Passenger car sliding resistance fitting calculation method

Abstract

The invention discloses a passenger vehicle sliding resistance fitting calculation method. The method comprises the following steps that S1, a benchmarking vehicle is selected and determined; s3, testing dragging force of front and rear wheels under the balance weight based on the selected benchmarking vehicle; s4, a computer is adopted to analyze the windward area and the wind resistance coefficient of the research and development sample car, and the wind resistance F4 of the research and development sample car is calculated; and S5, based on the dragging force test result of the front and rear wheels in the step S3 and the wind resistance calculation result in the step S4, calculating to obtain a sliding resistance parameter of the vehicle to be researched and developed. The method has the advantages that the sliding resistance of the research and development sample vehicle is fitted by measuring the dragging force of the chassis transmission system of the competitive vehicle and simulating and calculating the wind resistance, the part target of the chassis transmission system of the research and development sample vehicle is decomposed, and the sliding resistance fitting precision before project approval is improved. The problem that the sliding resistance fitting calculation precision is poor before project approval is solved, and the fitting calculation method is simple and reliable.

Description

Technical Field

[0001] The invention relates to the field of automobile research and development simulation, and in particular to a sliding resistance fitting calculation method for a passenger car. Background Art

[0002] In automobile research and development, the simulation calculations of performance such as power, economy and thermal management all require sliding resistance. The accuracy of sliding resistance affects the accuracy of simulation calculations of power, economy and thermal management. The principle of sliding resistance is to test the driving resistance of the test vehicle on the actual road or in a wind tunnel. Before the project was established, there was no test vehicle, and it was impossible to get the accurate sliding resistance through actual measurement. It could only be estimated and calculated through tire rolling resistance, brake drag, vehicle width and height, and estimated wind resistance coefficient. The estimation method of the existing technology has a relatively large calculation error, which affects the simulation analysis accuracy of power economy and thermal management, and affects the development of vehicle models.

[0003] In the prior art, when estimating the sliding resistance parameters during the automobile development process, an empirical formula is generally used to fit the estimated sliding resistance, and the formula is generally F=A+C*V*V; wherein F in the formula is the sliding resistance, A and C are constants, and V is the vehicle speed. After the constant AC is obtained by combining the formula with the empirical parameters, the sliding resistance at different vehicle speeds can be estimated. However, since the sliding resistance calculated by this method is obtained based on the conversion of the empirical value, the error between the calculated sliding resistance and the measured value is generally more than 10%, which is a large error and affects the subsequent development and simulation verification of the vehicle model. Summary of the invention

[0004] The purpose of the present invention is to overcome the shortcomings of the prior art and provide a sliding resistance fitting calculation method for a passenger car, and provide a higher-precision sliding resistance fitting calculation method for a passenger car, which is suitable for fitting the sliding resistance in the absence of a test sample car during the vehicle model development stage.

[0005] In order to achieve the above object, the technical solution adopted by the present invention is: a sliding resistance fitting calculation method for a passenger car, comprising the following steps:

[0006] S1. Select and determine the benchmark vehicle;

[0007] S3. Conduct front and rear wheel drag force test based on the selected benchmark vehicle under counterweight;

[0008] S4. Use computer to analyze the windward area and drag coefficient of the R&D prototype vehicle and calculate the wind resistance F4 of the R&D prototype vehicle;

[0009] S5. Based on the front and rear wheel drag force test results of step S3 and the wind resistance calculation results of step S4, the sliding resistance parameters of the vehicle to be developed are calculated.

[0010] In step S1, a competing vehicle model of the vehicle to be developed is determined based on basic information of the vehicle to be developed, and a competing vehicle against the vehicle to be developed is selected as a benchmark vehicle.

[0011] Step S3 includes front wheel drag force test and rear wheel drag force test steps, which are used to respectively test and obtain the front wheel drag force fitting formula F1 and the rear wheel drag force fitting formula F2; based on the addition of the front and rear wheel drag force fitting formulas F1 and F2, the drag force F3 of the benchmark vehicle under different test masses is obtained.

[0012] The calculation formula for the sliding resistance of the vehicle to be developed is F5=F3+F4.

[0013] The front wheel drag force test steps include:

[0014] (1) Place the front wheel of the benchmark vehicle on the drum to set the vehicle speed preheating setting time threshold T1;

[0015] (2) Load the benchmark vehicle with different test masses, place the front wheel of the benchmark vehicle on a drum, and drive the vehicle at a uniform speed at multiple speed points to set a threshold time T2, and record the drum drag force after the vehicle speed stabilizes at multiple speed points;

[0016] (3) Repeat step (2) multiple times to obtain the vehicle speed and the corresponding drum drag force;

[0017] (4) Using the test data obtained in step (3) to fit the front wheel drag force with a quadratic function, a relationship formula for the front wheel drag force is obtained: F1=A1+B1*V+C1*V*V; wherein F1 is the front wheel drag force, A1, B1, and C1 are constants, and V is the vehicle speed.

[0018] The rear wheel drag test steps include:

[0019] 1) Place the rear wheel of the benchmark vehicle on the drum to set the vehicle speed preheating setting time threshold T11;

[0020] 2) Load the benchmark vehicle with different test masses, place the rear wheels of the benchmark vehicle on a drum, drive the vehicle at a uniform speed at multiple speed points, set a threshold time T22, and record the drum drag force after the vehicle speed stabilizes at multiple speed points;

[0021] 3) Repeat step 2) multiple times to obtain the vehicle speed and the corresponding drum drag force;

[0022] 4) Using the test data obtained in step 3), a quadratic function is fitted to the rear wheel drag force to obtain the relationship formula of the front wheel drag force F2=A2+B2*V+C2*V*V; wherein F2 is the rear wheel drag force, A2, B2, C2 are constants, and V is the vehicle speed.

[0023] In the front wheel drag force test or the rear wheel drag force test, the drum drag force corresponding to the vehicle speed obtained by the test is checked to determine whether the recorded data error meets the requirements. If the error meets the requirements, the recorded data is used to fit the corresponding front wheel drag force F1 or rear wheel drag force F2; otherwise, the drum drag force is retested or the number of tests in step (3) or 3) is increased to obtain new test data for fitting.

[0024] Verification of the drum drag force corresponding to the vehicle speed obtained by the test includes:

[0025] For the front wheel drag force data verification, first calculate the average drag force X of the front wheel at each vehicle speed, and then calculate the standard deviation of the drag force

[0026] Then use the average error to estimate the accuracy P, where the calculation formula of accuracy P is:

[0027]

[0028] Where n is the number of tests in step (3); if the accuracy P is less than the set threshold, the test data is judged to be qualified, and the front wheel drag force F1 is fitted based on the test data; otherwise, it is judged that the verification fails.

[0029] For the rear wheel drag force data verification, first calculate the average drag force of the rear wheel at each vehicle speed, and then calculate the standard deviation of the drag force; then use the average error to estimate the accuracy. If the accuracy is less than the set threshold, the test data is judged to be qualified, and the rear wheel drag force F2 is fitted based on the test data; otherwise, it is judged that the verification fails.

[0030] In step S4, a computer is used to simulate and analyze the R&D prototype model, and the frontal area D and the drag coefficient E are calculated, and the wind resistance F4 is fitted to be F4=D*E*V*V / 21.15.

[0031] The benchmark vehicle is tested and the transmission angle, tire rolling resistance coefficient and brake drag force of the benchmark vehicle under different test masses are recorded. The target values ​​of the tire rolling resistance coefficient, brake drag force and transmission shaft angle of the vehicle to be developed are smaller than the test values ​​of the benchmark vehicle.

[0032] The advantages of the present invention are: by measuring the drag force of the chassis transmission system of the competitor car and simulating the wind resistance to fit the sliding resistance of the R&D prototype car, the component targets of the chassis transmission system of the R&D prototype car are decomposed, and the sliding resistance fitting accuracy before the project is approved is improved. The present invention solves the problem of poor sliding resistance fitting calculation accuracy before the project is approved, and the fitting calculation method is simple and reliable. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] The following is a brief description of the contents expressed in the drawings of the present invention and the symbols in the drawings:

[0034] Figure 1 A flow chart of a calculation method for improving the sliding resistance fitting accuracy of a passenger car according to an embodiment of the present invention;

[0035] Figure 2 The following is a calculation process of the drag force of the chassis of a passenger car according to an embodiment of the present invention;

[0036] Figure 3 The present invention implements the passenger car wind resistance calculation process. DETAILED DESCRIPTION

[0037] The specific implementation of the present invention will be further explained in detail below by describing the optimal embodiment with reference to the accompanying drawings.

[0038] In the vehicle development stage, since there is no actual vehicle as an experimental prototype, it is impossible to obtain the accurate sliding resistance of the vehicle to be developed through testing. In the absence of sliding resistance, many early development tests and simulations of the whole vehicle will be affected. Therefore, in order to meet the accurate calculation of sliding resistance in the absence of a test vehicle in the development stage, the present application provides an accurate estimation method for estimating the sliding resistance of the development vehicle in the automobile development stage before the physical test prototype is developed. The scheme is as follows: Figure 1-3 As shown, the detailed steps of the estimation calculation method are described as follows:

[0039] like Figure 1-3 As shown, a sliding resistance fitting calculation method for a passenger car in the R&D stage without a physical test sample includes the following steps:

[0040] S1. Select and determine the benchmark vehicle;

[0041] S3. Conduct front and rear wheel drag force test based on the selected benchmark vehicle under counterweight;

[0042] S4. Use computer to analyze the windward area and drag coefficient of the R&D prototype vehicle and calculate the wind resistance F4 of the R&D prototype vehicle;

[0043] S5. Based on the front and rear wheel drag force test results of step S3 and the wind resistance calculation results of step S4, the sliding resistance parameters of the vehicle to be developed are calculated.

[0044] In step S1, the competitive vehicle model of the R&D vehicle is determined based on the basic information of the vehicle to be developed, and the competitive vehicle benchmarked against the R&D vehicle is selected as the benchmark vehicle. Because there is no test sample vehicle in the R&D stage, in order to accurately obtain the sliding resistance of the R&D vehicle, it is necessary to select some competitive vehicles that can characterize the R&D vehicle as benchmark vehicles, because many car models have benchmark models, such as A-class sedans, small SUVs, etc., according to the vehicle benchmarking competitive vehicle model, select a competitive vehicle model as a benchmark vehicle for subsequent sliding resistance estimation test to reliably obtain sliding resistance data.

[0045] This solution is mainly based on the selected competitive models to test and obtain the sliding resistance parameters of the R&D vehicle, so it is necessary to test the benchmark vehicle; first, test the benchmark vehicle and record the transmission angle, tire rolling resistance coefficient and brake drag force of the benchmark vehicle under different test qualities, and set the target values ​​of the tire rolling resistance coefficient, brake drag force and transmission shaft angle of the R&D vehicle to be less than or equal to the test values ​​of the benchmark vehicle, so as to obtain the target values ​​of the tire rolling resistance coefficient, brake drag force and transmission shaft angle of the R&D vehicle. The different test qualities here include the test quality values ​​under at least three conditions, such as the curb weight of the R&D prototype, the National VI test weight and the fully loaded weight target value.

[0046] Step S3 includes front wheel drag force test and rear wheel drag force test steps, which are used to test and obtain the front wheel drag force fitting formula F1 and the rear wheel drag force fitting formula F2 respectively; the drag force F3 of the benchmark vehicle under different test masses is obtained by adding the front and rear wheel drag force fitting formulas F1 and F2. The sliding resistance calculation formula of the R&D vehicle is F5=F3+F4, where F3 is the sum of F1 and F2, and F4 is the wind resistance of the R&D prototype simulated by the computer;

[0047] The front wheel drag force test steps include:

[0048] (1) Place the front wheel of the benchmark vehicle on the drum to set the vehicle speed preheating setting time threshold T1; the vehicle speed is generally set at about 100 km / h and the time threshold T1 is about 40 minutes;

[0049] (2) Load different test masses on the benchmark vehicle, place the front wheel of the benchmark vehicle on the drum, set the threshold time T2 at multiple speed points with a uniform speed, and record the drum drag force after the vehicle speed stabilizes at multiple speed points; the different test masses here include the test mass values ​​under at least three conditions, such as the curb weight of the R&D prototype, the National VI test mass, and the full-load mass target value. The multiple speed points include 130km / h, 120km / h, 110km / h...10km / h, etc. The preset time T2 is generally about 60S.

[0050] (3) Repeat step (2) multiple times to obtain the vehicle speed and the corresponding drum drag force; the number of repetitions can be based on actual needs. The more repetitions, the more measured data, and the more accurate the subsequent curve fitting.

[0051] (4) Using the test data obtained in step (3) to fit the front wheel drag force with a quadratic function, a relationship formula for the front wheel drag force is obtained: F1=A1+B1*V+C1*V*V; wherein F1 is the front wheel drag force, A1, B1, and C1 are constants, and V is the vehicle speed.

[0052] Similarly, the rear wheel drag force test steps are the same as the front wheel, specifically the rear wheel drag force test steps include:

[0053] 1) Place the rear wheel of the benchmark vehicle on the drum to set the vehicle speed preheating setting time threshold T11; the vehicle speed is generally set at around 100KM / h, and the time threshold T11 is around 40 minutes;

[0054] 2) Load different test masses on the benchmark vehicle, place the rear wheel of the benchmark vehicle on the drum, set the threshold time T22 at multiple speed points with a uniform speed, and record the drum drag force after the vehicle speed stabilizes at multiple speed points; the different test masses here include the test mass values ​​under at least three conditions, such as the curb weight of the R&D prototype, the National VI test mass and the fully loaded mass target value. Multiple speed points include 130km / h, 120km / h, 110km / h...10km / h, etc. The preset time T21 is generally about 60S.

[0055] 3) Repeat step 2) multiple times to obtain the vehicle speed and the corresponding drum drag force; the number of repetitions can be based on actual needs. The more repetitions, the more measured data, and the more accurate the subsequent curve fitting.

[0056] 4) Using the test data obtained in step 3), a quadratic function is fitted to the rear wheel drag force to obtain the relationship formula of the front wheel drag force F2=A2+B2*V+C2*V*V; wherein F2 is the rear wheel drag force, A2, B2, C2 are constants, and V is the vehicle speed.

[0057] In the front wheel drag force test or the rear wheel drag force test, the drum drag force corresponding to the vehicle speed obtained by the test is checked to determine whether the recorded data error meets the requirements. If the error meets the requirements, the recorded data is used to fit the corresponding front wheel drag force F1 or rear wheel drag force F2; otherwise, the drum drag force is retested or the number of tests in step (3) or 3) is increased to obtain new test data for fitting.

[0058] Verification of the drum drag force corresponding to the vehicle speed obtained by the test includes:

[0059] For the front wheel drag force data verification, first calculate the average drag force X of the front wheel at each vehicle speed, and then calculate the standard deviation of the drag force

[0060] Then use the average error to estimate the accuracy P, where the calculation formula of accuracy P is:

[0061]

[0062] Where n is the number of tests in step (3); if the accuracy P is less than the set threshold, the test data is judged to be qualified, and the front wheel drag force F1 is fitted based on the test data; otherwise, it is judged to be unqualified. The accuracy threshold is set to 0.03. If the accuracy P≤0.03, the data is qualified, otherwise the data is unqualified, and the test is repeated or the amount of test data is increased according to the test steps, thereby reducing errors and providing more accurate data for subsequent fitting.

[0063] Similarly, the rear wheel drag data also needs to be verified, and its verification steps are the same as those for the front wheel data verification, that is, for the rear wheel drag data verification, first calculate the average drag of the rear wheel at each vehicle speed, and then calculate the standard deviation of the drag; then use the average error to estimate the accuracy. If the accuracy is less than the set threshold, the test data is judged to be qualified, and the rear wheel drag F2 is fitted based on the test data; otherwise, it is judged to be unqualified.

[0064] In step S4, a computer is used to simulate and analyze the R&D prototype model, and the frontal area D and the drag coefficient E are calculated, and the wind resistance F4 is fitted to be F4=D*E*V*V / 21.15.

[0065] The sliding resistance of the R&D prototype is F5 = F3 + F4 = A3 + B3 * V + (C3 + D * E / 21.15) * V * V. Among them, A3, B3 and C3 are constants, the frontal area D and the drag coefficient E, and the vehicle speed is V.

[0066] The following is a calculation method for the sliding resistance fitting accuracy of a passenger car with specific test parameters, which specifically includes the following steps:

[0067] ① Test and record the transmission angle, tire rolling resistance coefficient and brake drag force of the benchmark vehicle at different test masses (equal to the curb weight of the R&D prototype, the National VI test mass and the fully loaded mass target value);

[0068] ② The front wheels of the benchmark vehicle are preheated on the drum at a speed of 100 km / h for 40 minutes;

[0069] ③ The benchmark vehicle is loaded with different test masses (see step ①, equal to the curb weight of the R&D prototype vehicle, the National VI test mass and the fully loaded mass target value). The front wheels of the benchmark vehicle run on the drum at various uniform speeds (130km / h, 120km / h, 110km / h...10km / h) for 60S, and the drum drag force is recorded after the speed stabilizes;

[0070] ④ Carry out 6 tests according to test steps ③;

[0071] ⑤ Calculate the average drag force X of the front wheels at each speed, and then calculate the standard deviation using the following formula:

[0072]

[0073] Then use the average error to estimate the accuracy:

[0074]

[0075] If the accuracy P≤0.03, the 6 sets of data are qualified, otherwise, increase the measured data according to the test step ③, and then perform the accuracy calculation until the accuracy is ≤0.03. The qualified test data is finally fitted with a quadratic function for the front wheel drag force, and the front wheel drag force F1=A1+B1*V+C1*V*V (F1 is the front wheel drag force, A1, B1 and C1 are constants, and V is the vehicle speed). The meaning of each letter in the formula is:

[0076] n----Test step ③Test times;

[0077] ---Standard deviation;

[0078] P----Average error estimation accuracy.

[0079] ⑥ The rear wheels of the benchmark vehicle are preheated on the drum at a speed of 100 km / h for 40 minutes;

[0080] ⑦ The benchmark vehicle is loaded with different test masses (see step ①), and the rear wheels of the benchmark vehicle are on the drum. The vehicle is driven at various uniform speeds (130km / h, 120km / h, 110km / h...10km / h) for 60 seconds, and the drum drag force is recorded after the vehicle speed stabilizes;

[0081] ⑧ Carry out 6 tests according to test step ⑦;

[0082] ⑨ Calculate the rear wheel drag force according to the method in test step ⑤: rear wheel drag force F2 = A2 + B2*V + C2*V*V (F2 is the rear wheel drag force, A2, B2 and C2 are constants, and V is the vehicle speed);

[0083] ⑩ The drag force of the benchmark vehicle with different test masses is F3=F1+F2=A3+B3*V+C3*V*V (F3 is the drag force of the benchmark vehicle chassis, A3, B3 and C3 are constants, and V is the vehicle speed);

[0084] Use a computer to simulate and analyze the R&D prototype model, calculate the frontal area D and the drag coefficient E, and then calculate the wind resistance F4 = D*E*V*V / 21.15;

[0085] The target values ​​of the tire rolling resistance coefficient, brake drag force and drive shaft angle of the R&D test vehicle are ≤ the benchmark vehicle test values. The sliding resistance of the R&D prototype vehicle is as follows: F5=F3+F4=A3+B3*V+(C3+D*E / 21.15)*V*V.

[0086] The present invention is a calculation method for improving the sliding resistance fitting accuracy of a passenger car in the R&D stage without a test prototype. The sliding resistance of the R&D prototype is fitted by measuring the drag force of the chassis transmission system of a competitor car and simulating and calculating the wind resistance, decomposing the component targets of the chassis transmission system of the R&D prototype car, and improving the sliding resistance fitting accuracy before the project is approved. The present invention solves the problem of poor sliding resistance fitting calculation accuracy before the project is approved. It has the following characteristics:

[0087] 1. The sliding resistance of the R&D prototype vehicle is fitted by measuring the drag force of the chassis transmission system of the competitor vehicle and calculating the wind resistance based on the vehicle model simulation by computer;

[0088] 2. Measure the chassis drag force of the competitor's car, load different test masses, measure the drag force at each uniform speed for 6 times in a row, calculate the standard deviation and average error precision, if the average error precision is ≤3%, the test data is qualified, otherwise measure the drag force at each average speed multiple times;

[0089] 3. Wind resistance fitting: the computer simulates the windward area and drag coefficient of the vehicle based on the vehicle model, and then calculates the wind resistance of the vehicle based on automobile theory.

[0090] Obviously, the specific implementation of the present invention is not limited to the above-mentioned methods. As long as various non-substantial improvements are made using the method concept and technical solution of the present invention, they are all within the protection scope of the present invention.

Claims

1. A sliding resistance fitting calculation method for a passenger car, characterized in that: The steps include: S1. Select and determine the benchmark vehicle; S3. Conduct front and rear wheel drag force test based on the selected benchmark vehicle under counterweight; S4. Use computer to analyze the windward area and drag coefficient of the R&D prototype vehicle and calculate the wind resistance F4 of the R&D prototype vehicle; S5. Based on the front and rear wheel drag force test results of step S3 and the wind resistance calculation results of step S4, the sliding resistance parameters of the vehicle to be developed are calculated.

2. A passenger car sliding resistance fitting calculation method as claimed in claim 1, characterized in that: In step S1, a competing vehicle model of the vehicle to be developed is determined based on basic information of the vehicle to be developed, and a competing vehicle against the vehicle to be developed is selected as a benchmark vehicle.

3. A passenger car sliding resistance fitting calculation method as claimed in claim 1, characterized in that: Step S3 includes front wheel drag force test and rear wheel drag force test steps, which are used to test and obtain the front wheel drag force fitting formula F1 and the rear wheel drag force fitting formula F2 respectively; The drag force F3 of the benchmark vehicle under different test masses is obtained by adding the front and rear wheel drag force fitting formulas F1 and F2.

4. A passenger car sliding resistance fitting calculation method as claimed in claim 3, characterized in that: The calculation formula for the sliding resistance of the vehicle to be developed is F5=F3+F4.

5. A passenger car sliding resistance fitting calculation method as claimed in any one of claim 3, characterized in that: The front wheel drag force test steps include: (1) Place the front wheel of the benchmark vehicle on the drum to set the vehicle speed preheating setting time threshold T1; (2) Load the benchmark vehicle with different test masses, place the front wheel of the benchmark vehicle on a drum, and drive the vehicle at a uniform speed at multiple speed points to set a threshold time T2, and record the drum drag force after the vehicle speed stabilizes at multiple speed points; (3) Repeat step (2) multiple times to obtain the vehicle speed and the corresponding drum drag force; (4) Using the test data obtained in step (3) to fit the front wheel drag force with a quadratic function, a relationship formula for the front wheel drag force is obtained: F1=A1+B1*V+C1*V*V; wherein F1 is the front wheel drag force, A1, B1, and C1 are constants, and V is the vehicle speed.

6. A passenger car sliding resistance fitting calculation method as claimed in any one of claim 3, characterized in that: The rear wheel drag test steps include: 1) Place the rear wheel of the benchmark vehicle on the drum to set the vehicle speed preheating setting time threshold T11; 2) Load the benchmark vehicle with different test masses, place the rear wheels of the benchmark vehicle on a drum, drive the vehicle at a uniform speed at multiple speed points, set a threshold time T22, and record the drum drag force after the vehicle speed stabilizes at multiple speed points; 3) Repeat step 2) multiple times to obtain the vehicle speed and the corresponding drum drag force; 4) Using the test data obtained in step 3), a quadratic function is fitted to the rear wheel drag force to obtain the relationship formula of the front wheel drag force F2=A2+B2*V+C2*V*V; wherein F2 is the rear wheel drag force, A2, B2, C2 are constants, and V is the vehicle speed.

7. A passenger car sliding resistance fitting calculation method as claimed in claim 5 or 6, characterized in that: In the front wheel drag force test or the rear wheel drag force test, the drum drag force corresponding to the vehicle speed obtained by the test is verified to determine whether the recorded data error meets the requirements. If the error meets the requirements, the recorded data is used to fit the corresponding front wheel drag force F1 or rear wheel drag force F2; Otherwise, retest the drum drag force or increase the number of tests in step (3) or 3) to obtain new test data for fitting.

8. A passenger car sliding resistance fitting calculation method as claimed in claim 7, characterized in that: Verification of the drum drag force corresponding to the vehicle speed obtained by the test includes: For the front wheel drag force data verification, first calculate the average drag force X of the front wheel at each vehicle speed, and then calculate the standard deviation of the drag force Then use the average error to estimate the accuracy P, where the calculation formula of accuracy P is: Where n is the number of tests in step (3); if the accuracy P is less than the set threshold, the test data is judged to be qualified, and the front wheel drag force F1 is fitted based on the test data; otherwise, it is judged that the verification fails. For the rear wheel drag force data verification, first calculate the average drag force of the rear wheel at each vehicle speed, and then calculate the standard deviation of the drag force; then use the average error to estimate the accuracy. If the accuracy is less than the set threshold, the test data is judged to be qualified, and the rear wheel drag force F2 is fitted based on the test data; otherwise, it is judged that the verification fails.

9. A passenger car sliding resistance fitting calculation method according to any one of claims 1 to 8, characterized in that: In step S4, a computer is used to simulate and analyze the R&D prototype model, and the frontal area D and the drag coefficient E are calculated, and the wind resistance F4 is fitted to be F4=D*E*V*V / 21.

15.

10. A passenger car sliding resistance fitting calculation method according to any one of claims 1 to 8, characterized in that: The benchmark vehicle is tested and the transmission angle, tire rolling resistance coefficient and brake drag force of the benchmark vehicle under different test masses are recorded. The target values ​​of the tire rolling resistance coefficient, brake drag force and transmission shaft angle of the vehicle to be developed are smaller than the test values ​​of the benchmark vehicle.

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