A method and system for automatic control of a motor winding process

Abstract

The application relates to the motor winding technology field and provides a motor winding process automatic control method and system.The method comprises the following steps: obtaining motion state information, stress state information and material characteristic information of a flat wire; inputting the motion state information, the stress state information and the material characteristic information into a preset flat wire mechanical simulation model to obtain a predicted torsion angle of the flat wire in a bending process output by the preset flat wire mechanical simulation model; obtaining an actual torsion angle of the flat wire; adjusting a parameter value of an equivalent shear modulus of the flat wire in the preset flat wire mechanical simulation model according to the predicted torsion angle and the actual torsion angle to obtain an adjusted preset flat wire mechanical simulation model; and performing winding control on the flat wire based on the adjusted preset flat wire mechanical simulation model. The accuracy of motor winding can be controlled.

Description

Technical Field

[0001] This application relates to the field of motor winding technology, and in particular to an automated control method and system for the motor winding process. Background Technology

[0002] In modern industrial production, automated control of the motor winding process is a key element in improving production efficiency and product quality. As market demands for motor performance continue to rise, traditional winding technology faces new challenges, especially when using new types of wire. Ensuring winding quality and efficiency has become a focal point for the industry.

[0003] Specifically, in modern motor manufacturing workshops, the winding process is usually automated to ensure production efficiency and product consistency. The winding station on the automated production line is equipped with a highly sophisticated control system. This system pre-stores the process parameters required for winding various motor models, such as the winding nozzle's path, the wire feeding speed, the number of turns per coil, and the tension applied to the enameled wire.

[0004] However, as market demands for motor performance increase, especially in fields such as new energy vehicles and high-precision servo motors, motors require higher power density and energy conversion efficiency. To achieve this goal, the motor design field has begun to widely use flat enameled wire to replace traditional round enameled wire. Because of its cross-sectional shape, flat wire can achieve a closer arrangement in the stator slots, significantly improving the slot fill rate. This allows for more copper to be packed into the same volume, effectively reducing coil resistance and minimizing copper energy loss, thereby improving the overall performance of the motor.

[0005] However, this material innovation brought unexpected challenges to the existing automated winding control system. The crux of the problem lies in the significant difference in mechanical properties between flat and round wires. Round wire has essentially the same stiffness in all directions, and during winding, it can be considered a material with similar properties in all directions. Flat wire, on the other hand, exhibits significant anisotropy; its bending stiffness in the width direction (i.e., the direction of the flat surface) is much greater than its bending stiffness in the thickness direction. This uneven stiffness becomes apparent when the winding nozzle guides the flat wire to make a bend at the end of the stator core. The existing control system simply moves the winding nozzle according to a preset path and maintains a constant tension. However, when the flat wire is forced to bend in a direction other than its thickness, it does not obediently follow the predetermined path like round wire.

[0006] More troublesome and insidious than the springback problem is the torsion phenomenon that occurs during the winding of flat wire. When navigating complex winding paths in three-dimensional space, especially when crossing from one slot to another non-adjacent slot, the flat wire not only needs to bend but may also be subjected to a force that causes it to rotate around its own axis. Due to its slender cross-section, even a small lateral force can cause unpredictable torsion. Once the flat wire twists, its wide face is no longer parallel to the sidewall of the stator slot but enters the slot at an angle. In this case, the space occupied by the wire in the slot increases dramatically, severely disrupting the originally desired high-density arrangement and completely negating the core advantage of using flat wire to improve slot fill rate. Existing automated control systems can typically only sense and control the spatial position of the winding nozzle (X, Y, Z coordinates) and the one-dimensional tension of the wire. The system is completely "invisible" to the attitude of the flat wire during feeding, especially the rotation angle of its cross-section. While visual inspection systems can be used to check the quality of the final product, capturing and measuring the minute twists of a thin, flat wire in real time and with high precision during high-speed winding is technically very difficult and costly. Therefore, winding defects caused by flat wire twisting frequently occur on the production line, resulting in a large number of defective and scrap products, significantly reducing production efficiency and severely undermining the advantages of automated production lines. Summary of the Invention

[0007] This application provides an automated control method and system for the motor winding process, which can control the accuracy of motor winding.

[0008] To achieve the above objectives, this application adopts the following technical solution:

[0009] In a first aspect, this application discloses an automated control method for the winding process of an electric motor, comprising the following steps: acquiring motion state information, stress state information, and material property information of a flat wire; inputting the motion state information, stress state information, and material property information into a preset flat wire mechanical simulation model to obtain the predicted torsion angle of the flat wire during bending, output by the preset flat wire mechanical simulation model; acquiring the actual torsion angle of the flat wire; adjusting the parameter value of the equivalent shear modulus of the flat wire in the preset flat wire mechanical simulation model according to the predicted torsion angle and the actual torsion angle to obtain an adjusted preset flat wire mechanical simulation model; and controlling the winding of the flat wire based on the adjusted preset flat wire mechanical simulation model.

[0010] This technical solution enables the real-time acquisition of various status information of flat wires, and by comparing the predicted and actual torsion angles with the mechanical simulation model, the simulation model parameters can be dynamically adjusted. This allows for accurate prediction and control of the torsion behavior of flat wires, effectively solving the torsion problem during the winding process of flat wires and improving the winding quality and the accuracy of automated control.

[0011] Furthermore, the parameter values ​​of the equivalent shear modulus of the flat wire in the preset flat wire mechanical simulation model are adjusted according to the predicted torsion angle and the actual torsion angle to obtain the adjusted preset flat wire mechanical simulation model. This includes: using the difference between the predicted torsion angle and the actual torsion angle as the target angle difference; determining the target adjustment amount of the equivalent shear modulus of the flat wire based on the target angle difference; using the difference between the current parameter value of the equivalent shear modulus of the flat wire and the target adjustment amount as the adjustment parameter value of the equivalent shear modulus of the flat wire; and setting the parameter value of the equivalent shear modulus of the flat wire in the preset flat wire mechanical simulation model as the adjustment parameter value to obtain the adjusted preset flat wire mechanical simulation model.

[0012] This technical solution enables the quantitative prediction of the difference between the torsion angle and the actual torsion angle, and uses this as a basis to accurately calculate the adjustment amount of the equivalent shear modulus. This allows the simulation model to more accurately reflect the actual mechanical properties of flat wire, further improving the precision of model adjustment and the accuracy of control.

[0013] Based on the above, this application further proposes a method for determining the target adjustment amount of the equivalent shear modulus of flat wire based on the target angle difference, including: obtaining a first preset correspondence; the first preset correspondence includes a one-to-one correspondence between multiple angle difference ranges and multiple adjustment coefficients; using the adjustment coefficient corresponding to the target angle difference in the first preset correspondence as the target adjustment coefficient; and using the product of the target adjustment coefficient and the target angle difference as the target adjustment amount.

[0014] This technical solution enables intelligent and nonlinear determination of the equivalent shear modulus adjustment amount by using the pre-set correspondence between the angle difference and the adjustment coefficient. This avoids the errors that may be caused by simple linear adjustment, making the model adjustment process more flexible and accurate, and adapting to different degrees of torsional deviation.

[0015] As an optional approach, when the material property information includes the material's elastic modulus, the material property information is obtained by: controlling the acoustic wave emitting device to emit acoustic waves into the flat wire; detecting the acoustic wave velocity in the flat wire based on the time-of-flight method; and determining the material's elastic modulus based on the acoustic wave velocity.

[0016] This technical solution enables the real-time and accurate acquisition of the elastic modulus of flat wire using a non-destructive acoustic wave detection method. This provides precise material parameters for mechanical simulation models, improving the quality of input data and the accuracy of predictions.

[0017] Furthermore, determining the elastic modulus of a material based on the sound wave velocity includes: obtaining the density of the flat wire; and using the product of the density and the square of the sound wave velocity as the elastic modulus of the material.

[0018] This technical solution enables the precise calculation of the material's elastic modulus based on physical principles by combining the density of flat wires and the velocity of sound waves, ensuring the accuracy of material parameters and further improving the reliability of the mechanical simulation model.

[0019] In some preferred embodiments, before inputting motion state information, stress state information, and material property information into a preset flat wire mechanical simulation model to obtain the predicted torsion angle of the flat wire during bending as output by the preset flat wire mechanical simulation model, the method further includes: obtaining a second preset correspondence and the hardness value of the flat wire; the second preset correspondence includes a one-to-one correspondence between multiple hardness value ranges and multiple flat wire mechanical simulation models; and using the flat wire mechanical simulation model corresponding to the hardness value range in the second preset correspondence as the preset flat wire mechanical simulation model.

[0020] This technical solution enables the dynamic selection of the most suitable mechanical simulation model based on the hardness value of the flat wire, achieving adaptive model selection. This allows the simulation model to better adapt to the characteristics of different batches or specifications of flat wire, improving the accuracy and applicability of predictions.

[0021] This application also proposes a method for controlling the winding of flat wire based on an adjusted preset flat wire mechanical simulation model, including: inputting the current motion state information, current stress state information, and material property information of the flat wire into the adjusted preset flat wire mechanical simulation model to obtain the current predicted torsion angle of the flat wire during the bending process output by the adjusted preset flat wire mechanical simulation model; inputting the current predicted torsion angle into a preset flat wire control model to obtain the initial control information for suppressing the torsion of the flat wire output by the preset flat wire control model; obtaining the internal damage index of the flat wire; adjusting the initial control information according to the internal damage index to obtain and execute the target control information.

[0022] This technical solution enables fine-tuning of winding control information by combining real-time predicted torsion angles and the internal damage index of flat wires. It not only suppresses torsion but also takes into account the damage to the wires, avoiding secondary damage caused by over-control and achieving smarter and safer winding control.

[0023] Preferably, obtaining the internal damage index of the flat wire includes: controlling the light source to irradiate the flat wire and obtaining the spectral data of the flat wire; performing spectral analysis on the spectral data to obtain the current spectral information; determining the similarity between the current spectral information and the preset spectral information when the flat wire is undamaged; and using the reciprocal of the similarity as the internal damage index.

[0024] This technical solution enables non-destructive detection of internal damage in flat wires using spectral analysis, quantifying it into a damage index. This provides crucial damage assessment data for winding control, allowing the control system to adaptively adjust based on the wire's health condition and effectively prevent further damage.

[0025] Based on the above, this application further proposes that the initial control information includes an initial traction force, and that the initial control information is adjusted according to the internal damage index to obtain and execute target control information, including: obtaining a third preset correspondence; the third preset correspondence includes a one-to-one correspondence between multiple internal damage index ranges and multiple traction force adjustment coefficients; using the traction force adjustment coefficient corresponding to the internal damage range in the third preset correspondence as the target traction force adjustment coefficient; using the product of the initial traction force and the target traction force adjustment coefficient as the target traction force in the target control information, and executing the target control information.

[0026] This technical solution enables intelligent and precise adjustment of traction force by establishing a pre-defined relationship between the damage index and the traction force adjustment coefficient. This ensures that while suppressing torsion, it also prevents excessive traction force from exacerbating wire damage, thus optimizing and protecting the winding process.

[0027] Secondly, this application also discloses an automated control system for the motor winding process, comprising: an acquisition device and a processing device; the acquisition device is used to acquire motion state information, stress state information, and material property information of a flat wire; the processing device is used to input the motion state information, stress state information, and material property information into a preset flat wire mechanical simulation model to obtain the predicted torsion angle of the flat wire during the bending process output by the preset flat wire mechanical simulation model; the processing device is used to acquire the actual torsion angle of the flat wire; the processing device is used to adjust the parameter value of the equivalent shear modulus of the flat wire in the preset flat wire mechanical simulation model according to the predicted torsion angle and the actual torsion angle to obtain an adjusted preset flat wire mechanical simulation model; the processing device is used to perform winding control of the flat wire based on the adjusted preset flat wire mechanical simulation model.

[0028] Beneficial effects

[0029] This application discloses an automated control method for the winding process of a motor. It acquires the motion state, stress state, and material properties of a flat wire and inputs these into a preset flat wire mechanical simulation model to obtain the predicted torsion angle of the flat wire during bending. Simultaneously, it acquires the actual torsion angle of the flat wire and dynamically adjusts the parameter value of the equivalent shear modulus of the flat wire in the preset flat wire mechanical simulation model based on the predicted and actual torsion angles, resulting in an adjusted mechanical simulation model. Finally, it controls the winding of the flat wire based on the adjusted mechanical simulation model. This method effectively solves the torsion problem caused by anisotropy during the winding process of flat wires in existing technologies, as well as the problem that existing automated control systems cannot accurately sense and control the attitude of flat wires in real time. By introducing a mechanical simulation model and making real-time adaptive adjustments, this application can accurately predict the torsional behavior of flat wires and optimize the winding control strategy accordingly, thereby significantly improving the quality and efficiency of flat wire winding, reducing the defective and scrap rates, overcoming the shortcomings of the prior art in terms of reduced slot filling rate and low production efficiency caused by flat wire torsion, and realizing the automation and intelligent upgrade of the motor winding process. Attached Figure Description

[0030] Figure 1 A flowchart illustrating an automated control method for the motor winding process provided in this application;

[0031] Figure 2 A flowchart illustrating another automated control method for the motor winding process provided in this application;

[0032] Figure 3 A flowchart illustrating another automated control method for the motor winding process provided in this application;

[0033] Figure 4 This application provides a schematic diagram of the architecture of an automated control system for the motor winding process. Detailed Implementation

[0034] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments. The components of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0035] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0036] In the field of automated control of motor winding, traditional technologies face numerous challenges when handling flat wires. Existing systems typically only control the spatial position of the winding nozzle and the tension of the wire, lacking effective means to sense and control the torsion that may occur in flat wires during complex winding paths. This limitation leads to unpredictable torsion of flat wires during winding, affecting the tightness of the wire arrangement in the stator slots, severely reducing slot filling rate, ultimately damaging motor performance and causing low production efficiency and increased scrap rates.

[0037] In this regard, such as Figure 1 As shown, this application proposes an automated control method for the motor winding process, including the following steps:

[0038] S101. Obtain motion state information, stress state information, and material property information of the flat wire.

[0039] S102. Input the motion state information, force state information and material property information into the preset flat wire mechanical simulation model to obtain the predicted torsion angle of the flat wire during the bending process output by the preset flat wire mechanical simulation model.

[0040] S103. Obtain the actual torsion angle of the flat wire.

[0041] S104. Adjust the parameter values ​​of the equivalent shear modulus of the flat wire in the preset flat wire mechanical simulation model according to the predicted torsion angle and the actual torsion angle to obtain the adjusted preset flat wire mechanical simulation model.

[0042] S105. Based on the adjusted preset flat wire mechanical simulation model, the flat wire is wound and controlled.

[0043] This application aims to introduce a mechanical simulation model of flat wire and adaptively adjust the model parameters in combination with the actual torsion angle, thereby achieving accurate prediction and effective control of torsion phenomena during the winding process of flat wire, significantly improving winding quality and production efficiency.

[0044] To better understand the technical solution proposed in this application, some key terms are explained first. Flat wire, generally referring to enameled wire with a rectangular or near-rectangular cross-section, is characterized by a width much greater than its thickness, resulting in significant differences in its bending resistance in different directions, i.e., anisotropy. Motion state information can include the linear velocity, acceleration, and winding trajectory of the flat wire, describing its dynamic behavior in space. Stress state information encompasses various forces acting on the wire, such as traction force, friction force, and contact force generated during bending. Material property information refers to the inherent physical properties of the flat wire, such as elastic modulus, shear modulus, and density, which determine the wire's deformation response under stress. The preset flat wire mechanical simulation model is a mathematical model used to simulate the mechanical behavior of the flat wire under specific stress conditions and motion states, particularly its torsional response during bending. This model can predict the wire's torsion angle based on input parameters. The equivalent shear modulus of flat wire is a key parameter in this simulation model. It comprehensively reflects the characteristics of flat wire in shear deformation and has an important impact on the prediction of torsion angle.

[0045] The core of the method proposed in this application lies in achieving precise control of the torsion of the flat wire during the winding process by adaptively adjusting the mechanical simulation model of the flat wire.

[0046] Specifically, various methods can be used to acquire information on the motion, stress, and material properties of flat wire. For example, motion information can be acquired in real time using encoders, laser rangefinders, or vision tracking systems installed on the winding equipment. These sensors provide data such as the wire's linear velocity and position coordinates. Stress information can be obtained by placing force or tension sensors along the wire feeding path. These sensors can measure the traction or bending forces acting on the wire. Material property information, such as the elastic modulus and density of the flat wire, can be obtained by consulting datasheets provided by material suppliers or by measuring using laboratory testing methods. For example, the elastic modulus can be obtained by performing tensile tests on the flat wire, or its density can be determined by weighing and volumetric measurements.

[0047] In terms of inputting motion state information, stress state information, and material property information into a preset flat wire mechanical simulation model to obtain the predicted torsional angle of the flat wire during bending, the preset flat wire mechanical simulation model can be a computational model based on the principles of finite element analysis (FEA) or multibody dynamics (MBD). This model can use the input motion, stress, and material parameters as boundary conditions and material properties, and simulate the complex bending and torsional deformation experienced by the flat wire in the winding path by numerically solving the mechanical equations, and output the predicted torsional angle at a specific bending point or throughout the entire bending process. For example, this model can be a simplified model based on beam theory or shell theory, which calculates the torsional angle of the wire cross-section by inputting the wire's geometric dimensions, material parameters, bending radius, and tensile force.

[0048] To obtain the actual torsion angle of flat wire, non-contact measurement methods can be used. For example, a high-speed camera combined with image processing algorithms can be used to capture images of the flat wire cross-section in real time, and the actual torsion angle can be calculated by analyzing the orientation of the cross-section in the image. Another approach is to pre-mark specific patterns or textures on the surface of the flat wire, and then use a vision sensor to track the rotation of these marks to deduce the actual torsion angle.

[0049] In adjusting the parameter values ​​of the equivalent shear modulus of flat wire in the preset flat wire mechanical simulation model based on the predicted and actual torsion angles, the adjustment process can employ iterative optimization algorithms. For example, the difference between the predicted and actual torsion angles can be used as an error signal. Through a feedback control mechanism, the parameter values ​​of the equivalent shear modulus of flat wire in the preset flat wire mechanical simulation model can be gradually adjusted until the error between the predicted and actual values ​​converges to an acceptable range. Specifically, optimization algorithms such as gradient descent or least squares can be used to calculate the adjustment direction and step size of the equivalent shear modulus parameter based on the error signal, thereby updating the model parameters.

[0050] In controlling the winding of flat wire based on the adjusted preset flat wire mechanical simulation model, the adjusted model can more accurately reflect the current mechanical characteristics of the flat wire. Using this more accurate model, the control system can predict the torsional trend of the flat wire in the subsequent winding path in real time and generate corresponding control commands accordingly. For example, control commands may include adjusting the posture of the winding nozzle, changing the traction force of the wire, or applying additional torque to counteract or correct the torsion of the wire. In this way, it can be ensured that the flat wire maintains the correct posture throughout the winding process, avoiding unnecessary torsion and thus guaranteeing winding quality.

[0051] The overall working principle of this application is as follows: First, by acquiring the motion state, stress state, and material property information of the flat wire, comprehensive input data is provided for the mechanical simulation model. Then, this information is input into a preset flat wire mechanical simulation model to predict the torsion angle of the flat wire during bending. To ensure the accuracy of the prediction, this application introduces the acquisition of the actual torsion angle and uses the difference between the predicted and actual torsion angles to adaptively adjust the equivalent shear modulus parameter value of the flat wire in the preset flat wire mechanical simulation model. This adjustment process allows the simulation model to be calibrated in real time, more accurately reflecting the actual mechanical behavior of the flat wire. Finally, based on the adjusted and more accurate preset flat wire mechanical simulation model, the flat wire is controlled during winding. The entire process forms a closed-loop feedback control system, which, through continuous prediction, measurement, adjustment, and control, effectively solves the technical problem of easy torsion of flat wire during winding, ensuring winding quality and efficiency.

[0052] The core innovation of this application lies in the introduction of an adaptive adjustment mechanism for the mechanical simulation model of flat wire. Traditional winding control systems often rely on preset fixed parameters, which cannot cope with the torsion problems caused by changes in material properties or external environmental disturbances that may occur during the actual winding process of flat wire. For example, in the prior art, winding equipment may only set control strategies based on empirical parameters or offline test results. Once the batch of wire changes or the winding speed is adjusted, its prediction and control accuracy will be greatly reduced, leading to frequent torsion phenomena in flat wire.

[0053] In contrast, this application acquires the actual torsion angle of the flat wire in real time and compares it with the prediction results of the simulation model, thereby dynamically adjusting key parameters in the simulation model (such as the equivalent shear modulus of the flat wire). This adaptive adjustment mechanism enables the simulation model to continuously learn and optimize, maintaining its accurate predictive ability of the mechanical behavior of the flat wire. As a result, the control system can generate more precise control commands based on more accurate predictions, effectively suppressing the torsion of the flat wire and ensuring that the wire enters the stator slot in the correct orientation. This real-time adaptive control strategy significantly improves the automation level and control accuracy of the winding process, effectively solving the limitations of traditional methods in handling the torsion problem of flat wire, thereby improving the quality and production efficiency of motor winding.

[0054] This application further proposes adjusting the parameter values ​​of the equivalent shear modulus of flat wire in the preset flat wire mechanical simulation model to obtain the adjusted preset flat wire mechanical simulation model. The specific steps include:

[0055] The difference between the predicted torsion angle and the actual torsion angle is used as the target angle difference; the target adjustment amount of the equivalent shear modulus of the flat wire is determined based on the target angle difference; the difference between the current parameter value of the equivalent shear modulus of the flat wire and the target adjustment amount is used as the adjustment parameter value of the equivalent shear modulus of the flat wire; the parameter value of the equivalent shear modulus of the flat wire in the preset flat wire mechanical simulation model is set as the adjustment parameter value to obtain the adjusted preset flat wire mechanical simulation model.

[0056] Specifically, the difference between the predicted torsion angle and the actual torsion angle is used as the target angle difference. The purpose is to quantify the deviation between the simulation model's prediction and the actual situation. This difference directly reflects the accuracy of the current simulation model in predicting the torsional behavior of flat wire during bending. Determining the target adjustment amount for the equivalent shear modulus of the flat wire based on the target angle difference can be understood as converting the quantified deviation into correction instructions for key model parameters. This adjustment aims to guide the update direction and magnitude of the equivalent shear modulus parameters, making the model's prediction results closer to reality.

[0057] In practical applications, using the difference between the current parameter value and the target adjustment amount of the equivalent shear modulus of flat wire as the adjustment parameter value means calculating the new equivalent shear modulus parameter by subtracting or adding the target adjustment amount. For example, if the predicted torsion angle is smaller than the actual torsion angle, it may be necessary to reduce the equivalent shear modulus to make the wire exhibit greater flexibility in the model, thereby increasing the predicted torsion angle; and vice versa. Furthermore, setting the parameter value of the equivalent shear modulus of flat wire in the preset flat wire mechanical simulation model as the adjustment parameter value aims to apply the calculated new parameter value to the simulation model, thereby updating the internal state of the model and enabling subsequent simulation calculations based on more accurate physical properties.

[0058] This application's solution addresses the potential blindness or inefficiency in adjusting the equivalent shear modulus parameter in basic schemes by introducing a systematic feedback adjustment mechanism. Specifically, it first precisely quantifies the deviation between the simulation model and the actual physical process by calculating the target angle difference between the predicted and actual torsion angles. Subsequently, based on this target angle difference, the target adjustment amount for the equivalent shear modulus of the flat wire is determined. This makes parameter correction no longer an empirical guess, but a targeted adjustment based on quantified deviations. By calculating the current parameter value with the target adjustment amount, a new adjustment parameter value is obtained and applied to the simulation model, thereby achieving iterative optimization of the model parameters. This closed-loop adjustment process ensures that the simulation model can continuously learn and adapt to the actual mechanical behavior of the flat wire, gradually improving its predictive ability and ultimately achieving a state that highly matches reality.

[0059] The above technical solution enables precise and automated adjustment of the equivalent shear modulus parameter of flat wire in a pre-defined flat wire mechanical simulation model. Compared to traditional empirical or manual adjustment methods, this solution significantly improves the efficiency and accuracy of model parameter calibration and reduces the need for manual intervention. As a result, the simulation model can more quickly and accurately reflect the actual mechanical properties of flat wire, providing more reliable predictive data for subsequent winding control. This improves the accuracy and stability of the automated control of the entire motor winding process, effectively avoiding winding defects or low production efficiency caused by inaccurate models.

[0060] This application further proposes a more refined method for determining the target adjustment amount of the equivalent shear modulus of flat wire based on the target angle difference. By introducing a preset correspondence, the adjustment process is made more intelligent and precise.

[0061] In this regard, such as Figure 2 As shown, this application further proposes a step for determining the target adjustment amount of the equivalent shear modulus of flat wire based on the aforementioned target angle difference, including:

[0062] S201. Obtain the first preset correspondence.

[0063] The first preset correspondence includes a one-to-one correspondence between multiple angle difference ranges and multiple adjustment coefficients.

[0064] S202, take the adjustment coefficient corresponding to the target angle difference in the first preset correspondence as the target adjustment coefficient.

[0065] S203. The product of the target adjustment coefficient and the difference in the target angle is taken as the target adjustment amount.

[0066] Specifically, the first pre-defined correspondence can be understood as a pre-established lookup table or functional relationship. Its purpose is to systematically determine the adjustment value for the equivalent shear modulus of the flat wire based on the degree of difference between the predicted torsion angle and the actual torsion angle during the bending process. This correspondence is usually established and optimized through a large amount of experimental data, simulation analysis, or expert experience. Multiple angle difference ranges refer to dividing the difference between the predicted torsion angle and the actual torsion angle (i.e., the target angle difference) into several intervals, such as 0 degrees to 2 degrees, 2 degrees to 5 degrees, 5 degrees to 10 degrees, etc. Each angle difference range corresponds to a specific adjustment coefficient, which is used to quantify the adjustment intensity to be applied under different angle differences.

[0067] In practical applications, after obtaining the target angle difference, the system queries a first preset correspondence to find the angle difference range within which the target angle difference falls, and obtains the adjustment coefficient corresponding to that range, using it as the target adjustment coefficient. For example, if the target angle difference is 7 degrees, and the first preset correspondence contains an angle difference range of 5 to 10 degrees with a corresponding adjustment coefficient of 0.6, then 0.6 is determined as the target adjustment coefficient. Subsequently, the target adjustment coefficient is multiplied by the target angle difference, and the result is the target adjustment amount for the equivalent shear modulus of the flat wire. This adjustment method based on preset correspondence ensures that the adjustment of the equivalent shear modulus is more reasonable and accurate under different levels of deviation.

[0068] The solution proposed in this application establishes a nonlinear, piecewise, or more refined mapping relationship between the difference between the predicted and actual torsion angles (target angle difference) and the target adjustment amount of the equivalent shear modulus of flat wire by introducing a first pre-defined correspondence. When the target angle difference is small, a smaller adjustment coefficient may be needed for fine-tuning; while when the target angle difference is large, a larger adjustment coefficient may be needed for rapid convergence. This mechanism makes the adjustment of the equivalent shear modulus of flat wire no longer a simple linear relationship, but rather allows for the intelligent selection of an appropriate adjustment intensity based on the magnitude and nature of the actual deviation. It is precisely because of this refined adjustment strategy that the pre-defined flat wire mechanical simulation model can converge to a state consistent with the actual situation more quickly and accurately, thereby improving the prediction accuracy and stability of the simulation model.

[0069] Through the above technical solution, this application enables precise and intelligent adjustment of the equivalent shear modulus parameter value of flat wire. Compared with traditional empirical or simple linear adjustment methods, the introduction of a first preset correspondence allows the adjustment process to select the most suitable adjustment coefficient based on the specific magnitude of the target angle difference, thereby avoiding over-adjustment or under-adjustment. This not only significantly improves the calibration efficiency and accuracy of the preset flat wire mechanical simulation model, but also enhances the robustness and adaptability of the automated control method for the entire motor winding process, ensuring that the torsional behavior prediction of the flat wire during bending is closer to reality, and providing more reliable basic data for subsequent winding control.

[0070] This application proposes a more accurate and real-time method for obtaining material property information, especially when the material property information includes the material's elastic modulus. The method uses acoustic wave detection technology to determine the material's elastic modulus, thereby improving the accuracy and efficiency of automated control of the entire winding process.

[0071] like Figure 3As shown, in the above-mentioned automated control method for the motor winding process, when the material property information includes the material's elastic modulus, the material property information is obtained, including:

[0072] S301, Control the sound wave emitting device to emit sound waves to the flat wire.

[0073] S302. Detection of acoustic velocity in flat wire based on time-of-flight method.

[0074] S303. Determine the elastic modulus of the material based on the sound wave velocity.

[0075] Specifically, material property information can be understood as a set of parameters describing the physical and mechanical properties of flat wires. Among these, the elastic modulus is a crucial indicator of a material's resistance to elastic deformation and is essential for accurately predicting the mechanical behavior of flat wires during bending. To accurately obtain this elastic modulus, this application employs a non-contact detection method. In this method, an acoustic wave emitting device is configured to emit acoustic waves, such as ultrasonic waves, into the flat wire. This acoustic wave emitting device can be a piezoelectric transducer or other device capable of generating mechanical waves. The propagation speed of acoustic waves in the flat wire is closely related to the material's elastic modulus, density, and other physical properties.

[0076] Furthermore, Time-of-Flight (TOF) is a commonly used technique for measuring the speed of sound. This method calculates the speed of sound in a material by measuring the time it takes for a sound wave to travel from the transmitting device to the receiving device, and combining this with the known distance the sound wave travels through the flat wire. For example, a sound receiving device can be positioned opposite a sound transmitting device; as the sound wave passes through the flat wire, its speed can be obtained by measuring the propagation time.

[0077] Therefore, once the propagation speed of sound waves in a flat wire is obtained, the elastic modulus of the material can be calculated based on the principles of materials mechanics and acoustics, combined with known parameters such as the density of the flat wire. For example, for isotropic materials, there is a specific mathematical relationship between the speed of sound and the elastic modulus, and the elastic modulus of the material can be deduced from this relationship.

[0078] The solution presented in this application effectively addresses the aforementioned problems by utilizing the inherent physical relationship between the propagation speed of sound waves in materials and the elastic modulus of those materials. By controlling a sound wave emitting device to emit sound waves into the flat wire and accurately detecting the propagation speed of the sound waves in the flat wire using the time-of-flight method, non-contact, real-time or near-real-time measurement of the elastic modulus of the flat wire material can be achieved. The propagation speed of sound waves directly reflects the stiffness characteristics of the material, i.e., the elastic modulus. Therefore, the material elastic modulus data obtained in this way has higher accuracy and real-time performance compared to traditional offline testing or empirical estimation. Using this precise material elastic modulus information as input can significantly improve the accuracy of the preset flat wire mechanical simulation model, making the predicted torsional angle output by the model closer to the actual situation, thereby providing a more reliable basis for subsequent winding control.

[0079] Through the above technical solution, this application can achieve accurate, real-time or near-real-time acquisition of material property information of flat wire, especially the material's elastic modulus. This acoustic wave-based detection method has the advantages of being non-contact and non-destructive, avoiding the damage to the wire that may be caused by traditional measurement methods, and can adapt to the needs of automated production lines, realizing online monitoring of material parameters. Therefore, the acquired material elastic modulus data is more accurate and reliable, significantly improving the prediction accuracy of the preset flat wire mechanical simulation model, making the predicted torsional angle of the flat wire during bending more consistent with the actual situation. This directly helps to improve the accuracy and stability of automated control in the motor winding process, reduce winding defects caused by inaccurate material property parameters, and thus improve product quality and production efficiency.

[0080] Specifically, in some of the above embodiments, determining the elastic modulus of a material based on the sound wave velocity includes:

[0081] Obtain the density of the flat wire; use the product of density and the square of the sound wave velocity as the material's elastic modulus.

[0082] The density of the flat wire refers to the mass of the flat wire per unit volume, which can be obtained through conventional measurement methods, such as weighing and volume measurement. The velocity of sound refers to the speed at which sound waves propagate through the flat wire, which has been determined using time-of-flight methods. Multiplying the density by the square of the velocity of sound yields the material's elastic modulus. This calculation method is based on the principles of materials mechanics and acoustics, linking macroscopically measurable physical quantities with the microscopic mechanical properties of the material.

[0083] This application proposes a method to determine the elastic modulus of a material by obtaining the density of a flat wire and the propagation speed of sound waves within it, and then using the product of the density and the square of the sound wave velocity. This principle is based on the physical properties of elastic waves propagating in solid media. When sound waves propagate in an elastic medium, their velocity has a specific mathematical relationship with the medium's elastic modulus and density. Specifically, for longitudinal waves propagating in isotropic solids, the square of their velocity is directly proportional to the elastic modulus and inversely proportional to the density. Therefore, by measuring the sound wave velocity and the material density, the material's elastic modulus can be deduced. This method provides a non-contact and relatively accurate means of measuring the material's elastic modulus, offering reliable input parameters for subsequent adjustments to mechanical simulation models.

[0084] The above technical solution provides a scientific and accurate method for determining the elastic modulus of materials. This method utilizes the inherent physical properties of materials, calculating the elastic modulus through easily measurable density and sound wave velocity, avoiding the errors and time-consuming issues that may exist in traditional mechanical testing methods. Therefore, it is possible to obtain material property information of flat wire more accurately, thereby improving the accuracy of the preset flat wire mechanical simulation model, providing more reliable data support for the automated control of the motor winding process, and ultimately improving winding accuracy and efficiency.

[0085] This application further proposes an automated control method for the motor winding process. Before inputting motion state information, force state information, and material property information into a preset flat wire mechanical simulation model to obtain the predicted torsional angle of the flat wire during the bending process output by the preset flat wire mechanical simulation model, the method further includes:

[0086] Obtain the second preset correspondence and the hardness value of the flat wire; the second preset correspondence includes a one-to-one correspondence between multiple hardness value ranges and multiple flat wire mechanical simulation models; the flat wire mechanical simulation model corresponding to the hardness value range in the second preset correspondence is used as the preset flat wire mechanical simulation model.

[0087] Specifically, before inputting the motion state information, stress state information, and material property information of the flat wire into the preset flat wire mechanical simulation model, it is first necessary to obtain the second preset correspondence and the hardness value of the flat wire to be processed. The second preset correspondence can be understood as a pre-established mapping table or database, which stores a one-to-one correspondence between multiple hardness value ranges and multiple flat wire mechanical simulation models. For example, when the hardness value of the flat wire falls within a specific hardness value range, the system will specify a particular flat wire mechanical simulation model to use. The hardness value of the flat wire can be obtained through real-time or offline detection using conventional hardness measuring equipment (such as Vickers hardness testers, Rockwell hardness testers, etc.). After obtaining the hardness value of the flat wire, the system will look up its corresponding hardness value range in the second preset correspondence based on that hardness value, and select the flat wire mechanical simulation model corresponding to that hardness value range as the preset flat wire mechanical simulation model used for this winding control.

[0088] The solution proposed in this application dynamically selects a suitable pre-set mechanical simulation model for flat wire based on the hardness value of the flat wire before inputting motion state information, stress state information, and material property information into the pre-set mechanical simulation model. This ensures that the simulation model used is more closely matched with the actual physical properties of the flat wire. Hardness value is an important indicator reflecting a material's resistance to plastic deformation and is closely related to the mechanical response (including torsion angle) of the flat wire during bending. Therefore, selecting different mechanical simulation models for flat wires with different hardness values ​​can significantly improve the initial accuracy of the predicted torsion angle and reduce the initial deviation between the predicted and actual torsion angles. This helps to accelerate the convergence speed of subsequent adjustments to the equivalent shear modulus parameters of the flat wire and improve the accuracy of the adjusted pre-set mechanical simulation model for flat wire.

[0089] Through the above technical solution, this application can adaptively select the most suitable mechanical simulation model based on the hardness value of the flat wire, thereby significantly improving the initial accuracy of predicting the torsion angle. This not only improves the applicability and robustness of the flat wire mechanical simulation model, enabling it to better handle different batches or types of flat wire, but also shortens the number of iterations for model adjustment and accelerates the speed at which the system reaches a stable control state. Therefore, the overall automated control method for the motor winding process can achieve higher precision and efficiency, effectively reducing winding defects caused by model mismatch and improving product quality.

[0090] This application further proposes a scheme to refine and optimize the winding control process, so as to more comprehensively consider the actual state of flat wire and ensure the automation and high quality of the winding process.

[0091] Specifically, the winding control of flat wire is performed based on the adjusted preset flat wire mechanical simulation model, including the following steps:

[0092] The current motion state, current stress state, and material property information of the flat wire are input into the adjusted preset flat wire mechanical simulation model to obtain the current predicted torsion angle of the flat wire during bending, output by the adjusted preset flat wire mechanical simulation model. The current predicted torsion angle is input into the preset flat wire control model to obtain the initial control information for suppressing the torsion of the flat wire, output by the preset flat wire control model. The internal damage index of the flat wire is obtained. The initial control information is adjusted according to the internal damage index to obtain and execute the target control information.

[0093] The process involves inputting the current motion state, current stress state, and material property information of the flat wire into a pre-defined flat wire mechanical simulation model after adjustment. The aim is to obtain the predicted torsional angle of the flat wire under the current operating conditions in real time, providing immediate data support for subsequent control decisions. The current motion state information may include the feed rate and bending radius of the flat wire; the current stress state information may include the tension and pressure experienced by the flat wire; and the material property information may refer to the elastic modulus and yield strength of the flat wire.

[0094] Furthermore, the current predicted torsion angle is input into the preset flat wire control model. The purpose is to generate preliminary control commands, i.e., initial control information, based on the predicted torsion angle, to suppress unwanted torsion of the flat wire during the winding process. The preset flat wire control model can be a rule-based controller, a PID controller, or a more complex adaptive controller, and its output initial control information may include traction force, bending torque, or speed adjustment, etc.

[0095] Furthermore, obtaining the internal damage index of the flat wire is one of the key features of this solution. The internal damage index is used to quantify the microstructural changes or fatigue damage that may occur in the flat wire during the winding process. This index can be a dimensionless value; the larger the value, the more severe the internal damage of the flat wire. Its purpose is to provide direct evidence of the material's health status for subsequent control and adjustment.

[0096] Finally, the initial control information is adjusted based on the internal damage index to obtain and execute the target control information. This means that the initial control information is not the final instruction to be executed, but needs to be modified according to the actual damage condition of the flat wire. When the internal damage index is high, it may be necessary to make conservative adjustments to the initial control information, such as reducing the traction force or the bending speed, to avoid further damage or even breakage; conversely, when the damage index is low, the control parameters can be maintained or appropriately optimized to improve winding efficiency. Thus, the target control information is an optimized control instruction that better suits the current state of the flat wire after damage assessment.

[0097] The solution proposed in this application effectively solves the problem that existing technologies rely solely on mechanical simulation models for control and cannot fully consider the actual damage state of materials by introducing an internal damage index for flat wires and adjusting the initial control information accordingly.

[0098] Specifically, based on the current predicted torsion angle obtained from the adjusted preset flat wire mechanical simulation model and the generation of initial control information, this scheme further obtains the internal damage index of the flat wire. This damage index can reflect the fatigue accumulation or microstructural changes experienced by the flat wire during winding in real time, thus providing the control system with key information about the material's health status. By incorporating this internal damage index into the control decision, the system can dynamically and adaptively correct the initial control information according to the actual damage level of the flat wire. For example, when a high internal damage index is detected in the flat wire, the control system can correspondingly reduce the winding speed, decrease the traction force, or adjust the bending path to alleviate further stress on the wire, thereby avoiding wire breakage or performance degradation due to excessive fatigue or damage accumulation. This feedback adjustment mechanism based on the damage index makes winding control no longer a simple mechanical parameter matching, but an intelligent decision combining the material's health status, significantly improving the precision and robustness of the control.

[0099] Through the above technical solution, this application enables more refined and intelligent control of the flat wire winding process. By acquiring and utilizing the internal damage index of the flat wire in real time, the control system can dynamically adjust the winding parameters, effectively avoiding wire breakage or performance degradation caused by material fatigue or damage accumulation, thereby significantly improving the stability and reliability of the winding process. Furthermore, this solution helps extend the service life of the flat wire, reduce the scrap rate, and ultimately improve the overall quality and reliability of the motor products. Compared to control methods that rely solely on mechanical simulation models, this solution can more comprehensively consider the actual state of the flat wire, significantly improving the automation level and quality control capabilities of the winding process.

[0100] This application further proposes a method for obtaining the internal damage index of flat wires. This method uses optical detection and spectral analysis to non-destructively assess the degree of internal damage of flat wires, thereby providing a reliable basis for subsequent control and adjustment.

[0101] Specifically, obtaining the internal damage index of the aforementioned flat wire includes the following steps:

[0102] The light source is controlled to irradiate the flat wire to obtain its spectral data; the spectral data is analyzed to obtain the current spectral information; the similarity between the current spectral information and the preset spectral information when the flat wire is undamaged is determined; the reciprocal of the similarity is used as the internal damage index.

[0103] Controlling the illumination of flat wires with a light source refers to illuminating the surface or interior of the flat wire with one or more light sources. This light source can be visible light, infrared light, ultraviolet light, or other electromagnetic waves of specific wavelengths. The purpose is to excite the molecules or crystal structure within the flat wire to produce a specific spectral response. Obtaining the spectral data of the flat wire can be understood as collecting and recording curves or data showing the intensity of light reflected, transmitted, or emitted by the flat wire under illumination as a function of wavelength, using a spectrometer or similar optical sensor. This spectral data carries information about the internal structure and material state of the flat wire.

[0104] Furthermore, spectral analysis of the spectral data involves mathematically processing the acquired spectral data, such as using Fourier transform and wavelet analysis, to extract the frequency components and their intensities, thereby obtaining the current spectral information. This current spectral information can more clearly reflect the microstructural changes within the flat wire, such as lattice defects, stress concentrations, and microcracks.

[0105] Furthermore, determining the similarity between the current spectral information and the preset spectral information when the flat wire is undamaged refers to comparing the currently analyzed spectral information with the preset spectral information that represents the flat wire in an ideal undamaged state. Similarity can be calculated using various mathematical methods, such as correlation coefficient, Euclidean distance, and cosine similarity, with the aim of quantifying the degree of deviation between the current internal state of the flat wire and the undamaged state. The preset spectral information can be collected and stored when the flat wire leaves the factory or after rigorous testing confirms it is undamaged.

[0106] Finally, the reciprocal of the similarity is used as the internal damage index. This means that the lower the similarity (i.e., the greater the difference between the current state and the undamaged state), the higher the internal damage index, and vice versa. This reciprocal relationship can intuitively reflect the degree of damage, providing a quantitative basis for subsequent control adjustments. For example, when the similarity is close to 1, the internal damage index is close to 1, indicating minimal damage; when the similarity decreases, the internal damage index increases significantly, indicating aggravated damage.

[0107] This application's solution assesses internal damage by utilizing the influence of changes in the internal structure of flat wire on its spectral response. When damage occurs within the flat wire (such as microcracks, lattice defects, stress concentration, etc.), its light absorption, reflection, or scattering characteristics change, leading to corresponding changes in its spectral data. By controlling the light source to illuminate the flat wire and acquiring its spectral data, these subtle optical changes can be captured. Subsequently, spectral analysis of the spectral data transforms these changes into quantifiable spectral information, making the characteristics of internal damage more prominent. Comparing the current spectral information with the preset spectral information when there is no damage allows for an objective assessment of the deviation between the current internal state and the healthy state of the flat wire. Finally, by using the reciprocal of the similarity as an internal damage index, the degree of internal damage to the flat wire is quantified, providing precise and real-time input for subsequent winding control adjustments based on the degree of damage. This avoids the problem of decreased winding quality or further wire damage caused by undetected and untreated damage.

[0108] Through the above technical solution, this application enables non-destructive, real-time, and quantitative detection of internal damage in flat wires. Compared to traditional visual inspection or destructive testing methods, this solution avoids secondary damage to the flat wires, improving detection efficiency and accuracy. By obtaining an accurate internal damage index, control parameters during the winding process, such as traction force and bending angle, can be adjusted more precisely, thereby effectively suppressing torsion, deformation, or breakage of the flat wires due to internal damage during winding. This significantly improves the automation control level and product quality of the motor winding process and extends the service life of the flat wires.

[0109] This application further proposes initial control information including initial traction force, adjusting the initial control information based on the internal damage index to obtain and execute target control information, including:

[0110] Obtain the third preset correspondence; the third preset correspondence includes a one-to-one correspondence between multiple internal damage index ranges and multiple traction force adjustment coefficients; take the traction force adjustment coefficient corresponding to the internal damage range in which the internal damage index is located in the third preset correspondence as the target traction force adjustment coefficient; take the product of the initial traction force and the target traction force adjustment coefficient as the target traction force in the target control information, and execute the target control information.

[0111] Specifically, the third preset correspondence refers to a pre-established set of rules used to guide traction adjustment. This correspondence divides the internal damage index of flat wire into multiple discrete internal damage index ranges, and presets a specific traction adjustment coefficient for each range.

[0112] This design aims to provide corresponding traction force adjustment suggestions based on the degree of damage to the flat wire. For example, when the internal damage index is low, the traction force adjustment coefficient may be close to 1 or slightly greater than 1 to maintain normal winding efficiency; while when the internal damage index is high, the traction force adjustment coefficient may be less than 1 to reduce traction force, thereby reducing further stress on the damaged wire. The target traction force adjustment coefficient is a specific value determined by querying a third preset correspondence based on the currently acquired internal damage index of the flat wire. This coefficient directly reflects the degree of traction force adjustment required under the current damage state. In practical applications, the target traction force in the target control information is obtained by multiplying the initial traction force by the target traction force adjustment coefficient. The initial traction force is the original traction force value output by the preset flat wire control model, used to suppress flat wire torsion. By multiplying by the target traction force adjustment coefficient, dynamic adjustment of the initial traction force can be achieved, making it more adaptable to the actual damage condition of the flat wire.

[0113] This application solves the aforementioned problem by introducing a third preset correspondence and dynamically adjusting the initial traction force based on the internal damage index of the flat wire. Specifically, after obtaining the internal damage index of the flat wire, the system queries a pre-set third preset correspondence. This correspondence associates different ranges of internal damage indices with corresponding traction force adjustment coefficients. In this way, a target traction force adjustment coefficient can be accurately determined based on the actual damage level of the flat wire. Subsequently, multiplying the initial traction force by this target traction force adjustment coefficient yields the target traction force used for winding control. This mechanism ensures that the traction force can be adaptively adjusted according to the damage condition of the flat wire, avoiding excessive traction force that exacerbates damage or insufficient traction force that affects winding efficiency.

[0114] Through the above technical solution, this application enables precise and adaptive control of the traction force during the winding process of flat wire. Compared to a solution that only makes general adjustments based on the internal damage index, this application establishes a quantitative correspondence between the internal damage index and the traction force adjustment coefficient, making the traction force adjustment more accurate and reasonable. This not only effectively avoids unnecessary damage to the flat wire during the winding process and extends the wire's service life, but also optimizes the winding process parameters and improves the intelligence level of automation control and production efficiency while ensuring wire safety.

[0115] This application also discloses an automated control system for the motor winding process, which aims to achieve adaptive adjustment of the mechanical simulation model of flat wire by introducing physical devices, thereby realizing accurate prediction and effective control of torsion phenomena during the winding process of flat wire, significantly improving winding quality and production efficiency. The system includes an acquisition device and a processing device.

[0116] An acquisition device is used to acquire motion state information, stress state information, and material property information of a flat wire. Specifically, the acquisition device may include, but is not limited to: motion sensors for acquiring motion state information, such as encoders or laser rangefinders mounted on winding equipment; force sensors or tension sensors for acquiring stress state information, such as strain gauge sensors installed on the wire feeding path; and input modules or detection modules for acquiring material property information, such as a user interface for receiving manually input material parameters, or dedicated detection equipment for performing material physical tests. In some embodiments, the motion sensor can monitor the linear velocity and position of the flat wire in real time, the force sensor can accurately measure the traction force on the wire, and the material property information can be obtained by querying a pre-stored database or through simple physical tests (such as density measurement).

[0117] A processing device is used to execute the various processing functions proposed in this application. Specifically, the processing device may be one or more processors, such as a central processing unit (CPU), a graphics processing unit (GPU), a digital signal processor (DSP), or an application-specific integrated circuit (ASIC), and may be configured with memory for storing program instructions and data.

[0118] The processing device inputs motion state information, stress state information, and material property information into a preset flat wire mechanical simulation model to obtain the predicted torsional angle of the flat wire during bending, as output by the preset flat wire mechanical simulation model. Specifically, the processing device can run a mechanical simulation software module, which is built based on finite element analysis or multibody dynamics principles. This module can receive various parameters from the acquisition device and perform complex numerical calculations to predict the torsional angle of the flat wire under specific bending conditions.

[0119] The processing unit is also used to obtain the actual torsion angle of the flat wire. This can be achieved by integrating with a vision inspection system; for example, the processing unit can receive image data of the flat wire taken by a high-speed camera and analyze the orientation of the wire cross-section using image processing algorithms to calculate the actual torsion angle.

[0120] The processing device is further used to adjust the parameter values ​​of the equivalent shear modulus of the flat wire in the preset flat wire mechanical simulation model based on the predicted torsion angle and the actual torsion angle, thereby obtaining the adjusted preset flat wire mechanical simulation model. This adjustment process can be completed by the adaptive control module inside the processing device, for example, by comparing the error between the predicted value and the actual value, and using preset adjustment rules or optimization algorithms (such as a simple proportional-integral-derivative control algorithm) to iteratively correct the equivalent shear modulus parameter.

[0121] Finally, the processing device controls the winding of the flat wire based on the adjusted preset flat wire mechanical simulation model. This means that the processing device uses an updated and more accurate simulation model to predict the torsional trend of the flat wire in real time and generate corresponding control commands, such as adjusting the movement trajectory and speed of the winding nozzle or the traction force of the wire, to ensure that the flat wire maintains the correct posture during the winding process.

[0122] The overall working principle of this application is as follows: The acquisition device first collects motion, stress, and material property information of the flat wire, providing comprehensive input data for the mechanical simulation model. Subsequently, the processing device inputs this information into a preset flat wire mechanical simulation model to predict the torsion angle of the flat wire during bending. To ensure the accuracy of the prediction, the processing device acquires the actual torsion angle and uses the difference between the predicted and actual torsion angles to adaptively adjust the equivalent shear modulus parameter value of the flat wire in the preset flat wire mechanical simulation model. This adjustment process allows the simulation model to be calibrated in real time, more accurately reflecting the actual mechanical behavior of the flat wire. Finally, based on the adjusted and more accurate preset flat wire mechanical simulation model, the processing device controls the winding of the flat wire. The entire process forms a closed-loop feedback control system, which, through continuous prediction, measurement, adjustment, and control, effectively solves the technical problem of easy torsion of flat wire during winding, ensuring winding quality and efficiency.

[0123] The core innovation of the automated control system for the motor winding process proposed in this application lies in its real-time adaptive adjustment of the mechanical simulation model of flat wire through the coordinated operation of physical devices. Traditional winding control systems often rely on preset fixed parameters and empirical models, which cannot effectively cope with the torsion problems caused by changes in material properties or external environmental disturbances that may occur in flat wires during actual winding. For example, the control logic of existing automated winding equipment is usually based on pre-set process parameters. Once the wire batch or winding conditions change, the accuracy of its prediction and control of flat wire torsion will decrease significantly, leading to an increase in winding defects and scrap rate.

[0124] In contrast, the system of this application acquires real-time motion, stress, and material property information of the flat wire through an acquisition device, and then processes this information into a mechanical simulation model for prediction. More importantly, the processing device can acquire the actual torsion angle of the flat wire and compare it with the prediction results of the simulation model, thereby dynamically adjusting key parameters in the simulation model, such as the equivalent shear modulus of the flat wire. This real-time adaptive adjustment mechanism, jointly implemented by the acquisition and processing devices, allows the simulation model to continuously learn and optimize, maintaining its accurate predictive ability of the mechanical behavior of the flat wire. Therefore, the processing device can generate more precise control commands based on more accurate prediction results, effectively suppressing the torsion of the flat wire and ensuring that the wire enters the stator slot in the correct posture. This system-level real-time adaptive control strategy significantly improves the automation level and control accuracy of the winding process, effectively solving the limitations of traditional methods in handling the torsion problem of flat wire, thereby improving the quality and production efficiency of motor winding.

[0125] The above are merely embodiments of this application and are not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. An automated control method for the motor winding process, characterized in that, Includes the following steps: Acquire motion, stress, and material properties information of flat wires; The motion state information, the force state information, and the material property information are input into a preset flat wire mechanical simulation model to obtain the predicted torsion angle of the flat wire during the bending process output by the preset flat wire mechanical simulation model. Obtain the actual torsion angle of the flat wire; The parameter values ​​of the equivalent shear modulus of the flat wire in the preset flat wire mechanical simulation model are adjusted according to the predicted torsion angle and the actual torsion angle to obtain the adjusted preset flat wire mechanical simulation model. The winding control of flat wire is performed based on the adjusted preset flat wire mechanical simulation model.

2. The automated control method for the motor winding process according to claim 1, characterized in that, The parameter values ​​of the equivalent shear modulus of the flat wire in the preset flat wire mechanical simulation model are adjusted according to the predicted torsion angle and the actual torsion angle to obtain the adjusted preset flat wire mechanical simulation model, including: The difference between the predicted torsion angle and the actual torsion angle is taken as the target angle difference. The target adjustment amount of the equivalent shear modulus of the flat wire is determined based on the target angle difference; The difference between the current parameter value of the equivalent shear modulus of the flat wire and the target adjustment amount is used as the adjustment parameter value of the equivalent shear modulus of the flat wire. The parameter value of the equivalent shear modulus of flat wire in the preset flat wire mechanical simulation model is set to the adjusted parameter value to obtain the adjusted preset flat wire mechanical simulation model.

3. The automated control method for the motor winding process according to claim 2, characterized in that, Determining the target adjustment amount for the equivalent shear modulus of flat wire based on the target angle difference includes: Obtain a first preset correspondence; the first preset correspondence includes a one-to-one correspondence between multiple angle difference ranges and multiple adjustment coefficients; The adjustment coefficient corresponding to the target angle difference in the first preset correspondence is used as the target adjustment coefficient; The product of the target adjustment coefficient and the target angle difference is taken as the target adjustment amount.

4. The automated control method for the motor winding process according to claim 1, characterized in that, When the material property information includes the material elastic modulus, obtaining the material property information includes: Control the sound wave emitting device to emit sound waves toward the flat wire; The acoustic velocity in the flat wire was detected using the time-of-flight method. The elastic modulus of the material is determined based on the sound wave velocity.

5. The automated control method for the motor winding process according to claim 4, characterized in that, Determining the elastic modulus of the material based on the sound wave velocity includes: Obtain the density of the flat wire; The product of the density and the square of the sound wave velocity is taken as the elastic modulus of the material.

6. The automated control method for the motor winding process according to claim 4, characterized in that, Before inputting the motion state information, the force state information, and the material property information into a preset flat wire mechanical simulation model to obtain the predicted torsion angle of the flat wire during bending as output by the preset flat wire mechanical simulation model, the method further includes: Obtain the second preset correspondence and the hardness value of the flat wire; the second preset correspondence includes a one-to-one correspondence between multiple hardness value ranges and multiple flat wire mechanical simulation models; The mechanical simulation model of flat wire corresponding to the hardness value range in the second preset correspondence is used as the preset mechanical simulation model of flat wire.

7. The automated control method for the motor winding process according to claim 1, characterized in that, The winding control of flat wire is performed based on the adjusted preset flat wire mechanical simulation model, including: The current motion state information, current stress state information, and material property information of the flat wire are input into the adjusted preset flat wire mechanical simulation model to obtain the current predicted torsion angle of the flat wire during the bending process output by the adjusted preset flat wire mechanical simulation model. The current predicted torsion angle is input into the preset flat wire control model to obtain the initial control information output by the preset flat wire control model for suppressing flat wire torsion. Obtain the internal damage index of the flat wire; The initial control information is adjusted based on the internal damage index to obtain and execute the target control information.

8. The automated control method for the motor winding process according to claim 7, characterized in that, Obtaining the internal damage index of the flat wire includes: The flat wire is illuminated by a light source to obtain its spectral data. Perform spectral analysis on the spectral data to obtain the current spectral information; Determine the similarity between the current spectrum information and the preset spectrum information when the flat wire is undamaged; The reciprocal of the similarity is used as the internal damage index.

9. The automated control method for the motor winding process according to claim 7, characterized in that, Initial control information includes initial traction force. This initial control information is adjusted based on the internal damage index to obtain and execute target control information, including: Obtain a third preset correspondence; the third preset correspondence includes a one-to-one correspondence between multiple internal damage index ranges and multiple traction force adjustment coefficients; The traction force adjustment coefficient corresponding to the internal damage range in the third preset correspondence is taken as the target traction force adjustment coefficient. The product of the initial traction force and the target traction force adjustment coefficient is used as the target traction force in the target control information, and the target control information is executed.

10. An automated control system for the motor winding process, characterized in that, include: Acquisition device and processing device; The acquisition device is used to acquire motion state information, stress state information and material property information of the flat wire; The processing device is used to input the motion state information, the force state information and the material property information into a preset flat wire mechanical simulation model to obtain the predicted torsion angle of the flat wire during the bending process output by the preset flat wire mechanical simulation model. The processing device is used to obtain the actual torsion angle of the flat wire; The processing device is used to adjust the parameter value of the equivalent shear modulus of the flat wire in the preset flat wire mechanical simulation model according to the predicted torsion angle and the actual torsion angle, so as to obtain the adjusted preset flat wire mechanical simulation model. The processing device is used to control the winding of flat wires based on an adjusted preset flat wire mechanical simulation model.

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