Machining compensation system and method suitable for vehicle domain controller shell

Abstract

The invention provides a machining compensation system and method suitable for a vehicle domain controller shell, and the method comprises the steps: carrying out the error fusion of a thermal deformation displacement vector, a friction force vector and a path deviation vector of a numerical control machine tool, and obtaining a coupling deviation value of each error source of the numerical control machine tool in the machining of the vehicle domain controller shell; performing optimization compensation on trust domain parameters of a servo control ring in the numerical control machine tool based on each coupling deviation value to obtain a compensation matrix of the numerical control machine tool under the current working condition, and determining a machining compensation instruction of the numerical control machine tool through the compensation matrix; and the machining compensation instruction is input to each axis servo driving unit in the numerical control machine tool, the numerical control machine tool is controlled to execute machining compensation, a multi-dimensional error source of the numerical control machine tool is monitored circularly and continuously in the machining compensation process, and then error compensation of machining of the vehicle domain controller shell is achieved. Based on the above scheme, real-time fusion of multi-source errors and adaptive optimization compensation of servo ring parameters can be realized.

Description

Technical Field

[0001] This application relates to the field of CNC machine tool processing technology, and more specifically, to a machining compensation system and method applicable to the housing of a vehicle domain controller. Background Technology

[0002] CNC machine tools are automated equipment that uses digital signals to precisely control the movement of the machine tool and its machining process. By analyzing the machining program through the CNC system, the servo axes and spindle of the machine tool are driven to move in coordination, thereby realizing high-precision and high-efficiency cutting, drilling, milling and other machining operations on workpieces made of metal and other materials. It is the core foundation of modern manufacturing.

[0003] Traditional CNC machine tools maintain fixed servo control loop parameters after initial tuning during the initial debugging phase. This static parameter configuration strategy struggles to adapt to the drift in system dynamic characteristics caused by changes in machine tool thermal distribution, tool cutting edge wear, and differences in workpiece material and cutting parameters during dynamic machining. Fixed gain cannot consistently guarantee the optimal response characteristics of the servo system under varying operating conditions. Consequently, in high-speed, high-precision machining scenarios, the tracking error of the position loop and the disturbance rejection performance of the speed loop cannot always remain within their optimal range, thus hindering further improvement and stability of overall machining accuracy. Therefore, achieving real-time fusion of multi-source errors and adaptive optimization compensation of servo loop parameters to improve the position control stability of CNC machine tools during dynamic machining has become a challenge for the industry. Summary of the Invention

[0004] This application provides a machining compensation system and method for the housing of a vehicle domain controller, which can realize real-time fusion of multi-source errors and adaptive optimization compensation of servo loop parameters, thereby improving the position control stability of CNC machine tools during dynamic machining.

[0005] In a first aspect, this application provides a machining compensation method for the housing of a vehicle domain controller, comprising the following steps: Mathematical modeling is performed on the multi-dimensional error sources of CNC machine tool machining of the vehicle domain controller shell, and the thermal deformation displacement vector, friction force vector and path deviation vector of CNC machine tool are obtained respectively. The multi-dimensional error sources include the thermal deformation error, dynamic friction error and geometric path error of CNC machine tool. The thermal deformation displacement vector, the friction force vector, and the path deviation vector are fused to obtain the coupling deviation values ​​of each error source in the machining of the vehicle domain controller shell by the CNC machine tool, thereby determining the error state value of the CNC machine tool in the machining of the vehicle domain controller shell. When the error state value is greater than the standard machining error of the CNC machine tool, the trust domain parameters of the servo control loop in the CNC machine tool are optimized and compensated based on the values ​​of each coupling deviation to obtain the compensation matrix of the CNC machine tool under the current working condition. Then, the position command, speed command and acceleration command of the CNC machine tool are compensated in three levels through the compensation matrix to obtain the machining compensation command of the CNC machine tool. The machining compensation command is input to the servo drive unit of each axis in the CNC machine tool to control the CNC machine tool to perform machining compensation. During the machining compensation, the multi-dimensional error sources of the CNC machine tool are continuously monitored in a loop, thereby compensating for the error in the machining of the vehicle domain controller shell.

[0006] In some embodiments, mathematical modeling is performed on the multi-dimensional error sources of the CNC machine tool in the machining of the vehicle domain controller housing, specifically obtaining the thermal deformation displacement vector, friction force vector, and path deviation vector of the CNC machine tool: A linear mapping relationship between thermal deformation and temperature rise is established based on the temperature rise data of various temperature monitoring points in the CNC machine tool, thereby obtaining the thermal deformation displacement vector of the CNC machine tool; Using the current and speed signals of the servo drive unit in the CNC machine tool, the nonlinear friction force is calculated through the dynamic friction model of parameter identification, and then the friction force vector of the CNC machine tool is obtained. Based on the geometric error elements measured by the laser interferometer, a model of the spatial position deviation between the tool and the workpiece in the machine tool motion chain is constructed, thereby obtaining the path deviation vector of the CNC machine tool.

[0007] In some embodiments, the error fusion of the thermal deformation displacement vector, the friction force vector, and the path deviation vector to obtain the coupling deviation values ​​of each error source in the machining of the vehicle domain controller shell by the CNC machine tool specifically includes: The thermal deformation displacement vector, the friction force vector, and the path deviation vector are spatiotemporally registered and then unified to the same timestamp and machine tool coordinate system. For each error source, obtain the deviation value of the error source and determine the coupling mapping coefficient of other error sources in the multi-dimensional error sources to the current error source. By fusing and correcting the deviation values ​​using various coupling mapping coefficients, the coupling deviation values ​​of the error sources in the machining of the vehicle domain controller shell by the CNC machine tool are obtained, and then the coupling deviation values ​​of each error source in the machining of the vehicle domain controller shell by the CNC machine tool are obtained.

[0008] In some embodiments, determining the error state value of the CNC machine tool during the machining of the vehicle domain controller housing specifically includes: Obtain the coupling deviation values ​​of each error source in the machining of the vehicle domain controller shell by CNC machine tool; Based on the values ​​of various coupling deviations, fuzzy inference is performed on the machining error in the machining of the vehicle domain controller shell to obtain the fuzzy subset of error sources in the machining of the vehicle domain controller shell. The machining error in the machining of the vehicle domain controller shell is defuzzified by the fuzzy subset of the error sources, and the error state value of the CNC machine tool in the machining of the vehicle domain controller shell is obtained.

[0009] In some embodiments, the trust domain parameters of the servo control loop in the CNC machine tool are optimized and compensated based on the values ​​of various coupling deviations to obtain the compensation matrix of the CNC machine tool under the current working condition. Specifically, this includes: The position loop proportional gain, velocity loop proportional gain, and velocity loop integral gain of the servo control loop are defined as trust domain parameters to be optimized. With the goal of minimizing the values ​​of each coupling deviation, a parameter compensation model for the CNC machine tool under the current working conditions is established. The parameter compensation model is used to iteratively converge the parameters of each trust domain, thereby obtaining the compensation matrix of the CNC machine tool under the current working condition.

[0010] In some embodiments, the position commands, speed commands, and acceleration commands of the CNC machine tool are subjected to three-level cascade compensation through the compensation matrix to obtain the machining compensation commands of the CNC machine tool, specifically including: The acceleration command of the CNC machine tool is fed forward using the velocity loop proportional gain in the compensation matrix to obtain the acceleration compensation command of the CNC machine tool. The speed command of the CNC machine tool is adjusted by the acceleration compensation command and the speed loop integral gain in the compensation matrix to obtain the speed compensation command of the CNC machine tool. The position command of the CNC machine tool is proportionally adjusted by using the position loop proportional gain in the compensation matrix to obtain the position compensation command of the CNC machine tool. The machining compensation command for the CNC machine tool is determined based on the acceleration compensation command, the speed compensation command, and the position compensation command.

[0011] In some embodiments, the servo control loop is a three-loop nested controller based on a composite control of instruction domain feedforward and feedback.

[0012] Secondly, this application provides a machining compensation system for a vehicle domain controller housing, used to execute a machining compensation method for a vehicle domain controller housing, comprising an error compensation unit, the error compensation unit including: The error modeling module is used to mathematically model the multi-dimensional error sources of CNC machine tools in the machining of the shell of the vehicle domain controller, and obtain the thermal deformation displacement vector, friction force vector and path deviation vector of the CNC machine tool respectively. The multi-dimensional error sources include the thermal deformation error, dynamic friction error and geometric path error of the CNC machine tool. The processing module is used to perform error fusion of the thermal deformation displacement vector, the friction force vector and the path deviation vector to obtain the coupling deviation values ​​of each error source in the machining of the vehicle domain controller shell by the CNC machine tool, and then determine the error state value of the CNC machine tool in the machining of the vehicle domain controller shell. The processing module is also used to optimize and compensate the trust domain parameters of the servo control loop in the CNC machine tool based on the values ​​of each coupling deviation when the error state value is greater than the standard machining error of the CNC machine tool, so as to obtain the compensation matrix of the CNC machine tool under the current working condition, and then perform three-level series compensation on the position command, speed command and acceleration command of the CNC machine tool through the compensation matrix to obtain the machining compensation command of the CNC machine tool. The execution module is used to input the machining compensation command to the servo drive unit of each axis in the CNC machine tool, control the CNC machine tool to perform machining compensation, and continuously monitor the multi-dimensional error sources of the CNC machine tool in a loop during machining compensation, thereby compensating for the error of the machining of the shell of the vehicle domain controller.

[0013] Thirdly, this application provides a computer device including a memory and a processor, the memory storing code, and the processor being configured to acquire the code and execute the above-described machining compensation method for a vehicle domain controller housing.

[0014] Fourthly, this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described machining compensation method for a vehicle domain controller housing.

[0015] The technical solutions provided by the embodiments disclosed in this application have the following beneficial effects: This application provides a machining compensation system and method for vehicle domain controller housings. It mathematically models multi-dimensional error sources of CNC machine tools during the machining of the vehicle domain controller housing, obtaining the thermal deformation displacement vector, friction force vector, and path deviation vector of the CNC machine tool. These multi-dimensional error sources include thermal deformation error, dynamic friction error, and geometric path error of the CNC machine tool. The system then fuses these errors to obtain the coupling deviation values ​​of each error source during the machining of the vehicle domain controller housing, thereby determining the error state of the CNC machine tool during the machining of the vehicle domain controller housing. When the error state value is greater than the standard machining error of the CNC machine tool, the trust domain parameters of the servo control loop in the CNC machine tool are optimized and compensated based on the values ​​of each coupling deviation to obtain the compensation matrix of the CNC machine tool under the current working condition. Then, the position command, speed command and acceleration command of the CNC machine tool are compensated in three levels through the compensation matrix to obtain the machining compensation command of the CNC machine tool. The machining compensation command is input to the servo drive unit of each axis in the CNC machine tool to control the CNC machine tool to perform machining compensation. In the machining compensation, the multi-dimensional error sources of the CNC machine tool are continuously monitored in a loop to compensate for the error of the machining of the shell of the vehicle domain controller.

[0016] Therefore, in this application, the machining compensation command is input to the servo drive units of each axis in the CNC machine tool to control the CNC machine tool to perform machining compensation. During machining compensation, the multi-dimensional error sources of the CNC machine tool are continuously monitored in a loop, thereby compensating for the error in the machining of the vehicle domain controller shell. First, determining the error state value yields a dynamic evaluation index characterizing the overall accuracy degradation of the machine tool, thus providing a precise decision-making basis for triggering and guiding adaptive compensation. By integrating thermal deformation, friction, and geometric path into a single scalar value, the one-sidedness of compensation decisions caused by viewing a single error source in isolation in traditional control is avoided. This error state value, as a high-order characteristic quantity, can sensitively perceive and respond to the complexities between different error sources. The complex interactions mean that CNC machine tools no longer rely on a single error threshold, but instead assess a global precision health status. When this error status exceeds the limit, the CNC machine tool issues a quantitative command that clearly indicates that the current machining accuracy has deviated from the optimal working range. This ensures that subsequent parameter optimization and compensation are neither initiated too frequently to increase the computational load, nor too sluggish to miss the best compensation opportunity, thus guaranteeing the accuracy and timeliness of adaptive control decisions. Then, by determining the machining compensation command, a set of dynamic control sequences that have undergone feedforward and feedback composite correction and are precisely matched with the current error mode can be obtained, thereby realizing online reshaping and precise compensation of the gain characteristics and dynamic response of the servo loop. By applying the optimized velocity loop gain to the acceleration feedforward, the CNC machine tool's ability to suppress dynamic inertial disturbances is effectively improved. Furthermore, applying the optimized position loop gain and integral element to the velocity and position commands directly corrects the bandwidth and stiffness of the servo loop. The CNC machine tool outputs a control strategy that dynamically adjusts the entire servo unit based on the real-time identified error characteristics, ensuring it remains in an optimal or near-optimal operating state. This significantly enhances the CNC machine tool's position tracking capability and anti-interference stability under complex conditions of varying loads and temperatures, thereby improving the position control stability of the CNC machine tool during dynamic machining. In summary, based on the above scheme, real-time fusion of multi-source errors and adaptive optimization compensation of servo loop parameters can be achieved, thus improving the position control stability of the CNC machine tool during dynamic machining. Attached Figure Description

[0017] Figure 1 This is an exemplary flowchart illustrating a machining compensation method for a vehicle domain controller housing according to some embodiments of this application; Figure 2 This is an exemplary flowchart illustrating the determination of the compensation matrix according to some embodiments of this application; Figure 3 This is a schematic diagram of the structure of an error compensation unit according to some embodiments of this application; Figure 4This is a schematic diagram of the structure of a computer device that implements a machining compensation method applicable to the housing of a vehicle domain controller, according to some embodiments of this application. Detailed Implementation

[0018] To better understand the technical solution of this application, the technical solution of this application will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0019] refer to Figure 1 The figure is an exemplary flowchart of a machining compensation method for a vehicle domain controller housing according to some embodiments of this application. The figure mainly includes the following steps: In step 101, a mathematical model is performed on the multi-dimensional error sources of the CNC machine tool in the machining of the vehicle domain controller shell, and the thermal deformation displacement vector, friction force vector and path deviation vector of the CNC machine tool are obtained respectively. The multi-dimensional error sources include the thermal deformation error, dynamic friction error and geometric path error of the CNC machine tool.

[0020] It should be noted that, in this application, the multi-dimensional error sources include thermal deformation error, dynamic friction error, and geometric path error of the CNC machine tool.

[0021] In some embodiments, mathematical modeling of the multi-dimensional error sources in the machining of the vehicle domain controller housing by a CNC machine tool, and obtaining the thermal deformation displacement vector, friction force vector, and path deviation vector of the CNC machine tool, can be achieved through the following steps: A linear mapping relationship between thermal deformation and temperature rise is established based on the temperature rise data of various temperature monitoring points in the CNC machine tool, thereby obtaining the thermal deformation displacement vector of the CNC machine tool; Using the current and speed signals of the servo drive unit in the CNC machine tool, the nonlinear friction force is calculated through the dynamic friction model of parameter identification, and then the friction force vector of the CNC machine tool is obtained. Based on the geometric error elements measured by the laser interferometer, a model of the spatial position deviation between the tool and the workpiece in the machine tool motion chain is constructed, thereby obtaining the path deviation vector of the CNC machine tool.

[0022] It should be noted that, in this application, the thermal deformation displacement vector is a set of displacements in the machine tool coordinate system that quantify the structural deformation of the CNC machine tool caused by temperature rise in terms of magnitude and direction; the friction force vector is a set of force values ​​in the respective axial direction of the nonlinear resistance experienced by each servo axis transmission system of the CNC machine tool during motion; and the path deviation vector is a set of six-degree-of-freedom errors that describe the position and orientation deviation of the actual tool center point of the CNC machine tool relative to the ideal tool center point in the workpiece coordinate system.

[0023] In specific implementation, firstly, a linear mapping relationship between thermal deformation and temperature rise is established based on the temperature rise data of various temperature monitoring points in the CNC machine tool. The resulting thermal deformation displacement vector of the CNC machine tool can be achieved as follows: Multiple temperature sensors pre-installed at temperature monitoring points on the CNC machine tool spindle bearing, ball screw nut seat, and bed are used to collect real-time temperature rise data during machine tool operation. Based on the finite element thermodynamic analysis results of the machine tool structure, a linear regression model is established that maps the temperature rise data of each measuring point to the displacement of the machine tool spindle tip or moving parts. The coefficient matrix of this linear regression model is identified using the least squares method through machine tool idle temperature rise tests and thermal drift data measured by a laser tracker. In real-time control, the acquired temperature rise data vector is input into the identified linear mapping model, and the calculated three-dimensional displacement vector is the thermal deformation displacement vector. Therefore, the three-dimensional displacement vector output by the model is used as the thermal deformation displacement vector for that control cycle. Then, using the current and speed signals of the servo drive unit in the CNC machine tool, the nonlinear friction force is calculated through the parameter-identified dynamic friction model, thus obtaining the friction force vector of the CNC machine tool. This can be achieved by: real-time reading of the motor current and speed signals fed back by the servo drive unit inside the CNC machine tool, where the current signal is proportional to the motor torque; and using a dynamic friction model capable of describing pre-slip and the Stribek effect. As a basic model framework, specific parameters of the dynamic friction model are offline fitted using a model parameter identification algorithm by having each servo axis perform specific uniform and directional motion tests, synchronously recording current and speed data. In real-time control, the speed signal of the current servo axis is input into the parameterized dynamic friction model, and the nonlinear friction force estimate corresponding to the motion state is calculated in real time. The vector formed by combining the nonlinear friction force estimates calculated by each servo axis is then used as the friction force vector for that control cycle. Finally, based on the geometric error elements measured by the laser interferometer, a tool and workpiece spatial pose deviation model of the machine tool kinematic chain is constructed, thus obtaining the path deviation vector of the CNC machine tool. The above method is implemented as follows: using precision measuring instruments such as laser interferometers and ballbars, before the machine tool is put into use, offline measurements are taken to obtain various geometric error elements, including the positioning error, straightness error, angular error, and perpendicularity error of each linear axis; based on multibody system theory, the mechanical structure of the CNC machine tool is abstracted into a kinematic chain composed of a series of rigid bodies connected by kinematic pairs, and the ideal motion transformation matrix from the machine tool bed to the tool and from the machine tool bed to the workpiece, and the actual motion transformation matrix containing the geometric error elements obtained from the above measurements are established using the homogeneous coordinate transformation method; by calculating the difference between the ideal transformation and the actual transformation, a spatial pose deviation model between the tool and the workpiece is constructed.In real-time control, based on the theoretical position commands of each axis, the comprehensive error of the tool center is calculated in real time using this spatial pose deviation model. This results in a six-degree-of-freedom error vector containing three linear deviations and three angular deviations, which is then used as the path deviation vector for that control cycle.

[0024] In step 102, the thermal deformation displacement vector, the friction force vector, and the path deviation vector are fused to obtain the coupling deviation values ​​of each error source in the machining of the vehicle domain controller shell by the CNC machine tool, thereby determining the error state value of the CNC machine tool in the machining of the vehicle domain controller shell.

[0025] In some embodiments, the following steps can be used to fuse the thermal deformation displacement vector, the friction force vector, and the path deviation vector to obtain the coupling deviation values ​​of each error source in the machining of the vehicle domain controller housing by a CNC machine tool: The thermal deformation displacement vector, the friction force vector, and the path deviation vector are spatiotemporally registered and then unified to the same timestamp and machine tool coordinate system. For each error source, obtain the deviation value of the error source and determine the coupling mapping coefficient of other error sources in the multi-dimensional error sources to the current error source. By fusing and correcting the deviation values ​​using various coupling mapping coefficients, the coupling deviation values ​​of the error sources in the machining of the vehicle domain controller shell by the CNC machine tool are obtained, and then the coupling deviation values ​​of each error source in the machining of the vehicle domain controller shell by the CNC machine tool are obtained.

[0026] It should be noted that, in this application, the coupling deviation value is a composite error value that reflects the current accuracy state of the CNC machine tool; the deviation value is a scalar value that characterizes the degree of influence of various types of error sources on the machining accuracy at the current moment. The types of error sources include thermal deformation, friction, and geometric path; the coupling mapping coefficient is a set of proportional factors that quantify the degree to which the change in one error source triggers a correlated change in another error source among multi-dimensional error sources.

[0027] In specific implementation, firstly, the thermal deformation displacement vector, the friction force vector, and the path deviation vector are spatiotemporally registered and then unified to the same timestamp and machine tool coordinate system. This can be achieved in the following way: A central data buffer is established to receive the thermal deformation displacement vector, friction force vector, and path deviation vector. The central data buffer uses a unified real-time clock as a reference, timestamps all input vectors, and uses an interpolation algorithm to extrapolate vectors arriving at different times to a common control cycle time point; all vectors are then converted to the workpiece coordinate system of the CNC machine tool. The thermal deformation displacement vector and path deviation vector are already defined in this coordinate system, while the friction force vector is obtained from various servo drives. The Jacobian matrix is ​​used to transform the physical coordinate system of the machine tool to the workpiece coordinate system, thereby transforming and interpolating all error vectors into standardized error vectors that are registered in the same time stamp and machine tool coordinate system. Then, for each error source, the deviation value of the error source is obtained, and the coupling mapping coefficients of other error sources in the multi-dimensional error sources to the current error source can be determined in the following way: For each error source, a directed graph describing the mutual influence between thermal deformation, friction and geometric path error is pre-established based on the physical structure and control principle of the machine tool. This is achieved by performing a large number of tests under different machine tool operating conditions (e.g., different spindle speeds, different feed rates, different ambient temperatures). The test was conducted, and multiple regression analysis was used to analyze the statistical relationship between one error source (e.g., spindle lifting caused by thermal deformation) as the independent variable and another error source (e.g., the Z-direction component of geometric path error) as the dependent variable. For each pair of coupled error sources, the correlation coefficient and sensitivity between their changes were calculated. The set of proportional factors indicating the strength of influence between error sources was then used as the coupling mapping coefficient between other error sources and the current error source. This yielded the coupling mapping coefficients of other error sources to the current error source in the multi-dimensional error source analysis. Finally, the deviation values ​​were fused and corrected using these coupling mapping coefficients to obtain the coupling deviation values ​​of the error sources in the machining of the vehicle domain controller shell on the CNC machine tool. The coupling deviation values ​​of each error source in the machining of the vehicle domain controller shell of the CNC machine tool can be obtained in the following way: the original deviation values ​​of each error source obtained after spatiotemporal registration are used as input, and the coupling mapping coefficient is used as the correction weight. The original deviation values ​​of other error sources are multiplied by the corresponding coupling mapping coefficient pointing to the current error source to obtain the corresponding coupling influence components, thus obtaining multiple coupling influence components. The sum of each coupling influence component and the original deviation value of the current error source is used as the coupling deviation value of the error source in the machining of the vehicle domain controller shell of the CNC machine tool. The coupling deviation values ​​of each error source in the machining of the vehicle domain controller shell of the CNC machine tool can be obtained in the above way.

[0028] In some embodiments, determining the error state value of the CNC machine tool during the machining of the vehicle domain controller housing can be achieved by the following steps: Obtain the coupling deviation values ​​of each error source in the machining of the vehicle domain controller shell by CNC machine tool; Based on the values ​​of various coupling deviations, fuzzy inference is performed on the machining error in the machining of the vehicle domain controller shell to obtain the fuzzy subset of error sources in the machining of the vehicle domain controller shell. The machining error in the machining of the vehicle domain controller shell is defuzzified by the fuzzy subset of the error sources, and the error state value of the CNC machine tool in the machining of the vehicle domain controller shell is obtained.

[0029] It should be noted that in this application, the error state value is a numerical index characterizing the current comprehensive machining accuracy of the CNC machine tool; the error source fuzzy subset is a set of linguistic variables describing the fuzzy level and membership degree of each coupled deviation value expressed in natural language.

[0030] In specific implementation, firstly, the coupling deviation values ​​of each error source in the machining of the vehicle domain controller shell by the CNC machine tool are obtained; then, based on each coupling deviation value, fuzzy inference is performed on the machining error in the machining of the vehicle domain controller shell to obtain the fuzzy subset of the error sources in the machining of the vehicle domain controller shell. This can be achieved in the following way: predefine the universe of discourse and fuzzy set for each coupling deviation value. For example, the universe of discourse of "thermal deformation coupling deviation value" is divided into three fuzzy sets: "small", "medium", and "large". For each fuzzy set, a triangular or trapezoidal membership function is set. During the inference process, each coupling deviation value obtained in real time is used as input, and its membership function is used to calculate the membership degree of each coupling deviation value to each fuzzy set. The calculated membership degree is used as a premise condition and matched and inferred with the "if-then" rule in the pre-set fuzzy rule base, thereby obtaining the inferred value for use in the machining of the vehicle domain controller shell. The output linguistic variable (e.g., "good accuracy") describing the overall state of the current machining error and its membership degree are used as the error source fuzzy subset in the machining of the vehicle domain controller shell. Finally, the machining error in the machining of the vehicle domain controller shell is defuzzified using the error source fuzzy subset to obtain the error state value of the CNC machine tool in the machining of the vehicle domain controller shell. This can be achieved in the following way: the error source fuzzy subset is received as input, and the universe of discourse of the output fuzzy subset is defined as a continuous numerical range from 0 (best accuracy) to 100 (worst accuracy), and is also divided into several fuzzy sets identified by linguistic values. In actual use, the centroid method of fuzzification can be used to calculate the centroid value corresponding to the area enclosed by the membership function and the horizontal coordinate of all activated output fuzzy sets. This defuzzification process integrates the influence of all activated rules, and the calculated centroid horizontal coordinate value is used as the error state value of the CNC machine tool in the machining of the vehicle domain controller shell.

[0031] In step 103, when the error state value is greater than the standard machining error of the CNC machine tool, the trust domain parameters of the servo control loop in the CNC machine tool are optimized and compensated based on the values ​​of each coupling deviation to obtain the compensation matrix of the CNC machine tool under the current working condition. Then, the position command, speed command and acceleration command of the CNC machine tool are compensated in three levels through the compensation matrix to obtain the machining compensation command of the CNC machine tool.

[0032] It should be noted that, in this application, when the error state value is greater than the standard machining error of the CNC machine tool, it indicates that the current comprehensive machining error formed by the coupling effect of multiple error sources such as thermal deformation, friction, and geometric path has exceeded the safety threshold set by the machine tool to ensure machining accuracy and workpiece pass rate. If no machining intervention is performed, the CNC machine tool will continue to operate according to the original command with inherent deviation, which will inevitably reproduce this out-of-tolerance state on the workpiece being machined, resulting in workpiece dimensional deviation or unqualified form and position accuracy. Therefore, an adaptive compensation mechanism must be activated to generate a compensation command with the opposite direction and equal magnitude to the current error by optimizing the parameters of the servo control loop in real time, so as to actively offset and correct the comprehensive error that is occurring, thereby pulling the dynamic accuracy of the machining process back and stabilizing it within the allowable standard machining error range, and ultimately ensuring that the final machining quality of the workpiece meets the preset accuracy requirements. In addition, the servo control loop is a three-loop nested controller based on command domain feedforward and feedback composite control.

[0033] In some embodiments, the trust domain parameters of the servo control loop in the CNC machine tool are optimized and compensated based on the values ​​of various coupling deviations to obtain the compensation matrix of the CNC machine tool under the current operating conditions, with reference to... Figure 2 The diagram is a flowchart illustrating the determination of the compensation matrix in some embodiments of this application. In this embodiment, the determination of the compensation matrix can be achieved using the following steps: In step 1031, the position loop proportional gain, velocity loop proportional gain, and velocity loop integral gain of the servo control loop are defined as trust domain parameters to be optimized. In step 1032, a parameter compensation model for the CNC machine tool under the current working condition is established with the goal of minimizing the values ​​of each coupling deviation. In step 1033, the parameter compensation model is used to iteratively converge the parameters of each trust domain to obtain the compensation matrix of the CNC machine tool under the current working condition.

[0034] It should be noted that in this application, the compensation matrix is ​​a diagonal coefficient matrix used to dynamically correct the original CNC commands; the trust domain parameter is a set of servo control loop gains used as the variable to be optimized in the trust domain optimization algorithm to improve the dynamic response characteristics and accuracy of the CNC machine tool; and the parameter compensation model is a mathematical optimization objective function that describes the mapping relationship between the values ​​of the trust domain parameters and the numerical value of the comprehensive coupling deviation of the CNC machine tool.

[0035] In specific implementation, firstly, defining the position loop proportional gain, speed loop proportional gain, and speed loop integral gain of the servo control loop as the trust domain parameters to be optimized can be achieved in the following way: From the control loop structure of the CNC machine tool servo drive unit, select the three control gains that have the greatest influence on the dynamic performance and steady-state accuracy of the system, namely the position loop proportional gain, speed loop proportional gain, and speed loop integral gain; set each control gain from the fixed parameters of the servo driver as variables that can be dynamically adjusted by the upper-level optimization algorithm, and combine them to form a parameter vector; this parameter vector defines the solution space to be explored by the optimization algorithm, and finally, the parameter vector formed by the combination of the position loop proportional gain, speed loop proportional gain, and speed loop integral gain is used as the trust domain parameters to be optimized; then, with the goal of minimizing the values ​​of each coupling deviation, establishing a parameter compensation model of the CNC machine tool under the current working condition can be achieved in the following way: The optimization objective is to minimize the values ​​of coupling deviations that characterize the overall accuracy of the machine tool; the trust domain parameters to be optimized are used as the input independent variables of the mathematical model; the output of the mathematical model is the fusion calculation of the coupling deviation values ​​of thermal deformation, friction force, and geometric path error. The calculated total objective function value; this mathematical model establishes a direct correlation between servo control loop parameter adjustment and final machining accuracy, providing an evaluation basis for subsequent optimization algorithms, thus using the mathematical relationship of input as trust domain parameters, output as coupling deviation value, and objective as minimization as the parameter compensation model of the CNC machine tool under the current working condition; finally, the parameter compensation model is used to iteratively converge each trust domain parameter to obtain the compensation matrix of the CNC machine tool under the current working condition, which can be achieved in the following way: taking the parameter compensation model and the target initial trust domain parameters as the starting point, in each iteration, the trust domain optimization algorithm will construct a quadratic approximation model of the parameter compensation model within a set trust domain radius around the current parameter point; by solving the optimal point of the quadratic approximation model, a set of candidate trust domain parameters is obtained, and the performance improvement degree of the parameters on the actual parameter compensation model is calculated; the trust domain radius is dynamically adjusted according to the improvement degree and it is decided whether to update the current parameters, and the output value of the parameter compensation model is converged to the minimum through multiple iterations, and finally the diagonal matrix formed by the combination of trust domain parameters obtained after iterative convergence is used as the compensation matrix of the CNC machine tool under the current working condition.

[0036] In some embodiments, the machining compensation commands of the CNC machine tool are obtained by performing three-level series compensation on the position commands, speed commands, and acceleration commands of the CNC machine tool through the compensation matrix, which can be achieved by the following steps: The acceleration command of the CNC machine tool is fed forward using the velocity loop proportional gain in the compensation matrix to obtain the acceleration compensation command of the CNC machine tool. The speed command of the CNC machine tool is adjusted by the acceleration compensation command and the speed loop integral gain in the compensation matrix to obtain the speed compensation command of the CNC machine tool. The position command of the CNC machine tool is proportionally adjusted by using the position loop proportional gain in the compensation matrix to obtain the position compensation command of the CNC machine tool. The machining compensation command for the CNC machine tool is determined based on the acceleration compensation command, the speed compensation command, and the position compensation command.

[0037] It should be noted that, in this application, the machining compensation instruction is a complete set of instructions used to drive the servo drive units of each axis of the CNC machine tool to complete precise coordinated motion; the acceleration compensation instruction is a desired acceleration signal used to improve the dynamic response capability of the CNC machine tool; the speed compensation instruction is a desired speed signal used as a connection between the position loop and the current loop; and the position compensation instruction is a desired position signal used to directly control the endpoint of the motion trajectory of each axis of the CNC machine tool.

[0038] In specific implementation, firstly, the acceleration command of the CNC machine tool is feedforward compensated using the velocity loop proportional gain in the compensation matrix. The resulting acceleration compensation command can be achieved as follows: The original acceleration command issued by the CNC machine tool planning module is read, and the optimized velocity loop proportional gain is extracted from the compensation matrix; the original acceleration command is differentiated with respect to time to obtain the rate of change of acceleration, and this rate of change is multiplied by the velocity loop proportional gain to calculate the feedforward compensation amount; this feedforward compensation amount is algebraically added to the original acceleration command, thus using the acceleration signal superimposed with the feedforward compensation amount as the acceleration compensation command of the CNC machine tool; secondly, through the... The speed compensation command and the speed loop integral gain in the compensation matrix are used to adjust the speed command of the CNC machine tool. The resulting speed compensation command can be achieved as follows: the acceleration compensation command is used as a feedforward input, while simultaneously receiving the speed adjustment signal output from the position loop controller; the speed adjustment signal is multiplied by the speed loop integral gain in the compensation matrix and integrated to obtain the integral compensation component; the speed feedforward component obtained by integrating the acceleration compensation command, the original speed command, and the integral compensation component are algebraically superimposed to obtain the comprehensive speed signal after proportional and integral combined adjustment, which is then used as the speed compensation command of the CNC machine tool; finally, the speed compensation command in the compensation matrix is ​​used... The proportional gain of the position loop is used to proportionally adjust the position command of a CNC machine tool to obtain the position compensation command. This can be achieved as follows: Receive the original position command from the CNC machine tool interpolation module and simultaneously obtain the position loop proportional gain from the compensation matrix; calculate the difference between the original position command and the actual position fed back by the machine tool's linear encoder, i.e., the position deviation; multiply this position deviation by the position loop proportional gain to obtain the proportional adjustment component; simultaneously, use the coupling deviation value of the geometric path error as the static position offset compensation amount; algebraically add the original position command, the proportional adjustment component, and the static position offset compensation amount to obtain the position signal after superimposed proportional adjustment and static offset compensation. The position compensation command for the CNC machine tool is determined based on the acceleration compensation command, the speed compensation command, and the position compensation command. This can be achieved by encapsulating and synchronizing the acceleration compensation command, the speed compensation command, and the position compensation command according to the format of the CNC machine tool command frame; ensuring that the three levels of compensation commands are perfectly aligned in timestamps and point to the same control cycle; and sending the encapsulated and synchronized command data packet to the CNC machine tool's command execution queue, thereby using the command data packet consisting of the position compensation command, the speed compensation command, and the acceleration compensation command obtained after three levels of cascaded compensation as the CNC machine tool's machining compensation command.

[0039] In step 104, the machining compensation command is input to the servo drive unit of each axis in the CNC machine tool to control the CNC machine tool to perform machining compensation. During the machining compensation, the multi-dimensional error sources of the CNC machine tool are continuously monitored in a loop to compensate for the error in the machining of the vehicle domain controller shell.

[0040] In practice, the machining compensation command is sent as electronic signals to the servo drive units of the corresponding X, Y, and Z axes of the CNC machine tool. After receiving the compensation command, each axis servo drive unit takes it as a new control target and drives the servo motor to generate compensatory motion through precise closed-loop calculations of the internal current loop and speed loop to offset the previously identified error. While this compensatory motion is being executed, the CNC machine tool continuously and periodically collects new data on multi-dimensional error sources such as thermal deformation error, dynamic friction error, and geometric path error through a monitoring network of temperature sensors, motor encoders, and grating rulers. This real-time data is fed into the multi-dimensional error source mathematical model, initiating a new round of complete calculation process from error modeling, fusion, state assessment to parameter optimization and command compensation. This forms a cyclical adaptive closed-loop control system with real-time machining accuracy as the control target, thereby achieving dynamic maintenance of accuracy and closed-loop error compensation throughout the machining process.

[0041] Furthermore, in another aspect of this application, in some embodiments, this application provides a machining compensation system suitable for a vehicle domain controller housing. This machining compensation system includes an error compensation unit, referencing... Figure 3 The figure is a schematic diagram of the structure of an error compensation unit according to some embodiments of this application. The error compensation unit includes: an error modeling module 201, a processing module 202, and an execution module 203, which are described below: Error modeling module 201, in this application, is mainly used to mathematically model the multi-dimensional error sources of CNC machine tools in the machining of the shell of the vehicle domain controller, and obtain the thermal deformation displacement vector, friction force vector and path deviation vector of the CNC machine tool respectively. The multi-dimensional error sources include the thermal deformation error, dynamic friction error and geometric path error of the CNC machine tool. Processing module 202, in this application, is used to perform error fusion on the thermal deformation displacement vector, the friction force vector and the path deviation vector to obtain the coupling deviation values ​​of each error source in the machining of the vehicle domain controller shell by the CNC machine tool, and then determine the error state value of the CNC machine tool in the machining of the vehicle domain controller shell; It should be noted that the processing module 202 is also used to optimize and compensate the trust domain parameters of the servo control loop in the CNC machine tool based on the values ​​of each coupling deviation when the error state value is greater than the standard machining error of the CNC machine tool, so as to obtain the compensation matrix of the CNC machine tool under the current working condition, and then perform three-level series compensation on the position command, speed command and acceleration command of the CNC machine tool through the compensation matrix to obtain the machining compensation command of the CNC machine tool; The execution module 203 in this application is mainly used to input the machining compensation command to the servo drive unit of each axis in the CNC machine tool, control the CNC machine tool to perform machining compensation, and continuously monitor the multi-dimensional error sources of the CNC machine tool in the machining compensation process, thereby compensating for the error of the machining of the shell of the vehicle domain controller.

[0042] The foregoing has detailed examples of machining compensation systems and methods for vehicle domain controller housings provided in this application. It is understood that the corresponding apparatus includes hardware structures and / or software modules for performing each function in order to achieve the aforementioned functions. Those skilled in the art should readily recognize that, based on the units and algorithm steps of the examples described in conjunction with the embodiments disclosed herein, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0043] In some embodiments, this application also provides a computer device, the computer device including a memory and a processor, the memory for storing a computer program, and the processor for calling and running the computer program from the memory, causing the computer device to perform the above-described machining compensation method for a vehicle domain controller housing.

[0044] In some embodiments, reference Figure 4 The dashed lines in the figure indicate that the unit or module is optional. This figure is a structural schematic diagram of a computer device implementing a machining compensation method suitable for a vehicle domain controller housing according to an embodiment of this application. The machining compensation method suitable for a vehicle domain controller housing described in the above embodiments can be achieved through… Figure 4 The computer device shown is used to implement this, and the computer device includes at least one processor 301, a memory 302 and at least one communication unit 305. The computer device may be a terminal device, a server or a chip.

[0045] Processor 301 can be a general-purpose processor or a special-purpose processor. For example, processor 301 can be a central processing unit (CPU), which can be used to control computer devices, execute software programs, and process data from software programs. The computer device may also include a communication unit 305 for inputting (receiving) and outputting (transmitting) signals.

[0046] For example, the computer device may be a chip, and the communication unit 305 may be the input and / or output circuit of the chip, or the communication unit 305 may be the communication interface of the chip, which may be a component of a terminal device, network device or other device.

[0047] For example, the computer device may be a terminal device or a server, and the communication unit 305 may be a transceiver of the terminal device or the server, or the communication unit 305 may be a transceiver circuit of the terminal device or the server.

[0048] The computer device may include one or more memories 302 storing a program 304. The program 304 can be executed by a processor 301 to generate instructions 303, causing the processor 301 to execute the method described in the above method embodiments according to the instructions 303. Optionally, the memory 302 may also store data (such as a target audit model). Optionally, the processor 301 may also read data stored in the memory 302, which may be stored at the same storage address as the program 304, or it may be stored at a different storage address than the program 304.

[0049] The processor 301 and memory 302 can be configured separately or integrated together, for example, integrated on the system on chip (SOC) of the terminal device.

[0050] It should be understood that each step of the above method embodiment can be completed by hardware logic circuits or software instructions in the processor 301. The processor 301 can be a CPU, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, such as discrete gates, transistor logic devices, or discrete hardware components.

[0051] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0052] For example, in some embodiments, this application also provides a computer-readable storage medium storing instructions or code that, when executed on a computer, cause the computer to implement the above-described machining compensation method for the housing of a vehicle domain controller.

[0053] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0054] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A machining compensation method for the housing of a vehicle domain controller, characterized in that, Includes the following steps: Mathematical modeling is performed on the multi-dimensional error sources of CNC machine tool machining of the vehicle domain controller shell, and the thermal deformation displacement vector, friction force vector and path deviation vector of CNC machine tool are obtained respectively. The multi-dimensional error sources include the thermal deformation error, dynamic friction error and geometric path error of CNC machine tool. The thermal deformation displacement vector, the friction force vector, and the path deviation vector are fused to obtain the coupling deviation values ​​of each error source in the machining of the vehicle domain controller shell by the CNC machine tool, thereby determining the error state value of the CNC machine tool in the machining of the vehicle domain controller shell. When the error state value is greater than the standard machining error of the CNC machine tool, the trust domain parameters of the servo control loop in the CNC machine tool are optimized and compensated based on the values ​​of each coupling deviation to obtain the compensation matrix of the CNC machine tool under the current working condition. Then, the position command, speed command and acceleration command of the CNC machine tool are compensated in three levels through the compensation matrix to obtain the machining compensation command of the CNC machine tool. The machining compensation command is input to the servo drive unit of each axis in the CNC machine tool to control the CNC machine tool to perform machining compensation. During the machining compensation, the multi-dimensional error sources of the CNC machine tool are continuously monitored in a loop, thereby compensating for the error in the machining of the vehicle domain controller shell.

2. The method as described in claim 1, characterized in that, Mathematical modeling was performed on the multi-dimensional error sources of the CNC machine tool in the machining of the vehicle domain controller shell, resulting in the thermal deformation displacement vector, friction force vector, and path deviation vector of the CNC machine tool, specifically including: A linear mapping relationship between thermal deformation and temperature rise is established based on the temperature rise data of various temperature monitoring points in the CNC machine tool, thereby obtaining the thermal deformation displacement vector of the CNC machine tool; Using the current and speed signals of the servo drive unit in the CNC machine tool, the nonlinear friction force is calculated through the dynamic friction model of parameter identification, and then the friction force vector of the CNC machine tool is obtained. Based on the geometric error elements measured by the laser interferometer, a model of the spatial position deviation between the tool and the workpiece in the machine tool motion chain is constructed, thereby obtaining the path deviation vector of the CNC machine tool.

3. The method as described in claim 1, characterized in that, By fusing the thermal deformation displacement vector, the friction force vector, and the path deviation vector, the coupling deviation values ​​of each error source in the machining of the vehicle domain controller shell by the CNC machine tool are obtained, specifically including: The thermal deformation displacement vector, the friction force vector, and the path deviation vector are spatiotemporally registered and then unified to the same timestamp and machine tool coordinate system. For each error source, obtain the deviation value of the error source and determine the coupling mapping coefficient of other error sources in the multi-dimensional error sources to the current error source. By fusing and correcting the deviation values ​​using various coupling mapping coefficients, the coupling deviation values ​​of the error sources in the machining of the vehicle domain controller shell by the CNC machine tool are obtained, and then the coupling deviation values ​​of each error source in the machining of the vehicle domain controller shell by the CNC machine tool are obtained.

4. The method as described in claim 1, characterized in that, Determining the error state values ​​of CNC machine tools during the machining of the vehicle domain controller housing specifically includes: Obtain the coupling deviation values ​​of each error source in the machining of the vehicle domain controller shell by CNC machine tool; Based on the values ​​of various coupling deviations, fuzzy inference is performed on the machining error in the machining of the vehicle domain controller shell to obtain the fuzzy subset of error sources in the machining of the vehicle domain controller shell. The machining error in the machining of the vehicle domain controller shell is defuzzified by the fuzzy subset of the error sources, and the error state value of the CNC machine tool in the machining of the vehicle domain controller shell is obtained.

5. The method as described in claim 1, characterized in that, Based on the values ​​of various coupling deviations, the trust domain parameters of the servo control loop in the CNC machine tool are optimized and compensated to obtain the compensation matrix of the CNC machine tool under the current working condition. Specifically, the compensation matrix includes: The position loop proportional gain, velocity loop proportional gain, and velocity loop integral gain of the servo control loop are defined as trust domain parameters to be optimized. With the goal of minimizing the values ​​of each coupling deviation, a parameter compensation model for the CNC machine tool under the current working conditions is established. The parameter compensation model is used to iteratively converge the parameters of each trust domain, thereby obtaining the compensation matrix of the CNC machine tool under the current working condition.

6. The method as described in claim 1, characterized in that, The position, speed, and acceleration commands of the CNC machine tool are compensated in three stages through the compensation matrix to obtain the machining compensation commands for the CNC machine tool, specifically including: The acceleration command of the CNC machine tool is fed forward using the velocity loop proportional gain in the compensation matrix to obtain the acceleration compensation command of the CNC machine tool. The speed command of the CNC machine tool is adjusted by the acceleration compensation command and the speed loop integral gain in the compensation matrix to obtain the speed compensation command of the CNC machine tool. The position command of the CNC machine tool is proportionally adjusted by using the position loop proportional gain in the compensation matrix to obtain the position compensation command of the CNC machine tool. The machining compensation command for the CNC machine tool is determined based on the acceleration compensation command, the speed compensation command, and the position compensation command.

7. The method as described in claim 1, characterized in that, The servo control loop is a three-loop nested controller based on a composite control of instruction domain feedforward and feedback.

8. A machining compensation system for a vehicle domain controller housing, used to perform the machining compensation method for a vehicle domain controller housing as described in any one of claims 1 to 7, the machining compensation system for a vehicle domain controller housing comprising an error compensation unit, characterized in that, The error compensation unit includes: The error modeling module is used to mathematically model the multi-dimensional error sources of CNC machine tools in the machining of the shell of the vehicle domain controller, and obtain the thermal deformation displacement vector, friction force vector and path deviation vector of the CNC machine tool respectively. The multi-dimensional error sources include the thermal deformation error, dynamic friction error and geometric path error of the CNC machine tool. The processing module is used to perform error fusion of the thermal deformation displacement vector, the friction force vector and the path deviation vector to obtain the coupling deviation values ​​of each error source in the machining of the vehicle domain controller shell by the CNC machine tool, and then determine the error state value of the CNC machine tool in the machining of the vehicle domain controller shell. The processing module is also used to optimize and compensate the trust domain parameters of the servo control loop in the CNC machine tool based on the values ​​of each coupling deviation when the error state value is greater than the standard machining error of the CNC machine tool, so as to obtain the compensation matrix of the CNC machine tool under the current working condition, and then perform three-level series compensation on the position command, speed command and acceleration command of the CNC machine tool through the compensation matrix to obtain the machining compensation command of the CNC machine tool. The execution module is used to input the machining compensation command to the servo drive unit of each axis in the CNC machine tool, control the CNC machine tool to perform machining compensation, and continuously monitor the multi-dimensional error sources of the CNC machine tool in a loop during machining compensation, thereby compensating for the error of the machining of the shell of the vehicle domain controller.

9. A computer device, characterized in that, The computer device includes a memory and a processor, the memory storing code, and the processor being configured to retrieve the code and execute the machining compensation method for a vehicle domain controller housing as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the machining compensation method for the housing of the vehicle domain controller as described in any one of claims 1 to 7.

Images