Electric power steering-by-wire intelligent test system

Abstract

The invention discloses an electric power steering-by-wire intelligent test system, and the system comprises a rotation angle and torque collection module which is used for collecting a steering wheel rotation angle and a steering wheel input torque; the motor acquisition module is used for acquiring motor information; the rack acquisition module is used for acquiring rack information; the vehicle acquisition module is used for acquiring vehicle information; the data processing module is used for processing the steering wheel angle, the steering wheel input torque, the motor information, the steering rack information and the vehicle information to generate test evaluation information; and the information sending module is used for sending the test evaluation information to a preset receiving terminal. According to the invention, comprehensive acquisition of multi-source heterogeneous data and environmental adaptability testing can be realized, and an efficient and accurate technical tool is provided for research and development optimization, quality control and engineering application of an electric power steering-by-wire system.

Description

Technical Field

[0001] The present invention relates to the field of test systems, and particularly to an intelligent test system for electric power assisted steer-by-wire. Background Art

[0002] As a core subsystem of modern intelligent vehicles, the electric power assisted steer-by-wire system replaces the traditional mechanical steering through motor assistance, significantly improving driving ease, road feel adjustability, and compatibility with autonomous driving. Its performance directly affects vehicle handling safety, comfort, and system reliability. Therefore, extremely high requirements are imposed on the comprehensiveness, accuracy, and intelligence of the test system.

[0003] Existing test technologies mainly have problems such as single data acquisition dimension, lack of environmental adaptability assessment, weak abnormal data processing ability, insufficient system-level performance analysis, and low degree of automation and intelligence. Therefore, an intelligent test system for electric power assisted steer-by-wire is proposed. Summary of the Invention

[0004] The technical problem to be solved by the present invention is: how to solve the problems of single data acquisition dimension, lack of environmental adaptability assessment, weak abnormal data processing ability, insufficient system-level performance analysis, and low degree of automation and intelligence existing in existing test technologies, and provides an intelligent test system for electric power assisted steer-by-wire.

[0005] The present invention solves the above technical problems through the following technical solutions. The present invention includes: A steering angle and torque acquisition module, which is used to acquire the steering wheel angle and the steering wheel input torque; A motor acquisition module, which is used to acquire motor information; A rack acquisition module, which is used to acquire rack information; A vehicle acquisition module, which is used to acquire vehicle information; A data processing module, which is used to process the steering wheel angle, the steering wheel input torque, the motor information, the steering rack information, and the vehicle information to generate test evaluation information; The information sending module is used to send the test evaluation information to a preset receiving terminal.

[0006] Furthermore, the specific process of the steering angle and torque acquisition module for acquiring the steering wheel angle and the steering wheel input torque is as follows: A steering wheel angle sensor and a steering wheel torque sensor are set; The steering wheel angle sensor is used to acquire the steering wheel angle θ in at least three different temperature environments; The steering wheel torque sensor is used to acquire the steering wheel input torque Td in at least three different temperature environments.

[0007] Furthermore, the specific process of processing the steering wheel angle and the steering wheel input torque to obtain the test evaluation information is as follows: Mark three different temperature environments as G1, G2, and G3. Mark the steering wheel angle θ collected in the G1 group as Qt in the order of collection time, and mark the steering wheel input torque Td collected in the G1 group as Ht in the order of collection time; Mark the steering wheel angle θ collected in the G2 group as Wt in the order of collection time, and mark the steering wheel input torque Td collected in the G2 group as Pt in the order of collection time; Mark the steering wheel angle θ collected in the G3 group as Rt in the order of collection time, and mark the steering wheel input torque Td collected in the G3 group as Zt in the order of collection time; Process Qt, Wt, and Rt to generate test evaluation information; Process Ht, Pt, and Zt to generate test evaluation information.

[0008] Furthermore, the specific process of processing Qt, Wt, and Rt to generate test evaluation information is as follows: Step 1: When the difference between the maximum value Qmax and the minimum value Qmin in Qt is greater than the preset value, directly generate the test evaluation information. At this time, the test evaluation information is that the test evaluation fails; When the difference between the maximum value Qmax and the minimum value Qmin is less than or equal to the preset value, after removing the maximum value Qmax and the minimum value Qmin in Qt, calculate the mean value of the remaining Qt to obtain the mean value of the steering wheel angle Qt of the G1 group 均 ; Step 2: When the difference between the maximum value Wmax and the minimum value Wmin in Wt is greater than the preset value, directly generate the test evaluation information. At this time, the test evaluation information is that the test evaluation fails; When the difference between the maximum value Wmax and the minimum value Wmin in Wt is less than or equal to the preset value, perform the same processing on Wt as on Qt to obtain the mean value of the steering wheel angle Wt of the G2 group 均 ; Step 3: When the difference between the maximum value Rmax and the minimum value Rmin in Rt is greater than the preset value, directly generate the test evaluation information. At this time, the test evaluation information is that the test evaluation fails; When the difference between the maximum value Rmax and the minimum value Rmin in Rt is less than or equal to the preset value, perform the same processing on Rt as on Qt to obtain the mean value of the steering wheel angle Rt of the G3 group 均 ; Step 4: When Qt 均 , Wt 均 and Rt 均When there is a value exceeding the preset range among the pairwise differences, test evaluation information is directly generated. At this time, the test evaluation information indicates that the test evaluation fails. The specific process of generating test evaluation information by processing Ht, Pt, and Zt is as follows: Step 1: When the difference between the maximum value Hmax and the minimum value Hmin in Ht is greater than the preset value, test evaluation information is directly generated. At this time, the test evaluation information indicates that the test evaluation fails. When the difference between the maximum value Hmax and the minimum value Hmin is less than or equal to the preset value, after removing the maximum value Hmax and the minimum value Hmin in Ht, calculate the mean value of the remaining Ht to obtain the mean value of the steering wheel angle Ht of Group G1 均 ; Step 2: When the difference between the maximum value Pmax and the minimum value Pmin in Pt is greater than the preset value, test evaluation information is directly generated. At this time, the test evaluation information indicates that the test evaluation fails. When the difference between the maximum value Pmax and the minimum value Pmin is less than or equal to the preset value, after removing the maximum value Pmax and the minimum value Pmin in Pt, calculate the mean value of the remaining Pt to obtain the mean value of the steering wheel angle Pt of Group G1 均 ; Step 3: When the difference between the maximum value Zmax and the minimum value Zmin in Zt is greater than the preset value, test evaluation information is directly generated. At this time, the test evaluation information indicates that the test evaluation fails. When the difference between the maximum value Zmax and the minimum value Zmin is less than or equal to the preset value, after removing the maximum value Zmax and the minimum value Zmin in Zt, calculate the mean value of the remaining Zt to obtain the mean value of the steering wheel angle Zt of Group G1 均 ; When the situations from Step 1 to Step 4 and from Step 1 to Step 3 do not exist, calculate Qt 均 、Wt 均 and Rt 均 to obtain the mean value of the steering wheel angle Qwr; Then calculate the mean values of Ht 均 、Pt 均 and Zt 均 to obtain the mean value of the steering wheel input torque Hpt; Process the mean value of the steering wheel angle Qwr and the mean value of the steering wheel input torque Hpt to obtain the steering wheel drive model, and analyze the steering wheel drive model to generate test evaluation information.

[0009] Furthermore, the process of obtaining the steering wheel drive model and the process of analyzing the steering wheel drive model to generate test evaluation information are as follows: Collect the steering wheel rotational inertia Js, the steering wheel damping coefficient Bs, the steering wheel stiffness coefficient Ks, the steering wheel angular velocity , and the steering wheel angular acceleration , as well as the steering wheel input torque Tc; When , generate test evaluation information, and at this time the test evaluation information is that the evaluation passes; When , generate test evaluation information, and at this time the test evaluation information is that the evaluation fails.

[0010] Furthermore, the specific process of processing the motor information to generate the test evaluation information is as follows: Extract the motor information, where the motor information includes the current, voltage, speed, and temperature of the motor; Continuously collect the current, voltage, speed, and temperature within a preset time period. When any one of the collected current, voltage, speed, and temperature exceeds the preset value by more than the preset number of times, generate the test evaluation information, and at this time the test evaluation information is that the test evaluation fails; When the collected current, voltage, speed, and temperature are all less than the preset value, collect the motor moment of inertia Jm, the viscous damping Bm from the motor shaft, the motor torque coefficient Kk, and the motor rotation angle , the motor angular velocity , the motor angular acceleration , the motor measured torque Tb, the auxiliary motor drive torque Ta, and mark the motor current as Im; When , generate the test evaluation information, and at this time the test evaluation information is that the test evaluation passes; When , generate the test evaluation information, and at this time the test evaluation information is that the test evaluation fails.

[0011] Furthermore, the auxiliary motor drive torque Ta is obtained through the following formula: , where G is the motor transmission ratio, Ka is the stiffness coefficient of the auxiliary motor driver, and xc is the rack displacement, that is, xc is the rack information collected by the rack information acquisition module; The motor measured torque is obtained through the following formula .

[0012] Furthermore, the specific process of processing the vehicle information to generate the test evaluation information is as follows: Extract the collected vehicle information, where the vehicle information includes the vehicle speed v, the vehicle mass m, the wheelbase L, the distance from the center of mass to the front axle a, the distance from the center of mass to the rear axle b, the total cornering stiffness of the front wheels N1, the total cornering stiffness of the rear wheels N2, the steering system transmission ratio i, and the maximum front wheel steering angle δmax; Conduct a steady-state steering characteristic evaluation of the vehicle. When the vehicle is in steady-state steering, the understeer coefficient reflects the vehicle's steering characteristics. , where g is the acceleration due to gravity; When D is within the preset range, generate test evaluation information, and at this time, the test evaluation information is that the evaluation passes; When D exceeds the preset range, generate test evaluation information, and at this time, the test evaluation information is that the evaluation fails; Then calculate the minimum turning radius value. Through the formula , obtain the minimum turning radius Jmin; When the minimum turning radius Jmin is less than or equal to the preset value, generate test evaluation information, and at this time, the test evaluation information is that the evaluation passes; When the minimum turning radius Jmin is greater than the preset value, generate test evaluation information, and at this time, the test evaluation information is that the evaluation fails; Conduct a critical speed calculation. Through the formula

[0013] When D is less than 0, compare C with the maximum design speed Cmax. When C ≤ 1.5Cmax, generate test evaluation information, and at this time, the test evaluation information is that the evaluation fails, otherwise the evaluation passes.

[0014] The present invention has the following advantages compared with the prior art: This electric power-assisted steer-by-wire intelligent test system conducts multi-dimensional data collection and environmental adaptability evaluation. Through the corner and torque collection module, motor collection module, steering rack collection module, and vehicle collection module, it comprehensively covers the steering wheel input, motor operating state, steering mechanism parameters, and vehicle dynamics parameters, ensuring full-link performance monitoring from components to the whole vehicle. Collect key data in at least three different temperature environments, which can effectively evaluate the stability of the system under extreme conditions such as high and low temperatures, and ensure reliable operation in different climate scenarios.

[0015] Intelligently process the collected data. By removing the extreme values in each temperature environment and calculating the mean value, it significantly reduces the interference of abnormal data and improves the credibility of the test results. If the data fluctuation exceeds the preset range, the system directly determines that the test fails, quickly locates component or system-level abnormalities, avoids invalid tests, and improves the problem diagnosis efficiency.

[0016] Regarding the motor operating state, the system real-time collects parameters such as current, voltage, speed, and temperature, continuously monitors whether they exceed the limit and counts the number of times of exceeding the limit, and timely discovers potential hazards such as motor overload, overheating, or abnormal speed. Combine parameters such as the motor transmission ratio and stiffness coefficient to construct a drive torque model, which can accurately evaluate the motor assistance characteristics and stability, and ensure the safety and efficiency of the electric power-assisted system.

[0017] By calculating core indicators such as the vehicle's steady-state steering characteristics, minimum turning radius, and critical vehicle speed, comprehensively analyze the handling flexibility, driving stability, and safety under extreme conditions of vehicle steering, provide data support for the optimization of the vehicle's steering system, and enhance driving safety and comfort.

[0018] By integrating data on steering wheel input, motor assistance, steering mechanism response, and vehicle dynamic characteristics, the system can verify the collaborative matching between components, ensure the consistency of the electric power-assisted steer-by-wire system in control logic, mechanical transmission, power assistance, etc., and improve system reliability and user experience from the source.

[0019] Through multi-scenario data collection, intelligent data processing, full-link performance analysis, and automated evaluation, the system provides efficient and accurate technical support for the research and development testing, quality control, and optimization design of the electric power-assisted steer-by-wire system, significantly improves the safety, reliability, and comprehensive performance of the system under complex working conditions, and makes the system more worthy of popularization and use. Brief Description of the Drawings

[0020] Figure 1 is the system block diagram of the present invention. Detailed Embodiment

[0021] The following details the embodiments of the present invention. These embodiments are implemented on the premise of the technical solution of the present invention, and provide detailed implementation methods and specific operation processes. However, the protection scope of the present invention is not limited to the following embodiments.

[0022] As Figure 1 shown, this embodiment provides a technical solution: an intelligent test system for electric power-assisted steer-by-wire, including: A steering angle and torque acquisition module for acquiring the steering wheel angle and the steering wheel input torque; A motor acquisition module for acquiring motor information; A rack acquisition module for acquiring rack information; A vehicle acquisition module for acquiring vehicle information; A data processing module for processing the steering wheel angle, the steering wheel input torque, the motor information, the steering rack information, and the vehicle information to generate test evaluation information; The information sending module is used to send the test evaluation information to a preset receiving terminal.

[0023] The specific process of the steering angle and torque acquisition module for acquiring the steering wheel angle and the steering wheel input torque is as follows: A steering wheel angle sensor and a steering wheel torque sensor are set; The steering wheel angle sensor is used to acquire the steering wheel angle θ in at least three different temperature environments; The steering wheel torque sensor is used to collect the steering wheel input torque Td under at least three different temperature environments; Covering typical working conditions such as high temperature and low temperature, it can accurately identify the influence of temperature on the sensor accuracy and the input characteristics of the steering system (such as the change of sensor sensitivity at low temperature and the torque transmission difference caused by thermal expansion of components at high temperature), ensuring the reliability of the system in extreme climates.

[0024] High-precision data acquisition: Special sensors (magnetoresistive, strain type) are used to improve the measurement resolution and anti-interference ability, avoiding the wear error of traditional mechanical sensors, and providing stable and accurate basic data for subsequent performance analysis.

[0025] Temperature sensitivity diagnosis: By comparing multi-temperature data, anomalies related to temperature can be located (such as abnormal fluctuations in torque signals in a certain temperature range), which helps to optimize sensor selection or system thermal management design during the R & D stage.

[0026] The specific process of processing the steering wheel angle and the steering wheel input torque to obtain the test evaluation information is as follows: Mark the three different temperature environments as G1, G2, and G3. Mark the steering wheel angle θ collected in the G1 group as Qt in the order of collection time, and mark the steering wheel input torque Td collected in the G1 group as Ht in the order of collection time; Mark the steering wheel angle θ collected in the G2 group as Wt in the order of collection time, and mark the steering wheel input torque Td collected in the G2 group as Pt in the order of collection time; Mark the steering wheel angle θ collected in the G3 group as Rt in the order of collection time, and mark the steering wheel input torque Td collected in the G3 group as Zt in the order of collection time; Process Qt, Wt, and Rt to generate test evaluation information; Process Ht, Pt, and Zt to generate test evaluation information; Unify the data format and grouping rules to facilitate subsequent cross-temperature and cross-condition comparative analysis (such as the difference in angle response at different temperatures under the same driving operation), improving the repeatability of test results and the engineering reference value.

[0027] Through grouping processing, abnormal data in a single temperature environment can be quickly located (such as data fluctuations exceeding the limit in a certain group), distinguishing whether it is a characteristic change caused by temperature or accidental noise, and improving the problem diagnosis efficiency.

[0028] Correspond the angle and torque data according to the same time series to facilitate the establishment of a real-time coupling relationship between the driver's input (torque) and the steering action. Combining the temperature variable, the human-machine interaction performance of the system in different environments can be deeply evaluated (such as whether the steering is heavier and the response is delayed at low temperature).

[0029] Through multi-temperature environment data acquisition and structured grouping processing, a test system covering environmental adaptability, data reliability, and performance correlation is constructed, providing key technical support for the stability evaluation and optimization of the electric power-assisted steer-by-wire system under complex working conditions.

[0030] The specific process of processing the Qt, Wt, and Rt to generate test evaluation information is as follows: Step 1: When the difference between the maximum value Qmax and the minimum value Qmin in Qt is greater than the preset value, directly generate the test evaluation information, and at this time, the test evaluation information is that the test evaluation fails; When the difference between the maximum value Qmax and the minimum value Qmin is less than or equal to the preset value, after removing the maximum value Qmax and the minimum value Qmin in Qt, calculate the mean value of the remaining Qt, and obtain the mean value of the steering wheel angle Qt of Group G1 均 ; Step 2: When the difference between the maximum value Wmax and the minimum value Wmin in Wt is greater than the preset value, directly generate the test evaluation information, and at this time, the test evaluation information is that the test evaluation fails; When the difference between the maximum value Wmax and the minimum value Wmin in Wt is less than or equal to the preset value, perform the same processing on Wt as on Qt to obtain the mean value of the steering angle Wt of Group G2 均 ; Step 3: When the difference between the maximum value Rmax and the minimum value Rmin in Rt is greater than the preset value, directly generate the test evaluation information, and at this time, the test evaluation information is that the test evaluation fails; When the difference between the maximum value Rmax and the minimum value Rmin in Rt is less than or equal to the preset value, perform the same processing on Rt as on Qt to obtain the mean value of the steering angle Rt of Group G3 均 ; Step 4: When there are values exceeding the preset range among the pairwise differences between Qt 均 , Wt 均 and Rt 均 , directly generate the test evaluation information, and at this time, the test evaluation information is that the test evaluation fails; The specific process of processing the Ht, Pt, and Zt to generate test evaluation information is as follows: Step 1: When the difference between the maximum value Hmax and the minimum value Hmin in Ht is greater than the preset value, directly generate the test evaluation information, and at this time, the test evaluation information is that the test evaluation fails; When the difference between the maximum value Hmax and the minimum value Hmin is less than or equal to the preset value, after removing the maximum value Hmax and the minimum value Hmin in Ht, calculate the mean value of the remaining Ht, and obtain the mean value of the steering wheel angle Ht of Group G1均 ; Step 2: When the difference between the maximum value Pmax and the minimum value Pmin in Pt is greater than the preset value, directly generate test evaluation information, and at this time, the test evaluation information is that the test evaluation fails; When the difference between the maximum value Pmax and the minimum value Pmin is less than or equal to the preset value, after removing the maximum value Pmax and the minimum value Pmin in Pt, calculate the mean value of the remaining Pt, and obtain the mean value of the steering wheel angle Pt of Group G1 均 ; Step 3: When the difference between the maximum value Zmax and the minimum value Zmin in Zt is greater than the preset value, directly generate test evaluation information, and at this time, the test evaluation information is that the test evaluation fails; When the difference between the maximum value Zmax and the minimum value Zmin is less than or equal to the preset value, after removing the maximum value Zmax and the minimum value Zmin in Zt, calculate the mean value of the remaining Zt, and obtain the mean value of the steering wheel angle Zt of Group G1 均 ; When the situations of Steps 1 to 4 and Steps 1 to 3 do not exist, calculate Qt 均 , Wt 均 and Rt 均 's mean value, and obtain the mean value of the steering wheel angle Qwr; Then calculate Ht 均 , Pt 均 and Zt 均 's mean value, and obtain the mean value of the steering wheel input torque Hpt; Process the mean value of the steering wheel angle Qwr and the mean value of the steering wheel input torque Hpt to obtain the steering wheel drive model, analyze the steering wheel drive model, and generate test evaluation information; The above process realizes accurate filtering of abnormal data, improves data reliability. For the corner and torque data of each group of temperature environments, first judge whether the difference between its maximum value and minimum value exceeds the limit. If it exceeds the limit, directly determine that the test fails, quickly locate sudden anomalies (such as sensor failures, signal interference); if it does not exceed the limit, calculate the mean value after removing the extreme values, effectively excluding accidental noise (such as operation jitter, instantaneous interference), ensuring the stability of the basic data, and providing a reliable basis for subsequent analysis.

[0031] Value of data purification: Avoid misjudgment caused by individual abnormal data. For example, a sudden change in the corner at a certain moment under high temperature may be misread as a system failure. By removing extreme values, the true performance can be restored, and the credibility of the test results can be improved.

[0032] Cross-temperature environment consistency assessment, exposing temperature sensitivity defects, multi-group mean comparison analysis: Calculate the mean rotation angle and mean torque under each temperature environment, and check whether the pairwise differences exceed the preset range. If significant differences occur, it indicates that the system performance is greatly affected by temperature (for example, the increase in steering resistance at low temperatures leads to an increase in the mean torque), and temperature-related design defects can be accurately located (such as the hardening of lubricating materials at low temperatures and the temperature drift of sensors).

[0033] Environmental adaptability verification: Ensure the response consistency of the steering system at different temperatures, avoid fluctuations in handling performance caused by temperature changes (such as insufficient power assistance at high temperatures and over-heavy steering at low temperatures), and meet the reliability requirements under complex climate conditions.

[0034] Steering wheel drive model integration: After excluding abnormal data and obtaining stable means, combine dynamic parameters such as the moment of inertia, damping coefficient, and stiffness coefficient of the steering wheel to construct a steering wheel drive model. This model can quantify the dynamic relationship between the driver's input (torque) and the steering output (rotation angle), and reveal potential problems in aspects such as power assistance characteristics, response delay, and stiffness matching of the system (such as the deviation between the model calculation value and the actual value, indicating errors in the power assistance algorithm or mechanical transmission).

[0035] Upgrading from single-parameter detection to multi-parameter coupling analysis. For example, by comparing the matching degree between the mean rotation angle and the mean torque of the steering wheel, judge whether the power assistance system provides reasonable auxiliary torque, avoid the imbalance between steering lightness and road feel feedback, and improve the driving experience and safety.

[0036] First, quickly exclude obvious anomalies (such as drastic data fluctuations) through simple difference judgment, then perform mean calculation and cross-group comparison, and finally complete in-depth diagnosis through the drive model. This hierarchical processing avoids complex calculations in the entire process and significantly shortens the test time, especially suitable for rapid screening in mass production testing.

[0037] The determination results at different levels can directly point to the problem type. Data exceeding the limit may correspond to sensor or hardware failures, mean differences may point to temperature sensitivity design defects, and abnormal model analysis may point to system control logic or dynamic matching problems, facilitating targeted optimization by R & D or quality inspection personnel.

[0038] The process of obtaining the steering wheel drive model and the process of analyzing the steering wheel drive model to generate test evaluation information are as follows: Collect the rotational inertia Js of the steering wheel, the damping coefficient Bs of the steering wheel, the stiffness coefficient Ks of the steering wheel, the angular velocity of the steering wheel , the angular acceleration of the steering wheel , and the input torque Tc of the steering wheel; When , generate test evaluation information, and at this time the test evaluation information is passed; When test evaluation information is generated, and at this time, the test evaluation information indicates a failed evaluation; Integrate key dynamic parameters such as the steering wheel rotation inertia, damping coefficient, and stiffness coefficient to construct a mathematical model that reflects the driver's input and the steering system response, which can quantify the dynamic coupling characteristics of steering wheel operation, power assist feedback, and mechanical transmission. For example, through the model, the impact of inertia parameters on the steering return performance can be analyzed, or the effect of the damping coefficient on the clarity of road feel feedback can be studied, avoiding the one-sidedness of relying solely on single-parameter detection.

[0039] By comparing the steering wheel input torque with the model calculation value, it is possible to evaluate whether the electric power steering system provides a reasonable auxiliary torque. For example, if the model shows a deviation between the theoretical power assist demand and the actual motor output, the logic error of the power assist algorithm or the problem of hardware transmission efficiency can be located to ensure that the power assist system achieves an optimal balance between "steering lightness" and "driver road feel".

[0040] The conclusion of passing / failing the evaluation is directly output through the model formula, avoiding the error of manual subjective judgment. For example, when the model calculation result meets the preset dynamic balance condition, it indicates that the inertia, damping, stiffness, and power assist torque of the steering wheel system are well matched and the steering operation is stable; if not, it directly exposes the defects in the design of dynamic parameters or control strategies of the system.

[0041] Precise positioning of abnormal states: The model can identify hidden problems that are difficult to detect by traditional tests, such as high-frequency vibrations caused by insufficient steering wheel stiffness and steering return delays caused by mismatched inertia parameters, providing accurate quantitative basis for optimizing the mechanical structure (such as the stiffness design of the steering column) or control algorithms (such as power assist torque compensation strategies) during the R & D stage.

[0042] Ensure that the steering wheel operation torque and the actual steering response conform to the design expectations through the model, avoiding "road feel distortion" caused by environmental changes such as temperature and vehicle speed (such as increased steering play due to excessive power assist at high speeds), improving the driver's perception accuracy of the vehicle state, and reducing the control risk.

[0043] Enhanced dynamic stability: Model analysis can optimize the damping and stiffness parameters of the steering wheel system, suppress abnormal vibrations or overshoot during steering return, ensure the steering accuracy and stability of the vehicle under conditions such as turning and lane changing, and provide reliable hardware performance guarantee for the underlying steering control of the autonomous driving assistance system in particular.

[0044] The specific process of processing the motor information to generate the test evaluation information is as follows: Extract the motor information, which includes the current, voltage, speed, and temperature of the motor; Continuously collect current, voltage, rotational speed, and temperature within a preset duration. When any one of the collected current, voltage, rotational speed, and temperature exceeds the preset value by more than the preset number of times, test evaluation information is generated, and at this time, the test evaluation information indicates that the test evaluation fails. When the collected current, voltage, rotational speed, and temperature are all less than the preset value, collect the motor moment of inertia Jm, the viscous damping Bm of the motor shaft, the motor torque coefficient Kk, and the motor rotation angle , the motor angular velocity , the motor angular acceleration , the measured motor torque Tb, the auxiliary motor drive torque Ta, and mark the motor current as Im. When , test evaluation information is generated, and at this time, the test evaluation information indicates that the test evaluation passes. When , test evaluation information is generated, and at this time, the test evaluation information indicates that the test evaluation fails. Multi-dimensional real-time monitoring to achieve early warning of motor faults Real-time collect the four key parameters of the motor: current, voltage, rotational speed, and temperature, and continuously track their fluctuations within a preset duration. It can accurately capture obvious faults such as motor overload (current exceeding limit), overheating (temperature anomaly), and rotational speed out of control, avoiding power assistance failure or steering jamming caused by motor anomalies, and ensuring system safety from the source.

[0045] By counting the number of times the parameters exceed the limit (instead of a single time exceeding the limit), distinguish accidental interference from real faults (such as short-term voltage fluctuations may be electromagnetic interference, and continuous exceeding the limit is a hardware defect), reduce the misjudgment rate, and improve the reliability of anomaly diagnosis.

[0046] Introduce dynamic parameters such as motor moment of inertia, viscous damping, and torque coefficient, combine the rack displacement (xc) and transmission ratio to construct a mathematical model of the auxiliary motor drive torque and the measured torque, and can quantitatively evaluate the matching degree between the motor power assistance output and the actual demand. For example, if the deviation between Ta calculated by the model and the measured Tb is too large, the insufficient stiffness of the motor driver or the problem of the transmission mechanism clearance can be located to ensure the accurate transmission of the power assistance torque.

[0047] Judge whether the motor drive torque meets the dynamic balance condition through the formula, directly reflecting the power assistance stability of the motor under different working conditions (such as whether the power assistance is sufficient during low-speed steering, and whether the power assistance is too strong at high speed resulting in blurred road feeling), and avoiding control risks caused by uneven power assistance (such as excessive steering causing driver fatigue, and too light power assistance causing steering out of control).

[0048] Assist failure risk control: If the motor parameter abnormality triggers a failed test determination, the system alarm can be linked in a timely manner or the standby mode can be switched to ensure that the basic steering function is still retained in case of motor failure, improving the safety of the vehicle in case of emergencies.

[0049] Embedding real-time monitoring logic on the production line can quickly eliminate products with abnormal motor parameters, preventing unqualified components from entering the market; during the R & D stage, through model analysis, the motor selection or control algorithm can be optimized, shortening the development cycle.

[0050] The correlation analysis between motor parameters and the displacement of the steering rack can verify the collaborative efficiency of motor assistance and mechanical transmission, providing data support for the overall design of the steering system (such as the stiffness of the rack and pinion, the installation position of the motor), and improving the system-level energy utilization efficiency and response speed.

[0051] The auxiliary motor drive torque Ta is obtained through the following formula: , where G is the motor transmission ratio, Ka is the stiffness coefficient of the auxiliary motor driver, xc is the rack displacement, that is, xc is the rack information collected by the rack information acquisition module; The motor measurement torque is obtained through the following formula, The above process ensures that the auxiliary torque output by the motor is synchronized in real time with the driver's operation and the actual motion state of the steering mechanism (such as rack displacement), avoiding insufficient or excessive assistance, improving the consistency of steering lightness and road feel feedback, and optimizing the handling experience under different vehicle speeds and working conditions.

[0052] By correlating the motor current, transmission characteristics and rack displacement, it can be verified in real time whether the motor assistance output meets the actual requirements of the steering system, quickly locate mechanical transmission faults (such as gear wear) or motor control abnormalities, and improve the system anomaly recognition efficiency.

[0053] Provide a standardized calculation framework for key parameters such as motor transmission ratio and driver stiffness, facilitating accurate calibration during the R & D stage and consistency calibration during mass production, reducing the difficulty of cross-component matching, and improving the reliability of system-level design.

[0054] Support dynamic adjustment of the assistance strategy according to the actual motion state of the steering mechanism to ensure the stability of the assistance torque under extreme conditions such as high temperature, low temperature, and heavy load, avoid fluctuations in handling performance caused by environmental or load changes, and strengthen the reliable operation ability of the system in complex scenarios.

[0055] The specific process of processing vehicle information to generate test evaluation information is as follows: Extract the collected vehicle information, which includes vehicle speed v, vehicle mass m, wheelbase L, distance from the center of mass to the front axle a, distance from the center of mass to the rear axle b, total cornering stiffness of the front wheels N1, total cornering stiffness of the rear wheels N2, steering system transmission ratio i, maximum front wheel steering angle δmax; Evaluate the steady-state steering characteristics of the vehicle. When the vehicle is in steady-state steering, the understeer coefficient reflects the steering characteristics of the vehicle. , where g is the acceleration due to gravity; When D is within the preset range, generate test evaluation information, and at this time, the test evaluation information is that the evaluation passes; When D exceeds the preset range, generate test evaluation information, and at this time, the test evaluation information is that the evaluation fails; Then calculate the minimum turning radius. Through the formula , obtain the minimum turning radius Jmin; When the minimum turning radius Jmin is less than or equal to the preset value, generate test evaluation information, and at this time, the test evaluation information is that the evaluation passes; When the minimum turning radius Jmin is greater than the preset value, generate test evaluation information, and at this time, the test evaluation information is that the evaluation fails; Conduct the critical speed calculation. Through the formula When D is less than 0, compare C with the maximum design speed Cmax. When C ≤ 1.5Cmax, generate test evaluation information, and at this time, the test evaluation information is that the evaluation fails, otherwise the evaluation passes; By evaluating the steady-state steering characteristics (understeer coefficient) of the vehicle, ensure that the vehicle has reasonable steering characteristics (understeer, neutral steer, or oversteer) during uniform steering, avoid driving instability caused by abnormal steering characteristics (such as the risk of side slip on high-speed curves), and improve the handling safety of the vehicle under normal working conditions.

[0056] Calculating the minimum turning radius can directly evaluate the passing ability of the vehicle in scenarios such as turning around and parking on narrow roads, ensure that the design meets the actual usage requirements, and avoid operation inconvenience or safety problems caused by too large a turning radius.

[0057] Through the critical speed calculation, analyze the stability limit of the vehicle during high-speed steering, prevent the risk of rollover or loss of control caused by the vehicle speed exceeding the critical value, especially provide a basis for safety redundancy design for high-performance vehicles or extreme driving scenarios, and improve the driving reliability under extreme working conditions.

[0058] Integrate multiple parameters such as vehicle speed, mass, and wheelbase for systematic analysis, which can comprehensively verify the matching degree of the vehicle steering system and chassis dynamics (such as whether the cornering stiffness and transmission ratio design are reasonable), provide data support for optimizing the steering system structure (such as adjusting the wheelbase and suspension parameters) or control strategy during the R & D stage, and promote the balanced improvement of the overall vehicle handling performance.

[0059] By determining whether each index meets the standard within a preset range, rapid automated evaluation of the vehicle's steering performance is achieved, which is applicable to R & D testing and mass production quality inspection scenarios, ensuring that the product meets industry standards or enterprise design specifications, reducing the cost of manual analysis, and improving the efficiency of quality control.

[0060] In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise specifically defined.

[0061] In the description of this specification, the description with reference to terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0062] Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present invention.

Claims

1. An intelligent test system for electric power steering by wire, characterized in that: include: Angle and torque acquisition module, used to collect steering wheel angle and steering wheel input torque; Motor acquisition module, used for motor information acquisition; Rack collection module, used to collect rack information; Vehicle collection module, used to collect vehicle information; A data processing module is used to process the steering wheel angle, steering wheel input torque, motor information, steering rack information, and vehicle information to generate test evaluation information; The information sending module is used to send the test evaluation information to a preset receiving terminal.

2. The electric power steering by wire intelligent test system according to claim 1, characterized in that: The specific process of the steering wheel angle and steering wheel input torque acquisition module is as follows: A steering wheel angle sensor and a steering wheel torque sensor are provided; The steering wheel angle sensor is used to collect the steering wheel angle θ under at least three different temperature environments; The steering wheel torque sensor is used to collect the steering wheel input torque Td under at least three different temperature environments.

3. The electric power steering by wire intelligent test system according to claim 2, characterized in that: The specific process of processing the steering wheel angle and steering wheel input torque to obtain the test evaluation information is as follows: The three different temperature environments are marked as G1, G2 and G3, the steering wheel angle θ collected in the G1 group is marked as Qt according to the time sequence of collection, and the steering wheel input torque Td collected in the G1 group is marked as Ht according to the time sequence of collection; The steering wheel angle θ collected in group G2 is marked as Wt in the order of time collected, and the steering wheel input torque Td collected in group G2 is marked as Pt in the order of time collected; The steering wheel angle θ collected in the G3 group is marked as Rt in the order of time collected, and the steering wheel input torque Td collected in the G3 group is marked as Zt in the order of time collected; Process Qt, Wt and Rt to generate test evaluation information; Ht, Pt and Zt are processed to generate test evaluation information.

4. The electric power steering by wire intelligent test system according to claim 3, characterized in that: The specific process of Qt, Wt and Rt processing to generate test evaluation information is as follows: Step 1: When the difference between the maximum value Qmax and the minimum value Qmin in Qt is greater than the preset value, the test evaluation information is directly generated, and the test evaluation information is that the test evaluation fails; When the difference between the maximum value Qmax and the minimum value Qmin is less than or equal to the preset value, after removing the maximum value Qmax and the minimum value Qmin in Qt, the mean of the remaining Qt is calculated to obtain the steering wheel angle mean Qt of group G1. 均 ; Step 2: When the difference between the maximum value Wmax and the minimum value Wmin in Wt is greater than the preset value, the test evaluation information is directly generated. At this time, the test evaluation information indicates that the test evaluation fails. When the difference between the maximum value Wmax and the minimum value Wmin in Wt is less than or equal to the preset value, Wt is processed in the same way as Qt to obtain the average rotation angle Wt of group G2. 均 ; Step 3: When the difference between the maximum value Rmax and the minimum value Rmin in Rt is greater than the preset value, the test evaluation information is directly generated, and the test evaluation information is that the test evaluation fails; When the difference between the maximum value Rmax and the minimum value Rmin in Rt is less than or equal to the preset value, Rt is processed in the same way as Qt to obtain the average rotation angle Rt of group G3. 均 ; Step 4: When Qt 均 , Wt 均 With Rt 均 When there is a value beyond the preset range in the difference between the two, the test evaluation information is directly generated, and the test evaluation information is that the test evaluation fails; The specific process of processing Ht, Pt and Zt to generate test evaluation information is as follows: Step 1: When the difference between the maximum value Hmax and the minimum value Hmin in Ht is greater than the preset value, the test evaluation information is directly generated, and the test evaluation information is that the test evaluation fails; When the difference between the maximum value Hmax and the minimum value Hmin is less than or equal to the preset value, the maximum value Hmax and the minimum value Hmin in Ht are removed, and the mean value of the remaining Ht is calculated to obtain the steering wheel angle mean value Ht of group G1. 均 ; Step 2: When the difference between the maximum value Pmax and the minimum value Pmin in Pt is greater than the preset value, the test evaluation information is directly generated. At this time, the test evaluation information indicates that the test evaluation fails. When the difference between the maximum value Pmax and the minimum value Pmin is less than or equal to the preset value, after removing the maximum value Pmax and the minimum value Pmin in Pt, the mean of the remaining Pt is calculated to obtain the steering wheel angle mean Pt of group G1. 均 ; Step 3: When the difference between the maximum value Zmax and the minimum value Zmin in Zt is greater than the preset value, the test evaluation information is directly generated. At this time, the test evaluation information indicates that the test evaluation fails. When the difference between the maximum value Zmax and the minimum value Zmin is less than or equal to the preset value, after removing the maximum value Zmax and the minimum value Zmin in Zt, the mean of the remaining Zt is calculated to obtain the steering wheel angle mean Zt of group G1 均 ; When steps 1 to 4 and steps 1 to 3 do not exist, calculate Qt 均 , Wt 均 With Rt 均 The mean of the steering wheel angle Qwr is obtained; Then calculate Ht 均 , Pt 均 With Zt 均 The average of the steering wheel input torque Hpt is obtained; The steering wheel angle mean Qwr and the steering wheel input torque mean Hpt are processed to obtain a steering wheel drive model, which is then analyzed to generate test evaluation information.

5. The electric power steering by wire intelligent test system according to claim 4, characterized in that: The process of obtaining the steering wheel drive model and analyzing the steering wheel drive model to generate test evaluation information is as follows: Collect steering wheel rotation inertia Js, steering wheel damping coefficient Bs, steering wheel stiffness coefficient Ks, steering wheel angular velocity , steering wheel angular acceleration , steering wheel input torque Tc; when , generate test evaluation information, at this time the test evaluation information is passed; when , generate test evaluation information, at this time the test evaluation information is evaluation failure.

6. The electric power steering by wire intelligent test system according to claim 1, characterized in that: The specific process of processing motor information and generating test evaluation information is as follows: Extract motor information, including motor current, voltage, speed and temperature; The current, voltage, speed and temperature are continuously collected within a preset time. When any one of the collected current, voltage, speed and temperature exceeds a preset value for more than a preset number of times, a test evaluation information is generated. In this case, the test evaluation information indicates that the test evaluation fails. When the collected current, voltage, speed and temperature are all less than the preset values, the motor moment of inertia Jm, motor shaft viscous damping Bm, motor torque coefficient Kk, motor angle , motor angular velocity , motor angular acceleration , the motor measured torque Tb, the auxiliary motor driving torque Ta, and the motor current is marked as Im; when , that is, generating test evaluation information, at this time the test evaluation information is that the test evaluation is passed; when , that is, generating test evaluation information, at this time the test evaluation information is that the test evaluation fails.

7. The electric power steering by wire intelligent test system according to claim 6, characterized in that: The auxiliary motor driving torque Ta is obtained by the following formula: , G is the motor transmission ratio, Ka is the auxiliary motor driver stiffness coefficient, xc is the rack displacement, that is, xc is the rack information collected by the rack information acquisition module; The motor measured torque is obtained by the following formula, .

8. The electric power steering by wire intelligent test system according to claim 1, characterized in that: The specific process of processing vehicle information and generating test evaluation information is as follows: Extract the collected vehicle information, including vehicle speed v, vehicle mass m, wheelbase L, distance from center of mass to front axle a, distance from center of mass to rear axle b, total cornering stiffness of front wheel N1, total cornering stiffness of rear wheel N2, steering system transmission ratio i, and maximum turning angle of front wheel δmax; Evaluate the vehicle's steady-state steering characteristics. When the vehicle is in steady-state steering, the understeering coefficient reflects the vehicle's steering characteristics. , g is the acceleration due to gravity; When D is within the preset range, test evaluation information is generated, and the test evaluation information is evaluated as passed; When D exceeds the preset range, test evaluation information is generated, and the test evaluation information is evaluation failure; Then calculate the minimum turning radius, through the formula , obtain the minimum turning radius Jmin; When the minimum turning radius Jmin is less than or equal to the preset value, the test evaluation information is generated, and the test evaluation information is evaluated as passed; When the minimum turning radius Jmin is greater than the preset value, the test evaluation information is generated, and the test evaluation information is evaluation failure; Calculate the critical speed using the formula ; When D is less than 0, C is compared with the maximum design vehicle speed Cmax. When C≤1.5Cmax, test evaluation information is generated. At this time, the test evaluation information indicates that the evaluation failed, otherwise the evaluation passed.

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