CN113776854A - Drive axle durability test method based on user road association - Google Patents
Drive axle durability test method based on user road association Download PDFInfo
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Abstract
The invention particularly relates to a drive axle durability test method based on user road association, which comprises the following steps: acquiring drive axle loads of a user road under all road conditions, and then calculating a target damage matrix of the user road according to the drive axle loads of the user road under all road conditions; acquiring drive axle loads under all road conditions of a test field, and then calculating a coefficient damage matrix after single circulation of all road conditions of the test field according to the drive axle loads under all road conditions of the test field; constructing a corresponding equal damage correlation model based on the target damage matrix and the coefficient damage matrix; and resolving the equal damage correlation model to obtain the cycle times corresponding to all road conditions of the test field, and carrying out the durability test of the drive axle based on the cycle times corresponding to all road conditions of the test field. The method for testing the durability of the drive axle can give consideration to both the practicability and the accuracy of the durability test of the drive axle, so that the test effect of the durability of the automobile drive axle can be effectively improved.
Description
Technical Field
The invention relates to the technical field of drive axle durability testing, in particular to a drive axle durability testing method based on user road association.
Background
The automobile drive axle is a key part for realizing automobile power transmission and ensuring the rotating speed difference of the inner wheel and the outer wheel, and the durability of the automobile drive axle directly influences the service life of an automobile and the safety of passengers. Therefore, road tests are required to be carried out in a test field before new vehicles come into the market, and the road tests are used as a final link for checking and verifying the durability and reliability of the power transmission system. Most of internationally advanced vehicle enterprises establish own vehicle test fields and test specifications and develop durability evaluation of the whole vehicle and key parts thereof. The existing test field test specifications of a plurality of vehicle enterprises in China mostly refer to the foreign test field specifications, and depend on past experience and habits so as to meet the established worst road conditions and be difficult to truly represent the user roads in China. Therefore, how to design a test method of the durability test field of the drive axle suitable for the road of the user in China is a problem of key research.
Aiming at the problem that the traditional drive axle durability test method is influenced by a plurality of factors such as weather, places, personnel and the like, Chinese patent with publication number CN104748971A discloses a durability test rack and a test method for a differential assembly of an automobile drive axle, which comprises the following steps: in the non-differential running-in stage, the rotating speeds of the left wheel and the right wheel are kept consistent, and the automobile drive axle assembly is subjected to initial running-in; in the differential running-in stage, the left wheel and the right wheel are kept at a certain differential speed, and the automobile drive axle assembly is subjected to differential running-in; and in the formal differential test stage, loading is carried out through a loading end of the test bed, so that the left wheel and the right wheel are alternately subjected to differential speed, the test service life is prolonged to a certain extent or the automobile drive axle differential assembly fails, and the test is stopped.
The durability test method for the drive axle (differential assembly) in the prior art achieves the purpose of checking the durability of the axle differential of the heavy-duty car through tests carried out on a test bed. However, in the existing scheme, the user road is not considered during the durability test of the drive axle, so that a certain difference exists between the failure mode of the automobile parts in a test field and the actual use of the user road, and the practicability of the durability test of the drive axle is low. Meanwhile, compared with a rack, the influence of various road conditions of a real test field on the durability of the drive axle is different, and the existing scheme does not distinguish the cycle times of various road conditions, so that relevant important factors of the durability of the drive axle are ignored, and the accuracy of the durability test of the drive axle is low. Therefore, how to design a driving axle durability test method which can take both the practicability and the accuracy of the driving axle durability test is an urgent technical problem to be solved.
Disclosure of Invention
Aiming at the defects of the prior art, the technical problems to be solved by the invention are as follows: how to provide a driving axle durability test method which can take account of the practicability and the accuracy of the driving axle durability test, thereby effectively improving the test effect of the durability of the automobile driving axle.
In order to solve the technical problems, the invention adopts the following technical scheme:
a driving axle durability test method based on user road association comprises the following steps:
s1: acquiring drive axle loads of a user road under all road conditions, and then calculating a target damage matrix of the user road according to the drive axle loads of the user road under all road conditions;
s2: acquiring drive axle loads under all road conditions of a test field, and then calculating a coefficient damage matrix after single circulation of all road conditions of the test field according to the drive axle loads under all road conditions of the test field;
s3: constructing a corresponding equal damage correlation model based on the target damage matrix and the coefficient damage matrix;
s4: and resolving the equal damage correlation model to obtain the cycle times corresponding to all road conditions of the test field, and carrying out the durability test of the drive axle based on the cycle times corresponding to all road conditions of the test field.
Preferably, the axle load comprises an axle load and a tooth load of the axle.
Preferably, in step S1, firstly, the corresponding axle load and tooth load of the user road under each road condition are obtained based on a rotating rain flow counting method; then, based on a rain flow matrix extrapolation method, extrapolating the axle load and the tooth load of each road condition of the user road to the corresponding target mileage of the user road and superposing the axle load and the tooth load; and finally obtaining damage values of 12 gear channels of left and right half shafts under a user road based on a Miner fatigue damage accumulation algorithm to form a target damage matrix T.
Preferably, in step S2, firstly, the corresponding axle load and tooth load under each road condition of the test site are obtained based on a rotating rain flow counting method; and then obtaining damage values of 12 gear channels of the left half shaft and the right half shaft under 10 test field working conditions in the test field after single circulation to form a coefficient damage matrix D based on a Miner fatigue damage accumulation algorithm.
Preferably, the damage correlation model is expressed as:
in the formula: dijThe coefficient damage value of the ith channel of the two half shafts of the drive axle under the condition of a single cycle of a j road condition of a test field is represented, wherein the two half shafts of the drive axle are divided into 12 channels according to gears; beta is ajRepresenting the cycle times of the road condition of the test field j; t isjAnd representing the target damage value of the j channel under the user road.
Preferably, when the equal damage correlation model is solved, the equal damage correlation model is converted into an objective function of a multi-objective optimization problem, and the objective function is expressed by the following formula:
fi(x:D,T)＝|[Di1,Di2,…,Dij]·[x1,x2,…,xj]T-[T1,T2,…Ti]T|；
min[f1(x),f2(x),…,fi(x)]
in the formula: 1,2, …, 12; j ═ 1,2, …, 10; f. ofi(x) Representing an objective function; lb represents a lower limit matrix; ub denotes an upper limit matrix; aeq represents the ratio of the cycle times of each road condition in the test field; beq denotes the zero matrix; a represents a one-way mileage matrix of each road condition of a test field; b represents the total mileage of the test field.
Preferably, when the equal damage correlation model is solved, the following constraint conditions need to be satisfied:
the lower limit of the cycle number is larger than zero, and the upper limit of the cycle number is the total mileage of the test field divided by the one-way mileage of each road;
the test field is provided with five strengthening loops, and the ratio of the number of circulation times among the five strengthening loops is set to be 1:2:1:1: 1;
the total mileage of the test field does not exceed fifty thousand kilometers.
Preferably, the injury association models are solved by a fast non-dominated sorting genetic algorithm.
Preferably, when the equal damage correlation model is solved through a fast non-dominated sorting genetic algorithm, a group of non-inferior solutions with the relative damage average value close to 1 and the relative damage standard deviation minimum is selected as an optimal solution, namely the cycle times corresponding to all road conditions of the test field.
Preferably, the relative damage is calculated by the following formula:
in the formula: pmiRepresenting the relative damage of the ith channel under the mth group of non-inferior solutions; t ismiRepresenting the correlated damage of the ith channel under the mth group of non-inferior solutions; t isiRepresenting the damage of the ith channel of the target damage matrix T;
wherein, TmiIs a non-inferior solution X using an approximationjReplacement of beta in Isodamage Association modelsjAnd the associated damage is obtained.
Compared with the prior art, the method for testing the durability of the drive axle has the following beneficial effects:
in the invention, through the mode of constructing the damage correlation model such as the target damage matrix and the coefficient damage matrix, and simultaneously considering the influence of the user road and the test field on the durability of the drive axle, the failure mode of the automobile parts in the test field is more fit with the actual use of the user road, thereby ensuring the practicability of the durability test of the drive axle. Meanwhile, the influence of various road conditions of the test field on the durability of the drive axle can be distinguished by calculating the coefficient damage matrix after single circulation of each road condition of the test field and the circulation times corresponding to each road condition of the test field, so that the accuracy of the durability test of the drive axle is ensured, and the durability test effect of the automobile drive axle can be improved.
In the invention, the loading characteristics of each part of the drive axle can be more comprehensively reflected through the shaft load and the tooth load, so that relevant important factors of the durability of the drive axle cannot be ignored, and the accuracy of the durability test of the drive axle can be further improved. Meanwhile, the mode of obtaining the axle load and the tooth load of the drive axle based on the rotating rain flow counting method can lay a foundation for establishing a damage incidence matrix equation of a user road-test field and the like, and can improve the correlation effect of the user road and the test field.
In the invention, the model is solved by a rapid non-dominated sorting genetic algorithm, so that the method has the advantages of small dispersity, stable relative damage ratio of each channel within the range of 0.6-1.5 and better coincidence with the road damage of a user. Meanwhile, compared with the least square method, the fast non-dominated sorting genetic algorithm does not have the condition of 0 solution.
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For purposes of promoting a better understanding of the objects, aspects and advantages of the invention, reference will now be made in detail to the present invention as illustrated in the accompanying drawings, in which:
FIG. 1 is a logic diagram of a method for testing durability of a drive axle in an embodiment;
FIG. 2 is a flowchart of a method for testing durability of a transaxle in an embodiment;
FIG. 3 is a schematic flow chart of a fast non-dominated sorting genetic algorithm in an embodiment;
FIG. 4 is a tooth load construction diagram of an embodiment;
FIG. 5 is a comparison graph of the extrapolated front and rear amplitude frequency curves for the left axle shaft 1-gear load in the embodiment;
FIG. 6 is a diagram showing the relative damage distribution of each channel in the example;
FIG. 7 is a schematic diagram showing a Form-To matrix distribution in the example;
FIG. 8 is a schematic view of the load distribution of the left and right half shafts at 1-gear position in the embodiment.
Detailed Description
The following is further detailed by the specific embodiments:
example (b):
the embodiment of the invention discloses a drive axle durability test method based on user road association.
As shown in fig. 1 and 2, a method for testing durability of a drive axle based on user road association includes:
s1: acquiring drive axle loads of a user road under all road conditions, and then calculating a target damage matrix of the user road according to the drive axle loads of the user road under all road conditions;
s2: acquiring drive axle loads under all road conditions of a test field, and then calculating a coefficient damage matrix after single circulation of all road conditions of the test field according to the drive axle loads under all road conditions of the test field;
s3: constructing a corresponding equal damage correlation model based on the target damage matrix and the coefficient damage matrix;
s4: and resolving the equal damage correlation model to obtain the cycle times corresponding to all road conditions of the test field, and carrying out the durability test of the drive axle based on the cycle times corresponding to all road conditions of the test field.
In the invention, through the mode of constructing the damage correlation model such as the target damage matrix and the coefficient damage matrix, and simultaneously considering the influence of the user road and the test field on the durability of the drive axle, the failure mode of the automobile parts in the test field is more fit with the actual use of the user road, thereby ensuring the practicability of the durability test of the drive axle. Meanwhile, the influence of various road conditions of the test field on the durability of the drive axle can be distinguished by calculating the coefficient damage matrix after single circulation of each road condition of the test field and the circulation times corresponding to each road condition of the test field, so that the accuracy of the durability test of the drive axle is ensured, and the durability test effect of the automobile drive axle can be improved.
In a specific implementation, the drive axle load includes an axle load and a tooth load of the drive axle.
Specifically, in step S1, firstly, the corresponding axle load and tooth load of the user road under each road condition are obtained based on a rotating rain flow counting method; then, based on a rain flow matrix extrapolation method, extrapolating the axle load and the tooth load of each road condition of the user road to the corresponding target mileage of the user road and superposing the axle load and the tooth load; and finally obtaining damage values of 12 gear channels of left and right half shafts under a user road based on a Miner fatigue damage accumulation algorithm to form a target damage matrix T.
Specifically, in step S2, the corresponding axle load and tooth load under each road condition of the test site are obtained based on a rotating rain flow counting method; and then obtaining damage values of 12 gear channels of the left half shaft and the right half shaft under 10 test field working conditions in the test field after single circulation to form a coefficient damage matrix D based on a Miner fatigue damage accumulation algorithm.
In the present invention, the damage calculated by the Miner fatigue damage accumulation algorithm is pseudo damage (nominal damage). The pseudo damage has the advantages of simple calculation, no relation between the characteristics of the signal and specific structures, and suitability for comparison and equivalent correlation of the endurance load. The calculation of the pseudo-damage is that firstly, a standard S-N curve needs to be constructed, and the formula is as follows:
Smn ═ C; in the formula: s represents a generalized stress amplitude, and N represents the fatigue life of the tested piece under the amplitude S; c represents a constant.
Then, a pseudo damage value D is calculated according to a Miner linear accumulated damage criterion, and the formula is as follows:
In the invention, the loading characteristics of each part of the drive axle can be more comprehensively reflected through the shaft load and the tooth load, so that relevant important factors of the durability of the drive axle cannot be ignored, and the accuracy of the durability test of the drive axle can be further improved. Meanwhile, the mode of obtaining the axle load and the tooth load of the drive axle based on the rotating rain flow counting method can lay a foundation for establishing a damage incidence matrix equation of a user road-test field and the like, and can improve the correlation effect of the user road and the test field. In addition, due to the limitation of time and cost, the collection of actually measured data of a user is limited, so that the road condition of the user is extrapolated to the target mileage by a rain flow matrix extrapolation mode, the influence of the road of the user can be fully considered, and the practicability of the durability test of the drive axle is effectively ensured.
In a specific implementation process, the equal damage correlation model is expressed as follows:
in the formula: dijThe coefficient damage value of the ith channel of the two half shafts of the drive axle under the condition of a single cycle of a j road condition of a test field is represented, wherein the two half shafts of the drive axle are divided into 12 channels according to gears; beta is ajRepresenting the cycle times of the road condition of the test field j; t isjAnd representing the target damage value of the j channel under the user road.
In a specific implementation process, when the equal damage correlation model is solved, the equal damage correlation model is converted into an objective function of a multi-objective optimization problem, and the objective function is expressed by the following formula:
fi(x:D,T)＝|[Di1,Di2,…,Dij]·[x1,x2,…,xj]T-[T1,T2,…Ti]T|；
min[f1(x),f2(x),…,fi(x)]
in the formula: 1,2, …, 12; j ═ 1,2, …, 10; f. ofi(x) Representing an objective function; lb represents a lower limit matrix; ub denotes an upper limit matrix; aeq represents the ratio of the cycle times of each road condition in the test field; beq denotes the zero matrix; a represents a one-way mileage matrix of each road condition of a test field; b represents the total mileage of the test field.
Specifically, when the damage correlation model such as the solution is calculated, the following constraint conditions need to be satisfied:
the lower limit of the cycle number is larger than zero, and the upper limit of the cycle number is the total mileage of the test field divided by the one-way mileage of each road:
The test field has five strengthening loops, and the ratio of the number of cycles between the five strengthening loops is 1:2:1:1: 1.
The total mileage of the test field does not exceed fifty thousand kilometers.
Specifically, the injury correlation model such as the injury correlation model is solved through a rapid non-dominated sorting genetic algorithm. The principle of the fast non-dominated ranking genetic algorithm is shown in FIG. 3.
Specifically, when the equal damage correlation model is solved through a rapid non-dominated sorting genetic algorithm, a group of non-inferior solutions with the relative damage average value close to 1 and the relative damage standard deviation minimum are selected as the optimal solution, namely the cycle times corresponding to all road conditions of the test field.
The relative damage was calculated by the following formula:
in the formula: pmiRepresenting the relative damage of the ith channel under the mth group of non-inferior solutions; t ismiIndicates that the m-th group is not inferiorSolving the correlated damage of the ith channel; t isiRepresenting the damage of the ith channel of the target damage matrix T;
wherein, TmiIs a non-inferior solution X using an approximationjReplacement of beta in Isodamage Association modelsjAnd the associated damage is obtained.
In the invention, the model is solved by a rapid non-dominated sorting genetic algorithm, so that the method has the advantages of small dispersity, stable relative damage ratio of each channel within the range of 0.6-1.5 and better coincidence with the road damage of a user. Meanwhile, compared with the least square method, the fast non-dominated sorting genetic algorithm does not have the condition of 0 solution. In addition, the society of each constraint condition enables the cycle number output by the model to further guarantee the continuity of the road condition of the test site and the reasonability of the cycle number on the basis of guaranteeing the practicability and the accuracy of the test of the drive axle.
To better illustrate the advantages of the method for testing the durability of the drive axle of the present invention, the following tests are also disclosed in this example:
and selecting a commercial vehicle as a test vehicle. Mounting six-component force sensors at two wheel ends of a rear axle of a commercial vehicle to obtain torque and rotating speed information of an output end of a half axle; the gear signal CAN be read by a CAN signal; a GPS sensor is installed to know the vehicle speed and to acquire the line. In addition, in order to distinguish the subsequent collected road conditions and working conditions, the logic switch is used for distinguishing.
Load collection of user road
The mileage proportion of commercial vehicles passing through expressways, urban roads, general roads (national roads, provincial roads and rural roads) and severe roads is respectively set to be 40%, 30%, 20% and 10%. The experiment utilizes a plurality of groups of drivers to carry out segmentation, extrapolation and superposition on the actual measurement load under the road condition of a typical user road to equivalently simulate a 200000km overall sample of the user road. The road condition information of the user road is shown in table 1.
TABLE 1 road condition information of user roads
Second, load collection of test field
According to the existing test run operation specification, single acquisition of two half-shaft torque is carried out on each characteristic road condition in a certain large-scale test field in China. The main working conditions of the test field comprise a strengthening working condition, a power working condition, a high-speed working condition and the like, and in order to ensure the continuity of subsequent tests, the road conditions consisting of various road surfaces are taken as one of test standard working conditions and are divided into 10 sub-working conditions, namely F1-F10. The differences of driving habits of different users are considered during the collection, and the 3 drivers respectively collect the driving habits for 3 times. The test site road condition information is shown in the table 2.
TABLE 2 information of road conditions in test field
Thirdly, constructing an isodamage correlation model
Firstly, the statistical counting of the load is carried out to obtain the corresponding relation between the load and the frequency, and the axle load and the tooth load of the drive axle are obtained by a rotating rain flow counting method because the drive axle rotating part mainly comprises components such as a half axle, a gear and the like.
The axial load represents a half-shaft torque rain flow counting result and is an important data source for examining a half-shaft bench test; according to the rule that the half shaft rotates for a circle and the single tooth is meshed for one time, the pulse torque time history of the single tooth is drawn, and then the conventional rain flow counting is carried out to record the pulse torque time history as the tooth load, as shown in fig. 4. And because the assessment component is a drive axle assembly, the load and frequency results obtained by superposing the shaft load and the tooth load are recorded as Total.
Due to the limitation of time and cost, the collection of the actual measurement data of the user road is limited, so that the load sample measured under a certain condition is used for replacing the whole, and the road condition of the user road is extrapolated to the target mileage based on the rain flow matrix extrapolation principle, as shown in fig. 5.
Four, equal damage correlation model calculation
Programming in matlab, iterating for 134 times based on NSGA-II (fast non-dominated sorting genetic) algorithm, and obtaining 77 groups of pareto optimal solutions which are converged, wherein each group of non-inferior solutions is concentrated with 10 solutions and represents the circulation times of each working condition of a test field. Specifically, the results are shown in Table 3.
TABLE 3 non-inferior solution set
According to the distribution of the solution, the proportional relation between the loop cycles F1-F5 and the loop cycles X1-X5 meets the set constraint condition. In addition, the solution set is limited in the [ lb, ub ] range, the total test mileage obtained by multiplying and accumulating the cycle times of each working condition and the one-way mileage of each road condition is less than fifty thousand kilometers, and therefore the solution condition meets the design requirement.
77 groups of non-inferior solutions Xmi are respectively substituted into the equal damage correlation model to obtain the correlation damage values T of 12 channelsmiBy comparing the correlated lesions T of 12 channelsmiAnd target lesion TiThe damage ratio between was recorded as the relative damage PmiThe closer the value is to 1, the better the equivalent effect, and 77 groups of relative lesions are finally obtained as shown in Table 4.
TABLE 4 relative Damage
As can be seen from table 4, most of the relative damages show positive correlation, that is, the values of the channels affect each other, and an increase or decrease of one value causes global change, and it cannot be ensured that all solutions are close to 1 at the same time. Therefore, a group of non-inferior solutions with the relative damage average value close to 1 and the relative damage standard deviation minimum, namely the fluctuation minimum, is selected as the optimal solution. Through multiple calculations, group 6 with an average value μ of 1.00 and a standard deviation σ of 0.31 was selected.
Fifth, making test standard of test field
Considering the rationality of the test field endurance test standard driving path planning, optimization needs to be properly carried out according to engineering experience on the basis of the cycle times of the test field under various working conditions calculated based on NSGA-II. According to the characteristics of the sixth solution, each working condition is an integral multiple of 100, so that the test field endurance test is convenient to carry out. The established transaxle durability test field test specifications are shown in table 5.
TABLE 5 Transaxle durability test field test Specification
Sixthly, relative damage verification
The correlation damage channel is reliable when the relative damage ratio P is within 0.5-2. Therefore, the relative damage value under each channel is calculated based on the least square solution and the test specification after NSGA-II optimization, and the average value and standard deviation are further calculated, and the result is shown in FIG. 6. As can be seen from fig. 6, the relative damage is distributed on both sides of the 1 value, the range is stable between 0.6 and 1.5, the mean value is 0.96, and the standard deviation is 0.28 (it is difficult to achieve that the relative damage ratio is completely equal to 1 due to the difference between the user road and the test field condition and the complexity of the objective function).
Seventhly, load distribution verification
According to the new test field test specification, a load amplitude cumulative frequency curve of the test field equivalent to 20 km of the user road can be obtained, and whether the load distribution condition under the test specification is reasonable or not can be analyzed by comparing the load amplitude cumulative frequency curve with the load amplitude cumulative frequency curve under the user road condition. The comparative results are shown in fig. 7, taking the 1 st gear load of the left and right half shafts as an example. As can be seen from fig. 7, the low-frequency second-order large load contributes most to damage of the component.
As can be seen from the graph in FIG. 8, the frequency of the large load on the road surface of the test field is greater than that of the user road. Based on the damage equivalence principle, the frequency of small load occurrence in a test field should be reduced, and the user roads are opposite. Therefore, the load distribution is more reasonable by comparing the two graphs, which shows that the correlation result between the user road and the test field is more ideal.
In conclusion, the test field test specification of the invention can better reproduce the effect of the actual use condition of the road of the user in both the relative damage and the load distribution, and meet the requirement of the test field test of the durability of the drive axle.
Eighthly, calculating the pavement strengthening coefficient of the test field
The test field pavement strengthening coefficient is the ratio of the driving mileage of the drive axle on the user road to the test mileage of the test field under the same failure mode, and the calculation formula is as follows:
The strengthening coefficient K was calculated to be 4.34. The user can run 20 km on the road, and only tests 46133.3km in a test field, so that the requirement for checking the durability of the drive axle can be met.
Nine conclusion
The test researches the test specification of the durability test field of the commercial vehicle drive axle based on the user road association method, and establishes a new test specification, so that the following conclusion can be obtained:
(1) based on a rotating rain flow counting method, the axle load and the tooth load of the drive axle are obtained, the loading characteristics of all parts of the drive axle are reflected more comprehensively, and a foundation is laid for building a damage incidence matrix equation such as 'user road-test field'.
(2) Compared with the situation that the least square method has 0 solution, the solution obtained by the genetic algorithm has small dispersity, the relative damage ratio of each channel is stable within the range of 0.6-1.5, and the solution is more consistent with the road damage of a user. And the test standard test mileage consisting of various characteristic road surfaces is 46133.3km, which is equivalent to 20 km of road driving of users, thereby greatly shortening the test time and the cost.
(3) The durability test field test specification of the invention conforms to the road driving condition of users in China, and the thought and the method thereof provide reference and basis for the formulation of a drive axle transmission system, even the reliability of the whole vehicle and the durability test field test specification.
It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that, while the invention has been described with reference to preferred embodiments thereof, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims. Meanwhile, the detailed structures, characteristics and the like of the common general knowledge in the embodiments are not described too much. Finally, the scope of the claims should be determined by the content of the claims, and the description of the embodiments and the like in the specification should be used for interpreting the content of the claims.
Claims (10)
1. A drive axle durability test method based on user road association is characterized by comprising the following steps:
s1: acquiring drive axle loads of a user road under all road conditions, and then calculating a target damage matrix of the user road according to the drive axle loads of the user road under all road conditions;
s2: acquiring drive axle loads under all road conditions of a test field, and then calculating a coefficient damage matrix after single circulation of all road conditions of the test field according to the drive axle loads under all road conditions of the test field;
s3: constructing a corresponding equal damage correlation model based on the target damage matrix and the coefficient damage matrix;
s4: and resolving the equal damage correlation model to obtain the cycle times corresponding to all road conditions of the test field, and carrying out the durability test of the drive axle based on the cycle times corresponding to all road conditions of the test field.
2. The user-roadway-association-based transaxle durability test method of claim 1, wherein: the axle loads include axle loads and tooth loads of the drive axle.
3. The user-roadway-association-based transaxle durability test method of claim 2, wherein: in step S1, firstly, obtaining corresponding axle load and tooth load of a user road under each road condition based on a rotating rain flow counting method; then, based on a rain flow matrix extrapolation method, extrapolating the axle load and the tooth load of each road condition of the user road to the corresponding target mileage of the user road and superposing the axle load and the tooth load; and finally obtaining damage values of 12 gear channels of left and right half shafts under a user road based on a Miner fatigue damage accumulation algorithm to form a target damage matrix T.
4. The user-roadway-association-based transaxle durability test method of claim 3, wherein: in step S2, firstly, obtaining corresponding axle load and tooth load under each road condition of a test field based on a rotating rain flow counting method; and then obtaining damage values of 12 gear channels of the left half shaft and the right half shaft under 10 test field working conditions in the test field after single circulation to form a coefficient damage matrix D based on a Miner fatigue damage accumulation algorithm.
5. The user road association-based transaxle durability test method of claim 4, wherein the damage-waiting correlation model is expressed as:
in the formula: dijThe coefficient damage value of the ith channel of the two half shafts of the drive axle under the condition of a single cycle of a j road condition of a test field is represented, wherein the two half shafts of the drive axle are divided into 12 channels according to gears; beta is ajRepresenting the cycle times of the road condition of the test field j; t isjAnd representing the target damage value of the j channel under the user road.
6. The user-roadway-association-based transaxle durability test method of claim 5, wherein: when the equal damage correlation model is solved, the equal damage correlation model is converted into an objective function of a multi-objective optimization problem, and the objective function is expressed by the following formula:
fi(x:D,T)＝|[Di1,Di2,…,Dij]·[x1,x2,…,xj]T-[T1,T2,…Ti]T|；
min[f1(x),f2(x),…,fi(x)]
in the formula: 1,2, …, 12; j ═ 1,2, …, 10; f. ofi(x) Representing an objective function; lb represents a lower limit matrix; ub denotes an upper limit matrix; aeq represents the ratio of the cycle times of each road condition in the test field; beq denotes the zero matrix; a represents a one-way mileage matrix of each road condition of a test field; b represents the total mileage of the test field.
7. The user-roadway-association-based transaxle durability test method of claim 6, wherein: when the equal damage correlation model is solved, the following constraint conditions are required to be met:
the lower limit of the cycle number is larger than zero, and the upper limit of the cycle number is the total mileage of the test field divided by the one-way mileage of each road;
the test field is provided with five strengthening loops, and the ratio of the number of circulation times among the five strengthening loops is set to be 1:2:1:1: 1;
the total mileage of the test field does not exceed fifty thousand kilometers.
8. The user-roadway-association-based transaxle durability test method of claim 7, wherein: and solving the equal damage correlation model by a rapid non-dominated sorting genetic algorithm.
9. The user-roadway-association-based transaxle durability test method of claim 8, wherein: when the equal damage correlation model is solved through a rapid non-dominated sorting genetic algorithm, a group of non-inferior solutions with the relative damage average value close to 1 and the relative damage standard deviation minimum are selected as the optimal solution, namely the cycle times corresponding to all road conditions of the test field.
10. The user-roadway-association-based transaxle durability test method of claim 9, wherein: the relative damage was calculated by the following formula:
in the formula: pmiRepresenting the relative damage of the ith channel under the mth group of non-inferior solutions; t ismiRepresenting the correlated damage of the ith channel under the mth group of non-inferior solutions; t isiRepresenting the damage of the ith channel of the target damage matrix T;
wherein, TmiIs a non-inferior solution X using an approximationjReplacement of beta in Isodamage Association modelsjAnd the associated damage is obtained.
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