DC-biased Vernier motor deadbeat predictive current control method and system

Abstract

This invention relates to the field of motor drive and control, and provides a deadbeat predictive current control method and system for a DC biased vernier reluctance motor. The method includes: acquiring the operating data of the target motor and preprocessing the acquired operating data; inputting the preprocessed operating data into an extended state observer with coupling compensation, and outputting extended state prediction parameters; inputting the extended state prediction parameters into a deadbeat predictive current control model to obtain the regulating voltage of the dq0 axis; performing coordinate transformation on the regulating voltage of the dq0 axis and performing space vector pulse width modulation to obtain a dual-inverter SVPWM modulated switching sequence; and applying the switching sequence to the phase windings of the target motor. This invention considers voltage coupling-induced disturbances during the prediction of current and disturbances; this allows for compensation of voltage coupling interference, thereby mitigating the impact of interference caused by parameter changes and coupling voltage, and enhancing dynamic response capability.

Description

Technical Field

[0001] This invention belongs to the field of motor drive and control, and provides a method and system for predictive current control of DC biased vernier reluctance motor without deadbeat. Background Technology

[0002] Open-winding motor systems, or simply open-winding motors, have garnered increasing attention and research from academia and industry due to their advantages such as flexible control, high voltage utilization, high fault tolerance, and low power device capacity requirements. The DC-biased vernier reluctance motor is a novel type of motor system employing an open-winding structure. Its armature current is a superposition of a DC bias component and a sinusoidal component. The motor structure can be referenced... Figure 1 This motor system boasts excellent speed regulation performance, high control precision, simple manufacturing process, convenient heat dissipation, and high reliability. It has broad application prospects in harsh environments such as aviation starters / generators, mining machinery, and automotive turbocharger motors, where high speed regulation performance and reliability are required.

[0003] Aircraft starters / generators are core components of the electrical systems of multi-electric aircraft. The harsh location and high temperatures of the internal starter / generator place higher demands on its reliability. Meanwhile, how to control the starting and power generation processes of the starter / generator to achieve high real-time performance and stable control has also received widespread attention in recent years.

[0004] In terms of motor control strategy optimization, PI controllers have been used for dq0 axis current control in DC-biased-VRMs (DC bias voltage regulator modules), but their dynamic response is sluggish. Deadbeat predictive current control (DPCC) strategies perform well in permanent magnet synchronous motor drive systems with excellent dynamic performance, but their performance in DC-biased-VRM applications is limited by the accuracy of motor parameters. In actual operation, motor parameters are prone to variation, significantly reducing the effectiveness of DPCC control. Therefore, academic research has been conducted, with some methods expanding the prediction range, introducing control strategies, or using observers to improve DPCC performance. However, existing DPCC strategies for open-winding permanent magnet synchronous motors do not consider the zero-sequence current regulation and current coupling characteristics of DC-biased-VRMs, making direct application difficult.

[0005] Currently, DPCC strategies based on conventional ESO (Extended State Observer) typically discretize the motor voltage equations and predict the current for the next cycle based on the sampled dq0 axis current of the current control cycle and motor parameters. To enhance DPCC immunity and mitigate the impact of parameter changes, an Extended State Observer (ESO) is designed to detect and compensate for disturbances caused by parameter variations. Specifically, an ESO is designed based on the discretized formulas and motor equations. After obtaining the predicted current and disturbances, the DPCC strategy is optimized, enabling the regulated voltage to accurately adjust the current to track the reference value, achieving the control objective, and possessing zero-sequence current regulation capability.

[0006] However, the parameters of the DC-biased-VRM change significantly during actual operation. For example, the static and AC inductive components fluctuate with the effective value of the current, and the phase resistance changes with ambient temperature. These parameter variations increase the predicted current error, cause inaccurate voltage regulation, deteriorate the control effect, and even lead to system instability, severely weakening the DPCC strategy's ability to accurately control the motor current. Furthermore, the motor's dq0-axis voltage and current are interrelated. Traditional DPCC strategies derive the predicted current and calculate the regulating voltage based on instantaneous current, ignoring inter-axis coupling. This deficiency causes dynamic disturbances to the predicted current and regulating voltage, further reducing control performance when parameters change, causing severe phase current fluctuations, increasing system losses, shortening the lifespan of power electronic devices, and affecting the motor's operational stability and efficiency; therefore, improvement is necessary. Summary of the Invention

[0007] The purpose of this invention is to provide a deadbeat predictive current control method and system for a DC-biased vernier reluctance motor, which enables real-time adjustment of zero-sequence voltage, ensures the regulation capability of zero-sequence current, and improves the dynamic response and anti-interference capability of the control system; it provides an effective solution for improving the efficiency of DC-biased vernier reluctance motor (DC-biased-VRM) drive systems.

[0008] This invention is implemented as follows: a method for predictive current control of a DC biased vernier reluctance motor without deadbeat, the method comprising the following steps:

[0009] The operating data of the target motor is acquired and preprocessed; the operating data includes the given electrical angular velocity of the motor. Rotor current electric speed θ e (k) Current i of the three-phase winding abc (k) and voltage u abc (k);

[0010] The preprocessed running data is input into the extended state observer with coupling compensation, and the extended state prediction parameters are output. The extended state prediction parameters include the predicted current for the next control cycle and the disturbance voltage considering the coupling and parameter changes of the dq0 axis.

[0011] The extended state prediction parameters are input into the deadbeat prediction current control model to obtain the adjustment voltage of the dq0 axis;

[0012] The adjustment voltage of the dq0 axis is subjected to coordinate transformation and space vector pulse width modulation to obtain the switching sequence of dual inverter SVPWM modulation.

[0013] The switching sequence is applied to the phase windings of the target motor to control the current of phases A, B, and C of the motor windings, so as to achieve deadbeat predictive current control.

[0014] This invention provides a deadbeat predictive current control system for a DC biased vernier reluctance motor, the system comprising:

[0015] The data acquisition module is used to acquire the operating data of the target motor and preprocess the acquired operating data; the operating data includes the given electrical angular velocity of the motor. Rotor current electric speed θ e (k) Current i of the three-phase winding abc (k) and voltage u abc (k);

[0016] The model running module is used to input the preprocessed running data into the extended state observer with coupling compensation and output extended state prediction parameters. These extended state prediction parameters include the predicted current for the next control cycle and the disturbance voltage considering the coupling and parameter changes of the dq0 axis.

[0017] The algorithm execution module is used to input the extended state prediction parameters into the deadbeat prediction current control model to obtain the adjustment voltage of the dq0 axis;

[0018] The signal conversion and modulation module is used to perform coordinate transformation on the adjustment voltage of the dq0 axis and perform space vector pulse width modulation to obtain the switching sequence of dual inverter SVPWM modulation.

[0019] The pulse signal input module is used to apply the switching sequence to the phase windings of the target motor to control the current of phases A, B, and C of the motor windings, so as to achieve deadbeat predictive current control.

[0020] This invention provides a deadbeat predictive current control method for a DC-biased vernier reluctance motor. It introduces an improved extended state observer with coupling compensation and a deadbeat predictive current control model. During the prediction of current and disturbances, it considers disturbances caused by voltage coupling. This allows for compensation of voltage coupling interference, thereby mitigating the impact of interference caused by parameter variations and coupling voltage, and further enhancing dynamic response capabilities. Compared to traditional ESO-based DPCC methods that do not consider coupling phenomena, this control method has faster current regulation capabilities; furthermore, the current regulation process is smoother, with less interference, improving current utilization and reducing the impact of current surges on power electronic devices. Attached Figure Description

[0021] Figure 1 This is a schematic diagram of the stator and rotor structure of a DC-biased vernier reluctance motor provided in an embodiment of the present invention;

[0022] Figure 2 This is a winding connection diagram in an open-winding motor system according to one embodiment;

[0023] Figure 3 This is a topology of an open-winding motor system in one embodiment;

[0024] Figure 4 This is a control block diagram of a deadbeat predictive current control method for a DC biased vernier reluctance motor provided in an embodiment of the present invention;

[0025] Figure 5 A flowchart illustrating a deadbeat predictive current control method for a DC biased vernier reluctance motor provided in an embodiment of the present invention;

[0026] Figure 6 This is a structural block diagram of a deadbeat predictive current control system for a DC biased vernier reluctance motor provided in an embodiment of the present invention. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0028] Explanation of the name:

[0029] PWM: Pulse Width Modulation;

[0030] SVPWM: Space Vector Pulse Width Modulation;

[0031] ESO: Extended State Observer;

[0032] DPCC: Deadbeat Predictive Current Control.

[0033] like Figures 1 to 5 As shown, in one embodiment, a deadbeat predictive current control method for a DC-biased vernier reluctance motor is proposed, which can be used for, for example... Figure 1 The diagram shows the structure of a DC-biased vernier reluctance motor; the control principle of this method can be found in [reference needed]. Figure 4 ; Figure 5 This is a flowchart of a method for predictive current control of a DC biased vernier reluctance motor without deadbeat, which may specifically include the following steps S101 to S105.

[0034] S101: Acquire the operating data of the target motor and preprocess the acquired operating data; wherein, the operating data includes the given electrical angular velocity of the motor. Rotor current electric speed θ e (k) Current i of the three-phase winding abc (k) and voltage u abc (k);

[0035] In this step, the target motor is specifically a DC-biased vernier reluctance motor, powered and driven by an open-winding inverter. The open-winding inverter comprises two inverters, namely inverter 1 and inverter 2, connected to the same DC bus, as shown in the reference. Figure 3 The voltage vector of the open-winding inverter is obtained by synthesizing the output voltage vectors of the two inverters (inverter 1 and inverter 2).

[0036] For example, acquiring the operating data of the target motor and preprocessing the acquired operating data specifically includes:

[0037] Obtain the given electrical angular velocity of the target motor Rotor current electrical angle θ e (k);

[0038] Based on the current electrical angle θ of the rotor e (k) Determine the current electric angular velocity w of the rotor e (k), and the given electric angular velocity of the motor. After multiplication, the result is used as the input to the PI controller, which outputs the dq0-axis current setpoint.

[0039] Obtain the current i of the three-phase windings of the target motor abc (k) and voltage u abc (k);

[0040] The coordinates of the current and voltage of the three-phase windings are transformed to obtain the dq0-axis current feedback value i. dq0 (k), dq0 axis voltage feedback value u dq0 (k).

[0041] S102: Input the preprocessed running data into the extended state observer with coupling compensation, and output the extended state prediction parameters; the extended state prediction parameters include the predicted current for the next control cycle and the disturbance voltage considering the coupling and parameter changes of the dq0 axis.

[0042] The extended state observer with coupling compensation is configured as follows:

[0043]

[0044] Where k represents time, h x (k)(x=d,q,0) represents the disturbance voltage with coupling compensation and parameter variation at time k, h x (k+1)(x=d,q,0) represents the disturbance voltage with coupling compensation and parameter variation at the predicted time (k+1); Representing the predicted dq0-axis current, i d (k), i q (k) and i0(k) are i dq0 (k) components; u d (k), u q (k) and u0(k) are u dq0 (k) components; T S It is the control cycle, R is the phase resistance, and D is the differential operator;

[0045]

[0046] Where L0 represents zero-sequence inductance, L1 represents AC inductance, and c1d, c2d, c1q, c2q, c10, and c20 are parameters of the extended state observer with coupling compensation.

[0047] S103: Input the extended state prediction parameters into the deadbeat predictive current control model to obtain the adjustment voltage of the dq0 axis, i.e., u. * d (k), u * q (k) and u * 0(k);

[0048] Among them, the deadbeat predictive current control model is configured as follows:

[0049]

[0050] Among them, i dref i qref i 0ref Indicates the reference values ​​for the d-axis, q-axis, and 0-axis currents; u * x (k+1)(x=d,q,0) represents the adjustment voltage for the next control cycle, i.e., u * d (k+1), u * q (k+1) and u * 0(k+1).

[0051] S104: Perform coordinate transformation on the adjustment voltage of the dq0 axis and perform space vector pulse width modulation to obtain the switching sequence of dual inverter SVPWM modulation;

[0052] S105: Apply the switching sequence to the phase windings of the target motor to control the current of phases A, B, and C of the motor windings, so as to achieve deadbeat predictive current control.

[0053] In step S102, for the target motor, since the DC-biased vernier reluctance motor allows zero-sequence current to flow, the current in the winding can be expressed as:

[0054]

[0055] In the target motor, the inductance mainly consists of a DC component and a primary AC component. The amplitude changes of other components are too small, even negligible, and can therefore be ignored. Therefore, the phase inductance is expressed as equation (2).

[0056] Combining equations (1) and (2), the voltage equation can be expressed as equation (3).

[0057]

[0058] Among them, L s This represents the stator inductance of the motor; L1 represents the AC inductance; L0 represents the zero-sequence inductance; R S θ represents the stator resistance; e ω represents the electrical angle of the motor; e L represents electric angular velocity. a L b L c The abc-axis coordinate system represents the three-phase inductance of a motor. It is a three-phase stationary coordinate system where the a, b, and c axes are 120° electrical degrees out of phase, representing the three phases of the motor (usually phase A, phase B, and phase C). The voltage, current, and other electrical quantities of each phase winding can be represented on its respective axis. For example, the current in the three-phase stator windings of the motor can be expressed as i... a i bi c Voltage can be expressed as u a u b u c The dq0-axis coordinate system is a three-phase rotating coordinate system; the d, q, and 0 axes are 120° electrical degrees out of phase with each other; the winding current can be expressed as i d i q i0; voltage can be expressed as u d u q 、u0.

[0059] Alternating current generates stator flux, while direct current generates virtual rotor flux. The interaction between the stator and rotor fluxes produces electromagnetic torque, driving the motor. The average electromagnetic torque in a DC-biased vernier reluctance motor is related to i... q The product of i0 and i0 is proportional; if the sampling time is too short, then equation (3) can be discretized and rewritten as equation (4);

[0060]

[0061] In equation (4), i d (k), i q (k) and i0(k) represent the sampled current of the dq0 axis in the current control cycle, respectively. Then, the current of the dq0 axis in the next control cycle is predicted based on the motor operating parameters. Because the control cycle is very short, the electric angular velocity ω between two consecutive cycles e It can be considered to remain constant.

[0062] For example, in the step of predicting the current of the dq0 axis in the next control cycle based on the motor operating parameters, the predicted value of the current control cycle is used as the reference current for the subsequent control cycle; ensuring that the feedback current of the motor follows its corresponding reference value; based on this, the regulating voltage for the next control cycle can be calculated according to the voltage of the current control cycle; this regulating voltage is implemented on the dual-winding inverter at the beginning of each control cycle, thereby enabling precise current regulation so that the desired value is reached at the end of the cycle. The regulating voltage can be obtained according to equation (5);

[0063]

[0064] Among them, i dref i qref i 0ref Indicates the reference values ​​for the d-axis, q-axis, and 0-axis currents; u * x (k+1)(x=d,q,0) represents the adjustment voltage for the next control cycle.

[0065] In this embodiment, the extended state observer with coupling compensation is obtained by improving an extended state observer;

[0066] The discretization formula for the extended state observer is as follows:

[0067]

[0068] Among them, f d (k), f q f(k) and f0(k) represent the dq0-axis current disturbance, respectively; while f d (k+1), f q (k+1) and f0(k+1) represent the predicted dq0-axis current perturbation, respectively; T S Indicates the control period; c1 and c2 are parameters of the extended state observer, e rr (k) represents the current error. The extended state observer can help motor servo control minimize the impact of parameter changes and improve the robustness of deadbeat predictive current control (DPCC) to disturbances.

[0069] According to equations (4) and (6), the extended state observer can be expressed as follows:

[0070]

[0071] Thus, predicted currents and current disturbances can be obtained by extending the state observer.

[0072] Equation (5) can be rewritten as Equation (9);

[0073]

[0074] In the practical application of this embodiment, ambient temperature fluctuations are unavoidable, causing the phase resistance of the motor to change accordingly with temperature variations; furthermore, both the static inductance component and the AC inductance component exhibit a response to the RMS current (IS). rms ) changes.

[0075] The changes in the static inductance component and the AC inductance component are represented by ΔL0 and ΔL1, respectively, and the change in phase resistance is represented by ΔR. Therefore, the predicted current error caused by these changes in motor parameters can be expressed as Equation (10), and by combining Equation (4), Equation (11) is obtained.

[0076] As shown in equation (11), the predicted current with parameter variations can be derived. The predicted current disturbance caused by the parameter variation at time k is expressed as i fd (k), i fq (k) and i f0(k). It is clear that changes in motor parameters will impair the accuracy of current prediction, lead to errors in voltage regulation, ultimately affect control performance and potentially cause instability in the motor system.

[0077]

[0078]

[0079] Furthermore, it is evident from equation (3) that the voltage on the d0 axis is related to the current on the d0 axis. This means that the accuracy of the current prediction on the d0 axis directly affects the accuracy of the regulating voltage on the dq0 axis, thereby affecting the control efficiency. However, as shown in equations (4) and (7), the traditional DPCC strategy uses instantaneous current instead of its derivative to derive the predicted current. Similarly, in equations (5) and (9), the predicted current is used instead of the derivative of the predicted current. This direct substitution method ignores the coupling phenomenon on the dq0 axis, inevitably leading to dynamic disturbances in the predicted current and regulating voltage, and ultimately affecting the dynamic performance of the control strategy. In addition, changes in motor parameters further reduce control performance, and this coupling phenomenon exacerbates the impact on control performance. Therefore, in this embodiment, the extended state observer with coupling compensation is an extended state observer that considers voltage coupling on the dq0 axis. The coupling situation and parameter changes on the dq0 axis are extended into disturbance quantities and observed; ultimately, disturbance compensation is achieved, improving the dynamic performance of the control method.

[0080] For example, equation (3) can be rewritten as follows:

[0081]

[0082] in,

[0083] Furthermore, equation (12) is rewritten as equation (13);

[0084]

[0085] in, E is the identity matrix, h d h q h0 and h0 represent the disturbance voltages considering the coupling of the dq0 axis and the parameter changes, respectively.

[0086] According to equation (13), the extended state observer with coupling compensation can be expressed as equation (14)-(15).

[0087] The voltage adjustment can be expressed as equation (16).

[0088]

[0089] The aforementioned extended state observer with coupling compensation compensates for control delay by predicting instantaneous current and disturbance voltage. Simultaneously, it reduces the impact of voltage coupling and parameter disturbances, ensuring fast response and stability of motor control.

[0090] In step S104, the adjustment voltage of the dq0 axis is subjected to coordinate transformation and space vector pulse width modulation to obtain the switching sequence of dual inverter SVPWM modulation.

[0091] The coordinate transformation is achieved through a rotary-stationary coordinate transformer (dq / αβ), used to adjust the voltage u along the d-axis. d * (k), q-axis adjustment voltage u q * (k) is transformed into the corresponding coordinate value u in the two-phase stationary coordinate system. ɑ * u β * Specifically, it is divided into coordinate values ​​(u) α1 *(k), u β1 *(k)) and (u α2 *(k), u β2 *(k)) is fed into two space vector pulse width modulators (i.e., Figure 4 SVPWM1 and SVPWM2 in the dual inverter are used to perform space vector pulse width modulation to obtain the switching sequence of SVPWM modulation for the dual inverter (i.e., PWM 1-6, PWM 7-12).

[0092] Then, the switching sequence is applied to the phase windings of the target motor to control the current of phases A, B, and C of the motor windings, so as to achieve deadbeat predictive current control.

[0093] For example, determine a given voltage vector u αβ * In the sector where the coordinate values ​​are located in the two-phase stationary coordinate system, the distribution relationship between the independent output voltage vectors of the two inverters is determined, and the two adjacent effective working vectors and corresponding action times of the two inverters are obtained according to the distribution results. Then, the dual inverter PWM modulation is performed according to the alternating clamping PWM strategy.

[0094] Among them, the voltage vector u can be determined. αβ * In the sector containing the coordinate values ​​in the two-phase stationary coordinate system, determine the distribution relationship between the independent output voltage vectors of the two inverters; specifically including:

[0095] Voltage vector u αβ * The coordinates in the two-phase stationary coordinate system are (u α *u β * ), through (u α * u β * Determine u αβ * The sector in question determines the distribution relationship between the independent output voltage vectors of the two inverters, which are u... αβ1 * u αβ2 * ;

[0096] via (u α1 * u β1 * ) and (u α2 * u β2 * This yields the two adjacent operating vectors of the two inverters and their corresponding operating times;

[0097] Among them, (u α1 * u β1 * ) and (u α2 * u β2 * ) by u αβ1 * u αβ2 * Sure.

[0098] This embodiment provides a deadbeat predictive current control method for a DC-biased vernier reluctance motor. In the process of predicting current and disturbances, it considers disturbances caused by voltage coupling; it allows compensation for voltage coupling interference, thereby mitigating the impact of interference caused by parameter changes and coupling voltage, and further enhancing dynamic response capability. Compared with traditional ESO-based DPCC methods that do not consider coupling phenomena, the control method of this embodiment has faster current regulation capability; in addition, the regulation process is smoother, with less interference, and improved current utilization.

[0099] like Figure 6 As shown, in another embodiment, a deadbeat predictive current control system 100 for a DC biased vernier reluctance motor includes:

[0100] The data acquisition module 110 is used to acquire the operating data of the target motor and preprocess the acquired operating data; wherein, the operating data includes the given electrical angular velocity of the motor. Rotor current electric speed θ e (k) Current i of the three-phase windingabc (k) and voltage u abc (k);

[0101] The model running module 120 is used to input the preprocessed running data into the extended state observer with coupling compensation and output extended state prediction parameters; the extended state prediction parameters include the predicted current for the next control cycle and the disturbance voltage considering the coupling and parameter changes of the dq0 axis.

[0102] Algorithm execution module 130 is used to input the extended state prediction parameters into the deadbeat prediction current control model to obtain the adjustment voltage of the dq0 axis;

[0103] The signal conversion and modulation module 140 is used to perform coordinate transformation on the adjustment voltage of the dq0 axis and perform space vector pulse width modulation to obtain a dual inverter SVPWM modulation switching sequence.

[0104] The pulse signal input module 150 is used to apply the switching sequence to the phase windings of the target motor to control the current of phases A, B, and C of the motor windings, so as to achieve deadbeat predictive current control.

[0105] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0106] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

[0107] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for predictive current control of a DC biased vernier reluctance motor without deadbeat, characterized in that, The method includes: The operating data of the target motor is acquired and preprocessed; the operating data includes the given electrical angular velocity of the motor. Current electric speed of rotor Current in the three-phase winding and voltage ; The preprocessed running data is input into the extended state observer with coupling compensation, and the extended state prediction parameters are output. The extended state prediction parameters include the predicted current for the next control cycle and the disturbance voltage considering the coupling and parameter changes of the dq0 axis. The extended state prediction parameters are input into the deadbeat prediction current control model to obtain the adjustment voltage of the dq0 axis; The adjustment voltage of the dq0 axis is subjected to coordinate transformation and space vector pulse width modulation to obtain the switching sequence of dual inverter SVPWM modulation. The switching sequence is applied to the phase windings of the target motor to control the current of phases A, B, and C of the motor windings, so as to achieve deadbeat predictive current control.

2. The method for predictive current control of a DC biased vernier reluctance motor without deadbeat according to claim 1, characterized in that, The steps of acquiring the operating data of the target motor and preprocessing the acquired operating data specifically include: Obtain the given electrical angular velocity of the target motor Rotor current electrical angle ; Based on the current electrical angle of the rotor Determine the current electric angular velocity of the rotor and the given electric angular velocity of the motor The result of the subtraction operation is used as the input to the PI controller, which outputs the dq0-axis current setpoint. ; Obtain the current of the three-phase windings of the target motor and voltage ; The coordinates of the current and voltage of the three-phase windings are transformed to obtain the dq0-axis current feedback value. dq0 axis voltage feedback value .

3. The method for predictive current control of a DC biased vernier reluctance motor without deadbeat according to claim 2, characterized in that, In the step of inputting the preprocessed running data into the coupled-compensated extended state observer and outputting the extended state prediction parameters, the coupled-compensated extended state observer is configured as follows: ； ； Where k represents time, h x (k) represents the disturbance voltage with coupling compensation and parameter variation at time k, h x (k+1) represents the disturbance voltage with coupling compensation and parameter variation at the predicted time (k+1), x=d,q,0; , , Representing the predicted dq0-axis current, i d (k), i q (k) and i0(k) are The component; u d (k), u q (k) and u0(k) are The component of T; S It is the control cycle, and R is the phase resistance; ， ； Where L0 represents zero-sequence inductance, L1 represents AC inductance, and c1d, c2d, c1q, c2q, c10, and c20 are parameters of the extended state observer with coupling compensation.

4. The deadbeat predictive current control method for a DC biased vernier reluctance motor according to claim 3, characterized in that, The deadbeat predictive current control model is configured as follows: ； wherein, i dref , i qref , i 0ref represent the d-axis, q-axis, 0-axis current reference values; u * x (k+1) represents the adjustment voltage of the next control period; in the step of predicting the current of the d-q-0 axis of the next control period according to the motor operating parameters, the predicted value of the current control period is used as the reference current of the subsequent control period; to ensure that the feedback current of the motor follows its corresponding reference value.

5. A deadbeat predictive current control system for a DC-biased vernier reluctance motor, used in the deadbeat predictive current control method for a DC-biased vernier reluctance motor as described in any one of claims 1-4, characterized in that, The deadbeat predictive current control system for the DC bias vernier reluctance motor includes: The data acquisition module is used to acquire the operating data of the target motor and preprocess the acquired operating data; the operating data includes the given electrical angular velocity of the motor. Current electric speed of rotor Current in the three-phase winding and voltage ; The model running module is used to input the preprocessed running data into the extended state observer with coupling compensation and output extended state prediction parameters. These extended state prediction parameters include the predicted current for the next control cycle and the disturbance voltage considering the coupling and parameter changes of the dq0 axis. The algorithm execution module is used to input the extended state prediction parameters into the deadbeat prediction current control model to obtain the adjustment voltage of the dq0 axis; The signal conversion and modulation module is used to perform coordinate transformation on the adjustment voltage of the dq0 axis and perform space vector pulse width modulation to obtain the switching sequence of dual inverter SVPWM modulation. The pulse signal input module is used to apply the switching sequence to the phase windings of the target motor to control the current of phases A, B, and C of the motor windings, so as to achieve deadbeat predictive current control.

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