New energy automobile hardware-in-the-loop performance calibration method and system

Abstract

The invention provides a new energy automobile hardware-in-the-loop performance calibration method and system, and the system comprises a virtual function test module which is used for determining each calibration item and a corresponding calibration value range by taking the function set by a virtual whole automobile as a target; the virtual calibration module is used for determining a calibration value of each calibration item and performance data corresponding to the calibration item by taking the calibration item and the calibration value range as constraint conditions and taking the performance set by the virtual whole vehicle as a target; the calibration correction module is used for acquiring calibration values and performance data corresponding to all calibration items of a real vehicle corresponding to the virtual whole vehicle, and performing difference calculation on the calibration values and the performance data corresponding to all the calibration items of the real vehicle and the calibration values and the performance data corresponding to the calibration items determined by calibration of the virtual whole vehicle; and when the calibration difference value or the performance difference value exceeds a set threshold value, modifying the basic function model combination and the performance model combination used in the whole vehicle simulation virtual calibration to perform simulation virtual calibration again until the set threshold value is met.

Description

Technical Field

[0001] This invention relates to the technical field of virtual calibration, and more specifically to a method and system for hardware-in-the-loop performance calibration of new energy vehicles. Technical Background With the rapid development of the new energy vehicle market, development cycles are constantly shortening, placing higher demands on development efficiency. In the traditional automotive development process, calibration work (i.e., adjusting and optimizing vehicle control system parameters) usually relies on real-vehicle testing, which is not only time-consuming and labor-intensive but also cannot be carried out in advance, making it difficult to meet the needs of rapid development. Therefore, virtual calibration technology has emerged, using simulation methods to perform calibration in the early stages of development to improve efficiency and reduce costs.

[0002] However, existing virtual calibration technologies have the following shortcomings: 1. Separation of Function and Performance: Existing virtual calibration systems mostly focus on the single objective of functional testing or performance calibration, failing to organically combine the two. For example, patent CN102073278A proposes an ECM calibration system based on a virtual vehicle, which only focuses on functional calibration and does not cover overall vehicle performance optimization.

[0003] 2. Lack of data comparison and accumulation: Existing technologies lack a mechanism for comparing simulation calibration data with real-vehicle calibration data. This results in each calibration operation being relatively independent, failing to provide a reference for subsequent models and limiting development efficiency. For example, although patent CN110987476A proposes a virtual calibration testing method, it does not involve data accumulation and reuse. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings and deficiencies of the prior art and provide a hardware-in-the-loop performance calibration method and system for new energy vehicles. It aims to organically combine functional testing and performance calibration, and provide a reference for subsequent models by storing the basic model used in the calibration process, thereby improving development efficiency and shortening the calibration cycle.

[0005] The solution of the present invention to the above-mentioned technical problems is as follows: a hardware-in-the-loop performance calibration system for new energy vehicles. The virtual function testing module is used to determine each calibration item and the corresponding calibration value range with the goal of meeting the functions set in the virtual vehicle. The virtual calibration module is used to determine the calibration values ​​of each calibration item and the corresponding performance data based on the calibration items and the corresponding calibration value range, with the performance set by the virtual vehicle as the target and the calibration value range as the constraint. The calibration correction module is used to obtain the corresponding calibration values ​​and performance data of each calibration item of the real vehicle corresponding to the virtual vehicle. It calculates the calibration difference and performance difference by comparing the corresponding calibration values ​​and performance data of each calibration item of the real vehicle with the corresponding calibration values ​​and performance data of the virtual vehicle calibration. When the calibration difference or performance difference exceeds the set threshold, it modifies the basic function model combination and performance model combination used in the virtual calibration of the vehicle simulation and performs virtual calibration again until the set threshold is met.

[0006] During the virtual calibration process, through a three-layer closed-loop iteration of function, performance, and real vehicle, functional testing and performance calibration can be combined in a simulated environment before the vehicle is developed, shortening the vehicle development cycle. After the vehicle is produced, the difference between the virtual calibration results and the real vehicle is always controlled within a set threshold, which is beneficial for the reuse of calibration personnel.

[0007] Preferably, the virtual function testing module is used to determine each calibration item and the corresponding calibration value range with the goal of meeting the functions set in the virtual vehicle, specifically including: The virtual functional testing module includes a virtual functional testing environment and a basic model library; The basic model library includes vehicle drive models, braking models, and controller strategy models; Based on the functions set by the virtual vehicle, drive models, braking models, and controller strategy models are selected from the basic model library to form a combination of basic functional models. Functional tests are conducted in the virtual functional test environment to determine the parameters related to the set functions as calibration items, and the calibration values ​​of the calibration items are determined to meet the parameter value range of the set functions.

[0008] Virtual functional test environments are an important component of hardware-in-the-loop (HiL) simulation and virtual calibration technologies. HiL simulation technology is widely used in the development and verification of automotive electronic control units (ECUs) to ensure the performance of ECUs under various operating conditions by simulating the actual operating environment of the vehicle.

[0009] The virtual functional testing module constructs a virtual vehicle model, runs functional tests, records and analyzes test data, and determines calibration items related to functional requirements and their value ranges. This not only ensures that the virtual vehicle meets the set functional requirements but also provides crucial foundational data for subsequent calibration work, significantly improving development efficiency and product quality.

[0010] Preferably, the virtual calibration module is used to determine the calibration values ​​of each calibration item and the corresponding performance data of the calibration item based on the calibration items and the corresponding calibration value range, with the performance set by the virtual vehicle as the objective and the calibration value range as the constraint condition. Specifically, it includes: The virtual calibration module includes a performance model and a virtual calibration environment; Select the appropriate performance model based on each calibration item type, input the corresponding calibration value range into the selected performance model, perform working condition cycles in the virtual calibration environment, record the performance data of the virtual vehicle, filter the value corresponding to the optimal performance data of the virtual vehicle, and use the initial calibration value of the corresponding calibration item. The initial calibration values ​​of the corresponding calibration items are all within the corresponding calibration value range. The calibration values ​​of all calibration items that meet the set function and have the same type of performance are cycled through the working conditions. The performance data of the virtual vehicle is recorded, and the performance data of the vehicle is compared with the performance data of the same type of vehicle obtained from the standard test (data obtained from bench component tests of the same type of vehicle). If the data difference exceeds the set difference, the initial calibration values ​​of each calibration item are adjusted one by one until the difference between the corresponding performance data of the virtual vehicle recorded during the working condition cycle and the performance data of the same type of vehicle obtained from the standard test is within the set difference. The calibration values ​​of each calibration item and the corresponding performance data are obtained.

[0011] Virtual calibration environments are an important component of hardware-in-the-loop (HiL) simulation and virtual calibration technologies. HiL simulation technology is widely used in the development and verification of automotive electronic control units (ECUs) by simulating the actual operating environment of the vehicle.

[0012] The virtual calibration module loads the performance model, runs a cycle of operating conditions, records and analyzes performance data, and determines the optimal values ​​for each calibration item. This process ensures that the virtual vehicle meets the set performance requirements.

[0013] Preferably, based on the functions set in the virtual vehicle configuration, a basic functional model combination is formed by selecting a drive model, braking model, and controller strategy model from the basic model library. Functional testing is then conducted in a virtual functional testing environment. Parameters related to the configured functions are determined as calibration items, and the calibration values ​​for these calibration items are set to satisfy the parameter value range of the configured functions. Specifically: To achieve the goal of continuous output of the virtual vehicle motor under all operating conditions, a combination of basic functional models is formed by selecting drive models, braking models, and controller strategy models from the basic model library. Functional testing is then conducted in a virtual test environment. The peak torque limit of the motor related to the continuous output of the virtual vehicle motor under all operating conditions is determined as a calibration item. The range of the peak torque limit of the motor is A~BN·m, which is the calibration value range of the calibration item. The process involves selecting the appropriate performance model based on each calibration item type, inputting the corresponding calibration value range into the selected performance model, performing a cycle of operating conditions in a virtual calibration environment, recording the performance data of the virtual vehicle, and filtering out the optimal performance data of the virtual vehicle to obtain the initial calibration value for the corresponding calibration item. Specifically: The peak torque limit of the motor is determined to be an economic calibration item. Therefore, the motor thermal management model is selected as the chosen performance model from the thermal management models, as detailed below: The expression for the motor thermal management model is as follows: The formula for calculating the heat generation of the motor is: in, To generate heat for the motor, This refers to the mechanical power of the motor. The motor efficiency is obtained by looking up the table; Motor mechanical power The calculation formula is: in, This refers to the motor speed. This is the peak torque limit for the motor; motor speed n motor The calculation formula is: in, v For vehicle speed, i g This refers to the gear ratio of the transmission. i t The main reducer transmission ratio is given by r, where r is the wheel rolling radius. π Pi; Input the range of the motor peak torque limit A~BN·m into the motor thermal management model and perform operating condition cycles in a virtual calibration environment. Record the motor heat generation of the virtual vehicle accordingly, and select the value A1 corresponding to the optimal motor heat generation of the virtual vehicle as the initial calibration value of the motor peak torque limit, where A1 ∈ A~B.

[0014] Preferably, based on the functions set in the virtual vehicle configuration, a basic functional model combination is formed by selecting a drive model, braking model, and controller strategy model from the basic model library. Functional testing is then conducted in a virtual functional testing environment. Parameters related to the configured functions are determined as calibration items, and the calibration values ​​for these calibration items are set to satisfy the parameter value range of the configured functions. Specifically: To achieve the goal of continuous output of the virtual vehicle motor under all operating conditions, a combination of basic functional models is formed by selecting drive models, braking models, and controller strategy models from the basic model library and conducting functional tests in a virtual test environment. The transmission ratio related to the continuous output of the virtual vehicle motor under all operating conditions is determined as a calibration item, and the transmission ratio value range C~D is the calibration value range of the calibration item. The process involves selecting the appropriate performance model based on each calibration item type, inputting the corresponding calibration value range into the selected performance model, performing a cycle of operating conditions in a virtual calibration environment, recording the performance data of the virtual vehicle, and filtering out the optimal performance data of the virtual vehicle to obtain the initial calibration value for the corresponding calibration item. Specifically: Since the transmission ratio is determined to be a calibration item for economic efficiency, the motor thermal management model is selected as the chosen performance model from the thermal management models, as follows: The expression for the motor thermal management model is as follows: The formula for calculating the heat generation of the motor is: in, To generate heat for the motor, This refers to the mechanical power of the motor. The motor efficiency is obtained by looking up the table; Motor mechanical power The calculation formula is: in, This refers to the motor speed. This is the peak torque limit for the motor; motor speed n motor The calculation formula is: in, v For vehicle speed, i g This refers to the gear ratio of the transmission. i t The main reducer transmission ratio is given by r, where r is the wheel rolling radius. π Pi; Input the transmission ratio range C~D into the motor thermal management model and perform operating condition cycles in a virtual calibration environment. Record the motor heat generation of the virtual vehicle accordingly. Select the optimal motor heat generation value C1 of the virtual vehicle as the initial calibration value of the motor peak torque limit, where C1∈C~D.

[0015] Preferably, the calibration values ​​of all calibration items that meet the set function and are of the same type of performance are cycled through operating conditions to record the performance data of the virtual vehicle. The performance data of the vehicle is then compared with the performance data of the same type of vehicle obtained from standard tests. If the data difference exceeds a set difference, the initial calibration values ​​of each calibration item are adjusted one by one until the difference between the corresponding performance data of the virtual vehicle recorded during the operating condition cycle and the performance data of the same type of vehicle obtained from standard tests is within the set difference, thus obtaining the calibration values ​​of each calibration item and the corresponding performance data. Specifically, this includes: To meet the target function of continuous output of the virtual vehicle motor under all operating conditions, the economical calibration values ​​include the motor peak torque limit and the transmission ratio. The initial calibration values ​​of the motor peak torque limit (A1 N·m) and the transmission ratio (C1) are used. The motor thermal management model is cyclically tested in a virtual calibration environment, and the motor heat generation of the virtual vehicle is recorded accordingly. This data is compared with the motor heat generation data of the vehicle obtained from standard tests. If the difference exceeds a set difference, the initial calibration values ​​of the motor peak torque limit (A1 N·m) and the transmission ratio (C1) are adjusted gradually until the difference between the motor heat generation of the virtual vehicle recorded during the operating cycle and the motor heat generation data of the vehicle obtained from standard tests is within the set difference. This yields the calibration values ​​of the motor peak torque limit, the transmission ratio, and the corresponding motor heat generation.

[0016] Preferably, the calibration values ​​and performance data of each calibration item of the real vehicle corresponding to the virtual vehicle are obtained. The calibration values ​​and performance data of each calibration item of the real vehicle are then compared with the corresponding calibration values ​​and performance data of the corresponding calibration items determined by the virtual vehicle calibration to calculate calibration differences and performance differences. If the calibration difference or performance difference exceeds a set threshold, the basic functional model combination and performance model combination used in the virtual vehicle simulation calibration are modified, and virtual simulation calibration is performed again until the set threshold is met. This includes: Obtain the calibration values ​​and performance data of each calibration item of the real vehicle corresponding to the virtual vehicle, and calculate the calibration difference and performance difference between the calibration values ​​and performance data of each calibration item of the real vehicle and the corresponding calibration values ​​and performance data of the virtual vehicle calibration. If the difference between the corresponding calibration values ​​of the corresponding calibration items determined by the virtual vehicle calibration meets the set threshold, but the difference in performance data does not meet the set threshold; Then, based on the difference performance data, locate the basic functional model combination and the distortion model in the performance model; Adjust the parameters of the distorted model, or reload other models corresponding to the same type of virtual vehicle and perform simulation virtual calibration again until the set threshold is met; If the difference between the corresponding calibration values ​​of the corresponding calibration items determined by the virtual vehicle calibration does not meet the set threshold, but the difference between the performance data meets the set threshold; If the gradient adjustment calibration difference does not meet the set threshold, the corresponding calibration value of the calibration item will be used again for simulation virtual calibration until the set threshold is met.

[0017] Preferably, the system further includes a cloud data storage module for storing basic functional model combinations and performance model combinations that have completed vehicle simulation virtual calibration. Specifically, it is used by vehicles of the same type to call upon the basic functional model combinations and performance model combinations that have completed vehicle simulation virtual calibration for simulation virtual calibration.

[0018] The cloud can reuse calibrated model combinations, and vehicles on the same platform can be directly called up, which greatly reduces the model building time and realizes the accumulation of knowledge assets and cross-project sharing.

[0019] Preferably, the system further includes a user calibration management module for assigning user permissions based on user type. When the customer is the calibration initiator, they are authorized to see the progress of the calibration work and the final available calibration report. When the customer is a tester, they are authorized to see: the host computer and the virtual function testing module, virtual calibration module, calibration correction module, and cloud data storage module within the host computer.

[0020] This invention also provides a method for hardware-in-the-loop performance calibration of new energy vehicles, comprising the following steps: To meet the functional requirements of the virtual vehicle, each calibration item and its corresponding calibration value range are determined. Based on the calibration items and the corresponding calibration value range, with the performance set by the virtual vehicle as the target and the calibration value range as the constraint, the calibration value of each calibration item and the performance data corresponding to the calibration item are determined. Obtain the calibration values ​​and performance data of each calibration item of the real vehicle corresponding to the virtual vehicle. Calculate the calibration difference and performance difference between the calibration values ​​and performance data of each calibration item of the real vehicle and the corresponding calibration values ​​and performance data of the virtual vehicle calibration. If the calibration difference or performance difference exceeds the set threshold, modify the basic functional model combination and performance model combination used in the virtual vehicle simulation calibration and perform virtual simulation calibration again until the set threshold is met.

[0021] The present invention also provides a computer storage medium storing a computer program, which, when executed by a processor, implements the steps of the hardware-in-the-loop performance calibration method for new energy vehicles as described above.

[0022] The present invention also provides an electronic device, including a memory and a processor: the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions, wherein when the computer-executable instructions are executed by the processor, the steps of the hardware-in-the-loop performance calibration method for new energy vehicles as described above are implemented.

[0023] The beneficial effects of this invention are as follows: This application combines functional testing and performance calibration, and then places the calibration work on a cloud platform, realizing simultaneous local and remote calibration. The calibration data is then entered into a cloud database as a reference base for calibration on the same platform. This method not only performs functional testing while considering performance before vehicle development, but also places the calibration work on a cloud platform, combining the calibration results of the design and the actual vehicle, breaking geographical limitations. Furthermore, the calibration database serves as a calibration reference for the next model, reducing redundant modeling and calibration work and significantly compressing the overall development time.

[0024] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it according to the contents of the specification, the preferred embodiments of the present invention are described in detail below with reference to the accompanying drawings. Specific embodiments of the present invention are given in detail below with reference to the accompanying drawings. Attached Figure Description

[0025] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this invention, illustrate exemplary embodiments of the invention and are used to explain the invention, but do not constitute an undue limitation of the invention. In the drawings: Figure 1 This is a block diagram of a hardware-in-the-loop performance calibration system for new energy vehicles provided in Example 1; Figure 2 This is a flowchart of a hardware-in-the-loop performance calibration method for new energy vehicles provided in Example 2. Detailed Implementation

[0026] The principles and features of the present invention are described below with reference to the accompanying drawings. The examples given are only for explaining the present invention and are not intended to limit the scope of the present invention.

[0027] like Figure 1 As shown, this embodiment provides a hardware-in-the-loop performance calibration system for new energy vehicles, including: The virtual function testing module is used to determine each calibration item and its corresponding calibration value range, aiming to meet the functional requirements of the virtual vehicle. Specifically, it is used for: The virtual functional testing module includes a virtual functional testing environment and a basic model library; The basic model library includes vehicle drive models, braking models, and controller strategy models; Based on the functions set by the virtual vehicle, drive model, braking model, and controller strategy model are selected from the basic model library to form a combination of basic functional models, and recorded as shown in Table 1. Table 1 Basic Functional Model Combination The resulting selection-driven model, braking model, and controller strategy model are combined to form a basic functional model. Functional testing is then conducted in a virtual functional testing environment. Parameters related to the set function are identified as calibration items, and the parameter value ranges that satisfy the set function are defined as the calibration value ranges for these calibration items. The results are recorded and compiled into a calibration quantity database, as shown in Table 2.

[0028] Table 2 Standardized Database For example, to achieve the target function of a virtual vehicle shifting gears in 1 second, a basic functional model combination is formed by selecting a drive model, a braking model, and a controller strategy model from the basic model library. This combination is then used for functional testing in a virtual test environment. The shift speeds of 1st and 2nd gears and 3rd and 4th gears, which are related to the virtual vehicle's ability to shift gears in 1 second, are determined as calibration items. The range of 15-20 km / h for the 1st and 2nd gear shift speeds is defined as the calibration value range for the calibration items, and the range of 15-20 km / h for the 3rd and 4th gear shift speeds is also defined as the calibration value range for the calibration items.

[0029] For example, to achieve the goal of continuous output of the virtual vehicle motor under all operating conditions, a basic functional model combination is formed by selecting drive model, braking model, and controller strategy model from the basic model library and conducting functional tests in a virtual test environment. The peak torque limit of the motor and the transmission ratio related to the continuous output of the virtual vehicle motor under all operating conditions are determined as calibration items. The peak torque limit of the motor is 100~108 N·m, which is the calibration value range of the calibration item, and the transmission ratio is 2.5~5.0, which is the calibration value range of the calibration item.

[0030] The virtual calibration module is used to determine the calibration values ​​of each calibration item and the corresponding performance data based on the calibration items and the corresponding calibration value ranges, with the performance set by the virtual vehicle as the target and the calibration value ranges as constraints. Specifically, it is used for: The virtual calibration module includes a performance model and a virtual calibration environment; Based on each calibration item type, select the corresponding performance model, input the corresponding calibration value range into the selected performance model, perform working condition cycles in the virtual calibration environment, and record the performance data of the virtual vehicle. Filter the optimal performance data of the virtual vehicle and use the corresponding initial calibration value of the corresponding calibration item. The initial calibration values ​​of the corresponding calibration items are all within the corresponding calibration value range, forming a calibration model table, as shown in Table 3.

[0031] Table 3 Calibration Model Table The calibration values ​​of all calibration items that meet the set function and are of the same type of performance are cycled through operating conditions. The performance data of the virtual vehicle is recorded, and the performance data of the vehicle is compared with the performance data of the same type of vehicle obtained from standard tests (data obtained from bench component tests of similar models). If the data difference exceeds the set difference, the initial calibration values ​​of each calibration item are adjusted one by one until the difference between the corresponding performance data of the virtual vehicle recorded during the operating condition cycle and the performance data of the same type of vehicle obtained from standard tests is within the set difference. The calibration values ​​of each calibration item and the corresponding performance data are then obtained. After determining the calibration values ​​of each calibration item, the calibration item database is updated, as shown in Table 4.

[0032] Table 4 Updated Standardization Database The shift speeds for 1st and 2nd gears and 3rd and 4th gears are determined to be calibration items related to economy. The whole vehicle thermal management model is selected as the performance model from the thermal management models.

[0033] Input the vehicle speed range of 15-20 km / h for shifting from 1st to 2nd gear into the vehicle thermal management model and perform operating cycle in a virtual calibration environment. Record the energy consumption of the virtual vehicle accordingly, and select the optimal energy consumption value of 16 km / h for the virtual vehicle as the initial calibration value for shifting from 1st to 2nd gear.

[0034] Input the 3-4 gear shift speed range of 30-40 km / h into the vehicle thermal management model and perform operating condition cycles in a virtual calibration environment. Record the energy consumption of the virtual vehicle accordingly, and select the optimal energy consumption value of 33 km / h as the initial calibration value for the 3-4 gear shift speed.

[0035] To achieve the goal of enabling the virtual vehicle to shift gears in 1 second, the economical calibration values ​​include the shift speeds for 1st and 2nd gears and 3rd and 4th gears. The initial calibration values ​​for the 1st and 2nd gear shift speeds are set to 16 km / h, and for the 3rd and 4th gear shift speeds to 33 km / h. These values ​​are input into the motor thermal management model and cycled through operating conditions in a virtual calibration environment. The energy consumption of the virtual vehicle is recorded accordingly and compared with the energy consumption data obtained from standard tests. If the difference exceeds a set threshold, the initial calibration values ​​for the 1st and 2nd gear shift speeds (16 km / h) and the 3rd and 4th gear shift speeds (33 km / h) are gradually adjusted until the difference between the virtual energy consumption data recorded during the operating condition cycle and the energy consumption data obtained from standard tests is within the set threshold. This yields the calibration values ​​for the 1st and 2nd gear shift speeds and the corresponding vehicle energy consumption.

[0036] Since the peak torque limit of the motor and the gear ratio of the transmission are both determined to be calibration items related to economic efficiency, the motor thermal management model is selected as the performance model from the thermal management models, as detailed below: The expression for the motor thermal management model is as follows: The formula for calculating the heat generation of the motor is: in, To generate heat for the motor, This refers to the mechanical power of the motor. The motor efficiency is obtained by looking up the table; Motor mechanical power The calculation formula is: in, This refers to the motor speed. This is the peak torque limit for the motor; motor speed n motor The calculation formula is: in, v For vehicle speed, i g This refers to the gear ratio of the transmission. i t The main reducer transmission ratio is given by r, where r is the wheel rolling radius. π Pi is the mathematical constant of a circle.

[0037] The peak torque limit of the motor is input into the motor thermal management model in the range of 100~108 N·m. The model is then cyclically tested in a virtual calibration environment, and the motor heat generation of the virtual vehicle is recorded accordingly. The optimal motor heat generation value of 107 N·m for the virtual vehicle is selected as the initial calibration value for the peak torque limit of the motor.

[0038] The transmission ratio is set to a range of 2.5 to 5.0. The motor thermal management model is then cyclically tested in a virtual calibration environment. The motor heat generation of the virtual vehicle is recorded accordingly. The optimal motor heat generation value of 3.0 is selected as the initial calibration value for the motor peak torque limit.

[0039] To meet the target function of continuous output of the virtual vehicle motor under all operating conditions, the economical calibration values ​​include the motor peak torque limit and the transmission ratio. The initial calibration values ​​of the motor peak torque limit (107 N•m) and the transmission ratio (3.0) are input into the motor thermal management model and cycled in the virtual calibration environment. The motor heat generation of the virtual vehicle is recorded accordingly and compared with the motor heat generation data of the vehicle obtained from the standard test. If the difference exceeds the set difference, the initial calibration values ​​of the motor peak torque limit (107 N•m) and the transmission ratio (3.0) are adjusted gradually until the difference between the motor heat generation of the virtual vehicle recorded during the operating cycle and the motor heat generation of the vehicle obtained from the standard test is within the set difference. The calibration values ​​of the motor peak torque limit, the transmission ratio, and the corresponding motor heat generation are obtained.

[0040] The calibration correction module is used to acquire the calibration values ​​and performance data of each calibration item of the real vehicle corresponding to the virtual vehicle. It calculates the calibration difference and performance difference by comparing the calibration values ​​and performance data of each calibration item of the real vehicle with the corresponding calibration values ​​and performance data determined by the virtual vehicle calibration. When the calibration difference or performance difference exceeds a set threshold, it modifies the basic functional model combination and performance model combination used in the virtual vehicle simulation calibration and performs virtual calibration again until the set threshold is met. Specifically, this includes: Obtain the calibration values ​​and performance data of each calibration item of the real vehicle corresponding to the virtual vehicle, and calculate the calibration difference and performance difference between the calibration values ​​and performance data of each calibration item of the real vehicle and the corresponding calibration values ​​and performance data of the virtual vehicle calibration. If the difference between the corresponding calibration values ​​of the corresponding calibration items determined by the virtual vehicle calibration meets the set threshold, but the difference in performance data does not meet the set threshold; Then, based on the difference performance data, locate the basic functional model combination and the distortion model in the performance model; Adjust the parameters of the distorted model, or reload other models corresponding to the same type of virtual vehicle and perform simulation virtual calibration again until the set threshold is met; If the difference between the corresponding calibration values ​​of the corresponding calibration items determined by the virtual vehicle calibration does not meet the set threshold, but the difference between the performance data meets the set threshold; If the gradient adjustment does not meet the corresponding calibration value of the set threshold calibration item, the simulation virtual calibration is performed again until the set threshold is met, and the results are recorded as shown in Table 5.

[0041] Table 5 Corrected Calibration Data The cloud data storage module is used to store the basic functional model combination and performance model combination that have completed the virtual calibration of the whole vehicle simulation. Specifically, it is used by the same type of whole vehicle to call the basic functional model combination and performance model combination that have completed the virtual calibration of the whole vehicle simulation for simulation virtual calibration, as shown in Table 6.

[0042] Table 6 Cloud Calibration Model Table The user calibration management module is used to assign user permissions based on user type. When the customer is the one initiating the calibration, they are authorized to see the progress of the calibration work and the final available calibration report. When the customer is a tester, they are authorized to see: the host computer and the virtual functional testing module, virtual calibration module, calibration correction module, and cloud data storage module within the host computer.

[0043] Example 2 like Figure 2 As shown, this embodiment provides a hardware-in-the-loop performance calibration method for new energy vehicles, including the following steps: User permissions are assigned based on user type. When the customer is the calibration initiator, they are authorized to see the calibration work progress and the final available calibration report. When the customer is a tester, they are authorized to see the host computer and the virtual function test module, virtual calibration module, calibration correction module and cloud data storage module in the host computer.

[0044] To meet the functional requirements of the virtual vehicle, each calibration item and its corresponding calibration value range are determined. Based on the calibration items and the corresponding calibration value range, with the performance set by the virtual vehicle as the target and the calibration value range as the constraint, the calibration value of each calibration item and the performance data corresponding to the calibration item are determined. Obtain the calibration values ​​and performance data of each calibration item of the real vehicle corresponding to the virtual vehicle. Calculate the calibration difference and performance difference between the calibration values ​​and performance data of each calibration item of the real vehicle and the corresponding calibration values ​​and performance data of the virtual vehicle calibration. If the calibration difference or performance difference exceeds the set threshold, modify the basic functional model combination and performance model combination used in the virtual vehicle simulation calibration and perform virtual simulation calibration again until the set threshold is met.

[0045] The system stores the basic functional model combination and performance model combination that have completed the virtual calibration of the whole vehicle simulation and uploads them to the cloud. Specifically, when a vehicle of the same type calls the basic functional model combination and performance model combination that have completed the virtual calibration of the whole vehicle simulation from the cloud, it performs virtual calibration.

[0046] Example 3 This embodiment provides a computer storage medium storing a computer program. When the computer program is executed by a processor, it implements the steps of the hardware-in-the-loop performance calibration method for new energy vehicles as described in Embodiment 2.

[0047] Example 4 This embodiment provides an electronic device, including a memory and a processor: the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, they implement the steps of the hardware-in-the-loop performance calibration method for new energy vehicles as described in Embodiment 2.

[0048] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the foregoing drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. A hardware-in-the-loop performance calibration system for new energy vehicles, characterized in that, include: The virtual function testing module is used to determine each calibration item and the corresponding calibration value range with the goal of meeting the functions set in the virtual vehicle. The virtual calibration module is used to determine the calibration values ​​of each calibration item and the corresponding performance data based on the calibration items and the corresponding calibration value range, with the performance set by the virtual vehicle as the target and the calibration value range as the constraint. The calibration correction module is used to obtain the corresponding calibration values ​​and performance data of each calibration item of the real vehicle corresponding to the virtual vehicle. It calculates the calibration difference and performance difference by comparing the corresponding calibration values ​​and performance data of each calibration item of the real vehicle with the corresponding calibration values ​​and performance data of the virtual vehicle calibration. When the calibration difference or performance difference exceeds the set threshold, it modifies the basic function model combination and performance model combination used in the virtual calibration of the vehicle simulation and performs virtual calibration again until the set threshold is met.

2. The hardware-in-the-loop performance calibration system for new energy vehicles according to claim 1, characterized in that, The virtual function testing module is used to determine each calibration item and its corresponding calibration value range, with the goal of meeting the functions set in the virtual vehicle. Specifically, it includes: The virtual functional testing module includes a virtual functional testing environment and a basic model library; The basic model library includes vehicle drive models, braking models, and controller strategy models; Based on the functions set by the virtual vehicle, drive models, braking models, and controller strategy models are selected from the basic model library to form a combination of basic functional models. Functional tests are conducted in the virtual functional test environment to determine the parameters related to the set functions as calibration items, and the calibration values ​​of the calibration items are determined to meet the parameter value range of the set functions.

3. The hardware-in-the-loop performance calibration system for new energy vehicles according to claim 2, characterized in that, The virtual calibration module is used to determine the calibration values ​​of each calibration item and the corresponding performance data based on the calibration items and the corresponding calibration value ranges, with the performance set by the virtual vehicle as the objective and the calibration value ranges as constraints. Specifically, it includes: The virtual calibration module includes a performance model and a virtual calibration environment; Based on each calibration item type, select the corresponding performance model, input the corresponding calibration value range into the selected performance model, the performance model performs working condition cycles in the virtual calibration environment, and records the performance data of the virtual vehicle. The value corresponding to the optimal performance data of the virtual vehicle is selected as the initial calibration value of the corresponding calibration item. The calibration values ​​of all calibration items that meet the set function and have the same type of performance are cycled through the working conditions. The performance data of the virtual vehicle is recorded, and the performance data of the vehicle is compared with the performance data of the same type of vehicle obtained from the standard test. If the data difference exceeds the set difference, the initial calibration values ​​of each calibration item are adjusted one by one until the difference between the corresponding performance data of the virtual vehicle recorded during the working condition cycle and the performance data of the same type of vehicle obtained from the standard test is within the set difference. The calibration values ​​of each calibration item and the corresponding performance data are obtained.

4. The hardware-in-the-loop performance calibration system for new energy vehicles according to claim 3, characterized in that, The functions based on the virtual vehicle settings involve selecting drive models, braking models, and controller strategy models from a basic model library to form a basic functional model combination. These models are then tested in a virtual functional testing environment. Parameters related to the set functions are identified as calibration items, and the calibration values ​​for these calibration items are determined based on the parameter value ranges of the set functions. Specifically: To achieve the goal of continuous output of the virtual vehicle motor under all operating conditions, a combination of basic functional models is formed by selecting drive models, braking models, and controller strategy models from the basic model library. Functional testing is then conducted in a virtual test environment. The peak torque limit of the motor related to the continuous output of the virtual vehicle motor under all operating conditions is determined as a calibration item. The range of the peak torque limit value A to B is the calibration value range of the calibration item. The process involves selecting the appropriate performance model based on each calibration item type, inputting the corresponding calibration value range into the selected performance model, performing a cycle of operating conditions in a virtual calibration environment, recording the performance data of the virtual vehicle, and filtering out the optimal performance data of the virtual vehicle to obtain the initial calibration value for the corresponding calibration item. Specifically: The peak torque limit of the motor is determined to be an economic calibration item. Therefore, the motor thermal management model is selected as the chosen performance model from the thermal management models, as detailed below: The expression for the motor thermal management model is the formula for calculating motor heat generation: in, To generate heat for the motor, This refers to the mechanical power of the motor. The motor efficiency is obtained by looking up the table; Motor mechanical power The calculation formula is: in, This refers to the motor speed. This is the peak torque limit for the motor; motor speed n motor The calculation formula is: in, v For vehicle speed, i g This refers to the gear ratio of the transmission. i t The main reducer transmission ratio is given by r, where r is the wheel rolling radius. π Pi; Input the range A~B of the motor peak torque limit into the motor thermal management model and perform operating condition cycles in a virtual calibration environment. Record the motor heat generation of the virtual vehicle accordingly, and select the value A1 corresponding to the optimal motor heat generation of the virtual vehicle as the initial calibration value of the motor peak torque limit, where A1∈A~B.

5. The hardware-in-the-loop performance calibration system for new energy vehicles according to claim 4, characterized in that, The functions based on the virtual vehicle settings involve selecting drive models, braking models, and controller strategy models from a basic model library to form a basic functional model combination. These models are then tested in a virtual functional testing environment. Parameters related to the set functions are identified as calibration items, and the calibration values ​​for these calibration items are determined based on the parameter value ranges of the set functions. Specifically: To achieve the goal of continuous output of the virtual vehicle motor under all operating conditions, a combination of basic functional models is formed by selecting drive models, braking models, and controller strategy models from the basic model library and conducting functional tests in a virtual test environment. The transmission ratio related to the continuous output of the virtual vehicle motor under all operating conditions is determined as a calibration item, and the transmission ratio value range C~D is the calibration value range of the calibration item. The process involves selecting the appropriate performance model based on each calibration item type, inputting the corresponding calibration value range into the selected performance model, performing a cycle of operating conditions in a virtual calibration environment, recording the performance data of the virtual vehicle, and filtering out the optimal performance data of the virtual vehicle to obtain the initial calibration value for the corresponding calibration item. Specifically: Since the transmission ratio is determined to be a calibration item for economic efficiency, the motor thermal management model is selected as the chosen performance model from the thermal management models, as follows: The expression for the motor thermal management model is the formula for calculating motor heat generation: in, To generate heat for the motor, This refers to the mechanical power of the motor. The motor efficiency is obtained by looking up the table; Motor mechanical power The calculation formula is: in, This refers to the motor speed. This is the peak torque limit for the motor; motor speed n motor The calculation formula is: in, v For vehicle speed, i g This refers to the gear ratio of the transmission. i t The main reducer transmission ratio is given by r, where r is the wheel rolling radius. π Pi; Input the transmission ratio range C~D into the motor thermal management model and perform operating condition cycles in a virtual calibration environment. Record the motor heat generation of the virtual vehicle accordingly. Select the optimal motor heat generation value C1 of the virtual vehicle as the initial calibration value of the motor peak torque limit, where C1∈C~D.

6. The hardware-in-the-loop performance calibration system for new energy vehicles according to claim 5, characterized in that, The process involves cycling through all calibration items that meet the set function's performance requirements for the same type, recording the performance data of the virtual vehicle, and comparing the vehicle's performance data with the performance data of the same type of vehicle obtained from standard tests. If the data difference exceeds a set difference, the initial calibration values ​​of each calibration item are adjusted one by one until the difference between the corresponding performance data of the virtual vehicle recorded during the cycle and the performance data of the same type of vehicle obtained from standard tests is within the set difference. This yields the calibration values ​​of each calibration item and the corresponding performance data. Specifically: To meet the target function of continuous output of the virtual vehicle motor under all operating conditions, the economical calibration values ​​include the motor peak torque limit and the transmission ratio. The initial calibration values ​​A1 of the motor peak torque limit and C1 of the transmission ratio are used. The motor thermal management model is cyclically tested in a virtual calibration environment, and the motor heat generation of the virtual vehicle is recorded accordingly. This data is compared with the motor heat generation data of the vehicle obtained from standard tests. If the difference exceeds the set difference, the initial calibration values ​​A1 of the motor peak torque limit and C1 of the transmission ratio are adjusted step by step until the difference between the motor heat generation of the virtual vehicle recorded during the operating cycle and the motor heat generation of the vehicle obtained from standard tests is within the set difference. This yields the calibration values ​​of the motor peak torque limit, the transmission ratio, and the corresponding motor heat generation.

7. The hardware-in-the-loop performance calibration system for new energy vehicles according to claim 1, characterized in that, Obtain the calibration values ​​and performance data corresponding to each calibration item of the real vehicle corresponding to the virtual vehicle. Calculate the calibration difference and performance difference by comparing the calibration values ​​and performance data of each calibration item of the real vehicle with the corresponding calibration values ​​and performance data determined by the virtual vehicle calibration. If the calibration difference or performance difference exceeds a set threshold, modify the basic functional model combination and performance model combination used in the virtual vehicle simulation calibration and perform virtual simulation calibration again until the set threshold is met. This includes: Obtain the calibration values ​​and performance data of each calibration item of the real vehicle corresponding to the virtual vehicle, and calculate the calibration difference and performance difference between the calibration values ​​and performance data of each calibration item of the real vehicle and the corresponding calibration values ​​and performance data of the virtual vehicle calibration. If the difference between the corresponding calibration values ​​of the corresponding calibration items determined by the virtual vehicle calibration meets the set threshold, but the difference in performance data does not meet the set threshold; Then, based on the difference performance data, locate the basic functional model combination and the distortion model in the performance model; Adjust the parameters of the distorted model, or reload other models corresponding to the same type of virtual vehicle and perform simulation virtual calibration again until the set threshold is met; If the difference between the corresponding calibration values ​​of the corresponding calibration items determined by the virtual vehicle calibration does not meet the set threshold, but the difference between the performance data meets the set threshold; If the gradient adjustment calibration difference does not meet the set threshold, the corresponding calibration value of the calibration item will be used again for simulation virtual calibration until the set threshold is met.

8. A hardware-in-the-loop performance calibration system for new energy vehicles according to claim 2, characterized in that, The system also includes a cloud data storage module, which stores the basic functional model combination and performance model combination that have completed the virtual calibration of the whole vehicle simulation. Specifically, it is used by the same type of whole vehicle to call the basic functional model combination and performance model combination that have completed the virtual calibration of the whole vehicle simulation.

9. A method for hardware-in-the-loop performance calibration of new energy vehicles, characterized in that, Includes the following steps: To meet the functional requirements of the virtual vehicle, each calibration item and its corresponding calibration value range are determined. Based on the calibration items and the corresponding calibration value range, with the performance set by the virtual vehicle as the target and the calibration value range as the constraint, the calibration value of each calibration item and the performance data corresponding to the calibration item are determined. Obtain the calibration values ​​and performance data of each calibration item of the real vehicle corresponding to the virtual vehicle. Calculate the calibration difference and performance difference between the calibration values ​​and performance data of each calibration item of the real vehicle and the corresponding calibration values ​​and performance data of the virtual vehicle calibration. If the calibration difference or performance difference exceeds the set threshold, modify the basic functional model combination and performance model combination used in the virtual vehicle simulation calibration and perform virtual simulation calibration again until the set threshold is met.

10. A computer storage medium, wherein the computer-readable storage medium stores a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the hardware-in-the-loop performance calibration method for new energy vehicles as described in claim 9.

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