WO2022145075A1

WO2022145075A1 - Position inference method, position inference device, and automatic guided vehicle

Info

Publication number: WO2022145075A1
Application number: PCT/JP2021/022214
Authority: WO
Inventors: 翔太石上
Original assignee: 日本電産株式会社
Priority date: 2020-12-28
Filing date: 2021-06-10
Publication date: 2022-07-07

Abstract

One aspect of a position inference method according to the present invention comprises: a learning step for acquiring a learning value which is necessary for inferring a rotation position; and a position inference step for inferring the rotation position of a rotor on the basis of the learning value. The learning step includes a second step for acquiring, as learning values, magnetic field intensities that are indicated by signals which are output from N magnetic sensors and a fourth step for acquiring origin point learning data that shows correspondences between all pole pair numbers and the learning values. The position inference step includes a sixth step for acquiring, as detection values, the magnetic field intensities that are indicated by output signals from the N magnetic sensors and a seventh step for determining, as the initial position of the rotor, one of the pole pair numbers included in the origin point learning data acquired in the learning step, on the basis of the detection values and of the origin point learning data.

Description

Position estimation method, position estimation device and automatic guided vehicle

The present invention relates to a position estimation method, a position estimation device, and an automatic guided vehicle.

Conventionally, as a motor capable of accurately controlling the rotor position, a configuration equipped with an absolute angle position sensor such as an optical encoder or a resolver is known. However, the absolute angle position sensor is large and expensive. Therefore, Patent Document 1 discloses a method of estimating the rotational position of the rotor of a motor without using an absolute angular position sensor.

Japanese Patent No. 6233532

In the position estimation method described in Patent Document 1, the initial position of the rotation position of the rotor may not be estimated in the range where the rotor angle is less than one rotation. Therefore, it is difficult to apply it to applications where the preliminary operation of rotating the rotor for estimating the initial position is not allowed, for example, a drive motor such as a robot or an automatic guided vehicle.

One aspect of the position estimation method of the present invention is a method of estimating the rotational position of a motor including a rotor having a plurality of magnetic pole pairs, which includes a learning step of acquiring a learning value necessary for estimating the rotational position. It has a position estimation step for estimating the rotation position of the rotor based on the learning value. In the learning step, the rotor is fixed in a predetermined position by passing a predetermined current from the stator coil of one phase to the stator coils of the remaining phases among the stator coils of a plurality of phases of the motor. The magnetic field indicated by the first step and the signals output from N magnetic sensors (N is an integer of 3 or more) arranged so as to face the rotor in the axial direction of the rotor and along the rotation direction of the rotor. The second step of acquiring the strength as the learning value, the third step of associating the learning value with the pole pair number representing the pole pair position which is the position of the magnetic pole pair, and the first step to the third step. By performing a series of steps a plurality of times, there is a fourth step of acquiring origin learning data showing the correspondence between all the pole pair numbers and the learning values. In the position estimation step, the rotor is fixed in a predetermined position by passing a predetermined current from the stator coil of one phase to the stator coils of the remaining phases among the stator coils of a plurality of phases of the motor. Based on the fifth step, the sixth step of acquiring the magnetic field strength indicated by the output signals of the N magnetic sensors as a detection value, the detection value, and the origin learning data acquired in the learning step. It has a seventh step of determining one of the pole pair numbers included in the origin learning data as the initial position of the rotor.

One aspect of the position estimation device of the present invention is a device that estimates the rotational position of a motor including a rotor having a plurality of magnetic pole pairs, which faces the rotor in the axial direction of the rotor and the rotational direction of the rotor. N magnetic sensors (N is an integer of 3 or more) arranged along the line, a processing unit that calculates the rotation position of the motor based on the output signals of the N magnetic sensors, and predetermined data are stored. It is equipped with a storage unit. As a learning process for acquiring a learning value necessary for estimating the rotation position of the motor, the processing unit has a stator coil of one phase among the stator coils of a plurality of phases of the motor and a stator of the remaining phases. The first process of fixing the rotor to a predetermined position by passing a predetermined current through the coil, and the second process of acquiring the magnetic field strength indicated by the output signals of the N magnetic sensors as the learning value. By performing the third process of associating the learned value with the pole pair number representing the pole pair position, which is the position of the magnetic pole pair, and a series of processes from the first process to the third process a plurality of times, all the above. The fourth process of acquiring the origin learning data showing the correspondence between the pole pair position and the learning value and storing the origin learning data in the storage unit is executed. As the rotation position estimation process, the processing unit causes a predetermined current to flow from the stator coil of one phase to the stator coils of the remaining phases among the stator coils of a plurality of phases of the motor. The fifth process of fixing the rotor in a predetermined position, the sixth process of acquiring the magnetic field strength indicated by the output signals of the N magnetic sensors as a detection value, the detection value, and the storage stored in the storage unit. Based on the origin learning data, the seventh process of determining one of the pole pair numbers included in the origin learning data as the initial position of the rotor is executed.

One aspect of the automatic guided vehicle of the present invention includes a motor including a rotor having a plurality of magnetic pole pairs, and the position estimation device of the above-described aspect for estimating the rotational position of the motor.

According to the above aspect of the present invention, there is provided a position estimation method, a position estimation device, and an automatic guided vehicle that can eliminate the need for a preliminary rotation operation for estimating a rotation position.

FIG. 1 is a block diagram schematically showing a configuration of a position estimation device according to an embodiment of the present invention. FIG. 2 is a flowchart showing a pre-learning process and a learning process executed by the processing unit in the present embodiment. FIG. 3 is a supplementary explanatory diagram regarding the prior learning process and the learning process in the present embodiment. FIG. 4 is an enlarged view of Hall signals Hu, Hv and Hw contained in one pole pair region. FIG. 5 is a diagram showing an example of origin learning data obtained by the learning process in the present embodiment. FIG. 6 is a flowchart showing a position estimation process executed by the processing unit in the present embodiment. FIG. 7 is a diagram showing an example of the detected values of the three Hall signals obtained by the processing unit in the present embodiment executing the sixth processing. FIG. 8 is a diagram showing the appearance of an automatic guided vehicle, which is an application example of the present invention.

Hereinafter, an embodiment of the present invention will be described in detail with reference to the drawings. FIG. 1 is a block diagram schematically showing the configuration of the position estimation device 1 according to the embodiment of the present invention. As shown in FIG. 1, the position estimation device 1 is a device that estimates the rotation position (rotation angle) of a motor 100 including a rotor 110 having a plurality of magnetic pole pairs. In this embodiment, as an example, the rotor 110 has four pole pairs. The magnetic pole pair means a pair of N pole and S pole. That is, in the present embodiment, the rotor 110 has four pairs of N pole and S pole, and has a total of eight magnetic poles (rotor magnets).

The motor 100 is, for example, an inner rotor type three-phase brushless DC motor. Although not shown in FIG. 1, the motor 100 has a stator and a motor housing in addition to the rotor 110. The motor housing houses the rotor 110 and the stator inside. The rotor 110 is rotatably supported around a rotating shaft by bearing components inside the motor housing. The stator has a three-phase excitation coil including a U-phase coil, a V-phase coil, and a W-phase coil, and is fixed in a state of facing the outer peripheral surface of the rotor 110 inside the motor housing. As shown in FIG. 1, the three-phase excitation coil of the motor 100 is electrically connected to the drive unit 3. The energized state of the three-phase excitation coil is controlled by the control device 2 via the drive unit 3, so that the electromagnetic force required to rotate the rotor 110 is generated.

The position estimation device 1 includes a sensor unit 10 and a signal processing unit 20. The sensor unit 10 has three

magnetic sensors

10u, 10v, and 10w. The signal processing unit 20 includes a processing unit 21 and a storage unit 22. Although not shown in FIG. 1, a circuit board is mounted on the motor 100, and the sensor unit 10, the signal processing unit 20, the control device 2, and the drive unit 3 are arranged on the circuit board. ..

The three

magnetic sensors

10u, 10v, and 10w face the rotor 110 in the axial direction of the rotor 110 and are arranged on the circuit board at predetermined intervals along the rotation direction of the rotor 110. In the present embodiment, the case where the signal estimation device 1 includes three

magnetic sensors

10u, 10v, and 10w is illustrated, but the number of magnetic sensors may be N (N is an integer of 3 or more). For example, the

magnetic sensors

10u, 10v, and 10w are Hall elements or linear Hall ICs, respectively. The

magnetic sensors

10u, 10v, and 10w each output an analog signal indicating the magnetic field strength. One cycle of the electric angle of each analog signal corresponds to 1 / P of one cycle of the mechanical angle. The number of pole pairs of the "P" rotor 110. In the present embodiment, since the pole logarithm P of the rotor 110 is "4", one cycle of the electric angle of each analog signal corresponds to 1/4 of one cycle of the mechanical angle, that is, 90 ° in the mechanical angle.

In the present embodiment, the

magnetic sensors

10u, 10v, and 10w are arranged at intervals of 30 ° along the rotation direction of the rotor 110. Therefore, the analog signals output from the

magnetic sensors

10u, 10v, and 10w have a phase difference of 120 ° in electrical angle from each other. Hereinafter, the analog signal output from the

magnetic sensors

10u, 10v, and 10w is referred to as a hall signal. The magnetic sensor 10u outputs the Hall signal Hu to the signal processing unit 20. The magnetic sensor 10v outputs the Hall signal Hv to the signal processing unit 20. The magnetic sensor 10w outputs the Hall signal Hw to the signal processing unit 20.

The signal processing unit 20 estimates the rotation position of the motor 100, that is, the rotation position of the rotor 110 based on the Hall signals Hu, Hv, and Hw, and outputs the estimation result of the rotation position to the control device 2. As described above, the signal processing unit 20 includes a processing unit 21 and a storage unit 22. The processing unit 21 is a microprocessor such as an MCU (Microcontroller Unit), for example. The Hall signals Hu, Hv and Hw output from the

magnetic sensors

10u, 10v and 10w are input to the processing unit 21. The processing unit 21 is connected to the storage unit 22 via a data bus so as to be capable of data communication.

The Hall signals Hu, Hv, and Hw are converted into digital signals inside the processing unit 21 via the A / D converter, but for convenience of explanation, the digital signals output from the A / D converter are also Hall. The signals are referred to as Hu, Hv and Hw.

The processing unit 21 executes at least the following three processes according to the program stored in the storage unit 22. The processing unit 21 executes a learning process of acquiring a learning value necessary for estimating the rotation position of the rotor 110 based on the Hall signals Hu, Hv, and Hw. The processing unit 41 executes a position estimation process for estimating the rotation position of the rotor 110 based on the Hall signals Hu, Hv, and Hw. Further, before executing the learning process, the processing unit 21 executes a pre-learning process for acquiring the correspondence between the magnetic field strengths indicated by the Hall signals Hu, Hv, and Hw and the pole pair number. The processing unit 21 outputs the estimation result of the rotation position of the rotor 110 to the control device 2.

The storage unit 22 has a non-volatile memory for storing programs, various setting values, learning data, etc. required for the processing unit 21 to execute various processes, and temporary data when the processing unit 21 executes various processes. Includes volatile memory used as a storage destination. The non-volatile memory is, for example, EEPROM (Electrically Erasable Programmable Read-Only Memory) or flash memory. The volatile memory is, for example, RAM (RandomAccessMemory).

The drive unit 3 is, for example, a three-phase full bridge circuit having three upper arm switches and three lower arm switches, or a current source. The drive unit 3 is electrically connected to each of the U-phase terminal 120, the V-phase terminal 130, and the W-phase terminal 140 of the motor 100. When the drive unit 3 is a three-phase full bridge circuit, a DC voltage for driving a motor is input to the three-phase full bridge circuit from a battery (not shown). By controlling the open / closed state of each arm switch included in the three-phase full bridge circuit by the control device 2, the three-phase full bridge circuit converts the input DC voltage into a three-phase AC voltage and outputs it to the motor 100. When the drive unit 3 is a current source, the current source is controlled by the control device 2 or outputs a predetermined drive current to the motor 100 in response to a manual operation.

The control device 2 controls the energization of the motor 100 by controlling the drive unit 3 based on the estimation result of the rotation position obtained from the processing unit 21 of the position estimation device 1.

Next, the advance learning process and the learning process executed by the processing unit 21 will be described. FIG. 2 is a flowchart showing the advance learning process and the learning process executed by the processing unit 21 in the present embodiment. The processing unit 21 executes the processing shown in FIG. 2 at least when the power of the position estimation device 1 is turned on for the first time.

As shown in FIG. 2, when the power of the position estimation device 1 is turned on for the first time, the processing unit 21 first acquires the correspondence between the magnetic field strength and the pole pair number indicated by the Hall signals Hu, Hv and Hw. The learning process is executed (step S0). This prior learning process corresponds to the prior learning step in the position estimation method of claim 4.

Specifically, in step S0, the processing unit 21 rotates the rotor 110 by controlling the energization of the motor 100 via the control device 2. As an example of a start sequence in which the motor 100 is started in a state where the rotation position of the rotor 110 is unknown, the rotation position of the rotor 110 is fixed to a specific position by performing DC excitation for a predetermined time, and then a constant drive voltage is applied to the energized phase. There is known an activation sequence that performs forced commutation control to forcibly switch the energized phase at a constant commutation frequency while applying. In the present embodiment, the processing unit 21 rotates the rotor 110 by controlling the energization of the motor 100 according to the above start sequence. The rotating shaft of the rotor 110 may be connected to an external rotating machine, and the rotor 110 may be rotated by the rotating machine.

Then, the processing unit 21 acquires three Hall signals Hu, Hv, and Hw output from the three

magnetic sensors

10u, 10v, and 10w as the rotor 110 rotates. As shown in FIG. 3, each electric angle 1 cycle of the Hall signals Hu, Hv, and Hw corresponds to 1/4 of the mechanical angle 1 cycle, that is, 90 ° in the mechanical angle. In FIG. 3, the period from time t1 to time t5 corresponds to one machine angle cycle. In FIG. 3, the period from time t1 to time t2, the period from time t2 to time t3, the period from time t3 to time t4, and the period from time t4 to time t5 are 90 in machine angle, respectively. Corresponds to °. Further, the Hall signals Hu, Hv and Hw have a phase difference of 120 ° in electrical angle from each other.

Then, the processing unit 21 sets the learning period as a pole pair number representing the pole pair position of each of the four magnetic pole pairs based on the Hall signals Hu, Hv, and Hw obtained in the learning period corresponding to one cycle of the machine angle. It is divided into four pole pair regions associated with, each of the four pole pair regions is further divided into a plurality of sections, and each of the plurality of sections is associated with a segment number indicating the rotation position of the rotor 110.

In the present embodiment, in order to estimate the rotation position of the rotor 110, pole pair numbers representing the pole pair positions are assigned to the four magnetic pole pairs of the rotor 110. For example, as shown in FIG. 1, the four magnetic pole pairs of the rotor 110 are assigned pole pair numbers in the order of "0", "1", "2", and "3" in the clockwise direction.

As shown in FIG. 3, the processing unit 21 divides the learning period into four pole pair regions based on the Hall signals Hu, Hv, and Hw obtained during the learning period. In FIG. 3, "No. C" indicates a pole pair number. The processing unit 21 divides the period from time t1 to time t2 in the learning period as a pole pair region associated with the pole pair number "0". The processing unit 21 divides the period from time t2 to time t3 in the learning period as a pole pair region associated with the pole pair number "1". The processing unit 21 divides the period from time t3 to time t4 in the learning period as a pole pair region associated with the pole pair number "2". The processing unit 21 divides the period from time t4 to time t5 in the learning period as a pole pair region associated with the pole pair number "3".

As shown in FIG. 3, the processing unit 21 further divides each of the four pole pair regions into 12 sections based on the three Hall signals Hu, Hv, and Hw obtained during the learning period, and twelve pieces. A segment number indicating the rotation position of the rotor 110 is associated with each of the sections. In FIG. 3, "No. A" indicates a section number assigned to a section, and "No. B" indicates a segment number.

As shown in FIG. 3, section numbers from "0" to "11" are assigned to the 12 sections included in each of the four pole pair regions. On the other hand, consecutive numbers over the entire learning period are associated with each section as segment numbers. Specifically, as shown in FIG. 3, in the pole pair region associated with the pole pair number "0", the segment numbers "0" to "11" are obtained for the section numbers "0" to "11". Is linked up to. In the pole pair area associated with the pole pair number "1", the segment numbers "12" to "23" are associated with the section numbers "0" to "11". In the pole pair area associated with the pole pair number "2", the segment numbers "24" to "35" are associated with the section numbers "0" to "11". In the pole pair area associated with the pole pair number "3", the segment numbers "36" to "47" are associated with the section numbers "0" to "11".

FIG. 4 is an enlarged view of Hall signals Hu, Hv, and Hw contained in one pole pair region. Hereinafter, a method of dividing the pole pair region into 12 sections will be described with reference to FIG. 4. In FIG. 4, the digital value of the amplitude, which is a positive value, represents the digital value of the magnetic field strength of the N pole as an example. Further, the digital value of the amplitude, which is a negative value, represents the digital value of the magnetic field strength of the S pole as an example.

The processing unit 21 extracts a zero cross point, which is a point where the three Hall signals Hu, Hv, and Hw included in each of the four pole pair regions intersect with the reference value “0”. As shown in FIG. 4, the processing unit 21 extracts points P1, point P3, point P5, point P7, point P9, point P11, and point P13 as zero cross points.

Then, the processing unit 21 extracts an intersection point at which the three Hall signals Hu, Hv, and Hw included in each of the four pole pair regions intersect with each other. As shown in FIG. 4, the processing unit 21 extracts points P2, P4, P6, P8, P10, and P12 as intersections. Then, the processing unit 21 determines the section between the zero crossing points and the intersections adjacent to each other as a section.

As shown in FIG. 4, the processing unit 21 determines the section between the zero cross point P1 and the intersection P2 as a section to which the section number “0” is assigned. The processing unit 21 determines the section between the intersection P2 and the zero crossing point P3 as the section to which the section number "1" is assigned. The processing unit 21 determines the section between the zero cross point P3 and the intersection P4 as a section to which the section number "2" is assigned. The processing unit 21 determines the section between the intersection P4 and the zero crossing point P5 as the section to which the section number "3" is assigned. The processing unit 21 determines the section between the zero cross point P5 and the intersection P6 as a section to which the section number "4" is assigned. The processing unit 21 determines the section between the intersection P6 and the zero crossing point P7 as the section to which the section number "5" is assigned.

The processing unit 21 determines the section between the zero cross point P7 and the intersection P8 as a section to which the section number "6" is assigned. The processing unit 21 determines the section between the intersection P8 and the zero crossing point P9 as the section to which the section number "7" is assigned. The processing unit 21 determines the section between the zero cross point P9 and the intersection point P10 as a section to which the section number “8” is assigned. The processing unit 21 determines the section between the intersection P10 and the zero crossing point P11 as the section to which the section number "9" is assigned. The processing unit 21 determines the section between the zero cross point P11 and the intersection P12 as a section to which the section number "10" is assigned. The processing unit 21 determines the section between the intersection P12 and the zero crossing point P13 as the section to which the section number "11" is assigned.

By performing the above-mentioned prior learning process before the learning process, as shown in FIG. 3, the learning period is divided into four pole pair regions associated with the pole pair numbers, and the four pole pair regions. Each of the sections is divided into 12 sections, and a segment number is associated with each section. In the following description, for example, the section to which the section number "0" is assigned is referred to as "0th section", and the section to which the section number "11" is assigned is referred to as "11th section". ..

Subsequently, as shown in FIG. 2, as one of the learning processes, the processing unit 21 changes from the stator coil of one phase to the stator coil of the remaining phase among the stator coils of the plurality of phases of the motor 100. The first process of fixing the rotor 110 to a predetermined position is executed by passing a predetermined current to the rotor 110 (step S1). This first process corresponds to the first step of the learning step in the position estimation method of claim 1.

Specifically, in step S1, the processing unit 21 applies a rated current from the U-phase stator coil to the remaining V-phase and W-phase stator coils among the three-phase stator coils of the motor 100. By flowing, the rotor 110 is fixed in a predetermined position. Hereinafter, passing a predetermined current from the stator coil of one phase to the stator coil of the remaining phase among the stator coils of a plurality of phases of the motor 100 is referred to as "d-axis current energization". The processing unit 21 energizes the d-axis current as described above via the control device 2 and the drive unit 3.

Subsequently, as one of the learning processes, the processing unit 21 outputs three Hall signals Hu, Hv, and Hw output from the three

magnetic sensors

10u, 10v, and 10w with the rotor 110 fixed at a predetermined position. A second process is executed in which sampling is performed and the magnetic field strength indicated by each Hall signal Hu, Hv, and Hw obtained by sampling is acquired as a learning value (step S2). This second process corresponds to the second step of the learning step in the position estimation method of claim 1.

Subsequently, the processing unit 21 executes a third process of associating the three learning values acquired in step S2 with the pole pair number as one of the learning processes (step S3). This third process corresponds to the third step of the learning step in the position estimation method of claim 1.

For example, in FIG. 4, a point PHu located on the waveform of the Hall signal Hu, a point PHv located on the waveform of the Hall signal Hv, and a point PHw located on the waveform of the Hall signal Hw were obtained by sampling. It is assumed that each hall signal is Hu, Hv, and Hw. In this case, the processing unit 21 acquires the value of the point PHu (magnetic field strength) as the learning value of the Hall signal Hu. Further, the processing unit 21 acquires the value of the point PHv as the learning value of the Hall signal Hv. Further, the processing unit 21 acquires the value of the point PHw as the learning value of the hall signal Hw. The processing unit 21 obtains the three learning values acquired as described above based on the correspondence between the magnetic field strengths of the Hall signals Hu, Hv, and Hw learned in advance by the prior learning process and the pole pair numbers. Correspond to one of.

Subsequently, the processing unit 21 performs a series of processes from the first process (step S1) to the third process (step S3) a plurality of times to show the correspondence between all the pole pair numbers and the learning values. The fourth process of acquiring the learning data and storing the acquired origin learning data in the storage unit 22 is executed (step S4). This fourth process corresponds to the fourth step of the learning step in the position estimation method of claim 1. In order to obtain the correspondence between all the pole pair numbers and the learned values, the rotating shaft of the rotor 110 is connected to an external rotating machine as necessary, and the d-axis is rotated by the rotating machine. Current may be applied.

FIG. 5 is a diagram showing an example of origin learning data obtained by the learning process from step S1 to step S4. As shown in FIG. 5, for example, for the pole pair number "0", the learning value "-800" acquired from the Hall signal Hu, the learning value "400" acquired from the Hall signal Hv, and the Hall signal Hw are acquired. It is associated with the learned value "450". For example, the pole pair number "1" includes a learning value "-700" acquired from the hall signal Hu, a learning value "370" acquired from the hall signal Hv, and a learning value "350" acquired from the hall signal Hw. Is associated with. For example, the pole pair number "2" includes a learning value "-1000" acquired from the hall signal Hu, a learning value "500" acquired from the hall signal Hv, and a learning value "550" acquired from the hall signal Hw. Is associated with. For example, the pole pair number "3" includes a learning value "-1200" acquired from the hall signal Hu, a learning value "600" acquired from the hall signal Hv, and a learning value "650" acquired from the hall signal Hw. Is associated with.

Next, the position estimation process executed by the processing unit 21 will be described. The position estimation process corresponds to the position estimation step in the position estimation method of claim 1. FIG. 6 is a flowchart showing a position estimation process executed by the processing unit 21. After executing the advance learning process and the learning process shown in FIG. 2, the processing unit 21 executes the position estimation process shown in FIG. 6 when the power of the position estimation device 1 is turned on again.

As shown in FIG. 6, when the position estimation process is started, the processing unit 21 first executes a fifth process of fixing the rotor 110 to a predetermined position by energizing the d-axis current (step S5). This fifth process corresponds to the fifth step of the position estimation step in the position estimation method of claim 1.

Subsequently, the processing unit 21 samples the three Hall signals Hu, Hv, and Hw output from the three

magnetic sensors

10u, 10v, and 10w with the rotor 110 fixed at a predetermined position, and obtains the sampling. The sixth process of acquiring the magnetic field strength indicated by each Hall signal Hu, Hv, and Hw as a detection value is executed (step S6). This sixth process corresponds to the sixth step of the position estimation step in the position estimation method of claim 1.

FIG. 7 is a diagram showing an example of the detected values of the three Hall signals Hu, Hv, and Hw obtained by the processing unit 21 executing the sixth process (step S6). As shown in FIG. 7, for example, the processing unit 21 acquires the detected value “-1050” from the Hall signal Hu, acquires the detected value “-520” from the Hall signal Hv, and acquires the detected value “-520” from the Hall signal Hw. Get 600 ".

Subsequently, the processing unit 21 is one of the pole pair numbers included in the origin learning data based on the three detected values acquired in step S6 and the origin learning data shown in FIG. 5 stored in the storage unit 22. Is executed as the seventh process for determining the initial position of the rotor 110 (step S7). This seventh process corresponds to the seventh step of the position estimation step in the position estimation method of claim 1.

Specifically, as the seventh process of the position estimation process, the processing unit 21 compares the three detected values acquired in step S6 with all the learned values included in the origin learning data shown in FIG. 5, and 3 The pole pair number associated with the three learning values closest to the one detected value is determined as the initial position of the rotor 110. For example, when three detected values as shown in FIG. 7 are obtained, the pole pair number associated with the three learning values closest to these three detected values is the pole from the origin learning data shown in FIG. It can be seen that the pair number is "3". Therefore, in this case, the processing unit 21 determines the pole pair number "3" as the initial position of the rotor 110.

The processing unit 21 determines the initial position of the rotor 110 immediately after the power is turned on again by the position estimation process as described above, and then outputs the pole pair number determined as the initial position of the rotor 110 to the control device 2. The control device 2 rotates the rotor 110 by starting the energization control of the motor 100 via the drive unit 3 based on the pole pair number determined as the initial position of the rotor 110.

The processing unit 21 estimates the rotation position of the rotor 110 based on the Hall signals Hu, Hv, and Hw output from the three

magnetic sensors

31, 32, and 33 as the rotor 110 rotates, and estimates the estimation result. Output to the control device 2. As the rotation position estimation algorithm, for example, the position estimation algorithm described in Japanese Patent No. 6233532 can be used. Therefore, the description of the rotation position estimation algorithm is omitted in the present specification. The control device 2 continuously controls the energization of the motor 100 via the drive unit 3 based on the estimation result of the rotation position of the rotor 110.

As described above, the position estimation device 1 of the present embodiment has a learning process of acquiring a learning value necessary for estimating the rotational position of the rotor 110 based on the Hall signals Hu, Hv and Hw, and a Hall signal Hu. A processing unit 21 that executes a position estimation process for estimating the rotation position of the rotor 110 based on Hv and Hw and the origin learning data is provided. The processing unit 21 executes the learning process at least when the power of the position estimation device 1 is turned on for the first time, and acquires the origin learning data showing the correspondence between all the pole pair numbers and the learning values. The processing unit 21 executes the position estimation process when the power of the position estimation device 1 is turned on again, so that any one of the pole pair numbers is determined as the initial position of the rotor 110.

Thereby, the position estimation device 1 of the present embodiment can estimate the initial position of the rotor 110 without rotating the rotor 110. Therefore, the motor 100 provided with the position estimation device 1 does not have to adjust the origin of the rotation position of the rotor 110 when the power is turned on. Since the motor 100 does not require a preliminary rotation operation for adjusting the origin, it can be suitably used for a drive motor application such as a robot or an automatic guided vehicle in which the preliminary rotation operation is not allowed. Since the motor 100 does not require a preliminary rotation operation for adjusting the origin, the drive time and power consumption required for the preliminary rotation operation can be reduced.

(Modification example)
The present invention is not limited to the above-described embodiment, and the configurations described in the present specification can be appropriately combined within a range that does not contradict each other. In the above embodiment, the case where three magnetic sensors that output Hall signals are provided is illustrated, but the number of magnetic sensors is not limited to three, and the number of magnetic sensors is N (N1 is an integer of 3 or more). It should be. That is, the number of magnetic sensors may be four or more. Further, in the above embodiment, a motor including a rotor having four pole pairs is exemplified, but the number of pole pairs of the rotor is not limited to four, and the number of pole pairs of the rotor is P (P is an integer of 2 or more). All you need is.

[Application example]
FIG. 8 is a diagram showing the appearance of the automatic guided vehicle 200, which is an application example of the present invention. The automatic guided vehicle 200 includes a motor including a rotor having a plurality of magnetic pole pairs, and a position estimation device for estimating the rotation position of the motor. As the motor, the motor 100 described in the above embodiment can be used. Further, as the position estimation device, the position estimation device 1 of the above embodiment can be used. Since the motor provided on the automatic guided vehicle 200 does not require a preliminary rotation operation for adjusting the origin, it is possible to prevent the automatic guided vehicle 200 from moving at an unintended timing. The application example of the present invention is not limited to the automatic guided vehicle 200, and the present invention can be widely applied to a device such as a robot which cannot tolerate the preliminary rotation operation of the motor.

1 ... position estimation device, 2 ... control device, 3 ... drive unit, 10 ... sensor unit, 10u, 10v, 10w ... magnetic sensor, 20 ... signal processing unit, 21 ... processing unit, 22 ... storage unit, 100 ... motor, 110 ... rotor, 200 ... automatic guided vehicle

Claims

A method of estimating the rotational position of a motor with a rotor with multiple pole pairs.
A learning step for acquiring the learning value required for estimating the rotation position, and
A position estimation step for estimating the rotation position of the rotor based on the learning value, and
Have,
The learning step is
With the first step of fixing the rotor in a predetermined position by passing a predetermined current from the stator coil of one phase to the stator coils of the remaining phases among the stator coils of the plurality of phases of the motor. ,
The magnetic field strength indicated by the signals output from N magnetic sensors (N is an integer of 3 or more) arranged in the axial direction of the rotor facing the rotor and along the rotation direction of the rotor is used as the learning value. The second step to be acquired, the third step of associating the learned value with the pole pair number representing the pole pair position which is the position of the magnetic pole pair, and the third step.
By performing the series of steps from the first step to the third step a plurality of times, the fourth step of acquiring the origin learning data showing the correspondence between all the pole pair numbers and the learning values, and
Have,
The position estimation step is
A fifth step of fixing the rotor in a predetermined position by passing a predetermined current from the stator coil of one phase to the stator coils of the remaining phases among the stator coils of a plurality of phases of the motor.
The sixth step of acquiring the magnetic field strength indicated by the output signals of the N magnetic sensors as a detection value, and
A seventh step of determining one of the pole pair numbers included in the origin learning data as the initial position of the rotor based on the detected value and the origin learning data acquired in the learning step.
Have,
Position estimation method.
In the seventh step of the position estimation step, the detected value is compared with all the learned values included in the origin learning data, and the pole pair associated with the learned value closest to the detected value. The number is determined as the initial position of the rotor,
The position estimation method according to claim 1.
The learning step is performed at least when the power of the learning step and the position estimation device performing the position estimation step is turned on for the first time, and the position estimation step is performed after the learning step is executed. This happens when the power is turned on again.
The position estimation method according to claim 1 or 2.
Prior to the learning step, there is further a prior learning step of acquiring the correspondence between the magnetic field strength indicated by the output signals of the N magnetic sensors and the pole pair number.
The position estimation method according to any one of claims 1 to 3.
A device that estimates the rotational position of a motor with a rotor with multiple magnetic pole pairs.
N magnetic sensors (N is an integer of 3 or more) arranged so as to face the rotor in the axial direction of the rotor and along the rotation direction of the rotor.
A processing unit that calculates the rotation position of the motor based on the output signals of the N magnetic sensors, a storage unit that stores predetermined data, and a storage unit.
Equipped with
As a learning process, the processing unit acquires a learning value necessary for estimating the rotation position of the motor.
The first process of fixing the rotor in a predetermined position by passing a predetermined current from the stator coil of one phase to the stator coils of the remaining phases among the stator coils of the plurality of phases of the motor. ,
The second process of acquiring the magnetic field strength indicated by the output signals of the N magnetic sensors as the learning value, and
The third process of associating the learned value with the pole pair number representing the pole pair position which is the position of the pole pair,
By performing a series of processes from the first process to the third process a plurality of times, origin learning data showing the correspondence between all the pole pair numbers and the learning values is acquired, and the origin learning data is used as described above. The fourth process stored in the storage unit and
And run
The processing unit performs the estimation processing of the rotation position.
A fifth process of fixing the rotor in a predetermined position by passing a predetermined current from the stator coil of one phase to the stator coils of the remaining phases among the stator coils of a plurality of phases of the motor.
The sixth process of acquiring the magnetic field strength indicated by the output signals of the N magnetic sensors as a detection value, and
A seventh process of determining one of the pole pair numbers included in the origin learning data as the initial position of the rotor based on the detected value and the origin learning data stored in the storage unit.
To execute,
Position estimation device.
As the seventh process of the estimation process, the processing unit compares the detected value with all the learned values included in the origin learning data, and associates the detected value with the learned value closest to the detected value. The pole pair number is determined as the initial position of the rotor.
The position estimation device according to claim 5.
The processing unit executes the learning process at least when the power of the position estimation device is turned on for the first time.
After executing the learning process, the processing unit executes the estimation process when the power of the position estimation device is turned on again.
The position estimation device according to claim 5 or 6.
Before executing the learning process, the processing unit executes a pre-learning process for acquiring the correspondence between the magnetic field strength indicated by the output signals of the N magnetic sensors and the pole pair number.
The position estimation device according to any one of claims 5 to 7.
A motor with a rotor with multiple pole pairs and
The position estimation device according to any one of claims 5 to 8, which estimates the rotational position of the motor, and the position estimation device.
An automatic guided vehicle equipped with.