Filtering method for hall position sensor bias signal of robot joint

Abstract

The application discloses a filtering method for a Hall position sensor deviation signal of a robot joint, and comprises the following steps: acquiring the duration of each Hall state when a motor is running; calculating the current Hall average duration, the previous Hall average duration and the Hall average duration before the previous Hall average duration according to the duration of each Hall state; judging the running state of the motor according to the rotating speed; if the motor is in the acceleration and deceleration state, calculating the ideal duration of the current Hall state by a three-step filter combined with a linear extrapolation filtering method; and if the motor is in the steady running state, calculating the ideal duration of the current Hall state by a six-step filter combined with a linear extrapolation filtering method. The embodiment of the application gives two filters for different running states of the motor to achieve the best filtering effect. The filtering method provided by the embodiment of the application avoids the absolute position deviation and the rotor estimated position deviation.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of servo motors, in particular to a filtering method for a Hall position sensor deviation signal of a robot joint. BACKGROUND

[0002] Permanent magnet synchronous motors use permanent magnets for excitation, greatly reducing the volume and mass of the motor, and have good application space in industrial robots.

[0003] Hall sensors are a position sensor for synchronous motor vector control. When estimating the position, the traditional method is to estimate the rotor position based on the current sector time and six absolute positions. If the Hall position deviates, it will often cause the absolute position to deviate, thereby causing the rotor estimated position to deviate.

[0004] Therefore, how to correct the position of the Hall sector to avoid the rotor estimated position deviation caused by the deviation of the Hall sensor position has become a problem to be solved. SUMMARY

[0005] Therefore, the present application provides a filtering method for a Hall position sensor deviation signal of a robot joint to solve the problem that the Hall sensor position deviates, which often causes the absolute position to deviate, thereby causing the rotor estimated position to deviate.

[0006] The present application provides a filtering method for a Hall position sensor deviation signal of a robot joint, comprising:

[0007] Obtain the duration of each Hall state during motor operation;

[0008] Calculate the current Hall average duration, the previous Hall average duration, and the previous Hall average duration according to the duration of each Hall state;

[0009] Determine the running state of the motor according to the speed;

[0010] If the motor is in acceleration and deceleration state, the ideal duration of the current Hall state is calculated by a three-step filter combined with linear extrapolation filtering method;

[0011] If the motor is in steady running state, the ideal duration of the current Hall state is calculated by a six-step filter combined with linear extrapolation filtering method.

[0012] Optionally, the three-step filter is set as:

[0013]

[0014] τ is the current Hall state duration time; n represents the index of the current time; τ(n-m) represents the duration time of the mth historical Hall state, which is used to estimate the current ideal duration time; represents the filtering value at the current time when a three-step filter is used;

[0015] The six-step filter is set as:

[0016]

[0017] wherein, bm is the filter coefficient; M is the order; the three-step filter six-step filter represents the filtering value at the current time when a six-step filter is used;

[0018] Optionally, the duration time of each Hall state when the motor is running is obtained, comprising:

[0019] The duration time of the first Hall state, the duration time of the second Hall state, the duration time of the third Hall state and the duration time of the fourth Hall state are obtained.

[0020] Wherein, the duration time τ(n-3) of the first Hall state represents the duration time when the rising edge of the A-phase Hall sensor is triggered and the falling edge of the C-phase Hall sensor is triggered; the duration time τ(n-2) of the second Hall state represents the duration time when the falling edge of the C-phase Hall sensor is triggered and the rising edge of the B-phase Hall sensor is triggered; the duration time τ(n-1) of the third Hall state represents the duration time when the rising edge of the B-phase Hall sensor is triggered and the falling edge of the A-phase Hall sensor is triggered; the duration time τ(n) of the fourth Hall state represents the duration time when the falling edge of the A-phase Hall sensor is triggered and the rising edge of the C-phase Hall sensor is triggered.

[0021] Optionally, the extrapolation filtering method comprises:

[0022] The linear extrapolation result of the current Hall state duration time is obtained according to the difference between twice the duration time of the previous Hall state and the duration time of the Hall state before the previous Hall state:

[0023] τ ex_l = 2τ(k-1)-τ(k-2)

[0024] Wherein, τ ex_l is linear extrapolation based on two-step history; k is a natural number.

[0025] Optionally, the current Hall average duration time, the previous Hall average duration time and the Hall average duration time before the previous Hall average duration time are calculated according to the duration time of each Hall state, comprising:

[0026] The current Hall average duration time is calculated:

[0027] τ ex_l (i) = 2τ(i-1) - τ(i-2)

[0028] Calculate the previous Hall average duration:

[0029] τ ex_l (i-1) = 2τ(i-2) - τ(i-3)

[0030] Calculate the duration of the previous Hall state:

[0031] τ ex_l (i-2) = 2τ(i-3) - τ(i-4)

[0032] Where i is a natural number.

[0033] Optionally, the ideal duration of the current Hall state is calculated by a three-step filter combined with a linear extrapolation filter method, including:

[0034]

[0035] Where t is a natural number.

[0036] Optionally, after determining that the motor is in a steady running state according to the rotating speed, the method further includes:

[0037] Obtain the duration of the previous seven Hall states;

[0038] The ideal duration of the current Hall state is calculated by a six-step filter combined with a linear extrapolation filter method, including:

[0039]

[0040] Where t is a natural number.

[0041] The beneficial effects of the embodiments of the present application are:

[0042] The embodiments of the present application provide a filtering method for a Hall position sensor deviation signal of a robot joint, two filters are given for different running states of the motor to achieve the best filtering effect, and the filtering method provided by the embodiments of the present application avoids the case that the rotor estimated position deviates due to the absolute position deviation. BRIEF DESCRIPTION OF DRAWINGS

[0043] The features and advantages of the present application can be more clearly understood by referring to the accompanying drawings, which are schematic and should not be construed as limiting the present application, and in the drawings:

[0044] Figure 1A flow chart of a method for filtering a Hall position sensor deviation signal of a robot joint is shown in the embodiments of the present application.

[0045] Figure 2 A waveform diagram of the duration of each Hall state when the motor is running is shown in the embodiments of the present application.

[0046] Figure 3 A schematic diagram of a method for calculating the duration of a current ideal Hall state is shown in the embodiments of the present application. DETAILED DESCRIPTION

[0047] To make the objectives, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some but not all of the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of protection of the present application.

[0048] The embodiments of the present application provide a method for filtering a Hall position sensor deviation signal of a robot joint, as shown in Figure 1 The method comprises the following steps:

[0049] In step S10, the duration of each Hall state when the motor is running is obtained.

[0050] For the convenience of analysis, a logic signal (0 or 1) of 180° electrical angle output of the Hall sensor is set; wherein, “0” is a low level; and “1” is a high level.

[0051] In step S20, the current Hall average duration, the previous Hall average duration and the Hall average duration before the previous one are calculated according to the duration of each Hall state.

[0052] In the embodiments, the duration of the first Hall state, the duration of the second Hall state, the duration of the third Hall state and the duration of the fourth Hall state are obtained; wherein, the duration of the first Hall state τ(n-3) represents the duration when the rising edge of the A-phase Hall sensor is triggered and the falling edge of the C-phase Hall sensor is triggered; the duration of the second Hall state τ(n-2) represents the duration when the falling edge of the C-phase Hall sensor is triggered and the rising edge of the B-phase Hall sensor is triggered; the duration of the third Hall state τ(n-1) represents the duration when the rising edge of the B-phase Hall sensor is triggered and the falling edge of the A-phase Hall sensor is triggered; and the duration of the fourth Hall state τ(n) represents the duration when the falling edge of the A-phase Hall sensor is triggered and the rising edge of the C-phase Hall sensor is triggered.

[0053] The rising edge of the duration τ(n-3) and the falling edge of the duration τ(n-1) correspond to the switching of the same phase sensor (here, the A-phase Hall sensor).

[0054] In step S30, the running state of the motor is determined according to the rotating speed.

[0055] If the motor is in the acceleration or deceleration state, step S401 is performed to calculate the ideal duration of the current Hall state by a three-step filter combined with a linear extrapolation filter.

[0056] If the motor is in the steady running state, step S402 is performed to calculate the ideal duration of the current Hall state by a six-step filter combined with a linear extrapolation filter.

[0057] In the embodiment, the application provides a filtering method for the Hall position sensor deviation signal of a robot joint, two filters are given for different running states of the motor to achieve the best filtering effect. In addition, the average filtering method provided by the application is used to adjust the Hall state duration to correct the position of the Hall sector, avoiding the deviation of the absolute position and the deviation of the rotor estimated position.

[0058] As an optional implementation, the three-step filter is set as:

[0059]

[0060] The six-step filter is set as:

[0061]

[0062] wherein, b m is a filter coefficient; and M is an order.

[0063] As an optional implementation, the duration of each Hall state during the running of the motor is obtained, including:

[0064] As an optional implementation, the extrapolation filter method includes:

[0065] The linear extrapolation result of the duration of the current Hall state is obtained according to the difference between twice the duration of the previous Hall state and the duration of the Hall state before the previous Hall state:

[0066] τ ex_l = 2τ(k-1)-τ(k-2)

[0067] wherein, τ ex_l is the linear extrapolation based on two-step history; and k is a natural number.

[0068] In the embodiment, the linear extrapolation result of the current Hall state duration time is calculated by the historical values of the previous two Hall state duration times, so as to better cope with the acceleration and deceleration of the motor.

[0069] As an optional implementation, the current Hall average duration time, the previous Hall average duration time and the further previous Hall average duration time are calculated according to the duration time of each Hall state, including:

[0070] The current Hall average duration time is calculated as:

[0071] τ ex_l (i) = 2τ(i-1) - τ(i-2)

[0072] The previous Hall average duration time is calculated as:

[0073] τ ex_l (i-1) = 2τ(i-2) - τ(i-3)

[0074] The further previous Hall average duration time is calculated as:

[0075] τ ex_l (i-2) = 2τ(i-3) - τ(i-4)

[0076] Wherein, i is a natural number.

[0077] As an optional implementation, the ideal duration time of the current Hall state is calculated by a three-step filter combined with a linear extrapolation filter method, including:

[0078]

[0079] Wherein, t is a natural number.

[0080] As an optional implementation, after judging that the running state of the motor is a steady running state according to the rotating speed, further including:

[0081] The duration times of the previous seven Hall states are obtained;

[0082] The ideal duration time of the current Hall state is calculated by a six-step filter combined with a linear extrapolation filter method, including:

[0083]

[0084]

[0085] Wherein, t is a natural number.

[0086] In a specific embodiment, the values of the Hall duration times τ(n-1), τ(n-2), τ(n-3), τ(n-4) are obtained:

[0087] τ(n-1) = 0.9 ms

[0088] τ(n-2) = 0.8 ms

[0089] τ(n-3) = 1.1 ms

[0090] τ(n-4) = 0.8 ms

[0091] Current Hall average duration:

[0092] τ ex_l (n) = 2τ(n-1) - τ(n-2) = 2*0.9 - 0.8 = 1 ms

[0093] Previous Hall average duration:

[0094] τ ex_l (n-1) = 2τ(n-2) - τ(n-3) = 2*0.8 - 1.1 = 0.5 ms

[0095] Further previous Hall average duration:

[0096] τ ex_l (n-2) = 2τ(n-3) - τ(n-4) = 2*1.1 - 0.8 = 1.4 ms

[0097] When the motor speed is obtained to determine that the motor is in a non-stable running state, a three-step filter combined with a linear extrapolation filter method is used to calculate the ideal Hall state duration:

[0098]

[0099] The three-step filter is:

[0100]

[0101] When the motor speed is obtained to determine that the motor is in a stable running state, the values of τ(n-5), τ(n-6), and τ(n-7) are obtained:

[0102] τ(n-5) = 1 ms

[0103] τ(n-6) = 0.9 ms

[0104] τ(n-7) = 1.2 ms

[0105] The previous Hall average duration of the further previous Hall average duration is:

[0106] τ ex_l (n-3) = 2τ(n-4) - τ(n-5) = 2*0.8 - 1 = 0.6 ms

[0107] The re-rearward Hall average duration of the re-rearward Hall average duration of the re-rearward Hall average duration is:

[0108] τ ex_l (n-4)=2τ(n-5)-τ(n-6)=2*1-0.9=1.1ms

[0109] The re-rearward Hall average duration of the re-rearward Hall average duration of the re-rearward Hall average duration is:

[0110] τ ex_l (n-5)=2τ(n-6)-τ(n-7)=2*0.9-1.2=0.6ms

[0111] The ideal Hall state duration is calculated using a six-step filter combined with a linear extrapolation filter method:

[0112]

[0113] The six-step filter is:

[0114]

[0115] As described above, the embodiment of the application provides a filtering method for the deviation signal of the Hall position sensor of the robot joint, two filters are given for different operating states of the motor to achieve the best filtering effect, and the filtering method provided by the embodiment of the application avoids the deviation of the absolute position, so that the rotor estimated position is deviated.

[0116] Although the embodiments of the application are described in conjunction with the drawings, various modifications and changes can be made by those skilled in the art without departing from the spirit and scope of the application, and such modifications and changes fall within the scope defined by the appended claims.

Claims

1. A filtering method for Hall position sensor deviation signals of robot joints, characterized in that, include: Obtain the duration of each Hall state during motor operation; Calculate the current Hall average duration, the previous Hall average duration, and the previous Hall average duration based on the duration of each Hall state; The operating status of the motor is determined based on its rotational speed; If the motor is in an acceleration or deceleration state, the ideal duration of the current Hall state is calculated by a three-step filter combined with a linear extrapolation filter method. If the motor is in a steady-speed operation state, the ideal duration of the current Hall state is calculated by using a six-step filter combined with a linear extrapolation filter method. The three-step filter is configured as follows: τ represents the duration of the current Hall state; n represents the index of the current time; τ(nm) represents the duration of the m-th historical Hall state, used to estimate the current ideal duration; This represents the filtered value at the current moment when a three-step filter is used; The six-step filter is configured as follows: Where bm represents the filter coefficients; M represents the order; a three-step filter. Six-step filter This represents the filtered value at the current moment when a six-step filter is used; Obtain the duration of each Hall state during motor operation, including: Obtain the duration of the first Hall state, the duration of the second Hall state, the duration of the third Hall state, and the duration of the fourth Hall state; Wherein, the duration τ(n-3) of the first Hall state represents the duration when the A-phase Hall sensor triggers the rising edge and the C-phase Hall sensor triggers the falling edge; the duration τ(n-2) of the second Hall state represents the duration when the C-phase Hall sensor triggers the falling edge and the B-phase Hall sensor triggers the rising edge; the duration τ(n-1) of the third Hall state represents the duration when the B-phase Hall sensor triggers the rising edge and the A-phase Hall sensor triggers the falling edge; and the duration τ(n) of the fourth Hall state represents the duration when the A-phase Hall sensor triggers the falling edge and the C-phase Hall sensor triggers the rising edge. The extrapolation filtering method includes: The linear extrapolation result of the current Hall state duration is obtained based on the difference between twice the duration of the previous Hall state and the duration of the Hall state before that: t ex_l =2τ(k-1)-τ(k-2) Where, τ ex_l This is for linear extrapolation based on two-step history; k is a natural number.

2. The filtering method for Hall position sensor deviation signals of robot joints according to claim 1, characterized in that, Calculate the current Hall average duration, the previous Hall average duration, and the previous Hall average duration based on the duration of each Hall state, including: Calculate the current Hall average duration: t ex_l (i)=2τ(i-1)-τ(i-2) Calculate the average duration of the previous Hall effect: t ex_l (i-1)=2τ(i-2)-τ(i-3) Calculate the average duration of the previous Hall effect: t ex_l (i-2)=2τ(i-3)-τ(i-4) Where i is a natural number.

3. The filtering method for Hall position sensor deviation signals of robot joints according to claim 2, characterized in that, The ideal duration of the current Hall state is calculated using a three-step filter combined with a linear extrapolation filter method, including: Where t is a natural number.

4. The filtering method for Hall position sensor deviation signals of robot joints according to claim 3, characterized in that, After determining that the motor's operating state is a steady-speed operating state based on the rotational speed, the method further includes: Obtain the duration of the first seven Hall states; The ideal duration of the current Hall state is calculated using a six-step filter combined with a linear extrapolation filter method, including: Where t is a natural number.

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