A method for evaluating the risk of iliac bone injury of a frontal collision oblique dummy

Abstract

The present application relates to the technical field of automobile collision safety test, and discloses a front collision oblique dummy ilium injury risk assessment method, which comprises three types of data of collecting trolley collision test, trolley collision simulation and corpse real vehicle calibration, three independent ilium injury risk functions with ilium X direction load as independent variable are respectively constructed, the injury curve is drawn based on each risk function, the load values corresponding to multiple injury probability are extracted and mean value fusion is carried out, the standardized ilium injury theoretical threshold is obtained, a batch of measured ilium loads are collected to establish a cumulative distribution model, the same probability quantile measured load is extracted, and the comprehensive injury assessment combined with theory and measurement is completed by comparing the theoretical threshold value. The present application can realize injury quantification relying on existing dummy single-axis sensing data, effectively reduce single data deviation by multi-path modeling fusion, and improve engineering practicability by combining with measured load distribution checking, and can be used for intelligent cabin large inclination seat restraint optimization, collision safety evaluation index and related regulation threshold value setting.

Description

Technical Field

[0001] This invention relates to the field of automotive crash safety testing technology, specifically to a method for assessing the risk of iliac bone injury in a tilted dummy during a frontal collision. Background Technology

[0002] In the field of automotive crash safety, crash test dummies are widely used evaluation tools in automotive safety standards. Their built-in sensors measure the dynamic response during a collision, and the output indicators are directly related to the safety evaluation of the tested object and the design optimization of constraint settings. The existing automotive safety standards' crash test injury assessment system basically covers the head, neck, chest, and lower limbs, serving as a regulatory benchmark for automotive development.

[0003] With the development and popularization of intelligent driving, occupants are increasingly inclined to adopt a large-angle semi-reclined posture in the cabin, leading to a proliferation of large-angle seat products designed to enhance comfort. However, the collision injury mechanism of occupants changes in abnormal sitting postures. Accident statistics show a higher rate of iliac bone injury in injuries sustained in tilted positions. Existing research indicates that seat belts tend to concentrate load on the iliac bone in a tilted posture, causing iliac bone fractures. Current automotive safety standards primarily focus on occupants in normal sitting positions, and dummy injury assessment systems do not yet include requirements for the iliac bone. Future automotive safety regulations addressing the safety of tilted occupants in intelligent cockpit environments need to introduce iliac bone injury assessment, including the selection of iliac bone injury indicators and the establishment of indicator values ​​for each assessment level.

[0004] Currently, the more advanced THOR crash test dummies used in the regulations, as well as the THOR-AV and THOR-RS dummies based on THOR and applied to tilted postures, all have force sensors installed in the iliac bone of the pelvis. Due to the limited internal space of the iliac bone structure in the dummies, the iliac bone force sensors are uniaxial sensors, which can only measure loads perpendicular to the inclined plane where the iliac bone is located. Furthermore, they lack a damage risk function for the iliac bone, making it difficult to accurately assess the risk of iliac bone damage under different measured values ​​of uniaxial loads on the iliac bone.

[0005] To promote the development of intelligent vehicle safety technology, there is an urgent need for a method to assess the injury risk of the iliac bone in tilted dummies, to assist in the formulation of key iliac bone injury indicators and thresholds under large tilt seats, and to promote the establishment of future safety evaluation standards for occupants of large tilt seats. Summary of the Invention

[0006] The present invention aims to provide a method for assessing the risk of iliac bone injury in a frontal collision tilting dummy, in order to solve the problem that existing tilting posture collision dummies can only measure the uniaxial X-axis load of the iliac bone, lack an assessment model based on this uniaxial load to quantify the probability of iliac bone injury, and cannot reliably calibrate the load threshold for grading iliac bone injury under large tilting seats.

[0007] To achieve the above objectives, the present invention adopts the following technical solution: A method for assessing the risk of iliac bone injury in a tilted dummy during a frontal collision includes: S1, acquire data from frontal collision tests and simulations of large-angle seat trolley crash tests using dummies, as well as calibration data from cadaver tests on real vehicles; S2. Based on the data obtained from the trolley collision test, the trolley collision simulation and the calibration data from the cadaver vehicle test, an iliac bone injury risk function with the iliac bone X-direction load as the independent variable was constructed respectively. S3. Draw the damage risk curve according to the damage risk function, extract the iliac bone load value corresponding to each curve according to the probability level, and calculate the theoretical threshold of iliac bone load corresponding to each probability level by means fusion. S4. Collect several measured X-axis loads on the iliac bone from collisions with tilted dummy trolleys, construct a cumulative probability distribution model of the measured loads, extract the measured load values ​​corresponding to the cumulative probabilities of each probability level, compare the theoretical threshold with the measured load values, and complete the comprehensive assessment of the iliac bone injury risk of the tilted dummy.

[0008] The principle and advantages of this scheme are as follows: In practical applications, three types of differentiated data sources are collected simultaneously: trolley physical test data, trolley simulation data, and cadaver tilt collision calibration data. These correspond to the force transmission law of the actual vehicle, the simulation full-domain working condition data, and the actual human injury benchmark, respectively, providing an independent and cross-validated data foundation for multi-path parallel modeling. Three independent data links are used to establish injury risk functions with only the measurable iliac bone X-axis load of the dummy as input. This transforms the uniaxial load that the dummy hardware can only collect into a quantitative model that can characterize the probability of iliac bone injury in humans, thus solving the limitations of dummy sensor hardware and human injury. The core contradiction of the benchmark model mismatch is addressed by averaging the damage probability load values ​​output by three independent risk functions. This multi-model cross-comparison cancels out systematic errors caused by a single data source and a single mapping path, outputting a unified and robust theoretical threshold for graded iliac bone injury, forming a standardized damage judgment scale. Furthermore, a batch of experimental loads is introduced to construct an empirical cumulative distribution, extracting experimental loads with the same probability quantile as the theoretical threshold. The theoretical critical value derived purely from the mechanism is then compared with the actual collision force level of mass-produced seats, completing a dual verification of mechanistic damage risk and engineering measured performance, thus achieving a complete and practical comprehensive assessment of iliac bone injury.

[0009] Preferably, as an improvement, S2 includes S21, constructing a first damage risk function based on the data from the trolley test; S21 includes: S211, using the cadaveric iliac bone AIS2+ injury risk function as the baseline function:

[0010] in, This represents the probability of AIS2+ injury in the iliac bone when the independent variable is F. This represents the triaxial composite load borne by the iliac crest in the human body. Represents the natural constant; S212, linear regression analysis was performed using the least squares method to establish... and Linear regression relationship:

[0011] In the formula, The regression slope, The regression intercept; S213, based on industry standards and The mapping relationship in S212 and The mapping relationship was derived to obtain the X-axis load of the dummy iliac bone. Combined force with triaxial load The linear mapping relationship is as follows:

[0012] In the formula and The values ​​are respectively and ; S214, X-axis load on the dummy's iliac bone Combined force with triaxial load Substituting the linear mapping relationship into the reference function, we obtain the X-axis load of the dummy iliac bone. The first damage risk function for the input indicators: .

[0013] Technical benefits: Based on the correlation between lumbar belt force and iliac bone load in real vehicle trolley tests, and combined with the mature human cadaver injury benchmark formula, an indirect mapping is completed. The first risk function fits the force transmission logic of real trolley tests, making full use of existing physical test data. The damage assessment model can be quickly built without a large number of cadaver test samples, and is suitable for conventional vehicle development test scenarios.

[0014] Preferably, as an improvement, S2 includes S22, constructing a second damage risk function based on the trolley collision simulation data; S22 includes: S221, Conduct least squares linear regression analysis and establish... The linear mapping relationship is:

[0015] , The regression constant; S222, will Substituting the linear mapping relationship into the reference function, the derivation of the X-axis load on the dummy iliac bone is obtained. The second damage risk function is the independent variable: .

[0016] Technical benefits: Linear fitting modeling is performed directly based on the uniaxial load and triaxial composite load of the iliac bone output by the simulation model. It is not affected by the measurement error of the seat belt lap force and can form data cross-validation with the S21 test path, making up for the deficiencies of small physical test samples and incomplete work condition coverage, and broadening the sources of modeling data.

[0017] Preferably, as an improvement, S2 includes S23, constructing a third damage risk function based on cadaver vehicle test calibration data: the third damage risk function is obtained by fitting a survival analysis based on the Weibull distribution as follows:

[0018] In the formula , It is a constant parameter.

[0019] Technical effect: Based on real human cadaver tilt collision injury data, Weibull survival analysis is used to directly calibrate the correspondence between uniaxial load and human injury probability, avoiding the transmission error caused by multi-level mapping of the first two paths. The third risk function best fits the real human iliac bone injury mechanism, improving the physiological authenticity of the overall assessment results.

[0020] Preferably, as an improvement, in S3, the theoretical threshold of iliac bone load corresponding to each damage probability is... for:

[0021] In the formula, i represents the damage probability level, and j represents the damage risk function. The value of the iliac bone X-axis load corresponding to the j-th risk curve under the i-th level of injury probability.

[0022] Technical effect: The arithmetic mean of the probability quantile loads of the three risk curves with completely independent mechanisms and data sources is taken to offset the modeling bias of the single path, output a unified and objective theoretical threshold for graded damage, avoid the evaluation results of a single model being too conservative or too optimistic, and provide a unified quantitative reference benchmark for industry evaluation standards.

[0023] Preferably, as an improvement, in S4, the cumulative probability distribution model of the measured iliac bone X-axis load is as follows:

[0024] in, To measure the total number of tilting dummy trolley crash tests, The measured iliac bone load data The position of the value in the ascending sequence. This indicates that the iliac bone load of the dummy under the current tilt seat product does not exceed The percentage of trials.

[0025] Technical benefits: It adopts empirical cumulative distribution calculation, without assuming that the load follows a specific probability distribution, which is suitable for the engineering situation where the sample size of automobile crash tests is limited; by comparing the theoretical threshold with the actual load of the product through a unified quantile value, it can intuitively quantify the safety margin of the iliac crest of the seat force, realize a comprehensive assessment that combines theoretical damage risk with the actual working conditions of mass-produced products, and provide a quantitative basis for design optimization.

[0026] Preferably, as an improvement, the frontal collision condition includes either FRB or MPDB conditions.

[0027] Technical benefits: It covers the current mainstream frontal collision regulations and test conditions for passenger vehicles. The evaluation method can be directly adapted to various frontal collision development and verification. The method is highly universal and does not require separate modification of the evaluation process for different collision conditions.

[0028] Preferably, as an improvement, the dummy is an improved THOR 50th dummy.

[0029] Technical advantages: This type of dummy is equipped with a uniaxial force sensor on the iliac bone, which can collect the data required for modeling without modifying the dummy hardware, making it suitable for assessment tools for the development of tilt occupant safety in smart cockpits.

[0030] Preferably, as an improvement, the backrest angle of the large-angle seat is ≥35°.

[0031] Technical effect: By distinguishing between traditional upright sitting posture and the scenario of large-angle reclining seats in smart cockpits, the evaluation results are only for high-risk iliac bone injury conditions, avoiding interference from normal sitting posture data in injury threshold calibration, and the evaluation is more targeted. Attached Figure Description

[0032] Figure 1 This is a flowchart illustrating a method for assessing the risk of iliac bone injury in a tilted dummy during a frontal collision. Detailed Implementation

[0033] The following detailed description illustrates the specific implementation method: The basic implementation examples are as follows: Figure 1 As shown: A method for assessing the risk of iliac bone injury in a tilted dummy during a frontal collision includes: S1, acquire data from frontal collision tests using dummies at large angles of the seat trolley and trolley collision simulations, as well as calibration data from cadaver vehicle tests.

[0034] The frontal collision conditions include either FRB or MPDB, and the seat back is tilted at 35° or more during the large tilt seat test.

[0035] The trolley crash test includes: using a modified THOR 50th dummy, installing a seat with a large tilt angle (backrest tilt angle ≥35°), and setting up the FRB or MPDB frontal crash trolley test conditions; installing uniaxial force sensors on the left and right iliac crests of the dummy, and lumbar force sensors on the seat belt lap belt; performing the trolley frontal crash test, and simultaneously acquiring the time-domain load curves of the sensors throughout the entire crash process; extracting the peak load of the sensors on both the left and right iliac crests throughout the entire crash, and simultaneously extracting the peak load of the lumbar force of the seat belt throughout the entire crash process; comparing the peak load values ​​of the left and right iliac crests, selecting the side with the larger load as the target side; and recording the peak uniaxial X-direction load of the iliac crest on the target side. Simultaneously record the peak force of the seat belt under the corresponding collision condition. To form a set of experimental data pairs ( , );repeat Secondary collision test, accumulation Group valid ( , The data pairs are used for subsequent modeling.

[0036] The trolley collision simulation includes: replicating the finite element model of the trolley, seat, seat belt, and THOR series tilted dummy in the large-angle frontal collision test; establishing load output measurement points at the corresponding positions of the sensors on one side of the dummy's iliac crest (either left or right), and defining the triaxial force output measurement points of the iliac crest; submitting the frontal collision simulation calculation using FRB or MPDB; and reading the peak X-axis load output from the single-axis sensor of the iliac crest from the simulation output file. Simultaneously, the force components in the X, Y, and Z directions at the iliac bone measuring point are read, and the resultant force of the triaxial load is calculated using the three-dimensional force components of the iliac bone. ; in the same simulation With the calculated Form a set of simulation data pairs ( , );repeat Group simulation working conditions, accumulation Group( , The data pairs are used for subsequent modeling.

[0037] The calibration data for the live-vehicle crash test with a corpse was obtained by collecting domestic and international frontal collision tests on a human corpse trolley, screening and summarizing test cases with a seat-torso tilt angle ≥35°, and recording the total number of cases as follows: Review the test reports of each case to determine whether the cadaver's iliac bone suffered AIS2 or higher damage. If AIS2+ damage was present, the damage label was marked as 1; otherwise, it was marked as 0. For each screened cadaver collision case, the X-axis load on the dummy's iliac bone under the corresponding working conditions was obtained using two methods based on the cadaver's body shape and physical characteristics. If the cadaver's physical characteristics meet the 50th percentile male standard in Europe and America, then a physical inclined dummy will be used to reproduce all the boundary conditions of the cadaver test to carry out the trolley collision test, and the X-axis load on the dummy's iliac bone will be collected and recorded. If the cadaver's physical characteristics exceed the 50th percentile male standard in Europe and America, the dummy finite element model is scaled down to match the body shape of the cadaver being tested. Then, a trolley environment model consistent with the cadaver test is imported to conduct collision simulation, and the X-axis load of the dummy's iliac bone in the simulation output is extracted and recorded. For all For example, after the cadaver test completes the corresponding dummy load reproduction, the iliac bone load of the dummy measured under each working condition is... One-to-one matching with the binary tags of AIS2+ injury in the iliac crest of the cadaver to form Group( Damage label data pairs are used for subsequent modeling.

[0038] S2, based on data obtained from trolley collision tests, trolley collision simulations, and calibration data from cadaver vehicle tests, constructs a system with X-axis load on the iliac crest. S2 is a risk function for iliac bone injury, with the independent variable being the iliac bone injury risk function. S2 includes: S21. A damage risk function is constructed based on data from the trolley test. Using existing research findings on damage risk in cadaver iliac bone failure tests under load, and based on the AIS2+ damage baseline risk function for the cadaver iliac bone, combined with dummy load data collected from the trolley collision test, a linear mapping is used to derive the damage risk function based on the X-axis load of the dummy iliac bone. The first damage risk function for the independent variable is defined as follows: S211, Determine the baseline function for human injury, using the AIS2+ injury risk function obtained from cadaver iliac crest band load failure tests in existing research as the baseline:

[0039] in, This represents the probability of AIS2+ injury in the iliac bone when the independent variable is F. This represents the triaxial composite load borne by the iliac crest in the human body. Represents the natural constant.

[0040] S212, for The dataset was analyzed using the least squares method for linear regression to establish... and The linear relationship:

[0041] In the formula, The regression slope, The regression intercept is used, and both are constant terms. After fitting, the coefficient of determination R is checked. 2 We confirm that its value is close to 1 to ensure the fitting accuracy of linear regression.

[0042] S213, Simultaneous Derivation and The mapping relationship is used, referencing the THOR 50th dummy crash test response analysis results with improved tilted attitude under existing frontal collision conditions, and the resultant force of the triaxial load on the iliac crest. With seat belt lap force The following mapping relationship is satisfied:

[0043] The above and The linear relationship and S212 With seat belt lap force Mapping relation, eliminating intermediate variables The X-axis load of the dummy iliac bone was derived. Combined force with triaxial load The linear mapping relationship is:

[0044] In the formula and The values ​​are respectively and .

[0045] S214, Generate the first damage risk function, and load the dummy's iliac bone in the X direction. Combined force with triaxial load Substituting the linear mapping relationship into the benchmark function (AIS2+ damage risk function), we obtain the X-axis load of the dummy iliac bone. The first damage risk function for the input indicators:

[0046] Before substituting, first check the intercept term. Perform a significance test: if A p-value greater than 0.05 indicates that the statistical significance of this term is not significant, and it should be removed when substituting it into the benchmark function. item.

[0047] S22, Construct the second damage risk function based on the trolley collision simulation data. The specific steps are as follows: S221, for Group( , The data were subjected to least squares linear regression analysis to establish... The linear mapping relationship is:

[0048] , The coefficient of determination R is the regression constant. After the regression is completed, the coefficient of determination R is verified. 2 Guarantee R 2 The value approaches 1 to ensure that the linear fitting effect meets the accuracy requirements.

[0049] S222, will Substituting the linear mapping relationship into the reference function, the derivation of the X-axis load on the dummy iliac bone is obtained. The second damage risk function is the independent variable:

[0050] S23, a third injury risk function is constructed based on the calibration data from the cadaver vehicle test. Specifically, a survival analysis based on the Weibull distribution is used for fitting. Based on the data set, the third damage risk function is obtained as follows:

[0051] In the formula , These are constant parameters obtained through survival analysis.

[0052] S3. Based on the three injury risk functions in S2, plot the injury risk curves respectively, and extract the iliac bone load value corresponding to each curve according to the probability level. The theoretical threshold of iliac bone load corresponding to each damage probability was obtained by mean fusion calculation. The specific steps are as follows: For the three damage risk functions in S2, the X-axis load of the dummy iliac bone is used. The x-axis represents the independent variable, indicating the probability of AIS2+ injury in the iliac bone. Using the vertical axis as the dependent variable, for each damage risk function, iterate through a set of continuous... The numerical values ​​are substituted one by one into the formula to calculate the corresponding damage probability. Multiple groups ( , By connecting the coordinate points, three independent damage risk curves are generated. These three curves are generated based on three types of data sources: experimental mapping, simulation mapping, and cadaver calibration. They can be cross-validated to avoid threshold distortion caused by a single data source.

[0053] Four preset engineering evaluation standard probability levels are defined: i=1, 2, 3, 4, corresponding to 25%, 50%, 75%, and 95% respectively. i=1 corresponds to a damage probability of 25% (low damage risk), i=2 corresponds to a damage probability of 50% (medium damage risk), i=3 corresponds to a damage probability of 75% (high damage risk), and i=4 corresponds to a damage probability of 95% (extremely high damage risk). Path numbers are defined as j=1, 2, 3, corresponding to three damage risk functions.

[0054] Inverse solution of load values For the i-th probability level and the j-th risk curve, fix Perform the inverse operation on the risk function of the corresponding path to solve for the unique independent variable loading value, denoted as . This yielded 4×3 sets of load values, representing the loads on 3 curves with a 25% probability. , , 3 curves under 50% probability of loading , , 3 curves under 75% probability of loading , , 95% probability of loading on 3 curves , , .

[0055] Theoretical threshold for iliac bone load sensor measurement at the i-th injury risk level in the dummy for:

[0056] S4, collecting multiple sets of tilted dummy trolley collision measurements of iliac bone X-axis load. A cumulative probability distribution model of the measured load is constructed, and the measured load values ​​corresponding to the cumulative probability of each probability level (25%, 50%, 75%, and 95% in this embodiment) are extracted. Comparison with theoretical thresholds Compared with the measured load value A comprehensive assessment of the risk of iliac bone injury was completed on the tilted dummy.

[0057] The specific steps include: Using the aforementioned unified test conditions (frontal collision FRB / MPDB conditions, seat back tilt angle ≥35°, and THOR 50th dummy with improved tilt posture), the test was conducted. In each group of independent trolley crash tests, the X-axis load output from the iliac bone sensor on the side of the dummy where the force was greater was extracted. The total amount obtained is One-dimensional load sample set: S={ , ,…, Arrange all valid sample sets S in ascending order of loading values ​​to obtain an ordered sequence: ={ , ,…, }, where the subscript (1) represents the minimum load, ( () represents the maximum load.

[0058] Calculating arbitrary measured loads using empirical cumulative distribution functions Corresponding cumulative probability Calculation formula:

[0059] in, The measured iliac bone load data The value in the ascending sequence The position number in This reflects that the load on the iliac bone of the dummy under the current tilt seat product does not exceed The proportion of the test results. The output results are plotted as a cumulative distribution curve of the measured load, with the horizontal axis representing the load in the X-direction of the iliac crest. The vertical axis represents the cumulative probability, which intuitively reflects the overall distribution characteristics of the product load.

[0060] Based on the four preset engineering evaluation standard probability levels (25%, 50%, 75%, 95%) in S3, the corresponding measured loads are solved for each level. The gradation markers i=1, 2, 3, and 4 correspond to 25%, 50%, 75%, and 95% respectively: cumulative probability of the target. ∈{25%,50%,75%,95%}, inverse solution formula = Calculate the target ranking: = × ,like If is an integer, then the in the ordered sequence is... The displacement load is... ;like If the value is a decimal, then take the load from two adjacent quantiles and perform linear interpolation to obtain the accurate quantile load. Output four sets of measured quantile loads. , , , .

[0061] For auxiliary A comprehensive assessment combining theoretical and practical methods was conducted to evaluate the risk of iliac bone injury in dummy models using current tilt-and-seat products, applying the theoretical injury threshold of the same probability level output by S3. , , , Comparing with the measured quantile loads respectively , , , contrast, ≤ The measured load of the product at this quantile is far lower than the critical load with the same probability of damage, the risk of iliac bone injury is extremely low, and the existing seat restraint scheme meets the protection requirements. ≈ The measured load is close to the theoretical damage threshold, indicating a moderate probability of iliac bone injury. Slight optimization of the lumbar belt arrangement and seat tilt angle can reduce the stress on the iliac bone. At this quantile, a large number of test loads exceeded the corresponding injury probability threshold, indicating a high risk of iliac bone injury. It is necessary to optimize the seat belt guidance and pelvic support structure to reduce concentrated load on the iliac bone.

[0062] By combining the difference distribution of the four probability levels, a complete assessment conclusion is output: whether the high-risk interval (95th percentile) exceeds the standard represents the safety margin of the occupant's iliac crest under extreme collision conditions; the difference in the median (50th percentile) represents the average risk level under normal collision conditions; finally, an engineering reference benchmark combining the theoretical damage probability threshold and the actual measured load distribution of the product is formed, which is used for iterative optimization of large tilt angle seat restraint systems, calibration of threshold indicators for occupant collision safety assessment in the industry for tilt posture, and data support for safety regulations for semi-reclining sitting posture in intelligent cockpits.

[0063] The above descriptions are merely embodiments of the present invention, and common knowledge such as specific technical solutions and / or characteristics are not described in detail here. It should be noted that those skilled in the art can make various modifications and improvements without departing from the technical solutions of the present invention, and these should also be considered within the scope of protection of the present invention. These modifications and improvements will not affect the effectiveness of the implementation of the present invention or the practicality of the patent. The scope of protection claimed in this application should be determined by the content of its claims, and the specific embodiments described in the specification can be used to interpret the content of the claims.

Claims

1. A method for assessing the risk of iliac bone injury in a tilted dummy during a frontal collision, characterized in that, include: S1, acquire data from frontal collision tests and simulations of large-angle seat trolley crash tests using dummies, as well as calibration data from cadaver tests on real vehicles; S2. Based on the data obtained from the trolley collision test, the trolley collision simulation and the calibration data from the cadaver vehicle test, an iliac bone injury risk function with the iliac bone X-direction load as the independent variable was constructed respectively. S3. Draw the damage risk curve according to the damage risk function, extract the iliac bone load value corresponding to each curve according to the probability level, and calculate the theoretical threshold of iliac bone load corresponding to each probability level by means fusion. S4. Collect several measured X-axis loads on the iliac bone from collisions with tilted dummy trolleys, construct a cumulative probability distribution model of the measured loads, extract the measured load values ​​corresponding to the cumulative probabilities of each probability level, compare the theoretical threshold with the measured load values, and complete the comprehensive assessment of the iliac bone injury risk of the tilted dummy.

2. The method for assessing the risk of iliac bone injury in a frontal collision tilted dummy according to claim 1, characterized in that, S2 includes S21, which constructs the first damage risk function based on the data from the trolley test; S21 includes: S211, using the cadaveric iliac bone AIS2+ injury risk function as the baseline function: in, This represents the probability of AIS2+ injury in the iliac bone when the independent variable is F. This represents the triaxial composite load borne by the iliac crest in the human body. Represents the natural constant; S212, linear regression analysis was performed using the least squares method to establish... and Linear regression relationship: In the formula, The regression slope, The regression intercept; S213, based on industry standards and The mapping relationship in S212 and The mapping relationship was derived to obtain the X-axis load of the dummy iliac bone. Combined force with triaxial load The linear mapping relationship is as follows: In the formula and The values ​​are respectively and ; S214, X-axis load on the dummy's iliac bone Combined force with triaxial load Substituting the linear mapping relationship into the reference function, we obtain the X-axis load of the dummy iliac bone. The first damage risk function for the input indicators: 。 3. The method for assessing the risk of iliac bone injury in a tilted dummy in a frontal collision according to claim 2, characterized in that, S2 includes S22, which constructs a second damage risk function based on the trolley collision simulation data; S22 includes: S221, Conduct least squares linear regression analysis and establish... The linear mapping relationship is: , The regression constant; S222, will Substituting the linear mapping relationship into the reference function, the derivation of the X-axis load on the dummy iliac bone is obtained. The second damage risk function is the independent variable: 。 4. The method for assessing the risk of iliac bone injury in a tilted dummy in a frontal collision according to claim 1, characterized in that: S2 includes S23, which constructs a third injury risk function based on the calibration data from the cadaver vehicle test: The third injury risk function is obtained by fitting a survival analysis based on the Weibull distribution as follows: In the formula , It is a constant parameter.

5. The method for assessing the risk of iliac bone injury in a tilted dummy in a frontal collision according to claim 1, characterized in that: In S3, the theoretical threshold of iliac bone load corresponding to each damage probability. for: In the formula, i represents the damage probability level, and j represents the damage risk function. The value of the iliac bone X-axis load corresponding to the j-th risk curve under the i-th level of injury probability.

6. The method for assessing the risk of iliac bone injury in a tilted dummy in a frontal collision according to claim 1, characterized in that: In S4, the measured cumulative probability distribution model of the X-axis load on the iliac bone is as follows: in, To measure the total number of tilting dummy trolley crash tests, The measured iliac bone load data The position of the value in the ascending sequence. This indicates that the iliac bone load of the dummy under the current tilt seat product does not exceed The percentage of trials.

7. The method for assessing the risk of iliac bone injury in a tilted dummy in a frontal collision according to claim 1, characterized in that: The frontal collision conditions include two types: FRB and MPDB.

8. The method for assessing the risk of iliac bone injury in a tilted dummy in a frontal collision according to claim 1, characterized in that: The dummy in question is an improved THOR 50th dummy.

9. The method for assessing the risk of iliac bone injury in a frontal collision tilted dummy according to claim 1, characterized in that: The backrest angle of the large-angle seat is ≥35°.

Images