Full-scene energy consumption test method and device based on power assembly bench vehicle

Abstract

The application discloses a full-scene energy consumption test method and device based on a power assembly bench vehicle. The full-scene energy consumption test method based on the power assembly bench vehicle is as follows: obtaining driving resistance coefficients at different temperatures according to real vehicle road sliding tests under different environmental temperature conditions, and constructing a full-temperature range resistance curve library; reconstructing a characteristic speed curve of a typical driving scene based on real vehicle road data, and extracting user behavior parameters under the typical driving scene; calling driving resistance coefficients corresponding to a target test temperature and corresponding characteristic speed curves and user behavior parameter sets according to a target test scene for time-domain synchronous multi-parameter collaborative loading and testing on the power assembly bench; comparing and verifying obtained bench energy consumption test data with real vehicle road energy consumption test data under the same scene, and outputting verification results of the bench energy consumption test. The application realizes accurate reproduction of real use conditions of users on the power assembly bench.

Description

Technical Field

[0001] This invention relates to the field of vehicle testing technology, and in particular to a method and apparatus for testing the energy consumption of vehicles in all scenarios based on a powertrain bench. Specifically, it relates to a method and apparatus for testing energy consumption that reproduces real-world user conditions across all scenarios and temperature ranges on a powertrain bench. Background Technology

[0002] Currently, the energy consumption and driving range of new energy vehicles are mainly tested using bench testing methods. Following standards such as GB / T18386.1-2021 "Test Methods for Energy Consumption and Driving Range of Electric Vehicles Part 1: Light Vehicles," the vehicle is placed on a chassis dynamometer and driven under simulated road resistance and standard operating conditions (such as CLTC and WLTC) to measure its energy consumption and driving range. This method has good controllability and repeatability and is widely used in the standardized evaluation and certification of vehicle performance.

[0003] However, current standard operating conditions are mostly idealized driving modes, which cannot cover the diverse driving behaviors, road types, traffic conditions, and ambient temperature changes faced by users in actual use. This leads to a significant discrepancy between bench test results and actual user experience. To compensate for this deficiency, some studies have attempted to conduct energy consumption tests in real-world road environments to evaluate the energy consumption performance of vehicles under real-world usage conditions. Road tests can reflect the energy consumption characteristics of vehicles under actual road conditions, traffic conditions, and driving behaviors, and have high external validity. However, road tests have limitations such as high testing costs, uncontrollable environmental conditions, and poor repeatability of test results, making them difficult to use for refined calibration and iterative optimization during the R&D phase.

[0004] Therefore, resolving the contradiction between the current difficulty in replicating real-world user conditions in bench testing and the poor controllability of road testing has become a necessary issue to address. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings and defects of the prior art and to provide a method and apparatus for testing the energy consumption of vehicles in all scenarios based on a powertrain bench.

[0006] One aspect of the present invention provides a method for full-scenario energy consumption testing of a vehicle based on a powertrain bench, comprising:

[0007] Based on the actual vehicle road coasting test under different ambient temperature conditions, the driving drag coefficient at different temperatures was obtained, and a full-temperature range drag curve library was constructed.

[0008] Based on real vehicle road data, we reconstruct the characteristic speed curves of typical driving scenarios, and extract user behavior parameters under typical driving scenarios to construct a parameter set for typical driving scenarios.

[0009] The driving resistance coefficient corresponding to the target test temperature will be called from the full-temperature range resistance curve library according to the target test scenario, and the corresponding characteristic speed curve and user behavior parameter set will be called from the typical driving scenario parameter set to perform time-domain synchronous multi-parameter collaborative loading and testing on the powertrain bench.

[0010] The obtained bench energy consumption test data is compared and verified with the real vehicle road energy consumption test data under the same scenario, and the verification results of the bench energy consumption test are output.

[0011] Preferably, a real vehicle road coasting test is conducted under three different ambient temperature conditions, covering at least a low temperature range, a normal temperature range, and a high temperature range, to obtain the driving resistance coefficient at different temperatures, wherein the low temperature range is ≤-7℃, the normal temperature range is 20℃-25℃, and the high temperature range is ≥30℃.

[0012] Preferably, the formation of the full-temperature range resistance curve library includes:

[0013] The driving resistance coefficient is normalized to the standard temperature using the first temperature correction method to establish a benchmark resistance model.

[0014] The reference resistance model is mapped to any target test temperature within a preset temperature range from low to high using a second temperature correction method, forming a full-temperature range resistance curve library.

[0015] Preferably, the characteristic speed curves of the typical driving scenarios include at least the characteristic speed curves of typical driving scenarios such as urban commuting, highway cruising, and mountain roads.

[0016] Preferably, the characteristic speed curve is formed by slicing, clustering and recombining the actual driving data in the real vehicle road acquisition scenario, and the characteristic speed curve includes scene labels.

[0017] Preferably, the user behavior parameters include at least the air conditioning set temperature, vehicle load, and energy recovery level.

[0018] Preferably, during the multi-parameter collaborative loading and testing process, the vehicle accessories are simultaneously turned on to reproduce real user habits.

[0019] Preferably, the powertrain test bench includes four motors, each of which is independently controlled to achieve dynamic and independent loading of the resistance of each wheel, simulating the vehicle's driving state in the target scenario.

[0020] Preferably, the bench energy consumption test data includes energy consumption per unit mileage and / or driving range, which are calculated and determined based on the voltage, current, and SOC data collected in real time during the bench test.

[0021] Another aspect of the present invention provides a full-scenario energy consumption test device based on a powertrain bench vehicle, used to implement the full-scenario energy consumption test method based on a powertrain bench vehicle, comprising:

[0022] A temperature-controlled chamber for simulating target ambient temperature within a preset temperature range, a wind speed simulation device arranged within the temperature-controlled chamber for simulating the wind speed of a vehicle during driving, a powertrain bench for carrying the test vehicle, and a control and data acquisition system; the powertrain bench is used to load the driving drag coefficient and the characteristic speed curve; the control and data acquisition system is used to call and execute the user behavior parameters, control the temperature-controlled chamber, the wind speed simulation device, and the powertrain bench system to work together, collect preset data during the test in real time, calculate energy consumption data, and compare and verify the calculated bench energy consumption test data with the corresponding scenario data in the preset real vehicle road energy consumption test data, and output the verification results of the bench energy consumption test.

[0023] Compared with the prior art, the present invention has the following beneficial effects:

[0024] First, it balances realism and controllability. This invention integrates real resistance characteristics obtained from road coasting tests with typical driving scenarios constructed from user surveys, achieving accurate reproduction of real-world user conditions on a powertrain test bench. This retains the controllability and repeatability of test bench testing while also possessing the realism of road testing.

[0025] Second, it achieves full temperature range coverage. By conducting coasting tests in typical temperature ranges such as low temperature, normal temperature, and high temperature, and combining the first temperature correction method and the second temperature correction method to map to the full temperature range, it overcomes the limitation of the single temperature condition in traditional bench tests and can systematically evaluate the energy consumption performance of vehicles under different climatic conditions.

[0026] Third, multi-dimensional parameter coupling loading. This invention achieves time-domain synchronous and coordinated loading of resistance parameters, characteristic speed curves, and user behavior parameter sets on a four-motor powertrain test bench. By independently controlling each motor, it can simulate different road surface adhesion coefficients and mountain road curve driving conditions, reproduce the interactive effects of multiple factors in real driving (such as the superimposed effect of low temperature + high speed + air conditioning), and significantly improve the accuracy of test results.

[0027] Fourth, the testing is highly efficient and cost-effective. This method can efficiently obtain energy consumption data in the laboratory, which originally required extensive road testing, significantly shortening the R&D cycle, reducing testing costs, and facilitating the optimization of vehicle strategies and rapid product iteration.

[0028] Fifth, it has strong verifiability. By comparing and verifying the results with those of real-vehicle road tests, a closed-loop optimization mechanism is formed, outputting bench test accuracy verification results, ensuring the credibility of test data, and providing a high-precision engineering verification platform for the evaluation of electric vehicle energy consumption and driving range. Attached Figure Description

[0029] Figure 1 This is a flowchart of the energy consumption test method for vehicles in all scenarios based on powertrain benches according to the present invention.

[0030] Figure 2 This is a schematic diagram of the structural principle of the powertrain bench-based vehicle energy consumption test device of the present invention.

[0031] In the picture:

[0032] 1-Temperature control chamber; 2-Wind speed simulation device; 3-Powertrain test bench; 4-Load dynamometer; 5-Drive half shaft; 6-Test bench auxiliary equipment; 7-Control and data acquisition system; 8-Speed ​​sensor; 9-Signal acquisition unit. Detailed Implementation

[0033] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0034] The present invention provides a full-scenario energy consumption test technology for vehicles based on a powertrain bench. By integrating real resistance characteristics obtained from road coasting tests, typical driving scenarios constructed from user surveys and real vehicle data, and a full-temperature range resistance correction model, the technology accurately reproduces real-world user conditions on a powertrain bench. This balances the authenticity and controllability of the test, providing a high-precision and high-efficiency engineering verification method for evaluating the energy consumption and driving range of electric vehicles.

[0035] In an exemplary embodiment of this application, the powertrain bench vehicle full-scenario energy consumption test method includes:

[0036] S1. Based on the actual vehicle road coasting test under different ambient temperature conditions, obtain the driving resistance coefficient at different temperatures, and construct a full-temperature range resistance curve library;

[0037] S2. Based on real vehicle road data, reconstruct the characteristic speed curves of typical driving scenarios, and extract user behavior parameters under typical driving scenarios to construct a parameter set for typical driving scenarios;

[0038] S3. Based on the target test scenario, the driving resistance coefficient corresponding to the target test temperature will be called from the full-temperature range resistance curve library, and the corresponding characteristic speed curve and user behavior parameter set will be called from the typical driving scenario parameter set to perform time-domain synchronous multi-parameter collaborative loading and testing on the powertrain bench.

[0039] S4. Compare and verify the obtained bench energy consumption test data with the real vehicle road energy consumption test data under the same scenario, and output the verification results of the bench energy consumption test.

[0040] As a preferred implementation method, during the test, a real vehicle road coasting test is conducted under three different ambient temperature conditions, covering at least a low temperature range, a normal temperature range, and a high temperature range, to obtain the driving resistance coefficient at different temperatures. For example, the low temperature range is ≤-7℃, the normal temperature range is 20℃-25℃, and the high temperature range is ≥30℃. For example, the vehicle coasting test is conducted on a horizontal straight track in a test track according to national standards to obtain driving resistance coefficients such as rolling resistance coefficient f0, primary wind resistance coefficient f1, and secondary wind resistance coefficient f2.

[0041] In one exemplary embodiment, the formation of the full-temperature range resistance curve library includes:

[0042] The first temperature correction method is used to normalize the driving resistance coefficient to a standard temperature to establish a reference resistance model; the second temperature correction method is used to map the reference resistance model to any target test temperature within a preset temperature range from low temperature to high temperature to form a full-temperature range resistance curve library.

[0043] For example, the temperature correction method of the National VI standard is used as the first temperature correction method, the resistance data at different temperatures are fitted and corrected to the standard temperature of 20℃, and the parameter with the highest degree of overlap with the standard temperature curve is selected as the reference resistance model; the method of using a preset temperature mapping model for correction is used as the second temperature correction method, and the reference resistance model is mapped to any target test temperature in the full temperature range of -20℃ to +60℃.

[0044] The arbitrary target test temperature, such as -10℃, 0℃, 20℃, 28℃, and 38℃, is selected as representative test points to establish a full-temperature range resistance curve library.

[0045] In one exemplary embodiment, the characteristic speed curves of the typical driving scenarios include at least the characteristic speed curves of typical driving scenarios such as urban commuting, highway cruising, and mountain roads, and the typical driving scenarios are determined by analyzing real vehicle road data.

[0046] In one exemplary embodiment, the characteristic speed curve includes characteristic speed curves for various different scenarios. It is formed by slicing, clustering, and recombining actual driving data collected from real-vehicle roads and then reconstructing the data. The characteristic speed curve includes scenario labels.

[0047] In one exemplary embodiment, the user behavior parameters are determined based on user survey data statistics and include at least the air conditioning set temperature, vehicle load, and energy recovery level. For example, in an urban commuting scenario, the vehicle load is set to 150kg and the air conditioning is set to 21℃; in a highway cruising scenario, the vehicle load is set to 300kg and the air conditioning is set to 24℃; the energy recovery level is set to standard mode in both cases.

[0048] For example, during the multi-parameter collaborative loading and testing process, in-vehicle accessories, such as air conditioners, are simultaneously turned on to reproduce real user habits.

[0049] In one exemplary embodiment, the powertrain test bench 3 includes four load dynamometers 4, each independently controlled to dynamically and independently apply resistance to each wheel, simulating the vehicle's driving state in a target scenario. Specifically, each load dynamometer 4 is connected to one wheel of the test vehicle via a drive half-shaft 5.

[0050] In this application, the test system is constructed based on the powertrain test bench 3, which is arranged in a temperature control chamber 1. The temperature control chamber is equipped with a wind speed simulation device 2. The temperature control chamber can adjust the temperature inside the chamber, such as achieving temperature control from -20℃ to +60℃, to form a temperature environment for testing. The wind speed simulation device can simulate the wind speed when the vehicle is driving. For example, it can be implemented by using a fan, which is arranged in the front direction of the test vehicle, with the air outlet facing the front of the vehicle, to simulate the wind speed when the vehicle is driving.

[0051] In this application, the powertrain bench is used for precise loading of road resistance and driving conditions during vehicle full-scenario energy consumption testing. Each motor of the powertrain bench is independently controlled, enabling dynamic and independent loading of resistance at each wheel. The test platform or system also includes a high-precision control and data acquisition system 7, which is connected to a signal acquisition unit 9 to collect test data. The signal acquisition unit 9 is connected to the data acquisition system 7 to call and execute the user behavior parameters, control the temperature control chamber, wind speed simulation device, and powertrain bench system to work together, and collect preset data in real time during the test process, calculate energy consumption data, and compare and verify the calculated bench energy consumption test data with the corresponding scenario data in the preset real vehicle road energy consumption test data, and output the verification result of the bench energy consumption test.

[0052] In the embodiments of this application, for example, the bench energy consumption test data includes energy consumption per unit mileage and / or driving range, which are calculated and determined based on the voltage, current, and SOC data collected in real time during the bench test.

[0053] Taking a high-speed cruising scenario with a target test environment of 38℃ as an example, during the test, the control and data acquisition system automatically retrieves the resistance parameters corresponding to 38℃, the characteristic speed curve of the high-speed cruising scenario, and the user behavior parameters of the high-speed cruising scenario (such as air conditioning at 24℃ and a load of 300kg). The temperature control chamber is controlled to 38℃ and the fan is turned on to simulate the wind speed. The powertrain bench is simultaneously loaded with resistance parameters and speed curves, and the vehicle's air conditioning is automatically turned on to 24℃. The control and data acquisition system records the voltage, current, SOC, and other data of the power battery in real time until the end of the test. The collected test data is processed to calculate the energy consumption per unit mile (kWh / 100km) and driving range. Then, the bench test results are compared with the real vehicle road test data under the same scenario to output the accuracy verification results of the bench test.

[0054] This invention further provides a full-scenario energy consumption test device based on a powertrain bench vehicle, used to implement the full-scenario energy consumption test method based on a powertrain bench vehicle, including:

[0055] A temperature-controlled chamber for simulating target ambient temperature within a preset temperature range, a wind speed simulation device arranged within the temperature-controlled chamber for simulating the wind speed of a vehicle during driving, a powertrain bench for carrying the test vehicle, and a control and data acquisition system; the powertrain bench is used to load the driving drag coefficient and the characteristic speed curve; the control and data acquisition system is used to call and execute the user behavior parameters, control the temperature-controlled chamber, the wind speed simulation device, and the powertrain bench system to work together, collect preset data during the test in real time, calculate energy consumption data, and compare and verify the calculated bench energy consumption test data with the corresponding scenario data in the preset real vehicle road energy consumption test data, and output the verification results of the bench energy consumption test.

[0056] This invention is based on a powertrain bench vehicle full-scenario energy consumption test device. Through user data-driven scenario construction and multi-parameter collaborative loading, it can accurately reproduce real user usage scenarios. It achieves high-precision reproduction of real user vehicle operating conditions in the laboratory, taking into account the authenticity of road tests and the controllability of bench tests. It provides a high-precision, high-efficiency and reproducible engineering verification platform for the evaluation of electric vehicle energy consumption and driving range.

[0057] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. It will be apparent to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or basic features of the present invention.

[0058] Therefore, the embodiments should be regarded as exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, it is intended that all variations falling within the meaning and scope of the equivalents of the claims be included within the invention.

[0059] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

Claims

1. A full-scenario energy consumption test method based on a powertrain bench vehicle, characterized in that, include: Based on the actual vehicle road coasting test under different ambient temperature conditions, the driving drag coefficient at different temperatures was obtained, and a full-temperature range drag curve library was constructed. Based on real vehicle road data, we reconstruct the characteristic speed curves of typical driving scenarios, and extract user behavior parameters under typical driving scenarios to construct a parameter set for typical driving scenarios. The driving resistance coefficient corresponding to the target test temperature will be called from the full-temperature range resistance curve library according to the target test scenario, and the corresponding characteristic speed curve and user behavior parameter set will be called from the typical driving scenario parameter set to perform time-domain synchronous multi-parameter collaborative loading and testing on the powertrain bench. The obtained bench energy consumption test data is compared and verified with the real vehicle road energy consumption test data under the same scenario, and the verification results of the bench energy consumption test are output.

2. The method for full-scenario energy consumption testing of vehicles based on powertrain benches according to claim 1, characterized in that, Actual vehicle road coasting tests were conducted under three different ambient temperature conditions, including at least a low temperature range, a normal temperature range, and a high temperature range, to obtain the driving resistance coefficient at different temperatures. The low temperature range is ≤-7℃, the normal temperature range is 20℃-25℃, and the high temperature range is ≥30℃.

3. The method for full-scenario energy consumption testing of vehicles based on a powertrain bench as described in claim 1, characterized in that, The formation of the full-temperature range resistance curve library includes: The driving resistance coefficient is normalized to the standard temperature using the first temperature correction method to establish a benchmark resistance model. The reference resistance model is mapped to any target test temperature within a preset temperature range from low to high using a second temperature correction method, forming a full-temperature range resistance curve library.

4. The method for full-scenario energy consumption testing of vehicles based on powertrain benches according to claim 1, characterized in that, The characteristic speed curves for the typical driving scenarios include at least the characteristic speed curves for typical driving scenarios such as urban commuting, highway cruising, and mountain roads.

5. The method for full-scenario energy consumption testing of vehicles based on powertrain benches according to claim 1, characterized in that, The characteristic speed curve is formed by slicing, clustering, and recombining actual driving data acquired from real-vehicle road scenarios, and the characteristic speed curve includes scene labels.

6. The method for full-scenario energy consumption testing of vehicles based on a powertrain bench as described in claim 1, characterized in that, The user behavior parameters include at least the air conditioning set temperature, vehicle load, and energy recovery level.

7. The method for full-scenario energy consumption testing of vehicles based on a powertrain bench as described in claim 1, characterized in that, During the multi-parameter collaborative loading and testing process, in-vehicle accessories are simultaneously enabled to reproduce real user habits.

8. The method for full-scenario energy consumption testing of vehicles based on powertrain benches according to claim 1, characterized in that, The powertrain test bench includes four motors, each of which is independently controlled to dynamically and independently apply resistance to each wheel, simulating the vehicle's driving state in a target scenario.

9. The method for full-scenario energy consumption testing of vehicles based on a powertrain bench as described in claim 1, characterized in that, The bench energy consumption test data includes energy consumption per unit mileage and / or driving range, which are calculated and determined based on the voltage, current, and SOC data collected in real time during the bench test.

10. A full-scenario energy consumption test device for powertrain bench vehicles, characterized in that, The method for implementing the full-scenario energy consumption test method for powertrain bench vehicles as described in any one of claims 1-9 includes: A temperature-controlled chamber for simulating target ambient temperature within a preset temperature range, a wind speed simulation device arranged within the temperature-controlled chamber for simulating the wind speed of a vehicle during driving, a powertrain bench for carrying the test vehicle, and a control and data acquisition system; the powertrain bench is used to load the driving drag coefficient and the characteristic speed curve; the control and data acquisition system is used to call and execute the user behavior parameters, control the temperature-controlled chamber, the wind speed simulation device, and the powertrain bench system to work together, collect preset data during the test in real time, calculate energy consumption data, and compare and verify the calculated bench energy consumption test data with the corresponding scenario data in the preset real vehicle road energy consumption test data, and output the verification results of the bench energy consumption test.

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