Construction system and method based on speed signal fusion algorithm of combined seed and fertilizer drill and brushless direct current motor sensorless drive

Abstract

The invention discloses a construction system and method based on a speed signal fusion algorithm of a combined seed and fertilizer drill and sensorless driving of a brushless direct current motor, and the method comprises the steps: carrying out the fusion calculation of driving speeds v1 and v2 obtained by a Beidou satellite signal module and a radar signal module through an extended Kalman filter, and obtaining a driving speed signal v3 of a tractor; a corresponding rotating speed instruction value n * is obtained according to the sowing amount; the motor rotating speed instruction value serves as the input of the intelligent driving control module and is used for driving the brushless direct current motor and the brushless direct current fan to operate adaptively. According to the invention, the extended Kalman filter fusion algorithm is adopted, the Beidou satellite signal v1 and the radar signal v2 are fused, the problems of positioning deviation and low positioning precision of the Beidou satellite signal are effectively solved, and the problems of low precision of the radar signal and large measurement error in a complex weather environment are also effectively solved.

Description

Technical Field

[0001] The invention relates to a construction system and method based on a speed signal fusion algorithm of a fertilizer seeding machine and a sensorless drive of a brushless DC motor. Background Art

[0002] Multi-purpose fertilizer seeders are mainly used for spreading seeds and fertilizers. At present, the drive control system used for spreading (seed distribution, arrangement and spraying) in multi-purpose fertilizer seeders includes a motor and a fan. The motor is used to deliver seeds, and the fan is used to blow seeds. The motor is mostly a DC motor or a stepper motor, and the tractor speed is mainly detected by a radar sensor. DC motors and stepper motors have disadvantages such as poor control accuracy and high motor power at the same torque. The radar sensor used for speed detection has low accuracy and large measurement errors in complex weather environments, resulting in waste of seeds and fertilizers during the system's fertilization and sowing process.

[0003] Regarding the multi-purpose fertilizer seeding machine drive control system, the motor power is maximized by assembling a reducer, and a brushless DC motor is used to achieve high-precision speed control. The existing solution mainly uses photoelectric encoders and Hall current sensors to achieve dual closed-loop control of speed and current. In order to reduce system costs, low-precision Hall sensors, speed sensors, and current sensors are used while ensuring control performance, and high-precision drive control is achieved with high-performance control algorithms. At the same time, the speed detection signal can also use Beidou satellite signals, but the existing solution has disadvantages such as positioning deviation and low positioning accuracy. Summary of the invention

[0004] The present invention aims to solve the problems existing in the above-mentioned prior art and provides a construction system and method based on a speed signal fusion algorithm of a fertilizer seeder and a sensorless drive of a brushless DC motor.

[0005] The technical solutions adopted in the present invention are:

[0006] A construction system based on a speed signal fusion algorithm of a fertilizer planter and a sensorless drive of a brushless DC motor, comprising a drive control system, wherein the drive control system comprises a brushless DC motor and a brushless DC fan, and further comprising:

[0007] Beidou satellite signal module and radar signal module for obtaining the tractor's driving speed;

[0008] Extended Kalman filter, the extended Kalman filter converts the driving speed v obtained by the Beidou satellite signal module and the radar signal module 1 and v 2 Fusion calculation to obtain the tractor speed signal v 3 , and obtain the corresponding speed command value n* according to the sowing amount;

[0009] Intelligent drive control module, the motor speed command value is used as the input of the intelligent drive control module to drive the brushless DC motor and the brushless DC fan to operate adaptively.

[0010] Furthermore, the extended Kalman filter includes a state prediction module and a measurement update module, the state prediction module iteratively predicts the driving speed signal obtained by the Beidou satellite signal module and the radar signal module, and the measurement update module updates the driving speed signal obtained by the Beidou satellite signal module and the radar signal module.

[0011] Furthermore, the intelligent drive control module also includes a motor drive module and a fan drive module, and the brushless DC motor and the brushless DC fan are connected to the motor drive module and the fan drive module respectively.

[0012] Furthermore, the motor drive module and the fan drive module both include a first PI controller, a second PI controller, a third PI controller, a first coordinate transformation module, an SVPWM inverter, a feedback speed calculation unit and a current sensorless module. The first PI controller is connected to the third PI controller, the second PI controller, the third PI controller and the SVPWM inverter are all connected to the first coordinate transformation module, the current sensorless module, the brushless DC motor and the brushless DC fan are all connected to the SVPWM inverter, and the feedback speed n of the brushless DC motor and the brushless DC fan is obtained by the feedback speed calculation unit.

[0013] Furthermore, the motor feedback speed calculation unit includes a Hall sensor, a speedless speed sensor and a speed angle calculation module.

[0014] The present invention also discloses a construction method, comprising:

[0015] The tractor's driving speed is obtained through the Beidou satellite signal module and the radar signal module, respectively, and is recorded as v 1 and v 2 , by changing v 1 and v 2 Perform fusion calculation of state prediction and measurement update to obtain the driving speed v 3 ;

[0016] According to the sowing amount of different seeds and fertilizers, the corresponding speed command value n* is calculated;

[0017] The speed command value n* is used as the input of the motor drive module and the fan drive module. After being controlled by the motor and fan drive modules, the three-phase drive voltage u is obtained. A 、u B 、u C , used to drive the brushless DC motor and brushless DC fan to operate adaptively.

[0018] Furthermore, the state prediction function is:

[0019]

[0020] In the formula, is the predicted value of the state at time k, is the state prediction value at time k+1, and the two correspond to the driving speed signal v 3 ;

[0021] u(k) is the input value at time k, including v 1 and v 2 ; A' and B' are the state transfer coefficient matrix and gain matrix respectively; represents the posterior estimated covariance at time k; represents the prior estimated covariance at time k+1; F(k+1) represents the Jacobian matrix at time k+1; Q represents the system noise covariance matrix;

[0022] The measurement update function is:

[0023]

[0024] Where K(k+1) represents the gain matrix at time k+1; G(k+1) represents the Jacobian matrix at time k+1; represents the output matrix at time k+1; C' represents the state transfer coefficient matrix; y(k+1) represents the actual output variable at time k+1; I represents the unit gain matrix.

[0025] Furthermore, the feedback speed calculation unit obtains the feedback speed n of the brushless DC motor and the brushless DC fan, and the speed command value n* and the feedback speed n are adjusted by the first PI controller 43 to obtain the q-axis current control signal i q *, the speed error Δn is obtained after the difference, and the speed error Δn is used as the input of the first PI controller 43, and the d-axis current control signal i is specified at the same time. d * = 0;

[0026] i d * with i q * respectively with the d-axis current feedback signal i d and q-axis current feedback signal i q The current error signal Δi is obtained by subtracting d and Δi q , where i d and i q Calculated by the current sensorless module;

[0027] Current error signal Δi d and Δiq The d-axis and q-axis voltage instructions u are obtained through the second PI controller and the third PI controller respectively. d and u q ;

[0028] u d and u q After the first coordinate transformation module, we get u α and u β ,u α and u β As the input of the SVPWM inverter, the three-phase voltage u is obtained after modulation and amplification. A 、u B 、u C The three-phase voltage is used to drive the brushless DC motor and the brushless DC fan.

[0029] Furthermore, the process of the feedback speed calculation unit obtaining the feedback speed n is:

[0030] The Hall sensor detects three Hall signals and sends the signals to the speed angle calculation module and the speed sensor 49 for calculation to obtain the speed n and angle signal θ e , the calculation process is:

[0031]

[0032] In the formula, ω m Represents the mechanical angular velocity of the motor in the brushless DC motor and brushless DC fan, ω e It represents the electrical angular velocity of the motor in the brushless DC motor and brushless DC fan, P n Indicates the number of motor pole pairs in brushless DC motors and brushless DC fans;

[0033] θ e (k) = θ e (k-1)+ω e Δt(18)

[0034] In the formula, θ e (k-1) represents the motor angle of the brushless DC motor and brushless DC fan at time k-1, θ e (k) represents the motor angle at time k in the brushless DC motor and the brushless DC fan, and Δt represents the time interval;

[0035] After the feedback speed calculation unit calculates, the feedback speed n and angle signal θ are obtained. e , the signal is sent to the current sensorless module, and then the voltage u output by the SVPWM inverter module A 、u B 、u CSent to the current sensorless module to calculate the d-axis and q-axis current signals i d and i q ;

[0036] The d-axis and q-axis current signals i d and i q The calculation process is:

[0037] Three-phase voltage u A 、u B 、u C After coordinate transformation, the d and q axis voltages u are obtained d and u q :

[0038]

[0039] The corresponding d and q axis currents are calculated using the following formula:

[0040]

[0041] In the formula,

[0042] Furthermore, the obtained current feedback signal i d and i q The corresponding current i is converted into the stationary coordinate system α and i β , perform speed sensorless calculation to obtain the calibrated speed n 1 and the angle signal θ e1 , the calculation process is:

[0043]

[0044] Where, L s Represents the motor stator inductance in brushless DC motors and brushless DC fans; λ f Represents the permanent magnet flux; the rotor electrical angle θ is obtained by sampling the current and voltage signals in the stationary coordinate system e ;

[0045] Magnetic flux λ in the stationary coordinate system α and λ β The expression is expressed as:

[0046]

[0047] The stator flux is calculated by the following formula:

[0048]

[0049] In the formula, λ αβ =[λ α λβ ] T ;

[0050] Define a vector function η(λ αβ ), the function satisfies:

[0051]

[0052] The corresponding Euclidean norm in formula (10) is expressed as:

[0053]

[0054] definition is the estimated value of stator flux, is the cost function;

[0055] The gradient corresponding to the cost function is:

[0056]

[0057] The observer is constructed according to the gradient descent method:

[0058]

[0059] Where a is the gain coefficient;

[0060] From (10), we can conclude that:

[0061]

[0062] In the formula, is the angle error,

[0063] The present invention has the following beneficial effects:

[0064] The present invention adopts an extended Kalman filter fusion algorithm to fuse the Beidou satellite signal v1 and the radar signal v2, which not only effectively solves the problems of Beidou satellite signal positioning deviation and low positioning accuracy, but also effectively solves the problems of low radar signal accuracy and large measurement errors in complex weather environments.

[0065] The current loop feedback signal of the present invention adopts a current sensorless solution, takes a voltage signal, a rotation speed signal and an angle signal as inputs of a current sensorless module, and obtains accurate current feedback signals id and iq through iterative calculations.

[0066] The present invention uses a Hall sensor and a speed sensorless algorithm to calculate the motor speed, combines the low-precision Hall sensor with a speed sensorless algorithm that depends on model parameters, and improves the speed control effect of the entire controller.

[0067] The present invention uses a brushless DC motor and a high-performance drive control algorithm to solve the problems of low control accuracy and small output torque existing in DC motors and stepper motors. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] Figure 1 It is a system block diagram of the present invention.

[0069] Figure 2 for Figure 1 The block diagram of the extended Kalman filter.

[0070] Figure 3 This is the connection block diagram between the motor drive module and the brushless DC motor.

[0071] Figure 4 for Figure 3 Schematic diagram of the motor drive module (the schematic diagram of the fan drive module is the same as Figure 4 same).

[0072] Figure 5 This is the connection block diagram between the fan drive module and the brushless DC fan. DETAILED DESCRIPTION

[0073] The present invention will be further described below in conjunction with the accompanying drawings.

[0074] like Figures 1 to 5 , a construction system based on a speed signal fusion algorithm of a fertilizer seeder and a sensorless drive of a brushless DC motor, including a drive control system, a Beidou satellite signal module 1, a radar signal module 2, an extended Kalman filter 3 and an intelligent drive control module 4.

[0075] The driving control system includes a brushless DC motor and a brushless DC fan. The Beidou satellite signal module 1 and the radar signal module 2 are both used to obtain the driving speed of the tractor.

[0076] The extended Kalman filter 3 converts the driving speed v obtained by the Beidou satellite signal module 1 and the radar signal module 2 into 1 and v 2 Fusion calculation to obtain the tractor speed signal v 3 , and obtain the corresponding speed command value n* according to the sowing amount.

[0077] The motor speed command value is used as the input of the intelligent drive control module to drive the brushless DC motor and the brushless DC fan to operate adaptively.

[0078] The extended Kalman filter 3 includes a state prediction module 31 and a measurement update module 32. The state prediction module 31 iteratively predicts the driving speed signal obtained by the Beidou satellite signal module 1 and the radar signal module 2, and the measurement update module 32 updates the driving speed signal obtained by the Beidou satellite signal module 1 and the radar signal module 2.

[0079] The intelligent drive control module 4 includes a motor drive module 41 and a fan drive module 51 , and the brushless DC motor and the brushless DC fan are connected to the motor drive module 41 and the fan drive module 51 respectively.

[0080] The motor drive module 41 and the fan drive module 51 both include a first PI controller 43, a second PI controller 44, a third PI controller 45, a first coordinate transformation module 46, an SVPWM inverter 47, a feedback speed calculation unit and a current sensorless module 50. The first PI controller 43 is connected to the third PI controller 45, the second PI controller 44, the third PI controller 45 and the SVPWM inverter 47 are all connected to the first coordinate transformation module 46, the current sensorless module 50, the brushless DC motor and the brushless DC fan are all connected to the SVPWM inverter 47, and the feedback speed n of the brushless DC motor and the brushless DC fan is obtained by the feedback speed calculation unit.

[0081] The motor feedback speed calculation unit includes a Hall sensor 48, a speed sensor 49 and a speed angle calculation module.

[0082] The workflow of the present invention is further described below.

[0083] Output v in Beidou satellite signal module 1 and radar signal module 2 1 and v 2 Perform fusion calculation to obtain a more accurate tractor speed signal v 3 Among them, the state prediction process is:

[0084]

[0085] In the formula, is the predicted value of the state at time k, is the state prediction value at time k+1, and the two correspond to the driving speed signal v 3 ; u(k) is the input value at time k, including the output v in Beidou satellite signal module 1 and radar signal module 2 1 and v 2 ; A' and B' are the state transfer coefficient matrix and gain matrix respectively; represents the posterior estimated covariance at time k; represents the prior estimated covariance at time k+1; F(k+1) represents the Jacobian matrix at time k+1; Q represents the system noise covariance matrix.

[0086] The measurement update process is:

[0087]

[0088] Where K(k+1) represents the gain matrix at time k+1; G(k+1) represents the Jacobian matrix at time k+1; represents the output matrix at time k+1; C' represents the state transfer coefficient matrix; y(k+1) represents the actual output variable at time k+1; I represents the unit gain matrix.

[0089] Step 2: For Figure 3 The motor drive module 41 in the embodiment is specifically constituted as follows Figure 4 shown.

[0090] The input signal n* of the motor drive module 41 is Figure 2 The input signal n* is calculated by subtracting the motor feedback speed n, where the motor feedback speed n is obtained by the Hall sensor 48, speed angle calculation and the speed sensor 49. The speed error Δn is obtained by subtracting the speed command value n* from the feedback speed n. The speed error Δn is used as the input of the first PI controller 43. After being adjusted by the first PI controller 43, the q-axis current control signal i is obtained. q *, and specify the d-axis current control signal i d * = 0. i d * with i q *Differentiate with the current feedback signal to obtain the current error signal Δi d and Δi q , where the d-axis current feedback signal i d and q-axis current feedback signal i q The current error signal Δi is calculated by the current sensorless module 50. d and Δi q The d-axis and q-axis voltage commands u are obtained through the second PI controller 44 and the third PI controller 45 respectively. d and u q .u d and u q After the first coordinate transformation module 46, u α and u β ,u α and u β As the input of SVPWM inverter 47, the three-phase voltage u is obtained after modulation and amplification. A 、u B 、u CThe brushless DC motor 42 is driven to operate with the voltage.

[0091] The Hall sensor 48 detects three Hall signals and sends the signals to the speed angle calculation and the speed sensor 49 for calculation to obtain the speed n and the angle signal θ e , the calculation process is:

[0092]

[0093] In the formula, ω m Represents the motor mechanical angular velocity, ω e Represents the motor electrical angular velocity, P n Indicates the number of motor pole pairs.

[0094] θ e (k) = θ e (k-1)+ω e Δt(32)

[0095] In the formula, θ e (k-1) represents the motor angle at time k-1, θ e (k) represents the motor angle at time k, and Δt represents the time interval.

[0096] After the Hall sensor 48 and the speed angle calculation and the speed sensor 49 calculation, the motor rotor speed n and angle signal θ are obtained. e , the signal is sent to the current sensorless module 50, and then the voltage u output by the SVPWM inverter module 47 is A 、u B 、u C Sent to the current sensorless module 50, the d-axis and q-axis current signals i can be calculated d and i q The specific calculation process is:

[0097] Three-phase voltage u A 、u B 、u C After coordinate transformation, the d and q axis voltages u are obtained d and u q :

[0098]

[0099] The corresponding d and q axis currents can be calculated by the following formula:

[0100]

[0101] In the formula,

[0102] After calculation by formula (6), the dq axis current can be obtained. In order to obtain more accurate dq axis current, it can also be filtered after passing through a current filter, including a Kalman filter, a median filter, etc.

[0103] After calculation by the current sensorless module 50, the current feedback signal i is obtained. d and i q , convert the current signal into the current i in the stationary coordinate system α and i β After that, a speed sensorless calculation is performed to obtain the calibrated speed n 1 and the angle signal θ e1 The specific calculation process is:

[0104]

[0105] Where, L s Represents the motor stator inductance. For surface-mount brushless DC motors, L s =L d =L q ; f Represents the flux linkage of a permanent magnet.

[0106] The rotor electrical angle θ can be estimated by sampling the current and voltage signals in the stationary coordinate system. e . Magnetic flux λ in the stationary coordinate system α and λ β The expression can be expressed as:

[0107]

[0108] The stator flux can be calculated by the following formula:

[0109]

[0110] In the formula, λ αβ =[λ α λ β ] T .

[0111] Define a vector function η(λ αβ ), the function satisfies:

[0112]

[0113] The corresponding Euclidean norm in the above formula can be expressed as:

[0114]

[0115] definition is the estimated value of stator flux, is the cost function.

[0116] The gradient corresponding to the cost function is:

[0117]

[0118] The following observer is constructed according to the gradient descent method:

[0119]

[0120] Where a is the gain coefficient.

[0121] From (10), we can conclude that:

[0122]

[0123] In the formula, is the angle error,

[0124] Step 3: For Figure 5 The fan drive module 51 in the embodiment has a specific structure and Figure 4 The whole control process is similar to step 2, the fan speed n, angle signal θ e , feedback current i d and i q The calculation process of is similar to step 2 and will not be repeated here.

[0125] The above description is only a preferred embodiment of the present invention. It should be pointed out that a person skilled in the art can make several improvements without departing from the principle of the present invention, and these improvements should also be regarded as within the protection scope of the present invention.

Claims

1. A construction system based on a speed signal fusion algorithm of a fertilizer planter and a sensorless drive of a brushless DC motor, comprising a drive control system, wherein the drive control system comprises a brushless DC motor and a brushless DC fan, and is characterized in that: Also includes: Beidou satellite signal module and radar signal module for obtaining the tractor's driving speed; An extended Kalman filter, wherein the extended Kalman filter fuses and calculates the driving speeds v1 and v2 obtained by the Beidou satellite signal module and the radar signal module to obtain the tractor driving speed signal v3, and obtains a corresponding speed command value n* according to the sowing amount; Intelligent drive control module, the motor speed command value is used as the input of the intelligent drive control module to drive the brushless DC motor and the brushless DC fan to operate adaptively.

2. The construction system based on the speed signal fusion algorithm of the fertilizer planter and the sensorless drive of the brushless DC motor as claimed in claim 1 is characterized in that: The extended Kalman filter includes a state prediction module and a measurement update module. The state prediction module iteratively predicts the driving speed signal obtained by the Beidou satellite signal module and the radar signal module, and the measurement update module updates the driving speed signal obtained by the Beidou satellite signal module and the radar signal module.

3. The construction system based on the speed signal fusion algorithm of the fertilizer planter and the sensorless drive of the brushless DC motor as claimed in claim 1 is characterized in that: The intelligent drive control module also includes a motor drive module and a fan drive module, and the brushless DC motor and the brushless DC fan are connected to the motor drive module and the fan drive module respectively.

4. The construction system based on the speed signal fusion algorithm of the fertilizer planter and the sensorless drive of the brushless DC motor as claimed in claim 3 is characterized in that: The motor drive module and the fan drive module both include a first PI controller, a second PI controller, a third PI controller, a first coordinate transformation module, an SVPWM inverter, a feedback speed calculation unit and a current sensorless module. The first PI controller is connected to the third PI controller, the second PI controller, the third PI controller and the SVPWM inverter are all connected to the first coordinate transformation module, the current sensorless module, the brushless DC motor and the brushless DC fan are all connected to the SVPWM inverter, and the feedback speed n of the brushless DC motor and the brushless DC fan is obtained by the feedback speed calculation unit.

5. The construction system based on the speed signal fusion algorithm of the fertilizer planter and the sensorless drive of the brushless DC motor as claimed in claim 4 is characterized in that: The motor feedback speed calculation unit includes a Hall sensor, a speed sensor and a speed angle calculation module.

6. A method for constructing a construction system as claimed in any one of claims 1 to 5, characterized in that: The driving speed of the tractor is obtained through the Beidou satellite signal module and the radar signal module, respectively, which are recorded as v1 and v2. The driving speed v3 is obtained by fusion calculation of v1 and v2 for state prediction and measurement update. According to the sowing amount of different seeds and fertilizers, the corresponding speed command value n* is calculated; The speed command value n* is used as the input of the motor drive module and the fan drive module. After being controlled by the motor and fan drive modules, the three-phase drive voltage u is obtained. A 、u B 、u C , used to drive the brushless DC motor and brushless DC fan to operate adaptively.

7. The construction method according to claim 6, characterized in that: The state prediction function is: In the formula, is the predicted value of the state at time k, is the state prediction value at time k+1, and these two correspond to the driving speed signal v3; u(k) is the input value at time k, including v1 and v2; A' and B' are the state transfer coefficient matrix and gain matrix respectively; represents the posterior estimated covariance at time k; represents the prior estimated covariance at time k+1; F(k+1) represents the Jacobian matrix at time k+1; Q represents the system noise covariance matrix; The measurement update function is: Where K(k+1) represents the gain matrix at time k+1; G(k+1) represents the Jacobian matrix at time k+1; represents the output matrix at time k+1; C' represents the state transfer coefficient matrix; y(k+1) represents the actual output variable at time k+1; I represents the unit gain matrix.

8. The construction method according to claim 7, characterized in that: The feedback speed calculation unit obtains the feedback speed n of the brushless DC motor and the brushless DC fan, and the speed command value n* and the feedback speed n are adjusted by the first PI controller 43 to obtain the q-axis current control signal i q *, the speed error Δn is obtained after the difference, and the speed error Δn is used as the input of the first PI controller 43, and the d-axis current control signal i is specified at the same time. d * = 0; i d * with i q * respectively with the d-axis current feedback signal i d and q-axis current feedback signal i q The current error signal Δi is obtained by subtracting d and Δi q , where i d and i q Calculated by the current sensorless module; Current error signal Δi d and Δi q The d-axis and q-axis voltage instructions u are obtained through the second PI controller and the third PI controller respectively. d and u q ; u d and u q After the first coordinate transformation module, we get u α and u β ,u α and u β As the input of the SVPWM inverter, the three-phase voltage u is obtained after modulation and amplification. A 、u B 、u C The three-phase voltage is used to drive the brushless DC motor and the brushless DC fan.

9. The construction method according to claim 8, characterized in that: The process of the feedback speed calculation unit obtaining the feedback speed n is: The Hall sensor detects three Hall signals and sends the signals to the speed angle calculation module and the speed sensor 49 for calculation to obtain the speed n and angle signal θ e , the calculation process is: In the formula, ω m Represents the mechanical angular velocity of the motor in the brushless DC motor and brushless DC fan, ω e It represents the electrical angular velocity of the motor in the brushless DC motor and brushless DC fan, P n Indicates the number of motor pole pairs in brushless DC motors and brushless DC fans; i e (k)=θ e (k-1)+ω e Δt(4) In the formula, θ e (k-1) represents the motor angle of the brushless DC motor and brushless DC fan at time k-1, θ e (k) represents the motor angle at time k in the brushless DC motor and the brushless DC fan, and Δt represents the time interval; After the feedback speed calculation unit calculates, the feedback speed n and angle signal θ are obtained. e , the signal is sent to the current sensorless module, and then the voltage u output by the SVPWM inverter module A 、u B 、u C Sent to the current sensorless module to calculate the d-axis and q-axis current signals i d and i q ; The d-axis and q-axis current signals i d and i q The calculation process is: Three-phase voltage u A 、u B 、u C After coordinate transformation, the d and q axis voltages u are obtained d and u q : The corresponding d and q axis currents are calculated using the following formula: In the formula, 10. The construction method according to claim 9, characterized in that: The current feedback signal i d and i q The corresponding current i is converted into the stationary coordinate system α and i β , perform speed sensorless calculation to obtain the calibrated speed n1 and angle signal θ e1 , the calculation process is: Where, L s Represents the motor stator inductance in brushless DC motors and brushless DC fans; λ f Represents the permanent magnet flux; the rotor electrical angle θ is obtained by sampling the current and voltage signals in the stationary coordinate system e ; Magnetic flux λ in the stationary coordinate system α and λ β The expression is expressed as: The stator flux is calculated by the following formula: where λ αβ = [λ α λ β T ;​ Define a vector function η(λ αβ ), the function satisfies: The corresponding Euclidean norm in formula (10) is expressed as: definition is the estimated value of stator flux, is the cost function; The gradient corresponding to the cost function is: The observer is constructed according to the gradient descent method: Where a is the gain coefficient; From (10), we can conclude that: In the formula, is the angle error,

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