. 13 is a schematic diagram of a framework of one embodiment of a computer-readable storage medium of the present application.

Detailed Description

The following describes the embodiments of the present application in detail with reference to the drawings.

In the following description, for purposes of explanation and not limitation, specific details are set forth such as the particular system architecture, interfaces, techniques, etc., in order to provide a thorough understanding of the present application.

The terms "system" and "network" are often used interchangeably herein. The term "and/or" is herein merely an association relationship describing an associated object, meaning that there may be three relationships, e.g., a and/or B, may represent: a exists alone, A and B exist together, and B exists alone. In addition, the character "/" herein generally indicates that the front and rear associated objects are an "or" relationship. Further, "a plurality" herein means two or more than two.

Before further describing the application, a life acceleration test method needs to be described so as to facilitate a reader to thoroughly understand the application; the life acceleration test is that the stress level is higher than that of the component under the normal operation condition, so that the component works under the stress level, damage caused by long-time operation of the component under the normal operation condition is simulated in a short time, and the assessment result of the component can be obtained in a short time.

Here, a method for testing the reliability of a vehicle generator and a method for predicting the lifetime will be described by taking a life acceleration test of an extended-range generator as an example.

Referring to fig. 1, fig. 1 is a schematic flow chart of an embodiment of a reliability test method of a vehicle generator in the present application; specifically, the reliability test method of the vehicle generator includes:

step S11: acquiring operation data of vehicle generators of a plurality of target users in various dimensions; wherein the various dimensions include a temperature dimension, a mechanical dimension, and a voltage dimension;

in one embodiment, the operating data in the temperature dimension may include a first operating duration at the temperature of the at least one insulated winding, the operating data in the mechanical dimension may include a second operating duration at the at least one set of rotational speeds/torques, and the operating data in the voltage dimension may include a third operating duration at the voltage of the at least one insulated winding. Wherein the first operation duration refers to the duration that the insulated winding of the generator operates at a certain insulated winding temperature; the second operating period is a period during which the generator rotor assembly operates at a certain speed/torque combination; the third operating period is the period during which the generator insulation winding is operating at a certain insulation winding voltage.

In this embodiment, acquiring operational data of the vehicle generator of the several target users in various dimensions may include: based on an automobile cloud platform system, selecting running data of users in typical areas such as northeast, north China, east China, northwest, southwest, china, south China and the like according to a seven-large geographic area of China, and setting a data acquisition period to be one year in order to eliminate the influence of seasonal factors; randomly selecting the same number of user data in each area, and obtaining the insulated winding temperature-time data, the rotating speed/torque-time data and the insulated winding terminal voltage-time data of each user through simple counting; it should be noted that the data acquisition period may be set not only to one year but also to two years, ten years, etc. as required; the user data can be selected according to the age of the user, for example, the user data of 18 years old to 28 years old, 29 years old to 38 years old, 39 years old to 48 years old and the like can be collected respectively, so that influences of different driving habits caused by the age of the user on motor working conditions are reduced. Specifically, in this embodiment, the collected operation data of the temperature dimension of the user includes a first operation duration at the temperatures of the plurality of insulated windings.

In this embodiment, considering that the main failure stress of the insulating winding on the stator is thermal stress, and the secondary factors include winding end voltage, so that data of temperature dimension and voltage dimension in user data are selected and acquired; for the generator rotor, the mechanical fatigue is a main failure cause, so that the data of mechanical dimension in the user data is selected to be acquired; in the application, the generator assembly is selected for life acceleration test, namely, the form of rotor and stator, so that the assembly quality of the generator and the stress state in the using process can be better simulated.

Step S12: screening operation data covering a target proportion in various dimensions respectively to serve as target data of corresponding dimensions, determining a first life model of an insulated winding based on first test data of the insulated winding in a temperature dimension, and determining a second life model of a rotor assembly based on second test data of the rotor assembly in a mechanical dimension;

in this embodiment, according to the definition in GB/T20111, the lifetime equation of the insulated winding conforms to the Arrhenius model, so the first lifetime model of the insulated winding is the Arrhenius model, and the Arrhenius model can be expressed as:

the acceleration factor may be defined as: the time of normal usage conditions of the product divided by the time of the accelerated life test, the acceleration coefficient can be calculated as:

Wherein TF is lifetime, A is constant, T is temperature, T ₀ Represents the temperature under normal use conditions, T _s The temperature under acceleration is represented, K represents Boltzmann constant, and the value is 8.617 x 10 < -5 > ev/K, E _a For activation energy, E in the art _a Experience values are often taken based on failure modes;

the effect of mechanical fatigue of a rotor assembly on product life is typically described by an inverse model, and thus, the second life model of the rotor assembly may be an inverse model, which may be expressed as: c=s ^σ N；

Similarly, the acceleration factor can be calculated:

where C is a constant, S is a loading stress, sp1 is a normal stress, sp2 is an acceleration stress, N is a lifetime, σ is an exponential coefficient, and in the art, σ is often an empirical value based on failure mode.

Referring to fig. 2, fig. 2 is a flow chart illustrating another embodiment of a reliability test method of a vehicle generator according to the present application; in one embodiment, in the case that the various dimensions include a temperature dimension, the operation data covering the target proportion is screened in the various dimensions, as the target data of the corresponding dimension, including:

s21: for each operation data in the temperature dimension, predicting the equivalent time length of the insulated winding at the target temperature based on the preset life model of the insulated winding and the insulated winding temperature and the first operation time length in the operation data; wherein, the preset life model of the insulating winding can comprise an Arrhenius model; the temperature of the insulated winding in the operation data represents the temperature reached by the insulated winding under the normal operation working condition; the target temperature is a temperature value set manually and represents a temperature acceleration condition which is wanted to be reached in a reliability test, so that the corresponding equivalent time length is operated at the target temperature, and the damage equivalent time length is reached when the first operation time length is operated at the temperature of the insulated winding.

S22: sequencing all operation data in the temperature dimension according to the sequence of the equivalent duration from small to large;

s23: and selecting the operation data covering the target proportion as the target data of the temperature dimension based on the operation data sequenced in the temperature dimension.

In the embodiment, an automobile generator is used as a test object, and user data covering 95% of users are screened in various dimensions as target data of corresponding dimensions respectively in order to meet the requirements of high reliability and high coverage rate in the automobile industry; it should be noted that, the above-mentioned user data covering 95% of users takes the insulation winding temperature-time data of the generator insulation system as an example, and the following table is an example of the collected insulation winding temperature-time in one year for a certain user, where the time of using the user in one year is 800 hours, the driving mileage is 2 ten thousand kilometers, and the activation energy E is based on the empirical value _a Taking 0.7, the temperature of the insulated winding is the temperature under the normal use condition, according to the calculation formula of the acceleration coefficient,the acceleration coefficient converted to the target temperature at each insulated winding temperature can be obtained respectively, after the acceleration coefficient is calculated, the equivalent time of each insulated winding temperature at the target temperature value can be calculated according to the relationship between the service life of the product under normal use conditions and the service life of the accelerated service life test by the first operation time length at each insulated winding temperature in the following table, for example: to calculate the equivalent time from 35 ℃ of winding temperature under normal use condition to acceleration test condition, firstly calculating the corresponding acceleration coefficient, substituting the empirical values of insulation winding temperature, target temperature and activation energy into an acceleration coefficient calculation formula, and obtaining the acceleration coefficient 950424; and then according to the definition of the acceleration coefficient: dividing the time of the normal use condition of the product by the time of the accelerated life test, and knowing the time under the normal use condition and the acceleration coefficient, calculating to obtain the equivalent time under the corresponding condition, wherein the equivalent time is approximately calculated to be 0.0001 hour; similarly, the equivalent time converted to the target temperature at each winding temperature is calculated respectively, and the equivalent time of the user is obtained by accumulation, namely, the calculated equivalent time of the user is 22 hours, which means that the life acceleration test is required to be carried out at the preset temperature dimension, and the reliability test temperature is 80 ℃, and the loss of the generator caused by the running of the user in 800 hours in one year can be simulated only by carrying out the test for 22 hours. After the equivalent time of each user is obtained, the equivalent time of each user is arranged from small to large, and an equivalent time value under the coverage of 95% of the users and the temperature-time data of the users corresponding to the equivalent time value are selected as target data under the temperature dimension.

It should be noted that, in this context, the operation data of the coverage target proportion is based on the high coverage rate and high reliability required by the automotive industry, so that a higher coverage target proportion is selected, and the specific value of the coverage target proportion may be 95%, or may be other values, such as 90%, 85%, 98%, etc.; in other embodiments, the operating data covering the target proportion may also be selected to be a lower proportion, such as 70%, based on factors such as cost.

Referring to fig. 3, fig. 3 is a flow chart illustrating a reliability test method of a vehicle generator according to another embodiment of the present application; in one implementation scenario, in the case where the various dimensions include a mechanical dimension, the operation data covering the target proportion is screened in the various dimensions, as target data of the corresponding dimension, including:

s31: selecting one of the operation data in the mechanical dimension as reference data; for each operation data in the mechanical dimension, predicting a pseudo damage value of the operation data relative to the reference data based on a preset life model of the rotor assembly;

s32: sequencing all operation data in the mechanical dimension according to the sequence of the pseudo damage value from small to large;

s33: and selecting the operation data covering the target proportion as the target data of the mechanical dimension based on the operation data sequenced in the mechanical dimension. To obtain the rotation speed/torque-time under the coverage of 95% of users, firstly randomly selecting the rotation speed/torque-time data of one user, calculating the damage proportion of the rest users relative to the user according to an inverse model, namely obtaining the pseudo damage value of the rest users, marking the pseudo damage value of the selected users as 1, arranging all the pseudo damage values from small to large, and selecting the pseudo damage value under the coverage of 95% of users and the rotation speed/torque-time data of the users corresponding to the pseudo damage value as target data of mechanical dimension; it should be noted that, the calculation method of the damage ratio is a method commonly used in the art, and the present application is not repeated here.

In this embodiment, in order to obtain target data of voltage dimension under 95% of user coverage, after collecting voltage-time data of insulated winding ends of each user, voltage values of 95% coverage in the voltage distribution of the insulated winding ends, that is, voltage values of insulated winding ends with voltage greater than 95% of other voltage values, are directly selected as target data of voltage dimension.

Referring to fig. 4, fig. 4 is a flow chart illustrating a reliability test method of a vehicle generator according to another embodiment of the present application; in one possible embodiment, determining a first life model of the insulated winding based on first test data of the insulated winding in a temperature dimension includes:

s41: acquiring at least three first test data of the insulated winding in a temperature dimension; wherein the first test data comprises a component failure duration when operating at the test temperature; since Arrhenius model is tf=a ₀ exp(E _a V), taking the natural logarithm of the above formula for both sides: ln (TF) =ln (a ₀ )+ _a As can be seen from the above formula, ln (TF) and 1/T are in a linear relationship, and the slope thereof is E _a and/K, so that only three groups of stator insulating winding components are arranged for test, the linear can be obtained by fitting to obtain the slope, and the activation energy E is obtained _a To determine a first life model of the insulated winding. In this embodiment, at least three stator insulation winding components may be selected and divided into three groups, and the three groups are tested under three different temperature conditions respectively until all the components fail, and the failure time of each component is recorded, if each group includes a plurality of stator insulation winding components, for the failure time of different stator insulation winding components under the same temperature condition, the intermediate value of all the failure times may be selected as the lifetime value of the stator insulation winding component under the corresponding temperature condition; in other embodiments, the average value of all failure times may be selected as the service life value of the stator insulation winding component under the corresponding temperature condition, and other value methods may also be provided, which is not limited herein;

s42: performing function fitting on a preset life model of the insulated winding based on at least three first test data to obtain a predicted value of an experience parameter in the preset life model; wherein the predicted value of the empirical parameter in the preset life model is the activation energy E in the Arrhenius model _a Is a value of (2); based on the failure time of the stator insulation winding component at different temperatures recorded in the step S42 as first test data, taking 1/T as an abscissa and ln (TF) as an ordinate, establishing a coordinate system, obtaining a straight line in the coordinate system through data fitting by only three groups of data at least, and calculating to obtain the slope of the straight line, thereby obtaining the value of the activation energy;

S43: and updating the preset life model based on the predicted value of the experience parameter in the preset life model of the insulated winding to obtain a first life model.

According to the scheme, the first life model of the insulated winding is determined through the test, and the value is more accurate relative to the activation energy based on the empirical value, so that over-test or under-test is avoided.

Referring to fig. 5, fig. 5 is a flow chart illustrating a reliability test method of a vehicle generator according to another embodiment of the present application; in one possible embodiment, determining a second life model of the rotor assembly based on second test data of the rotor assembly in the mechanical dimension includes:

s51: acquiring at least three second test data of the rotor assembly in the mechanical dimension; wherein the second test data comprises a component failure duration when operating at the test speed/torque combination; the inverse epower model is c=s ^σ N, taking natural logarithms from the two sides:

from the above formula, lnN and lnS are linear and have a slope of +.>

Therefore, the slope of the straight line can be obtained by fitting only three groups of rotor components to obtain the value of the index coefficient sigma, so that the second life model of the rotor assembly is determined. In this embodiment, as in the first life model for determining the insulation winding in the above embodiment, at least three rotor components may be selected and divided into three groups, and the test is performed under three different rotational speed/torque conditions, respectively, until all the components fail, and the failure time of each component is recorded, and if each group includes a plurality of rotor components, the failure time of different rotor components under the same rotational speed/torque condition may be selected, wherein the intermediate value of all the failure times is selected as the rotation under the corresponding rotational speed/torque condition A lifetime value of the sub-component; in other embodiments, the average value of all failure times may be selected as the life value of the rotor component under the corresponding rotation speed/torque condition, and other value methods may also be available, which is not limited herein;

s52: performing function fitting on a preset life model of the rotor assembly based on at least three second test data to obtain a predicted value of an experience parameter in the preset model; the specific fitting manner is similar to that of determining the first life model of the insulated winding in the previous embodiment, and will not be repeated here;

s53: and updating the preset life model based on the predicted value of the experience parameter in the preset life model of the rotor assembly to obtain a second life model.

Step S13: predicting a first equivalent test duration at a reliability test temperature based on the first life model and the insulation winding temperature and the first operation duration in the target data in the temperature dimension, and predicting a second equivalent test duration at the reliability test speed/torque combination based on the second life model and the speed/torque combination and the second operation duration in the target data in the mechanical dimension; the reliability test temperature is an insulation winding temperature adopted in the reliability test, namely the insulation winding needs to be operated at the reliability test temperature for a first equivalent test time in the reliability test, so that damage to the insulation winding in the reliability test is equivalent to damage caused by the insulation winding operating at the insulation winding temperature in target data for the first equivalent test time.

In step S13, since the predicted values of the empirical parameters in the first life model and the second life model, i.e., the activation energy E in the Arrhenius model, have been obtained in step S12 _a The value of the index coefficient sigma in the inverse model, and thus both models are determined, the equivalent test duration can be calculated based on the determined models; according to the target data in each dimension obtained in step S12, predicting an equivalent test duration in the corresponding dimension includes: based on the insulated winding temperature-time data at 95% user coverage, the equivalent to reliability test temperature is calculated using the determined Arrhenius modelThe calculation method of the first equivalent test duration of step S23 has already been described in the foregoing embodiment of step S23, and will not be described in detail here; based on the rotation speed/torque-time data under the coverage of 95% of the user, calculating a second equivalent test duration equivalent to the reliability test rotation speed/torque combination by using the determined inverse model, wherein the specific calculation method is similar to the calculation method for calculating the first equivalent test duration in the step S23, and only the Arrhenius model applied in the calculation method is required to be changed into the inverse model, which is not repeated herein.

In step S13, the reliability test temperature and the reliability test speed/torque combination are manually selected, and may be any values that satisfy the acceleration test condition, as long as the predetermined maximum load of the component is not exceeded.

Step S14: and controlling the insulation winding of the target generator to work under the insulation winding voltage in the target data under the voltage dimension based on the first equivalent test duration and/or the second equivalent test duration, and controlling the rotor assembly of the target generator to operate at the reliability test temperature and/or the reliability test rotating speed/torque combination, so as to obtain a reliability test result of the target generator.

It should be noted that, because the reliability test temperature and the reliability test rotation speed/torque combination in step S13 are manually selected, the calculated first equivalent test duration and second equivalent test duration can both obtain the temperature acceleration reliability test result or the mechanical acceleration reliability test result in an independent temperature or mechanical acceleration test, but in order to comprehensively consider each factor of generator failure, and simultaneously perform acceleration tests on the generator in various dimensions, it is necessary to satisfy both the temperature acceleration equivalent condition and the mechanical acceleration equivalent condition under a certain equivalent test duration; and different reliability test temperatures or reliability test rotation speed/torque combinations can obtain different first equivalent test time periods and second equivalent test time periods respectively, so that when the first equivalent test time periods and the second equivalent test time periods calculated based on the selected reliability test temperatures and reliability test rotation speed/torque combinations in the step S13 are not equal, the reliability test temperatures or the reliability test rotation speed/torque combinations can be adjusted in the test so that the first equivalent test time periods are equal to the second equivalent test time periods, and the temperature acceleration equivalent conditions and the mechanical acceleration equivalent conditions can be simultaneously satisfied. In some implementation scenarios, if the first equivalent test duration is equal to the second equivalent test duration, the insulation winding of the target generator can be controlled to work under the insulation winding voltage in the target data under the voltage dimension based on the first equivalent test duration and the second equivalent test duration, and the rotor assembly of the target generator is controlled to operate at the reliability test temperature and/or the reliability test speed/torque combination, so that the reliability test result of the target generator is obtained.

Referring to fig. 6, fig. 6 is a flow chart illustrating a reliability test method of a vehicle generator according to another embodiment of the present application; in one implementation scenario, based on the first equivalent test duration and/or the second equivalent test duration, controlling an insulation winding of the target generator to operate at an insulation winding voltage in target data in a voltage dimension, and controlling a rotor assembly of the target generator to operate at a reliability test temperature and/or a reliability test speed/torque combination, to obtain a reliability test result of the target generator, including:

s61: monitoring real-time temperature of the insulated winding in the process of controlling the insulated winding of the target generator to work under the voltage of the insulated winding in the target data under the voltage dimension and controlling the rotor assembly of the target generator to operate for a second equivalent test duration with the reliability test speed/torque combination;

s62: adjusting at least one of the coolant temperature and the coolant flow based on whether the real-time temperature reaches the equivalent damage temperature for the second equivalent test period;

s63: and responding to the second equivalent test time when the target generator is operated, controlling the target generator to stop operating, and obtaining a reliability test result of the target generator. The reliability test result can be obtained by observing by a professional or by testing related data by a professional instrument.

When the accelerated life test of the extended-range generator is carried out, during the operation process of the extended-range generator, the rotor can work under the rotating speed/torque combined working condition exceeding the normal working condition when the extended-range generator is mechanically accelerated, so that the rotor can be damaged in mechanical structure, and meanwhile, the temperature of the insulating winding of the stator can be raised; the extended-range generator can be cooled by using the cooling liquid when in operation, so that the temperature of the stator insulation winding can be regulated and controlled only by regulating the flow or the temperature of the cooling liquid.

In some embodiments, in order for the accelerated life test of the extended-range generator to simulate its operating condition as much as possible during normal operation, it is desirable to cycle it through different speed/torque combinations during the accelerated life test.

In step S61, when the accelerated lifetime test is performed, in addition to operating the extended-range generator under the temperature and mechanical acceleration conditions, a voltage is applied to the stator insulation winding, where the voltage is the target data of the voltage dimension under the 95% of the user coverage obtained in the foregoing embodiment, that is, after collecting the voltage-time data of the insulation winding end of each user, the voltage value of the 95% coverage in the insulation winding end voltage distribution, that is, the insulation winding end voltage value of other voltage values with the voltage greater than 95% is directly selected. The voltage is applied all the way across the stator insulated windings.

It should be noted that, since the first equivalent test duration and the second equivalent test duration corresponding to the selected temperature acceleration condition and the mechanical acceleration condition are not necessarily equal, the temperature acceleration condition or the mechanical acceleration condition may be adjusted to be equal during the subsequent test, specifically, the temperature acceleration condition may be adjusted to change the first equivalent test duration to be equal to the second equivalent test duration, and at this time, at least one of the coolant temperature and the coolant flow may be adjusted based on whether the real-time temperature reaches the equivalent damage temperature of the second equivalent test duration, including at least one of the following:

1. in response to the real-time temperature not reaching the equivalent damage temperature for the second equivalent test duration, performing at least one of increasing the coolant temperature and decreasing the coolant flow;

2. at least one of reducing the temperature of the coolant and increasing the flow of the coolant is performed in response to the real-time temperature exceeding the equivalent damage temperature for the second equivalent test period.

In other possible embodiments, the mechanical acceleration condition may be further adjusted to change the second equivalent test duration to be equal to the first equivalent test duration, and then at this time, based on whether the real-time temperature reaches the equivalent damage temperature of the second equivalent test duration, at least one of the coolant temperature and the coolant flow rate is adjusted, including at least one of:

1. In response to the real-time temperature not reaching the equivalent damage temperature for the first equivalent test period, performing at least one of increasing the coolant temperature and decreasing the coolant flow;

2. at least one of reducing the temperature of the coolant and increasing the flow of the coolant is performed in response to the real-time temperature exceeding the equivalent damage temperature for the first equivalent test period.

Referring to fig. 7, fig. 7 is a flowchart illustrating an embodiment of a method for predicting a lifetime of a vehicle generator according to the present application; specifically, the life prediction method of the vehicle generator includes:

s71: acquiring a rotating speed/torque combination, an insulating winding temperature and an operated time length of a rotor assembly of a generator to be tested, and acquiring a first service life model of the insulating winding and a second service life model of the rotor assembly; the first life model and the second life model are obtained based on the vehicle generator reliability test method;

in some possible embodiments, the first life model comprises a first functional relationship between confidence and life time at different insulation winding temperatures, and the second life model comprises a second functional relationship between confidence and life time at different speed/torque combinations.

S72: predicting and obtaining a first service life duration based on the first service life model and the temperature of an insulating winding of the generator to be tested, and predicting and obtaining a second service life duration based on the second service life model and the rotating speed/torque combination of the generator to be tested;

In some possible embodiments, predicting a first life duration based on the first life model and an insulation winding temperature of the generator under test includes: selecting a first function relation matched with the temperature of an insulating winding of the generator to be tested based on the first life model, and predicting first life time lengths under a plurality of target confidence degrees respectively based on the matched first function relation; based on a second life model and a rotation speed/torque combination of the generator to be tested, predicting to obtain a second life duration, including: selecting a second function relation matched with the rotating speed/torque combination of the generator to be tested based on a second life model, and predicting second life time lengths under a plurality of target confidence degrees respectively based on the matched second function relation;

specifically, after at least three first test data of the insulation winding in the temperature dimension and at least three second test data of the rotor assembly in the mechanical dimension are obtained in the foregoing embodiment, data fitting is performed by analysis software based on the obtained three first test data and the obtained second test data, respectively, please refer to fig. 8, fig. 8 is a schematic diagram of data fitting analysis of the first test data, and Weibull (Weibull) distribution, 3-parameter Weibull distribution, exponential distribution and normal distribution fitting are performed on the first test data, respectively, and as seen in fig. 8, the fitting degree under Weibull distribution is the best and the three lines are relatively parallel, so the best fitting is Weibull distribution. Referring to fig. 9, fig. 9 is a schematic diagram of a weibull distribution fitting performed on three first test data; the three first test data are obtained by testing the insulated winding at the temperature of 60 ℃, 80 ℃ and 100 ℃ respectively; in fig. 9, three straight lines represent the relationship between the service life time of the insulated winding and the confidence coefficient at different temperatures, and the larger the percentage value of the ordinate is, the lower the confidence coefficient is, and the time of the abscissa is the service life of the insulated winding at the corresponding temperature; as an example, the first life time durations at 60 degrees celsius, 80 degrees celsius, and 100 degrees celsius, respectively, at 50% confidence level can be predicted by software based on the first functional relationship obtained in fig. 9, respectively, are: 146 hours, 81 hours and 22 hours. Similarly, at least three second test data of the rotor assembly in the mechanical dimension are obtained in the foregoing embodiment, and the best fit is obtained as a weibull distribution, and a second functional relationship is obtained, and the second life duration under several confidence degrees can be predicted, which is not described herein.

S73: and obtaining the residual life duration of the generator to be tested based on the first life duration, the second life duration and the operated duration.

In some possible embodiments, obtaining the remaining life duration of the generator to be tested based on the first life duration, the second life duration, and the operated duration includes: and for a plurality of target confidence degrees, obtaining the residual life time of the generator to be tested under the corresponding target confidence degrees based on the first life time and the second life time under the same target confidence degrees and the operated time.

Specifically, after the first life duration, the second life duration and the operated duration are obtained, the first life duration and the second life duration under the same confidence level can be subtracted from the operated duration, wherein the smaller one is the remaining life duration of the generator; for example, the first life time length for obtaining the 50% confidence at 60 degrees celsius is 146 hours, and assuming that the second life time length for obtaining the 50% confidence is 100 hours and the operated time length is 60 hours, the remaining life time length should be 40 hours; in other implementation scenarios, the reliability test can enable the generator rotor assembly to operate under different rotating speed/torque working conditions, if the generator rotor assembly is assumed to operate under the working condition A for 40 hours and under the working condition B for 10 hours, the second service life of the generator rotor under the working condition A and under the condition that the confidence coefficient is 50% can be obtained by applying the obtained second functional relation, and if the second service life is 80 hours, the loss of 1/2 is considered to be caused; the second service life time of the generator rotor assembly under the condition of operating under the working condition B and the confidence coefficient of 50% is 100 hours, and the loss of 1/10 is considered to be caused; and adding the loss percentages of the generator rotor assembly under all working conditions to obtain a loss percentage of 60%, dividing the operated time length by the loss percentage to obtain the total service life time length, and subtracting the operated time length from the total service life time length to obtain the residual service life time length in the mechanical dimension.

Referring to fig. 10, fig. 10 is a schematic diagram illustrating a frame of an embodiment of a reliability test apparatus 100 for a vehicle generator according to the present application. The reliability test device 100 of the vehicle generator includes: an acquisition module 101, configured to acquire operation data of vehicle generators of a plurality of target users in various dimensions; wherein the various dimensions include a temperature dimension, a mechanical dimension, and a voltage dimension; the screening module 102 is configured to screen the operation data covering the target proportion in each dimension, as target data of the corresponding dimension; a determining module 103, configured to determine a first life model of the insulated winding based on first test data of the insulated winding in a temperature dimension, and determine a second life model of the rotor assembly based on second test data of the rotor assembly in a mechanical dimension; the prediction module 104 is configured to predict a first equivalent test duration at a reliability test temperature based on the first life model and the insulation winding temperature and the first operation duration in the target data in the temperature dimension, and predict a second equivalent test duration at a reliability test speed/torque combination based on the second life model and the speed/torque combination and the second operation duration in the target data in the mechanical dimension; the control module 105 is configured to control, based on the first equivalent test duration and the second equivalent test duration, the insulation winding of the target generator to operate under the insulation winding voltage in the target data in the voltage dimension and control the rotor assembly of the target generator to operate with a reliability test speed/torque combination, so as to obtain a reliability test result of the target generator.

According to the scheme, the reliability test device 100 of the vehicle generator realizes the steps in the embodiment of the reliability test method of the vehicle generator, and the reliability acceleration test is carried out on the insulated winding and the rotor of the motor at the same time, so that the motor assembly can work at the temperature, the rotating speed/torque and the voltage conditions of the reliability acceleration test at the same time, the test sample size and the test times can be reduced, and the test time is shortened; and the stress state of the motor after assembly can be well simulated, and the accuracy of the reliability test of the motor is improved.

In some disclosed embodiments, the control module 105 includes a detection submodule 1051, an adjustment submodule 1052, and a result acquisition submodule 1053; the detection submodule 1051 is used for monitoring real-time temperature of the insulation winding in the process of controlling the insulation winding of the target generator to work in the voltage dimension under the insulation winding voltage in the target data and controlling the rotor assembly of the target generator to operate in a reliability test speed/torque combination for a second equivalent test duration; the adjusting submodule 1052 is used for adjusting at least one of the temperature of the cooling liquid and the flow rate of the cooling liquid based on whether the real-time temperature reaches the equivalent damage temperature of the second equivalent test duration; the result acquisition submodule 1053 controls the target generator to stop operating in response to the second equivalent test period in which the target generator has operated, and acquires the reliability test result of the target generator.

Therefore, the temperature of the cooling liquid is regulated and controlled, and the equivalent of temperature damage and mechanical damage are achieved at the same time, so that the reliability test is closer to the actual operation condition, the result is more accurate, and the number of test factors is reduced.

In some disclosed embodiments, the screening module 102 includes a first equivalent time duration calculation sub-module 1021, a first ordering sub-module 1022, a first data selection sub-module 1023; the first equivalent time length calculation sub-module 1021 is configured to predict an equivalent time length of the insulation winding at the target temperature based on the insulation winding temperature and the first operation time length in the preset lifetime model and the operation data of the insulation winding; the first sorting submodule 1022 is used for sorting the operation data in the temperature dimension according to the order of the equivalent duration from small to large; the first data selection sub-module 1023 selects the operation data covering the target proportion as the target data of the temperature dimension based on the operation data ordered in the temperature dimension.

Therefore, by acquiring the operation data in the temperature dimension as the target data and screening the operation data covering the target proportion, the target data can meet specific requirements, and the subsequent model determination is more accurate.

In some disclosed embodiments, the screening module 102 further includes a second equivalent time length calculation sub-module 1024, a second ordering sub-module 1025, a second data selection sub-module 1026, and a reference data selection sub-module 1027; wherein, the reference data selecting sub-module 1027 is used for selecting one of the operation data in the mechanical dimension as the reference data; the second equivalent duration calculation sub-module 1024 is configured to predict, for each operation data in the mechanical dimension, a pseudo damage value of the operation data relative to the reference data based on a preset lifetime model of the rotor assembly; the second sorting sub-module 1025 is configured to sort the operation data in the machine dimension according to the order from the small to the large of the pseudo-damage values; the second data selection sub-module 1026 selects the operational data that covers the target proportion as the target data for the machine dimension based on the operational data ordered in the machine dimension.

Therefore, by acquiring the operation data in the mechanical dimension as the target data and screening the operation data covering the target proportion, the target data can meet specific requirements, and the subsequent model determination is more accurate.

In some disclosed embodiments, the determining module 103 includes a first test data acquisition sub-module 1031, a first function fitting sub-module 1032, and a first updating sub-module 1033, wherein the first test data acquisition sub-module 1031 acquires at least three first test data of the insulation winding in a temperature dimension; wherein the first test data comprises a component failure duration when operating at the test temperature; the first function fitting sub-module 1032 performs function fitting on a preset life model of the insulated winding based on at least three first test data to obtain a predicted value of an experience parameter in the preset life model; the first updating submodule 1033 updates the preset life model based on the predicted value of the empirical parameter in the preset life model of the insulated winding to obtain a first life model.

Therefore, the predicted value of the experience parameter is obtained through the test, and the first life model is determined, so that the calculation result of the first life model is more accurate, and the undertest and the over-test are avoided.

In some disclosed embodiments, the determination module 103 further includes a second test data acquisition sub-module 1034, a second function fitting sub-module 1035, and a second updating sub-module 1036, wherein the second test data acquisition sub-module 1034 acquires at least three second test data of the rotor assembly in the mechanical dimension; wherein the second test data comprises a component failure duration when operating at the test speed/torque combination; the second function fitting sub-module 1035 performs function fitting on the preset life model of the rotor assembly based on at least three second test data to obtain a predicted value of the experience parameter in the preset model; the second update sub-module 1036 updates the preset life model based on the predicted values of the empirical parameters in the preset life model of the rotor assembly to obtain a second life model.

Therefore, the predicted value of the experience parameter is obtained through the test, and the second life model is determined, so that the calculation result of the second life model is more accurate, and the undertest and the over-test are avoided.

Referring to fig. 11, fig. 11 is a schematic diagram illustrating a life prediction apparatus 110 of a vehicle generator according to an embodiment of the present application. Specifically, the life prediction device 110 includes an obtaining module 111, configured to obtain a rotation speed/torque combination of a rotor assembly, an insulation winding temperature, and an operated duration of a generator to be tested, and obtain a first life model of the insulation winding and a second life model of the rotor assembly; the first life model and the second life model are obtained based on the reliability test device; the prediction module 112 is configured to predict a first life duration based on the first life model and an insulation winding temperature of the generator to be tested, and predict a second life duration based on a second life model and a rotation speed/torque combination of the generator to be tested; the determining module 113 is configured to obtain a remaining lifetime of the generator to be tested based on the first lifetime, the second lifetime, and the operated lifetime.

According to the scheme, the residual life time of the generator can be calculated through the life time and the operated time under different test dimensions.

In some disclosed embodiments, the prediction module 112 includes a first prediction submodule 1121 and a second prediction submodule 1122; the first prediction submodule 1121 is used for selecting a first functional relation matched with the temperature of the insulated winding of the generator to be tested based on the first life model, and predicting first life time lengths under a plurality of target confidence degrees respectively based on the matched first functional relation; the second prediction submodule 1122 selects a second functional relationship matched with the rotational speed/torque combination of the generator to be tested based on the second life model and predicts second life time lengths under a plurality of target confidence degrees respectively based on the matched second functional relationship;

in some disclosed embodiments, the determining module 113 includes a determining sub-module 1131 configured to, for a number of target confidences, obtain a remaining life duration of the generator to be tested under the corresponding target confidence, based on the first life duration and the second life duration under the same target confidence, and the operated duration.

Referring to fig. 12, fig. 12 is a schematic diagram of a frame of an embodiment of an electronic device 120 of the present application. The electronic device 120 includes: a memory 121 and a processor 122 coupled to each other, the memory 121 storing program instructions, the processor 122 being configured to execute the program instructions to implement the steps of any of the generator reliability test method or generator life prediction method embodiments described above. In particular, the electronic device 120 may include, but is not limited to: desktop computers, notebook computers, servers, cell phones, tablet computers, car phones, and the like, are not limited herein.

In particular, the processor 122 is configured to control itself and the memory 121 to implement the steps of any of the peripheral vision calibration method embodiments described above. The processor 122 may also be referred to as a CPU (Central Processing Unit ). The processor 122 may be an integrated circuit chip having signal processing capabilities. The processor 122 may also be a general purpose processor, a digital signal processor (Digital Signal Processor, DSP), an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), a Field programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. In addition, the processor 122 may be commonly implemented by an integrated circuit chip.

According to the scheme, the electronic equipment 120 realizes the steps in the reliability test or life prediction method embodiment of the vehicle generator, on one hand, the reliability acceleration test is carried out on the insulated winding and the rotor of the motor, and the motor assembly is enabled to work under the temperature, the rotating speed/torque and the voltage conditions of the reliability acceleration test, so that the test sample size and the test times can be reduced, and the test time is shortened; the stress state of the motor after assembly can be well simulated, the accuracy of the reliability test of the motor is improved, and the residual life time of the generator can be calculated through the life time and the running time under different test dimensions.

Referring to fig. 13, fig. 13 is a schematic diagram illustrating an embodiment of a computer readable storage medium 130 according to the present application. The computer readable storage medium 130 stores program instructions 131 that can be executed by the processor, the program instructions 131 being for implementing the steps in any of the vehicle generator reliability test methods or vehicle generator life prediction method embodiments described above.

According to the scheme, the steps in the reliability test or life prediction method embodiment of the vehicle generator are realized by the computer readable storage medium 130, on one hand, the reliability acceleration test is carried out on the insulated winding and the rotor of the motor, and the motor assembly is enabled to work under the temperature, the rotating speed/torque and the voltage conditions of the reliability acceleration test, so that the test sample size and the test times can be reduced, and the test time is shortened; the stress state of the motor after assembly can be well simulated, the accuracy of the reliability test of the motor is improved, and the residual life time of the generator can be calculated through the life time and the running time under different test dimensions.

In the several embodiments provided in the present application, it should be understood that the disclosed methods and apparatus may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of modules or units is merely a logical functional division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical, or other forms.

The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiment.

In addition, each functional unit in each embodiment of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.

The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be embodied essentially or in part or all or part of the technical solution contributing to the prior art or in the form of a software product stored in a storage medium, including several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) or a processor (processor) to perform all or part of the steps of the methods of the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.

If the technical scheme of the application relates to personal information, the product applying the technical scheme of the application clearly informs the personal information processing rule before processing the personal information, and obtains independent consent of the individual. If the technical scheme of the application relates to sensitive personal information, the product applying the technical scheme of the application obtains individual consent before processing the sensitive personal information, and simultaneously meets the requirement of 'explicit consent'. For example, a clear and remarkable mark is set at a personal information acquisition device such as a camera to inform that the personal information acquisition range is entered, personal information is acquired, and if the personal voluntarily enters the acquisition range, the personal information is considered as consent to be acquired; or on the device for processing the personal information, under the condition that obvious identification/information is utilized to inform the personal information processing rule, personal authorization is obtained by popup information or a person is requested to upload personal information and the like; the personal information processing rule may include information such as a personal information processor, a personal information processing purpose, a processing mode, and a type of personal information to be processed.

Claims

1. A reliability test method of a vehicle generator, comprising:

Acquiring operation data of vehicle generators of a plurality of target users in various dimensions; wherein the various dimensions include a temperature dimension, a mechanical dimension, and a voltage dimension;

screening operation data covering a target proportion in each dimension respectively to serve as target data of corresponding dimensions, determining a first life model of an insulated winding based on first test data of the insulated winding in the temperature dimension, and determining a second life model of a rotor assembly based on second test data of the rotor assembly in the mechanical dimension;

predicting a first equivalent test duration at a reliability test temperature based on the first life model and the insulation winding temperature and first operation duration in the target data in the temperature dimension, and predicting a second equivalent test duration at a reliability test speed/torque combination based on the second life model and the speed/torque combination and second operation duration in the target data in the mechanical dimension;

and controlling an insulated winding of a target generator to work under the voltage of the insulated winding in the target data under the voltage dimension based on the first equivalent test duration and/or the second equivalent test duration, and controlling a rotor assembly of the target generator to operate at the reliability test temperature and/or the reliability test rotating speed/torque combination to obtain a reliability test result of the target generator.

2. The method according to claim 1, wherein said controlling the insulated winding of the target generator to operate at the insulated winding voltage in the target data in the voltage dimension and controlling the rotor assembly of the target generator to operate at the reliability test temperature and/or reliability test speed/torque combination based on the first equivalent test duration and/or the second equivalent test duration, results in a reliability test result of the target generator, comprises:

monitoring a real-time temperature of an insulated winding of the target generator during the second equivalent test period by controlling the insulated winding of the target generator to work at the voltage of the insulated winding in the target data in the voltage dimension and controlling a rotor assembly of the target generator to operate at the reliability test speed/torque combination;

adjusting at least one of a coolant temperature and a coolant flow based on whether the real-time temperature reaches an equivalent damage temperature of the second equivalent test duration;

and responding to the second equivalent test duration of the target generator, controlling the target generator to stop running, and obtaining a reliability test result of the target generator.

3. The method of claim 2, wherein the adjusting at least one of the coolant temperature, the coolant flow based on whether the real-time temperature reaches an equivalent damage temperature for the second equivalent test duration comprises at least one of:

responsive to the real-time temperature not reaching the equivalent damage temperature for the second equivalent test duration, performing at least one of increasing the coolant temperature, decreasing the coolant flow;

and in response to the real-time temperature exceeding the equivalent damage temperature for the second equivalent test duration, performing at least one of reducing the coolant temperature and increasing the coolant flow.

4. The method according to claim 1, wherein, in the case where the various dimensions include the temperature dimension, the screening the operation data covering the target proportion in the various dimensions, respectively, as the target data corresponding to the dimensions, includes:

for each operation data in the temperature dimension, predicting the equivalent time length of the insulation winding at the target temperature based on a preset life model of the insulation winding and the insulation winding temperature and the first operation time length in the operation data;

Sequencing the operation data in the temperature dimension according to the sequence of the equivalent time length from small to large;

and selecting the operation data covering the target proportion as the target data of the temperature dimension based on the operation data sequenced in the temperature dimension.

5. The method according to claim 1, wherein, in the case where the various dimensions include the mechanical dimension, the screening the operation data covering the target proportion in the various dimensions, respectively, as the target data corresponding to the dimensions, includes:

selecting one of the operation data of the mechanical dimension as reference data;

predicting, for each of the operational data in the mechanical dimension, a pseudo-damage value of the operational data relative to the reference data based on a preset life model of the rotor assembly;

sequencing the operation data in the mechanical dimension according to the sequence of the pseudo damage values from small to large;

and selecting the operation data covering the target proportion as the target data of the mechanical dimension based on the operation data sequenced in the mechanical dimension.

6. The method of claim 1, wherein the determining a first life model of the insulated winding based on first test data of the insulated winding in the temperature dimension comprises:

Acquiring at least three first test data of the insulated winding in the temperature dimension; wherein the first test data comprises a component failure duration when operating at a test temperature;

performing function fitting on a preset life model of the insulated winding based on the at least three first test data to obtain a predicted value of an experience parameter in the preset life model;

and updating the preset life model based on the predicted value of the experience parameter in the preset life model of the insulated winding to obtain the first life model.

7. The method of claim 1, wherein the determining a second life model of the rotor assembly based on second test data of the rotor assembly in the mechanical dimension comprises:

acquiring at least three of the second test data for the rotor assembly in the mechanical dimension; wherein the second test data comprises a component failure duration when operating at a test speed/torque combination;

performing function fitting on a preset life model of the rotor assembly based on the at least three second test data to obtain a predicted value of an experience parameter in the preset life model;

And updating the preset life model based on the predicted value of the experience parameter in the preset life model of the rotor assembly to obtain the second life model.

8. A life prediction method of a vehicle generator, comprising:

acquiring a rotating speed/torque combination, an insulating winding temperature and an operated time length of a rotor assembly of a generator to be tested, and acquiring a first service life model of the insulating winding and a second service life model of the rotor assembly; wherein the first life model and the second life model are derived based on the method of any one of claims 1 to 7;

predicting and obtaining a first service life duration based on the first service life model and the temperature of an insulating winding of the generator to be tested, and predicting and obtaining a second service life duration based on the second service life model and the rotating speed/torque combination of the generator to be tested;

and obtaining the residual life duration of the generator to be tested based on the first life duration, the second life duration and the operated duration.

9. The method of claim 8, wherein the first life model comprises a first functional relationship between confidence and life time for different temperatures of the insulated winding and the second life model comprises a second functional relationship between confidence and life time for different speed/torque combinations.

10. The method of claim 9, wherein predicting a first life duration based on the first life model and an insulation winding temperature of the generator under test comprises:

selecting a first functional relation matched with the temperature of the insulated winding of the generator to be tested based on the first life model, and predicting first life time lengths under a plurality of target confidence degrees respectively based on the matched first functional relation;

the predicting a second life duration based on the second life model and the rotation speed/torque combination of the generator to be tested includes:

selecting a second function relation matched with the rotating speed/torque combination of the generator to be tested based on the second life model, and predicting second life time lengths under the plurality of target confidence degrees respectively based on the matched second function relation;

the obtaining the remaining life duration of the generator to be tested based on the first life duration, the second life duration and the operated duration includes:

and for the plurality of target confidence degrees, obtaining the residual life time of the generator to be tested under the corresponding target confidence degrees based on the first life time and the second life time under the same target confidence degrees and the operated time.

11. A reliability test device for a vehicle generator, comprising:

the acquisition module is used for acquiring operation data of the vehicle generators of a plurality of target users in various dimensions; wherein the various dimensions include a temperature dimension, a mechanical dimension, and a voltage dimension;

the screening module is used for screening the operation data covering the target proportion in the various dimensions respectively to serve as target data corresponding to the dimensions;

a determining module for determining a first life model of the insulated winding based on first test data of the insulated winding in the temperature dimension and a second life model of the rotor assembly based on second test data of the rotor assembly in the mechanical dimension;

the prediction module is used for predicting a first equivalent test duration at a reliability test temperature based on the first life model and the insulation winding temperature and the first operation duration in the target data in the temperature dimension, and predicting a second equivalent test duration at a reliability test speed/torque combination based on the second life model and the speed/torque combination and the second operation duration in the target data in the mechanical dimension;

The control module is used for controlling the insulated winding of the target generator to work under the voltage of the insulated winding in the target data under the voltage dimension and controlling the rotor assembly of the target generator to operate at the reliability test rotating speed/torque combination based on the first equivalent test duration and the second equivalent test duration, so as to obtain a reliability test result of the target generator.

12. A life prediction apparatus of a vehicle generator, comprising:

the acquisition module is used for acquiring the rotating speed/torque combination, the temperature of the insulated winding and the running time of the rotor assembly in the generator to be tested, and acquiring a first service life model of the insulated winding and a second service life model of the rotor assembly; wherein the first life model and the second life model are derived based on the apparatus of claim 11;

the prediction module is used for predicting and obtaining a first service life duration based on the first service life model and the temperature of the insulating winding of the generator to be detected, and predicting and obtaining a second service life duration based on the second service life model and the rotating speed/torque combination of the generator to be detected;

the determining module is used for obtaining the residual life duration of the generator to be tested based on the first life duration, the second life duration and the operated duration.

13. An electronic device comprising a memory and a processor coupled to each other, the memory storing program instructions, the processor for executing the program instructions to implement the reliability test method of the vehicle generator of any one of claims 1 to 7, or the life prediction method of the vehicle generator of any one of claims 8 to 10.

14. A computer-readable storage medium, characterized in that program instructions executable by a processor for implementing the reliability test method of a vehicle generator according to any one of claims 1 to 7 or the life prediction method of a vehicle generator according to any one of claims 8 to 10 are stored.