Motor dead zone error voltage identification method and system based on linear regression, and medium

Abstract

The invention relates to the technical field of motors, in particular to a motor dead-zone error voltage identification method and system based on linear regression and a medium, and the method comprises the steps: building a voltage equation of d-axis voltage, and building a resistance model when a motor is static based on the voltage equation; establishing a dead-zone error voltage identification model based on linear regression, and establishing a steady-state voltage equation based on the dead-zone error voltage identification model and the resistance model; converting the steady-state voltage equation into a linear equation, performing recursion processing on the linear equation to obtain equivalent dead-zone error voltage, and determining equivalent dead-zone time based on the dead-zone error voltage; establishing a two-stage d-axis voltage injection dead time identifier, and identifying actual dead time of the motor under different working conditions; determining a difference value between the actual dead-zone time and the equivalent dead-zone time of the motor, and adjusting PWM output by the motor according to the difference value so as to enable the actual output voltage to be consistent with an expected value; the control precision of the motor can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of production control, and specifically relates to a method, system and medium for identifying the dead zone error voltage of a motor based on linear regression. Background Art

[0002] In the field of motor control technology, the dynamic performance and precise control of motors have always been a key research object. Among them, the dead zone effect is a common problem, which limits the accuracy and performance of motor control. The dead zone is caused by the switching characteristics of the motor driver and affects the dynamic performance and stability of the motor. In order to overcome the dead zone effect, it is necessary to compensate for the disturbance error voltage caused by the dead zone. Traditional dead zone compensation methods often rely on fixed parameters and do not take into account the changes under actual working conditions, so the compensation effect is not ideal, and it is necessary to more accurately identify the dead zone error voltage. Summary of the Invention

[0003] The purpose of the present invention is to provide a method, system and medium for identifying the dead zone error voltage of a motor based on linear regression to more accurately identify the dead zone error voltage.

[0004] To achieve the above purpose, the present invention provides the following technical solutions:

[0005] In the first aspect, an embodiment of the present invention provides a method for identifying the dead zone error voltage of a motor based on linear regression, the method comprising the following steps:

[0006] S100, establish a voltage equation for the d-axis voltage, and establish a resistance model when the motor is stationary based on the voltage equation;

[0007] S200, establish a dead zone error voltage identification model based on linear regression, and establish a steady-state voltage equation based on the dead zone error voltage identification model and the resistance model;

[0008] S300, convert the steady-state voltage equation into a linear equation, perform a recursive process on the linear equation to obtain an equivalent dead zone error voltage, and determine an equivalent dead zone time based on the dead zone error voltage;

[0009] S400, establish a two-stage d-axis voltage injection dead zone time identifier to identify the actual dead zone time of the motor under different working conditions;

[0010] S500, determine the difference between the actual dead zone time and the equivalent dead zone time of the motor, and adjust the PWM output by the motor according to the difference so that the actual output voltage is consistent with the expected value.

[0011] Optionally, in S100, the establishment of the voltage equation for the d-axis voltage and the establishment of the resistance model when the motor is stationary based on the voltage equation include:

[0012] For the d-axis, establish the voltage equation of the d-axis voltage u d :

[0013] u d = R s i d + L d pi d - ω e L q i q ;

[0014] Among them, R s is the stator resistance, L d is the d-axis inductance, p is the differential symbol, ω e is the rotational speed, u d , i d are the d-axis voltage and the d-axis current respectively;

[0015] Under the condition of the motor in a static steady state, the voltage equation is simplified to: u d = R s i d .

[0016] Optionally, in S200, establishing the dead zone error voltage identification model based on linear regression, and establishing the steady-state voltage equation based on the dead zone error voltage identification model and the resistance model, includes:

[0017] In the dq coordinate system, establish the dead zone error voltage identification model, and the expression is:

[0018]

[0019] k = 1, 2, 3...

[0020] Among them, γ represents the angle between the real-time current vector and the dq coordinate system, V dead is the single-phase average dead zone error voltage in the three-phase static coordinate system, ω r is the angular velocity of the rotor, n is the polarity of the three-phase current, and t is the dead zone time;

[0021]

[0022] In the formula, T dead , T on , T off , T pwm and V dc are the dead zone time, on-time, off-time, switching period, and DC bus voltage respectively; V set and V diode represent the switch saturation voltage and the diode forward voltage;

[0023] When the motor is in a stationary operating condition, ω r = 0, the expression of the dead - zone error voltage identification model is simplified to:

[0024] where, ΔV q is the average dead - zone error voltage of the q - axis;

[0025] Combined with the dead - zone effect, the resistance model of the d - axis voltage u d is converted into the following steady - state voltage equation:

[0026]

[0027] where, Sign() is the sign function, and the expression is:

[0028]

[0029] where, i a represents the a - phase current.

[0030] Optionally, in S300, the process of converting the steady - state voltage equation into a linear equation and performing a recursive process on the linear equation to obtain the equivalent dead - zone error voltage includes:

[0031] Converting the steady - state voltage equation of the d - axis voltage model u d into a linear equation:

[0032] y = ax + b;

[0033] where, y = ud, x = id, a = Rs,

[0034] According to the optimal linear regression, the optimal prediction of a and b can be determined by the following equation:

[0035]

[0036] where, x i is at the i - th moment, y i is u at the i - th moment d sampling, n is the total number of samplings;

[0037] Performing a recursive process on the linear equation to obtain:

[0038]

[0039] where, IU∑ k is the total power at k sampling moments, U∑ k is the total voltage at k sampling moments, I∑ kThe total current at k sampling instants, N is N sampling instants, and id k-1 is the current at the (k - 1)-th sampling instant, and ud k-1 is the voltage at the (k - 1)-th instant. The equivalent dead-time error T dead is calculated according to a linear equation;

[0040] Simplify the single-phase average dead-time error voltage to obtain:

[0041]

[0042] Then the calculation formula for the final equivalent dead-time error is:

[0043]

[0044] Optionally, in S500, determining the difference between the actual dead-time of the motor and the equivalent dead-time, and adjusting the PWM output by the motor according to the difference to make the actual output voltage consistent with the expected value includes:

[0045] For the average dead-time error time, taking phase a as an example, the influence on the output duty cycle of the diode is:

[0046]

[0047] Consider introducing the set dead-time T set , and its insertion mechanism is:

[0048]

[0049] where T a represents the actual output duty cycle, represents the ideal output duty cycle;

[0050] Let be the identified equivalent dead-time, and T dead be the true equivalent dead-time;

[0051] By inserting the set dead-time T set to change the value of the identified equivalent dead-time so that the actual output voltage is consistent with the expected value.

[0052] In a second aspect, an embodiment of the present invention provides a motor dead-time error voltage identification system based on linear regression. The system includes:

[0053] At least one processor;

[0054] At least one memory for storing at least one program;

[0055] When the at least one program is executed by the at least one processor, the at least one processor implements the method for identifying the dead-time error voltage of the motor based on linear regression as described in any one of the above.

[0056] In a third aspect, an embodiment of the present invention provides a computer-readable storage medium, in which a program executable by a processor is stored. The program executable by the processor is used to execute the method for identifying the dead-time error voltage of the motor based on linear regression as described in any one of the above when executed by the processor.

[0057] The beneficial effects of the present invention are as follows: The present invention discloses a method, system and medium for identifying the dead-time error voltage of a motor based on linear regression. The present invention uses linear regression technology to optimize the model of the d-axis voltage equation and provides a novel method for identifying the dead-time error voltage. In view of the possible high-order harmonic interference in the actual working conditions, the present invention designs a specific recursive processing strategy to ensure the accuracy and real-time performance of the model. The present invention designs a two-stage d-axis voltage u d injection dead-time identifier, which fully considers the influence of PWM modulation resolution and actual working conditions and improves the identification accuracy of the true dead-time. By injecting an equivalent dead-time, the present invention enables the motor to obtain a more accurate compensation effect under various working conditions. Considering the actual influence of the microcontroller main frequency, the present invention establishes a specific mapping relationship between the d-axis voltage u d and the PWM comparison register, further improving the control accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0059] Figure 1 is a schematic flowchart of the method for identifying the dead-time error voltage of the motor based on linear regression in an embodiment of the present invention;

[0060] Figure 2 is the main circuit diagram of a three-phase PMSM inverter in an embodiment of the present invention;

[0061] Figure 3 is the equivalent dead-time identification block diagram for injecting the d-axis voltage in an embodiment of the present invention;

[0062] Figure 4 is the structure diagram of the system for identifying the dead-time error voltage of the motor based on linear regression in an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0063] The concept, specific structure, and technical effects of the present invention will be clearly and completely described below in conjunction with embodiments and the accompanying drawings to fully understand the purpose, solution, and effects of the present invention. It should be noted that, without conflict, the embodiments in the present invention and the features in the embodiments can be combined with each other.

[0064] Currently, most dead zone compensation strategies are based on fixed parameters for compensation and do not consider the dynamic changes of parameters in actual working conditions. Existing technologies often cannot accurately identify the dead zone error voltage, resulting in unsatisfactory compensation effects. In actual working conditions, the motor may be affected by high-order harmonics and other non-linear factors, which interfere with the identification of the dead zone error voltage.

[0065] Based on this, in order to solve the technical problems in the background art and considering the limitation of the main frequency of the microcontroller, the present invention designs a mapping strategy between u d and the PWM comparison register. Under this strategy, the set value of u d will be adjusted according to the value of the PWM comparison register, thereby ensuring the accuracy of the output voltage. First, calculate the value of the PWM comparison register according to the desired value of u d , and then write the value of the PWM comparison register into the microcontroller, thereby realizing the precise control of the value of u d . This strategy ensures the accuracy of the output voltage and improves the response speed of the system.

[0066] Refer to Figure 1 , Figure 1 which is a method for identifying the dead zone error voltage of a motor based on linear regression provided by the present invention. The method includes the following steps:

[0067] S100, establish a voltage equation for the d-axis voltage, and establish a resistance model when the motor is stationary based on the voltage equation;

[0068] S200, establish a dead zone error voltage identification model based on linear regression, and establish a steady-state voltage equation based on the dead zone error voltage identification model and the resistance model;

[0069] S300, convert the steady-state voltage equation into a linear equation, perform a recursive process on the linear equation to obtain an equivalent dead zone error voltage, and determine an equivalent dead zone time based on the dead zone error voltage;

[0070] S400, establish a two-stage d-axis voltage injection dead zone time identifier to identify the actual dead zone time of the motor under different working conditions;

[0071] S500, determine the difference between the actual dead zone time and the equivalent dead zone time of the motor, and adjust the PWM output by the motor according to the difference to make the actual output voltage consistent with the expected value.

[0072] Specifically, a two-stage u based on linear regression d Dead-time identification method for voltage injection. Based on the analysis of the dead-time disturbance voltage of the inverter, the response expression of the d-axis current i d when injecting the d-axis voltage u d under the static state considering the dead-time effect is further analyzed. According to the response curve of this response expression, a dead-time identification method based on linear regression is proposed. Before the formal identification, this method will pre-identify and estimate the stator resistance R s and the d-axis inductance L d , so as to determine the time interval of the injected voltage at subsequent points, ensuring that the identification process is not interfered by the transient current error.

[0073] During the implementation process, first establish a dead-time error voltage identification model based on linear regression. Considering the voltage-current relationship of the d-axis, a linear model can be derived. When the motor is stationary, ignoring the differential term, a simple resistance model can be obtained, providing a basis for subsequent linear regression analysis. The linear regression method is used to find the relationship between the dead-time error voltage and the motor current. By collecting a large number of data points and performing linear fitting, the relationship model between the dead-time and the current can be obtained. This model can be used as the basis for subsequent compensation strategies.

[0074] In actual PWM debugging, the main frequency of the microcontroller often causes limitations in PWM resolution. Therefore, the present invention designs a two-stage d-axis voltage u d injection dead-time identifier. In the first stage, the d-axis voltage u d gradually increases until it reaches a stable value; in the second stage, the u d voltage gradually decreases. This can ensure accurate dead-time data are obtained under different working conditions. To ensure better consistency of the data in the two stages, the present invention designs the waiting times t wait1 and t wait2 . This ensures that the current can reach a stable state after each change in the u d voltage, thereby improving the identification accuracy.

[0075] To further optimize the dead-time compensation effect, the present invention injects an equivalent dead-time according to the identification result. In this way, regardless of how the external conditions change, the actual dead-time of the motor will be maintained within a relatively stable range, thereby ensuring the control accuracy of the system. First, identify the actual dead-time of the motor, then compare it with the set equivalent dead-time, and adjust the output of the PWM according to the difference, so as to ensure that the actual output voltage is consistent with the expected value.

[0076] The present invention optimizes the model of the d-axis voltage equation by using linear regression technology and provides a novel method for identifying the dead-time error voltage. In view of the possible high-order harmonic interference in the actual working conditions, the present invention designs a specific recursive processing strategy to ensure the accuracy and real-time performance of the model. The present invention designs a two-stage d-axis voltage u d time identifier for injecting dead time, which fully considers the influence of PWM modulation resolution and actual working conditions and improves the identification accuracy of the true dead time. By injecting an equivalent dead time, the present invention enables the motor to obtain a more accurate compensation effect under various working conditions. Considering the actual influence of the microcontroller main frequency, the present invention establishes a specific mapping relationship between the d-axis voltage u d and the PWM comparison register, further improving the control accuracy.

[0077] As can be seen from the attached Figure 2 figures, the permanent magnet synchronous motor and the inverter constitute the main circuit of the system. Due to the delay in the on and off of the inverter, during the process of the inverter controlling the output voltage, it is necessary to insert dead time for the switching tubes of the same bridge arm to prevent the switching tubes from conducting simultaneously. Although the dead time is very short, a series of distorted pulses generated by the dead-time effect make the magnitude of the output voltage not controlled by the switch, and the polarity is determined by the instantaneous direction of the output current. At the same time, the on-state voltage drop and saturation voltage drop of the inverter will also have a certain impact on the output voltage. Therefore, the output voltage error generated by the inverter will surely affect the stability of the permanent magnet synchronous motor speed regulation system. It is very difficult to accurately measure the error voltage caused by the dead-time effect online quantitatively.

[0078] In some embodiments, in S100, establishing the voltage equation of the d-axis voltage and establishing a resistance model of the motor at rest based on the voltage equation includes:

[0079] For the d-axis, establish the voltage equation of the d-axis voltage u d :

[0080] u d =R s i d +L d pi d -ω e L q i q ;

[0081] Among them, R s is the stator resistance, L d is the d-axis inductance, p is the differential symbol, ω e is the rotational speed, u d , i d are the d-axis voltage and d-axis current respectively.

[0082] Under the static steady-state condition of the motor, since the rotational speed of the motor is 0, the derivative term of i d is also zero, and the voltage equation is simplified to: u d =R s i d .

[0083] That is, when voltage injection is performed on the d-axis, ignoring the transient process during voltage injection and entering the steady state, the d-axis voltage equation under ideal conditions can be regarded as a simple resistance model at this time.

[0084] In some embodiments, in S200, establishing a dead zone error voltage identification model based on linear regression, and establishing a steady-state voltage equation based on the dead zone error voltage identification model and the resistance model, includes:[[]]

[0085] Establishing a dead zone error voltage identification model in the dq coordinate system, and the expression is:[[]]

[0086]

[0087] k = 1, 2, 3...

[0088] Where γ represents the angle between the real-time current vector and the dq coordinate system. V dead is the single-phase average dead zone error voltage in the three-phase stationary coordinate system, ω r is the angular velocity of the rotor, n is the polarity of the three-phase current, and t is the dead zone time;

[0089]

[0090] In the formula, T dead , T on , T off , T pwm and V dc are the dead zone time, on-time, off-time, switching period, and DC bus voltage respectively; V set and V diode represent the switch saturation voltage and the diode forward voltage;

[0091] When the motor is in the stationary operating condition, ω r = 0, and the high-order harmonics related to ω r can all be omitted, and the expression of the dead zone error voltage identification model is simplified to:

[0092] Where ΔV q is the average dead zone error voltage of the q-axis;

[0093] Combining the dead zone effect, converting the resistance model of the d-axis voltage u d into the following steady-state voltage equation:

[0094]

[0095] Among them, Sign() is the sign function, and the expression is:

[0096] Among them, i a represents the current of phase a.

[0097] In the subsequent u d input, the direction of u d will remain unidirectional throughout a single test. Therefore, the sign of sign(i d ) will remain consistent and can be regarded as a constant.

[0098] In some embodiments, in S300, the conversion of the steady-state voltage equation into a linear equation and the recursive processing of the linear equation to obtain an equivalent dead-time error voltage include:

[0099] Converting the steady-state voltage equation of the d-axis voltage model u d into a linear equation:

[0100] y = ax + b;

[0101] Among them, y = ud, x = id, a = Rs,

[0102] According to the optimal linear regression, the optimal predictions of a and b can be determined by the following equation:

[0103]

[0104] Among them, x i is at the i-th moment, y i is the sampling of u d at the i-th moment, and n is the total number of samplings;

[0105] In practical applications, since the storage and computing capabilities of the microcontroller are limited, a recursive processing strategy is introduced. When each new data point is added, there is no need to recalculate from the beginning, but instead, it can be recursively calculated through the existing data, thus saving computing time and resources. This strategy makes the present invention more real-time and responsive in practical applications, and the specific processing is as follows.

[0106] Considering that the batch processing form may pose challenges to the storage and computing power of the microcontroller, the following recursive processing is performed on the linear equation.

[0107] Performing recursive processing on the linear equation to obtain:

[0108]

[0109] Among them, IU∑ k is the total power at k sampling moments, U∑ k is the total voltage at k sampling moments, I∑ k is the total current at k sampling moments, N is N sampling moments, id k-1 is the current at the (k - 1)-th sampling moment, ud k-1 is the voltage at the (k - 1)-th moment, and the equivalent dead-time error time T dead is calculated according to a linear equation;

[0110] a and b can be calculated when finally returning to D2(i2, u2), and the equivalent dead-time error time T is obtained according to a linear equation dead ;

[0111] Since the present invention mainly considers the error voltage caused by the dead time, and this factor also has the greatest influence on the average error voltage, the single-phase average dead-time error voltage is simplified to obtain:

[0112]

[0113] Then the calculation formula for the final equivalent dead-time error is:

[0114]

[0115] In some embodiments, in S500, the step of determining the difference between the actual dead time and the equivalent dead time of the motor, and adjusting the PWM output by the motor according to the difference to make the actual output voltage consistent with the expected value includes:

[0116] For the average dead-time error time, taking phase a as an example, the influence on the output duty cycle of the diode is:

[0117]

[0118] Considering introducing a set dead time T set , and its insertion mechanism is:

[0119]

[0120] Among them, T a represents the actual output duty cycle, represents the ideal output duty cycle;

[0121] As shown in the appendix Figure 3 Let be the identified equivalent dead time, and T dead be the true equivalent dead time, that is, the value of the identified equivalent dead time can be changed by inserting the set dead time T set .

[0122] Compared with the prior art, the present invention has the following advantages:

[0123] 1) Through the linear regression technique, the present invention can achieve high-precision identification of the dead zone error voltage.

[0124] 2) The model of the present invention adopts a recursive process, which can adapt to various working conditions and parameter changes, and enhances the dynamic adaptability of the compensation strategy.

[0125] 3) By accurately identifying the dead zone error voltage, the present invention greatly improves the stability of motor control.

[0126] 4) The present invention can simplify the motor control strategy, reduce the computational burden on the microcontroller, and improve the control response speed.

[0127] Compared with Figure 1 the corresponding method, referring to Figure 4 , an embodiment of the present invention provides a system for identifying the dead zone error voltage of a motor based on linear regression, including:

[0128] At least one processor;

[0129] At least one memory for storing at least one program;

[0130] When the at least one program is executed by the at least one processor, the at least one processor implements the above method.

[0131] It can be seen that the content in the above method embodiments is applicable to the system embodiments of the present invention. The functions specifically implemented by the system embodiments of the present invention are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those of the above method embodiments.

[0132] In addition, an embodiment of the present invention also discloses a computer program product or a computer program. The computer program product or the computer program is stored in a computer-readable storage medium. The processor of the computer device can read the computer program from the computer-readable storage medium, and the processor executes the computer program, so that the computer device executes the above method. Similarly, the content in the above method embodiments is applicable to the storage medium embodiments of the present invention. The functions specifically implemented by the storage medium embodiments of the present invention are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those of the above method embodiments.

[0133] Those of ordinary skill in the art will appreciate that all or some of the methods and systems disclosed above can be implemented as software, firmware, hardware, and appropriate combinations thereof. Some or all of the physical components can be implemented as software executed by a processor, such as a central processing unit, a digital signal processor, or a microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software can be distributed on a computer-readable medium, which can include a computer storage medium (or non-transitory medium) and a communication medium (or transitory medium). As is well known to those of ordinary skill in the art, the term computer storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information, such as computer-readable instructions, data structures, program modules, or other data. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVDs) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and that can be accessed by a computer. In addition, it is well known to those of ordinary skill in the art that communication media typically embodies computer-readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and can include any information delivery media.

[0134] The above is a specific description of the preferred embodiments of the present disclosure, but the present disclosure is not limited to the above embodiments. Those skilled in the art can also make various equivalent deformations or substitutions without departing from the spirit of the present disclosure, and these equivalent deformations or substitutions are all included within the scope defined by the claims of the present disclosure.

Claims

1. A method for identifying the dead - zone error voltage of a motor based on linear regression, characterized in that, The method includes the following steps: S100. Establish a voltage equation for the d-axis voltage, and establish a resistance model when the motor is stationary based on the voltage equation; S200. Establish a dead-time error voltage identification model based on linear regression, and establish a steady-state voltage equation based on the dead-time error voltage identification model and the resistance model; S300. Convert the steady-state voltage equation into a linear equation, perform a recursive process on the linear equation to obtain an equivalent dead-time error voltage, and determine an equivalent dead time based on the dead-time error voltage; S400. Establish a two-stage d-axis voltage injection dead-time identifier to identify the actual dead time of the motor under different operating conditions; S500. Determine the difference between the actual dead time and the equivalent dead time of the motor, and adjust the PWM output by the motor according to the difference so that the actual output voltage is consistent with the expected value.

2. The method for identifying the dead zone error voltage of a motor based on linear regression according to claim 1, wherein In S100, the establishment of the voltage equation for the d-axis voltage and the establishment of the resistance model when the motor is stationary based on the voltage equation include: For the d-axis, establish the voltage equation of the d-axis voltage u d : u d = R s i d + L d pi d - ω e L q i q ; Among them, R s is the stator resistance, L d is the d-axis inductance, p is the differential symbol, ω e is the rotational speed, u d and i d are the d-axis voltage and the d-axis current respectively; Under the static steady-state condition of the motor, the voltage equation is simplified to: u d = R s i d .

3. A method for identifying the dead - zone error voltage of a motor based on linear regression according to claim 1, characterized in that, In S200, the establishment of the dead-time error voltage identification model based on linear regression and the establishment of the steady-state voltage equation based on the dead-time error voltage identification model and the resistance model include: In the dq coordinate system, establish a dead-time error voltage identification model, and the expression is: k＝1,2,3... where γ represents the angle between the real-time current vector and the dq coordinate system, V dead is the single-phase average dead-time error voltage in the three-phase stationary coordinate system, ω r is the angular velocity of the rotor, n is the polarity of the three-phase current, and t is the dead-time; Wherein, T dead , T on , T off , T pwm , and V dc are the dead time, on-time, off-time, switching period, and DC bus voltage, respectively; V set and V diode represent the switch saturation voltage and the diode forward voltage; When the motor is in a stationary operating condition, ω r = 0, the expression of the dead zone error voltage identification model is simplified to: Among them, ΔV q is the average dead-time error voltage of the q-axis; Combined with the dead - zone effect, the resistance model of the d - axis voltage u d is converted into the following steady - state voltage equation: Among them, Sign() is the sign function, and the expression is: Among them, i a represents the current of phase a.

4. A method for identifying the dead zone error voltage of a motor based on linear regression according to claim 3, characterized in that, In S300, the conversion of the steady-state voltage equation into a linear equation and the recursive process on the linear equation to obtain an equivalent dead-time error voltage include: Convert the steady-state voltage equation of the d-axis voltage model u d into a linear equation: y = ax + b; where y = ud, x = id, a = Rs, According to the optimal linear regression, the optimal prediction of a and b can be determined by the following equation: Among them, x i is at time i, y i is u at time i d sampling, and n is the total number of samplings; Perform a recursive process on the linear equation to obtain: Among them, IU∑ k is the total power at k sampling moments, U∑ k is the total voltage at k sampling moments, I∑ k is the total current at k sampling moments, N is N sampling moments, id k-1 is the current at the (k - 1)-th sampling moment, ud k-1 is the voltage at the (k - 1)-th moment, and the equivalent dead-time error T dead is calculated according to the linear equation; Simplify the single-phase average dead-time error voltage to obtain: Then the calculation formula for the final equivalent dead-time error is:

5. A method for identifying the dead - zone error voltage of a motor based on linear regression according to claim 1, characterized in that, In S500, the determination of the difference between the actual dead time and the equivalent dead time of the motor and the adjustment of the PWM output by the motor according to the difference so that the actual output voltage is consistent with the expected value include: For the average dead-time error time, taking phase a as an example, the influence on the output duty cycle of the diode is: Consider introducing a set dead time T set , and its insertion mechanism is as follows: Among them, T a represents the actual output duty cycle, and represents the ideal output duty cycle; Let be the identified equivalent dead time and T dead be the true equivalent dead time; By inserting a set dead time T set to change the value of the identified equivalent dead time so that the actual output voltage is consistent with the expected value.

6. A motor dead zone error voltage identification system based on linear regression, characterized in that, The system includes: At least one processor; At least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the method for identifying the dead-time error voltage of the motor based on linear regression according to any one of claims 1 to 5.

7. A computer-readable storage medium storing a program executable by a processor, characterized in that, The program executable by the processor is used to execute the method according to any one of claims 1 to 5 when executed by the processor.

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