Method for predicting service life of transmission shaft of passenger car based on stiffness degradation law

Abstract

The invention relates to a method for predicting the service life of a transmission shaft of a passenger car based on a rigidity degradation law, which belongs to the technical field of vehicle quality control and comprises the following steps of: performing an abrasion test on the transmission shaft and recording test data; according to the test data, establishing a relational expression between a cubic function assumed abrasion loss and use time; establishing an index degradation formula; change of abrasion loss during service of the transmission shaft is obtained; the probability of failure caused by the fact that the shaft diameter exceeds the design deviation range is calculated, and a service life density function of the transmission shaft in the design deviation range is obtained; establishing a corrected transmission shaft service quality loss model according to the change relationship between the transmission shaft service life and the quality loss present value; and predicting the service life of the passenger car transmission shaft. According to the method, the service life of the passenger car transmission shaft in the service stage is predicted through the corrected passenger car transmission shaft service quality loss model on the basis of the rigidity degradation law, replacement can be carried out in time, and the safety of the passenger car and passengers is ensured.

Description

Technical Field

[0001] The invention belongs to the technical field of vehicle quality control, and in particular relates to a method for predicting the service life of a passenger car transmission shaft based on a stiffness degradation law. Background Art

[0002] The drive shaft of a passenger car is an important component in the automobile transmission system. Its main components include a universal joint fork, a cross shaft, a spline shaft, and a universal joint. The spline shaft and the universal joint fork are connected by a sliding bearing to form a telescopic sleeve. When the drive shaft transmits power, the active end and the passive end are not on the same plane, so there is a height difference and a length difference. Therefore, a telescopic sleeve is used for adjustment. As the drive shaft of a passenger car enters the service stage, due to the material of the drive shaft itself, complex working conditions and the personal habits of the driver, the key quality characteristics of the drive shaft will gradually change with the service time. The existing quality loss model does not consider the influencing factors of stiffness degradation, but the structural reliability of the drive shaft is crucial to the safety of vehicle operation. Therefore, it is necessary to combine the actual situation and predict the quality loss of the passenger car drive shaft during service based on the wear law and stiffness degradation law, so that it can be replaced in time before its quality does not meet normal use and ends its service life, so as to ensure the safety of the passenger car and the passengers on the vehicle. Summary of the invention

[0003] The purpose of the present invention is to address the problems existing in the prior art and provide a method for predicting the service life of a passenger car drive shaft based on the stiffness degradation law. By predicting the service life of a passenger car drive shaft during the service stage, it is convenient to replace it in time when its service life is reached, thereby ensuring the safety of the passenger car and passengers.

[0004] The technical solution is as follows:

[0005] A method for predicting the service life of a passenger car transmission shaft based on a stiffness degradation law comprises the following steps:

[0006] Step 1: Perform a wear test on the transmission shaft and record the test data;

[0007] Step 2: Based on the test data, establish a cubic function and assume that the relationship between the wear amount W(t) and the use time t is: W(t) = a1+a2t+a3t 2 +a4t 3 , where a1, a2, a3 and a4 are the wear coefficients of each term of the cubic function;

[0008] Step 3: According to the monotonically decreasing trend of the transmission shaft stiffness with the increase of service time, an exponential degradation formula is established: Where β0 is the initial value of transmission shaft stiffness degradation, and β1 is the transmission shaft stiffness degradation coefficient;

[0009] Step 4: Combine the formulas in steps 2 and 3 to obtain the change in wear of the drive shaft during service. where μ x is the process mean, σ x is the process standard deviation;

[0010] Step 5: The probability of failure caused by the shaft diameter x(t) exceeding the design deviation range is calculated by using the probability p(0) that the shaft diameter x(0) is a good product when it is delivered to the customer and the probability p(t) that the shaft diameter x(0) is a good product when it is in service: By taking the derivative of the shaft diameter x(t) with respect to time t, we can obtain the service life density function of the transmission shaft within the design deviation range:

[0011] Where ζ(t) represents the service life probability density distribution function of the transmission shaft, G(t) and g(t) represent the stiffness degradation amount and stiffness degradation rate of the transmission shaft, respectively, and W(t) and I(t) represent the wear amount and wear rate of the transmission shaft, respectively;

[0012] Step 6: Establish a modified transmission shaft service quality loss model based on the changing relationship between the transmission shaft service life and the quality loss present value:

[0013] Where T U 、T L They represent the upper and lower limits of product functions respectively, and α and β are service coefficients, which are determined by the service conditions of the drive shaft and the operating habits of the passenger car driver;

[0014] Step 7: Use the modified drive shaft service quality loss model to predict the service life of the passenger car drive shaft.

[0015] Furthermore, in step 2, a1, a2, a3 and a4 are obtained by the following formula: m represents the data set measured in each transmission shaft bench test.

[0016] Furthermore, the probability density function of the transmission shaft diameter x(0) being a good product when delivered to the customer in step 5 is: where k n is the normalization constant, k n =99.73%, and the probability after integrating it is: The probability density function of the transmission shaft being good when in service is: After integrating it, the probability is:

[0017] Furthermore, the wear rate of the transmission shaft in step 5 is I(t)=a2+2a3t+3a4t 2 , stiffness degradation rate

[0018] Furthermore, in step 6, based on the present value of capital flow theory, a modified transmission shaft service quality loss model is established through the following steps:

[0019] Step 61: Assume that the shaft diameter x(t) of the transmission shaft exceeds the design deviation range at the service time t, causing the transmission shaft to fail, and the loss caused is C m =L(t)(1+r) t , r is the annual interest rate of the transmission shaft, then the present value of quality loss is L(t) = C m (1+r) -t , the range is [0,C m ];

[0020] Step 62: Divide a year into m periods. As the service life of the transmission shaft increases, the total number of periods is tm, the unit time of each period is dt, and the mass loss of the transmission shaft in one period is C m ζ(t)dt, the discounted value of the mass loss of the transmission shaft per unit time is:

[0021] Step 63: Integrate the discounted value of the mass loss of the transmission shaft per unit time within the service life to obtain the total mass loss of the transmission shaft during its service life, that is, the formula for the service mass loss of the transmission shaft is:

[0022]

[0023] Step 64: Substitute the service life density function in step 5 into the service quality loss formula of the transmission shaft in step 63 to obtain a modified service quality loss model.

[0024] Beneficial effects:

[0025] 1) The present invention takes into account the influence of wear and stiffness degradation on the service of the drive shaft, and modifies the service life distribution function based on the geometric quality characteristics of the drive shaft to obtain a modified service quality loss model for the passenger car drive shaft. The result of life prediction using this model can be more in line with the actual situation.

[0026] 2) The service life of the passenger car drive shaft in the service stage, i.e., the service life, is predicted by the modified service quality loss model of the passenger car drive shaft, so that it can be replaced in time when the service life is reached to ensure the safety of the passenger car and passengers. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 The present invention is a flow chart of the method.

[0028] Figure 2 The figure is a curve diagram showing the average mass loss of the transmission shaft of the present invention changing with the service life. DETAILED DESCRIPTION

[0029] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention. The directions or positional relationships indicated by the terms "upper", "lower", "front", "back", "left", "right", "bottom", "inside", "outside", etc. are based on the directions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as limiting the present invention:

[0030] like Figure 1 A method for predicting the service life of a passenger car transmission shaft based on a stiffness degradation law is shown, comprising the following steps:

[0031] Step 1: Perform a wear test on the transmission shaft and record the test data;

[0032] Step 2: Based on the test data, establish a cubic function and assume that the relationship between the wear amount W(t) and the use time t is: W(t) = a1+a2t+a3t 2 +a4t 3 , where a1, a2, a3 and a4 are the wear coefficients of each cubic function, and a1, a2, a3 and a4 are obtained by the following formula m represents the data set measured in each transmission shaft bench test;

[0033] Step 3: According to the monotonically decreasing trend of the transmission shaft stiffness with the increase of service time, an exponential degradation formula is established:

[0034] Step 4: Combine the formulas in steps 2 and 3 to obtain the change in wear of the drive shaft during service. where μ x is the process mean, σ x is the process standard deviation;

[0035] Step 5: The probability of failure caused by the shaft diameter x(t) exceeding the design deviation range is calculated by using the probability p(0) that the shaft diameter x(0) is a good product when it is delivered to the customer and the probability p(t) that the shaft diameter x(0) is a good product when it is in service: By taking the derivative of the shaft diameter x(t) with respect to time t, we can obtain the service life density function of the transmission shaft within the design deviation range:

[0036] Where ζ(t) represents the service life probability density distribution function of the transmission shaft, G(t) and g(t) represent the stiffness degradation amount and stiffness degradation rate of the transmission shaft respectively, W(t) and I(t) represent the wear amount and wear rate of the transmission shaft respectively, and the probability density function of the transmission shaft diameter x(0 being a good product when delivered to the customer is: where k n is the normalization constant, k n =99.73%, and the probability after integrating it is: The probability density function of the transmission shaft being good when in service is: After integrating it, the probability is: Wear rate of transmission shaft I(t) = a2+2a3t+3a4t 2 , stiffness degradation rate Where β0 is the initial value of transmission shaft stiffness degradation, and β1 is the transmission shaft stiffness degradation coefficient;

[0037] Step 6: Establish a modified transmission shaft service quality loss model based on the changing relationship between the transmission shaft service life and the quality loss present value:

[0038] Where T U 、T L They represent the upper and lower limits of product functions respectively, and α and β are service coefficients, which are determined by the service conditions of the drive shaft and the operating habits of the passenger car driver;

[0039] Step 7: Use the modified drive shaft service quality loss model to predict the service life of the passenger car drive shaft.

[0040] In step 6, based on the present value of capital flow theory, the modified transmission shaft service quality loss model is established through the following steps:

[0041] Step 61: Assume that the shaft diameter x(t) of the transmission shaft exceeds the design deviation range at the service time t, causing the transmission shaft to fail, and the loss caused is C m =L(t)(1+r) t , r is the annual interest rate of the transmission shaft, then the present value of quality loss is L(t) = C m (1+r) -t , the range is [0,C m ];

[0042] Step 62: Divide a year into m periods. As the service life of the transmission shaft increases, the total number of periods is tm, the unit time of each period is dt, and the mass loss of the transmission shaft in one period is C m ζ(t)dt, the discounted value of the mass loss of the transmission shaft per unit time is:

[0043] Step 63: Integrate the discounted value of the mass loss of the transmission shaft per unit time within the service life to obtain the total mass loss of the transmission shaft during its service life, that is, the formula for the service mass loss of the transmission shaft is:

[0044]

[0045] Step 64: Substitute the service life density function in step 5 into the service quality loss formula of the transmission shaft in step 63 to obtain a modified service quality loss model.

[0046] Example 1: According to QC / T 29082-2019 "Technical Conditions and Bench Test Methods for Automobile Transmission Shaft Assemblies", a closed transmission shaft test bench with sliding bearings was built, and the transmission shaft specimen was loaded through a loading device using a rotary torque sensor. Before the test, the initial values ​​of the splines and shaft tubes on the transmission shaft spline shaft were measured. The transmission shaft first needed to undergo a 4-hour running-in test under no-load conditions, and then a 20% rated load was applied for a loading test. During the loading test, the following test requirements must be determined: the amount of expansion and contraction of the spline must be greater than 10 mm each time, the number of expansion and contraction per minute must be greater than 30 times, and the transmission shaft speed must be greater than 500 revolutions per minute. The specimen was disassembled and inspected every 30 hours, the wear data of the spline and shaft tube were recorded, and the loading test was continued after the lubricating oil was added. When the wear amount of more than three teeth in the measurement data of the spline wear exceeds 0.30 mm, it is determined that the transmission shaft has suffered wear fatigue failure, and the data of the spline and shaft tube at this time are recorded, and the test is terminated at this time.

[0047] The length of the transmission shaft specimen is 1700mm, the wall thickness of the shaft tube is 2.2mm, the diameter is 70mm, and its elastic modulus is 200GPa. If the lateral swing is set to 220mm, the length of the transmission shaft after extension is 1714mm, that is, the expansion is 14mm, which meets the requirements of the loading test. The wear amount of the shaft tube can be obtained by subtracting the measured shaft tube wall thickness data from the initial wall thickness data. Take some test data, as shown in Table 1:

[0048] Table 1 Drive shaft wear test data

[0049]

[0050] According to the cubic function, the relationship between the wear amount W(t) and the use time t is: W(t) = a1+a2t+a3t 2 +a4t 3

[0051] Where a1, a2, a3 and a4 are the coefficients of each term of the cubic function, which are obtained by the following formula:

[0052]

[0053] By fitting the experimental data in Table 1, the coefficients are obtained as follows: a1 = 0.002, a2 ​​= 1.962 × 10 -5 , a3=-3.669×10 -8 , a4=2.965×10 -11 , after substituting the above results into the fitting relationship between wear amount and time: W(t)=0.002+1.962×10 -5 t-3.669×10 -8 t 2 +2.965×10 -11 t 3

[0054] During the service life of a part, when the quality characteristics of the key features of the part deviate from the specified range, quality loss will inevitably occur, which is defined as the service quality loss of the part. The loss model is as follows:

[0055] Where: T U 、T L They represent the upper and lower limits of product functions, respectively, and α and β are service coefficients;

[0056] As the service time increases, the quality characteristic value of the part will change with the service condition of the part and the performance of the part itself. x (t),σ x (t) all change linearly with the service time. During the service process, the key quality characteristics of the parts will increase with the increase of service life. For shaft parts, if the key quality characteristic is the shaft diameter, as the service time increases, the shaft diameter will decrease, and at this time α < 0; for hole parts, if the key quality characteristic is the hole diameter, as the service time increases, the hole diameter will increase, and at this time α > 0. However, since the operating conditions of the parts will not always be single and the situation is complicated during the service process, the key quality characteristic values ​​of the parts will not show a single linear change with the service time of the parts. In order to more accurately analyze the changes in the key quality characteristics of the parts with the service time, it is necessary to correct the above-mentioned quality loss model.

[0057] For the transmission shaft of a passenger car, its failure is generally caused by long-term wear of the shaft. On the other hand, due to the degradation of the transmission shaft stiffness, the transmission shaft undergoes elastic deformation, during which the wear of the transmission shaft increases, which leads to the instability of the wear change and changes in its variance. Therefore, the wear and stiffness degradation law of the transmission shaft is used for correction.

[0058] As for the degradation law of transmission shaft stiffness, its stiffness generally shows a monotonically decreasing trend with the increase of service time. The exponential degradation model is established as shown in the following formula: Where β0 is the initial value of the transmission shaft stiffness degradation, and β1 is the transmission shaft stiffness degradation coefficient.

[0059] W(t)=a1+a2t+a3t 2 +a4t 3 and Substitution We can get μ x (t) and σ x The changing pattern of (t):

[0060]

[0061] In actual use, due to the complexity of the operating conditions, the key quality characteristics of the transmission shaft will change with the service time. For the transmission shaft, one of its key quality characteristics is the shaft diameter. As the service time increases, the transmission shaft will wear and the shaft diameter will decrease. At this time, the transmission shaft clearance will increase and resonance will occur. When the shaft diameter is lower than the normal working requirement range, the part fails. Assume that the key quality characteristic shaft diameter x(t) of a batch of transmission shafts obeys the normal distribution at any time, that is, x(t)~N(μ x (t),σ 2 x (t)). Assuming that the key quality feature of a batch of transmission shafts, the shaft diameter x(t), is random at every moment, the service life of the transmission shaft is also random due to complex and uncertain working conditions. When the transmission shaft passes the inspection and leaves the factory, the key quality feature of the transmission shaft, the shaft diameter x(0), must meet the design specifications within the design deviation upper limit T U And the lower limit of deviation T L Within the range, that is, T L <x(0)<T U At this time, the key quality feature of the transmission shaft, the shaft diameter x(0), needs to obey the truncated normal distribution, and its probability density function is as follows: Where k n is the normalization constant, k n =99.73%. By integrating the probability density function within the deviation range, the probability that the transmission shaft is a good product when it is delivered to the customer is:

[0062] On the other hand, when the transmission shaft is put into use and is in its service life, it must also meet the key quality characteristics of the transmission shaft, and the shaft diameter x(t) must be within the design deviation range, that is, T L <x(t)<T U Similarly, the key quality characteristic of the transmission shaft during service, the shaft diameter x(t), also needs to obey the truncated normal distribution, and its probability density function is as follows: By integrating the probability density function within the deviation range, the probability that the transmission shaft is good when in service is obtained as follows:

[0063] The probability of failure due to shaft diameter x(t) exceeding the design deviation range is:

[0064] By taking the derivative of the shaft diameter x(t) with respect to time t, we can obtain the service life density function of the transmission shaft within the design deviation range:

[0065] Where ζ(t) represents the service life probability density distribution function of the transmission shaft, G(t) and g(t) represent the stiffness degradation amount and stiffness degradation rate of the transmission shaft, W(t) and I(t) represent the wear amount and wear rate of the transmission shaft, I(t) = a2+2a3t+3a4t 2 ,

[0066] For a batch of transmission shafts, the key quality feature is the shaft diameter x(t). From the time the parts are inspected and shipped to the time they are put into service and then to the time they fail, x(t) is always changing. Once the key quality feature changes, the parts will have quality loss. If the shaft diameter x(t) of one of the transmission shafts exceeds the design deviation range at a certain time t in service, the transmission shaft will fail. Assume that the loss caused by the failed transmission shaft is C m The present value of the quality loss caused by the key quality characteristic value, i.e., the shaft diameter x(t), exceeding the design deviation range at the time of leaving the factory is L(t). According to the present value calculation method of capital flow, the loss caused by the failed transmission shaft is C m =L(t)(1+r) t , where r is the annual interest rate of the transmission shaft; the discounted value of the quality loss caused by the failure of the transmission shaft L(t) = C m (1+r) -t .

[0067] The discounted value of quality loss is a monotonically decreasing function. On the one hand, as the service time t of the transmission shaft increases, the discounted value of quality loss will decrease. On the other hand, when the annual interest rate r of the transmission shaft increases, its discounted value of quality loss will also decrease. If the service time t of the transmission shaft is infinite, the discounted value of quality loss will approach 0 infinitely. If the service time t of the transmission shaft is 0, that is, the transmission shaft is unqualified when it leaves the factory, the discounted value of quality loss caused at this time is C m The range of the discounted value of the transmission shaft quality loss should be [0,C m ].

[0068] The life cycle distribution of the transmission shaft is random. When the life distribution density function of the transmission shaft is known, the quality loss model of the transmission shaft is established. Due to the existence of the annual interest rate of the transmission shaft, that is, it will be divided into m periods in a year, then as the service life of the transmission shaft increases, the total number of periods is tm. Assuming that the unit time of each period is dt, the quality loss of the transmission shaft in one period is C m ζ(t)dt, substituting the mass loss in one period into formula (20), the discounted value of the mass loss of the transmission shaft per unit time is obtained as:

[0069] Integrating over the service life, the total mass loss of the transmission shaft during its service life can be obtained, that is, the service mass loss is: Substituting the service life density function of the transmission shaft within the design deviation range into the above formula, a modified service quality loss model based on the service life distribution density function of the transmission shaft considering the wear law and stiffness degradation law of the transmission shaft is obtained:

[0070]

[0071] Design value of transmission shaft diameter Then the deviation Δ=0.3mm, and the design target value is D x =63.5mm, upper limit of design specification D U =63.8mm, design specification lower limit D L =63.2mm. The present value of the loss after the drive shaft fails and is scrapped is C m =360, the present value of this loss can be determined by the drive shaft manufacturer. As shown in formula (16), in order to obtain the relationship between the average mass loss and service life of the drive shaft, it is necessary to first obtain the initial key quality characteristics x of the batch of drive shafts when they leave the factory. D The mean and variance of the parts are large when they leave the factory. In order to save time and cost, the distribution of key quality characteristics of the parts is analyzed by sampling the batch of parts to obtain sample characteristics. 200 samples are taken from 3500 transmission shaft parts leaving the factory, and the samples are measured and the relevant quality characteristic values ​​are recorded, as shown in Table 2:

[0072] Table 2 Sampling record of key quality characteristics of transmission shaft when leaving the factory

[0073]

[0074]

[0075] The normality test of the key quality characteristic values ​​of the samples in Table 2 is performed, and the relevant results are shown in Table 3:

[0076] Table 3 Normality test related data table

[0077]

[0078] The P value obtained from Table 3 is 0.4368. Since the sample P value of the key characteristic value of the transmission shaft obtained from this batch of sampling is greater than 0.05, it can be obtained that the sampling sample data approximately obeys the normal distribution.

[0079] It is known that the sampling samples of this batch of transmission shafts follow normal distribution when they leave the factory. The distribution parameters of the population are analyzed by the mean and variance of the samples. The mean can be obtained by analyzing the key quality characteristic values ​​of the samples in the table. Standard deviation σ=0.1079mm. When there are a large number of parts in the population, when sampling is selected to analyze the distribution characteristics of the population, errors will inevitably occur, namely sampling errors. Due to the existence of sampling errors, the mean and variance of the population will change. Given the sample standard deviation, more samples are needed to get closer to the population standard deviation. When the number of samples is insufficient, the sample standard deviation needs to be corrected. By correcting it, the population standard deviation S is made more accurate. The formula is:

[0080] If the overall standard deviation is known, the sampling mean error can be obtained, and then the overall distribution characteristic parameters and sampling distribution characteristic parameters of the batch of transmission shafts when leaving the factory can be obtained through analysis as shown in Table 4:

[0081] Table 4 Distribution characteristic parameter estimation table

[0082]

[0083] When analyzing the service life of the transmission shaft, the sample is used as the analysis basis, and the distribution characteristic parameter μ of the key quality characteristics when it leaves the factory is x =63.5022mm,σ x =0.0116mm. Assume that the service parameters of the drive shaft are α=-0.00015mm, β=0.0001mm / h, annual interest rate r=10%, β0=2.0751, β1=-0.7816. The above parameters can be obtained by statistics and experiments, which are indispensable for predicting the mass loss of the drive shaft. In the previous article, the wear law model of the drive shaft was obtained through the wear bench test of the drive shaft. Substituting the above parameters into the modified service mass loss model, the average mass loss of the drive shaft is obtained as the service life changes.

[0084] like Figure 2 As shown in the figure, after the transmission shaft is put into use, its mass loss increases with the increase of service life. In the early stage of service, the mass loss of the transmission shaft increases slowly. At about 2000h, the mass loss growth rate of the transmission shaft is fast. When the service life reaches about 4000h, the mass loss growth rate of the rotating shaft gradually decreases to a stable state and no longer increases. At this time, the transmission shaft is in a scrapped state and should be replaced in time.

[0085] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the principles and spirit of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for predicting the service life of a passenger car transmission shaft based on the stiffness degradation law, characterized in that: The following steps are involved: Step 1: Perform a wear test on the transmission shaft and record the test data; Step 2: Based on the test data, establish a cubic function and assume that the relationship between the wear amount W(t) and the use time t is: W(t) = a1+a2t+a3t 2 +a4t 3 , where a1, a2, a3 and a4 are the wear coefficients of each term of the cubic function; Step 3: According to the monotonically decreasing trend of the transmission shaft stiffness with the increase of service time, an exponential degradation formula is established: Step 4: Combine the formulas in steps 2 and 3 to obtain the change in wear of the drive shaft during service. where μ x is the process mean, σ x is the process standard deviation; Step 5: The probability of failure caused by the shaft diameter x(t) exceeding the design deviation range is calculated by using the probability p(0) that the shaft diameter x(0) is a good product when it is delivered to the customer and the probability p(t) that the shaft diameter x(0) is a good product when it is in service: And by taking the derivative of the shaft diameter x(t) with respect to time t, we can obtain the service life density function of the transmission shaft within the design deviation range: Where ζ(t) represents the service life probability density distribution function of the transmission shaft, G(t) and g(t) represent the stiffness degradation amount and stiffness degradation rate of the transmission shaft, respectively, and W(t) and I(t) represent the wear amount and wear rate of the transmission shaft, respectively; Step 6: Establish a modified transmission shaft service quality loss model based on the changing relationship between the transmission shaft service life and the quality loss present value: Where T U , T L They represent the upper and lower limits of product functions respectively, and α and β are service coefficients, which are determined by the service conditions of the drive shaft and the operating habits of the passenger car driver; Step 7: Use the modified drive shaft service quality loss model to predict the service life of the passenger car drive shaft.

2. The method for predicting the service life of a passenger car transmission shaft based on the stiffness degradation law according to claim 1, characterized in that: In step 2, a1, a2, a3 and a4 are obtained by the following formula: m represents the data set measured in each transmission shaft bench test.

3. The method for predicting the service life of a passenger car transmission shaft based on the stiffness degradation law according to claim 1, characterized in that: The probability density function of the transmission shaft diameter x(0) being a good product when delivered to the customer in step 5 is: where k n is the normalization constant, k n =99.73, and the probability after integrating it is: The probability density function of the transmission shaft being good when in service is: After integrating it, the probability is:

4. The method for predicting the service life of a passenger car transmission shaft based on the stiffness degradation law according to claim 1, characterized in that: The wear rate of the transmission shaft in step 5 is I(t)=a2+2a3t+3a4t 2 , stiffness degradation rate Where β0 is the initial value of the transmission shaft stiffness degradation, and β1 is the transmission shaft stiffness degradation coefficient.

5. The method for predicting the service life of a passenger car transmission shaft based on the stiffness degradation law according to claim 1, characterized in that: In step 6, based on the present value of capital flow theory, a modified transmission shaft service quality loss model is established through the following steps: Step 61: Assume that the shaft diameter x(t) of the transmission shaft exceeds the design deviation range at the service time t, causing the transmission shaft to fail, and the loss caused is C m =L(t)(1+r) t , r is the annual interest rate of the transmission shaft, then the present value of quality loss is L(t) = C m (1+r) -t , the range is [0,C m ]; Step 62: Divide a year into m periods. As the service life of the transmission shaft increases, the total number of periods is tm, the unit time of each period is dt, and the mass loss of the transmission shaft in one period is C m ζ(t)dt, the discounted value of the mass loss of the transmission shaft per unit time is: Step 63: Integrate the discounted value of the mass loss of the transmission shaft per unit time within the service life to obtain the total mass loss of the transmission shaft during its service life, that is, the formula for the service mass loss of the transmission shaft is: Step 64: Substitute the service life density function in step 5 into the service quality loss formula of the transmission shaft in step 63 to obtain a modified service quality loss model.

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