Method for detecting and testing performance of cooling system for reverse development of benchmarking sample car

Abstract

The invention discloses a benchmarking sample vehicle reverse development cooling system performance detection test method, and belongs to the technical field of automobile cooling system performance. The method comprises the following steps: driving a benchmarking sample vehicle into a drum test bed and fixing the benchmarking sample vehicle, performing upshift and downshift operation under a full-accelerator extreme working condition, acquiring speed point data, optimizing working condition points by utilizing a working condition screening algorithm based on normal distribution, acquiring thermal parameters of a transmission under a selected working condition, and calculating thermal power by utilizing a non-equilibrium heat transfer correction model. And finally, reverse development comparison is completed. The core innovation of the method is to solve the problems of lack of scientific basis of working condition point selection and insufficient precision of unbalanced calorific value measurement and calculation in the prior art, and by constructing a complete reverse development test system, the thermal load parameter extraction precision is significantly improved, the heat dissipation system matching period is shortened, and the heat dissipation efficiency is improved. And a key technical support is provided for rapid adaptive development of the automatic transmission.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of automobile cooling system performance, and particularly relates to a test method for detecting and testing the performance of a cooling system developed reversely based on a sample vehicle. BACKGROUND

[0002] With the development of the automobile industry, automatic transmissions have become the mainstream configuration of passenger vehicles, and the thermal management performance thereof directly affects the driving comfort, fuel economy and system reliability of the vehicle; in the forward development process of the automatic transmission, the design of the heat dissipation system faces a core contradiction: too high heat dissipation power will cause the transmission to be in a low-temperature working state for a long time under the cold start working condition, thereby causing problems such as transmission efficiency reduction, shift characteristic deterioration and lubricating oil viscosity abnormality; and insufficient heat dissipation power is prone to trigger thermal protection under high-temperature working conditions, and in extreme cases, may cause irreversible damage such as clutch plate ablation or sealing element failure; when lacking target vehicle thermal load benchmark data, the current industry usually adopts reverse development means based on a benchmark vehicle.

[0003] However, the prior art has two technical bottlenecks:

[0004] (1) The selection of key measurement working points lacks scientific basis, resulting in insufficient data representativeness;

[0005] (2) The decoupling calculation precision of heat generation and heat dissipation under a non-equilibrium state is insufficient,

[0006] mainly due to: ① the temperature response lag caused by the heat capacity effect of the transmission, ② the coupling interference of mechanical loss heat and hydraulic loss heat, and ③ the nonlinear heat exchange characteristics of the heat dissipation system.

[0007] Although the existing test standard (such as SAE J2683) specifies the basic thermal performance test method, it does not solve the problem of decoupling the heat flow parameters of the transmission under extreme working conditions, and some enterprises use CFD simulation to assist in design, but the accuracy thereof is seriously dependent on the quality of the measured data of the boundary conditions. SUMMARY

[0008] To solve the problems in the background art, the application provides a test method for detecting and testing the performance of a cooling system developed reversely based on a sample vehicle, the test method establishes a transmission classic static common working condition screening algorithm, develops a transmission heat generation measurement and calculation method under a non-equilibrium state of a vehicle under extreme working conditions, and constructs a heat transfer correction model under a non-equilibrium state, thereby forming a complete reverse development test system; the application can significantly improve the extraction precision of thermal load parameters, shorten the matching cycle of the heat dissipation system, and provide key technical support for the rapid adaptive development of the automatic transmission.

[0009] To achieve the above-mentioned purpose, the application adopts the following technical solution: a test method for detecting and testing the performance of a cooling system developed reversely based on a sample vehicle, the test method comprising the following steps:

[0010] S1: drive the sample vehicle into the drum test bench, use high-strength safety restraint device to stabilize the vehicle body, ensure that the vehicle remains fixed in extreme working conditions, at the same time, complete the precise connection and debugging of the test sensor, data acquisition system and communication wire harness, and ensure the stable operation of the equipment;

[0011] S2: according to the test working condition standard set by the application, drive the test vehicle to operate the upshift and downshift in the full throttle extreme working condition, in this process, use high-precision data acquisition equipment to collect the speed point data corresponding to the upshift and downshift time;

[0012] S3: record the test results;

[0013] S4: using the working condition screening algorithm based on normal distribution designed by the application, the initial data collected is analyzed, through data filtering and optimization processing, reasonable working condition points meeting the research requirements are screened out, and accurate working condition basis is provided for the next stage test;

[0014] S5: under the selected working condition point, the whole vehicle extreme working condition driving test is carried out, the transmission oil outlet temperature, oil pan temperature, transmission oil average flow and temperature rise time core thermal parameters are collected in real time and high precision, and the thermal performance data of the transmission in extreme working condition is comprehensively obtained;

[0015] S6: record the test results;

[0016] S7: thermal power calculation and analysis: based on the collected test data, using the non-equilibrium heat transfer correction model, the temperature rise power of the hydraulic torque converter, the temperature rise power of the transmission oil, the cooling power of the hydraulic torque converter and the total heat power key parameters are accurately calculated, the calculation results are corrected by the non-equilibrium heat transfer correction model, the peak heat power of the transmission is finally determined, and the heat dissipation power is compared and analyzed systematically, and the performance of the transmission thermal management system is evaluated;

[0017] S8: complete the reverse development comparison, and provide a scientific basis for product optimization design.

[0018] The working condition screening algorithm uses the normal distribution frequency statistical method in statistics, and selects the speed point with the highest frequency in the normal distribution as the reasonable working condition point.

[0019] The thermal power calculation is carried out by the formula , wherein m is the mass of the object, Cp is the specific heat capacity, ΔT is the temperature rise, and Δt is the temperature rise time.

[0020] Compared with the prior art, the application has the following beneficial effects:

[0021] 1. Improve the accuracy of thermal load parameter extraction: By using a normal distribution-based operating condition screening algorithm, representative operating condition points are scientifically selected, solving the problem of lack of scientific basis for operating condition point selection in existing technologies, making the collected data more reflective of the thermal load characteristics under actual operating conditions; a non-equilibrium heat transfer correction model is constructed, and the theoretical derivation and experimental data are cross-validated to make up for the shortcomings of traditional steady-state calculation methods, realize the accurate quantification of the non-steady-state heating process of the transmission, and solve the technical bottleneck of insufficient accuracy in decoupling the calculation of heat generation and heat dissipation under non-equilibrium conditions.

[0022] 2. Shorten the matching cycle of the heat dissipation system: Establish a full-process reverse development system covering test design, data acquisition, model building and result verification, improve testing efficiency and data quality, provide key technical support for the rapid adaptation and development of automatic transmissions, and reduce the number of design iterations caused by thermal management performance issues.

[0023] 3. Improve the reverse engineering testing system: Establish a complete reverse engineering testing method, including the classic static common working condition screening algorithm for transmissions, and the method for measuring and calculating the heat generation of transmissions under unbalanced conditions in extreme vehicle conditions, so as to provide the industry with standardized testing solutions when there is a lack of thermal load benchmark data for target models.

[0024] 4. Enhance the scientific nature of system performance evaluation: By accurately calculating key parameters such as the power rise of the hydraulic torque converter and the power rise of the transmission oil, and comparing and analyzing them with the power of the radiator, the performance of the transmission thermal management system is systematically evaluated, providing a scientific basis for product optimization design. Detailed Implementation

[0025] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the invention, and not all of the embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0026] This embodiment describes a performance testing method for a cooling system reverse-engineered from a benchmark vehicle, the testing method comprising the following steps:

[0027] S1: Drive the benchmark vehicle into the drum test bench and use a high-strength safety restraint device to stabilize the vehicle body (such as a four-point hydraulic fixing bracket) to ensure that the vehicle remains fixed under extreme working conditions. At the same time, complete the precise connection and debugging of the test sensors, data acquisition system and communication harness to ensure stable equipment operation.

[0028] S2: According to the test working condition standard set by the application, the driver tests the vehicle under full throttle extreme working condition, and in this process, high-precision data acquisition equipment is used to collect the speed points corresponding to the upshift and downshift time points;

[0029] S3: Record the test results;

[0030] S4: The initial data collected is analyzed by using the working condition screening algorithm based on normal distribution designed by the application, (such as taking the mean μ as the core working condition point, combining the data distribution density in the interval [μ-σ, μ+σ], selecting the speed point with the highest frequency, (for example, the mean of the 100 sampling data of D12 upshift is 14.0 kph, and the standard deviation is 1.2 kph, and the frequency of 14.0 kph in the interval 12.8-15.2 kph is the highest) through data filtering and optimization processing, the reasonable working condition point meeting the research requirements is screened out, and the accurate working condition basis for the next stage test is provided;

[0031] S5: Under the selected working condition point, the vehicle extreme working condition driving test is carried out, and the transmission oil outlet temperature, oil pan temperature, transmission oil average flow and core thermal parameters such as temperature rise time are collected in real time and high precision (the data collection accuracy meets the thermal performance test requirements in SAE J2683, the sampling frequency is not less than 10 Hz (to meet the transient working condition data capture requirement), the temperature sensor is preferably PT100 platinum resistance (accuracy ±0.5℃), and the flow sensor is electromagnetic (accuracy ±1.5%FS)), and the thermal performance data of the transmission under extreme working condition is comprehensively obtained;

[0032] S6: Record the test results;

[0033] S7: Thermal power calculation and analysis: based on the collected test data, a non-equilibrium heat transfer correction model is used to accurately calculate the hydraulic torque converter temperature rise power, transmission oil temperature rise power, hydraulic torque converter cooling power and total heat power key parameters, and the correction model is used to correct the calculation results, finally determine the peak heat power of the transmission, and compare and analyze the heat dissipation power, and evaluate the performance of the transmission thermal management system;

[0034] S8: Complete reverse development comparison, and provide scientific basis for product optimization design.

[0035] The working condition screening algorithm adopts a normal distribution frequency statistical method in statistics, and selects a speed point with the highest frequency of occurrence in the normal distribution as a reasonable working condition point. (such as determining the peak speed point by calculating the frequency density function f(v)=(1 / σ√2π) e^(-(v-μ)² / 2σ²), and based on at least 50 full throttle upshift test data, wherein σ is the standard deviation of the speed data set, e is the natural constant, v is the speed variable, and μ is the mean value of the speed data set)

[0036] The heat power calculation is performed by the formula , wherein m is the mass of the object, Cp is the specific heat capacity, ΔT is the temperature rise, and Δt is the temperature rise time.

[0037] In the field of transmission thermal performance testing and analysis, there is currently a lack of authoritative and universal reference standards. This situation leads to a lack of scientific and rigorous theoretical system and data support in the selection of key measurement working condition points, so that each unit relies on historical experience or subjective judgment in the working condition setting process. This non-standardized operation mode makes it difficult for the collected data to fully and accurately present the thermal load characteristics of the vehicle in the actual use scenario.

[0038] To solve the above problems, the application executes upshift and downshift operations under full throttle working condition by driving test vehicles, and uses high-precision data acquisition equipment to systematically collect speed points corresponding to upshift and downshift times. Then, a statistical method is used to select the speed point with the highest frequency of occurrence in the normal distribution, which is determined as the vehicle speed working condition point for the next transmission thermal performance test. This method effectively improves the scientificity and representativeness of the working condition point selection, and ensures that the test results can truly reflect the thermal performance of the transmission under actual working conditions.

[0039] The specific test data is shown in Table 1 and Table 2, which completely records the speed point data of each gear corresponding to the upshift and downshift processes under full throttle working condition.

[0040] Table 1: Speed points of each gear during upshift under full throttle working condition

[0041]

[0042] Table 2: Speed points of each gear during downshift under full throttle working condition

[0043]

[0044] Table 3 and Table 4 show the speed working condition points of each gear with the highest frequency of occurrence in the normal distribution algorithm as the speed working condition points for the next transmission thermal performance test.

[0045] Table three: Transmission thermal performance test full throttle extreme condition upshift each gear speed point

[0046]

[0047] Table four: Transmission thermal performance test full throttle extreme condition downshift each gear speed point

[0048]

[0049] The thermal performance test under full throttle extreme condition is carried out under the gear speed condition point of each gear in the above table three and table four, the core thermal parameters such as transmission oil outlet temperature, oil sump temperature, transmission oil average flow and temperature rise time are collected in real time and high precision, after the data record is completed, the formula can be used to calculate the heat power of the torque converter, the heat power of the automatic transmission oil (ATF), the cooling power of the torque converter, the heat power of the clutch and the total heat power of the torque converter:

[0050]

[0051] m: mass of the object (kg)

[0052] Cp: specific heat capacity (J / (kg·K))

[0053] ΔT: temperature rise (K / ℃)

[0054] Δt: temperature rise time (s)

[0055] The heat power of the torque converter can be calculated , the heat power of the automatic transmission oil (ATF) , the cooling power of the torque converter , the heat power of the clutch , and the total heat power of the torque converter:

[0056]

[0057] Total heat power:

[0058]

[0059] It is apparent to those skilled in the art that the present application is not limited to the details of the foregoing exemplary embodiments, and that the present application can be implemented in other particular forms without departing from the spirit or essential characteristics of the present application. Therefore, the embodiments should be considered in all respects as illustrative and not restrictive, the scope of the present application being defined by the appended claims rather than the foregoing description, and all changes which come within the meaning and range of equivalents of the claims are intended to be embraced therein.

Claims

1. A method for performance testing of a cooling system developed through reverse engineering of a benchmark vehicle, characterized in that, The test method comprises the following steps: S1: drive the sample vehicle into the drum test bench, use high-strength safety restraint devices to stabilize the vehicle body, ensure that the vehicle remains fixed in extreme working conditions, at the same time, complete the precise connection and debugging of the test sensor, data acquisition system and communication wire harness, and ensure stable operation of the equipment; S2: according to the test condition standard set by the application, drive the test vehicle to operate the upshift and downshift in the full throttle extreme working condition, in this process, use high-precision data acquisition equipment to collect the speed point data corresponding to the upshift and downshift time; S3: record the test results; S4: use the working condition screening algorithm based on normal distribution designed by the application to analyze the collected initial data, filter and optimize the data, and screen out reasonable working condition points meeting the research requirements, to provide accurate working condition basis for the next stage test; S5: under the selected working condition point, conduct the extreme working condition driving test of the whole vehicle, simultaneously collect the transmission oil outlet temperature, oil pan temperature, transmission oil average flow and core thermal parameters such as temperature rise time with high precision in real time, and comprehensively obtain the thermal performance data of the transmission in extreme working conditions; S6: record the test results; S7: thermal power calculation and analysis: based on the collected test data, use the non-equilibrium heat transfer correction model to accurately calculate the key parameters such as temperature rise power of the hydraulic torque converter, temperature rise power of the transmission oil, cooling power of the hydraulic torque converter and total heat power, correct the calculation results by using the non-equilibrium heat transfer correction model, finally determine the peak heat power of the transmission, and compare and analyze the calculation results with the radiator power systematically, to evaluate the performance of the transmission thermal management system; S8: complete the reverse development comparison, and provide scientific basis for product optimization design.

2. The method of claim 1, wherein: The working condition screening algorithm uses the normal distribution frequency statistical method in statistics, and selects the speed point with the highest frequency in the normal distribution as the reasonable working condition point.

3. The method of claim 1, wherein: The heat power calculation is performed by the formula where m is the mass of the object, Cp is the specific heat capacity, ΔT is the temperature rise, and Δt is the temperature rise time.

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