Method for estimating driving a brushless direct current motor using a magnetic chain

Abstract

The application relates to the technical field of alternating current motor transmission control, in particular to a method for driving a brushless direct current motor by using flux linkage estimation. The application comprises the following steps: step 1, establishing a voltage equation of a permanent magnet synchronous motor; step 2, signal acquisition; step 3, flux linkage estimation and updating the flux linkage value; step 4, calculating a current regulation value through a PID controller; and step 5, transmitting the calculated value to the motor to control the motor rotation. The application can effectively maintain the stability and accuracy of motor operation.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of AC motor drive control technology, and particularly relates to a brushless direct current motor. BACKGROUND

[0002] The brushless direct current motor refers to a motor without brush and commutator. When the stator winding is connected with direct current, a rotating magnetic field is generated. The magnetic field of the rotor permanent magnet and the stator rotating magnetic field have the relationship of mutual attraction and repulsion. The rotor will continuously adjust its position to maintain the relative motion with the stator rotating magnetic field, so as to realize the continuous rotation of the motor. In order to realize the real-time control of the brushless direct current motor, the accurate position of the rotor flux linkage relative to the stator winding needs to be known. Generally, the position sensor such as the Hall sensor, the rotary transformer and the optical encoder needs to be installed in the motor to detect the position information of the rotor, and the position information of the rotor is fed back to the control circuit of the motor, so as to control the commutation time and sequence of the electronic commutator.

[0003] However, the cost of the motor is more sensitive to the household appliances, power tools, small fans and water pumps and other consumer products, and the space is limited. These position sensors increase the complexity and cost of the system, and are easily disturbed by the environment, which leads to the decrease of the control accuracy. The brushless direct current motor without position sensor has a wide application in these fields due to its simple structure and low cost. Since the position sensor of the motor and the related installation structure, wiring and signal processing circuit are removed, the rotor position needs to be estimated by an indirect method, so as to realize the commutation control of the electronic commutator and ensure the normal operation of the motor, which increases the complexity of the control algorithm.

[0004] The Chinese invention patent with the authorized announcement number CN104601057B discloses a driving control method and system of the brushless direct current motor. The zero-crossing point of the back electromotive force is obtained through the three-phase voltage balance equation, the position of the rotor magnetic steel is determined, and the commutation time is estimated, so as to drive and control the motor. However, the driving control method has two limitations: first, the zero-crossing point is easily affected. For the delta connection winding, the back electromotive force method needs to find a special point which can make the direction of the back electromotive force of any two phases be the same and the size be equal, so as to determine the position of the rotor magnetic steel. When the zero-crossing point is advanced or lagged due to the sudden change of the load, the error of the zero-crossing point leads to the step loss of the motor; second, the hardware performance is required to be high. When the motor runs at high speed, the inaccurate detection of the zero-crossing point leads to the decrease of the control accuracy of the motor. SUMMARY

[0005] The purpose of the present application is to provide a method for driving the brushless direct current motor by estimating the flux linkage, which has the effect of calculating the flux linkage in real time and effectively maintaining the stability and accuracy of the motor operation.

[0006] The technical scheme of the present application is: a method for driving the brushless direct current motor by estimating the flux linkage, characterized by comprising the following steps:

[0007] Step 1, establish the voltage equation of permanent magnet synchronous motor, the formula is as follows:

[0008]

[0009] Where, U d , U q are the stator d-axis and q-axis voltage respectively, i d , i q are the stator d-axis and q-axis current respectively, L d , L q are the d-axis and q-axis inductance respectively, R s is the stator resistance, is the rotor flux, ω is the motor angular velocity;

[0010] Step 2, signal acquisition, get voltage signal U a , U b , current value i a , i b ; Wherein U a represents the phase voltage of motor A winding; U b represents the phase voltage of motor B winding; i a represents the phase current of motor A winding; i b represents the phase current of motor B winding;

[0011] Step 3, flux estimation, and update the step of flux value

[0012] Step 31, Clark transformation: convert i a and i b current signal into two orthogonal components:

[0013] i α = i a

[0014]

[0015] i α represents the α-axis current component in the stationary coordinate system, i β represents the β-axis current component in the stationary coordinate system;

[0016] Step 32, Park transformation: convert α-β coordinate system to d-q coordinate system

[0017] i d = i α *cosθ+i β *sinθ

[0018] i q =-i αsin theta + i β cos theta

[0019] i d represents the d-axis current component in the stationary coordinate system, i q represents the q-axis current component in the stationary coordinate system, theta is the rotor angle;

[0020] Step 33, an estimation step of estimating the rotor position based on the flux linkage:

[0021] using the extended back electromotive force calculating the rotor angle:

[0022]

[0023] represents the alpha-axis back electromotive force component in the stationary coordinate system; represents the beta-axis back electromotive force component in the stationary coordinate system;

[0024] omega_e_hat: is the estimated electrical angular velocity, which can be estimated by the measured motor angular velocity omega, is an estimated parameter, the formula is as follows:

[0025]

[0026] ObserverTheta(k) is the observation angle ObserverTheta at the current time;

[0027] ObserverTheta(k-1): observation angle at the last sampling time;

[0028] T S : system sampling period

[0029] Step 34, calculating intermediate variables y1, y2

[0030] Y1 = Ua - i α *[omega_e_hat*RsObserver*0.005]

[0031] Y2 = Ua - i β *[omega_e_hat*RsObserver*0.005]

[0032] RsObserver is the internal resistance of the motor;

[0033] Step 35, calculating the flux linkage component of the next step;

[0034] eta_x1_hat = X1_hat - Ls*i α

[0035] eta_x2_hat = X2_hat - Ls * i β

[0036] Flux^2 - (eta_x1_hat)^2 - (eta_x2_hat)^2 = eta_res

[0037] State update equations, X1_hat and X2_hat are fed back to step 35 for continuous iteration

[0038] FLUX is the flux of the motor calculated by back EMF;

[0039] x1_hat and x2_hat are the estimated α, β axis flux components;

[0040] eta_x1_hat, eta_x2_hat are the error feedback terms related to X1_hat and X2_hat for α, β axis state estimation error;

[0041] omega_e_hat is the estimated electrical angular velocity;

[0042] eta_res is the residual term for feedback correction link;

[0043] is the rate of change of X1_hat and X2_hat with respect to time, respectively;

[0044] Ls is the inductance value of the induced EMF;

[0045] The rotor angle is estimated, and the calculation formula is as follows:

[0046] Pll_omega * pll_xi + pll_omega^2 * Ts / (eta_x2_hat * cosθ - eta_x1_hat

[0047] * sinθ) = omega_e_hat

[0048] pll_omega is the angular frequency parameter; pll_xi is the damping coefficient in the phase-locked loop; Ts is the sampling frequency; step 4, the current regulation value is calculated by the pid controller

[0049] d-axis current error ed = ref_i d - i d

[0050] q-axis current error eq = ref_i q - i q

[0051] PI control output formula:

[0052] d-axis control voltage: U d = Kp_d * ed + Ki_d * ∫ed dt,

[0053] q-axis control voltage: U q = Kp_q * eq + Ki_q * ∫eq dt,

[0054] wherein Kp_d, Kp_q are proportional coefficients of d-axis, q-axis PI controller;

[0055] Ki_d, Ki_q are integral coefficients of d-axis, q-axis PI controller;

[0056] ∫ed dt, ∫eq dt are integral terms of d-axis, q-axis current error;

[0057] wherein ref_i d and ref_i q are given values;

[0058] Step 5, transmit the calculated value to the motor control motor rotation

[0059] Step 51, inverse park transformation

[0060] U α = U d *cos θ - U q *sin θ

[0061] U β = U d *cos θ + U q *sin θ

[0062] Step 52, inverse clark transformation inverse clark transformation converts into three-phase voltage drive motor operation:

[0063] U a = U α

[0064]

[0065]

[0066] Ua, Ub, Uc are generated three-phase voltage.

[0067] The beneficial effects of this invention are: the technical method of this invention can suppress harmonics and reduce electromagnetic interference (EMI) during motor operation. This invention can improve the robustness of the system, suppress external interference and parameter uncertainties; and by estimating the rotor flux linkage of the motor, it replaces position sensors to obtain the rotor position information of the motor. The calculation process of this invention is simple, and the input-to-output control can be completed within twenty nanoseconds, thereby achieving real-time calculation of flux linkage and updating control parameters, effectively maintaining the stability and accuracy of motor operation. Attached Figure Description

[0068] Figure 1 This is a schematic diagram of the process of the present invention.

[0069] Figure 2 This is a flowchart of the startup and calibration process for the analog-to-digital converter in a brushless DC motor drive control system.

[0070] Figure 3 Rotor position diagram for rotor position estimation based on magnetic flux linkage.

[0071] Figure 4 This is a flowchart for rotor estimation.

[0072] Figure 5 This is a diagram of a PID controller. Detailed Implementation

[0073] The technical solution of the present invention will be further described below with reference to the accompanying drawings.

[0074] like Figures 1 to 5 As shown, this invention provides a method for estimating the magnetic flux linkage of a brushless DC motor. This method uses a motor model and measured electrical signals to estimate the rotor flux linkage and position of the motor in real time. By controlling the flux linkage, it indirectly achieves efficient control of variables such as torque and current. The method includes the following steps:

[0075] Step 1: Initialize motor parameters

[0076] The voltage equation for a permanent magnet synchronous motor is as follows:

[0077]

[0078] Among them, U d U q Let i be the stator d-axis and q-axis voltages, respectively. d i q Let L be the stator d-axis and q-axis currents, respectively. d L q Let R be the inductance along the d-axis and q-axis, respectively. s For stator resistance, U is the rotor flux linkage, ω is the motor angular velocity, and in the above formula, U d Uq , i d , i q are unknown variables, are inherent parameters of the motor, confirmed by motor design, and the rest are obtained by measurement.

[0079] Step 2, signal acquisition, get two-phase current

[0080] The voltage signal of the motor is collected by the sensor, and the noise is removed by the filter to ensure the stability and accuracy of the signal. The analog-to-digital converter (ADC) is started and calibrated. First, the calibration is started. By calibration, the offset error inside the ADC can be eliminated, so that the measurement result is closer to the true value.

[0081] The calibration steps are as follows:

[0082] 1. When the input signal is zero, record the average value of the ADC output as the offset

[0083] 2. When collecting subsequently, subtract the offset from the original ADC value.

[0084] 3. Formula:

[0085] Secondly, the flag bits are cleared. By clearing these flag bits, the correct triggering and state judgment of the next conversion can be ensured, and the error operation caused by residual flag bits can be avoided; finally, the channel conversion is started.

[0086] As shown in Figure 2 , by starting ADC calibration and correctly handling flag bits, accurate voltage signals U a , U b can be obtained, where U a represents the phase voltage of the motor A phase winding (such as phase A in a three-phase motor). U b represents the phase voltage of the motor B phase winding (such as phase B in a three-phase motor).

[0087] Further, through sampling resistance and other circuit conversion, accurate current values i a , i b , i a are obtained, where i b represents the phase current of the motor A phase winding, and i b represents the phase current of the motor B phase winding. Provide reliable data support for subsequent flux estimation and current control modules.

[0088] Step 3, flux estimation, and update the flux value

[0089] Step 31, Clark transformation: i a and i bThe current signal is converted into two orthogonal components, the alpha axis and the beta axis (stationary coordinate system)

[0090] i α = i a

[0091]

[0092] i α = i β = i

[0093] Step 32, Park transformation: convert the alpha-beta coordinate system to the d-q coordinate system

[0094] i d = i α *cos theta + i β *sin theta

[0095] i q = -i α *sin theta + i β *cos theta

[0096] i d = i q = i a , i b are known, and theta is the rotor angle (this angle is obtained by rotor angle estimation and fed back to this part for use). The above two steps are to simplify the problem for motor control decoupling, greatly reduce the calculation amount of the present application, and thus improve the real-time performance of input and output.

[0097] Step 33, rotor position estimation based on flux linkage The estimation step of the rotor position is shown in Figure 3

[0098] i a = i b = i a = i b = iThe values of I_alpha, I_beta, u_alpha, and u_beta are obtained in the above steps. ObserverTheta is the observation angle, which is unknown and is estimated in real time by an observer algorithm. The modeling formula of the back electromotive force observer is as follows:

[0099]

[0100] The stator current i α (corresponding Figure 3 to I_alpha in the above formula), iβ (corresponding to Figure 3 I_beta);

[0101] Stator voltage u α (corresponding to Figure 3 V_alpha), u β (corresponding to Figure 3 V_beta).

[0102] These signals are the basic inputs for the observer algorithm. By making the estimated currents close to the actual currents, the extended back EMF represents the back EMF component on the alpha axis in the stationary reference frame; represents the back EMF component on the beta axis in the stationary reference frame;

[0103] The extended back EMF is used to calculate the rotor angle:

[0104]

[0105] where The above equations are the theoretical basis, defining the relationship between back EMF (flux differential) and voltage, current, but at this time X1_hat, X2_hat need to be obtained through subsequent iterative calculations.

[0106] omega_e_hat: is the estimated electrical angular velocity, which can be estimated by the measured motor angular velocity ω, is the estimated parameter, the formula is as follows:

[0107]

[0108] ObserverTheta(k) is the observation angle ObserverTheta at the current time

[0109] ObserverTheta(k-1): observation angle at the last sampling time

[0110] T S : system sampling period

[0111] Step 34, get intermediate variables y1, y2 from i_alpha, i_beta, u_alpha, u_beta and omega_e_hat

[0112] Y1 = Ua - i α *[omega_e_hat * RsObserver * 0.005]

[0113] Y2 = Ua - i β*[omega_e_hat*RsObserver*0.005]

[0114] RsObserver is the internal resistance of the motor, i.e. R s Stator resistance, RsObserver is determined by the physical characteristics of the motor itself, which belongs to the motor body parameters.

[0115] i a I_alpha, i b I_beta, U a u_alpha, U b u_beta, The numerical values of I_alpha, I_beta, u_alpha, u_beta are obtained by the above steps. ObserverTheta is the observation angle; omega_e_hat: is the estimated electrical angular velocity, which can be estimated by the measured motor angular velocity ω, which is the estimated parameter.

[0116] Step 35, calculate the next step flux component X1_hat and X2_hat

[0117] eta_x1_hat=X1_hat-Ls*i α

[0118] eta_x2_hat=X2_hat-Ls*i β

[0119] Flux^2-(eta_x1_hat)^2-(eta_x2_hat)^2=eta_res

[0120] State update formula, X1_hat and X2_hat obtained as follows are fed back to step 35 for continuous iteration

[0121] FLUX is the flux of the motor calculated by the back electromotive force.

[0122] x1_hat and x2_hat are the estimated alpha and beta axis flux components.

[0123] eta_x1_hat, eta_x2_hat: are the error feedback items related to X1_hat and X2_hat of the alpha and beta axes, which are used to feedback and correct the state estimation error;

[0124] omega_e_hat: estimated electrical angular velocity, obtained by the above steps, fed back to the flux update link in this step to form a closed loop iteration, and finally realize the accurate estimation of motor flux and electrical angular velocity

[0125] eta_res: residual term for feedback correction link

[0126] respectively represent the rate of change of X1_hat and X2_hat with respect to time.

[0127] Ls: inductance value of the induced electromotive force

[0128] According to these components, the rotor angle is estimated again, and the calculation formula is as follows:

[0129] Pll_omega*pll_xi+pll_omega^2*Ts / (eta_x2_hat*cosθ-eta_x1_hat

[0130] *sinθ)=omega_e_hat

[0131] pll_omega is an angular frequency parameter, which is used to determine the lock frequency and tracking speed of the PLL. pll_xi is a damping coefficient in the phase-locked loop, which is used to adjust the stability and response characteristics of the system, and this value is set as needed during debugging. Ts is the sampling frequency.

[0132] Through this step, the calculated omega_e_hat is fed back to the flux linkage update link to form a "electric angular velocity→flux linkage→electric angular velocity" closed loop iteration, and finally realize the accurate cooperative estimation of motor flux linkage and electric angular velocity.

[0133] Step 4, calculate the current regulation value through the pid controller

[0134] Given ref_i d and ref_i q The specific value of ref_i d is generally given as 0, and ref_i q is a self-given q-axis current reference graph. In control, generally Id=0 is given to simplify the calculation of the formula. After obtaining the error of them and i d , i q , the error is input into two PID (only PI is used) controllers to obtain the output control voltage U d , U q , as shown in Figure 5 .

[0135] The d-axis current error ed=ref_i d -i d

[0136] The q-axis current error eq=ref_i q -i q

[0137] PI control output formula:

[0138] d-axis control voltage: U d = Kp_d * ed + Ki_d * ∫eddt, (i.e. stator d-axis voltage)

[0139] q-axis control voltage: U q = Kp_q * eq + Ki_q * ∫eqdt, (i.e. stator q-axis voltage)

[0140] Where Kp_d, Kp_q: proportional coefficient of d-axis, q-axis PI controller, used for fast response to current error.

[0141] Ki_d, Ki_q: integral coefficient of d-axis, q-axis PI controller, used to eliminate current steady-state error.

[0142] ∫eddt, ∫eqdt: integral term of d-axis, q-axis current error, accumulates historical error to optimize control effect.

[0143] Through the above formula, PI controller calculates the required Ud, U q , and then generates three-phase voltage to drive the motor through techniques such as space vector modulation (SVPWM), achieving precise control of motor current.

[0144] The control effect of P proportional part makes the system quickly respond to error and adjust towards reducing error. I integral part is mainly used to eliminate steady-state error. During the operation of the control system, a fixed error may exist due to various factors (such as system α nonlinearity, external disturbance, etc.). Even if the proportional part can reduce the error, it may not be able to completely eliminate it. The integral part accumulates control effect through integration of error. As time accumulates, as long as there is error, the integral term will continue to increase until the error is zero. The control diagram is as follows:

[0145] Step 5, transmit the calculated value to the motor control motor rotation

[0146] Step 51, inverse park transformation

[0147] U α = U d *cosθ - U q *sinθ

[0148] U β = U d *cosθ + U q *sinθ

[0149] The inverse Park transformation can convert the direct current signal into two-phase alternating current signal, lay the foundation for generating three-phase alternating current driving signal, so that the control signal can correspond to the actual operation physical quantity of the motor, thereby accurately controlling the operation of the motor.

[0150] Step 52, inverse Clark transformation

[0151] The inverse Park transformation described above is converted into three-phase voltage driving motor operation through inverse Clark transformation.

[0152] U a = U α

[0153]

[0154] Generate three-phase voltage Ua, Ub, Uc, for driving the three-phase inverter of the motor (such as generating PWM signal by SVPWM technology)

[0155] Step 53, space vector pulse width modulation

[0156] By controlling the conduction and turn-off of the inverter power switching device, the direct current voltage is effectively converted into the desired alternating current voltage, so as to realize accurate control of the motor. According to the U α , U β The components are defined as follows:

[0157]

[0158] U3 = -U β

[0159] U1, U2: are the combinations of voltage components in two-phase stationary coordinate system (α-β), used to determine the sector where the reference voltage vector is located. U3: is the opposite number of U β , also participates in sector judgment or action time calculation

[0160] Sector N represents the 60° area where the reference voltage vector is located.

[0161] According to the positive and negative of U1, U2, U3, the sector is determined

[0162] N = 1, U1≥0, U2≥0, U3≥0

[0163] N = 2, U1≥0, U2≥0, U3≤0

[0164] N = 3, U1≤0, U2≥0, U3≤0

[0165] N = 4, U1≤0, U2≤0, U3≤0

[0166] N=5, U1≤0, U2≤0, U3≥0

[0167] N=6, U1≥0, U2≤0, U3≥0

[0168] For different sectors, the two adjacent effective vectors are respectively:

[0169] N=1,

[0170] N=2,

[0171] N=3,

[0172] N=4,

[0173] N=5,

[0174] N=6,

[0175] In space vector pulse width modulation (SVPWM), to represent six basic effective voltage vectors, each vector amplitude is (Vdc is the DC bus voltage), adjacent vectors in two-phase stationary coordinate system (a-β) phase difference 60°, together divided into six sectors (N=1 to N=6).

[0176] Where Vdc is the bus voltage. Take sector 1 as an example, the action time Ts of the adjacent effective vector is calculated as the sampling period:

[0177]

[0178] T0=Ts-T1-T2

[0179] T1: the action time of the first effective voltage vector in sector 1, calculated by the formula, and Uβ is related.

[0180] T2: the action time of the second effective voltage vector, involving Uα and Uβ.

[0181] T0: zero vector action time, to ensure that the total time is equal to the sampling period Ts.

[0182] According to the calculated action time, the duty ratio of three-phase PWM wave is calculated

[0183]

[0184] DC=0

[0185] Da: represents the duty ratio of phase A in three-phase PWM, that is, the ratio of the high level time of the A-phase PWM wave to the sampling period Ts, which is determined by the effective vector action time T1 and T2, and reflects the on-time ratio of the A-phase in synthesizing the target voltage.

[0186] Db: represents the duty ratio of phase B, that is, the ratio of the high level time of the B-phase PWM wave to the sampling period Ts, which is only related to T2, and embodies the on-time ratio of the B-phase.

[0187] Dc: Dc=0 here, representing that the high level duty ratio of the C-phase PWM wave is 0, that is, the high level duration of the C-phase in the current sampling period is 0, and it is always in the low level state.

[0188] From this, the three-phase output of the motor controlled by the calculated pwm is obtained.

[0189] Step 6, feedback loop: obtain new current data, repeat the above estimation and control process.

[0190] The method of the application can achieve the following technical effects: 1. Overshoot: in the scenario of sudden change of motor load, the overshoot of the electrical angular velocity estimation value is less than or equal to 5%, and the tracking ability is relatively stable. 2. Adjustment time: the adjustment time of the flux linkage estimation value after the load changes is less than or equal to 20ms, which maintains the control stability. 3. Electrical angular velocity estimation error: in the range of 0 to rated speed, the electrical angular velocity estimation error is less than or equal to ±1% of the rated speed, which ensures the accuracy of the motor speed loop control.

Claims

1. A method for estimating the driving of a brushless DC motor using flux linkage, characterized in that: Includes the following steps: Step 1: Establish the voltage equation for the permanent magnet synchronous motor, as shown in the following formula: Among them, U d U q Let i be the stator d-axis and q-axis voltages, respectively. d i q Let L be the stator d-axis and q-axis currents, respectively. d L q Let R be the inductance along the d-axis and q-axis, respectively. s For stator resistance, ω is the rotor flux linkage, and ω is the motor angular velocity; Step 2: Signal acquisition, obtain voltage signal U a U b Current value i a i b ;where U a U represents the phase voltage of phase A winding of the motor; b This represents the phase voltage of phase B winding of the motor; i a Indicates the phase current of phase A winding of the motor; i b This represents the phase current of phase B winding of the motor; Step 3: Estimate flux linkage and update the flux linkage value. Step 31, Clark Transform: Transform i a and i b The current signal is converted into two orthogonal components: i α i represents the α-axis current component in the stationary coordinate system. β Represents the β-axis current component in the stationary coordinate system; Step 32, Park Transformation: Convert the α-β coordinate system to the dq coordinate system. i d =i α *cosθ+i β *sinθ i q =-i α *sinθ+i β *cosθ i d i represents the d-axis current component in the stationary coordinate system. q θ represents the q-axis current component in the stationary coordinate system, where θ is the rotor angle. Step 33: Rotor position estimation based on flux linkage. The steps for estimating the rotor position are as follows: Using extended back electromotive force Calculate the rotor angle: Represents the α-axis back-electromotive component in the stationary coordinate system; Represents the β-axis back-electromotive component in the stationary coordinate system; omega_e_hat: This is the estimated electrical angular velocity. The estimated electrical angular velocity can be obtained by measuring the motor angular velocity ω. The estimated parameter is given by the following formula: ObserverTheta(k) is the observation angle ObserverTheta at the current moment; ObserverTheta(k-1): The observation angle at the previous sampling time; T S System sampling period Step 34: Calculate intermediate variables y1 and y2 Y1=Uα-i α *[omega_e_hat*RsObserver*0.005] Y2=Uα-i β *[omega_e_hat*RsObserver*0.005] RsObserver represents the internal resistance of the motor; Step 35: Calculate the flux linkage component for the next step; eta_x1_hat=X1_hat-Ls*i α eta_x2_hat=X2_hat-Ls*i β Flux^2-(eta_x1_hat)^2-(eta_x2_hat)^2=eta_res The state update formula, as shown below, yields X1_hat and X2_hat, which are fed back to step 35 for continuous iteration. FLUX is the flux linkage of the motor calculated from the back electromotive force; x1_hat and x2_hat are the estimated α and β axis flux linkage components; eta_x1_hat and eta_x2_hat are the error feedback terms related to the α and β axes and the state estimation errors of X1_hat and X2_hat; omega_e_hat is the estimated electric angular velocity; eta_res is the residual term, used in the feedback correction stage; Let X1_hat and X2_hat represent the rates of change of X1_hat and X2_hat with respect to time, respectively. Ls is the induced value of the magnetic induction electromotive force; The rotor angle can be estimated using the following formula: Pll_omega*pll_xi+pll_omega^2*Ts / (eta_x2_hat*cosθ-eta_x1_hat*sinθ) =omega_e_hat pll_omega is the angular frequency parameter; pll_xi is the damping coefficient in the phase-locked loop; Ts is the sampling frequency; Step 4: Calculate the current regulation value using the PID controller. d-axis current error ed=ref_i d -i d q-axis current error eq=ref_i q -i q PI control output formula: d-axis control voltage: U d =Kp_d·ed+Ki_d∫eddt, q-axis control voltage: U q =Kp_q·eq+Ki_q∫eqdt, Where Kp_d and Kp_q are the proportional coefficients of the d-axis and q-axis PI controllers; Ki_d and Ki_q are the integral coefficients of the d-axis and q-axis PI controllers, respectively. ∫eddt and ∫eqdt are the integral terms of the d-axis and q-axis current errors, respectively. Where ref_i d and ref_i q For a given value; Step 5: Transmit the calculated value to the motor control unit to control the motor's rotation. Step 51, Inverse Park Transform IN α =U d *cosθ-U q *sinθ IN β =U d *cosθ+U q *sinθ Step 52, Inverse Clark Transform Inverse Clarke transformation converts the voltage to a three-phase voltage to drive the motor. IN a =U α Ua, Ub, and Uc are the generated three-phase voltages.

2. The method for estimating the driving of a brushless DC motor using flux linkage according to claim 1, characterized in that: The specific process of step 2 is as follows: the voltage signal of the motor is acquired by the sensor, noise is removed by the filter, and the offset error inside the ADC is eliminated by calibration; The calibration steps are as follows:

1. When the input signal is zero, record the average value of the ADC output as the offset; 2. During subsequent data acquisition, subtract this offset from the original ADC value; 3. Official:

3. The method for estimating the driving of a brushless DC motor using flux linkage according to claim 1, characterized in that: The formula for back electromotive force is as follows:

4. The method for estimating the driving of a brushless DC motor using flux linkage according to claim 1, characterized in that: It also includes step 53, Step 53, Space Vector Pulse Width Modulation U calculated based on the inverse Park transform α U β Define the following components: U3=-U β U1 and U2 are combinations of voltage components in a two-phase stationary coordinate system; sector N represents the 60° region where the reference voltage vector is located.

5. The method for estimating the driving of a brushless DC motor using flux linkage according to claim 4, characterized in that: The sector is determined based on the sign of U1, U2, and U3. N=1,U1≥0,U2≥0,U3≥0 N=2,U1≥0,U2≥0,U3≤0 N=3,U1≤0,U2≥0,U3≤0 N=4,U1≤0,U2≤0,U3≤0 N=5,U1≤0,U2≤0,U3≥0 N=6,U1≥0,U2≤0,U3≥0 For different sectors, the two adjacent valid vectors are respectively: to It represents the six basic effective voltage vectors.

6. The method for estimating the driving of a brushless DC motor using flux linkage according to claim 1, characterized in that: It also includes step 6, feedback loop: acquire new current data, and repeat the estimation and control process from step 1 to step 5.

7. The method for estimating the driving of a brushless DC motor using flux linkage according to claim 1, characterized in that:

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