A hardware-in-the-loop calibration platform and method for chassis electronic control systems

Abstract

This application relates to a hardware-in-the-loop (HIL) calibration platform and method for a chassis electronic control system. The chassis domain control HiL bench includes an electronically controlled suspension HiL bench, a braking HiL bench, and a steering HiL bench. A host computer has a model that matches the subjective evaluation items with respect to the objective test items. The host computer runs the chassis domain control HiL bench, acquires data from the bench test items, treats these test items as objective test items, and combines them with the model to obtain data for subjective evaluation items. Based on this data, key items are selected from the calibration items corresponding to the objective test items in the chassis electronic control system. These key items are used as calibration variables. Based on the value range of the key items and the model, the optimization objective is to achieve the optimal value for the subjective evaluation items. This process yields data for all calibration items and the optimal value for the subjective evaluation items. This application enables multi-system interaction in the chassis and aligns with actual user scenarios.

Description

Technical Field

[0001] This application relates to the field of chassis electronic control system calibration technology, and in particular to a hardware-in-the-loop chassis electronic control system calibration platform and method. Background Technology

[0002] In recent years, chassis electronic control systems have been developing towards coordinated lateral, longitudinal, and vertical motion control. The controllers of various chassis electronic control systems are gradually being integrated into chassis domain controllers. Against this backdrop, the calibration of chassis electronic control systems has gradually become an important part of the development of independent algorithms.

[0003] Currently, chassis electronic control system calibration is mostly based on real vehicle testing. This calibration method results in time-consuming and labor-intensive development of chassis electronic control systems, high costs, insufficient safety, and significant seasonal influences (such as winter calibration), and often fails to achieve the desired calibration results.

[0004] Chassis electronic control system calibration based on HiL (Hardware in the Loop) bench provides a new approach to solving the above problems.

[0005] However, various drawbacks exist when using the HiL bench technology mentioned above.

[0006] For example, solutions based on the chassis electronic control HiL test bench and driving simulator suffer from excessively high equipment investment costs and overly complex system setup. Meanwhile, while drivers can conduct subjective tests to evaluate the steering system's performance and functionality through human perception, the accuracy of these subjective assessments is limited by the driving simulator's response bandwidth, resulting in low reliability.

[0007] For example, the HiL chassis electronic control bench is a single-system bench, which cannot meet the requirements for the development of chassis lateral, longitudinal and vertical coordinated motion control. Moreover, the aforementioned single system cannot accurately represent multi-system interaction scenarios, which does not match the actual vehicle usage scenarios of users. Summary of the Invention

[0008] This application provides a hardware-in-the-loop chassis electronic control system calibration platform and method, which realizes multi-system interaction of the chassis and conforms to the actual vehicle use scenarios of users.

[0009] Firstly, a hardware-in-the-loop chassis electronic control system calibration platform is provided, which includes:

[0010] The chassis domain control HiL test bench includes an electronically controlled suspension HiL test bench, a braking HiL test bench, and a steering HiL test bench. The electronically controlled suspension HiL test bench, the braking HiL test bench, and the steering HiL test bench are connected by hard wires for clock synchronization.

[0011] A host computer, having a storage module, pre-stores a subjective evaluation item corresponding to an objective test item consistency model. The host computer is connected to the electronic suspension HiL test bench, braking HiL test bench, and steering HiL test bench, and is used to drive the chassis domain control HiL test bench to operate, acquire test bench test item data, treat the test bench test items as objective test items, and combine them with the subjective evaluation consistency model to obtain subjective evaluation item data. Based on the subjective evaluation item data, at least a portion of the calibration items corresponding to the objective test items in the chassis electronic control system are selected as key items, and the key items are used as calibration variables. Based on the value range of the key items and the subjective evaluation consistency model, with the subjective evaluation item reaching its optimal value as the optimization objective, the data of all calibration items and the optimal value of the subjective evaluation item are obtained.

[0012] In some embodiments, one of the electronically controlled suspension HiL test bench, braking HiL test bench, and steering HiL test bench is equipped with an analog signal acquisition board. This analog signal acquisition board is connected to a PFI pin, which is connected to the PFI pins of the other two via the hardwire.

[0013] In some embodiments, the electronically controlled suspension HiL test bench, braking HiL test bench, and steering HiL test bench are all embedded with reflective memory cards, and each of the reflective memory cards is connected via optical fiber.

[0014] In some embodiments, the electronically controlled suspension HiL test bench includes an electronically controlled suspension HiL cabinet, a left front excitation platform, a right front excitation platform, a left rear excitation platform, and a right rear excitation platform;

[0015] The first sensor is installed on the left front excitation platform, the right front excitation platform, the left rear excitation platform, and the right rear excitation platform.

[0016] The electronically controlled suspension HiL cabinet is used to send suspension travel commands to the left front excitation platform, right front excitation platform, left rear excitation platform and right rear excitation platform, and to receive the suspension force detected by the first sensor.

[0017] In some embodiments, the braking HiL test bench includes an electrically controlled braking HiL cabinet, and a stepper motor, a brake pedal, a brake master cylinder, a brake wheel cylinder, and a caliper connected in sequence;

[0018] A second sensor is mounted on the caliper;

[0019] The electronically controlled braking HiL cabinet is used to send brake pedal travel commands to the stepper motor and receive the caliper clamping force detected by the second sensor.

[0020] In some embodiments, the braking HiL stand includes a wire-controlled braking HiL cabinet, and a stepper motor, a brake pedal, a wiring harness, and a motor brake caliper connected in sequence.

[0021] A second sensor is installed on the motor brake caliper;

[0022] The HiL control cabinet is used to send brake pedal travel commands to the stepper motor and receive the caliper clamping force detected by the second sensor.

[0023] In some embodiments, the steering HiL test bench includes an electronically controlled steering HiL cabinet, and a servo motor, steering column, intermediate shaft, steering gear and tie rod connected in sequence;

[0024] A third sensor is installed on the tie rod to detect the rack displacement stroke in order to obtain the tie rod displacement.

[0025] The HiL electronic steering cabinet is used to send steering wheel angle or torque input commands to the servo motor and receive rack displacement stroke detected by the third sensor.

[0026] In some embodiments, the steering HiL bench includes a steer-by-wire HiL cabinet, and a servo motor, steering column, wiring harness, steering gear and tie rod connected in sequence;

[0027] A third sensor is installed on the tie rod to detect the rack displacement stroke in order to obtain the tie rod displacement.

[0028] The HiL steer-by-wire cabinet is used to send steering wheel angle or torque input commands to the servo motor and receive rack displacement stroke detected by the third sensor.

[0029] In some embodiments, the subjective evaluation item's correspondence model with respect to the objective detection item includes one or more of the subjective evaluation correspondence model under steady-state conditions and the subjective evaluation correspondence model under transient conditions.

[0030] In some embodiments, the subjective evaluation item corresponding to the objective test item in a consistent subjective evaluation model includes one or more of the following: a subjective evaluation model with vehicle handling stability as the subjective evaluation item, a subjective evaluation model with vehicle ride comfort as the subjective evaluation item, and a subjective evaluation model with vehicle braking performance as the subjective evaluation item.

[0031] In some embodiments, the objective test items include a first objective test item for characterizing the vehicle's handling stability, a second objective test item for characterizing the vehicle's ride comfort, and a third objective test item for characterizing the vehicle's braking performance.

[0032] In some embodiments, the first objective detection item includes one or more of the following: yaw rate gain, steering sensitivity, understeer, vehicle pitch gradient, and vehicle roll gradient.

[0033] The second objective test item includes one or more of the following: the root mean square value of vertical acceleration at the front and rear seat rails, the root mean square value of pitch angle acceleration at the fenders, and the peak-to-peak value of longitudinal acceleration at the seat rails.

[0034] The third objective test item includes one or more of the following: brake pedal travel at 0.1g deceleration, brake pedal force at 0.1g deceleration, braking distance with reaction time, and braking distance without reaction time.

[0035] In some embodiments, among all the calibration items, at least a portion of the calibration items constitute calibration items for an electronically controlled suspension system, at least a portion of the calibration items constitute calibration items for an electronically controlled braking system, and at least a portion of the calibration items constitute calibration items for an electronically controlled steering system.

[0036] Of all the calibration items, those determined in the loop based on the MiL model constitute Class A calibration sub-items, and the remaining calibration items constitute Class B calibration sub-items.

[0037] In some embodiments, the Class A calibration sub-items include the weighting coefficient of the arbitration module in the semi-active suspension control algorithm, the pulse control unsprung acceleration limit value, the solenoid valve current protection limit value, the switching coefficient of the state estimation module in the vehicle stability control algorithm, the slip ratio threshold value of the drive anti-slip function, and the assist coefficient table in the steering basic assist algorithm;

[0038] The Class B calibration sub-items include threshold coefficients related to subjective feelings, which include turning control force, return-to-center accuracy, steering wheel impact, and brake pedal feel.

[0039] Secondly, a hardware-in-the-loop calibration method for chassis electronic control systems is provided, which includes:

[0040] Drive the chassis domain control HiL test bench to run in order to obtain data from the test bench items;

[0041] The bench test items are used as objective test items, and the subjective evaluation items are called in accordance with the objective evaluation correspondence model of the objective test items to obtain the data of the subjective evaluation items.

[0042] Based on the data of the subjective evaluation items, at least a portion of the calibration items corresponding to the objective test items in the chassis electronic control system are selected as key items;

[0043] Using the key items as calibration variables, and based on the value range of the key items and the consistency model of subjective and objective evaluation, with the optimal value of the subjective evaluation item as the optimization objective, the data of all calibration items and the optimal value of the subjective evaluation item are obtained.

[0044] In some embodiments, the method further includes the step of constructing a model for the correspondence between subjective evaluation items and objective detection items, which includes:

[0045] Obtain samples, which include objective test items and subjective evaluation items of the chassis electronic control system of the actual vehicle;

[0046] Based on the sample, a model for consistency between subjective and objective evaluations is constructed.

[0047] In some embodiments, the subjective evaluation item corresponds to the objective detection item in a consistent model, including a subjective evaluation item correspondence model under steady-state conditions.

[0048] Based on the aforementioned samples, a model for consistency between subjective and objective evaluations is constructed, specifically including:

[0049] Based on the samples, a second-order response surface model is constructed using a polynomial fitting method to obtain a model that corresponds to both subjective and objective evaluations.

[0050] In some embodiments, the subjective evaluation item corresponds to the objective detection item in a consistent model, including a subjective evaluation item correspondence model under transient conditions.

[0051] Based on the aforementioned samples, a model for consistency between subjective and objective evaluations is constructed, specifically including:

[0052] Construct a convolutional neural network model;

[0053] The samples are input into the convolutional neural network model and iteratively trained to obtain a model that corresponds to both subjective and objective evaluations.

[0054] In some embodiments, the accuracy of the model corresponding to the subjective and objective evaluations is verified;

[0055] If the accuracy does not meet the requirements, a model that aligns subjective and objective evaluations will be reconstructed.

[0056] In some embodiments, the model for reconstructing the consistency between subjective and objective evaluations is specifically included in the following ways:

[0057] Increase the number of samples and continue training until the accuracy meets the requirements.

[0058] In some embodiments, based on the data from the subjective evaluation items, at least a portion of the calibration items corresponding to the objective test items in the chassis electronic control system are selected as critical items, specifically including:

[0059] Based on the data of the aforementioned subjective evaluation items, a multi-factor analysis was performed to generate an analysis graph;

[0060] Using the analysis chart, at least a portion of the calibration items corresponding to the objective test items in the chassis electronic control system are selected as critical items.

[0061] In some embodiments, the analysis graph includes one or more of the following: Pareto graph, correlation graph, main effect graph, and interaction effect graph.

[0062] The beneficial effects of the technical solution provided in this application include:

[0063] This application provides a hardware-in-the-loop (HIL) chassis electronic control system calibration platform and method, which realizes multi-system interaction of the chassis and conforms to the actual vehicle use scenarios of users. By constructing a chassis domain control HiL bench including an electronic suspension HiL bench, a braking HiL bench, and a steering HiL bench, and by using hardwire to connect the electronic suspension HiL bench, the braking HiL bench, and the steering HiL bench to achieve clock synchronization, this application can realize multi-system interaction of the chassis, thereby conforming to the actual vehicle use scenarios of users. Attached Figure Description

[0064] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0065] Figure 1 A schematic diagram of a hardware-in-the-loop chassis electronic control system calibration platform provided for embodiments of this application;

[0066] Figure 2 This is a schematic diagram of the HiL electronically controlled suspension test bench provided in an embodiment of this application;

[0067] Figure 3 A schematic diagram of the electrically controlled braking HiL test bench provided in an embodiment of this application;

[0068] Figure 4 A schematic diagram of the HiL drive-by-wire braking test bench provided in an embodiment of this application;

[0069] Figure 5 A schematic diagram of the HiL electronic steering bench provided in the embodiments of this application;

[0070] Figure 6 A schematic diagram of the HiL (High-Lane) steering bench provided in an embodiment of this application;

[0071] Figure 7 A flowchart illustrating the hardware-in-the-loop calibration method for a chassis electronic control system provided in this application embodiment. Detailed Implementation

[0072] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0073] See Figure 1 As shown in the figure, this application provides a hardware-in-the-loop chassis electronic control system calibration platform, which includes a chassis domain controller HiL test bench and a host computer.

[0074] The chassis domain control HiL test bench includes an electronically controlled suspension HiL test bench, a braking HiL test bench, and a steering HiL test bench. The electronically controlled suspension HiL test bench, the braking HiL test bench, and the steering HiL test bench are connected by hardwire for clock synchronization. The hardwire can be a common type of cable, such as an SMA cable.

[0075] The host computer has a storage module that pre-stores a model showing the correspondence between subjective evaluation items and objective test items. The host computer is connected to the electronic suspension HiL test bench, braking HiL test bench, and steering HiL test bench, and is used to drive the chassis domain control HiL test bench to operate, acquire data of the test bench test items, treat the test bench test items as objective test items, and combine them with the model showing the correspondence between subjective and objective evaluation items to obtain data of subjective evaluation items. Based on the data of subjective evaluation items, at least a portion of the calibration items corresponding to the objective test items in the chassis electronic control system are selected as key items. The key items are used as calibration variables. Based on the value range of the key items and the model showing the correspondence between subjective and objective evaluation items, the optimal value of the subjective evaluation items is taken as the optimization objective, and the data of all calibration items and the optimal value of the subjective evaluation items are obtained.

[0076] The hardware-in-the-loop chassis electronic control system calibration platform provided in this application embodiment, on the one hand, constructs a chassis domain control HiL bench including an electronic suspension HiL bench, a braking HiL bench, and a steering HiL bench, and on the other hand, uses hard wiring to connect the electronic suspension HiL bench, the braking HiL bench, and the steering HiL bench to achieve clock synchronization, ensuring that this application can realize multi-system interaction of the chassis, thereby conforming to the actual vehicle use scenarios of users.

[0077] On the other hand, the chassis electronic control system includes the electronic suspension system, electronic braking system, and electronic steering system. In software development, the chassis electronic control system has many parameters that need to be calibrated, which are called calibration items. These calibration items directly affect the chassis electronic control system, and the results of this influence can be directly detected by sensors. These results of the influence corresponding to the calibration items are called objective detection items. When this influence of the chassis electronic control system directly affects the driver and passengers, the subjective feelings of the driver and passengers can be quantified by scoring. These quantified subjective feelings are called subjective evaluation items.

[0078] Based on this, this application directly uses existing subjective evaluation items and objective test items obtained from real vehicle testing to form a consistent model of subjective and objective evaluation. Then, it runs the HiL chassis domain control bench to obtain bench test item data. Combining this with the consistent model of subjective and objective evaluation, the subjective evaluation item data can be calculated. Since the value range of the calibration items (i.e., upper and lower limits) is available in advance, adjusting the calibration item data within this range can affect the bench test item data, and consequently, the calculated subjective evaluation item data. Therefore, when running the HiL chassis domain control bench, the subjective evaluation item data can be calculated multiple times by adjusting the calibration item data. By analyzing this data, key items can be identified. Using these key items as calibration variables, and combining their value ranges with the consistent model of subjective and objective evaluation, with the goal of achieving the optimal value for the subjective evaluation item, the data for all calibration items and the optimal value for the subjective evaluation item can be obtained.

[0079] Using the above methods, the subjective feelings of drivers and passengers were quantified. During the calibration process, drivers and passengers did not need to actually experience the driving experience through a driving simulator. This not only eliminated the need for a driving simulator and reduced the complexity of system construction, but also avoided the problem that the accuracy of the driver's subjective feelings was limited by the response bandwidth of the driving simulator, resulting in low reliability of the driver's subjective feelings. This improved the reliability of subjective feelings.

[0080] Furthermore, since this application divides all calibration items into critical items that have a significant impact on subjective perception and the remaining non-critical items that have a relatively small impact on subjective perception, during calibration, non-critical items that have a relatively small impact on subjective perception can be directly assigned values ​​from their respective value ranges, while critical items are calibrated with emphasis to obtain specific values. In the end, the specific values ​​of the assigned non-critical items and the calibrated items are output, which greatly reduces the complexity of calibration and improves calibration efficiency.

[0081] Understandably, compared to actual vehicle calibration, the improved calibration efficiency of this application is not only due to reduced workload, but also because it is not limited by time, location, or environment. HiL bench calibration is essentially a simulation, which can be performed at any time, in any place, and under any environment.

[0082] It is understandable that the subjective-objective evaluation correspondence consistency model refers to the carrier that describes the mapping process between subjective evaluation items and objective evaluation items; the consistency of the model means that when data of the same or similar objective evaluation items are input into the subjective-objective evaluation correspondence consistency model, the data of the output subjective evaluation items changes almost unchanged or slightly.

[0083] It is understandable that the aforementioned host computer can connect to the electronically controlled suspension HiL test bench, braking HiL test bench, and steering HiL test bench via a router or other means.

[0084] To achieve clock synchronization triggering, in this application, one of the electronic suspension HiL test bench, braking HiL test bench, and steering HiL test bench is equipped with an analog signal acquisition board. This analog signal acquisition board is connected to a PFI pin, which is connected to the PFI pins of the other two via a hardwired connection. The hardwired connection is configured in the Veristand project. The analog signal acquisition board can be selected from various models, such as the PXI6220 analog signal acquisition board.

[0085] The clock synchronization trigger signal is generated by one digital signal port of the analog signal acquisition board.

[0086] As an example, see Figure 1 As shown, the analog signal acquisition board is installed in the electric control brake cabinet of the brake HiL test bench.

[0087] Further, see Figure 1 As shown, the electronically controlled suspension HiL test bench, braking HiL test bench, and steering HiL test bench all have embedded reflective memory cards, and each reflective memory card is connected via optical fiber. The reflective memory cards enable real-time data sharing between the various systems, improving data transmission speed and ensuring system real-time performance.

[0088] See Figure 2The diagram shows an exemplary HiL (High-Low) electronic suspension test bench constructed according to this application. The HiL test bench includes an HiL control cabinet, a left front excitation platform, a right front excitation platform, a left rear excitation platform, and a right rear excitation platform. Each excitation platform is used to simulate the suspension force and suspension travel changes. Each of the left front, right front, left rear, and right rear excitation platforms is equipped with a first sensor, which detects the suspension force. The HiL control cabinet is used to send suspension travel commands to the left front, right front, left rear, and right rear excitation platforms and receive the suspension force detected by the first sensors, thereby associating the excitation platforms with the cabinet to form a closed-loop system.

[0089] See Figure 3 As shown, this is an exemplary brake HiL test bench constructed in this application. The brake HiL test bench is an electrically controlled brake HiL test bench. The brake HiL test bench includes an electrically controlled brake HiL cabinet, and a stepper motor, brake pedal, brake master cylinder, brake wheel cylinder and caliper connected in sequence. A second sensor is installed on the caliper. The electrically controlled brake HiL cabinet is used to send brake pedal travel commands to the stepper motor and receive the caliper clamping force detected by the second sensor.

[0090] The HiL control cabinet sends a brake pedal travel command, the stepper motor actuates the brake pedal, and pushes the master cylinder to build up oil pressure in the hydraulic line. The caliper is equipped with a force sensor, and the whole vehicle braking simulation is closed-loop by collecting the clamping force.

[0091] See Figure 4 As shown, this is an exemplary braking HiL test bench constructed in this application. The braking HiL test bench is a brake-by-wire HiL test bench, which includes a brake-by-wire HiL cabinet and a stepper motor, a brake pedal, a wiring harness, and a motor brake caliper connected in sequence. A second sensor is installed on the motor brake caliper to detect the caliper clamping force. The brake-by-wire HiL cabinet is used to send brake pedal travel commands to the stepper motor and receive the caliper clamping force detected by the second sensor, thereby realizing a closed loop for vehicle braking simulation.

[0092] See Figure 5 The diagram shows an exemplary steering HiL test bench constructed in this application. This steering HiL test bench is an electronically controlled steering HiL test bench, which includes an electronically controlled steering HiL cabinet and a servo motor, steering column, intermediate shaft, steering gear, and tie rod connected in sequence. A third sensor is installed on the tie rod to detect the rack displacement stroke in order to obtain the tie rod displacement. The electronically controlled steering HiL cabinet is used to send steering wheel angle input or torque input commands to the servo motor and receive the rack displacement stroke detected by the third sensor.

[0093] The HiL electronic steering cabinet sends steering wheel angle or torque input commands, the servo motor responds, and the steering wheel input is simulated. The input passes through the steering column, intermediate shaft, steering gear and tie rod, and the tie rod displacement is output. The displacement sensor collects the rack displacement stroke to realize the closed loop of the whole vehicle steering simulation.

[0094] See Figure 6 The image shows an exemplary steering HiL test bench constructed in this application. This steering HiL test bench is a steer-by-wire HiL test bench, which includes a steer-by-wire HiL cabinet and a servo motor, steering column, wiring harness, steering gear, and tie rod connected in sequence. A third sensor is installed on the tie rod to detect the rack displacement stroke to obtain the tie rod displacement. The steer-by-wire HiL cabinet is used to send steering wheel angle input or torque input commands to the servo motor and receive the rack displacement stroke detected by the third sensor.

[0095] It is understandable that, since the chassis electronic control system has steady-state and transient operating conditions during the calibration process, the subjective evaluation item corresponding to the objective test item in this application includes one or more of the subjective evaluation corresponding to the objective test item under steady-state conditions and the subjective evaluation corresponding to the objective test item under transient conditions.

[0096] It is understandable that in the model where subjective evaluation items correspond to objective test items in a consistent manner, there are multiple subjective evaluation items involved. For example, as an example, vehicle handling stability can be used as a subjective evaluation item, vehicle ride comfort can be used as a subjective evaluation item, and vehicle braking performance can be used as a subjective evaluation item.

[0097] Therefore, in this application, the subjective evaluation item corresponding to the objective test item is consistent with one or more of the subjective evaluation items corresponding to the objective test item, including the subjective evaluation item corresponding to the vehicle handling stability, the subjective evaluation item corresponding to the vehicle ride comfort, and the subjective evaluation item corresponding to the vehicle braking performance.

[0098] By combining the types of operating conditions (steady-state and transient) and the types of subjective evaluation items (vehicle handling stability, vehicle ride comfort, and vehicle braking performance), six consistent models of subjective and objective evaluation can be formed.

[0099] It is understood that, corresponding to the types of subjective evaluation items, the objective test items include a first objective test item for characterizing the vehicle's handling stability, a second objective test item for characterizing the vehicle's ride comfort, and a third objective test item for characterizing the vehicle's braking performance.

[0100] As an example, the first objective detection item includes one or more of the following: yaw rate gain, steering sensitivity, understeer, vehicle pitch gradient, and vehicle roll gradient.

[0101] The second objective test item includes one or more of the following: the root mean square value of vertical acceleration at the front and rear seat rails, the root mean square value of pitch angle acceleration at the fenders, and the peak-to-peak value of longitudinal acceleration at the seat rails.

[0102] The third objective test item includes one or more of the following: brake pedal travel at 0.1g deceleration, brake pedal force at 0.1g deceleration, braking distance with reaction time, and braking distance without reaction time.

[0103] Since the chassis electronic control system includes the electronic suspension system, the electronic braking system, and the electronic steering system, the electronic suspension system has a number of calibration items, the electronic braking system has a number of calibration items, and the electronic steering system has a number of calibration items. That is, among all the calibration items, at least some of the calibration items constitute the electronic suspension system calibration items, at least some of the calibration items constitute the electronic braking system calibration items, and at least some of the calibration items constitute the electronic steering system calibration items.

[0104] Whether it's the calibration items that make up the calibration items for the electronically controlled suspension system, the electronically controlled braking system, or the electronically controlled steering system, each of these three categories can be further divided into two subcategories: Category A calibration items and Category B calibration items. Category A calibration items are determined based on the MIL model in-loop, while the remaining items are Category B calibration items. In other words, among all calibration items, those determined based on the MIL model in-loop constitute Category A calibration items, and the remaining items constitute Category B calibration items.

[0105] For example, the Class A calibration sub-items include the weighting coefficient of the arbitration module in the semi-active suspension control algorithm, the limit value of unsprung acceleration of pulse control, the limit value of current protection of solenoid valve, the switching coefficient of the state estimation module in the vehicle stability control algorithm, the slip ratio threshold value of the drive anti-slip function, and the assist coefficient table in the steering basic assist algorithm; these can be added or reduced according to actual needs.

[0106] The Class B calibration sub-items include threshold coefficients related to subjective feelings, such as turning control force, return-to-center accuracy, steering wheel impact, and brake pedal feel. These can be increased or decreased according to actual needs.

[0107] Based on the aforementioned hardware-in-the-loop chassis electronic control system calibration platform, this application also provides a hardware-in-the-loop chassis electronic control system calibration method, see [link to relevant documentation]. Figure 7 As shown, it includes the following steps:

[0108] 101: Drive the chassis domain controller HiL test bench to run in order to obtain data of the test bench items.

[0109] 102: Treat the bench test items as objective test items, and call the subjective evaluation item's objective-subject evaluation correspondence consistency model to obtain the subjective evaluation item's data. Adjust the calibration item's data within the calibration item's value range, obtain the bench test item's data multiple times, and back-calculate the subjective evaluation item's data multiple times.

[0110] 103: Based on the data of the subjective evaluation items, at least a portion of the calibration items corresponding to the objective test items in the chassis electronic control system are selected as key items.

[0111] 104: Using the key items as calibration variables, based on the value range of the key items and the consistency model of subjective and objective evaluation, with the optimal value of the subjective evaluation item as the optimization objective, an intelligent multi-objective optimization method is used to perform global optimization, obtain the data of all calibration items and the optimal value of the subjective evaluation item, and finally output the specific values ​​of each calibration item and the optimal value of the subjective evaluation item in the form of a list.

[0112] It is understandable that intelligent multi-objective optimization methods include, but are not limited to, second-generation non-neighborhood cultivation genetic algorithms.

[0113] It is understandable that the value range of the above calibration items (i.e., the upper and lower limits) can be obtained in advance. Since there are multiple calibration items, the methods for obtaining the value range of different calibration items may not be the same. Therefore, various methods can be used to obtain them. For example, as an example, the methods for setting the upper and lower limits of calibration items include, but are not limited to, the actual physical meaning of the calibration items, the range determined by MIL model-in-the-loop simulation, the value range set during the software development stage, scaling a single initial value by ±50%, etc.

[0114] Preferably, the method provided in this application further includes the step of constructing a model for the correspondence between subjective evaluation items and objective detection items, which includes:

[0115] 201: Obtain samples, which include objective test items and subjective evaluation items of the chassis electronic control system of the actual vehicle.

[0116] In step 201, the above samples are objective detection items and subjective evaluation items obtained from real vehicle testing. The model is constructed using the samples obtained from real vehicle testing, making the model more objective and accurate.

[0117] 202: Based on the sample, construct a model that corresponds to the subjective and objective evaluation.

[0118] In step 202, the above samples are used to construct the relevant model components according to the model type.

[0119] Specifically, as mentioned above, by combining the types of operating conditions (steady-state and transient operating conditions) and the types of subjective evaluation items (vehicle handling stability, vehicle ride comfort, and vehicle braking performance), six consistent models of subjective and objective evaluation can be formed.

[0120] When the subjective evaluation item corresponds to the objective evaluation item in a consistent model, which is a consistent model of subjective and objective evaluation under steady-state conditions, a consistent model of subjective and objective evaluation is constructed based on the sample, specifically including:

[0121] Based on the samples, a second-order response surface model is constructed using a polynomial fitting method to obtain a model that corresponds to both subjective and objective evaluations.

[0122] For example, as an example, a second-order response surface model is as follows:

[0123]

[0124] In the formula, y represents the subjective evaluation term, and x1, ..., x2 represent the subjective evaluation terms. i x j ... x M For objective detection items, β0, ..., β 2M β ij These are the weighting coefficients.

[0125] It is evident that a polynomial fitting method is used to establish a consistent model between subjective and objective evaluations under steady-state operating conditions.

[0126] When the subjective evaluation item corresponds to the objective evaluation item in a consistent model, which is a consistent model of subjective and objective evaluation under transient conditions, a consistent model of subjective and objective evaluation is constructed based on the sample, specifically including:

[0127] 301: Construct a convolutional neural network model.

[0128] 302: Input the sample into the convolutional neural network model and perform iterative training to obtain a model that corresponds to both subjective and objective evaluations.

[0129] It is evident that a convolutional neural network method is adopted for a model that corresponds to both subjective and objective evaluations under transient operating conditions.

[0130] After completing step 202 above and establishing the model, accuracy testing can be performed to ensure the accuracy of the model during evaluation. Specifically, accuracy testing includes the following steps:

[0131] 401: Perform accuracy verification on the model that corresponds to the subjective and objective evaluations.

[0132] 402: If the accuracy meets the requirements, it can be used directly; if the accuracy does not meet the requirements, a model that corresponds to both subjective and objective evaluations should be reconstructed.

[0133] The above accuracy requirement can be understood as follows: input the data of objective inspection items of the actual vehicle that are not used in the model construction into the model to obtain the data of the calculated subjective evaluation items. Compare the data of the calculated subjective evaluation items with the data of the subjective evaluation items corresponding to the objective inspection items of the actual vehicle. If the difference is within the preset difference range, the requirement is met; otherwise, the requirement is not met. The above difference can be the absolute value of the difference between the two, or the ratio between the two, etc. The above preset difference range can be set in advance.

[0134] In step 402 above, the model for reconstructing the consistency between subjective and objective evaluations is reconstructed, specifically including:

[0135] Increase the number of samples and continue training until the accuracy meets the requirements.

[0136] In other words, we can add objective testing items and subjective evaluation items obtained from real vehicle testing to continue training.

[0137] When conducting the above-mentioned accuracy tests, it is advisable to prepare more objective test items and subjective evaluation items obtained from actual vehicle tests as samples for accuracy verification.

[0138] For example, as an example, the samples used to build the model account for 70% of the total samples, while the samples used for accuracy verification account for 30% of the total samples.

[0139] In step 103 above, based on the data of the subjective evaluation items, at least a portion of the calibration items corresponding to the objective test items in the chassis electronic control system are selected as key items, specifically including:

[0140] 501: Based on the data of the aforementioned subjective evaluation items, perform multifactor analysis to generate an analysis graph. The analysis graph includes one or more of the following: Pareto graph, correlation graph, main effect graph, and interaction effect graph.

[0141] 502: Using the analysis chart, select at least a portion of the calibration items corresponding to the objective test items in the chassis electronic control system as critical items, and lock the value range of the critical items.

[0142] In step 502, all the calibration items are divided into critical items that have a significant impact on subjective feelings and the remaining non-critical items that have a relatively small impact on subjective feelings. When screening and dividing, a mapping relationship between subjective evaluation items and calibration items is established. By drawing the above analysis diagram, the important critical items can be directly obtained. The above analysis diagram will give the influence weight percentage of each calibration item. For example, as an example, the calibration items with an influence weight percentage of more than 40% are selected as critical items.

[0143] As mentioned earlier, all calibration items are divided into calibration items for electronically controlled suspension systems, calibration items for electronically controlled braking systems, and calibration items for electronically controlled steering systems, with each category containing multiple calibration items.

[0144] For each calibration item in the electronically controlled suspension system calibration items, as elements of the test matrix, many different software data schemes can be combined.

[0145] Similarly, the various calibration items in the calibration items of the electric braking system can be combined into many different software data schemes.

[0146] The various calibration items in the electronic steering system calibration items can also be combined into many different software data schemes.

[0147] If all calibration tests were performed, the workload would be substantial. By employing methods including but not limited to optimal Latin hypercube design, Latin hypercube design, orthogonal experimental design, and parametric experimental design, an experimental matrix is ​​designed as a data scheme. These schemes drive the calibration platform of this application to generate test data as objective test items. These data are then substituted into the subjective-objective evaluation correspondence model to generate subjective evaluation data. As can be seen, this application designs a finite data scheme after consuming a large amount of data, and performs calibration tests on the finite data scheme, thereby reducing the calibration workload.

[0148] In summary, this application utilizes reflective memory cards and fiber optic communication to cascade and integrate the electronic suspension HiL test bench, steering HiL test bench, and braking HiL test bench, thereby constructing a chassis domain control HiL test bench and building a vehicle-level HiL testing environment. This improves the testing accuracy of the chassis electronic control system. The aforementioned chassis domain control HiL test bench is not only suitable for the development of traditional chassis electronic control systems, but also for the development of drive-by-wire chassis technology and chassis domain control technology.

[0149] This application establishes a model that includes consistent subjective and objective evaluation indicators for vehicle handling stability, vehicle ride comfort, and vehicle braking performance. The model is divided into two parts: one part is steady-state, which is characterized by specific indicators, and the other part is transient, which is described by curves in the entire time domain or frequency domain. This improves the application effect of the consistent subjective and objective evaluation model in HiL bench calibration, while significantly reducing the investment cost of bench calibration and is not affected by the response bandwidth of the driving simulator.

[0150] This application identifies the key components and value ranges of the chassis electronic control system on the HiL chassis domain control bench, reducing the workload of subsequent real vehicle testing and calibration, and significantly lowering the development cost of the chassis electronic control system.

[0151] In the description of this application, it should be noted that the terms "upper," "lower," etc., indicating the orientation or positional relationship are based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this application. Unless otherwise expressly specified and limited, the terms "installed," "connected," and "linked" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication between two elements. For those skilled in the art, the specific meaning of the above terms in this application can be understood according to the specific circumstances.

[0152] It should be noted that in this application, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0153] The above description is merely a specific embodiment of this application, enabling those skilled in the art to understand or implement this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A hardware-in-the-loop calibration platform for a chassis electronic control system, characterized in that, It includes: The chassis domain control HiL test bench includes an electronically controlled suspension HiL test bench, a braking HiL test bench, and a steering HiL test bench. The electronically controlled suspension HiL test bench, the braking HiL test bench, and the steering HiL test bench are connected by hard wires for clock synchronization. A host computer, having a storage module, pre-stores a model showing the correspondence between subjective evaluation items and objective test items. The host computer is connected to the electronically controlled suspension HiL test bench, braking HiL test bench, and steering HiL test bench, and is used to drive the chassis domain control HiL test bench to operate, acquire data from the test bench test items, treat these test bench test items as objective test items, and, in conjunction with the model showing the correspondence between subjective and objective evaluation items, obtain data from subjective evaluation items. Based on this data, at least a portion of the calibration items corresponding to the objective test items in the chassis electronic control system are selected as key... For key items, the key items are used as calibration variables. Based on the value range of the key items and the consistency model between subjective and objective evaluations, the optimization objective is to achieve the optimal value of the subjective evaluation item. Data of all calibration items and the optimal value of the subjective evaluation item are obtained. All calibration items are divided into key items that have a significant impact on subjective feelings and the remaining non-key items that have a smaller impact on subjective feelings. When calibrating, non-key items that have a smaller impact on subjective feelings can be directly assigned values ​​from their corresponding value ranges. Key items are calibrated in detail to obtain specific values. The specific values ​​of the assigned non-key items and the calibrated items are then output.

2. The chassis electronic control system calibration platform based on hardware-in-the-loop as described in claim 1, characterized in that: Of the electronically controlled suspension HiL test bench, braking HiL test bench, and steering HiL test bench, one of them is equipped with an analog signal acquisition board. This analog signal acquisition board is connected to a PFI pin, which is connected to the PFI pins of the other two via the hard wire.

3. The chassis electronic control system calibration platform based on hardware-in-the-loop as described in claim 1, characterized in that: The electronically controlled suspension HiL test bench, braking HiL test bench, and steering HiL test bench are all equipped with reflective memory cards, and each of the reflective memory cards is connected via optical fiber.

4. The chassis electronic control system calibration platform based on hardware-in-the-loop as described in claim 1, characterized in that: The electronically controlled suspension HiL test bench includes an electronically controlled suspension HiL cabinet, a left front excitation platform, a right front excitation platform, a left rear excitation platform, and a right rear excitation platform. The first sensor is installed on the left front excitation platform, the right front excitation platform, the left rear excitation platform, and the right rear excitation platform. The electronically controlled suspension HiL cabinet is used to send suspension travel commands to the left front excitation platform, right front excitation platform, left rear excitation platform and right rear excitation platform, and to receive the suspension force detected by the first sensor.

5. The chassis electronic control system calibration platform based on hardware-in-the-loop as described in claim 1, characterized in that: The braking HiL test bench includes an electrically controlled braking HiL cabinet, and a stepper motor, brake pedal, brake master cylinder, brake wheel cylinder and caliper connected in sequence; A second sensor is mounted on the caliper; The electronically controlled braking HiL cabinet is used to send brake pedal travel commands to the stepper motor and receive the caliper clamping force detected by the second sensor.

6. The chassis electronic control system calibration platform based on hardware-in-the-loop as described in claim 1, characterized in that: The braking HiL test bench includes a wire-controlled braking HiL cabinet, and a stepper motor, brake pedal, wiring harness and motor brake caliper connected in sequence; A second sensor is installed on the motor brake caliper; The HiL control cabinet is used to send brake pedal travel commands to the stepper motor and receive the caliper clamping force detected by the second sensor.

7. The chassis electronic control system calibration platform based on hardware-in-the-loop as described in claim 1, characterized in that: The steering HiL test bench includes an electronically controlled steering HiL cabinet, and a servo motor, steering column, intermediate shaft, steering gear and tie rod connected in sequence; A third sensor is installed on the tie rod to detect the rack displacement stroke in order to obtain the tie rod displacement. The HiL electronic steering cabinet is used to send steering wheel angle or torque input commands to the servo motor and receive rack displacement stroke detected by the third sensor.

8. The chassis electronic control system calibration platform based on hardware-in-the-loop as described in claim 1, characterized in that: The steering HiL bench includes a wire-controlled steering HiL cabinet, and a servo motor, steering column, wiring harness, steering gear and tie rod connected in sequence; A third sensor is installed on the tie rod to detect the rack displacement stroke in order to obtain the tie rod displacement. The HiL steer-by-wire cabinet is used to send steering wheel angle or torque input commands to the servo motor and receive rack displacement stroke detected by the third sensor.

9. The chassis electronic control system calibration platform based on hardware-in-the-loop as described in claim 1, characterized in that: The subjective evaluation item corresponds to the objective evaluation item in a consistent model, which includes one or more of the subjective and objective evaluation consistency models under steady-state conditions and the subjective and objective evaluation consistency models under transient conditions.

10. The chassis electronic control system calibration platform based on hardware-in-the-loop as described in claim 1, characterized in that: The subjective evaluation items correspond to the objective test items in a consistent model, including one or more of the following: a subjective evaluation model with vehicle handling stability as the subjective evaluation item, a subjective evaluation model with vehicle ride comfort as the subjective evaluation item, and a subjective evaluation model with vehicle braking performance as the subjective evaluation item.

11. The chassis electronic control system calibration platform based on hardware-in-the-loop as described in claim 1, characterized in that: The objective test items include a first objective test item for characterizing the vehicle's handling stability, a second objective test item for characterizing the vehicle's ride comfort, and a third objective test item for characterizing the vehicle's braking performance.

12. The chassis electronic control system calibration platform based on hardware-in-the-loop as described in claim 11, characterized in that: The first objective test item includes one or more of the following: yaw rate gain, steering sensitivity, understeer, vehicle pitch gradient, and vehicle roll gradient. The second objective test item includes one or more of the following: the root mean square value of vertical acceleration at the front and rear seat rails, the root mean square value of pitch angle acceleration at the fenders, and the peak-to-peak value of longitudinal acceleration at the seat rails. The third objective test item includes one or more of the following: brake pedal travel at 0.1g deceleration, brake pedal force at 0.1g deceleration, braking distance with reaction time, and braking distance without reaction time.

13. The chassis electronic control system calibration platform based on hardware-in-the-loop as described in claim 1, characterized in that: Of all the calibration items, at least some of the calibration items constitute calibration items for electronically controlled suspension systems, at least some of the calibration items constitute calibration items for electronically controlled braking systems, and at least some of the calibration items constitute calibration items for electronically controlled steering systems. Of all the calibration items, those determined in the loop based on the MiL model constitute Class A calibration sub-items, and the remaining calibration items constitute Class B calibration sub-items.

14. The chassis electronic control system calibration platform based on hardware-in-the-loop as described in claim 13, characterized in that: The Class A calibration sub-items include the weighting coefficient of the arbitration module in the semi-active suspension control algorithm, the limit value of unsprung acceleration of pulse control, the limit value of current protection of solenoid valve, the switching coefficient of the state estimation module in the vehicle stability control algorithm, the slip ratio threshold value of the drive anti-slip function, and the assist coefficient table in the steering basic assist algorithm. The Class B calibration sub-items include threshold coefficients related to subjective feelings, which include turning control force, return-to-center accuracy, steering wheel impact feel, and brake pedal feel.

15. A calibration method for a chassis electronic control system based on hardware-in-the-loop, characterized in that, It includes: Drive the chassis domain control HiL test bench to run in order to obtain data of the test bench items; The bench test items are used as objective test items, and the subjective evaluation items are called in accordance with the objective evaluation correspondence model of the objective test items to obtain the data of the subjective evaluation items. Based on the data of the subjective evaluation items, at least a portion of the calibration items corresponding to the objective test items in the chassis electronic control system are selected as key items. Using the critical items as calibration variables, based on the value range of the critical items and the model that corresponds to the subjective and objective evaluations, and taking the optimal value of the subjective evaluation items as the optimization objective, we obtain the data of all calibration items and the optimal value of the subjective evaluation items. All calibration items are divided into critical items that have a significant impact on subjective perception and non-critical items that have a relatively small impact on subjective perception. During calibration, non-critical items with a relatively small impact on subjective perception can be directly assigned values ​​from their respective value ranges. Calibrating critical items is carried out in detail to obtain specific values. The specific values ​​of the assigned non-critical items and the calibrated items are then output.

16. The chassis electronic control system calibration method based on hardware-in-the-loop as described in claim 15, characterized in that, The method further includes the step of constructing a model for the correspondence between subjective evaluation items and objective detection items, which includes: Obtain samples, which include objective test items and subjective evaluation items of the chassis electronic control system of the actual vehicle; Based on the sample, a model for consistency between subjective and objective evaluations is constructed.

17. The chassis electronic control system calibration method based on hardware-in-the-loop as described in claim 16, characterized in that: The subjective evaluation item corresponds to the objective detection item in a consistent model, including the subjective and objective evaluation correspondence model under steady-state conditions. Based on the aforementioned samples, a model for consistency between subjective and objective evaluations is constructed, specifically including: Based on the samples, a second-order response surface model is constructed using a polynomial fitting method to obtain a model that corresponds to both subjective and objective evaluations.

18. The chassis electronic control system calibration method based on hardware-in-the-loop as described in claim 16, characterized in that: The subjective evaluation item corresponds to the objective test item in a consistent model, including the subjective and objective evaluation correspondence model under transient conditions. Based on the aforementioned samples, a model for consistency between subjective and objective evaluations is constructed, specifically including: Construct a convolutional neural network model; The samples are input into the convolutional neural network model and iteratively trained to obtain a model that corresponds to both subjective and objective evaluations.

19. The chassis electronic control system calibration method based on hardware-in-the-loop as described in claim 16, characterized in that: Accuracy verification is performed on the model that corresponds to both subjective and objective evaluations. If the accuracy does not meet the requirements, a model that aligns subjective and objective evaluations will be reconstructed.

20. The chassis electronic control system calibration method based on hardware-in-the-loop as described in claim 19, characterized in that, Reconstructing the consistency model between subjective and objective evaluations, specifically including: Increase the number of samples and continue training until the accuracy meets the requirements.

21. The chassis electronic control system calibration method based on hardware-in-the-loop as described in claim 15, characterized in that, Based on the data from the subjective evaluation items, at least a portion of the calibration items corresponding to the objective testing items in the chassis electronic control system are selected as critical items, specifically including: Based on the data of the aforementioned subjective evaluation items, a multi-factor analysis was performed to generate an analysis graph; Using the analysis chart, at least a portion of the calibration items corresponding to the objective test items in the chassis electronic control system are selected as critical items.

22. The chassis electronic control system calibration method based on hardware-in-the-loop as described in claim 21, characterized in that: The analysis graphs include one or more of the following: Pareto graph, correlation graph, main effect graph, and interaction effect graph.

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