System optimization method based on motor parameter estimation and motor tactile feedback system

Abstract

The present application relates to the technical field of motor parameter estimation, and discloses a system optimization method based on motor parameter estimation and a motor tactile feedback system, wherein the method includes: calculating the damping motion frequency of the motor according to the detected back electromotive force of the motor in the aftershock stage; calculating the damping ratio of the motor in the aftershock stage according to the attenuation curve of the back electromotive force and the damping motion frequency; calculating the magnetic induction intensity coefficient of the motor according to the damping ratio and the maximum value of the back electromotive force; and adjusting the excitation signal and braking signal of the motor using the magnetic induction intensity coefficient of the motor and the damping ratio of the motor in the aftershock stage.

Description

Technical Field

[0001] The present application relates to the technical field of motor parameter estimation, for example, to a system optimization method based on motor parameter estimation and a motor tactile feedback system. Background Art

[0002] Currently, during motor haptic feedback testing, key motor parameters, such as the magnetic flux density coefficient and damping ratio, directly affect the motor's vibration intensity and braking performance, thus affecting the haptic feedback effect. Ensuring a good, consistent haptic feedback experience across different motors requires good, consistent key motor parameters and matching excitation signals.

[0003] The relevant technology provides a method for estimating the mass of a motor vibrator. First, an estimated mass value is obtained by estimating the mass of the motor vibrator. Then, the vibrator acceleration value of the motor is calculated based on the estimated mass value, the tooling acceleration and the tooling mass value. Then, the mass verification value of the motor is calculated based on the vibrator acceleration value and the voltage and current at both ends of the motor. Then, it is determined whether the estimated mass value is equal to the mass verification value. If so, the estimated mass value is the actual mass value of the motor vibrator. If not, the estimated mass value is corrected and the calculation and judgment continue.

[0004] During the implementation of the embodiments of the present disclosure, it was found that at least the following problems exist in the related art:

[0005] Due to factors such as manufacturing costs, processes, and aging during the motor's life cycle, there are differences in key motor parameters between different motors. As a result, under a fixed excitation signal, different motors have different vibration intensities and braking performances, leading to inconsistent tactile feedback experience between different motors.

[0006] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of this application, and therefore may include information that does not constitute prior art known to ordinary technicians in this field. Summary of the Invention

[0007] In order to provide a basic understanding of some aspects of the disclosed embodiments, a brief summary is given below. The summary is not an extensive review, nor is it intended to identify key / critical elements or delineate the scope of protection of these embodiments, but rather serves as a prelude to the detailed description that follows.

[0008] The embodiments of the present disclosure provide a system optimization method, computing device, motor tactile feedback system and storage medium based on motor parameter estimation, so that the vibration intensity and braking performance of different motor individuals are maintained within an appropriate range, thereby improving the consistency of the tactile feedback experience.

[0009] In some embodiments, the system optimization method based on motor parameter estimation is applied to a motor tactile feedback system, including:

[0010] Calculate the damping motion frequency of the motor according to the detected back electromotive force of the motor in the residual vibration stage;

[0011] Calculating the damping ratio of the motor in the residual vibration stage according to the attenuation curve of the back electromotive force and the damping motion frequency;

[0012] Calculating the magnetic induction coefficient of the motor according to the damping ratio and the maximum value of the back electromotive force envelope;

[0013] The motor's excitation signal and braking signal are adjusted using the motor's magnetic induction coefficient and the motor's damping ratio in the residual vibration stage.

[0014] Optionally, calculating the damped motion frequency of the motor according to the back electromotive force of the motor in the residual vibration stage includes:

[0015] After the current excitation signal is played, the back electromotive force signal of the motor is detected and the corresponding zero-crossing point information is generated;

[0016] The damping motion frequency of the motor is calculated according to the zero-crossing point index and the zero-crossing point moment of the back electromotive force in the zero-crossing point information.

[0017] Optionally, calculating the damping motion frequency of the motor damper according to the zero-crossing index and the zero-crossing moment of the back electromotive force in the zero-crossing information includes:

[0018] calculate Get the damping motion frequency f of the motor d ;

[0019] Among them, C n is the zero-crossing moment of the nth reverse electromotive force, C m is the zero-crossing moment of the mth back electromotive force, m and n are positive integers greater than or equal to 1 and not equal, and Fs is the sampling frequency.

[0020] Optionally, calculating the damping ratio of the motor in the residual vibration stage according to the attenuation curve of the back electromotive force and the damped motion frequency includes:

[0021] Perform envelope fitting on the attenuation curve of the back electromotive force to obtain the envelope of the back electromotive force;

[0022] Based on the envelope of the back electromotive force, calculate the damping ratio of the motor in the residual vibration stage.

[0023] Optionally, calculating the damping ratio of the motor in the residual vibration stage according to the envelope of the back electromotive force includes:

[0024] calculate Obtain the damping ratio ζ of the motor in the aftershock stage;

[0025] in,

[0026] in,

[0027] Where, ζ is the damping ratio, f d is the damping motion frequency, ω d is the damping angular frequency, P and Q are coefficients determined based on the number K of samples of the envelope in the aftershock phase. For t i According to the back electromotive force envelope at the moment The sampled back electromotive force value, ω n is the angular frequency of the motor's free oscillation, BLv Max is the maximum value of the back electromotive force envelope of the motor in the residual vibration stage.

[0028] Optionally, the calculating of the magnetic induction coefficient of the motor according to the damping ratio and the maximum value of the back electromotive force envelope includes:

[0029] calculate Get the angular frequency ω of the motor's free oscillation n ;

[0030] calculate Obtain the magnetic induction coefficient BL of the motor;

[0031] in,

[0032] Among them, e is the base of the natural logarithm, M and N are coefficients determined based on the number of samples K of the envelope in the aftershock phase. For t i According to the back electromotive force envelope at the moment The sampled back electromotive force value is BLv Max is the maximum value of the back electromotive force envelope of the motor in the residual vibration stage, m is the mass of the motor vibrator, U is the amplitude of the sine wave input at both ends of the linear motor, R e is the DC resistance in the coil path, ω d is the damping angular frequency, ζ is the damping ratio, f d is the damping motion frequency.

[0033] Optionally, the method further includes:

[0034] calculate Obtain the maximum value BLv Max of the back electromotive force envelope of the motor in the residual vibration stage.

[0035] Optionally, the method further includes:

[0036] According to the damping motion frequency of the motor, the damping angular frequency of the motor in the residual vibration stage is calculated.

[0037] Optionally, calculating the damping angular frequency of the motor in the aftershock stage according to the damping motion frequency of the motor includes:

[0038] Calculate ω d =2πf d , obtain the damping angular frequency ω of the motor in the residual vibration stage d ;

[0039] Among them, f d is the damping motion frequency.

[0040] In some embodiments, the computing device includes a processor and a memory storing program instructions, and the processor is configured to execute the system optimization method based on motor parameter estimation as described in the present application when running the program instructions.

[0041] In some embodiments, the motor tactile feedback system includes a computing device and a motor signal calibration device as described in the present application. The motor signal calibration device is used to use the magnetic induction intensity coefficient of the motor and the damping ratio of the motor in the aftershock stage to adjust the excitation signal and braking signal of the motor to adjust the tactile feedback of the motor in real time.

[0042] In some embodiments, the storage medium stores program instructions, and when the program instructions are run, they execute the system optimization method based on motor parameter estimation as described in the present application.

[0043] The system optimization method based on motor parameter estimation, computing device, motor tactile feedback system, and storage medium provided by the embodiments of the present disclosure can achieve the following technical effects:

[0044] This application calculates the damping motion frequency of the motor based on the back electromotive force of the motor in the after-vibration stage, and then calculates the damping ratio of the motor in the after-vibration stage based on the back electromotive force and the damping motion frequency. Then, the magnetic induction intensity coefficient of the motor is calculated based on the damping ratio and the maximum value of the back electromotive force envelope. In this way, it is possible to estimate the key parameters of the motor directly by collecting electrical signals, and use the estimated damping motion frequency, damping ratio and magnetic induction intensity coefficient of the current motor, so that in the subsequent driving process, the corresponding excitation signal and braking signal can be matched according to the estimated parameters, so that the vibration intensity and braking performance between different motor individuals are kept within an appropriate range, thereby improving the consistency of the tactile feedback experience.

[0045] The above general description and the following description are exemplary and explanatory only and are not intended to limit the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] One or more embodiments are exemplarily described by corresponding drawings. These exemplary descriptions and drawings do not limit the embodiments. Elements with the same reference numerals in the drawings are shown as similar elements. The drawings do not constitute a scale limitation. In addition,

[0047] Figure 1 This is a schematic diagram showing the different steady-state acceleration amplitudes caused by individual motor differences;

[0048] Figure 2 This is another diagram showing the different steady-state acceleration amplitudes caused by individual motor differences;

[0049] Figure 3 This is a diagram showing how large acceleration amplitude and unsafe motion range can occur due to individual differences in motors.

[0050] Figure 4 is a schematic diagram of a motor tactile feedback system provided by an embodiment of the present disclosure;

[0051] Figure 5 is a schematic diagram of a system optimization method based on motor parameter estimation provided by an embodiment of the present disclosure;

[0052] Figure 6 is a schematic diagram of another system optimization method based on motor parameter estimation provided by an embodiment of the present disclosure;

[0053] Figure 7 This is a schematic diagram of a zero-crossing point of the reverse electromotive force in the residual vibration stage of a motor provided by an embodiment of the present disclosure;

[0054] Figure 8 Schematic diagram of estimating the damping ratio of a motor vibrator in the residual vibration stage using the back electromotive force envelope provided by an embodiment of the present disclosure;

[0055] Figure 9 is a schematic diagram of matching an excitation signal of a motor based on a magnetic induction coefficient provided by an embodiment of the present disclosure;

[0056] Figure 10 It is a schematic diagram of a computing device provided by an embodiment of the present disclosure. DETAILED DESCRIPTION

[0057] In order to be able to understand the features and technical content of the embodiments of the present disclosure in more detail, the implementation of the embodiments of the present disclosure is described in detail below in conjunction with the accompanying drawings. The accompanying drawings are for reference only and are not used to limit the embodiments of the present disclosure. In the following technical description, for the sake of convenience of explanation, a full understanding of the disclosed embodiments is provided through multiple details. However, one or more embodiments can still be implemented without these details. In other cases, to simplify the drawings, well-known structures and devices can be simplified for display.

[0058] In the description and claims of the embodiments of the present disclosure, as well as in the accompanying drawings, the terms "first," "second," and the like are used to distinguish similar items and are not necessarily used to describe a particular order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate to describe the embodiments of the present disclosure herein. In addition, the terms "including," "having," and any variations thereof are intended to cover non-exclusive inclusions.

[0059] Unless otherwise stated, the term "plurality" means two or more.

[0060] In the embodiment of the present disclosure, the character " / " indicates that the preceding and following objects are in an "or" relationship. For example, A / B means: A or B.

[0061] The term "and / or" describes an association between objects, indicating that three relationships can exist. For example, A and / or B means: A or B, or A and B.

[0062] The term "correspondence" may refer to an association relationship or a binding relationship. The correspondence between A and B means that there is an association relationship or a binding relationship between A and B.

[0063] Among related technologies, tactile feedback, as a key means of human-computer interaction, has been widely adopted in various terminals, such as mobile phones, tablets, and game controllers. Tactile feedback technology can realistically simulate various natural vibrations, such as mechanical button presses, shooting, and motor vibrations.

[0064] For the motor control scheme with sensor feedback, it is usually based on the motor test model, and parameters such as the magnetic induction intensity coefficient and the damping ratio are set to be constant, so as to match the corresponding excitation signal and the brake signal. When the actual key parameters of the motor are not much different from the parameters of the motor test model, a relatively good tactile feedback experience can be provided. However, if the actual key parameters of the motor deviate greatly from the parameters of the motor test model, inconsistent tactile intensity will be caused. At the same time, the key parameters of the motor will also change with changes in the working environment of the motor (temperature, aging, etc.). Furthermore, some motors with large deviations in key motor parameters will be damaged due to excessive movement of the motor vibrator. In order to deal with the inconsistent tactile feedback in the related art, the voltage threshold of the excitation signal is often lowered during the large-scale use of motors to ensure that the motor vibrator has a safe movement range. This also means that in order to "protect" the travel safety of a small number of motor vibrators, the excitation signals of all motors are uniformly reduced.

[0065] Motor control solutions with sensor feedback, such as Hall effect sensors, can monitor the motor's motion state in real time. By calculating this motion state, the motor's resonant frequency can be tracked in real time, allowing the motor to be controlled at its optimal state. However, these solutions require integrating multiple Hall effect sensors within the motor, which is relatively costly. Another example is voltage-current feedback control, which monitors voltage and current in real time but cannot obtain parameters related to the motor's mechanical motion in real time.

[0066] Specifically, combined Figure 1 As shown, motor 1 has a normal magnetic flux density coefficient BL, and motor 2 has a larger magnetic flux density coefficient BL than motor 1. When the same excitation signal is input, there is a significant difference in the acceleration amplitude between motor 1 and motor 2 after steady state.

[0067] Similarly, combined Figure 2 As shown, motor 1 has a normal magnetic flux density coefficient BL, and motor 3 has a smaller magnetic flux density coefficient BL than motor 1. When the same excitation signal is input, the acceleration amplitudes of motor 1 and motor 3 after steady state also have obvious differences.

[0068] At the same time, combined Figure 3 As shown, when there are individual differences in motors, the resulting large acceleration amplitude will cause the motor vibrator to move a large distance, resulting in a shell cracking phenomenon, which deviates from the safe movement range of the motor vibrator.

[0069] The present disclosure provides a motor tactile feedback system, including a computing device and a motor signal calibration device as described in the present application. Figure 4As shown, while the computing device estimates the motor parameters, the motor is first placed in the fixture. The computing device then amplifies the matched excitation signal through a Class D power amplifier to excite the motor under test. After the motor vibrates, the motor signal calibration device samples the voltage, current, acceleration amplitude, and back EMF across the motor. The computing device receives the relevant parameters measured by the motor signal calibration device and estimates the key motor parameters to re-match the appropriate excitation signal.

[0070] The disclosed embodiment provides a system optimization method based on motor parameter estimation to solve the problem of different or changing key motor parameters due to individual differences in motors, which in turn causes inconsistent tactile experience and motor stroke safety protection. Figure 5 As shown, the method includes:

[0071] Step 501: The computing device calculates the damped motion frequency of the motor based on the detected back electromotive force of the motor in the residual vibration stage.

[0072] Step 502: The computing device calculates the damping ratio of the motor in the residual vibration stage according to the attenuation curve of the back electromotive force and the damping motion frequency.

[0073] Step 503: The computing device calculates the magnetic induction coefficient of the motor according to the damping ratio and the maximum value of the back electromotive force envelope.

[0074] Step 504: The computing device adjusts the excitation signal and the braking signal of the motor using the magnetic induction coefficient of the motor and the damping ratio of the motor in the residual vibration stage.

[0075] In the embodiments of this application, unlike feedback-based real-time control solutions, this application directly uses collected electrical signals to estimate motor parameters. Specifically, the motor's damped motion frequency, magnetic induction coefficient, and damping ratio are estimated using the back-electromotive force (BEMF) signal after each excitation signal is played. The estimated parameters are then applied during the subsequent driving process to match the corresponding excitation signal with the brake signal, resulting in a consistent tactile experience and safe motion travel.

[0076] The system optimization method based on motor parameter estimation provided by the embodiment of the present disclosure is adopted. The damped motion frequency of the motor is calculated according to the back electromotive force of the motor in the residual vibration stage, and then the damping ratio of the motor in the residual vibration stage is calculated according to the attenuation curve of the back electromotive force and the damped motion frequency. Then, the magnetic induction intensity coefficient of the motor is calculated based on the damping ratio and the maximum value of the back electromotive force envelope. In this way, it is possible to directly estimate the key parameters of the motor by collecting electrical signals, using the estimated damped motion frequency, damping ratio and magnetic induction intensity coefficient of the current motor. Therefore, in the subsequent driving process, the corresponding excitation signal and braking signal can be matched according to the estimated parameters, so that the vibration intensity and braking performance between different motor individuals are kept within an appropriate range, thereby improving the consistency of the tactile feedback experience.

[0077] Combine Figure 6 As shown, the embodiment of the present disclosure provides another system optimization method based on motor parameter estimation, including:

[0078] Step 601: After the current excitation signal is played, the computing device detects the back electromotive force signal of the motor and generates corresponding zero-crossing point information.

[0079] Step 602: The computing device calculates the damping motion frequency of the motor according to the zero-crossing index and the zero-crossing moment of the back electromotive force in the zero-crossing information.

[0080] Optionally, combined Figure 7 As shown, the damping motion frequency of the motor damper is calculated according to the zero-crossing index and zero-crossing moment of the back electromotive force in the zero-crossing information, including:

[0081] By calculation Get the damping motion frequency f of the motor d ;

[0082] Among them, C n is the zero-crossing moment of the nth reverse electromotive force, C m is the zero-crossing moment of the mth back electromotive force, m and n are positive integers greater than or equal to 1 and not equal, for example, 1, 2, 3, 4 or 5, and Fs is the sampling frequency.

[0083] At the same time, by calculating ω d =2πf d , to obtain the damping angular frequency ω of the motor in the residual vibration stage d , where f d is the damping motion frequency.

[0084] Step 603: The computing device performs envelope fitting on the attenuation curve of the back electromotive force to obtain an envelope line of the back electromotive force.

[0085] Specifically, combined Figure 8 As shown in the figure, after the excitation signal is played, the back electromotive force envelope formula of the motor that oscillates freely in the aftershock stage is:

[0086]

[0087] Among them, BLv Max is the maximum amplitude at the beginning of the aftershock stage, i.e., the maximum value of the back electromotive force envelope, ζ is the damping ratio of the oscillator aftershock motion, t is a certain moment in the aftershock stage, ε(t) is the value of the back electromotive force envelope at time t, e is the base of the natural logarithm, ω n is the angular frequency of the motor's free oscillation.

[0088] Step 604: The computing device calculates the damping ratio of the motor in the residual vibration stage according to the envelope of the back electromotive force.

[0089] Specifically, taking the natural logarithm of the motor back electromotive force envelope formula in step 603, we obtain:

[0090] Ln(ε(t))=Ln(BLv(t))=Ln(BLv Max )-ω n ζt

[0091] Furthermore, the parameter x1 is assigned to Ln(BLv Max ), that is, x1=Ln(BLv Max ), and assign parameter x2 to ω n ζ, that is, x2 = ω n ζ;

[0092] Furthermore, the least squares method is used to construct the cost (loss) function E:

[0093]

[0094] in,

[0095] Furthermore, we calculate the partial derivatives of the parameters x1 and x2 respectively and make the results equal to 0 to get the parameter estimates

[0096] equation:

[0097]

[0098] Furthermore, the parameter estimation equation is converted into a general matrix form:

[0099] y=Fx+w

[0100] Among them, the parameter vector to be estimated is Observation vector Observation time vector Measurement error vector

[0101] Furthermore, according to the optimal solution formula of the least square method x=(F T F) -1 F T y, calculate the optimal solution vector The parameter expressions of parameters x1 and x2 are obtained as follows:

[0102]

[0103] in,

[0104] Among them, M and N are coefficients determined based on the number of samples K of the envelope line in the aftershock phase, P and Q are coefficients determined based on the number of samples K of the envelope line in the aftershock phase, and f d is the damping motion frequency, For t=t i The back electromotive force value sampled at the moment.

[0105] Finally, by calculating Obtain the damping ratio ζ of the motor in the aftershock stage.

[0106] At the same time, since the back electromotive force envelope in the aftershock stage obeys exponential decay, the starting point of decay is the maximum value of the back electromotive force envelope BLv max , and then by calculating The maximum value of the back electromotive force envelope BLv of the motor in the residual vibration stage can be obtained Max .

[0107] Where BL is the magnetic induction coefficient, v Max is the maximum speed of the motor oscillator in the driving phase, the base of the natural logarithm of e.

[0108] Step 605: The computing device calculates the magnetic induction coefficient of the motor according to the damping ratio and the maximum value of the back electromotive force envelope.

[0109] Step 606: The computing device adjusts the excitation signal and the braking signal of the motor using the magnetic induction coefficient of the motor and the damping ratio of the motor in the residual vibration stage.

[0110] Optionally, during the driving phase of the motor, the motor oscillator motion speed and voltage transfer function is:

[0111]

[0112] Let s = jω, and the parameter expression of the maximum speed of the motor oscillator is obtained from the speed frequency response formula:

[0113]

[0114] Where BL is the magnetic induction coefficient, m is the mass of the motor vibrator, U is the amplitude of the sine wave input at both ends of the linear motor, and R e is the DC resistance in the coil path, ω n is the angular frequency of the motor's free oscillation, and ζ is the damping ratio.

[0115] Furthermore, in combination with the parameter expression of the maximum value of the back electromotive force envelope in step 604, It can be deduced that:

[0116]

[0117] After sorting out the above formula, we can get the parameter expression of the magnetic induction intensity coefficient:

[0118]

[0119] Among them, by calculating Get the angular frequency ω of the motor's free oscillation n ;

[0120] Among them, BLv Max is the maximum value of the back electromotive force envelope of the motor in the residual vibration stage, m is the mass of the motor vibrator, U is the amplitude of the sine wave input at both ends of the linear motor, R e is the DC resistance in the coil path, ω d is the damping angular frequency, and ζ is the damping ratio.

[0121] In this way, the present application can directly perform data acquisition on the motor signal calibration equipment. There are no special requirements for the basic conditions of the external organization, and no additional physical configuration is required. While obtaining the key parameters of the motor, the testing cost is reduced.

[0122] At the same time, this application can timely adjust and match the current motor's excitation signal and brake signal based on the motor's magnetic induction intensity coefficient and damping ratio parameters obtained each time, so as to obtain a consistent tactile experience. Figure 9 As shown, after matching the appropriate excitation signal (using a smaller excitation signal voltage), the motor 2 can obtain a tactile feedback vibration intensity that is relatively consistent with that of the motor 1 under the normal magnetic induction intensity coefficient.

[0123] Combine Figure 10As shown, an embodiment of the present disclosure provides a computing device, including a processor (processor) 100 and a memory (memory) 101. Optionally, the computing device may further include a communication interface (CommunicationInterface) 102 and a bus 103. The processor 100, the communication interface 102, and the memory 101 may communicate with each other through the bus 103. The communication interface 102 may be used for information transmission. The processor 100 may call the logic instructions in the memory 101 to execute the system optimization method based on motor parameter estimation of the above embodiment.

[0124] In addition, the logic instructions in the memory 101 can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product.

[0125] Memory 101, as a computer-readable storage medium, can be used to store software programs and computer-executable programs, such as the program instructions / modules corresponding to the methods in the embodiments of the present disclosure. Processor 100 executes the program instructions / modules stored in memory 101 to perform functional applications and data processing, thereby implementing the system optimization method based on motor parameter estimation in the above-mentioned embodiments.

[0126] The memory 101 may include a program storage area and a data storage area. The program storage area may store an operating system and at least one application required for a function; the data storage area may store data generated based on the use of the terminal device. Furthermore, the memory 101 may include high-speed random access memory and non-volatile memory.

[0127] An embodiment of the present disclosure provides a computer-readable storage medium storing computer-executable instructions, wherein the computer-executable instructions are configured to execute the above-mentioned system optimization method based on motor parameter estimation.

[0128] The aforementioned computer-readable storage medium may be a transient computer-readable storage medium or a non-transitory computer-readable storage medium.

[0129] The technical solution of the embodiments of the present disclosure may be embodied in the form of a software product, which is stored in a storage medium and includes one or more instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method of the embodiments of the present disclosure. The aforementioned storage medium may be a non-transitory storage medium, including: a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and other media that can store program code, or a transient storage medium.

[0130] The above description and the accompanying drawings fully illustrate the embodiments of the present disclosure to enable those skilled in the art to practice them. Other embodiments may include structural, logical, electrical, process and other changes. The embodiments represent only possible variations. Unless explicitly required, individual components and functions are optional, and the order of operations may vary. Parts and features of some embodiments may be included in or replace parts and features of other embodiments. Moreover, the words used in this application are only used to describe the embodiments and are not used to limit the claims. As used in the description of the embodiments and claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to also include plural forms. Similarly, the term "and / or" as used in this application refers to any and all possible combinations of one or more associated listings. In addition, when used in this application, the term "comprise" and its variations "comprises" and / or comprising refer to the presence of stated features, wholes, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or groups of these. In the absence of further restrictions, an element defined by the sentence "comprising a..." does not exclude the presence of other identical elements in the process, method or device that includes the element. In this article, each embodiment may focus on the differences from other embodiments, and the same and similar parts between the various embodiments can be referenced to each other. For the methods, products, etc. disclosed in the embodiments, if they correspond to the method part disclosed in the embodiments, then the relevant parts can be found in the description of the method part.

[0131] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software may depend on the specific application and design constraints of the technical solution. The technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the embodiments of the present disclosure. The technicians will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0132] In the embodiments disclosed herein, the disclosed methods and products (including but not limited to devices, equipment, etc.) can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units can be merely a logical functional division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between each other shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, and can be electrical, mechanical or other forms. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the units may be selected to implement this embodiment according to actual needs. In addition, the functional units in the embodiments of the present disclosure may be integrated into a processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0133] The flowcharts and block diagrams in the accompanying drawings show the possible implementation architectures, functions and operations of the systems, methods and computer program products according to the embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, program segment or part of the code, and the module, program segment or part of the code contains one or more executable instructions for implementing the specified logical functions. In some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, or they can sometimes be executed in the opposite order, which can depend on the functions involved. In the descriptions corresponding to the flowcharts and block diagrams in the accompanying drawings, the operations or steps corresponding to different boxes can also occur in an order different from that disclosed in the description, and sometimes there is no specific order between different operations or steps. For example, two consecutive operations or steps can actually be executed substantially in parallel, or they can sometimes be executed in the opposite order, which can depend on the functions involved. Each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented by a dedicated hardware-based system that performs the specified function or action, or may be implemented by a combination of dedicated hardware and computer instructions.

Claims

1. A system optimization method based on motor parameter estimation, characterized in that: Applied to motor tactile feedback systems, including: Calculate the damping motion frequency of the motor according to the detected back electromotive force of the motor in the residual vibration stage; Calculating the damping ratio of the motor in the residual vibration stage according to the attenuation curve of the back electromotive force and the damping motion frequency; Calculating the magnetic induction coefficient of the motor according to the damping ratio and the maximum value of the back electromotive force envelope; The motor's excitation signal and braking signal are adjusted using the motor's magnetic induction coefficient and the motor's damping ratio in the residual vibration stage.

2. The system optimization method according to claim 1, characterized in that: The method of calculating the damping motion frequency of the motor according to the detected back electromotive force of the motor in the residual vibration stage includes: After the current excitation signal is played, the back electromotive force signal of the motor is detected and the corresponding zero-crossing point information is generated; The damping motion frequency of the motor is calculated according to the zero-crossing point index and the zero-crossing point moment of the back electromotive force in the zero-crossing point information.

3. The system optimization method according to claim 2, characterized in that: Calculating the damping motion frequency of the motor damper according to the zero-crossing index and the zero-crossing moment of the back electromotive force in the zero-crossing information includes: calculate , obtain the damping motion frequency f of the motor d ; in, is the zero-crossing moment of the nth reverse electromotive force, is the zero-crossing moment of the mth back electromotive force, m and n are positive integers greater than or equal to 1 and not equal, and Fs is the sampling frequency.

4. The system optimization method according to claim 1, characterized in that: Calculating the damping ratio of the motor in the residual vibration stage according to the attenuation curve of the back electromotive force and the damping motion frequency includes: Perform envelope fitting on the attenuation curve of the back electromotive force to obtain the envelope of the back electromotive force; Based on the envelope of the back electromotive force, calculate the damping ratio of the motor in the residual vibration stage.

5. The system optimization method according to claim 4, characterized in that: Calculating the damping ratio of the motor in the residual vibration stage according to the envelope of the back electromotive force includes: calculate , obtain the damping ratio of the motor in the aftershock stage ; in, ; in, ; in, is the damping ratio, is the damping motion frequency, d is the damping angular frequency, P and Q are coefficients determined based on the number K of samples of the envelope in the aftershock phase. For t i According to the back electromotive force envelope at the moment The sampled back electromotive force value is is the angular frequency of the motor's free oscillation, is the maximum value of the back electromotive force envelope of the motor in the residual vibration stage.

6. The system optimization method according to claim 1, characterized in that: Calculating the magnetic induction coefficient of the motor according to the damping ratio and the maximum value of the back electromotive force envelope includes: calculate , get the angular frequency of the motor's free oscillation ; calculate , obtain the magnetic induction coefficient BL of the motor; in, ; Among them, e is the base of the natural logarithm, M and N are coefficients determined based on the number of samples K of the envelope in the aftershock phase. For t i According to the back electromotive force envelope at the moment The sampled back electromotive force value is is the maximum value of the back electromotive force envelope of the motor in the residual vibration stage, m is the mass of the motor vibrator, U is the amplitude of the sine wave input at both ends of the linear motor, is the DC resistance in the coil path, d is the damping angular frequency, is the damping ratio, is the damping motion frequency.

7. The system optimization method according to claim 6, characterized in that: Also includes: Calculate BLv Max = , obtain the maximum value BLv of the back electromotive force envelope of the motor in the residual vibration stage Max .

8. A computing device comprising a processor and a memory storing program instructions, characterized in that: The processor is configured to execute the system optimization method based on motor parameter estimation according to any one of claims 1 to 7 when running the program instructions.

9. A motor tactile feedback system, characterized in that: It includes a computing device as described in claim 8 and a motor signal calibration device, wherein the motor signal calibration device is used to adjust the excitation signal and braking signal of the motor by using the magnetic induction intensity coefficient of the motor and the damping ratio of the motor in the aftershock stage to adjust the tactile feedback of the motor in real time.

10. A storage medium storing program instructions, characterized in that: When the program instructions are executed, the system optimization method based on motor parameter estimation according to any one of claims 1 to 7 is executed.

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