Improved digital implementation method of high-reliability motor improved deadbeat torque control

Abstract

The application discloses a kind of high-reliability motor improved deadbeat torque control digital implementation methods, belong to motor drive control technical field.It includes the following steps: construct stator flux oriented coordinate system, acquisition motor signal and establish five-phase fault-tolerant motor model;Full-order Luenberger current observer is constructed to carry out delay compensation and state prediction to five-phase current;Hybrid flux observer is constructed, and integral drift of voltage model is corrected by closed-loop compensation, and the amplitude and phase angle of stator flux are obtained;Deadbeat control is carried out in MT coordinate system, and the simplified linear relationship between electromagnetic torque and load angle is established, and the reference voltage vector is linearly solved;The reference voltage is transformed back to the stationary coordinate system, and the switching signal is generated by using adjacent four-vector space vector pulse width modulation to drive the motor.The application can significantly improve the control performance of five-phase motor under normal operation of control system and the system stability under parameter mismatch, and has important significance for strengthening the reliability and stability of multiphase electric drive system.

Description

Technical Field

[0001] This invention relates to the field of deadbeat predictive control technology for multiphase permanent magnet fault-tolerant motors, and specifically to a digital implementation method for improved deadbeat torque control of highly reliable motors. Background Technology

[0002] Five-phase permanent magnet fault-tolerant motors have demonstrated significant application value in aerospace, new energy vehicles, and high-performance industrial drives due to their high power density, low torque ripple, and high reliability with multiple degrees of freedom. Compared with traditional three-phase motors, while the multi-degree-of-freedom five-phase system improves reliability, its complex electromagnetic relationships also pose serious challenges to the control system, especially in terms of real-time performance and robustness during digital implementation.

[0003] Driven by high-performance requirements, deadbeat torque and flux linkage control (DTFC) has become a research hotspot in the field of predictive motor control due to its advantages such as extremely fast dynamic response and no need for cumbersome parameter tuning. This method directly calculates the expected voltage for the next cycle through a discrete model of the motor, eliminating torque and flux linkage errors within one cycle. However, existing deadbeat torque control still faces the following challenges in its digital implementation.

[0004] First, digital controllers inherently suffer from sampling and computation delays. Under high-speed operating conditions, these delays can cause misalignment between the control voltage and the actual motor state in the time series, leading to current oscillations or even system malfunction. Second, traditional deadbeat torque control algorithms involve coupling between flux linkage and torque, requiring the solution of complex nonlinear equations in each sampling cycle. This involves tedious calculations of quadratic equations, making it difficult to meet the demands of high-frequency control. Furthermore, due to the dependence of deadbeat systems on mathematical models, deadbeat control is extremely sensitive to fluctuations in motor parameters. In actual operation, the permanent magnet flux linkage, stator resistance, and inductance of the motor dynamically change with current magnitude and temperature rise. Parameter mismatch can lead to decreased prediction accuracy, increased output torque ripple, and even shutdown. Therefore, constructing a digital control system with delay compensation capabilities, strong parameter robustness, and computational simplicity is crucial for improving the performance of five-phase permanent magnet fault-tolerant motor systems. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention proposes a highly reliable digital implementation method for improved deadbeat torque control of motors. The core ideas of this invention are as follows: First, a digital delay compensation mechanism based on a full-order Luenberger current observer and a two-step prediction method is proposed. By constructing a discretized state equation containing parameter disturbance terms, the current at time k+1 is accurately predicted using the state at time k, performing delay compensation and state prediction for the five-phase current, eliminating the impact of the inherent computational delay of the control system on dynamic performance, and suppressing disturbances caused by parameter mismatch. Second, a deadbeat torque solution strategy based on load angle linearization simplification is proposed. In the stator flux orientation coordinate system, the reference voltage vector is directly solved using the linear mapping relationship between torque and load angle, effectively avoiding the complex nonlinear equation calculations in traditional methods, reducing the computational complexity of multiphase systems and the computational burden on the processor. Finally, a hybrid flux observer is designed to achieve accurate observation of flux across the entire speed domain, and the parameters of the current and flux observers are rationally configured using a zero-pole placement method, significantly enhancing the stability and steady-state control accuracy of the system under parameter mismatch conditions.

[0006] A highly reliable digital implementation method for improved deadbeat torque control of motors includes the following steps:

[0007] Step S1. Construct the MT coordinate system: Define the direction of the stator flux linkage vector as the M-axis, and the direction leading the M-axis by 90 electrical degrees as the T-axis; collect the stator current, DC bus voltage, and rotor angle signals of the five-phase motor, and calculate the stator flux linkage amplitude ψ. s and the stator angle θ of the motor s The motor equations are transformed into the MT coordinate system to construct a five-phase fault-tolerant motor model, where the MT coordinate system is the stator flux linkage coordinate system.

[0008] Step S2. Construct a full-order Luenberger current observer for delay compensation and state prediction: Establish a discretized state equation for the motor containing parameter disturbance terms, and construct a full-order Luenberger current observer; use the control quantity and measurement quantity at the current time k to predict the five-phase stator current at time k+1, and observe the system disturbance voltage; the full-order Luenberger current observer introduces a feedback gain matrix to correct the prediction error, wherein the parameters of the feedback gain matrix are determined by the pole placement method;

[0009] Step S3. Construct a hybrid flux observer to calculate the stator flux angle and amplitude: Construct a hybrid flux observer based on the voltage model and the current model; use the corrected five-phase current model in step S2 to perform closed-loop compensation on the voltage model, correct the integral drift of the voltage model through a PI regulator, and output accurate stator flux amplitude and phase angle for real-time orientation of the MT axis coordinate system;

[0010] Step S4. Calculate the deadbeat reference voltage vector in the MT coordinate system: In the MT rotating coordinate system, the reference voltage components are calculated separately on the M and T axes using the decoupling characteristics of flux linkage and torque; For the M axis: The reference voltage of the M axis is linearly solved to control the stator flux linkage amplitude based on the error between the reference value and the predicted value of the flux linkage amplitude at the next moment; For the T axis: Based on the discretized torque equation, the non-dominant terms generated by the rotor flux linkage and current in the torque equation are ignored under the condition of ignoring the load angle, and a simplified linear relationship between the electromagnetic torque and the load angle is established. The reference voltage of the T axis is directly linearly solved to control the electromagnetic torque;

[0011] Step S5. Generate inverter switching signal to drive the motor: Transform the MT axis reference voltage component obtained in step S4 back to the stationary coordinate system. Considering the unique third harmonic interference of the five-phase motor, the adjacent four-vector SVPWM strategy is used to generate the inverter switching control signal to drive the five-phase permanent magnet fault-tolerant motor.

[0012] Furthermore, the specific steps for constructing the five-phase fault-tolerant motor model in the MT coordinate system in step S1 include:

[0013] Step S21: At time k, collect the five-phase stator current of the motor and obtain the current components in the stationary coordinate system through Clarke transformation. , ;

[0014] Step S22: Acquire DC bus voltage and the motor rotor position θ r (k) Using the stator flux component in the stationary coordinate system output by the hybrid flux observer in step S3. , The phase angle of the stator flux linkage vector is calculated using the arctangent function. The calculation formula is as follows:

[0015]

[0016] Step S23: Based on the stator flux linkage phase angle With rotor electrical angle Calculate the load angle at the current moment. :

[0017]

[0018] Step S24: Utilize the calculated stator flux linkage phase angle Construct a rotation transformation matrix to transform the current in the stationary coordinate system. , Transform to the MT rotating coordinate system with stator flux orientation to obtain the M-axis current. With T-axis current :

[0019]

[0020] Furthermore, the specific process of delay compensation in step S2 of the method is as follows: First step prediction: based on the sampled current at time k... and the voltage applied at the previous moment Predicting the current state at time k+1 based on the motor model The second step is to set the control objective: The control objective is set to eliminate the error at time k+2. The predicted values ​​are then used to determine the control objective. As input to the deadbeat controller, calculate the voltage vector that should be output at the current moment. This compensates for the control lag caused by the calculation delay of one beat.

[0021] Furthermore, the specific construction formula for the full-order Luneburg current observer described in step S2 is as follows: To address the parameter mismatch problem, the disturbance voltage caused by parameter errors is... As augmented state variables, a discretized observer model is constructed:

[0022]

[0023] In the formula, This is the estimated current value at the current moment. This is the current sample value at the current moment. This is the estimated value of the disturbance voltage at the current moment. For the controller output voltage, It is the back electromotive force. , These are the stator resistance and inductance, respectively. The sampling period; For current error feedback gain, This is the feedback gain for the disturbance error.

[0024] Furthermore, the hybrid flux observer described in step S3 is constructed by introducing a PI regulator into the flux correction voltage model obtained from the current model. The specific construction formula is as follows:

[0025]

[0026] in, The sampling period is For stator resistance, The controller output voltage at time k-1 The current sample value at time k-1, The compensation voltage term output by the PI regulator at time k is calculated using the following formula:

[0027]

[0028] In the formula, the error term The stator flux linkage vector estimated at the current moment; The reference value for flux linkage is calculated based on the current model; , These represent the proportional gain and integral gain of the hybrid observer, respectively.

[0029] Furthermore, the hybrid flux observer constructed in step S3 includes a current observer and a flux observer; its feedback gain parameter design and derivation method is as follows: configure the current observer parameters; establish the discrete error characteristic equation of the current observer and map it to the standard characteristic equation of a second-order system in the continuous domain. According to the system sampling period By selecting the observer bandwidth Damping ratio Calculate the gain using the pole placement method and This ensures the closed-loop poles lie within the unit circle; configure the flux linkage observer parameters: derive the transfer function of the hybrid flux linkage observer and compare its characteristic polynomial with the characteristic equation of a standard second-order system; based on the preset switching frequency... The relationship between the gain parameters is determined as follows: and The hybrid flux observer primarily uses a current model in the low-frequency band and a voltage model in the high-frequency band.

[0030] Furthermore, the process of solving the deadbeat reference voltage vector in step S4 is as follows: the voltage equation of the five-phase fault-tolerant motor is transformed into the MT coordinate system described in step S1 to obtain the discretized voltage equation:

[0031]

[0032] In the formula, , Let k be the reference voltage component at time k. , Let K be the reference current component at time k. For stator resistance, The sampling period is Let be the stator flux linkage amplitude at time k. Let $\frac{ ... This represents the load angle increment.

[0033] Using linear relationships, calculate the deadbeat reference voltage vector required to eliminate flux linkage error and torque error:

[0034]

[0035] In the formula, , To control the target value, , This is the observer's estimated value.

[0036] Furthermore, the linearization simplification logic for solving the reference voltage in step S4 is as follows: ignoring the load angle during the control cycle. Under the condition of ignoring non-dominant terms, a linear relationship between electromagnetic torque and load angle is established:

[0037]

[0038] In the formula, P is the pole logarithm. It is a permanent magnet flux chain. The stator inductance is used to deduce the torque increment at the next moment. With load angle increment Proportional;

[0039] This allows us to deduce the torque increment at the next moment. With load angle increment The voltage is proportional to the torque, and the reference voltage required to eliminate torque error is calculated accordingly.

[0040] The decoupling characteristic in step S4 specifically refers to: based on the linearization solution described in claim 2, the M-axis voltage component... Includes only flux linkage amplitude control term, T-axis voltage component It only includes torque control terms, thus achieving decoupling in the solution of control voltage, avoiding complex decoupling processes, and independently controlling torque and flux linkage; the overmodulation processing strategy specifically involves: through... Calculate the magnitude of the composite reference voltage vector ;when Exceeding the inverter's maximum output voltage When the system enters the overmodulation region, the controller output voltage is scaled proportionally, and the calculation formula is as follows:

[0041] .

[0042] Furthermore, the adjacent four-vector SVPWM strategy in step S5 is based on the distribution characteristics of the 32 spatial voltage vectors of the five-phase inverter, dividing the voltage space into 10 sectors; within each sector, two adjacent large vectors and two medium vectors are selected as basic voltage vectors, and the large and medium vectors are synthesized according to 0.618:0.312, so that the synthesized voltage vector of the third harmonic plane is zero, thus eliminating the influence of the third harmonic plane.

[0043] Compared with existing technologies, the method and system described in this invention have the following advantages:

[0044] 1. This invention proposes a highly reliable digital implementation method for improved deadbeat torque control of motors, effectively solving the torque oscillation caused by computational delay in digital systems. Addressing the sampling and computational lag problem in digital control, this invention utilizes a full-order observer in conjunction with a deadbeat algorithm to predict the current state at the next moment, thereby compensating for the control voltage in the time series. This method eliminates the beat frequency phenomenon easily generated by delay in traditional deadbeat control, reducing torque ripple in digital systems by 30%~50%, shortening dynamic response time by more than 40%, and maintaining stable output without overshoot or oscillation even under parameter mismatch and fault conditions.

[0045] 2. The highly reliable digital implementation method for improved deadbeat torque control of motors proposed in this invention significantly enhances the robustness of the control system to motor model parameter mismatch. Deadbeat control is typically highly sensitive to the accuracy of parameters such as motor inductance and flux linkage. This invention constructs a full-order state observer including a disturbance voltage term and uses the pole placement method to lock the closed-loop poles in the stable region. Even when the stator inductance parameter fluctuates drastically within the range of 0.5 to 1.5 times the true value, the method described in this invention can still maintain accurate torque tracking, solving the problem of system runaway or divergence caused by parameter changes.

[0046] 3. This invention proposes a highly reliable digital implementation method for deadbeat torque control of motors, which improves the orientation accuracy and flux linkage observation precision under low-speed operating conditions. The closed-loop hybrid flux linkage observer used in this invention solves the integral drift and phase deviation problems of the voltage model in the low-speed stage. Through real-time correction of the current model in the low-speed section, it ensures that the controller can always obtain an accurate stator flux linkage angle as an orientation reference during motor startup and low-speed operation, thereby significantly suppressing torque ripple under low-speed conditions and improving the low-speed output characteristics of the five-phase motor. Attached Figure Description

[0047] Figure 1 The present invention proposes a digital implementation method for a highly reliable motor improved deadbeat torque control, and presents an SVPWM flowchart.

[0048] Figure 2 The following is a digital control logic timing diagram of a highly reliable motor improved deadbeat torque control digital implementation method proposed in this invention;

[0049] Figure 3 This is a design diagram of a current observer for a highly reliable digital implementation method of improved deadbeat torque control for motors proposed in this invention.

[0050] Figure 4 This is a design diagram of a flux linkage observer for a highly reliable digital implementation method of improved deadbeat torque control for motors proposed in this invention.

[0051] Figure 5 This invention presents a highly reliable digital implementation method for improved deadbeat torque control of motors, including system decoupling solution and voltage limiting diagram.

[0052] Figure 6 This is a vector synthesis diagram of a digital implementation method for a highly reliable motor improved deadbeat torque control proposed in this invention;

[0053] Figure 7 The figure shows a dynamic performance comparison between the traditional deadbeat torque control method and the digital implementation method for improved deadbeat torque control of motors proposed in this invention.

[0054] Figure 8 The figure shows an experimental comparison between the traditional deadbeat torque control method and the digital implementation method for improved deadbeat torque control of motors proposed in this invention under the condition of flux linkage parameter mismatch.

[0055] Figure 9 The figure shows an experimental comparison between the traditional deadbeat torque control method and the digital implementation method for improved deadbeat torque control of motors proposed in this invention under the condition of inductor parameter mismatch.

[0056] Figure 10 This is a basic 3D design topology diagram of a digitally improved five-phase permanent magnet fault-tolerant motor in the digital implementation method of high-reliability motor improvement deadbeat torque control proposed in this invention;

[0057] Figure 11 This is a stator structure diagram of a digitally improved five-phase permanent magnet fault-tolerant motor in the digital implementation method of high-reliability motor improvement deadbeat torque control proposed in this invention;

[0058] Figure 12 Figure showing experimental results for improving the steady-state performance of a five-phase permanent magnet fault-tolerant motor through digitalization;

[0059] Figure 13 The waveforms of torque, speed and current when the torque increases during the experiment to improve the dynamic performance of a five-phase permanent magnet fault-tolerant motor through digitalization.

[0060] Figure 14 The waveforms of torque, speed, and current when the torque decreases during the experiment to improve the dynamic performance of a five-phase permanent magnet fault-tolerant motor through digitalization.

[0061] Figure 15 The torque and controller voltage response as the flux linkage parameters decrease from normal to reduced during the system robustness test of the five-phase permanent magnet fault-tolerant motor for digital improvement.

[0062] Figure 16The torque and controller voltage response diagrams are shown when the flux linkage parameter increases from normal to 1.4 times during the system robustness test of the digitally improved five-phase permanent magnet fault-tolerant motor.

[0063] Figure 17 The result of a single-phase open-circuit fault during an experiment to improve the fault-tolerant performance of a five-phase permanent magnet fault-tolerant motor using digital methods;

[0064] Figure 18 The result of a short-circuit fault during an experiment to improve the fault-tolerant performance of a five-phase permanent magnet fault-tolerant motor using digital methods. Detailed Implementation

[0065] The specific embodiments of the present invention are described below to enable those skilled in the art to understand the present invention. However, it should be understood that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, various changes are obvious as long as they are within the spirit and scope of the present invention as defined and determined by the appended claims. All inventions utilizing the concept of the present invention are protected.

[0066] Combination Figure 1 The present invention proposes a digital implementation method for improved deadbeat torque control of a high-reliability motor, which specifically includes the following steps:

[0067] Step S1. Construct the MT coordinate system: Define the direction of the stator flux linkage vector as the M-axis, and the direction leading the M-axis by 90 electrical degrees as the T-axis; collect the stator current, DC bus voltage, and rotor angle signals of the five-phase motor, and calculate the stator flux linkage amplitude ψ. s and the stator angle θ of the motor s The motor equations are transformed into the MT coordinate system to construct a five-phase fault-tolerant motor model, where the MT coordinate system is the stator flux linkage coordinate system.

[0068] Step S2. Construct a full-order Luenberger current observer for delay compensation and state prediction: Establish a discretized state equation for the motor containing parameter disturbance terms, and construct a full-order Luenberger current observer; use the control quantity and measurement quantity at the current time k to predict the five-phase stator current at time k+1, and observe the system disturbance voltage; the full-order Luenberger current observer introduces a feedback gain matrix to correct the prediction error, wherein the parameters of the feedback gain matrix are determined by the pole placement method;

[0069] Step S3. Construct a hybrid flux observer to calculate the stator flux angle and amplitude: Construct a hybrid flux observer based on the voltage model and the current model; use the corrected five-phase current model in step S2 to perform closed-loop compensation on the voltage model, correct the integral drift of the voltage model through a PI regulator, and output accurate stator flux amplitude and phase angle for real-time orientation of the MT axis coordinate system;

[0070] Step S4. Calculate the deadbeat reference voltage vector in the MT coordinate system: In the MT rotating coordinate system, the reference voltage components are calculated separately on the M and T axes using the decoupling characteristics of flux linkage and torque; For the M axis: The reference voltage of the M axis is linearly solved to control the stator flux linkage amplitude based on the error between the reference value and the predicted value of the flux linkage amplitude at the next moment; For the T axis: Based on the discretized torque equation, the non-dominant terms generated by the rotor flux linkage and current in the torque equation are ignored under the condition of ignoring the load angle, and a simplified linear relationship between the electromagnetic torque and the load angle is established. The reference voltage of the T axis is directly linearly solved to control the electromagnetic torque;

[0071] Step S5. Generate inverter switching signal to drive the motor: Transform the MT axis reference voltage component obtained in step S4 back to the stationary coordinate system. Considering the unique third harmonic interference of the five-phase motor, the adjacent four-vector SVPWM strategy is used to generate the inverter switching control signal to drive the five-phase permanent magnet fault-tolerant motor.

[0072] Furthermore, the specific steps for constructing the five-phase fault-tolerant motor model in the MT coordinate system in step S1 include:

[0073] Step S21: At time k, collect the five-phase stator current of the motor and obtain the current components in the stationary coordinate system through Clarke transformation. , ;

[0074] Step S22: Acquire DC bus voltage and the motor rotor position θ r (k) Using the stator flux component in the stationary coordinate system output by the hybrid flux observer in step S3. , The phase angle of the stator flux linkage vector is calculated using the arctangent function. The calculation formula is as follows:

[0075]

[0076] Step S23: Based on the stator flux linkage phase angle With rotor electrical angle Calculate the load angle at the current moment. :

[0077]

[0078] Step S24: Utilize the calculated stator flux linkage phase angle Construct a rotation transformation matrix to transform the current in the stationary coordinate system. , Transform to the MT rotating coordinate system with stator flux orientation to obtain the M-axis current. With T-axis current :

[0079]

[0080] Furthermore, the specific process of delay compensation in step S2 of the method is as follows: First step prediction: based on the sampled current at time k... and the voltage applied at the previous moment Predicting the current state at time k+1 based on the motor model The second step is to set the control objective: The control objective is set to eliminate the error at time k+2. The predicted values ​​are then used to determine the control objective. As input to the deadbeat controller, calculate the voltage vector that should be output at the current moment. This compensates for the control lag caused by the calculation delay of one beat.

[0081] Furthermore, the specific construction formula for the full-order Luneburg current observer described in step S2 is as follows: To address the parameter mismatch problem, the disturbance voltage caused by parameter errors is... As augmented state variables, a discretized observer model is constructed:

[0082]

[0083] In the formula, This is the estimated current value at the current moment. This is the current sample value at the current moment. This is the estimated value of the disturbance voltage at the current moment. For the controller output voltage, It is the back electromotive force. , These are the stator resistance and inductance, respectively. The sampling period; For current error feedback gain, This is the feedback gain for the disturbance error.

[0084] Furthermore, the hybrid flux observer described in step S3 is constructed by introducing a PI regulator into the flux correction voltage model obtained from the current model. The specific construction formula is as follows:

[0085]

[0086] in, The sampling period is For stator resistance, The controller output voltage at time k-1 The current sample value at time k-1, The compensation voltage term output by the PI regulator at time k is calculated using the following formula:

[0087]

[0088] In the formula, the error term The stator flux linkage vector estimated at the current moment; The reference value for flux linkage is calculated based on the current model; , These represent the proportional gain and integral gain of the hybrid observer, respectively.

[0089] Furthermore, the hybrid flux observer constructed in step S3 includes a current observer and a flux observer; its feedback gain parameter design and derivation method is as follows: configure the current observer parameters; establish the discrete error characteristic equation of the current observer and map it to the standard characteristic equation of a second-order system in the continuous domain. According to the system sampling period By selecting the observer bandwidth Damping ratio Calculate the gain using the pole placement method and This ensures the closed-loop poles lie within the unit circle; configure the flux linkage observer parameters: derive the transfer function of the hybrid flux linkage observer and compare its characteristic polynomial with the characteristic equation of a standard second-order system; based on the preset switching frequency... The relationship between the gain parameters is determined as follows: and The hybrid flux observer primarily uses a current model in the low-frequency band and a voltage model in the high-frequency band.

[0090] Furthermore, the process of solving the deadbeat reference voltage vector in step S4 is as follows: the voltage equation of the five-phase fault-tolerant motor is transformed into the MT coordinate system described in step S1 to obtain the discretized voltage equation:

[0091]

[0092] In the formula, , Let k be the reference voltage component at time k. , Let K be the reference current component at time k. For stator resistance, The sampling period is Let be the stator flux linkage amplitude at time k. Let $\frac{ ... This represents the load angle increment.

[0093] Using linear relationships, calculate the deadbeat reference voltage vector required to eliminate flux linkage error and torque error:

[0094]

[0095] In the formula, , To control the target value, , This is the observer's estimated value.

[0096] Furthermore, the linearization simplification logic for solving the reference voltage in step S4 is as follows: ignoring the load angle during the control cycle. Under the condition of ignoring non-dominant terms, a linear relationship between electromagnetic torque and load angle is established:

[0097]

[0098] In the formula, P is the pole logarithm. It is a permanent magnet flux chain. The stator inductance is used to deduce the torque increment at the next moment. With load angle increment Proportional;

[0099] This allows us to deduce the torque increment at the next moment. With load angle increment The voltage is proportional to the torque, and the reference voltage required to eliminate torque error is calculated accordingly.

[0100] The decoupling characteristic in step S4 specifically refers to: based on the linearization solution described in claim 2, the M-axis voltage component... Includes only flux linkage amplitude control term, T-axis voltage component It only includes torque control terms, thus achieving decoupling in the solution of control voltage, avoiding complex decoupling processes, and independently controlling torque and flux linkage; the overmodulation processing strategy specifically involves: through... Calculate the magnitude of the composite reference voltage vector ;when Exceeding the inverter's maximum output voltage When the system enters the overmodulation region, the controller output voltage is scaled proportionally, and the calculation formula is as follows:

[0101] .

[0102] Furthermore, the adjacent four-vector SVPWM strategy in step S5 is based on the distribution characteristics of the 32 spatial voltage vectors of the five-phase inverter, dividing the voltage space into 10 sectors. Within each sector, two adjacent large vectors and two medium vectors are selected as basic voltage vectors, and the large and medium vectors are synthesized according to a ratio of 0.618:0.312, so that the synthesized voltage vector of the third harmonic plane is zero, thus eliminating the influence of the third harmonic plane. The control algorithm is modularly built based on steps S1 to S5 of the present invention, including a coordinate transformation module, a full-order Luneburger observer module, a hybrid flux observer module, a linearized deadbeat controller module, and an SVPWM module.

[0103] Figure 8 A dynamic performance comparison chart of the control method of this invention and the traditional torque control method is presented. The simulation conditions are set as follows: the motor speed is 1000 r / min, and the given torque increases from 2 Nm to 3 Nm at t=0.2s. Due to the inherent one-step delay in the digital control system, the actual voltage vector lags behind the ideal value in the traditional method, resulting in a significant overshoot in the torque response, with an overshoot amplitude of approximately 0.3 Nm; and after entering steady state, there is a large high-frequency pulsation (torque pulsation amplitude of approximately 0.45 Nm, accounting for 15% of the torque after loading). This invention introduces a full-order Luneburger observer to accurately predict the current state at time k+1 and uses a two-step prediction method to compensate for the calculation delay. The motor loading dynamic response is extremely fast (response time is only about 30ms, which is 57% shorter than the 70ms of the traditional method), and there is no overshoot during loading. The current is smooth, and the flux jitter after loading is reduced from 0.0012Wb in the traditional method to 0.0009Wb, with a 25% reduction in fluctuation amplitude. The overall flux jitter is consistent with that in steady state, and it has excellent performance in dynamic conditions.

[0104] Figure 9Experimental comparisons of the control method of this invention and the traditional torque control method under inductor parameter mismatch are presented. The figures include torque, flux linkage, and voltage waveforms. With the controller parameters remaining constant, the inductor parameters vary from 1.0Ls to 0.5Ls to 1.8Ls to 1.0Ls. In the traditional method, torque ripple increases significantly when the inductance decreases; when the inductance increases, the voltage waveform is severely distorted, even leading to system oscillation and instability. This invention, by introducing a full-order observer, allows the system to estimate and compensate for parameter disturbances in real time. Under the same condition of drastic parameter changes, simulation verification shows that the output torque ripple is consistently controlled within 0.2 N·m, a 75% reduction compared to the traditional method. Transient shocks are effectively suppressed, no divergence occurs, the phase current sinusoidality remains good, and the controller output voltage is smooth and distortion-free. Experimental tests further demonstrate that the stator flux linkage amplitude is stable within the range of 0.03 Wb ± 0.0009 Wb, without divergence, the phase current sinusoidality remains good, and the controller output voltage is smooth and distortion-free. Therefore, this invention significantly improves the system's robustness to inductor parameter mismatch through the disturbance compensation effect of the full-order observer. Even with inductor parameter fluctuations of ±40%, the system can still maintain stable operation, and its steady-state accuracy and dynamic stability are superior to traditional control methods. Thus, by introducing the full-order observer, the system can estimate and compensate for parameter disturbances in real time. Under the same conditions of drastic parameter changes, the output torque remains smooth, transient shocks are effectively suppressed, and the stator flux linkage amplitude remains stable without divergence.

[0105] Figure 10 Experimental comparison graphs of the control method of this invention and the traditional torque control method under flux linkage parameter mismatch are presented. The graphs include torque, flux linkage, and voltage waveforms. With the controller parameters remaining constant, the flux linkage parameter changes from 1.0... -0.6 -1.4 -1.0 The variation range is within a certain range. Traditional methods, when reducing a portion of the flux linkage, result in increased torque ripple and unstable output voltage, causing a loss in system performance. However, the improved method proposed in this invention keeps the system in a stable state, reduces system glitches, stabilizes the output torque, and makes the controller output voltage smoother, ensuring stable operation.

[0106] Experimental verification:

[0107] To further verify the practical application effect of the method of the present invention, this embodiment constructs an experimental platform for a five-phase permanent magnet fault-tolerant motor based on optimized design. The motor adopts a 10-slot, 8-pole stator-rotor pole-slot configuration, combined with a fractional-slot concentrated winding structure. This winding structure effectively reduces end distance, lowers motor copper losses, and increases slot fill factor, thereby significantly increasing power density within the same volume. Simultaneously, this structure possesses a large harmonic inductance, improving inductance parameters while reducing inter-phase mutual inductance, achieving electromagnetic isolation between windings, and enhancing the motor's fault-tolerant operation capability. Regarding the rotor topology, the motor adopts a surface-mount permanent magnet (SPM) structure. This structure ensures a uniform distribution of air gap magnetic flux density between the stator and rotor, making the quadrature and direct-axis inductances approximately equal (…). This effectively suppresses armature reaction and enhances torque density by utilizing high air gap magnetic flux density. Furthermore, considering the characteristics of multi-phase fault-tolerant motors, this embodiment strengthens the electrical, magnetic, and thermal isolation between phases in its structural design, enhancing the ability to suppress short-circuit current and thus improving the safety of the drive system. In terms of material selection and key parameter design, this embodiment has undergone targeted optimization: samarium cobalt (SmCo30) is used for the permanent magnet to ensure excellent demagnetization resistance and thermal stability of the motor under extreme high-temperature conditions; 0.1mm thick T-100 silicon steel sheets are used for the core material, significantly reducing high-frequency iron losses compared to conventional DW310 material; electrical load parameters: current density is set at 7A / mm². 2 The conductors are selected as 0.9mm diameter round enameled wires, and the slot fill factor is designed to be 75%. The basic 3D design topology of the five-phase permanent magnet fault-tolerant motor is as follows: Figure 10 As shown, the stator structure is as follows Figure 11 As shown. The experimental platform also includes a 200V DC power supply, an RTU-BOX205 digital controller, a six-phase driver (integrated Hall current / voltage sensor), a rotary transformer, and a drag-load motor. Data was acquired via an oscilloscope and a host computer. The simulation and experimental test conditions were set to be consistent (switching frequency 10kHz, sampling period 100μs, dead time 2μs), and the motor parameters were consistent with the simulation (rated torque 4.7N·m, inductance 1.05mH, phase resistance 0.24Ω, main pole flux linkage 0.0305Wb). This verifies the effectiveness of the method proposed in this invention under actual working conditions. The experimental process is as follows:

[0108] Figure 12 The experimental results of verifying the steady-state performance of the digitally improved five-phase permanent magnet fault-tolerant motor are shown in the figure: given the motor at 500 r / min and a load torque of 1.8 N·m, when the motor is running in steady state, the electromagnetic torque pulsation of the motor is very small, which reflects the excellent steady-state performance of the system. At this time, the magnetic flux is stable at around 0.03 Wb, and the system noise is very small, which shows excellent steady-state performance.

[0109] Figure 13 , Figure 14 The experimental results of the dynamic performance of the digitally improved five-phase permanent magnet fault-tolerant motor are shown in the figure: When the motor load changes suddenly, the speed drops momentarily at the moment of loading, but it can quickly adjust back to the normal state. The torque pulsation is minimal. At this time, the motor torque loop is in a stable state, the given torque output by the speed loop is stable, the motor loading time is about 40ms, and the overshoot is very small. During the torque reduction process, the reduction process is about 60ms, and the motor torque will show some jitter, but it can quickly recover to a steady state, which has excellent dynamic performance.

[0110] Figure 15 , Figure 16 The experimental results of the parameter robustness verification of the digitally improved five-phase permanent magnet fault-tolerant motor are presented: Under the condition of constant 1 N·m and 500 rpm, the motor parameter mismatch is simulated by modifying the controller parameters: Figure 15 The graph shows the torque and controller voltage response as the flux linkage parameters decrease from normal to decreasing. Figure 16 The graph shows the torque and controller voltage response as the flux linkage parameter increases from normal to 1.4 times. At this point, the system exhibits minimal torque ripple and stable controller output voltage. Increasing or decreasing the flux linkage gain maintains stable output voltage, demonstrating the system's strong robustness. Furthermore, simulations of inductance and resistance mismatches were also verified, with the system operating stably in all cases, illustrating the robustness of the digitally improved five-phase permanent magnet fault-tolerant motor.

[0111] Figure 17 , Figure 18 The experimental results of verifying the fault-tolerant performance of the digitally improved five-phase permanent magnet fault-tolerant motor are presented: Under steady-state operating conditions of 500 r / min and 1 N·m load, manually disconnecting the A-phase air switch to simulate a single-phase open circuit resulted in automatic current compensation for the remaining four phases. The speed did not drop significantly, and although the torque pulsation increased slightly, it did not exceed 0.3 N·m. The system did not experience step loss or stalling. Figure 17 When the motor's AB windings are short-circuited, the short-circuit current between phases AB increases rapidly after a short-circuit fault occurs, remaining at approximately twice the rated value, and the motor does not stall. Figure 18 Experimental results show that the digitally improved five-phase permanent magnet fault-tolerant motor has excellent single-phase fault-tolerant operation capability and short-circuit current suppression capability.

[0112] The experimental results are consistent with the simulation results, proving that the method of the present invention has excellent steady-state accuracy, dynamic response and parameter robustness in actual working conditions, and meets the high reliability drive requirements of a five-phase permanent magnet fault-tolerant motor.

[0113] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A digital implementation method for improved deadbeat torque control of a high-reliability motor, characterized in that, Includes the following steps: Step S1. Construct the MT coordinate system: Define the direction of the stator flux linkage vector as the M-axis, and the direction leading the M-axis by 90 electrical degrees as the T-axis; collect the stator current, DC bus voltage, and rotor angle signals of the five-phase motor, and calculate the stator flux linkage amplitude ψ. s and the stator angle θ of the motor s The motor equations are transformed into the MT coordinate system to construct a five-phase fault-tolerant motor model, where the MT coordinate system is the stator flux linkage coordinate system. Step S2. Construct a full-order Luenberger current observer for delay compensation and state prediction: Establish a discretized state equation for the motor containing parameter disturbance terms, and construct a full-order Luenberger current observer; use the control quantity and measurement quantity at the current time k to predict the five-phase stator current at time k+1, and observe the system disturbance voltage; the full-order Luenberger current observer introduces a feedback gain matrix to correct the prediction error, wherein the parameters of the feedback gain matrix are determined by the pole placement method; Step S3. Construct a hybrid flux observer to calculate the stator flux angle and amplitude: Construct a hybrid flux observer based on the voltage model and the current model; use the corrected five-phase current model in step S2 to perform closed-loop compensation on the voltage model, correct the integral drift of the voltage model through a PI regulator, and output accurate stator flux amplitude and phase angle for real-time orientation of the MT axis coordinate system; Step S4. Calculate the deadbeat reference voltage vector in the MT coordinate system: In the MT rotating coordinate system, the reference voltage components are calculated separately on the M and T axes using the decoupling characteristics of flux linkage and torque; For the M axis: The reference voltage of the M axis is linearly solved to control the stator flux linkage amplitude based on the error between the reference value and the predicted value of the flux linkage amplitude at the next moment; For the T axis: Based on the discretized torque equation, the non-dominant terms generated by the rotor flux linkage and current in the torque equation are ignored under the condition of ignoring the load angle, and a simplified linear relationship between the electromagnetic torque and the load angle is established. The reference voltage of the T axis is directly linearly solved to control the electromagnetic torque; Step S5. Generate inverter switching signal to drive the motor: Transform the MT axis reference voltage component obtained in step S4 back to the stationary coordinate system. Considering the unique third harmonic interference of the five-phase motor, the adjacent four-vector SVPWM strategy is used to generate the inverter switching control signal to drive the five-phase permanent magnet fault-tolerant motor.

2. The method for digitally implementing improved deadbeat torque control of a high-reliability motor according to claim 1, characterized in that, The specific steps for constructing the five-phase fault-tolerant motor model in the MT coordinate system in step S1 include: Step S21: At time k, collect the five-phase stator current of the motor and obtain the current components in the stationary coordinate system through Clarke transformation. , ; Step S22: Acquire DC bus voltage and the motor rotor position θ r (k) Using the stator flux component in the stationary coordinate system output by the hybrid flux observer in step S3. , The phase angle of the stator flux linkage vector is calculated using the arctangent function. The calculation formula is as follows: Step S23: Based on the stator flux linkage phase angle With rotor electrical angle Calculate the load angle at the current moment. : Step S24: Utilize the calculated stator flux linkage phase angle Construct a rotation transformation matrix to transform the current in the stationary coordinate system. , Transform to the MT rotating coordinate system with stator flux orientation to obtain the M-axis current. With T-axis current : 。 3. The method for digitally implementing improved deadbeat torque control of a high-reliability motor according to claim 1, characterized in that, The specific process of delay compensation in step S2 of the method is as follows: Step 1: Prediction: Based on the sampled current at time k... and the voltage applied at the previous moment Predicting the current state at time k+1 based on the motor model The second step is to set the control objective: The control objective is set to eliminate the error at time k+2. The predicted values ​​are then used to determine the control objective. As input to the deadbeat controller, calculate the voltage vector that should be output at the current moment. This compensates for the control lag caused by the calculation delay of one beat.

4. The improved deadbeat torque control digital implementation method for a five-phase permanent magnet fault-tolerant motor according to claim 1, characterized in that, The specific construction formula for the full-order Luneburg current observer described in step S2 is as follows: To address the parameter mismatch problem, the disturbance voltage caused by parameter errors is... As augmented state variables, a discretized observer model is constructed: In the formula, This is the estimated current value at the current moment. This is the current sample value at the current moment. This is the estimated value of the disturbance voltage at the current moment. For the controller output voltage, It is the back electromotive force. , These are the stator resistance and inductance, respectively. The sampling period; For current error feedback gain, This is the feedback gain for the disturbance error.

5. The improved deadbeat torque control digital implementation method for a five-phase permanent magnet fault-tolerant motor according to claim 1, characterized in that, The hybrid flux observer described in step S3 is constructed by introducing a PI regulator into the flux correction voltage model obtained from the current model. The specific construction formula is as follows: in, The sampling period is For stator resistance, The controller output voltage at time k-1 The current sample value at time k-1, The compensation voltage term output by the PI regulator at time k is calculated using the following formula: In the formula, the error term The stator flux linkage vector estimated at the current moment; The reference value for flux linkage is calculated based on the current model; , These represent the proportional gain and integral gain of the hybrid observer, respectively.

6. The improved deadbeat torque control digital implementation method for a five-phase permanent magnet fault-tolerant motor according to claim 1, characterized in that, The hybrid flux observer constructed in step S3 includes a current observer and a flux observer; its feedback gain parameter design and derivation method is as follows: configure the current observer parameters; establish the discrete error characteristic equation of the current observer and map it to the standard characteristic equation of a second-order system in the continuous domain. According to the system sampling period By selecting the observer bandwidth Damping ratio Calculate the gain using the pole placement method and This ensures that the closed-loop poles are located inside the unit circle; configure the flux linkage observer parameters: derive the transfer function of the hybrid flux linkage observer and compare its characteristic polynomial with the characteristic equation of a standard second-order system; According to the preset switching frequency The relationship between the gain parameters is determined as follows: and The hybrid flux observer primarily uses a current model in the low-frequency band and a voltage model in the high-frequency band.

7. The method for digitally implementing improved deadbeat torque control of a high-reliability motor according to claim 1, characterized in that, The specific process for solving the deadbeat reference voltage vector in step S4 is as follows: the voltage equation of the five-phase fault-tolerant motor is transformed into the MT coordinate system described in step S1 to obtain the discretized voltage equation: In the formula, , Let k be the reference voltage component at time k. , Let K be the reference current component at time k. For stator resistance, The sampling period is Let be the stator flux linkage amplitude at time k. Let $\frac{ ... This represents the load angle increment. Using linear relationships, calculate the deadbeat reference voltage vector required to eliminate flux linkage error and torque error: In the formula, , To control the target value, , This is the observer's estimated value.

8. The method for digitally implementing improved deadbeat torque control of a high-reliability motor according to claim 1, characterized in that, The linearization simplification logic for solving the reference voltage in step S4 is as follows: ignoring the load angle during the control cycle. Under the condition of ignoring non-dominant terms, a linear relationship between electromagnetic torque and load angle is established: In the formula, P is the pole logarithm. It is a permanent magnet flux chain. The stator inductance is used to deduce the torque increment at the next moment. With load angle increment Proportional; This allows us to deduce the torque increment at the next moment. With load angle increment The voltage is proportional to the torque, and the reference voltage required to eliminate torque error is calculated accordingly.

9. The improved deadbeat torque control digital implementation method for a five-phase permanent magnet fault-tolerant motor according to claim 1, characterized in that, The decoupling characteristic in step S4 specifically refers to: based on the linearization solution described in claim 2, the M-axis voltage component... Includes only flux linkage amplitude control term, T-axis voltage component It only includes torque control terms, thus achieving decoupling in the solution of control voltage, avoiding complex decoupling processes, and independently controlling torque and flux linkage; the overmodulation processing strategy specifically involves: through... Calculate the magnitude of the composite reference voltage vector ;when Exceeding the inverter's maximum output voltage When the system enters the overmodulation region, the controller output voltage is scaled proportionally, and the calculation formula is as follows: 。 10. The improved deadbeat torque control digital implementation method for a five-phase permanent magnet fault-tolerant motor according to claim 1, characterized in that, The adjacent four-vector SVPWM strategy in step S5 is based on the distribution characteristics of 32 spatial voltage vectors of the five-phase inverter. The voltage space is divided into 10 sectors. In each sector, two adjacent large vectors and two medium vectors are selected as basic voltage vectors. The large and medium vectors are synthesized according to 0.618:0.312 so that the synthesized voltage vector of the third harmonic plane is zero, thus eliminating the influence of the third harmonic plane.

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