Electric bed motor control method and electric bed

Abstract

The invention relates to the technical field of motor control, in particular to an electric bed motor control method and an electric bed, and the method comprises the steps: sampling a current ripple signal, carrying out the spectrum analysis of the current ripple signal, extracting a load resonant frequency, generating an anti-phase harmonic current, and injecting the anti-phase harmonic current into a motor winding at the starting moment of a motor; damping harmonic waves are injected into the motor winding in the motor pre-braking stage, and phase-synchronous reverse currents are injected into the motor winding in the motor main braking stage. Low-impact control over starting and stopping of the electric bed is achieved through an electromechanical energy hedging mechanism, and an existing electric bed electromechanical framework is compatible; at the starting moment of the motor, high-frequency resonance excitation force can be neutralized by injecting anti-phase harmonic current; kinetic energy is dissipated through damping harmonic waves in the pre-braking stage, and current reverse locking is applied in the main braking stage, so that the in-place residual amplitude approaches zero; and dynamic tuning control parameters are analyzed based on a real-time spectrum, so that the start-stop time under a variable load is relatively constant, and the problems of light-load overshoot and heavy-load hysteresis are solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of motor control, and particularly relates to a motor control method for an electric bed and the electric bed. BACKGROUND

[0002] The electric bed is driven by a motor to realize functions such as bed body lifting and backboard adjustment, and is widely applied to postoperative rehabilitation, long-term care and other scenes. The traditional electric bed adopts a motor cooperating with a speed reduction mechanism and is started and stopped through open-loop PWM control. However, the control mode has the following problems:

[0003] The trapezoidal acceleration and deceleration curve currently adopted causes discontinuous bed body movement and mechanical impact; fixed control parameters cannot adapt to dynamic load changes, causing adjustment delay or overshoot; and the coupling of the above defects causes mechanical impact to be transmitted to the human interface, especially for postoperative patients, and the discontinuity of movement may cause abnormal mechanical stress on the wound surface, affecting the rehabilitation process. SUMMARY

[0004] The present application provides a motor control method for an electric bed and the electric bed, which can effectively solve the problems in the background art.

[0005] In order to achieve the above purpose, the technical solution adopted by the present application is:

[0006] A motor control method for an electric bed, comprising:

[0007] At the moment of starting the motor, a current ripple signal is sampled, the current ripple signal is subjected to frequency spectrum analysis, a load resonance frequency is extracted, an anti-phase harmonic current is generated based on the load resonance frequency, and is injected into the motor winding;

[0008] A damping harmonic is injected into the motor winding during the motor pre-braking stage, and a phase-synchronous reverse current is injected into the motor winding during the motor main braking stage.

[0009] Further, when it is detected that the extracted load resonance frequency exceeds a set threshold, an inertial weighted filter is used to update the load resonance frequency; the anti-phase harmonic current is generated based on the updated load resonance frequency, and the update adopts the following formula:

[0010] ;

[0011] In the formula,

[0012] f res is the updated load resonance frequency;

[0013] f last is the historically stored load resonance frequency;

[0014] f new is the currently extracted load resonance frequency;

[0015] α and β are respectively a first coefficient and a second coefficient, and α+β=1.

[0016] Further, the determination method of the first coefficient α and the second coefficient β comprises:

[0017] stiffness calibration is performed on the target electric bed transmission system to obtain a stiffness value;

[0018] A step load is applied in the range from no load to full load, and response data of the load resonant frequency changing over time is collected;

[0019] Based on the stiffness value and the response data, the value of the first coefficient α is calculated by an optimization function, the optimization function aims to balance the response speed and stability, and the optimization function is:

[0020] ;

[0021] In the formula, σ f is the standard deviation of frequency fluctuation, and γ is positively correlated with the stiffness value;

[0022] The second coefficient β is calculated according to β=1-α.

[0023] Further, the current ripple signal is subjected to frequency spectrum analysis to extract the load resonant frequency, which comprises:

[0024] The current ripple signal is processed by using a fast Fourier transform algorithm to obtain the frequency spectrum distribution in the frequency band of 50-500Hz;

[0025] Local amplitude maximum points with an amplitude higher than the base noise by more than 10dB are identified in the frequency band to form a preliminary screening peak value set;

[0026] The frequency band width of each peak value in the preliminary screening peak value set is calculated to identify candidate peak values with a frequency band width less than 10Hz;

[0027] The candidate peak value with the highest amplitude is selected as the load resonant frequency.

[0028] Further, the anti-phase harmonic current is generated by using the following formula:

[0029] ;

[0030] In the formula,

[0031] I c is the anti-phase harmonic current;

[0032] I a is the compensation current amplitude;

[0033] f0 is the load resonance frequency;

[0034] n is an odd harmonic order number;

[0035] t is a time reference variable.

[0036] Further, the anti-phase harmonic current is converted into a PWM duty cycle instruction by the H-bridge driving circuit, and the PWM duty cycle instruction is applied to the power input end of the motor winding to realize current injection.

[0037] Further, before the frequency spectrum analysis, it further comprises:

[0038] The sampling time window of the current ripple signal is set as an integer multiple of the power frequency period of the power grid.

[0039] The reference frequency spectrum distribution under the no-load working condition of the motor is pre-stored, and the amplitude component corresponding to the reference frequency spectrum distribution is subtracted from the measured frequency spectrum distribution.

[0040] Further, the sampling of the current ripple signal is completed within 3-10ms after the motor starts.

[0041] Further, the pre-braking stage is triggered when the zero-crossing offset of the motor current is greater than 5us for 3 consecutive power frequency periods, and the main braking stage is triggered when the zero-crossing offset of the motor current is less than 2us for 2 consecutive power frequency periods in the pre-braking stage.

[0042] An electric bed adopts the electric bed motor control method as described above.

[0043] The technical scheme of the present application can achieve the following technical effects:

[0044] The present application realizes low-impact control of the electric bed start-stop through the mechanism of mechanical and electrical energy hedging, is compatible with the existing mechanical and electrical architecture of the electric bed, analyzes the load-transmission system resonance frequency in real time using the motor starting transient current ripple spectrum, and does not require structural modification; at the moment of motor starting, the high-frequency resonance excitation force can be neutralized by injecting an anti-phase harmonic current, and the acceleration step mutation can be eliminated; in the pre-braking stage, the kinetic energy is dissipated by damping harmonics, and in the main braking stage, the current is reversed to lock, so that the residual amplitude tends to zero; based on real-time spectrum analysis, the control parameters are dynamically tuned to ensure constant start-stop time under varying loads, and to solve the problems of light load overshoot and heavy load delay. BRIEF DESCRIPTION OF DRAWINGS

[0045] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0046] Figure 1 A flowchart of the electric bed motor control method;

[0047] Figure 2 A flowchart illustrating the method for determining the first coefficient α and the second coefficient β;

[0048] Figure 3 This is a flowchart of the spectrum analysis;

[0049] Figure 4 This is a flowchart of the electric bed motor control method at the moment of motor startup. Detailed Implementation

[0050] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0051] Example 1

[0052] like Figure 1 As shown, an electric bed motor control method includes:

[0053] At the moment of motor startup, the current ripple signal is sampled, the current ripple signal is subjected to spectrum analysis, the load resonant frequency is extracted, and an anti-phase harmonic current is generated based on the load resonant frequency and injected into the motor winding.

[0054] Damping harmonics are injected into the motor windings during the pre-braking phase, and a phase-synchronized reverse current is injected into the motor windings during the main braking phase.

[0055] This invention achieves low-impact control of electric bed start-up and shutdown through an electromechanical energy counterbalancing mechanism, compatible with existing electric bed electromechanical architectures. It utilizes the real-time analysis of the load-transmission system resonant frequency using the transient current ripple spectrum during motor start-up, requiring no structural modifications. At the moment of motor start-up, injecting anti-phase harmonic current neutralizes the high-frequency resonant excitation force, eliminating acceleration step jumps. During the pre-braking phase, kinetic energy is dissipated through damped harmonics. In this embodiment, the current amplitude of the damped harmonics is dynamically calculated based on the real-time kinetic energy at the pre-braking start point and the calibrated transmission damping coefficient. During the main braking phase, current reverse locking is applied, making the residual amplitude approach zero upon arrival. Based on real-time spectrum analysis and dynamic tuning of control parameters, the start-up and shutdown times are kept constant under varying loads, solving the problems of overshoot under light loads and hysteresis under heavy loads.

[0056] To cope with the problem of load mutation, as a preferred embodiment, when the extracted load resonance frequency is detected to exceed the set threshold, the inertia weighted filtering is adopted to update the load resonance frequency; the anti-phase harmonic current is generated based on the updated load resonance frequency, and the update adopts the following formula:

[0057] ;

[0058] In the formula,

[0059] f res is the updated load resonance frequency;

[0060] f last is the historically stored load resonance frequency;

[0061] f new is the currently extracted load resonance frequency;

[0062] α and β are respectively the first coefficient and the second coefficient, and α+β=1.

[0063] In the load mutation scenario, such as the patient suddenly getting up, when the load resonance frequency change amount is detected to exceed the preset threshold, the preferred solution realizes the rapid update of the frequency value through the inertia weighted filtering. The filtering mechanism generates the update value by f last Reserve the long-term stable resonance state memory of the system, avoid the control instability under the mutation interference, f last in the embodiment refers to the load resonance frequency value that is verified for multiple times and determined to be optimal in the stable operation state of the system, and is continuously refreshed during the operation process. The gradually changed f res output through the weighted filtering makes the generated anti-phase harmonic current always accurately phase-matched with the mechanical resonance, and suppresses the vibration acceleration change rate under the load mutation in a lower range.

[0064] As a preferred embodiment, the threshold value can be selected as 2Hz. On the one hand, this value can effectively isolate physiological interference, and on the other hand, it can ensure that the real mutation is captured. Of course, this value is only a preferred value, and other values that can achieve the technical purpose of the present application are also within the protection scope of the present application. For the first coefficient α and the second coefficient β, specific values can be selected, such as α=0.7 and β=0.3. This is a preferred value selection method. As another embodiment, as shown in the formula, the determination method of the first coefficient α and the second coefficient β can include: Figure 2

[0065] A1: stiffness calibration is performed on the target electric bed transmission system to obtain the stiffness value;

[0066] ​A2: Apply a step load in the range of no load to full load, collect the response data of the load resonant frequency changing with time;

[0067] A3: Calculate the value of the first coefficient α based on the stiffness value and the response data, through an optimization function, the optimization function aims to balance the response speed and stability, the optimization function is:

[0068] ;

[0069] In the formula, σ f is the standard deviation of frequency fluctuation, γ is positively correlated with the stiffness value; is the updated load resonant frequency f res The derivative of time t, that is, f res The rate of change with time t;

[0070] A4: Calculate the second coefficient β according to β = 1-α.

[0071] In the preferred embodiment, the stiffness value can be obtained by first applying a known static load to the bed body, measuring the transmission shaft deformation, and finally taking the ratio of the known static load and the transmission shaft deformation as the calibrated stiffness value; σ f It can be calculated by the stored resonant frequency values of the last N control periods.

[0072] In step A3, α is an optimization variable, and the target term includes a speed term and a stability term; in step A1, the physical calibration of the transmission system stiffness converts the bed body mechanical characteristics into control parameter design basis, providing static structure parameters for step A3; step A2 provides dynamic behavior data for step A3, and the instantaneous change rate of the load resonant frequency and the standard deviation of the frequency fluctuation are both obtained based on the response data.

[0073] As a preferred embodiment of the above embodiment, as shown in Figure 3 , the current ripple signal is subjected to frequency spectrum analysis, and the load resonant frequency is extracted, including:

[0074] B1: Process the current ripple signal using a fast Fourier transform algorithm to obtain the frequency spectrum distribution in the frequency band of 50~500Hz;

[0075] B2: Identify the local amplitude maximum value points with an amplitude higher than the base noise by more than 10dB in the frequency band to form a preliminary screening peak value set;

[0076] B3: Calculate the frequency band width of each peak value in the preliminary screening peak value set, and identify the candidate peak values with a frequency band width less than 10Hz;

[0077] B4: Select the candidate peak value frequency with the highest amplitude as the load resonant frequency.

[0078] In the preferred solution, setting the lower limit of 50 Hz can exclude power frequency interference and avoid the influence of motor fundamental noise on the detection accuracy of the resonance frequency, and the upper limit of 500 Hz can shield noise unrelated to the mechanical resonance of the load; the fast Fourier transform algorithm meets the real-time requirements of the embedded system, can directly extract the frequency energy distribution from the time domain current ripple signal, and accurately locate the resonance peak.

[0079] Through the preferred solution, the load resonance frequency can be accurately extracted in a strong electromagnetic noise environment, and through the dual screening of amplitude and bandwidth, the motor tooth slot harmonic, PWM switching noise and other wideband interference can be effectively eliminated, and real-time narrowband resonance detection ensures that the anti-phase harmonic current accurately matches the mechanical characteristics of the load.

[0080] As a preferred embodiment of the above, the anti-phase harmonic current is generated, and the following formula is used:

[0081] ;

[0082] In the formula,

[0083] I c is the anti-phase harmonic current;

[0084] I a is the compensation current amplitude, which is a fixed preset value in the embodiment;

[0085] f0 is the load resonance frequency;

[0086] n is an odd harmonic number, and this parameter is set because the non-linear vibration of the electric bed speed reduction mechanism excites odd harmonics;

[0087] t is a time reference variable, which represents the real-time time calculated from the start point of the current control period, and is reset to zero at the start point of each PWM control period and linearly increases within the period.

[0088] As a preferred embodiment of the above, as shown in Figure 4 , the anti-phase harmonic current is converted into a PWM duty ratio command through an H-bridge drive circuit, and the PWM duty ratio command is applied to the power input end of the motor winding to realize current injection. In the preferred solution, the power input end is the gate drive pin of the MOSFET in the H-bridge circuit, and the PWM duty ratio command value is converted into a high-low level signal through a gate driver chip.

[0089] As a preferred embodiment of the above, before frequency spectrum analysis, it also includes:

[0090] The sampling time window of the current ripple signal is set as an integer multiple of the power frequency period of the power grid;

[0091] The reference spectrum distribution under the no-load working condition of the motor is pre-stored, and the amplitude component corresponding to the reference spectrum distribution is subtracted from the measured spectrum distribution point by point.

[0092] In the preferred scheme, the sampling window is strictly aligned with an integer multiple of the power grid cycle, so that the power frequency interference energy is self-canceled in the spectrum analysis; based on the pre-stored no-load spectrum tooth slot harmonic fingerprint feature, the reference component is subtracted point by point in the frequency domain to eliminate the masking effect of the electromagnetic noise of the motor itself on the load resonance feature.

[0093] As a preferred embodiment of the above-mentioned embodiment, the sampling current ripple signal is completed within 3-10 ms after the motor starts. The above-mentioned time covers the electromagnetic transient process during the start of the motor, including the establishment of the stator current and the initial positioning of the rotor, at this time, the load resonance feature has not been damped by the mechanical damping, and the spectrum energy is most significant. Through the execution of this time, the frequency noise pollution signal introduced by the rotor inertia motion can be avoided earlier than the mechanical vibration stable time.

[0094] As a preferred embodiment of the above-mentioned embodiment, the pre-braking stage is triggered when the zero-crossing offset of the motor current is greater than 5 us for 3 consecutive power frequency cycles, and the main braking stage is triggered when the zero-crossing offset of the motor current is less than 2 us for 2 consecutive power frequency cycles in the pre-braking stage.

[0095] For the triggering of the pre-braking stage, the zero-crossing offset greater than 5 us indicates that the motor back electromotive force waveform is distorted, and the duration of three cycles can exclude transient interference such as PWM switching noise interference; and for the triggering of the main braking stage, the offset less than 2 us indicates that the system has recovered to stable, and the maintenance of 2 power frequency cycles can ensure the robustness of state switching and avoid the influence of random noise. The preferred scheme realizes accurate control of the two stages by using a single current zero-crossing signal.

[0096] Embodiment two

[0097] An electric bed adopts the electric bed motor control method as described in embodiment one. The technical effects realized by the present embodiment are as described in embodiment one, which will not be described here.

[0098] Those skilled in the art should understand that the present application is not limited by the above-mentioned embodiments, and the above-mentioned embodiments and descriptions in the specification are only to illustrate the principles of the present application. Without departing from the spirit and scope of the present application, various changes and improvements can be made to the present application, and these changes and improvements all fall within the scope of the claimed present application. The scope of protection of the present application is defined by the appended claims and their equivalents.

Claims

1. A method of controlling an electric motor of an electric bed, characterized in that, Comprising: At the moment of motor starting, sample the current ripple signal, perform spectral analysis on the current ripple signal, extract the load resonance frequency, generate anti-phase harmonic current based on the load resonance frequency, and inject the motor winding; During the motor pre-braking stage, inject damping harmonic into the motor winding, and during the motor main braking stage, inject phase-synchronous reverse current into the motor winding.

2. The power bed motor control method of claim 1, wherein, When it is detected that the extracted load resonance frequency exceeds a set threshold, update the load resonance frequency using inertial weighted filtering; generate the anti-phase harmonic current based on the updated load resonance frequency, and update using the following formula: ； In the formula, f res is the updated load resonance frequency; f last Load resonant frequency stored for history; f new fres the current extracted load resonance frequency; α and β are the first coefficient and the second coefficient respectively, and α+β=1.

3. The power bed motor control method of claim 2, wherein, The determination method of the first coefficient α and the second coefficient β comprises: Calibrate the stiffness of the target electric bed transmission system to obtain the stiffness value; Apply a step load within the no-load to full-load range, and collect the response data of the load resonance frequency changing over time; Based on the stiffness value and the response data, calculate the value of the first coefficient α by an optimization function, which aims to balance the response speed and stability, and the optimization function is: ； where σ f is the standard deviation of the frequency fluctuations, and γ is positively correlated with the stiffness value. Calculate the second coefficient β according to β=1-α.

4. The power bed motor control method of claim 1, wherein, The spectral analysis on the current ripple signal to extract the load resonance frequency comprises: Process the current ripple signal using the fast Fourier transform algorithm to obtain the frequency spectrum distribution within the frequency band of 50~500Hz; Identify the local amplitude maximum value points with amplitude higher than 10dB above the base noise within the frequency band to form a preliminary screening peak value set; Calculate the frequency band width of each peak value in the preliminary screening peak value set, and identify the candidate peak value with frequency band width less than 10Hz; Select the highest amplitude candidate peak value frequency as the load resonance frequency.

5. The power bed motor control method of claim 1, wherein, Generate the anti-phase harmonic current using the following formula: ； In the formula, I c is the anti-phase harmonic current; I a to compensate for current amplitude; f0 is the load resonance frequency; n is the odd harmonic number; t is the time reference variable.

6. The electric bed motor control method according to claim 1 or 5, wherein Convert the anti-phase harmonic current into PWM duty cycle command through the H-bridge drive circuit, and apply the PWM duty cycle command to the power input end of the motor winding to realize current injection.

7. The power bed motor control method of claim 1, wherein, Before the spectral analysis, it further comprises: Set the sampling time window of the current ripple signal as an integer multiple of the power frequency cycle of the power grid; Pre-store the reference frequency spectrum distribution under the no-load working condition of the motor, and subtract the amplitude component corresponding to the reference frequency spectrum distribution from the measured frequency spectrum distribution point by point.

8. The power bed motor control method of claim 1, wherein, Sampling the current ripple signal is completed within 3~10ms after the motor starts.

9. The power bed motor control method of claim 1, wherein, The pre-braking stage is triggered when the zero-crossing offset of the motor current appears for more than 5us for 3 consecutive power frequency cycles, and the main braking stage is triggered when the zero-crossing offset of the motor current appears for less than 2us for 2 consecutive power frequency cycles within the pre-braking stage.

10. An electric bed, characterized in that Use the electric bed motor control method as claimed in any one of claims 1~9.

Images