CN116780956B - Control method for self-learning of Hall position of DC brushless motor based on vector algorithm - Google Patents
Control method for self-learning of Hall position of DC brushless motor based on vector algorithm Download PDFInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
- H02P21/00—Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
- H02P21/0003—Control strategies in general, e.g. linear type, e.g. P, PI, PID, using robust control
- H02P21/0017—Model reference adaptation, e.g. MRAS or MRAC, useful for control or parameter estimation
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
- H02P21/00—Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
- H02P21/0003—Control strategies in general, e.g. linear type, e.g. P, PI, PID, using robust control
- H02P21/0025—Control strategies in general, e.g. linear type, e.g. P, PI, PID, using robust control implementing a off line learning phase to determine and store useful data for on-line control
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
- H02P21/00—Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
- H02P21/14—Estimation or adaptation of machine parameters, e.g. flux, current or voltage
- H02P21/18—Estimation of position or speed
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
- H02P6/00—Arrangements for controlling synchronous motors or other dynamo-electric motors using electronic commutation dependent on the rotor position; Electronic commutators therefor
- H02P6/14—Electronic commutators
- H02P6/16—Circuit arrangements for detecting position
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
- H02P2203/00—Indexing scheme relating to controlling arrangements characterised by the means for detecting the position of the rotor
- H02P2203/03—Determination of the rotor position, e.g. initial rotor position, during standstill or low speed operation
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- Control Of Motors That Do Not Use Commutators (AREA)
Abstract
The invention discloses a control method for self-learning the Hall position of a DC brushless motor based on a vector algorithm, which comprises the following steps: determining the relation between the power-on sequence of the direct-current brushless motor and the Hall sensor to obtain a Hall sector, configuring parameters of an upper computer, and then sending an instruction to a control board; after receiving the instruction, the control board firstly learns the Hall sector by itself, and stores the Hall sector obtained by self-learning into FLASH in the chip; then, after the self-learning of the Hall sector is successful, the self-learning of the FOC algorithm is carried out, the electric speed of the motor operation is calculated through the sector, and the current angle is calculated through the electric speed; in the FOC algorithm, fixed parameters Ud and Uq are set, three paths of PWM waves are generated through the calculated angle values and are input into a three-phase stator of the motor, and the rotor is driven to rotate; through self-learning of various parameters of the direct current brushless motor in the early stage, the learned parameters are valued, so that the bus current value is collected when the motor rotates, whether the self-learning is successful or not is judged, and the rotating performance of the motor is optimized by adopting a vector control FOC algorithm; and secondly, the learned motor parameters are stored into the chip to obtain a FLASH region, so that the function of power-off protection is achieved.
Description
Technical Field
The invention belongs to the technical field of direct current brushless motors, and particularly relates to a control method for self-learning a Hall position of a direct current brushless motor based on a vector algorithm.
Background
In the control field, under the premise that a hall sensor is arranged at the rear end of the motor, in order to rotate the brushless direct-current motor, the position (HALLA, HALLB, HALLC) of the hall sensor corresponding to the three-phase winding (U phase, V phase and W phase) of the brushless direct-current motor needs to be known, and how to better control the rotation of the motor and improve the working efficiency of the motor is a problem which needs to be considered, and generally, the conventional control method comprises the following steps:
1. the counter electromotive force waveform of the three-phase voltage corresponding to the signal fed back by the Hall sensor is checked through an oscilloscope, so that the one-to-one correspondence relation is determined, finally, the direct current brushless motor is controlled to rotate through code writing, in addition, for the tiny direct current brushless motor (Brushless Direct Current Motor, BLDC), the traditional method adopts six-step reversing control, the method enables the torque output by the final motor to generate fluctuation through the included angle between the direction of the torque generated by the stator winding and the position of the rotor to be 60 degrees and 120 degrees, and the torque is not the optimal control strategy.
2. Under the control method with a Hall sensor, a brand new DC brushless motor is faced, the position of the Hall and the zero-degree position of the motor are required to be obtained through debugging, and the angle value of the motor corresponding to the Hall sector is searched through continuous debugging, so that the motor is controlled to rotate by adopting the FOC algorithm. However, the complicated debugging process and the designed system can only be applied to the same type of motor, and have no universality.
Disclosure of Invention
The invention aims to design a control method for self-learning the Hall position of a direct current brushless motor based on a vector algorithm, and the motor can self-learn the position of a Hall sensor and store the position into a FALSH area of a control board through the combination of an upper computer and the control board, so that data loss caused by power failure of the control board is avoided.
In order to achieve the above purpose, the technical scheme adopted by the invention is as follows:
s1, after the upper computer configures parameters, sending an instruction to a control panel
S2, after receiving the instruction, the control board firstly carries out self-learning of the Hall sector, and stores the Hall sector obtained by self-learning into FLASH in the chip;
and S3, after the self-learning of the Hall sector is successful, performing self-learning of the FOC algorithm, calculating the electric speed of the motor operation through the sector, and calculating the current angle value through the electric speed.
And S4, in the FOC algorithm, setting fixed parameters Ud and Uq, and generating three paths of PWM waves through the calculated angle values to be input into a three-phase stator of the motor to drive the rotor to rotate.
Through the self-learning algorithm, any type of motor can be successfully rotated under the algorithm of vector control FOC.
The invention has the following beneficial effects:
the system designed by the invention acquires the bus current value when the motor rotates through the self-learning of various parameters of the DC brushless motor in the early stage and the value of the learned parameters, judges whether the self-learning is successful or not, and adopts a vector control FOC algorithm to optimize the rotation performance of the motor; secondly, the learned motor parameters are stored into the chip to obtain a FLASH area, so that the function of power-off protection is achieved; finally, through the combination of the upper computer and the lower computer, the operation of the UI interface can bring more concise experience, and the real-time change of parameters of the DC brushless motor in the self-learning process can be detected in real time through the upper computer.
According to the invention, through a reasonable design and an intelligent control strategy, the self-learning function of the direct current brushless motor can be well completed, the cost for independently debugging each type of direct current brushless motor is saved, the designed algorithm has better adaptability and robustness, and the requirements of different products are met.
The brushless DC motor of any type does not need to work through early test, debugging, code writing and the like, and the motor can learn parameters by a designed algorithm.
Drawings
Fig. 1 is a positional relationship diagram of a hall sensor mounting position of a dc brushless motor and a motor rotor.
Fig. 2 is a graph of the relationship between hall order and sector hall state value HALLState for the final hall.
Fig. 3 is a graph of the relationship between back emf and HALLState.
Fig. 4 is a flowchart of a self-learning algorithm of the brushless dc motor of the hall sensor.
Fig. 5 is a flow chart of the sector sequence obtained by the second self-learning.
FIG. 6 is the final θ result And hall sector.
Fig. 7 is an interface diagram of the host computer.
Detailed Description
The invention is further described with reference to the accompanying drawings:
with the development of artificial intelligence, the designed product needs more intellectualization and stronger robustness, the algorithm designed in the invention can perform self-learning on any direct current brushless motor with a Hall sensor, the motor can learn various parameters of the motor by the algorithm, the rotation of the motor can be optimized by self-adaption through vector control, the motor is controlled by adopting an algorithm of solving an angle value of a Hall sector, the motor is controlled by vector control FOC algorithm, so that the motor generates larger torque in the running process, current loss is reduced, working efficiency is improved, the upper computer software is compiled by C# language, more visual feeling can be brought to the interface operation, and the designed system is more concise through the communication of the upper computer and the lower computer.
The invention discloses a control method for self-learning the Hall position of a DC brushless motor based on a vector algorithm by combining with figures 1-7, which comprises the following steps:
s1, determining the relation between the power-on sequence of a direct-current brushless motor and a Hall sensor to obtain a Hall sector, configuring parameters of an upper computer, and then sending an instruction to a control board;
s2, after receiving the instruction, the control board firstly learns the Hall sector by itself, and stores the Hall sector obtained by self-learning into FLASH in the chip;
the self-learning specific steps of the Hall sector are as follows: the rotor is moved to a designated position through the sequence of electrifying the direct current brushless motor, and a Hall state of the position is obtained; according to the sequence of power on, each time lasts for 100ms, the magnetic moment generated by the stator moves the rotor within 100ms, the obtained halltate is stored in a two-dimensional array BUFF, six reversals are needed in one period, 600ms is needed, 10 times of self-learning is needed, whether the bus current value is smaller than a set value or not is detected through a control method of six reversals, and whether self-learning is successful or not is verified;
s3, after the self-learning of the Hall sector is successful, performing self-learning of the FOC algorithm, calculating the electric speed of the motor operation through the sector, and calculating the current angle value through the electric speed;
and S4, in the FOC algorithm, setting fixed parameters Ud and Uq, and generating three paths of PWM waves through the calculated angle values to be input into a three-phase stator of the motor to drive the rotor to rotate.
Specific examples of the method are given below:
the invention has the object that the installation positions of three Hall differ by 120 degrees, 6 different Hall signal combinations can be output, and the 6 different areas respectively correspond to the three Hall signal combinations. The mounting position of the hall sensor of the brushless direct current motor and the position of the motor rotor are shown in fig. 1.
The relationship between the energization sequence of the dc brushless motor and the hall sensor is shown in the following table, wherein "x" represents the correlation close and "v" represents the conduction.
The three-phase hall signal is a switching signal, the high level is recorded as 1, the low level is recorded as 0, and the hall sector value can be calculated as follows:
HALLState Sum ＝HALL A +2*HALL B +4*HALL C
HALLState Sum the Hall sequence of the angle value sensor is 5-4-6-2-3-1, and the angle value sensor can be sequenced according to the actual situation according to the sequence (0-5), so that the angle value calculation processing is facilitated. The relationship between hall order and sector hall state value halltate of the final hall is shown as 2, the upper curve in the graph is the sector value halltate, and the lower curve is the graph after ordering in order.
The zero-crossing point (from positive to negative) of the counter-electromotive force of the a relative neutral point is essentially the absolute zero-degree position of the angle value, and the formula in the counter-electromotive force formula (surface-mounted brushless dc motor) is as follows:
ea. Eb, ec are the back EMF, ω, of the three-phase centering point of the stator winding of the DC brushless motor e For electric angular velocity, ψ f Is the flux linkage of the rotor, theta e For the angle values, the relationship between the counter electromotive force and halltate can be obtained, as shown in fig. 3, the upper curve in the graph is the sector value of halltate, the lower curve is the counter electromotive force of phase a, and the intersection point of the counter electromotive force from positive to negative can be obtained as the electric angle zero degree position, and the corresponding sector is called zero degree sector.
The invention firstly needs to identify the Hall sector of the direct current brushless motor, takes the following FOC algorithm as the basis, enables the rotor to move to a designated position through the sequence of electrifying the direct current brushless motor, obtains the Hall state of the position, continuously moves the rotor for 100ms each time according to the electrifying sequence, stores the obtained Hall state into a two-dimensional array BUFF by the magnetic moment generated by the stator within 100ms, has six commutations in one period, needs 600ms, self-learns for 10 times, improves the success rate of self-learning, and detects whether the bus current value is smaller than a set value or not through the control method of six commutations, and verifies whether self-learning is successful or not. The self-learning algorithm flow chart 4 of the brushless DC motor based on the Hall sensor is shown in the invention.
After the Hall position is obtained, the motor is rotated by adopting the FOC vector algorithm, and a sector corresponding to the zero angle position of the motor is needed to be obtained first. The first self-learning algorithm obtains Hall wire harnesses corresponding to the stator windings of the motor in a three-phase one-to-one mode, the second self-learning algorithm obtains the position of the zero-degree sector, and the sequence of sector change corresponding to forward and reverse rotation of the motor is known.
For the FOC vector algorithm, the displacement angle of the current sector is obtained by solving the electric angular velocity of the last sector and integrating the electric angular velocity of the last sector. As shown in the flow chart 5 of the sector sequence obtained by the second self-learning, before the motor is started, the motor may be in a static state, and we need to read three-phase Hall switch signals first to determine the Hall sector angle where the current rotor is located, and the maximum deviation between the angle and the actual angle is +/-30 °. After the motor rotates stably, 6 accurate Hall sector angles can be obtained in one electric period. When calculating the rotation speed, the signal capturing function can be utilized to trigger the interruption, and the counting result is read in the interruption for calculating the rotation speed, simultaneously clearing the counting, and entering the next sector counting. The motor rotates one electrical cycle and Hall produces 6 sector changes. In omega e The electrical angular velocity of the motor is represented by the following calculation formula:
where RegisterCnt is the read timer count value, f timer Is the frequency of the timer configuration. The mechanical rotation speed is (1/P) times of the electrical angular speed, and the formula is:
wherein P is the pole pair number, omega of the motor m Representing the mechanical angular velocity of the motor.
The Hall angle is calculated by integrating the speed. First, using a timer, the time T taken to walk through a Hall sector is calculated oneSec (T method speed measurement). Next, T is used oneSec Calculated during one carrier period (T carrier ) Angle delta theta of inner needed walk e . Finally, in each carrier interruption, the angle value is accumulated each time, so that continuous integration of angles is realized. Here Δθ e The angular velocity omega is updated every time the Hall sector jumps through the velocity estimation of the last sector e And clears the value of the register. In order to facilitate the self-learning process of the DC brushless motor, aiming at the deviation angle of the Hall sector, a fixed deviation angle is adopted as theta error The actual angle value finally calculated by the hall sector is:
θ result ＝θ Cumulate +θ error
in θ Cumulate The angle value theta obtained by integrating and accumulating Hall sectors error For a fixed offset value of 30 DEG, theta result The angle value obtained finally is used. Viewing the final θ through J-Scope software result The relationship between the stator and the hall sectors is shown in fig. 6, the fixed angle value is given in the initial stage, the magnetic moment generated by the stator drags the rotor to rotate, after dragging, the register in the chip can capture the jump of the hall sectors, so that the time of each sector can be recorded, then the electric speed can be solved, and the speed is integrated to calculate the current angle value.
To finally obtain theta result In the code input to SVPWM (Space Vector Pulse Width Modulation), three-phase PWM waves varying with time can be generated by fixed Ud equal to 0 and Uq equal to 10000, and finally, a rotating vector is synthesized to drive the motor rotor to rotate.
The invention adopts more convenient interface operation, so that a user can better know the function of the product, a UI interface is designed as an upper computer, the upper computer and a control panel can be communicated by clicking the buttons through defining different buttons, and the control panel executes the response action after obtaining the corresponding instruction, and the interface of the upper computer is shown in figure 7.
The whole method does not need to pass the earlier stage of testing, debugging, code writing and other works for any type of direct current brushless motor, and the motor can learn parameters by a designed algorithm. If the equipment is powered off, the parameter information is stored in the FLASH area in the chip in advance, so that the data cannot be lost along with the power off, and the experience obtained by self-learning is stored. The running state of the motor is detected in real time and displayed on the upper computer in real time, so that a user can more intuitively feel the parameter change of the related motor. The success rate of self-learning is increased through multiple self-learning training words.
The foregoing is a preferred embodiment of the present invention, and modifications, obvious to those skilled in the art, of the various equivalent forms of the present invention can be made without departing from the principles of the present invention, are intended to be within the scope of the appended claims.
Claims (6)
1. A control method for self-learning the Hall position of a DC brushless motor based on a vector algorithm is characterized by comprising the following steps: the method comprises the following steps:
s1, determining the relation between the power-on sequence of a direct-current brushless motor and a Hall sensor to obtain a Hall sector, configuring parameters of an upper computer, and then sending an instruction to a control board;
s2, after receiving the instruction, the control board firstly learns the Hall sector by itself, and stores the Hall sector obtained by self-learning into FLASH in the chip;
the self-learning specific steps of the Hall sector are as follows: the rotor is moved to a designated position through the sequence of electrifying the direct current brushless motor, and a Hall state of the position is obtained; according to the sequence of power on, each time lasts for 100ms, the magnetic moment generated by the stator moves the rotor within 100ms, the obtained halltate is stored in a two-dimensional array BUFF, six reversals are needed in one period, 600ms is needed, 10 times of self-learning is needed, whether the bus current value is smaller than a set value or not is detected through a control method of six reversals, and whether self-learning is successful or not is verified;
s3, after the self-learning of the Hall sector is successful, performing self-learning of the FOC algorithm, calculating the electric speed of the motor operation through the sector, and calculating the current angle value through the electric speed;
s4, in the FOC algorithm, fixed parameters Ud and Uq are set, three paths of PWM waves are generated through the calculated angle values and are input into a three-phase stator of the motor, and the rotor is driven to rotate;
the solution of the hall angle is achieved by integrating the speed:
first, using a timer, the time T taken to walk through a Hall sector is calculated oneSec Measuring the speed by a T method;
next, T is used oneSec Calculate at a carrier period T carrier Angle delta theta of inner needed walk e ；
Finally, in each carrier interruption, accumulating the angle value each time to realize continuous integration of angles;
here Δθ e The angular velocity omega is updated every time the Hall sector jumps through the velocity estimation of the last sector e And clearing the value of the register; fixed deviation angle θ error The actual angle value finally calculated by the hall sector is:
θ result ＝θ Cumulate +θ error
in θ Cumulate The angle value theta obtained by integrating and accumulating Hall sectors error For a fixed offset value of 30 DEG, theta result The angle value obtained finally is used.
2. The control method for self-learning the Hall position of the DC brushless motor based on the vector algorithm according to claim 1, wherein the control method is characterized by comprising the following steps: the mounting positions of the three Hall devices are different by 120 degrees, 6 different Hall signal combinations are output, 6 different areas are respectively corresponding to the three Hall devices, and the specific relation between the power-on sequence of the DC brushless motor and the Hall sensors is as follows:
wherein "×" represents the correlation, "∈v" represents the phase on, the high level signal is 1, and the low level signal is 0.
3. The control method for self-learning the Hall position of the DC brushless motor based on the vector algorithm according to claim 1, wherein the control method is characterized by comprising the following steps: the self-learning of the FOC algorithm is divided into two times, the first self-learning algorithm obtains Hall wire bundles corresponding to the stator windings of the motor in a three-phase one-to-one mode, the second self-learning algorithm obtains the position of a zero-degree sector, and the sequence of sector change corresponding to forward and reverse rotation of the motor is known.
4. A control method for self-learning a hall position of a brushless dc motor based on a vector algorithm according to claim 2 or 3, wherein: before the motor operates, three-phase Hall switch signals are required to be read, and the Hall sector angle where the current rotor is positioned is determined, wherein the maximum deviation between the angle and the actual angle is +/-30 degrees; after the motor rotates stably, 6 accurate Hall sector angles can be obtained in one electric period; when the rotating speed is calculated, the signal capturing function is utilized to trigger interruption, and the counting result is read in the interruption and used for calculating the rotating speed, simultaneously emptying counting and entering the next sector counting; the motor rotates for one electric period, and Hall generates 6 sector changes; in omega e The electrical angular velocity of the motor is represented by the following calculation formula:
where RegisterCnt is the read timer count value, f timer Is the frequency of the timer configuration; the mechanical rotation speed is 1/P times of the electrical angular speed, and the formula is as follows:
wherein P is the pole pair number, omega of the motor m Representing the mechanical angular velocity of the motor.
5. The control method for self-learning the Hall position of the DC brushless motor based on the vector algorithm according to claim 1, wherein the control method is characterized by comprising the following steps: to finally obtain theta result And inputting the three-phase time-varying PWM waves into SVPWM, generating three-phase time-varying PWM waves by fixed Ud being equal to 0 and Uq being equal to 10000, and finally synthesizing a rotating vector to drive a motor rotor to rotate.
6. The control method for self-learning the Hall position of the DC brushless motor based on the vector algorithm according to claim 1, wherein the control method is characterized by comprising the following steps: the upper computer designs a UI interface, the UI interface is operated to enable the upper computer to communicate with the control board, and the control board executes a response action after obtaining a corresponding instruction.
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| CN110380653A (en) * | 2019-06-17 | 2019-10-25 | 江苏大学 | Vector controlled location estimation compensation method based on hall position sensor |
| WO2020031882A1 (en) * | 2018-08-08 | 2020-02-13 | 日本電産株式会社 | Position estimation method, motor control device and motor system |
| CN111245307A (en) * | 2020-03-19 | 2020-06-05 | 深圳市微秒控制技术有限公司 | Hall line sequence self-adaptive learning method of brushless motor |
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| WO2020031882A1 (en) * | 2018-08-08 | 2020-02-13 | 日本電産株式会社 | Position estimation method, motor control device and motor system |
| CN110380653A (en) * | 2019-06-17 | 2019-10-25 | 江苏大学 | Vector controlled location estimation compensation method based on hall position sensor |
| CN111245307A (en) * | 2020-03-19 | 2020-06-05 | 深圳市微秒控制技术有限公司 | Hall line sequence self-adaptive learning method of brushless motor |
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| 《霍尔转子位置预估方法及其误差校正》;荀倩;《电工技术学报》;第32卷(第6期);全文 * |
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