Intelligent control method and system for high-speed brushless motor for dust collection

Abstract

This application relates to the field of motor control and electrical technology, and in particular to an intelligent control method and system for a high-speed brushless motor for vacuum cleaners. The method is applied to a high-speed brushless motor system, which includes a processor and a frequency-selective damping ring fitted onto the motor stator core. The inner wall or end face of the frequency-selective damping ring has multiple radial slots arranged at preset intervals. The method is executed by the processor and includes: acquiring a torque trend term characterizing the change trend of the motor load torque and an angular acceleration term characterizing the change trend of the motor rotor kinetic energy; calculating a real-time phase offset based on the torque trend term and the angular acceleration term; identifying the degree to which the real-time phase offset deviates from a preset dynamic threshold to determine whether the motor has entered a surge bud state; and outputting an overmodulation control signal when a surge bud state is detected to drive the motor stator windings to generate an excitation current containing high-frequency harmonic cluster components.

Description

Technical Field

[0001] This application relates to the field of motor control and electrical technology, and in particular to an intelligent control method and system for a high-speed brushless motor for vacuum cleaners. Background Technology

[0002] In applications such as high-end vacuum cleaners, high-speed brushless motors (such as those with a speed exceeding 100,000 rpm) are extremely sensitive to load fluctuations.

[0003] Existing technologies typically employ threshold monitoring based on current or speed fluctuations. When the system detects that operating parameters deviate from the preset safety range, the controller triggers shutdown protection or executes a speed reduction command via software instructions.

[0004] Conventional protection schemes can only monitor macroscopic operating parameters. This monitoring logic often fails to capture the microscopic trends of the motor system before it enters an unstable state, resulting in insufficient accuracy in identifying potential risks. Summary of the Invention

[0005] Therefore, it is necessary to provide an intelligent control method and system for a high-speed brushless motor for vacuum cleaners that can accurately identify surge risk at an early stage, in order to address the aforementioned technical problems.

[0006] In a first aspect, this application provides an intelligent control method for a high-speed brushless motor for vacuum cleaners, applied to a high-speed brushless motor system. The high-speed brushless motor system includes a processor and a frequency-selective damping ring sleeved on the stator core of the motor. The inner wall or end face of the frequency-selective damping ring has multiple radial slots arranged at preset intervals. The method is executed by the processor and includes:

[0007] Obtain the torque trend term, which characterizes the change trend of the motor load torque, and the angular acceleration term, which characterizes the change trend of the motor rotor kinetic energy;

[0008] Calculate the real-time phase offset based on the torque trend term and the angular acceleration term;

[0009] The degree to which the real-time phase offset deviates from the preset dynamic threshold is identified in order to determine whether the motor has entered the initial stage of surge.

[0010] When surge budding state is detected, an overmodulation control signal is output to drive the motor stator winding to generate an excitation current containing high-frequency harmonic cluster components.

[0011] The spectral characteristics of the overmodulation control signal are configured such that the high-frequency excitation magnetic field generated by the excitation current induced by it satisfies the physical constraints of the skin effect. The physical constraints of the skin effect include: the skin depth of the induced current induced by the high-frequency excitation magnetic field in the frequency-selective damping ring is less than the depth of the radial slot.

[0012] Secondly, this application provides a high-speed brushless motor system, including a stator, a motor rotor, and a frequency selective damping ring as described above; the stator includes a motor stator core, and the frequency selective damping ring is sleeved on the axial end of the motor stator core; the high-speed brushless motor system also includes a processor, which is configured to execute the intelligent control method for a high-speed brushless motor for vacuuming as described above.

[0013] Beneficial effects of this application: By deeply exploring the evolution law of load torque and motor rotor kinetic energy, this application achieves accurate identification of the initial state of motor surge, effectively making up for the lag of conventional macroscopic parameter monitoring in early risk warning; furthermore, by combining overmodulation excitation with a physical damping ring with a specific radial slotted structure, the "frequency-selective" switching of damping characteristics is achieved by utilizing the skin effect physical constraint. This not only specifically absorbs high-frequency oscillation energy under unstable conditions and smooths system impact, but also avoids the impact of conventional global damping on the efficient operation of the motor under normal operating conditions. While improving the sensitivity of protection identification, it enhances the operational robustness and mechanical life of high-speed motor systems under extreme disturbances. Attached Figure Description

[0014] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the accompanying drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below.

[0015] Figure 1 This is a schematic diagram of the frequency-selective damping ring in an embodiment of this application;

[0016] Figure 2 This is a flowchart illustrating the intelligent control method for a high-speed brushless motor used for vacuuming in an embodiment of this application.

[0017] Explanation of reference numerals in the attached figures:

[0018] 10. Frequency selective damping ring; 20. Motor stator core; 30. Motor rotor.

[0019] 101. Radial slotting; 21. Motor stator winding. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0021] In practical applications of high-speed vacuum cleaners (typically exceeding 100,000 rpm), unexpected blockage of the suction port or instantaneous switching of the air duct can cause a sudden drop in motor load torque (air resistance). Existing technologies typically monitor changes in bus current or speed and use software algorithms to shut off the inverter's pulse width modulation (PWM) output. However, this purely software-based protection suffers from a significant "kinetic redundancy vacuum period": due to the enormous mechanical inertia of the high-speed rotating motor rotor 30, even at the moment of power failure, the momentum contained in the motor rotor 30 can still induce severe physical oscillations (i.e., surge) in the bearings and electromagnetic air gap. This time difference between "sensing braking" makes it difficult for traditional methods to provide immediate physical constraints in the early stages of instability, easily leading to abnormal motor temperature rise and mechanical fatigue.

[0022] To address the aforementioned technical issues, this embodiment integrates a key energy dissipation terminal—a frequency-selective damping ring 10—into the high-speed brushless motor system.

[0023] The frequency-selective damping ring 10 is made of a highly conductive metallic material (preferably oxygen-free copper or aluminum alloy) and is compactly fitted onto the axially extending end of the motor stator core 20. The frequency-selective damping ring 10 has a unique physical design: its inner wall or end face has multiple radial slots 101 arranged at preset intervals along the circumferential direction. Spatially, the frequency-selective damping ring 10 is positioned within the envelope of the alternating magnetic field generated by the motor stator winding 21 and coupled to the main airflow cooling path of the vacuum cleaner. This hardware system achieves dynamic intervention in the motor's operating state by constructing a "physical switch based on frequency characteristics."

[0024] For typical vacuuming conditions: at the fundamental frequency where the motor is operating at its rated speed, the skin depth of the stator magnetic field within the frequency-selective damping ring 10 material... Larger. Because at this time The radial thickness is greater than that of the frequency-selective damping ring 10, and the radial slot 101 on the frequency-selective damping ring 10 effectively cuts off the circumferential closed path of the low-frequency induced current. Physically, the frequency-selective damping ring 10 is "transparent" to the motor's main magnetic field, generating almost no additional electromagnetic losses. This hardware design ensures that the vacuum cleaner maintains extremely high energy conversion efficiency during normal operation.

[0025] For surge suppression: When the processor detects the initial surge state, it injects a high-frequency excitation signal into the stator winding 21 of the motor, causing a high-frequency fluctuating excitation magnetic field to be generated in the electromagnetic space (i.e., air gap) between the stator and the motor rotor 30. According to the skin effect principle in electromagnetism, as the frequency of the magnetic field fluctuation increases, the induced current is forcibly compressed within an extremely thin layer (i.e., the skin layer) on the surface of the frequency-selective damping ring 10. When the skin depth of the induced current... Compressed to less than the physical depth of the radial slot 101 in the radial thickness direction of the frequency-selective damping ring 10. At this time, the conduction path of the induced current 'migrates' from the deep layers of the material to the surface. Since the induced current flows only within the extremely thin skin layer above the slot, it avoids the physical circuit break constraint at the bottom of the radial slot 101, achieving cross-conduction at the slot surface. This change closes the originally disconnected current path, forming a complete, low-impedance circumferential current loop within the frequency-selective damping ring 10, thereby generating an electromagnetic viscous torque opposite to the rotation direction of the motor rotor 30 to absorb the kinetic energy of the motor rotor 30.

[0026] Based on the aforementioned hardware mechanism, this solution constructs a frequency-controlled 'physical energy dissipation terminal': achieving high efficiency through slotted circuit breaking at low frequencies and instantaneous energy dissipation through the skin effect at high frequencies. After completing the construction of the aforementioned physical hardware environment, the processor, through... Figure 2 The algorithm logic shown (steps S101 to S104) drives the physical switch described above:

[0027] Step S101: Obtain the torque trend term characterizing the change trend of the motor load torque and the angular acceleration term characterizing the change trend of the motor rotor kinetic energy.

[0028] This step aims to extract the "dynamic energy fingerprint" of the tested motor under ultra-high speed operation, in order to eliminate the "perception lag" caused by traditional technologies that only monitor the absolute value of current or speed. Based on the "function-energy conversion" physical balance model, there is a real-time mapping relationship between the input electrical power of the motor and the mechanical output power of the motor rotor 30. Any disturbance at the load end will be preferentially reflected in the "change slope" of energy.

[0029] In some embodiments, the processor acquires the stator current vector and the real-time position signal of the motor rotor 30 via a high-speed sampling link. Instead of extracting the steady-state amplitude, it extracts the first or second-order gradient signal in the time domain using an internally preset state observation algorithm. Among these, the torque trend term... It reflects the instantaneous drop slope of the air gap load (e.g., the torque jump caused by the dust inlet being sealed), while the angular acceleration term... This characterizes the intensity of the instantaneous conversion of input power into the kinetic energy of the motor rotor 30 due to the disappearance of the load. This extraction method, based on "trend gradient" rather than "absolute value", essentially performs feedforward capture of the surge signal in the time domain, enabling the system to make predictions in the "budding stage" before the kinetic energy of the motor rotor 30 completely loses control.

[0030] Step S102: Calculate the real-time phase offset based on the torque trend term and the angular acceleration term.

[0031] This step aims to quantitatively assess the "degree of energy imbalance" of the system. Under steady-state operation of the motor, the variation in output torque and the feedback of the motor rotor 30 motion state are logically highly coupled (i.e., phase consistent); however, in the early stage of surge, due to the instantaneous removal of the load, the sudden drop in torque and the sudden increase in acceleration will exhibit a significant physical mismatch.

[0032] In some embodiments, the processor will acquire and This is mapped to an abstract feature coordinate system. The phase offset is obtained by calculating the spatial geometric angle between these two dynamic feature vectors. This value precisely characterizes, in its physical sense, the degree of deviation between the motor's "electromagnetic drive command" and "mechanical motion response": within the normal range, It maintains a preset low level of fluctuation; once the load changes abruptly, the two diverge in phase. It will quickly cross the linear region and enter the nonlinear abrupt change region. This provides an intuitive logical basis for the system to determine whether to activate the "physical energy dissipation terminal (damping ring)".

[0033] Step S103: Identify the degree to which the real-time phase offset deviates from the preset dynamic threshold to determine whether the motor has entered the budding surge state.

[0034] This step aims to construct a set of "dynamic stability criteria" that fluctuates with operating conditions. Since the instability critical point of high-speed motors at different energy levels (speeds) has nonlinear characteristics, this scheme abandons the fixed static threshold and achieves adaptive interception of surge risk.

[0035] In some embodiments, the processor retrieves a matching dynamic threshold as a logic threshold based on the current real-time operating speed of the motor. This is achieved by comparing the real-time phase offset. The deviation from this dynamic threshold allows for the detection of surge triggering symptoms at a very early stage, before physical oscillations occur. This determination mechanism based on the degree of phase deviation avoids the lag in protection decisions caused by the enormous mechanical inertia of the motor rotor 30.

[0036] Step S104: When the surge budding state is detected, an overmodulation control signal is output to drive the motor stator winding to generate an excitation current containing high-frequency harmonic cluster components.

[0037] This step enables an instantaneous switch from "software logic recognition" to "hardware physical energy dissipation." Unlike traditional passive protection that involves "shutting down and cutting off power," this step actively injects spectrum-controlled electromagnetic energy to directly cancel out more than 30 kJ of kinetic energy from the motor rotor at the physical level.

[0038] In some embodiments, the processor executes an overmodulation control strategy to superimpose specific high-frequency harmonic clusters into the PWM signal output by the inverter circuit. These high-frequency components generate a high-frequency excitation magnetic field in the air gap, thereby triggering the physical response mechanism of the frequency-selective damping ring 10: since the excitation frequency is much higher than the fundamental frequency, the skin depth of the induced current within the frequency-selective damping ring 10 is rapidly compressed to a depth less than that of the radial slot 101. At this point, a cross-conduction occurs at the physical level, and the induced current breaks through the barrier of the radial slot 101, spontaneously forming a strong, closed circumferential current loop on the surface of the frequency-selective damping ring 10.

[0039] According to the Lorentz force law, this circuit generates an electromagnetic viscous torque opposite to the rotation direction of the motor rotor 30, converting the unsteady kinetic energy accumulated in the motor rotor 30 into heat energy in situ. This closed-loop mechanism of "energy absorption in situ" achieves rigid physical suppression of high-speed surge without relying on an external discharge circuit.

[0040] In an exemplary embodiment, regarding the extraction of the "dynamic energy fingerprint" in step S101, to ensure that the torque trend term and angular acceleration term can simultaneously achieve "high real-time performance" and "strong noise resistance," this embodiment, in its specific execution process, constructs a second-order extended state observer (ESO) with self-learning and nonlinear anti-interference characteristics, thereby realizing deep stripping of the motor's micro-energy states. Its specific execution logic is as follows:

[0041] Phase 1: Construct a second-order extended state observer that includes speed state variables and total disturbance extended state variables.

[0042] This step aims to establish a dynamic observation benchmark for the motor's operating state. Within its internal algorithm space, the processor constructs a second-order state equation based on the motor's mechanical kinematics. The first-dimensional state variable is defined as the rotational speed state variable, used to track the mechanical speed of the motor rotor 30 in real time; the second-dimensional state variable is defined as the total disturbance expansion state variable. This expansion variable encapsulates all uncertainties, such as sudden changes in duct load, fluctuations in internal parameters, and frictional losses, into an observable linear state quantity, thus enabling the transformation of complex "nonlinear surge inducements" into "linear observations" in subsequent steps.

[0043] The second stage involves acquiring the measured quantum current of the motor and generating a state correction increment based on the deviation between the measured quantum current and the predicted current output by the second-order extended state observer.

[0044] This step is the core driver for the observer to maintain consistency between the model and physical reality. The processor collects the measured quantum current in real time and calculates a predicted current based on the current internal state of the observer. The measured value is compared with the predicted value, and the resulting deviation is processed by a feedback operator to generate a state correction increment. This increment is essentially a dynamic correction of the model's predicted value by the measured physical quantity, and its magnitude accurately reflects the deviation between the current actual operating state of the motor and the observer's preset model.

[0045] Phase 3: Use state correction increments to synchronously update the speed state variable and the total disturbance expansion state variable.

[0046] The processor feeds the generated state correction increments to the two integration channels of the observer, driving the observer to follow the actual evolution of the motor in real time with extremely high bandwidth. Because the observer has structured low-pass filtering characteristics, it can naturally filter out high-frequency random noise in the sampling process during synchronous update of state variables, thereby obtaining an estimation curve with a high signal-to-noise ratio and solving the signal "glitch" problem caused by traditional differential operations.

[0047] The fourth stage involves extracting intermediate variables related to the state correction increment from the dynamic update equation of the second-order extended state observer and mapping them to angular acceleration terms that characterize the trend of change in the motor rotor kinetic energy.

[0048] This step solves the problem of "phase lag" in angular acceleration extraction. Instead of directly performing lag-based post-processing differentiation on the rotational speed signal, this scheme directly extracts an internal intermediate variable linearly related to the state correction increment from the observer's closed-loop feedback loop. Since this variable represents the "acceleration compensation" that must be applied to eliminate model bias, it is proportional to the instantaneous angular acceleration of the motor rotor 30. By directly extracting this intermediate variable, a zero-lag angular acceleration term can be obtained, providing accurate time-domain characteristics for the phase calculation in the subsequent step S102.

[0049] Fifth stage: Extract the updated total disturbance expansion state variable, and based on its incremental change in adjacent sampling periods, combine it with the torque constant of the motor to map it into a torque trend term that characterizes the load torque change trend.

[0050] This step achieves precise decoupling from the "load shedding" event. Since the total disturbance expansion state variable has fully absorbed the characteristics of the external disturbance, it will undergo a sharp slope jump when surge precursors occur. The processor extracts this variable and calculates its incremental change in adjacent sampling periods, and performs proportional scaling based on the motor's torque constant, thereby separating the torque trend term purely caused by changes in the external duct load.

[0051] Through the operation of the aforementioned second-order extended state observer, the system achieves "transparent" monitoring of the physical quantities inside the motor. This deep transformation from electrical quantities (current) to kinematic quantities (torque, acceleration) provides a high-precision, zero-hysteresis data source for calculating the real-time phase offset in the subsequent step S102.

[0052] In an exemplary embodiment, regarding the aforementioned step S102, after obtaining the torque trend term and angular acceleration term with a high signal-to-noise ratio, this embodiment constructs a two-dimensional orthogonal energy state mapping space to achieve geometric decoupling and quantitative determination of surge risk.

[0053] In the actual operation of high-speed vacuum cleaners, simply monitoring the magnitude of a single physical quantity often makes it difficult to accurately distinguish between "normal dynamic adjustment" and "the onset of surge failure." For example, during the normal start-up or rapid speed adjustment phase of the motor, the angular acceleration will increase significantly, and the electromagnetic torque will be at a high level simultaneously; while in the early stage of surge caused by the suction port being sealed, the torque will suddenly drop, and the angular acceleration will abnormally spike due to the conversion of redundant input power.

[0054] To address this technical challenge of "misjudgment due to multivariate coupling," this embodiment no longer observes the magnitude of physical quantities in isolation. Instead, it identifies the "degree of deviation" in energy flow from a physical perspective through the following logic, the specific execution logic of which is as follows:

[0055] Phase 1: Construct a two-dimensional orthogonal energy state mapping space with the absolute value of the torque trend term as the first dimension component and the angular acceleration term as the second dimension component.

[0056] The processor defines a Cartesian coordinate system within its internal algorithm space. The load reference axis (horizontal axis) represents the system's "damping constraint strength," with its components representing the absolute values ​​of the torque trend term. The vertical axis represents the system's "kinetic energy gain strength," with its components corresponding to the angular acceleration term. For example, the processor first presets the torque reference gain. With acceleration reference gain The absolute values ​​of the torque trend term and the angular acceleration term acquired in real time are respectively normalized to obtain the dimensionless first-dimensional mapping value. Mapping value to the dimensionless second dimension The processor defines a space within its internal algorithm space that uses... The horizontal axis represents the system's damping constraint strength, and the vertical axis represents the horizontal axis (representing the system's damping constraint strength). The Cartesian coordinate system with the vertical axis (representing the kinetic energy gain intensity of the system) maps the physical scalar signals with inconsistent dimensions to feature points in this planar coordinate system.

[0057] The second stage involves orthogonally synthesizing the first-dimensional component and the second-dimensional component acquired in real time to generate a dynamic energy deviation vector pointing into the two-dimensional orthogonal energy state mapping space.

[0058] This step achieves a dimensionality upgrade from "scattered data" to "energy feature vectors." The processor utilizes the current two dimensional components to calculate a dynamic energy deviation vector originating from the coordinate origin, based on the principle of vector composition. For example, the real-time acquired first-dimensional mapping value... Mapping value with the second dimension Orthogonal synthesis is performed to generate a dynamic energy divergence vector pointing into the interior of the two-dimensional orthogonal energy state mapping space. According to the principle of vector composition, the length of this vector is... It reflects the instantaneous total intensity of the system's energy fluctuations.

[0059] The third stage: extract the instantaneous angle of the dynamic energy divergence vector relative to the load reference axis based on the first dimension component, and determine the instantaneous angle as the real-time phase offset.

[0060] Optionally, extract the dynamic energy divergence vector. Relative to the value mapped in the first dimension The instantaneous angle of the load reference axis, which is used as the reference, is calculated using the following formula: and will instantly widen the angle This was determined to be the real-time phase offset. This normalization process eliminated the inaccuracies in judgment caused by dimensional differences, thus ensuring the accuracy of the angular deviation. It can accurately depict the physical fingerprint of the motor's evolution from "load balance state" to "kinetic energy runaway state".

[0061] Under steady-state operation: As the load term dominates, the vector is close to the load reference axis, and the real-time phase offset remains in the minimum range. Under surge initiation conditions: As the load disappears, the first-dimensional component decreases sharply, while the angular acceleration surges, causing the second-dimensional component to increase abruptly. The dynamic energy deviation vector will rapidly shift towards the vertical axis.

[0062] This "angle determination method" possesses strong physical robustness; it does not fail with changes in the motor's base speed and can shield against interference from absolute speed values, extracting only the pure physical fingerprint of the system's evolution from a "load equilibrium state" to a "kinetic energy runaway state." By extracting this geometric feature, the system successfully simplifies the complex electromechanical nonlinear instability process into a clear angular displacement, providing a highly reliable criterion for the threshold comparison in subsequent step S103.

[0063] In an exemplary embodiment, regarding the aforementioned step S103, when determining whether the motor has entered the surge bud state, this embodiment introduces a dynamic threshold generation mechanism that adaptively shrinks with rotational speed, thus resolving the technical contradiction of balancing "protection sensitivity" and "operational robustness" of high-speed motors across the entire speed range.

[0064] During the operation of a high-speed brushless motor, the system's energy balance exhibits strong "speed sensitivity." At low speeds, the motor rotor 30 has low kinetic energy, and the system has a high tolerance for slight load fluctuations. However, when the speed increases to its rated high level, the kinetic energy of the motor rotor 30 increases quadratically with the speed, and even a tiny phase shift can evolve into devastating mechanical surge within milliseconds. Therefore, this embodiment constructs a dynamically changing "safety envelope" through the following logic, the specific implementation logic of which is as follows:

[0065] Phase 1: Obtain the current rotational speed state variable value output by the second-order extended state observer in the current sampling period.

[0066] The processor directly calls the current rotational speed state variable value estimated in real time by the ESO. Compared to the raw rotational speed calculated directly from physical sensors or back EMF, the state variable output by the ESO has undergone filtering and state expansion processing within the algorithm, resulting in higher smoothness and lower phase delay. This ensures the stability of subsequent threshold calculations and avoids frequent switching of protection logic due to signal glitches.

[0067] Phase Two: Calculate the real-time speed normalization ratio between the current speed state variable value and the preset rated motor speed. .

[0068] The processor calculates the ratio between the currently acquired speed state variable value and the preset rated motor speed (i.e., the system's design limit speed) to obtain the real-time speed normalization ratio. This ratio physically represents the motor's current "energy stress load": when the ratio approaches 1, it means that the motor is at the edge of its ultimate kinetic energy, and the system's tolerance for any phase deviation is reduced to the minimum.

[0069] Third stage: Generate a preset dynamic threshold that shrinks non-linearly with increasing rotational speed according to equation (1).

[0070] Based on the acquired real-time rotational speed normalization ratio, the processor generates a preset dynamic threshold using an exponential decay model. :

[0071] Equation (1)

[0072] in, This is the preset reference phase offset. The preset convergence coefficients are used. In this mapping model: the preset reference phase offset is used. The system is set to have a maximum tolerance deviation at low speeds. Utilizing the decay characteristic of a negative exponential function, the threshold value decreases rapidly and non-linearly as the rotational speed increases. This is achieved by adjusting a preset convergence coefficient. This allows for precise definition of the contraction slope of the safety envelope. In the ultra-high speed range, due to the exponential adjustment of this coefficient, the preset dynamic threshold is extremely compressed. This means that when the motor is operating at a high energy level, even a very slight instantaneous angular deflection will trigger this dynamic threshold and be identified as a "surge initiation state," thus forcibly triggering subsequent overmodulation control strategies.

[0073] This embodiment constructs a dynamic threshold that "exponentially contracts" with increasing rotational speed, thus creating a dynamically adjustable safety net for the motor at the physical level. This design cleverly utilizes the nonlinear characteristics of the mathematical model, perfectly matching the physical nature of the change in kinetic energy of the motor rotor with rotational speed, thereby achieving precise interception of high-speed surge risk without increasing hardware costs.

[0074] In an exemplary embodiment, regarding step S104 above, after identifying the initial surge state, the system needs to achieve "millisecond-level rigid suppression" of the instability kinetic energy of the motor rotor 30 without shutting down the main power circuit. This embodiment uses a complex "electromagnetic spectrum reconstruction strategy" to convert the electrical energy originally used to drive the motor into damping energy with physical viscosity characteristics. The specific execution steps are detailed below:

[0075] The first stage: Based on the built-in speed-current dual closed-loop control law, combined with the measured stator current and the speed state variable output by the second-order extended state observer, a basic stator voltage vector is synthesized to maintain the synchronous rotation of the motor.

[0076] The processor first maintains its built-in speed-current dual closed-loop control law. During this stage, the outer speed loop calculates the target torque based on the speed state variable output by the ESO, while the inner current loop calculates the target torque based on the measured current after coordinate transformation. Decoupling control is achieved through a spatial vector pulse width modulation (SVPWM) algorithm. The processor synthesizes a fundamental stator voltage vector to maintain synchronous rotation of the motor. This vector physically generates the fundamental magnetic field that sustains the synchronous rotation of the motor rotor 30; it serves as the "background carrier" for all subsequent overmodulation actions. This design ensures that during physical braking, the motor will not experience a reverse electromotive force surge due to momentary demagnetization or completely lose real-time control of the motor rotor 30.

[0077] Second stage: Select the material parameters of the damping ring 10 and the depth of the radial slot 101 according to the frequency, and calculate the lower limit of the target frequency that satisfies the physical constraint of the skin effect.

[0078] To accurately induce the energy dissipation characteristics of the frequency-selective damping ring 10, the processor must align the "software excitation frequency" with the "hardware physical dimensions" in real time. The processor extracts the material property parameters of the frequency-selective damping ring 10 and combines them with the preset physical depth of the radial slot 101 in memory. High-frequency calculations are performed according to equation (2) to lock in the lower limit of the target frequency that satisfies the physical constraint of the skin effect. .

[0079] (2)

[0080] In equation (2), The conductivity of the frequency-selective damping ring 10 material (e.g., when oxygen-free copper is used) refers to the conductivity of the material. Values ); The permeability of the material of the frequency-selective damping ring 10 (usually taken as the free permeability) ); Specifically refers to the cutting depth of the radial slot 101 in the radial thickness direction of the frequency-selective damping ring 10. Based on the material physical parameters and structural geometric parameters determined above, the system can pre-calculate the induced current generated by the skin effect to be sufficient to cross the groove depth. Critical frequency .

[0081] The third stage involves increasing the modulation coefficient of the basic stator voltage vector and redistributing the duration of the voltage vector according to the target frequency lower limit to generate a high-frequency harmonic cluster that covers the target frequency lower limit.

[0082] In acquiring Then, the processor immediately reconstructs the PWM modulation mode: after obtaining the target frequency lower limit. Then, the processor immediately reconstructs the PWM modulation mode: the processor modulates the modulation coefficients of the base stator voltage vector of the space vector pulse width modulation (SVPWM). Upgraded to the overmodulation range (value range is) In the overmodulation state, the endpoint trajectory of the voltage vector shifts from the inscribed circle of the SVPWM control towards the boundary of the regular hexagon.

[0083] Specifically, the processor actively compresses the zero vector during the PWM carrier cycle. The effective voltage vector's time width is correspondingly extended by adjusting the ratio of the effective voltage vector's action, causing controlled nonlinear distortion of the output current waveform, thereby superimposing a nonlinear distortion onto the fundamental output current waveform. Second-rate( This involves a high-frequency harmonic cluster dominated by higher harmonics. The processor dynamically adjusts the switching frequency of the PWM to ensure that the center frequency of the most concentrated harmonic component is at the lower limit of the aforementioned target frequency. Above this, the electromagnetic viscous torque of the frequency-selective damping ring 10 is triggered at the physical level.

[0084] To prevent the motor stator core 20 from entering a state of magnetic saturation, which could lead to a sharp decrease in inductance and overheating, the processor incorporates magnetic saturation constraint monitoring logic. This logic is based on the current air gap magnetic flux density. The estimated value is used to nonlinearly clamp the amplitude of the overmodulated waveform. This clamping ensures that even under extreme energy dissipation conditions, the magnetic flux density of the core remains below a safe threshold (such as 1.6T), achieving a balance between "maximizing damping torque" and "hardware safety".

[0085] The fourth stage involves frequency domain discretization of the high-frequency harmonic clusters to generate an overmodulated PWM pulse sequence, which serves as the overmodulation control signal, and then outputs the overmodulation control signal.

[0086] To prevent high-frequency resonance between harmonics of specific frequencies and the motor's mechanical structure, the processor performs frequency domain discretization on the generated high-frequency harmonic clusters. The processor reallocates the effective voltage vector and zero vector's duration within each PWM cycle, ensuring that high-frequency energy is not concentrated at a single frequency point but is uniformly distributed in the form of "energy clusters." Within the aforementioned wideband, the resulting overmodulated PWM pulse sequence is output to the inverter bridge, driving the motor stator winding 21 to generate an excitation current containing wideband high-frequency components.

[0087] Furthermore, to eliminate the negative feedback interference caused by overmodulation to the "observation system," this embodiment adds a notch filter processing stage to the feedback link. Since the high-frequency excitation current injected by overmodulation generates superimposed noise on the sampling resistor, directly inputting it to the ESO would cause the observer to mistakenly believe that the load has experienced high-frequency oscillation, thus triggering control divergence. After current sampling, the processor sets the center frequency to the main frequency point of the overmodulation harmonic using a digital notch filter, performing deep filtering on the measured rotor current. This operation precisely removes the high-frequency excitation component, retaining only the low-frequency fundamental current sent to the ESO. This "signal decoupling" ensures that the ESO can still accurately monitor the fundamental frequency operating state of the motor rotor 30 at the moment physical energy dissipation is activated, maintaining the closed-loop stability of the system.

[0088] When the overmodulated signal is injected into the system, the conductivity of the inner wall of the frequency-selective damping ring 10 undergoes a sudden change: the induced current changes from an "open circuit" to a "short circuit" within microseconds. The strong eddy currents formed within the skin layer interact violently with the permanent magnetic field of the motor rotor 30, generating a huge electromagnetic viscous torque on the surface of the motor rotor 30 directly, opposite to the direction of the instantaneous disturbance, according to the Lorentz force law. Since this energy consumption occurs "in situ," the instability kinetic energy is directly converted into heat energy within the damping ring and rapidly discharged through the high-speed air duct of the vacuum cleaner itself. This "energy trap" mechanism ensures that the system can forcibly suppress the nascent surge without shutting down or releasing energy.

[0089] In one exemplary embodiment, this embodiment provides a high-speed brushless motor system designed for high-speed vacuum cleaners (rated speed ≥ 100,000 rpm), aiming to solve the instability and surge problem at ultra-high speeds through hardware and software collaboration. The system includes a stator, a motor rotor 30, a processor, and a core energy dissipation component, a frequency-selective damping ring 10.

[0090] The stator of this system includes a stacked motor stator core 20 and three-phase motor stator windings 21 wound on it. The motor rotor 30 has a built-in permanent magnet structure and is supported on a high-speed bearing. The frequency-selective damping ring 10 is mounted on the axial end of the motor stator core 20. This "end-mounted" arrangement utilizes the physical characteristic that the leakage flux is most concentrated at the motor end. Under normal operating conditions, the end leakage flux passes through the damping ring at the fundamental frequency without generating additional losses.

[0091] Once the processor outputs an overmodulated signal, the high-frequency excitation magnetic field generated by the motor stator winding 21 will directly radiate to this end region and undergo intense electromagnetic coupling with the radial slot 101 on the surface of the damping ring. Since the damping ring is in close contact with the end of the motor stator core 20, its heat can be directly dissipated through the core, while also avoiding the central region of the motor rotor 30, thus ensuring the structural strength of the high-speed rotating components.

[0092] The processor in the system (such as a high-performance DSP or MCU) is configured to execute the intelligent control methods corresponding to steps S101 to S104. As the "brain" of the system, it is responsible for the following closed-loop tasks:

[0093] The trend of angular acceleration and torque can be extracted using ESO without physical sensors.

[0094] Angle determination is performed in a two-dimensional orthogonal energy state mapping space to generate an adaptive dynamic threshold.

[0095] At the moment when surge begins, the overmodulation algorithm is activated to "precisely inject" the calculated high-frequency energy into the frequency selective damping ring 10 fitted at the end of the stator.

[0096] The most crucial physical feature of this system lies in the geometric design of the frequency-selective damping ring 10. The radial thickness of the damping ring is configured to be strictly smaller than the skin depth of the damping ring material at the rated fundamental frequency of the motor. Assuming the motor's rated speed is 120,000 rpm (fundamental frequency approximately 2 kHz), a conductivity of [missing value] is selected. Conductive materials. At this frequency, the skin depth of electromagnetic waves... Thicker. By designing the radial thickness of the damping ring to be greater than... The thinner design allows the fundamental magnetic field to completely "penetrate" the damping ring during normal, efficient operation, preventing the generation of large-scale eddy currents within the ring. This means that in non-surge conditions, the damping ring is physically "nearly transparent," maintaining the motor's rated efficiency and resolving the heat loss problem caused by traditional fixed dampers.

[0097] Based on the aforementioned radial slot 101, the collaborative working logic of the system is as follows:

[0098] Low-frequency state (normal operation): The magnetic field frequency is the fundamental frequency. Since the skin depth is greater than the ring thickness, the magnetic field lines penetrate directly, and the damping ring does not generate damping.

[0099] High-frequency state (surge detected): Processor injection higher than High-frequency harmonics. At this time, the skin depth of the high-frequency magnetic field... It rapidly shrinks to a depth less than the radial slot 101.

[0100] The induced current is confined by an extremely narrow skin layer, forcing it to form a closed loop across the slot opening above the radial slot 101. As the equivalent resistance of this loop increases significantly at high frequencies, the damping ring instantly changes from a "transparent state" to a "high viscosity state," generating a huge Lorentz torque that acts on the motor rotor 30, thereby rigidly stabilizing the surge.

[0101] This system achieves "on-demand damping": maintaining zero-loss operation in the normal high-speed range; and converting instability energy into heat energy in situ during the extremely short instant of surge by utilizing spatial arrangement and dimensional constraints (radial thickness control). This hardware-software combined architecture enables high-speed vacuum cleaner motors to actively defend against mechanical surge while pursuing extreme speeds.

[0102] In one embodiment, a vacuum cleaner is provided. The vacuum cleaner includes a housing, a fan assembly, and a high-speed brushless motor system as described in the foregoing embodiment. The high-speed brushless motor system is housed within the housing, and the motor rotor 30 shaft of the high-speed brushless motor system is coaxially connected to the impeller of the fan assembly for driving the fan assembly to generate a high-speed suction airflow.

[0103] In the actual operation of this vacuum cleaner, the suction port formed on the casing and the fan assembly constitute the main air duct. When extreme conditions occur, such as the suction port being instantly blocked by the floor fabric or the user switching the air duct speed, the air damping in the main air duct will drop momentarily, causing the motor to enter the surge risk zone.

[0104] At this point, the processor integrated into the high-speed brushless motor system executes the aforementioned steps S101 to S104, using ESO to capture in real time the changes in load torque trend and abrupt changes in angular acceleration caused by airflow interruption. Once it is determined that the phase offset crosses the dynamic safety boundary, the processor immediately initiates the overmodulation algorithm.

[0105] Because the frequency-selective damping ring 10 is fitted at the stator end and coupled to the heat dissipation path of the main air duct, the high-frequency harmonics generated by overmodulation excite eddy current loops that cross the radial slots 101 within the damping ring. This loop not only instantaneously generates electromagnetic viscous torque to suppress the unstable oscillations of the motor rotor 30, but also directly discharges the heat generated by energy dissipation into the housing through the suction airflow of the vacuum cleaner.

[0106] 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 application.

[0107] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for intelligent control of a high-speed brushless motor for a vacuum cleaner, characterized by, The method is applied to a high-speed brushless motor system, which includes a processor and a frequency-selective damping ring (10) fitted onto the motor stator core (20). The frequency-selective damping ring (10) has multiple radial slots (101) arranged at preset intervals on its inner wall or end face. The method is executed by the processor and includes: Obtain the torque trend term, which characterizes the change trend of the motor load torque, and the angular acceleration term, which characterizes the change trend of the motor rotor kinetic energy; Calculate the real-time phase offset based on the torque trend term and the angular acceleration term; The degree to which the real-time phase offset deviates from the preset dynamic threshold is identified in order to determine whether the motor has entered the budding surge state; When the surge bud state is detected, an overmodulation control signal is output to drive the motor stator winding (21) to generate an excitation current containing high-frequency harmonic cluster components. The spectral characteristics of the overmodulation control signal are configured such that the high-frequency excitation magnetic field generated by the excitation current induced by it satisfies the physical constraint of the skin effect; the physical constraint of the skin effect includes: the skin depth of the induced current induced by the high-frequency excitation magnetic field in the frequency-selective damping ring (10) is less than the depth of the radial slot (101).

2. The method of claim 1, wherein, The acquisition of the torque trend term characterizing the change trend of the motor load torque and the angular acceleration term characterizing the change trend of the motor rotor kinetic energy specifically includes: Construct a second-order extended state observer that includes speed state variables and total disturbance extended state variables; The measured quantum current of the motor is obtained, and a state correction increment is generated based on the deviation between the measured quantum current and the predicted current output by the second-order extended state observer. The rotational speed state variable and the total disturbance expansion state variable are synchronously updated using the state correction increment; Intermediate variables related to the state correction increment are extracted from the dynamic update equation of the second-order extended state observer and mapped to angular acceleration terms that characterize the trend of change in the motor rotor kinetic energy. The updated total disturbance expansion state variable is extracted and mapped to a torque trend term characterizing the load torque change trend based on its incremental change in adjacent sampling periods and the torque constant of the motor.

3. The method of claim 2, wherein, The calculation of the real-time phase offset based on the torque trend term and the angular acceleration term specifically includes: Construct a two-dimensional orthogonal energy state mapping space with the absolute value of the torque trend term as the first dimension component and the angular acceleration term as the second dimension component; The first dimension component and the second dimension component, which are acquired in real time, are orthogonally synthesized to generate a dynamic energy deviation vector pointing into the interior of the two-dimensional orthogonal energy state mapping space. The instantaneous angle of the dynamic energy divergence vector relative to the load reference axis based on the first dimension component is extracted, and the instantaneous angle is determined as the real-time phase offset.

4. The method of claim 2, wherein, The preset dynamic threshold is generated in the following way: Obtain the current rotational speed state variable value output by the second-order extended state observer in the current sampling period; calculating a real-time speed normalization ratio of the current speed state variable value and a preset motor rated speed ; generating a preset dynamic threshold according to formula (1) that shrinks non-linearly as the rotational speed increases Formula (1) wherein, is a preset reference phase offset, is a preset convergence coefficient.

5. The method according to claim 2, characterized in that, The output overmodulation control signal specifically includes: Based on the built-in speed-current dual closed-loop control law, and combined with the measured stator current and the speed state variable output by the second-order extended state observer, a basic stator voltage vector for maintaining synchronous rotation of the motor is synthesized. Based on the material parameters of the frequency-selected damping ring (10) and the depth of the radial slot (101), the lower limit of the target frequency that satisfies the physical constraint of the skin effect is calculated. Increase the modulation coefficient of the basic stator voltage vector and reallocate the duration of the voltage vector according to the target frequency lower limit to generate a high-frequency harmonic cluster covering the target frequency lower limit; The high-frequency harmonic cluster is discretized in the frequency domain to generate an overmodulated PWM pulse sequence, which is used as an overmodulation control signal and then output.

6. The method according to claim 5, characterized in that, The material parameters of the damping ring (10) and the depth of the radial slot (101) are selected based on the frequency, and the lower limit of the target frequency that satisfies the physical constraint of the skin effect is calculated using equation (2): Equation (2) in, The permeability of the damping ring (10) is selected for the frequency. The conductivity of the damping ring (10) is selected for the frequency. The depth of the radial slot (101).

7. The method according to claim 5, characterized in that, When increasing the modulation coefficient of the basic stator voltage vector, the amplitude of the basic stator voltage vector is dynamically limited according to the magnetic saturation constraint of the motor stator core (20).

8. The method according to claim 5, characterized in that, Before being input into the second-order extended state observer, the measured quantum current is filtered out by notch filtering to remove interference signals corresponding to the frequency components of the high-frequency harmonic cluster.

9. A high-speed brushless motor system, characterized in that, The system includes a stator, a motor rotor (30), and a frequency selective damping ring (10) as described in claim 1; the stator includes a motor stator core (20), and the frequency selective damping ring (10) is sleeved on the axial end of the motor stator core (20); the high-speed brushless motor system further includes a processor configured to perform an intelligent control method for a high-speed brushless motor for vacuuming as described in any one of claims 1-8.

10. The high-speed brushless motor system according to claim 9, characterized in that, The radial thickness of the frequency selective damping ring (10) is less than the skin depth of the material of the frequency selective damping ring (10) at the rated fundamental frequency of the motor.

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