CN111953241B - Permanent magnet synchronous motor rotor position deviation compensation method, control device and automobile - Google Patents

Permanent magnet synchronous motor rotor position deviation compensation method, control device and automobile Download PDF

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CN111953241B
CN111953241B CN201910405870.XA CN201910405870A CN111953241B CN 111953241 B CN111953241 B CN 111953241B CN 201910405870 A CN201910405870 A CN 201910405870A CN 111953241 B CN111953241 B CN 111953241B
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vehicle
position deviation
rotor position
longitudinal vibration
delta
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CN111953241A (en
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李玮
刘超
梁海强
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Beijing Electric Vehicle Co Ltd
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Beijing Electric Vehicle Co Ltd
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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
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L15/00—Methods, circuits, or devices for controlling the traction-motor speed of electrically-propelled vehicles
    • B60L15/20—Methods, circuits, or devices for controlling the traction-motor speed of electrically-propelled vehicles for control of the vehicle or its driving motor to achieve a desired performance, e.g. speed, torque, programmed variation of speed
    • 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
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/60—Other road transportation technologies with climate change mitigation effect
    • Y02T10/64—Electric machine technologies in electromobility
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/60—Other road transportation technologies with climate change mitigation effect
    • Y02T10/72—Electric energy management in electromobility

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  • Power Engineering (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Control Of Motors That Do Not Use Commutators (AREA)

Abstract

The invention discloses a position deviation compensation method of a permanent magnet synchronous motor rotor, a control device and an automobile, wherein the method comprises the following steps: acquiring longitudinal vibration information of a vehicle and first state information of the vehicle; calculating a first longitudinal vibration parameter Q of the vehicle according to the longitudinal vibration information of the vehicle1(ii) a According to a first longitudinal vibration parameter Q of the vehicle1Obtaining a first rotor position deviation estimated value delta E through the RBF radial basis function neural network; and performing rotor position deviation compensation control according to the first rotor position deviation estimated value delta E. The method for compensating the position deviation of the permanent magnet synchronous motor rotor realizes the detection, verification and compensation of the small angle deviation of the position of the motor rotor, solves the problem of unsmooth vehicle running caused by the small angle deviation of the position of the motor rotor, ensures the riding comfort of personnel on the vehicle, does not involve the change of drive system hardware, has low cost and has wide popularization value.

Description

Permanent magnet synchronous motor rotor position deviation compensation method, control device and automobile
Technical Field
The invention relates to the technical field of motors, in particular to a permanent magnet synchronous motor rotor position deviation compensation method, a control device and an automobile.
Background
The pure electric vehicle is different from a traditional fuel vehicle, the pure electric vehicle drives wheels through a motor to realize vehicle running, the motor is used as a core component of the pure electric vehicle and has a great influence on the performance of the whole vehicle, wherein a permanent magnet synchronous motor (PMSM for short) has the advantages of high efficiency, high output torque, high power density, good dynamic performance and the like, and is the mainstream of a pure electric vehicle driving system at present. For a pure electric vehicle taking a permanent magnet synchronous motor as a power core, the precise detection of the position of a rotor is the premise of realizing high-precision control, and the permanent magnet synchronous motor adopts electronic commutation, so that the position information of the rotor directly influences the speed of the motor, the precision of position control and the dynamic performance. Considering that the running environment of a vehicle as a basic transport means is complex and changeable, under special and some limit working conditions, the zero position deviation of a motor rotor can be caused by factors such as vibration, temperature, component aging and the like, the zero position deviation of the rotor of the permanent magnet synchronous motor can cause unexpected and uncontrollable cross-axis current, and when the zero position deviation is serious, overcurrent and even power output out of control can be caused in the motor control process; when the zero point deviation is small, the smoothness of the power output of the driving system is influenced, and the smoothness is most intuitively represented as the vehicle shakes, wherein the shake degree is related to the deviation angle.
Regarding the estimation of the position deviation of the permanent magnet synchronous motor rotor of the pure electric vehicle, a great deal of research results are available at present, but the estimation precision and the engineering applicability of the estimation result are still to be improved, for the pure electric vehicle, due to the limitation of controller hardware, the calculation amount required by the position deviation estimation algorithm is required to be as small as possible, the estimation precision is accurate, and meanwhile, the estimation can be realized on line, and at present, no method which is mature in application, reliable and effective can simultaneously meet the requirements is available. In addition, for a pure electric vehicle driving system, when the zero deviation of the motor rotor position is large, the conditions of motor phase current overcurrent, torque output runaway and the like can be directly caused, corresponding faults can be triggered when the conditions are generated, and the vehicle can be protected through a corresponding fault mechanism at the moment, so that the large-angle deviation is not the problem to be solved urgently at present. However, the small-angle deviation of the zero point of the motor position is not so high, and the small-angle deviation can be represented by the phenomena of shaking, unsmooth power output and the like in the actual running process of the vehicle, so that the unsmooth driving safety cannot cause great hidden danger, and other fail-safe protection mechanisms cannot be triggered at the same time, but the driving feeling of people on the vehicle can be seriously influenced.
Disclosure of Invention
In order to solve the technical problems, the invention provides a permanent magnet synchronous motor rotor position deviation compensation method, a control device and an automobile, and solves the problem that small-angle deviation of the motor rotor position seriously affects the driving feeling of people on the automobile.
In order to solve the technical problem, the invention is realized as follows:
according to a first aspect of the present invention, there is provided a method for compensating for a rotor position deviation of a permanent magnet synchronous motor, the method comprising:
acquiring longitudinal vibration information of a vehicle and first state information of the vehicle;
calculating a first longitudinal vibration parameter Q of the vehicle according to the longitudinal vibration information of the vehicle1；
According to a first longitudinal vibration parameter Q of the vehicle1Obtaining a first rotor position deviation estimated value delta E through the RBF radial basis function neural network;
and performing rotor position deviation compensation control according to the first rotor position deviation estimated value delta E.
Optionally, the step of acquiring longitudinal vibration information of the vehicle includes:
and in the process of actively discharging the driving system in the static state of the vehicle, longitudinal vibration information of the vehicle is acquired through the acceleration sensor.
Optionally, the step of acquiring first state information of the vehicle includes:
the method comprises the steps that in a static state of a vehicle, first state information of the vehicle is obtained before a driving system actively discharges;
the first state information of the vehicle includes: first DC bus voltage V of vehicle1First driving wheel average tire pressure P of vehicle1。
Optionally, a first longitudinal vibration parameter Q of the vehicle is calculated according to the longitudinal vibration information of the vehicle1The method comprises the following steps:
carrying out second-order low-pass filtering processing on the longitudinal vibration information of the vehicle to obtain a first filtering signal;
calculating a first longitudinal vibration parameter Q of the vehicle according to the first filtering signal1。
Optionally, the step of calculating a first longitudinal vibration parameter of the vehicle from the first filtered signal comprises:
by the formula
Figure BDA0002061198440000031
Calculating a first longitudinal vibration parameter of the vehicle;
wherein Q is1Representing a first longitudinal vibration parameter, T, of the vehiclesIndicating the control period, TendIndicates the time required from the start to the end of the active discharge, Acc(n) denotes the first filtered signal.
Optionally, according to a first longitudinal vibration parameter Q of the vehicle1And first state information of the vehicle, obtaining a first rotor position deviation estimated value delta E through the RBF radial basis function neural network, comprising:
calculating a first longitudinal vibration parameter Q of the vehicle1And the first state information of the vehicle is used as an input value of the RBF neural network, and a first rotor position deviation estimated value delta E output by the RBF radial basis function neural network is obtained.
Optionally, before the step of obtaining the first rotor position deviation estimation value Δ E through the RBF radial basis function neural network, the method further includes:
executing active discharge experiments for multiple times to obtain multiple groups of ideal training data;
wherein each set of the ideal training data comprises: the method comprises the steps of presetting a motor rotor position deviation value, vehicle state information and vehicle longitudinal vibration parameters;
and training the RBF neural network according to the plurality of groups of ideal training data.
Optionally, the step of the active discharge experiment includes:
manually presetting a rotor position deviation value of a motor;
under the static state of the vehicle, developing an active discharge experiment under different vehicle state information conditions to obtain a longitudinal vibration information experiment value of the vehicle;
and calculating the longitudinal vibration parameters of the vehicle according to the longitudinal vibration information experiment value of the vehicle.
Optionally, the step of performing rotor position deviation compensation control according to the first rotor position deviation estimated value Δ E includes:
judging the actual sign of the first rotor position deviation estimated value delta E and obtaining a sign judgment result;
wherein the symbol judgment result comprises: the sign of the first rotor position deviation estimated value delta E is a negative value, the sign of the first rotor position deviation estimated value delta E is a positive value, and the first rotor position deviation estimated value delta E is an invalid value;
and performing rotor position deviation compensation control according to the symbol judgment result.
Optionally, the step of determining the sign of the first rotor position deviation estimate Δ E comprises:
decomposing said first rotor position deviation estimate Δ E into four deviation values, said four deviation values comprising: a Δ E, -a Δ E, and- Δ E;
wherein a is more than 0 and less than 1;
compensating the rotor position deviation according to the deviation value a delta E, and calculating a compensated position deviation value delta E through an RBF neural network1；
Compensating the rotor position deviation according to the deviation value delta E, and calculating a compensated position deviation binary value delta E through an RBF neural network2；
Compensating the rotor position deviation according to the deviation value-a delta E, and calculating three values delta E of the compensated position deviation through an RBF neural network3；
Compensating the rotor position deviation according to the deviation value-delta E, and calculating four values of the compensated position deviation delta E through an RBF neural network4；
If said Δ E1、ΔE2、ΔE3、ΔE4If the first condition is met, judging the sign of the first rotor position deviation estimated value delta E to be a negative value; wherein the first condition is:
ΔE4＜ΔE3and Δ E1＞ΔE3，ΔE2＞ΔE3，ΔE1＞ΔE4，ΔE2＞ΔE4；
If said Δ E1、ΔE2、ΔE3、ΔE4If the first condition is met, judging the sign of the first rotor position deviation estimated value delta E to be a positive value; wherein the second condition is:
ΔE2＜ΔE1and Δ E3＞ΔE1，ΔE3＞ΔE2，ΔE4＞ΔE1，ΔE4＞ΔE2；
If said Δ E1、ΔE2、ΔE3、ΔE4If the first condition is not met and the second condition is not met, the estimated value delta E of the position deviation of the first rotor is judged to be an invalid value.
Optionally, the step of performing rotor position deviation compensation control according to the symbol determination result includes:
if the actual sign of the first rotor position deviation estimated value delta E is judged to be a negative value, compensating the rotor position deviation according to-delta E;
if the sign of the first rotor position deviation estimated value delta E is judged to be a positive value, compensating the rotor position deviation according to the delta E;
and if the first rotor position deviation estimated value delta E is judged to be an invalid value, the rotor position deviation is not compensated.
According to a second aspect of the present invention, there is provided a permanent magnet synchronous motor rotor position deviation compensation control apparatus, comprising:
the acquisition module is used for acquiring longitudinal vibration information of the vehicle and first state information of the vehicle;
a first calculation module for calculating a first longitudinal vibration parameter Q of the vehicle according to the longitudinal vibration information of the vehicle1；
A second calculation module for calculating a first longitudinal vibration parameter Q of the vehicle1Obtaining a first rotor position deviation estimated value delta E through the RBF radial basis function neural network;
and the processing module is used for carrying out rotor position deviation compensation control according to the first rotor position deviation estimated value delta E.
According to a third aspect of the present invention, there is provided a vehicle comprising a processor, a memory, and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the method for compensating for rotor position deviation of a permanent magnet synchronous motor as described above when executing the computer program.
According to a fourth aspect of the present invention, a computer-readable storage medium is provided, on which a computer program is stored, which computer program, when being executed by a processor, realizes the steps of the method for compensating for a rotor position deviation of a permanent magnet synchronous motor as described above.
The embodiment of the invention has the beneficial effects that:
according to the scheme, the longitudinal vibration information of the vehicle is obtained, the first longitudinal vibration parameter of the vehicle is calculated according to the longitudinal vibration information of the vehicle, the RBF radial basis function neural network is creatively introduced on the basis, the first rotor position deviation estimated value delta E of the motor is calculated and obtained through the RBF neural network and by utilizing the obtained first longitudinal vibration information of the vehicle and combining the obtained first state information of the vehicle, and the rotor position deviation is compensated and controlled according to the first rotor position deviation estimated value delta E after the first rotor position deviation estimated value delta E of the motor is obtained. The scheme realizes accurate estimation of the small-angle deviation of the position of the motor rotor, and compensates the motor position deviation by using the estimated value on the basis, thereby avoiding the problem of non-smooth vehicle operation caused by the small-angle position deviation of the motor rotor and ensuring the riding comfort of personnel on the vehicle. In addition, the scheme does not involve the change of the hardware of the driving system, so the method has wide popularization value.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments of the present invention will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without inventive exercise.
FIG. 1 is a flow chart illustrating a method for compensating for rotor position deviation of a PMSM according to an embodiment of the present invention;
FIG. 2 illustrates a schematic diagram of motor zero offset torque generation according to an embodiment of the present invention;
FIG. 3 is a block diagram of an RBF neural network according to an embodiment of the present invention;
FIG. 4 is a diagram illustrating a position compensation control logic implementation of an embodiment of the present invention;
fig. 5 is a schematic structural diagram of a rotor position deviation compensation control device of a permanent magnet synchronous motor according to an embodiment of the present invention.
Detailed Description
Exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention can be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.
Firstly, a longitudinal vibration mechanism of a permanent magnet synchronous motor rotor position small angle deviation vehicle is introduced:
regarding the permanent magnet synchronous motor in the pure electric vehicle, in the case of small angle deviation of the rotor position, the most direct behavior is vehicle longitudinal vibration, however, the vibration is easily ignored during the vehicle running process, the transmission system of the vehicle can be simplified into a two-mass model, which includes a large number of elastic mechanisms, such as vehicle transmission shafts, transmissions, tires, etc., which can cause the vibration during the vehicle running process, and the vibration is complicated by the influence of suspension and road surface factors, so the vehicle longitudinal vibration caused by the small angle deviation of the rotor position can be easily annihilated in the "noise". In order to solve the problem, the deviation is not detected in a driving state so as to avoid introducing interference, the active discharging operation of a driving system is required to be executed before the vehicle is powered off (the active discharging refers to that the electric charges stored in the driving system and a vehicle direct current bus are consumed in a three-phase winding of a motor in a heat mode by controlling the dq-axis current of the permanent magnet synchronous motor on the premise of ensuring that the driving motor does not output torque so as to avoid electric shock risks of vehicle maintainers), the vehicle is static during the active discharging, and the influence of results of factors such as vehicle suspension, road surface and the like can be eliminated by detecting the position deviation. Therefore, the invention carries out the detection and compensation control of the rotor position deviation in the active discharging process.
For the plug-in permanent magnet synchronous motor, the output torque equation is as follows:
Figure BDA0002061198440000061
wherein T iseRepresenting motor output torque, p0Representing the number of pole pairs, ψ of the motorfDenotes the permanent magnet flux linkage, LdAnd LqRepresenting the dq-axis inductance, i, of the machinedAnd iqRepresenting the dq-axis current of the motor. According to the output torque formula, the final output torque of the motor is 0 no matter how the d-axis current takes the value under the condition that the q-axis current command is 0, so that the q-axis current command i is given in the active discharging process of the motorqIs 0, the d-axis current command is taken as a fixed value id＝Kdis(in general K)dis< 0) so as to realize an active discharge function with a discharge speed and K on the premise of ensuring that the driving motor does not output powerdisIt is related. The active discharge process is described above, but this is only an ideal state, when there is a deviation of the zero point of the rotor position of the motor, the driving motor will output power during the active discharge process, for the concrete principle, please refer to the schematic diagram of the zero point deviation torque generation of the motor in fig. 2, fig. 2 is the active discharge process, which shows that, during the active discharge control process, the given q-axis current command is 0, so the phase current vector i under the ideal state is the current vector i under the ideal statesAlong the direction of the d axis; but the actual current vector is shown as i in the figure due to the deviation of the zero point of the motorrsAs shown, this causes a current component, i.e., i, to be generated in the q-axis directionqNot equal to 0. Because the actual current of the q axis is not zero, the actual output torque T of the motor is obtained according to the output torque formulaeAnd is also not zero, which is the principle of the unexpected output of the torque of the driving motor due to the zero offset.
The invention utilizes the characteristic of vibration to estimate the zero point position deviation of the motor rotor and carry out subsequent compensation control.
As shown in fig. 1, an embodiment of the present invention provides a method for compensating for a rotor position deviation of a permanent magnet synchronous motor, where the method includes:
step 11: longitudinal vibration information of a vehicle and first state information of the vehicle are acquired.
In this embodiment, since the vibration condition of the vehicle is closely related to the deviation degree of the zero point of the rotor, in this embodiment, longitudinal vibration information of the vehicle is acquired during the active discharge of the vehicle. Meanwhile, in the active discharging process of the vehicle, a complex nonlinear relationship exists between the longitudinal vibration condition of the vehicle and the state of the vehicle before discharging, so the embodiment first acquires the longitudinal vibration information of the vehicle and the first state information of the vehicle, and performs the subsequent method steps on the basis of the longitudinal vibration information and the first state information of the vehicle.
Step 12: calculating a first longitudinal vibration parameter Q of the vehicle according to the longitudinal vibration information of the vehicle1。
In this embodiment, a longitudinal vibration parameter of the vehicle is defined, specifically, a first longitudinal vibration parameter Q in this embodiment1Here, the vehicle longitudinal vibration parameter, which is a dimensionless parameter specifically proposed by the present invention for calculating the rotor position deviation, is emphasized, and the longitudinal vibration parameter is a totality of the vibration degree of the vehicle during the active discharge of the vehicleAnd evaluating, namely representing the longitudinal shaking strength of the vehicle caused by the zero deviation of the motor rotor in the active discharging process by using a first characteristic, and reflecting the vibration condition of the vehicle in the active discharging process of the vehicle. Specifically, in the present embodiment, the first longitudinal vibration parameter Q of the vehicle1And calculating according to the acquired longitudinal vibration information of the vehicle.
Step 13: according to a first longitudinal vibration parameter Q of the vehicle1And first state information of the vehicle, and obtaining a first rotor position deviation estimated value delta E through the RBF radial basis function neural network.
In this embodiment, since a complex nonlinear relationship exists between the longitudinal vibration information of the vehicle and the first state information of the vehicle during the active discharge, it is impossible to describe the relationship by an accurate mathematical expression. Considering that a neural network method has nonlinear basic characteristics and has natural advantages for solving nonlinear problems, and the RBF radial basis function neural network is used as a feedforward type neural network with excellent performance, can approach any nonlinear function at any precision, has compact topological structure and global approximation capability, and solves the local optimal problem of a BP network1And under the condition of the first state information, calculating a first rotor position deviation estimated value delta E by using the RBF neural network.
Step 14: and performing rotor position deviation compensation control according to the first rotor position deviation estimated value delta E.
In this embodiment, the first rotor position deviation estimated value Δ E calculated by the RBF neural network is used to perform subsequent rotor position deviation compensation and subsequent drive system control through the first rotor position deviation estimated value Δ E. According to the embodiment provided by the invention, the compensation control of the small-angle deviation of the position of the motor rotor is realized by utilizing the estimated value delta E of the position deviation of the first rotor, the phenomenon of unsmooth running of vehicles such as 'shaking' caused by the small-angle position deviation of the motor rotor is avoided, and the riding comfort of people on the vehicles is ensured.
In a preferred embodiment of the present invention, the step 11 of acquiring the longitudinal vibration information of the vehicle and the first state information of the vehicle may specifically include:
and in the process of actively discharging the driving system in the static state of the vehicle, longitudinal vibration information of the vehicle is acquired through the acceleration sensor.
The method comprises the steps that in a static state of a vehicle, first state information of the vehicle is obtained before a driving system actively discharges; wherein the first state information of the vehicle includes: first DC bus voltage V of vehicle1First driving wheel average tire pressure P of vehicle1。
In the embodiment, the longitudinal vibration information of the vehicle is obtained through the vehicle-mounted acceleration sensor by utilizing the active discharging process of the driving system in the static state of the vehicle before the vehicle is powered off, and the first direct current bus voltage V of the vehicle is obtained before the driving system is actively discharged1And the first driving wheel average tire pressure P of the vehicle1And waiting for first state information of the vehicle. According to the embodiment, the longitudinal vibration information of the vehicle and the first state information of the vehicle are acquired in the active discharging process of the driving system in the static state of the vehicle, so that the longitudinal vibration information of the vehicle and the first state information of the vehicle are acquired under the condition that the riding feeling of passengers on the vehicle is guaranteed, and the rotor position deviation condition of the motor is detected under the condition that the driving is not influenced.
In a preferred embodiment of the present invention, in step 12, a first longitudinal vibration parameter Q of the vehicle is calculated according to the longitudinal vibration information of the vehicle1The method specifically comprises the following steps:
carrying out second-order low-pass filtering processing on the longitudinal vibration information of the vehicle to obtain a first filtering signal;
calculating a first longitudinal vibration parameter Q of the vehicle according to the first filtering signal1。
In this embodiment, as described in the above embodiments, the vehicle first longitudinal vibration parameter Q1The method is a dimensionless parameter specially proposed by the embodiment of the invention and is used for calculating the zero position deviation of the rotor of the motor. The longitudinal vibration parameter Q1In the embodiment of the present invention, an acceleration sensor in a vehicle is used to obtain a longitudinal acceleration signal of the vehicle, specifically, longitudinal vibration information of the vehicle may be the longitudinal acceleration signal, in the embodiment, first, second-order low-pass filtering is performed on the longitudinal vibration information, that is, the longitudinal acceleration signal, and a first longitudinal vibration parameter Q is calculated by using a first filtered signal obtained after filtering1. The detailed steps of the second-order low-pass filtering of the longitudinal vibration information of the vehicle will be described below:
the method comprises the steps of defining longitudinal vibration information of a vehicle, which is obtained by a vehicle acceleration sensor, namely an original value of a longitudinal acceleration signal is A, and carrying out second-order low-pass filtering on the longitudinal vibration information, so as to filter medium-high frequency interference suffered in the signal acquisition process. The second-order low-pass filtering method is a mature filtering method at present, wherein the second-order low-pass filtering processing is specifically realized as follows:
Acc(n)＝Ft(n)-Ft(n-2)；
in the above formula, AccRepresenting the longitudinal acceleration information of the vehicle obtained by second-order low-pass filtering of the control cycle, i.e. the first filtered signal, where Ft(n) is an intermediate variable expressed as:
Ft(n)＝A(n)Ka-KbFt(n-1)-KcFt(n-2)；
in the above formula, a (n) represents the original longitudinal acceleration signal of the vehicle acquired in the present null period; ka、KbAnd KcRepresenting the filter coefficients, which are used to adjust parameters such as the low pass filter cut-off frequency.
In particular, in a preferred embodiment of the invention, a first longitudinal vibration parameter Q of the vehicle is calculated on the basis of said first filtered signal1The step (b) may comprise:
by the formula
Figure BDA0002061198440000101
Calculating a first longitudinal vibration parameter Q of the vehicle1。
Wherein Q is1Representing a first longitudinal vibration parameter, T, of the vehiclesIndicating the control period, TendIndicates the time required from the start to the end of the active discharge, Acc(n) denotes the first filtered signal.
In this embodiment, the first filtered signal a is obtained by means of a second order low-pass filteringcc(n) performing a first longitudinal vibration parameter Q of the vehicle by the vibration parameter formula1According to the vibration parameter formula, the first longitudinal vibration parameter Q of the vehicle can be seen1In fact, it is an overall estimation of the vibration level of the vehicle during active discharge, and ideally (i.e. the motor has no torque output), a (n) should be 0, corresponding to Q1Is 0. But the unexpected output of the torque of the driving motor is caused due to the existence of the zero point deviation of the rotor position, and the vibration is generated in the longitudinal direction under the action of mechanisms such as a vehicle suspension, a tire, a half shaft and the like, and the vibration parameter Q is according to the first longitudinal vibration parameter Q1By the calculation formula of (a) longitudinal vibration information A for the vehiclecc(n) (taking absolute value) is integrated in a discrete form, and the first longitudinal vibration parameter Q obtained at this time1The vibration condition of the vehicle in the active discharging process can be reflected.
Wherein, in a preferred embodiment of the present invention, in step 13, according to a first longitudinal vibration parameter Q of the vehicle1And first state information of the vehicle, the step of obtaining the first rotor position deviation estimated value delta E through the RBF radial basis function neural network may include:
calculating a first longitudinal vibration parameter Q of the vehicle1And the first state information of the vehicle is used as an input value of the RBF neural network, and a first rotor position deviation estimated value delta E output by the RBF radial basis function neural network is obtained.
In this embodiment, referring to fig. 3, a block diagram of an RBF neural network is shown, and the RBF neural network provided in this embodiment is divided into three layers, an input layer, a hidden layer andan output layer, wherein the input quantity is three terms, and the three terms are respectively a first longitudinal vibration parameter Q1First DC bus voltage V of the vehicle at the moment before the active discharge1And the first driving wheel average tire pressure P of the vehicle1(ii) a The output is the first rotor position deviation estimate deltae.
As can be seen from fig. 3, the first longitudinal vibration parameter Q of the vehicle obtained by calculating1And first state information of the vehicle (first DC bus voltage V of the vehicle at a previous time of active discharge)1And the first driving wheel average tire pressure P of the vehicle1) As an input value of the RBF radial basis function neural network, the RBF radial basis function neural network can further estimate and output the first rotor position deviation estimated value Δ E. In detail, a specific expression for calculating the first rotor position deviation estimated value Δ E by the RBF neural network is as follows:
Figure BDA0002061198440000111
in the expression formula of the RBF radial basis function neural network, x is an input vector, i.e., x ═ Q1 V1 P1]Y (x, w) is the network output, i.e. the calculated estimated value Δ E of the position deviation of the first rotor; w is aiIs a weight; l is the number of hidden layer neurons, and preferably, l is 7; c. CiIs a central vector; i x-ci| | is the distance from the input vector to the node center (center vector); φ is a radial basis function, here taken as a Gaussian radial basis function.
The RBF neural network is a neural network application scheme which is mature at present, is a feedforward neural network with excellent performance, can approach any nonlinear function at any precision, and can solve the complex nonlinear relation existing between the vibration condition of the vehicle and the first state information of the vehicle. Therefore, the first longitudinal vibration parameter Q can be utilized through the RBF neural network1And first state information of the vehicle (first DC bus voltage V of the vehicle at the moment before the active discharge1And the first driving wheel average tire pressure P of the vehicle1) Estimating a first revolutionThe sub-position deviation estimate deltae.
Importantly, in order to improve the calculation accuracy of the RBF radial basis function neural network, in a preferred embodiment of the present invention, before the step of obtaining the first rotor position deviation estimated value Δ E by the RBF radial basis function neural network, the method may further include:
executing active discharge experiments for multiple times to obtain multiple groups of ideal training data;
wherein each set of the ideal training data comprises: the method comprises the steps of presetting a motor rotor position deviation value, vehicle state information and vehicle longitudinal vibration parameters;
and training the RBF neural network according to the plurality of groups of ideal training data.
Wherein, further, the step of the active discharge experiment may include: manually presetting a rotor position deviation value of a motor; under the static state of the vehicle, developing an active discharge experiment under different vehicle state information conditions to obtain a longitudinal vibration information experiment value of the vehicle; and calculating the longitudinal vibration parameters of the vehicle according to the longitudinal vibration information experiment value of the vehicle.
In this embodiment, the calculation accuracy of the RBF neural network is good or bad depending on whether the data for training the neural network is accurate, reliable, and efficient. Therefore, how to obtain ideal training data required for training the RBF neural network shown in fig. 3 is inseparable from designing the RBF neural network, and in view of this problem, the present invention provides a method for obtaining ideal training data, that is, multiple sets of ideal training data are obtained by performing active discharge experiments for multiple times, and the detailed steps are as follows:
manually calibrating the zero point of the motor rotor position, namely manually setting the zero point deviation of the motor rotor position of the small angle, and defining the deviation as E;
secondly, under the static state of the vehicle, an active discharge test is carried out under the conditions of different vehicle direct-current bus voltage V and vehicle driving wheel tire pressure P, and the longitudinal vibration parameter Q of the vehicle in the test is obtained by collecting the longitudinal acceleration generated by the vehicle in the active discharge process and utilizing the same method in the embodiment;
and thirdly, taking [ Q V P | E | as the ideal training data of the RBF neural network determined by the test. The absolute value of the small-angle position deviation E set manually in the step I is processed, because Q is an evaluation parameter reflecting the longitudinal vibration degree caused by the position deviation of the motor rotor in the active discharging process, and no matter whether E is a positive deviation or a negative deviation, the absolute value cannot be directly reflected through the longitudinal vibration parameter Q of the vehicle, namely the vibration parameters at the moment are basically consistent, so the absolute value of the set small-angle position deviation E is considered to be used as a group of ideal training data of the RBF neural network in the invention.
By repeatedly executing the steps I, II and III, a large number of groups of ideal training data can be obtained, and the RBF neural network shown in the figure 3 is trained by utilizing the ideal data obtained by the active discharge test method, so that the trained neural network has higher calculation precision.
It should be noted that, since all the data about the zero-point deviation of the motor rotor in the ideal training data are positive values, the estimated value Δ E of the zero-point deviation of the motor rotor calculated by using the RBF neural network is also positive values, which obviously ignores the case that Δ E is negative. This problem is solved in step 14.
In a preferred embodiment of the present invention, in step 14, the step of performing rotor position deviation compensation control according to the first estimated rotor position deviation Δ E may specifically include:
judging the actual sign of the first rotor position deviation estimated value delta E and obtaining a sign judgment result;
wherein the symbol judgment result comprises: the sign of the first rotor position deviation estimated value delta E is a negative value, the sign of the first rotor position deviation estimated value delta E is a positive value, and the first rotor position deviation estimated value delta E is an invalid value;
and performing rotor position deviation compensation control according to the symbol judgment result.
In this embodiment, as can be seen from the above embodiment, in order to always make a positive value for the first rotor position deviation estimated value Δ E obtained by using the calculation of the RBF neural network, and to determine the sign of the first rotor position deviation estimated value Δ E and verify the correctness of the estimation result, the present embodiment first determines the actual sign of the first rotor position deviation estimated value Δ E, obtains a sign determination result, and further performs compensation control on the rotor position deviation according to the sign determination result.
Specifically, the step of determining the sign of the first rotor position deviation estimated value Δ E includes:
decomposing said first rotor position deviation estimate Δ E into four deviation values, said four deviation values comprising: a Δ E, -a Δ E, and- Δ E;
wherein a is more than 0 and less than 1;
compensating the rotor position deviation according to the deviation value a delta E, and calculating a compensated position deviation value delta E through an RBF neural network1；
Compensating the rotor position deviation according to the deviation value delta E, and calculating a compensated position deviation binary value delta E through an RBF neural network2；
Compensating the rotor position deviation according to the deviation value-a delta E, and calculating three values delta E of the compensated position deviation through an RBF neural network3；
Compensating the rotor position deviation according to the deviation value-delta E, and calculating four values of the compensated position deviation delta E through an RBF neural network4；
If said Δ E1、ΔE2、ΔE3、ΔE4If the first condition is met, judging the sign of the first rotor position deviation estimated value delta E to be a negative value; wherein the first condition is:
ΔE4＜ΔE3and Δ E1＞ΔE3，ΔE2＞ΔE3，ΔE1＞ΔE4，ΔE2＞ΔE4；
If said Δ E1、ΔE2、ΔE3、ΔE4According to the second barIf the first rotor position deviation estimated value delta E is a positive value, judging the sign of the first rotor position deviation estimated value delta E to be a positive value; wherein the second condition is:
ΔE2＜ΔE1and Δ E3＞ΔE1，ΔE3＞ΔE2，ΔE4＞ΔE1，ΔE4＞ΔE2；
If said Δ E1、ΔE2、ΔE3、ΔE4If the first condition is not met and the second condition is not met, the estimated value delta E of the position deviation of the first rotor is judged to be an invalid value.
In this embodiment, referring to fig. 4, which shows a block diagram of an implementation of position compensation control logic, according to fig. 4, in an embodiment of the present invention, a first rotor position deviation estimated value Δ E calculated by an RBF neural network is first decomposed into four sub-deviation values a Δ E, -a Δ E, and- Δ E; wherein a is more than 0 and less than 1. In this embodiment, preferably, a is taken to be 0.5, and therefore preferably, the first rotor position deviation estimate Δ E is decomposed into a deviation of 1: 0.5 Δ E; deviation 2: Δ E; deviation 3: -0.5 Δ Ε; deviation 4: - Δ E. And then, respectively adopting the four deviation values to compensate the position of the motor rotor, and simultaneously, in the process of active discharge, calculating the estimated values of the position deviation of the motor rotor under different angle compensation by using the RBF neural network trained by using ideal training data, wherein the estimated values are respectively delta E1, delta E2, delta E3 and delta E4. Next, performing condition judgment by using four deviation estimated values calculated by the RBF neural network, if the true deviation value of the motor rotor position is a negative value, determining that a condition Δ E4 < Δ E3 is true, and meanwhile, determining that Δ E1 > Δ E3, Δ E2 > Δ E3, Δ E1 > Δ E4, and Δ E2 > Δ E4 are defined as first conditions, where the first conditions correspond to condition 1 in fig. 4; if the real deviation value of the position of the motor rotor is a positive value, determining that the condition is satisfied when the Δ E2 is less than Δ E1, and meanwhile, determining that the condition is Δ E3 is greater than Δ E1, Δ E3 is greater than Δ E2, Δ E4 is greater than Δ E1, and Δ E4 is greater than Δ E2, wherein the determination condition is defined as a second condition, and the second condition corresponds to condition 2 in fig. 4; when neither the first condition nor the second condition is satisfied (neither condition 1 nor condition 2 described with reference to condition 3 in fig. 4), the first rotor position deviation estimated value Δ E is defined as an invalid value.
Specifically, the step of performing rotor position deviation compensation control according to the symbol determination result includes:
if the actual sign of the first rotor position deviation estimated value delta E is judged to be a negative value, compensating the rotor position deviation according to-delta E;
if the sign of the first rotor position deviation estimated value delta E is judged to be a positive value, compensating the rotor position deviation according to the delta E;
and if the first rotor position deviation estimated value delta E is judged to be an invalid value, the rotor position deviation is not compensated.
In this embodiment, the judgment is performed according to the satisfaction condition of the estimated value of the position deviation of the motor rotor under different angle compensations, and the position compensation control is performed, wherein when a first condition (corresponding to condition 1 in fig. 4) is satisfied, it is judged that the zero point deviation of the position of the motor rotor at this time is- Δ E, at this time, the rotor position is compensated according to the deviation value, and the drive system control is performed on the basis; when a second condition (corresponding to condition 2 in fig. 4) is satisfied, the zero point deviation of the rotor position of the motor at the moment is judged to be Δ E, the rotor position is compensated according to the deviation value at the moment, and the driving system is controlled on the basis; if neither of the first condition and the second condition is satisfied (neither of the condition 1 and the condition 2 described with reference to the condition 3 in fig. 4), the first estimated rotor position deviation Δ E estimated by the RBF neural network is considered to be invalid, and in this case, the motor rotor position deviation is not compensated.
Through the scheme, the small angle deviation of the position of the motor rotor is accurately estimated on the premise of not damaging the driving feeling of the personnel on the vehicle, and the motor position is compensated by utilizing the estimated value in a reasonable mode on the basis, so that the influence of the small angle position deviation of the motor rotor on the running smoothness of the vehicle is eliminated, and the problems that the driving feeling of the personnel on the vehicle is seriously influenced due to the phenomena of shaking, unsmooth power output and the like of the vehicle in the actual running process after the small angle deviation occurs at the zero position of the rotor are solved.
Based on the method, the embodiment of the invention also provides a device for realizing the method.
Referring to fig. 5, a schematic structural diagram of a rotor position deviation compensation control device of a permanent magnet synchronous motor according to an embodiment of the present invention is shown, and a rotor position deviation compensation control device 200 of a permanent magnet synchronous motor according to the present invention includes:
a first obtaining module 210, configured to obtain longitudinal vibration information of a vehicle and first state information of the vehicle;
a first calculating module 220 for calculating a first longitudinal vibration parameter Q of the vehicle according to the longitudinal vibration information of the vehicle1；
A second calculation module 230 for calculating a first longitudinal vibration parameter Q of said vehicle1Obtaining a first rotor position deviation estimated value delta E through the RBF radial basis function neural network;
and the first processing module 240 is configured to perform rotor position deviation compensation control according to the first rotor position deviation estimated value Δ E.
In a preferred embodiment of the present invention, the first obtaining module 210 may include:
the first acquisition unit is used for acquiring longitudinal vibration information of the vehicle through the acceleration sensor in the active discharging process of the driving system in the static state of the vehicle.
The second acquisition unit is used for acquiring first state information of the vehicle before the driving system actively discharges in a static state of the vehicle; the first state information of the vehicle includes: first DC bus voltage V of vehicle1First driving wheel average tire pressure P of vehicle1。
In a preferred embodiment of the present invention, the first calculating module 220 may include:
and the first calculation submodule is used for carrying out second-order low-pass filtering processing on the longitudinal vibration information of the vehicle to obtain a first filtering signal.
Second meterAn operator module for calculating a first longitudinal vibration parameter Q of the vehicle from said first filtered signal1。
Preferably, the first calculation sub-module may include:
a first calculation unit for passing a formula
Figure BDA0002061198440000151
Calculating a first longitudinal vibration parameter of the vehicle;
wherein Q is1Representing a first longitudinal vibration parameter, T, of the vehiclesIndicating the control period, TendIndicates the time required from the start to the end of the active discharge, Acc(n) denotes the first filtered signal.
In a preferred embodiment of the present invention, the second calculation module 230 may include:
a third calculation submodule for calculating a first longitudinal vibration parameter Q of the vehicle1And the first state information of the vehicle is used as an input value of the RBF neural network, and a first rotor position deviation estimated value delta E output by the RBF radial basis function neural network is obtained.
Wherein the apparatus further comprises:
the second acquisition module is used for executing the active discharge experiment for multiple times to acquire multiple groups of ideal training data; wherein each set of the ideal training data comprises: the method comprises the steps of presetting a motor rotor position deviation value, vehicle state information and vehicle longitudinal vibration parameters;
and the second processing module is used for training the RBF neural network according to the plurality of groups of ideal training data.
Preferably, the second obtaining module may include:
the third acquisition unit is used for manually presetting a rotor position deviation value of the motor;
the fourth acquisition unit is used for developing an active discharge experiment under different vehicle state information conditions in a vehicle static state to acquire a longitudinal vibration information experiment value of the vehicle;
and the fifth acquisition unit is used for calculating the longitudinal vibration parameters of the vehicle according to the longitudinal vibration information experimental values of the vehicle.
In a preferred embodiment of the present invention, the first processing module 240 may include:
the first processing submodule is used for judging the actual symbol of the first rotor position deviation estimated value delta E and obtaining a symbol judgment result; wherein the symbol judgment result comprises: the sign of the first rotor position deviation estimated value delta E is a negative value, the sign of the first rotor position deviation estimated value delta E is a positive value, and the first rotor position deviation estimated value delta E is an invalid value;
and the second processing submodule is used for carrying out rotor position deviation compensation control according to the symbol judgment result.
Preferably, the first processing sub-module includes:
a first processing unit for decomposing said first rotor position deviation estimate Δ Ε into four deviation values, said four deviation values comprising: a Δ E, -a Δ E, and- Δ E;
wherein a is more than 0 and less than 1;
a second processing unit for compensating the rotor position deviation according to the deviation value a delta E and calculating a compensated position deviation value delta E through the RBF neural network1；
A third processing unit for compensating the rotor position deviation according to the deviation value delta E and calculating a compensated position deviation two value delta E through the RBF neural network2；
A fourth processing unit for compensating the rotor position deviation according to the deviation value-a delta E and calculating a three-value delta E of the compensated position deviation through the RBF neural network3；
A fifth processing unit for compensating the rotor position deviation according to the deviation value-Delta E and calculating a four-value Delta E of the compensated position deviation through the RBF neural network4；
A sixth processing unit for processing if the Δ E1、ΔE2、ΔE3、ΔE4If the first condition is met, judging the sign of the first rotor position deviation estimated value delta E to be a negative value; wherein the first conditionComprises the following steps:
ΔE4＜ΔE3and Δ E1＞ΔE3，ΔE2＞ΔE3，ΔE1＞ΔE4，ΔE2＞ΔE4；
A seventh processing unit for if said Δ E1、ΔE2、ΔE3、ΔE4If the first condition is met, judging the sign of the first rotor position deviation estimated value delta E to be a positive value; wherein the second condition is:
ΔE2＜ΔE1and Δ E3＞ΔE1，ΔE3＞ΔE2，ΔE4＞ΔE1，ΔE4＞ΔE2；
An eighth processing unit for if said Δ E1、ΔE2、ΔE3、ΔE4If the first condition is not met and the second condition is not met, the estimated value delta E of the position deviation of the first rotor is judged to be an invalid value.
Preferably, the second processing sub-module includes:
a ninth processing unit, configured to compensate the rotor position deviation according to- Δ E if an actual sign of the first rotor position deviation estimation value Δ E is determined as a negative value;
a tenth processing unit, configured to compensate for the rotor position deviation according to Δ E if the sign of the first rotor position deviation estimated value Δ E is determined to be a positive value;
and the eleventh processing unit is used for not compensating the rotor position deviation if the first rotor position deviation estimated value delta E is judged to be an invalid value.
The device for controlling the position deviation compensation of the permanent magnet synchronous motor rotor provided by the device embodiment and the method for controlling the position deviation compensation of the permanent magnet synchronous motor rotor provided by the method embodiment belong to the same conception, and the specific implementation process is detailed in the method embodiment.
In order to achieve the above technical effect, an embodiment of the present invention further provides an automobile, where the automobile includes a processor, a memory, and a computer program stored in the memory and capable of running on the processor, and when the processor executes the computer program, the steps of the method for compensating for a position deviation of a rotor of a permanent magnet synchronous motor are implemented.
Furthermore, an embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program implements the steps of the method for compensating for the rotor position deviation of the permanent magnet synchronous motor.
The invention provides a position deviation compensation method of a permanent magnet synchronous motor rotor, which comprises the following two aspects of content, firstly, detecting small-angle deviation of the position of the permanent magnet synchronous motor rotor to obtain an estimated value of the deviation; on the basis, the deviation value is finally determined in a reasonable mode, and the compensation control is carried out on the rotor position by using the value. The invention relates to small angle deviation detection of a permanent magnet synchronous motor rotor position of a pure electric vehicle, which utilizes the active discharge process of a driving system under a vehicle static state before the vehicle is powered off, obtains longitudinal vibration information of the vehicle through a vehicle-mounted acceleration sensor, creatively introduces an RBF neural network on the basis, and calculates an estimated value of the small angle deviation of the motor rotor position by utilizing the obtained longitudinal vibration information of the vehicle and combining the vehicle state; considering that the error of the motor rotor position is estimated by using the neural network, the precision of the error depends on whether the data of the RBF neural network trained in the early stage is real, effective and reliable, therefore, the invention also provides an ideal training data acquisition method aiming at the neural network, and the data obtained by the method is used for training the neural network, so that the calculation precision of the neural network can be ensured. After the estimated value of the motor position deviation is obtained, the invention provides a compensation control method, which comprises the steps of firstly verifying a compensation angle by utilizing an active discharging process of a vehicle lower electric front driving system, judging whether the motor rotor position angle compensation is correct and effective by observing the longitudinal vibration condition of a vehicle, and finally determining a compensation value of a rotor position, wherein the compensation value is used for final rotor position deviation compensation and subsequent driving system control. The invention realizes the detection, verification and compensation of the small-angle deviation of the position of the motor rotor by utilizing the static state of the vehicle during active discharge, thereby not causing interference to the normal running of the vehicle and ensuring the riding comfort of personnel on the vehicle to a certain extent. In addition, the method provided by the invention has clear thought and convenient realization, and does not involve the change of the hardware of the driving system, thereby having wide popularization value.
For simplicity of explanation, the foregoing method embodiments are described as a series of acts or combinations, but it should be understood by those skilled in the art that the present invention is not limited by the order of acts or acts described, as some steps may occur in other orders or concurrently with other steps in accordance with the invention. Further, those skilled in the art will appreciate that the embodiments described in the specification are presently preferred and that no particular act is required to implement the invention.
It is noted that, in the embodiments of the present invention, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a U disk, a removable hard disk, a ROM, a RAM, a magnetic disk, or an optical disk.
While the preferred embodiments of the present invention have been described, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention as defined in the following claims.

Claims (12)

1. A method for compensating position deviation of a rotor of a permanent magnet synchronous motor is characterized by comprising the following steps:
acquiring longitudinal vibration information of a vehicle and first state information of the vehicle, wherein the first state information comprises: first DC bus voltage V of vehicle1First driving wheel average tire pressure P of vehicle1；
Calculating a first longitudinal vibration parameter Q of the vehicle according to the longitudinal vibration information of the vehicle1(ii) a Wherein the first longitudinal vibration parameter Q1Characterizing the longitudinal shaking degree of a vehicle caused by the zero deviation of a motor rotor in the active discharging process;
according to a first longitudinal vibration parameter Q of the vehicle1Obtaining a first rotor position deviation estimated value delta E through the RBF radial basis function neural network;
according to the first rotor position deviation estimated value delta E, rotor position deviation compensation control is carried out;
wherein, according to the first estimated rotor position deviation Δ E, the step of performing rotor position deviation compensation control includes:
judging the actual sign of the first rotor position deviation estimated value delta E and obtaining a sign judgment result;
wherein the symbol judgment result comprises: the sign of the first rotor position deviation estimated value delta E is a negative value, the sign of the first rotor position deviation estimated value delta E is a positive value, and the first rotor position deviation estimated value delta E is an invalid value;
if the actual sign of the first rotor position deviation estimated value delta E is judged to be a negative value, compensating the rotor position deviation according to-delta E;
if the sign of the first rotor position deviation estimated value delta E is judged to be a positive value, compensating the rotor position deviation according to the delta E;
and if the first rotor position deviation estimated value delta E is judged to be an invalid value, the rotor position deviation is not compensated.
2. The method of compensating for the positional deviation of the rotor of the permanent magnet synchronous motor according to claim 1, wherein the step of obtaining longitudinal vibration information of the vehicle includes:
in the static state of the vehicle, in the active discharging process of a driving system, longitudinal vibration information of the vehicle is obtained through an acceleration sensor, wherein the active discharging is realized by controlling the dq axis current of a permanent magnet synchronous motor, and on the premise of ensuring that the driving motor does not output torque, charges stored in the driving system and a vehicle flow bus are consumed in a three-phase winding of the motor in a heat mode.
3. The method of claim 1, wherein the step of obtaining the first state information of the vehicle comprises:
the method comprises the steps that in a static state of a vehicle, first state information of the vehicle is obtained before a driving system actively discharges;
the first state information of the vehicle includes: first DC bus voltage V of vehicle1First driving wheel average tire pressure P of vehicle1。
4. The method of compensating for rotor position deviation of a PMSM according to claim 1, wherein the vehicle is driven by a motorLongitudinal vibration information of the vehicle, calculating a first longitudinal vibration parameter Q of the vehicle1The method comprises the following steps:
carrying out second-order low-pass filtering processing on the longitudinal vibration information of the vehicle to obtain a first filtering signal;
calculating a first longitudinal vibration parameter Q of the vehicle according to the first filtering signal1。
5. The method of claim 4, wherein the step of calculating a first longitudinal vibration parameter of the vehicle based on the first filtered signal comprises:
by the formula
Figure FDA0003407676150000021
Calculating a first longitudinal vibration parameter of the vehicle;
wherein Q is1Representing a first longitudinal vibration parameter, T, of the vehiclesIndicating the control period, TendIndicates the time required from the start to the end of the active discharge, Acc(n) denotes the first filtered signal.
6. Method for compensating for the deviation of the rotor position of a permanent magnet synchronous machine according to claim 1, characterized in that it is based on a first longitudinal vibration parameter Q of the vehicle1And first state information of the vehicle, obtaining a first rotor position deviation estimated value delta E through the RBF radial basis function neural network, comprising:
calculating a first longitudinal vibration parameter Q of the vehicle1And the first state information of the vehicle is used as an input value of the RBF neural network, and a first rotor position deviation estimated value delta E output by the RBF radial basis function neural network is obtained.
7. The method of claim 1, wherein the step of obtaining the first estimated rotor position deviation Δ E via the RBF radial basis function neural network is preceded by the step of:
executing active discharge experiments for multiple times to obtain multiple groups of ideal training data;
wherein each set of the ideal training data comprises: the method comprises the steps of presetting a motor rotor position deviation value, vehicle state information and vehicle longitudinal vibration parameters;
and training the RBF neural network according to the plurality of groups of ideal training data.
8. The method of claim 7, wherein the step of performing the active discharge test comprises:
manually presetting a rotor position deviation value of a motor;
under the static state of the vehicle, developing an active discharge experiment under different vehicle state information conditions to obtain a longitudinal vibration information experiment value of the vehicle;
and calculating the longitudinal vibration parameters of the vehicle according to the longitudinal vibration information experiment value of the vehicle.
9. The method of claim 1, wherein the step of determining the sign of the first estimated rotor position deviation Δ E comprises:
decomposing said first rotor position deviation estimate Δ E into four deviation values, said four deviation values comprising: a Δ E, -a Δ E, and- Δ E;
wherein 0< a < 1;
compensating the rotor position deviation according to the deviation value a delta E, and calculating a compensated position deviation value delta E through an RBF neural network1；
Compensating the rotor position deviation according to the deviation value delta E, and calculating a compensated position deviation binary value delta E through an RBF neural network2；
Compensating the rotor position deviation according to the deviation value-a delta E, and calculating three values delta E of the compensated position deviation through an RBF neural network3；
Compensating the rotor position deviation according to the deviation value-delta E and passing through an RBF neural networkCalculating the four values of the position deviation delta E after compensation4；
If said Δ E1、ΔE2、ΔE3、ΔE4If the first condition is met, judging the sign of the first rotor position deviation estimated value delta E to be a negative value; wherein the first condition is:
ΔE4<ΔE3and Δ E1>ΔE3，ΔE2>ΔE3，ΔE1>ΔE4，ΔE2>ΔE4；
If said Δ E1、ΔE2、ΔE3、ΔE4If the first condition is met, judging the sign of the first rotor position deviation estimated value delta E to be a positive value; wherein the second condition is:
ΔE2<ΔE1and Δ E3>ΔE1，ΔE3>ΔE2，ΔE4>ΔE1，ΔE4>ΔE2；
If said Δ E1、ΔE2、ΔE3、ΔE4If the first condition is not met and the second condition is not met, the estimated value delta E of the position deviation of the first rotor is judged to be an invalid value.
10. The utility model provides a PMSM rotor position deviation compensation controlling means which characterized in that includes:
the device comprises an acquisition module, a processing module and a display module, wherein the acquisition module is used for acquiring longitudinal vibration information of a vehicle and first state information of the vehicle, and the first state information comprises: first DC bus voltage V of vehicle1First driving wheel average tire pressure P of vehicle1；
A first calculation module for calculating a first longitudinal vibration parameter Q of the vehicle according to the longitudinal vibration information of the vehicle1(ii) a Wherein the first longitudinal vibration parameter Q1Characterizing the longitudinal shaking degree of a vehicle caused by the zero deviation of a motor rotor in the active discharging process;
a second calculation module for calculating a second calculation value based on the vehicleFirst longitudinal vibration parameter Q1Obtaining a first rotor position deviation estimated value delta E through the RBF radial basis function neural network;
the processing module is used for carrying out rotor position deviation compensation control according to the first rotor position deviation estimated value delta E;
wherein the processing module is specifically configured to:
judging the actual sign of the first rotor position deviation estimated value delta E and obtaining a sign judgment result;
wherein the symbol judgment result comprises: the sign of the first rotor position deviation estimated value delta E is a negative value, the sign of the first rotor position deviation estimated value delta E is a positive value, and the first rotor position deviation estimated value delta E is an invalid value;
if the actual sign of the first rotor position deviation estimated value delta E is judged to be a negative value, compensating the rotor position deviation according to-delta E;
if the sign of the first rotor position deviation estimated value delta E is judged to be a positive value, compensating the rotor position deviation according to the delta E;
and if the first rotor position deviation estimated value delta E is judged to be an invalid value, the rotor position deviation is not compensated.
11. A motor vehicle, characterized in that it comprises a processor, a memory, a computer program stored on said memory and executable on said processor, said processor implementing the steps of the method for compensating for a rotor position deviation of a permanent magnet synchronous motor according to any one of claims 1 to 9 when executing said computer program.
12. A computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, which computer program, when being executed by a processor, carries out the steps of the method for permanent magnet synchronous motor rotor position deviation compensation according to any one of claims 1 to 9.
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