JP-2026075410-A - Method and control device for estimating the rotational speed of a brushless DC motor

JP2026075410AJP 2026075410 AJP2026075410 AJP 2026075410AJP-2026075410-A

Abstract

[Problem] To provide a method for estimating the rotational speed of a brushless DC motor with high accuracy and robustness, based on information observed by a magnetic sensor. [Solution] The method for estimating the rotational speed of a brushless DC motor includes a particle filter setting step S12 in which a particle filter 54 is used to set a likelihood designed considering the effects of the position error (e h ) of the magnetic sensor 13 and the position error (e z ) of the magnetic poles of the rotor 11, and a rotational speed estimation step S15 in which the rotational speed of the rotor 11 is estimated as the estimated rotational speed (ω ^ ) by using the particle filter 54 with the set likelihood to remove observation error noise (ω n ) caused by the position error (e h ) of the magnetic sensor 13 and the position error (e z ) of the magnetic poles of the rotor 11 included in the observed value. [Selection Diagram] Figure 9

Inventors

千田有一
種村昌也
武藤直斗

Assignees

国立大学法人信州大学
シナノケンシ株式会社

Dates

Publication Date: 20260508
Application Date: 20241022

Claims (12)

A method for estimating the rotational speed of a brushless DC motor, comprising: calculating the rotational speed of the rotor based on the output of multiple magnetic sensors that detect the magnetic poles of the rotor; and estimating the actual rotational speed of the rotor by passing the calculated rotational speed through a filter, A particle filter setting step involves using a particle filter as the filter and setting the particle filter with a likelihood designed considering the effects of the position error of the magnetic sensor and the position error of the rotor's magnetic poles. A detection pulse signal acquisition step, which involves acquiring detection pulse signals output from each of the plurality of magnetic sensors at a predetermined sampling period, A rotational speed calculation step in which the rotational speed of the rotor is calculated as an observed value from a continuous pulse obtained by taking the exclusive OR (XOR) of the detection pulse signals acquired at each sampling time, A rotational speed estimation step in which the rotational speed of the rotor is estimated as the estimated rotational speed, obtained by using the particle filter with the likelihood set, to remove observation error noise caused by the position error of the magnetic sensor and the position error of the magnetic pole of the rotor included in the observed value. A method for estimating the rotational speed of a brushless DC motor, characterized by including the following:
In the method for estimating the rotational speed of a brushless DC motor according to claim 1, A rotation speed estimation method comprising the particle filter setting step, in which the rotor is rotated at a constant speed in advance, and the rotation angle between each edge of the continuous pulse is calculated from the pulse width of each continuous pulse obtained by taking the exclusive OR (XOR) of the detection pulse signals output from each of the plurality of magnetic sensors for one rotation of the rotor, and the likelihood is designed using the calculated rotation angle between each edge of the continuous pulse, taking into account the effects of the position error of the magnetic sensor and the position error of the magnetic pole of the rotor.
In the method for estimating the rotational speed of a brushless DC motor according to claim 2, A rotational speed estimation method in which the likelihood is designed using a probability density function that reflects the probability distribution of observed rotational speeds calculated from the rotation angles between each edge of the continuous pulse.
In the method for estimating the rotational speed of a brushless DC motor according to claim 3, A method for estimating the rotational speed of a brushless DC motor, wherein the probability density function is designed as a function of the particles in the particle filter as a variable.
In the method for estimating the rotational speed of a brushless DC motor according to claim 4, A method for estimating the rotational speed of a brushless DC motor, wherein the likelihood is designed by the following equation 26.
In the method for estimating the rotational speed of a brushless DC motor according to claim 4, In the particle filter setting step, the likelihood is set in the particle filter using a plurality of probability density functions that reflect the probability distribution of the observed rotational speed for each detection signal pattern of the magnetic sensor, based on the combination of detection pulse signals output from each of the plurality of magnetic sensors, and corresponding to each detection signal pattern. In the rotation speed estimation step, the particle filter is instructed to acquire detection pulse signals output from each of the plurality of magnetic sensors at a predetermined sampling period to understand the detection signal pattern, and to switch the likelihood used to estimate the estimated rotation speed from among the plurality of likelihoods according to the detection signal pattern. A method for estimating the rotational speed of a brushless DC motor.
A control device for a brushless DC motor, which is connected to a brushless DC motor having multiple magnetic sensors that detect and output the magnetic poles of the rotor, and is configured to drive and control the brushless DC motor, A motor drive unit configured to rotate the rotor at a target rotational speed based on a control command, A detection pulse signal acquisition unit that acquires detection pulse signals output from each of the plurality of magnetic sensors at a predetermined sampling period, A rotational speed calculation unit calculates the rotational speed of the rotor as an observed value from a continuous pulse obtained by taking the exclusive OR (XOR) of the detection pulse signals acquired at each sampling time, A particle filter is set with a likelihood factor that takes into account the effects of the position error of the magnetic sensor and the position error of the rotor's magnetic poles, and is designed to estimate the rotational speed with high accuracy by removing observation error noise resulting from the installation error of the magnetic sensor and the position error of the rotor's magnetic pole arrangement from the observed value calculated by the rotational speed calculation unit. A motor control command unit generates a control command based on the estimated rotation speed estimated by the particle filter and the target rotation speed, and outputs the control command to the motor drive unit, so as to follow the target rotation speed. A control device for a brushless DC motor, characterized by comprising the following:
In the control device for a brushless DC motor according to claim 7, A control device for a brushless DC motor, wherein the likelihood is calculated using the rotation angle between each edge of a continuous pulse, which is obtained by taking the exclusive OR (XOR) of the detection pulse signals output from each of the plurality of magnetic sensors for one rotation of the rotor after rotating the rotor at a constant speed in advance, and taking into account the effects of the position error of the magnetic sensors and the position error of the magnetic poles of the rotor.
In the control device for a brushless DC motor according to claim 8, A control device for a brushless DC motor, in which the likelihood is designed using a probability density function that reflects the probability distribution of the observed rotational speed calculated from the rotation angle between each edge of the continuous pulse.
In the control device for a brushless DC motor according to claim 9, A control device for a brushless DC motor, wherein the probability density function is designed as a function of the particles in the particle filter as a variable.
In the control device for a brushless DC motor according to claim 10, A control device for a brushless DC motor, wherein the likelihood is designed by the following equation 26.
In the control device for a brushless DC motor according to claim 10, The particle filter has multiple likelihoods defined as corresponding to each detection signal pattern, using multiple probability density functions that reflect the probability distribution of the observed rotational speed for each detection signal pattern of the magnetic sensor, based on the combination of detection pulse signals output from each of the multiple magnetic sensors. The particle filter is designed to acquire detection pulse signals output from each of the plurality of magnetic sensors at a predetermined sampling period to grasp the detection signal pattern, and to switch the likelihood used to estimate the estimated rotational speed from among the plurality of likelihoods according to the detection signal pattern. A control device for a brushless DC motor.

Description

This invention relates to a method for estimating the rotational speed of a brushless DC motor, and a control device for a brushless DC motor utilizing this rotational speed estimation method. Brushless DC motors are simple, easy to control, and widely used in various fields such as industrial products and computer peripherals. Typically, brushless DC motors are controlled to match a desired rotational speed while monitoring it using Hall sensors and rotary encoders. There are demands for lower costs and lighter weight for brushless DC motors. Therefore, while Hall sensors are inexpensive and easy to install, rotary encoders, being precision components, are expensive and heavy. Thus, a method has been proposed to control brushless DC motors by estimating the rotational speed from information observed by Hall sensors without using rotary encoders. On the other hand, in recent years, there has been a growing demand for more precise control of brushless DC motors. Therefore, a method has been proposed to control a brushless DC motor by estimating the rotational speed using a Kalman filter based on information observed by a Hall sensor, without using a rotary encoder. However, this method suffers from significant observation errors due to placement errors in the Hall sensor and the rotor's magnetic poles (hereinafter referred to as "position errors"), which could worsen the brushless DC motor's ability to track the target rotational speed. For this reason, a method has also been proposed to improve the brushless DC motor's ability to track the target rotational speed by refining the Kalman filter design to estimate the rotational speed of the brushless DC motor with high accuracy (see, for example, Patent Document 1). The method for estimating the rotational speed of a brushless DC motor proposed in Patent Document 1 is an invention of the present inventor, and is optimized to eliminate variations in observation error noise ( ωn ) by designing the Kalman filter so that the adjustment parameter (r) of the Kalman gain becomes a time-varying value r[k]. As a result, the method for estimating the rotational speed of a brushless DC motor proposed in Patent Document 1 can estimate the rotational speed of the brushless DC motor from information observed by a magnetic sensor with higher accuracy. Japanese Patent Publication No. 2024-120855 This is a diagram showing the configuration of the brushless DC motor system of Embodiment 1.This is a signal processing diagram for the brushless DC motor system of Embodiment 1.This is an explanatory diagram illustrating the processing of pulse signals detected by a magnetic sensor in the brushless DC motor system of Embodiment 1.This figure shows the position error of the magnetic sensor in the brushless DC motor used in Embodiment 1.This figure shows the positional error of the rotor's magnetic poles in the brushless DC motor used in Embodiment 1.This figure shows the rotational angle error between edges of the pulse signal detected by the magnetic sensor in the brushless DC motor system of Embodiment 1.This is a model diagram of the brushless DC motor used in Embodiment 1.This is a flowchart showing the algorithm for the particle filter used in Embodiment 1.This is a flowchart showing the control method for a brushless DC motor according to Embodiment 1.This is a signal processing diagram for the brushless DC motor system of Embodiment 2.This graph shows the observation results before passing the particles through the particle filter in the first simulation of the example.This graph shows the estimated results after passing the particle filter of Embodiment 1 through the observation results shown in Figure 11.This is an enlarged view of section Z1 in Figure 12.This is an enlarged view of section Z2 in Figure 12.This graph shows the estimation results in the second simulation of the embodiment, comparing the case where the particle filter of embodiment 1 is used with the case where the particle filter of embodiment 2 is used.This is an enlarged view of section Z3 in Figure 15.This is an enlarged view of section Z4 in Figure 15. Below, a brushless DC motor system 1 as one embodiment to which the present invention is applied will be described with reference to the drawings. Note that each drawing does not necessarily strictly reflect all actual configurations. In this specification, the term "rotational speed" is used to describe the rotation of the rotor of the brushless DC motor, but this term may be replaced with the term "angular velocity". In this specification, the structure of the brushless DC motor, the driving principle of the brushless DC motor using an inverter circuit, and the peripheral equipment for controlling the brushless DC motor are generally the same as in the conventional, and the explanation of parts that are the same as in the conventional will be simplified or omitted. Also, in the text, a signal symbol with the subscript " ^ ", such as "ω ^ ", means an esti