Position-free sensing method for joint module based on rotating speed estimation and virtual Z correction

Abstract

The invention discloses a position-free sensing method for a joint module based on rotating speed estimation and virtual Z correction. The method comprises the following steps: firstly, acquiring three-phase current of a permanent magnet motor for a joint module, and acquiring d-axis estimated current of a current period based on a d-axis current model in combination with a state quantity of the permanent magnet motor in a previous control period; based on the d-axis estimated current, constructing a rotating speed estimator taking the d-axis estimated current error as a sliding mode surface to obtain the estimated rotating speed of the motor rotor; integrating the estimated rotating speed, and combining with the initial position of the rotor to obtain the estimated position of the motor rotor in the current period; at the same time, at the zero crossing point of the stator phase current, the estimation position is forcibly corrected to a predetermined electrical angle corresponding to the zero crossing point so as to eliminate the integral error. The invention aims to directly estimate the rotating speed without depending on any intermediate signal, and simulate the correction mechanism of a mechanical sensor to eliminate the estimation error, thereby realizing high-performance noise-free full-speed-domain position-free sensing control.

Description

Technical Field

[0001] This invention relates to the field of permanent magnet motor technology, and more specifically to a position-free sensing method for joint modules based on speed estimation and virtual Z-correction. Background Technology

[0002] Permanent magnet electric drive systems (surface-mounted permanent magnet synchronous motors (SPMSMs) or embedded permanent magnet synchronous motors (IPMSMs)) are widely used in robot joint actuation due to their compact structure, high torque density, and excellent operational stability. To achieve high-precision control of the joint module, two mechanical position sensors are typically required: one to detect the mechanical position of the PMSM rotor, and the other to detect the position of the outer ring of the joint after the reducer output. However, the presence of these two sensors increases the module's size and weight, raises system complexity, and reduces overall reliability. Therefore, in recent years, sensorless control methods have been considered a more promising approach for robot joint actuation because they can effectively eliminate the need for sensors on the motor itself.

[0003] Traditional sensorless control methods can be divided into two main categories based on their applicable speed range: in the zero-speed and low-speed range, high-frequency injection (HFI) and open-loop induction (IF) starting methods are mainly used; in the medium- and high-speed range, methods based on back electromotive force and flux linkage estimation are typically employed. These methods are mostly implemented by constructing observers, such as sliding mode observers (SMO), model reference adaptive systems, extended Kalman filters, and Luenberger observers.

[0004] Although the above methods have achieved sensorless control, the following problems still exist in robot applications: (1) The HFI method introduces high-frequency noise, and the additional injected signal reduces the maximum output torque of the motor. Although some researchers have reduced the noise by injecting random frequencies, the noise problem has not been fundamentally solved. At the same time, the HFI method relies on the inherent or magnetic reluctance mutation caused by the motor's magnetic saturation, making it difficult to be applied to both SPMSM and IPMSM simultaneously; (2) The IF starting method has low control accuracy and large losses; (3) The back EMF and flux linkage estimation method based on the observer is only suitable for medium and high speeds.

[0005] Furthermore, all the aforementioned methods share a common characteristic: they rely on "intermediate signals" to extract rotational speed and position information. For example, HFI relies on high-frequency response current as an intermediate signal, while observer methods rely on intermediate signals such as back EMF or flux linkage. This makes it difficult for a single method to cover the entire speed domain, necessitating method switching between different speed ranges. This not only increases system complexity but also requires extensive debugging experience to ensure the reliability of the switching.

[0006] In summary, it is necessary to design a position-free control method that is free of intermediate signals, noise, operates across the entire speed range, and is applicable to both SPMSM and IPMSM, in order to overcome the limitations of traditional methods. Summary of the Invention

[0007] In view of the above problems, the present invention is proposed to provide a position-sensorless method for joint modules based on rotational speed estimation and virtual Z-correction that overcomes or at least partially solves the above problems.

[0008] To achieve the above objectives, the present invention adopts the following technical solution: This invention provides a sensorless method for joint modules based on rotational speed estimation and virtual Z-correction, comprising the following steps: The three-phase current of the permanent magnet motor used in the joint module is collected, and combined with the state variables of the permanent magnet motor in the previous control cycle, the estimated d-axis current of the current cycle is obtained based on the d-axis current model. Based on the d-axis estimated current, a speed estimator with the d-axis estimated current error as the sliding surface is constructed to obtain the estimated speed of the motor rotor. Integrating the estimated rotational speed and combining it with the initial rotor position, the estimated position of the motor rotor in the current cycle is obtained; And at the zero-crossing point of the stator phase current, the estimated position is forcibly corrected to a predetermined electrical angle corresponding to the zero-crossing point.

[0009] Preferably, the state variables of the permanent magnet motor in the previous control cycle include the motor speed, rotor position, and d-axis control voltage estimated in the previous control cycle.

[0010] Preferably, the three-phase current of the permanent magnet motor used in the joint module is collected, and combined with the state variables of the permanent magnet motor in the previous control cycle, the estimated d-axis current for the current cycle is obtained based on the d-axis current model; including: Based on the rotor position estimated in the previous control cycle, the three-phase current is converted into the d-axis estimated current. and q-axis current estimation ; Calculate the differential value of the estimated d-axis current based on the following d-axis current model;

[0011] In the formula, This indicates the d-axis control voltage of the previous cycle. Rs represents the estimated motor speed from the previous cycle, and Rs represents the motor phase resistance. and These are the d-axis and q-axis inductances of the permanent magnet motor, respectively. The d-axis estimated current is obtained by integrating the differential value of the d-axis estimated current.

[0012] Preferably, the expression for the sliding surface is:

[0013] In the formula, This indicates the d-axis estimated current error. This indicates the estimated current along the d-axis. This represents the measured current along the d-axis; The sliding mode control law of the speed estimator is:

[0014] In the formula, This is the estimated rotational speed of the motor rotor in the current cycle. For the sliding mode gain of the speed estimator, For symbolic functions, This indicates the d-axis estimated current error.

[0015] Preferably, the sliding mode gain of the speed estimator The following stability constraints must be met:

[0016] In the formula, This indicates the preset rotation speed.

[0017] Preferably, the initial position is obtained through the following steps: A fixed voltage vector is applied to the stator windings of the motor to synthesize a magnetic field aligned with the axis of one phase, forcing the rotor poles to align to the zero position of the d-axis or the opposite direction. By detecting the current direction and winding connection method during the alignment process, the polarity of the rotor magnetic poles is determined, thereby determining whether the initial position of the rotor is 0 or π.

[0018] Preferably, at the zero-crossing point of the stator phase current, forcibly correcting the estimated position to a predetermined electrical angle corresponding to the zero-crossing point includes: Select one stator phase current as the target phase current, and determine the predetermined electrical angle corresponding to the zero-crossing point from the negative value to the positive value; During each electrical cycle, the target phase current is sampled using a sliding window, and the integral sum of the sampled values ​​within the window is calculated. When the integral approaches zero from a negative value and satisfies a preset threshold condition, it is determined that the sliding window contains the target zero-crossing point; Select two sampling points within the window, one negative and one positive, with the largest span, and use linear interpolation to calculate the precise zero-crossing time; At the precise zero-crossing point, the estimated rotor position value is reset to the predetermined electrical angle.

[0019] Preferably, in calculating the precise zero-crossing time using linear interpolation, the linear interpolation function includes:

[0020] In the formula, Indicates the c-phase current at The linear interpolation expression at time t, and They are respectively c Phase current m In the first of the electrical cycles and One sampling point, The sampling period is and All are sampling point indices; make The time passing through zero is obtained as follows:

[0021] In the formula, It is past midnight.

[0022] Preferably, the tracking rate TR is defined, and the estimation performance of the speed estimator is comprehensively evaluated based on four key indicators: steady-state error, steady-state fluctuation, transient error, and response delay.

[0023] Preferably, the expressions for the four key indicators are as follows:

[0024] In the formula, where, Indicates steady-state error. Indicates steady-state fluctuations. Indicates transient error. This indicates a response delay. and These are the estimated rotational speed and the actual rotational speed at the k-th sampling point, respectively. The sampling start time when the system response enters a steady state. This is the end time of the sampling window; its length is determined based on the specific application scenario. The sampling period is The system response start time, This represents the rise time difference as the velocity changes. and These are the rise times of the estimated speed and the actual speed, respectively. This represents the peak time difference during load changes. and These are the peak times for the estimated speed and the actual speed, respectively.

[0025] This invention provides a position-sensorless method for joint modules based on rotational speed estimation and virtual Z-correction. It aims to directly estimate rotational speed without relying on any intermediate signals and to simulate the correction mechanism of mechanical sensors to eliminate estimation errors, thereby achieving high-performance, noise-free, full-speed-domain position-sensorless control.

[0026] Compared with the prior art, the beneficial effects of the above-mentioned technical solutions provided by the embodiments of the present invention include at least the following: 1. Based on permanent magnet motor d A sliding mode direct speed estimator (SM-DSE) is constructed using the shaft current model to achieve direct estimation of the rotational speed; and the rotor position is obtained by integrating the estimated rotational speed, thus achieving noiseless and position-sensorless control across the entire speed domain. 2. A zero-crossing correction method based on virtual Z-pulse of photoelectric encoder is proposed. By compensating the final position based on the zero-crossing point in each electrical angle cycle, the accumulation of integral error can be effectively eliminated, thereby achieving high-precision and noiseless control in the full speed domain, making it more suitable for high-precision control scenarios of robot joint modules. 3. By defining the tracking rate (TR) of the estimated rotational speed, the position estimation error caused by the rotational speed integral and the low-pass filter can be accurately evaluated. Attached Figure Description

[0027] 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 embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0028] Figure 1 This is a structural diagram of the SM-DSE provided in an embodiment of the present invention.

[0029] Figure 2 This is a description diagram of the key TR indicators provided in the embodiments of the present invention.

[0030] Figure 3 This is a diagram showing the effect of TR on position error provided in an embodiment of the present invention.

[0031] Figure 4 This is a graph showing the relationship between position estimation error, TR, and number of actions provided in an embodiment of the present invention.

[0032] Figure 5 This is a specific zero-crossing point diagram of the three-phase current provided in the embodiment of the present invention.

[0033] Figure 6 This is a schematic diagram of the c-phase current zero-crossing detection method provided in an embodiment of the present invention. Detailed Implementation

[0034] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0035] This invention addresses the limitations of traditional low-speed sensorless control methods by proposing a sensorless method for joint modules based on rotational speed estimation and virtual Z-correction, applicable to the full-speed domain control of permanent magnet synchronous motors used in robot joint modules.

[0036] First, a sliding mode direct speed estimator (SM-DSE) is constructed based on the d-axis current model of a permanent magnet motor to directly estimate the rotational speed. The rotor position is obtained by integrating the estimated speed, achieving noiseless and sensorless control across the entire speed domain. This application is applicable to both surface-mounted and embedded permanent magnet synchronous motors. Second, by defining the tracking rate (TR) of the estimated speed, the position estimation error caused by speed integration and low-pass filtering is analyzed. The relationship between the error, TR, and the number of actions is analyzed through simulation of the joint module's motion state. Subsequently, to address the above problems, this invention proposes a zero-crossing correction method based on a virtual Z-pulse from a photoelectric encoder. By compensating for the final position based on the zero-crossing point in each electrical angle cycle, the accumulation of integral error is effectively eliminated, enabling high-precision, noiseless control across the entire speed domain. This method is highly suitable for high-precision control scenarios in robot joint modules.

[0037] In one embodiment, the flowchart of the joint module using a sensorless method based on rotational speed estimation and virtual Z-correction in this application includes the following steps: The three-phase current of the permanent magnet motor used in the joint module is collected, and combined with the state variables of the permanent magnet motor in the previous control cycle, the estimated d-axis current of the current cycle is obtained based on the d-axis current model. Based on the d-axis estimated current, a speed estimator with the d-axis estimated current error as the sliding surface is constructed to obtain the estimated speed of the motor rotor. Integrating the estimated rotational speed and combining it with the initial rotor position, the estimated position of the motor rotor in the current cycle is obtained; And at the zero-crossing point of the stator phase current, the estimated position is forcibly corrected to a predetermined electrical angle corresponding to the zero-crossing point to eliminate integration error.

[0038] In one specific embodiment, the electrical parameters of the permanent magnet motor are as follows: inductance is... L d =L q=0.167mH, resistance is R s =0.5Ω, rotor flux linkage is ψ f = 0.135 Wb ， The number of permanent magnets is p =4, the full-speed test speed is 1000 r / min, and the control cycle is T s = 0.0002 s, moment of inertia of the motor J =0.031, coefficient of friction B =0.008, the implementation process of achieving noiseless full-speed sensorless control and solving the accuracy degradation problem caused by low tracking rate is as follows: The first step is to collect the three-phase current of the permanent magnet motor used in the joint module, and combine it with the state variables of the permanent magnet motor in the previous control cycle to obtain the estimated d-axis current of the current cycle based on the d-axis current model. In this embodiment, the step includes: 1. First, measure the permanent magnet motor. a , b , c Three-phase current, denoted as i a , i b , i c And record the previous control cycle d The motor speed estimated by the shaft speed estimator and rotor position ,as well as d Shaft control voltage u d ; 2. Based on the rotor position estimated in the previous control cycle, after performing CLARK and PARK transformations, the three-phase current is calculated using the following formula. i a , i b , i c Convert to d-axis estimated current and q-axis current estimation ;

[0039] 3. Calculate the differential value of the estimated d-axis current based on the following d-axis current model;

[0040] In the formula, This indicates the d-axis control voltage of the previous cycle. Rs represents the estimated motor speed from the previous cycle, and Rs represents the motor phase resistance. and These are the d-axis and q-axis inductances of the permanent magnet motor, respectively. 4. Integrate the differential value of the estimated d-axis current to obtain the estimated d-axis current for the current period.

[0041] The second step is to construct a speed estimator based on the d-axis estimated current, with the d-axis estimated current error as the sliding surface, to obtain the estimated speed of the motor rotor. In this embodiment, the expression for the sliding surface is:

[0042] In the formula, This indicates the d-axis estimated current error. This indicates the estimated current along the d-axis. This represents the measured current along the d-axis; The sliding mode control law for the speed estimator is:

[0043] In the formula, This is the estimated rotational speed of the motor rotor in the current cycle. For the sliding mode gain of the speed estimator, For symbolic functions, This indicates the d-axis estimated current error.

[0044] As a preferred embodiment in this example, the sliding mode gain of the speed estimator The following stability constraints must be met:

[0045] In the formula, This indicates the preset rotation speed.

[0046] The third step is to integrate the estimated rotational speed and combine it with the initial rotor position to obtain the estimated position of the motor rotor in the current cycle; the expression is:

[0047] In the formula, This is the initial position of the motor rotor. This is the estimated rotational speed of the motor rotor in the current cycle.

[0048] In one embodiment, the present invention provides an initial position alignment method to ensure that the entire operation is completely noise-free.

[0049] This method, based on the principle of vector control, applies a fixed voltage vector to the stator windings and synthesizes a magnetic field aligned with the axis of one phase by directly turning on specific switches in the three-phase inverter bridge, thereby forcibly aligning the rotor to the desired position. d At the zero position of the shaft or its opposite direction, the three-phase current relationship satisfies the following equation:

[0050] The determined initial position corresponds to 0 or π Specifically, this depends on the polarity of the N and N poles, which in turn is affected by the current direction and the winding connection method. For example, when the current flows counterclockwise and the N pole is close to the winding side, the initial position is 0; otherwise, the initial position is... π In practical applications, polarity can be determined by detecting the direction of the current and the wiring method of the winding terminals.

[0051] The entire process of building the speed estimator, as described above, is as follows: Figure 1 As shown.

[0052] This invention achieves noiseless, sensorless control across the entire speed range and is applicable to both surface-mounted and embedded permanent magnet synchronous motors. The tracking performance of the speed estimator based on the sliding surface determines the magnitude of the position estimation error. If the tracking performance is poor, errors in speed estimation will accumulate during integration, leading to position estimation deviations.

[0053] To further optimize the above technical solution, this application defines the tracking rate TR and comprehensively evaluates the estimation performance of the speed estimator based on four key indicators: steady-state error, steady-state fluctuation, transient error, and response delay.

[0054] The expressions for the four key indicators are:

[0055] In the formula, where, Indicates steady-state error. Indicates steady-state fluctuations. Indicates transient error. This indicates a response delay. and These are the estimated rotational speed and the actual rotational speed at the k-th sampling point, respectively. The sampling start time when the system response enters a steady state. This is the end time of the sampling window, the length of which is determined based on the specific application scenario. The sampling period is The system response start time, This represents the rise time difference as the velocity changes. This indicates the peak time difference when the load changes.

[0056] Figure 2 A diagram illustrating four indicators is provided, among which... Indicates the given rotational speed.

[0057] Among the above key indicators, This reflects the long-term estimation accuracy of the velocity estimator. A large steady-state error indicates a bias, which, after integration, will cause significant cumulative position error, thus limiting its long-term use in robot joints. The long-term operational stability of the velocity estimator is reflected, which in turn affects the stability of the position estimation and consequently the stable operation of the robot joints. The transient error reflects the speed and robustness of the system. The larger the transient error, the worse the speed estimator's ability to respond to disturbances or sudden changes, thus affecting the joint's ability to handle external disturbances and its ability to execute quickly. Reflecting the lag between the estimated rotational speed and the actual rotational speed, the low-pass filter (LPF) in the speed estimator is the main source of lag. The longer the delay, the greater the position lag obtained by integration, which will affect the robot's fast response and control accuracy.

[0058] Furthermore, based on the above indicators, TR is defined as follows:

[0059] Where TR ∈ (0,1], a larger value indicates better performance, and 100% indicates complete tracking. p i The nonlinear amplification factor corresponding to each indicator ( p i >1), used to characterize its influence weight, performs exponentiation; the smaller the value, the greater the influence of the indicator on TR, and should be set according to the specific application scenario. Since this application is aimed at robot joint modules, it is set as follows: p 1=2、 p 2=3、 p 3=3、 p 4 = 2. E ss , E flu , E max and T d The normalized errors of the four indicators are defined as follows:

[0060] in, for The corresponding period.

[0061] In this application, to illustrate the impact of TR on position estimation error, a sliding mode speed estimator (SM-DSE) was used to simulate and analyze the robot joint motor. The motor's operating state was simulated through speed and load changes: the motor started from zero speed and accelerated to 500 rpm, then to 1000 rpm; a test load of 2.5 N·m was applied and removed during this process; subsequently, the speed decreased to 500 rpm, and the load was applied and removed again. SM-DSE was used throughout the process, and TR = 99% and TR = 88% were selected for comparative analysis. The results are as follows: Figure 3 As shown.

[0062] Depend on Figure 3 It can be seen that both TR values ​​can achieve reliable speed tracking with relatively small overall position estimation errors, verifying the feasibility of SM-DSE. However, compared to TR=99%, when TR=88%, the speed estimation error and fluctuation are larger, leading to a significant increase in position deviation and fluctuation after integration.

[0063] To better suit the application scenarios of robot joint modules, this invention further verifies the position estimation error under different TR and disturbance conditions by simulating the lifting action of a robotic arm. The entire lifting process lasts for 1 minute, with each complete reciprocating motion considered as one action. Within the allowable speed and load range of the joint, the speed and load of each action are randomly set. During this time, the joint motor provides driving force, and the SM-DSE is used for speed and position estimation. The maximum number of actions is set to 60, and the TR range is 88%–99%. The results are as follows: Figure 4 As shown.

[0064] from Figure 4 It can be seen that the lower the TR (True Position), the greater the position estimation error. Furthermore, as the number of actions increases, the estimation error gradually rises, indicating that the error accumulates during continuous movement. The lower the TR, the faster the error accumulates.

[0065] The above analysis shows the relationship between the position estimation error of SM-DSE and TR and the number of actions. To solve the above problems, a zero-crossing correction method based on the Z-pulse of a virtual photoelectric encoder is proposed below.

[0066] Step 4: At the zero-crossing point of the stator phase current, forcibly correct the estimated position to the predetermined electrical angle corresponding to the zero-crossing point.

[0067] In one implementation, the steps include: Virtual Z-pulse signal selection: In photoelectric encoders (PE), the position information recorded when the Z-pulse is triggered is typically used to represent the offset from the zero position. This offset is superimposed on the position calculation in each subsequent cycle for correction, thereby ensuring precise alignment between the encoder zero position and the rotor magnetic pole position. Inspired by this idea, this invention constructs a virtual Z-pulse based on the zero-crossing points of the three-phase current. Since the zero-crossing points of the three-phase current have a fixed phase relationship with the rotor position, they can be considered as virtual zero reference points. By identifying these positions, the position estimate can be periodically corrected. Taking one electrical cycle as an example, the specific zero-crossing points of the three-phase current are as follows: Figure 5 As shown.

[0068] This invention uses the zero-crossing point of the c-phase current as it changes from negative to positive for correction. The basic principle is: when the c-phase current changes from a negative value to a positive value by crossing the zero point, the corresponding electrical angle π / 3 is used as the final estimated position.

[0069] C-phase current zero-crossing point extraction: Based on the above principle, accurately extracting the negative-to-positive zero-crossing point of the C-phase current is crucial. Under the conditions of no-position sensing and no-load operation of a permanent magnet motor, the three-phase current is often affected by high-order harmonics and external disturbances, which may cause fluctuations in the zero-crossing region, making it difficult to reliably detect the true zero-crossing point. Therefore, this invention proposes a zero-crossing point detection method based on five-point sampling and interval integration. This method utilizes integration combined with a sliding window strategy, and simultaneously employs linear interpolation to achieve unique negative-to-positive zero-crossing point detection per cycle, making it suitable for digital control systems.

[0070] make i c [ k m ] is the first m In the first of the electrical cycles k sampling points c Phase current, system sampling frequency is f s The motor's operating frequency is f e Then the number of sampling points contained in each current cycle is:

[0071] No. m The sampling current within the sliding window during each cycle I ck m Defined as:

[0072] The sliding window slides backward at the sampling rate, meaning that within each sampling period, one sampling point enters the window and one sampling point leaves the window. A sliding window including zero crossings is detected by the following formula:

[0073] in ε The threshold that approaches zero; S ( k m ) indicates the first m The sum of the current integrals at five sampling points within a sliding window of one period. When S ( k m When a negative value gradually approaches zero and meets a threshold condition, it indicates that the window contains the unique zero-crossing point that changes from negative to positive in this period. To accurately determine the true zero-crossing point position in the window while ensuring real-time performance, two points are selected from the window and their precise positions are calculated using linear interpolation.

[0074] The selected two points must satisfy the condition that the first point is negative and the second point is positive. Accordingly, let the sampling point indices be as follows:

[0075] Then any two conditions that satisfy the above conditions must also satisfy:

[0076] Where 0≤ p < q ≤4. To improve accuracy and suppress false zero crossings, the pair of points with the largest span is preferentially selected to smooth local disturbances. The corresponding times for the two points are respectively k p m T s and k q m T s Thus, a linear interpolation function is constructed:

[0077] in t m ∈[ k p m T s , k q m T s ].make i c ( t m zero If ) = 0, then the zero-crossing time can be obtained:

[0078] Since the algorithm will be implemented on a DSP, the resulting... t m zero It needs to be mapped to the nearest discrete sampling point within the window. The final zero-crossing point. k m zero Obtained by rounding:

[0079] To further ensure that only a unique zero-crossing is detected within a single electrical cycle, this method does not begin detection at the start of each electrical cycle. Instead, it delays the detection window for the next cycle by 90% of the electrical cycle based on the zero-crossing detected in the previous cycle. This helps avoid false detections and reduces computational complexity. Figure 6 As shown.

[0080] Sampling start point for the next cycle satisfy:

[0081] To prevent DSP register overflow, in each cycle At the sampling point of the sliding window k m Reset to zero. Get each cycle. c Once the phase current crosses zero at its unique point of change from negative to positive, it can be used as a virtual Z-pulse for position correction. Specifically, at the zero-crossing point, the position used for closed-loop control is reset to [position value]. π / 3, to achieve periodic position correction:

[0082] The above method can effectively eliminate the cumulative error caused by integration and LPF, making the SM-DSE proposed in this invention more suitable for robot joint modules with high performance requirements.

[0083] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to the method section.

[0084] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A sensorless method for joint modules based on rotational speed estimation and virtual Z-correction, characterized in that, include: The three-phase current of the permanent magnet motor used in the joint module is collected, and combined with the state variables of the permanent magnet motor in the previous control cycle, the estimated d-axis current of the current cycle is obtained based on the d-axis current model. Based on the d-axis estimated current, a speed estimator with the d-axis estimated current error as the sliding surface is constructed to obtain the estimated speed of the motor rotor. Integrating the estimated rotational speed and combining it with the initial rotor position, the estimated position of the motor rotor in the current cycle is obtained; And at the zero-crossing point of the stator phase current, the estimated position is forcibly corrected to a predetermined electrical angle corresponding to the zero-crossing point.

2. The position-sensorless method for a joint module according to claim 1, characterized in that, The state variables of the permanent magnet motor in the previous control cycle include the estimated motor speed, rotor position, and d-axis control voltage of the previous control cycle.

3. The position-sensorless method for a joint module according to claim 1 or 2, characterized in that, The three-phase current of the permanent magnet motor used in the joint module is collected, and combined with the state variables of the permanent magnet motor in the previous control cycle, the estimated d-axis current for the current cycle is obtained based on the d-axis current model; including: Based on the rotor position estimated in the previous control cycle, the three-phase current is converted into the d-axis estimated current. and q-axis current estimation ; Calculate the estimated differential value of the d-axis current for the current period based on the following d-axis current model; In the formula, This indicates the d-axis control voltage of the previous cycle. Rs represents the estimated motor speed from the previous cycle, and Rs represents the motor phase resistance. and These are the d-axis and q-axis inductances of the permanent magnet motor, respectively. The estimated d-axis current for the current period is obtained by integrating the differential value of the estimated d-axis current for the current period.

4. The position-sensorless method for joint modules according to claim 1, characterized in that, The sliding mode control law of the speed estimator is: In the formula, This is the estimated rotational speed of the motor rotor in the current cycle. For the sliding mode gain of the speed estimator, For symbolic functions, This indicates the d-axis estimated current error.

5. The position-sensorless method for a joint module according to claim 4, characterized in that, The sliding mode gain of the speed estimator The following stability constraints must be met: In the formula, This indicates the preset rotation speed.

6. The position-sensorless method for a joint module according to claim 1, characterized in that, The initial position is obtained through the following steps: A fixed voltage vector is applied to the stator windings of the motor to synthesize a magnetic field aligned with the axis of one phase, forcing the rotor poles to align to the zero position of the d-axis or the opposite direction. By detecting the current direction and winding connection method during the alignment process, the polarity of the rotor magnetic poles is determined, thereby determining whether the initial position of the rotor is 0 or π.

7. The position-sensorless method for a joint module according to claim 1, characterized in that, At the zero-crossing point of the stator phase current, forcibly correcting the estimated position to a predetermined electrical angle corresponding to the zero-crossing point includes: Select one stator phase current as the target phase current, and determine the predetermined electrical angle corresponding to the zero-crossing point from the negative value to the positive value; During each electrical cycle, the target phase current is sampled using a sliding window, and the integral sum of the sampled values ​​within the window is calculated. When the integral approaches zero from a negative value and satisfies a preset threshold condition, it is determined that the sliding window contains the target zero-crossing point; Select two sampling points with the largest span, one negative and one positive, from the sliding window, and use linear interpolation to calculate the precise zero-crossing time. At the precise zero-crossing point, the estimated rotor position value is reset to the predetermined electrical angle.

8. The position-sensorless method for a joint module according to claim 7, characterized in that, In calculating the precise zero-crossing time using linear interpolation, the linear interpolation function includes: In the formula, Indicates the c-phase current at The linear interpolation expression at time t, and They are respectively c Phase current m In the first of the electrical cycles and One sampling point, The sampling period is and All are sampling point indices; make The time passing through zero is obtained as follows: In the formula, It is past midnight.

9. The position-sensorless method for a joint module according to claim 1, characterized in that, The tracking rate TR is defined, and the estimation performance of the speed estimator is comprehensively evaluated based on four key indicators: steady-state error, steady-state fluctuation, transient error, and response delay.

10. The position-sensorless method for a joint module according to claim 9, characterized in that, The expressions for the four key indicators are: In the formula, where, Indicates steady-state error. Indicates steady-state fluctuations. Indicates transient error. This indicates a response delay. and These are the estimated rotational speed and the actual rotational speed at the k-th sampling point, respectively. The sampling start time when the system response enters a steady state. This is the end time of the sampling window. The sampling period is The system response start time, This represents the rise time difference as the velocity changes. and These are the rise times of the estimated speed and the actual speed, respectively. This represents the peak time difference during load changes. and These are the peak times for the estimated speed and the actual speed, respectively.

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