CN112152532A - Method, system and device for online estimation of joint motor parameters - Google Patents
Method, system and device for online estimation of joint motor parameters Download PDFInfo
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Abstract
The application relates to a method, a system and a device for online estimation of joint motor parameters, which comprises the steps of obtaining joint parameters for describing a motor, wherein the types of the joint parameters comprise two types, one type is an A-type parameter which is less influenced by temperature but is greatly influenced by the saturation degree of an air gap of the motor; one is a B-type parameter which is greatly influenced by temperature but is less influenced by the saturation degree of the air gap of the motor; estimating the A-type parameters, and if the estimated A-type parameters meet preset conditions, acquiring the estimated A-type parameters; and adjusting the B-type parameters according to the estimated A-type parameters to obtain the adjusted B-type parameters. The method and the device have the effect of being capable of improving the estimation accuracy of the joint motor parameters.
Description
Technical Field
The present application relates to the field of joint motors, and in particular, to a method, a system, and a device for online estimation of joint motor parameters.
Background
The cooperative robot is a new type of robot that has appeared in the field of robots in recent years. Compared with the traditional industrial robot, the cooperative robot is small in size, light in weight, highly flexible, convenient to move, more intelligent and safer, and due to the characteristics, the cooperative robot can complete work with workers in a close-range interaction and cooperation mode.
In the field of joint motors for cooperative robots, the control of a motor body is the lowest measure, and the quality of the control performance of the joint motor directly determines the upper limit level of the action execution effect of the cooperative robot. If the control performance of the motor is excellent, the motor can well follow a given target moment on the joint layer.
High performance motor control algorithms often require accurate joint motor parameters such as model predictive control, adaptive PID, and the like. Therefore, in order to improve the control performance of the joint motor, the estimation accuracy of the motor parameter needs to be improved.
However, parameters of the joint motor often change with factors such as the temperature of the motor body and the saturation degree of the air gap magnetic field, and accurate estimation of the motor parameters is difficult.
Disclosure of Invention
The method for the on-line estimation of the joint motor parameters has the advantage that the accuracy of the estimation of the joint motor parameters can be improved.
The above object of the present application is achieved by the following technical solutions: a method for online estimation of joint motor parameters comprises the following steps:
acquiring joint parameters for describing a motor, wherein the types of the joint parameters comprise two types, one type is a type A parameter which is less influenced by temperature but more influenced by the saturation degree of an air gap of the motor; one is a B-type parameter which is greatly influenced by temperature but is less influenced by the saturation degree of the air gap of the motor;
estimating the A-type parameters, and if the estimated A-type parameters meet preset conditions, acquiring the estimated A-type parameters;
and adjusting the B-type parameters according to the estimated A-type parameters to obtain the adjusted B-type parameters.
By adopting the technical scheme, joint parameters for describing the motor are determined and obtained firstly, wherein the joint parameters comprise A-type parameters and B-type parameters, so that offline measurement values can be conveniently made, the A-type parameters are estimated, and if preset conditions are met, the estimated A-type parameters are obtained and can be directly used; estimating B-class parameters with different leading influence factors by using different estimation methods, and adjusting the B-class parameters according to the estimated A-class parameters to obtain the adjusted B-class parameters; the method can estimate the motor parameters with different leading influence factors by different methods so as to improve the estimation accuracy of the joint motor parameters.
The present invention in a preferred example may be further configured to: the obtaining of the joint parameters for describing the motor comprises establishing a mathematical model under a dq axis coordinate system and extracting required joint parameters, wherein the joint parameters comprise A-type parameters and B-type parameters.
By adopting the technical scheme, a mathematical model of the joint motor on the dq axis is established, and parameters to be estimated of the motor, namely A-type parameters and B-type parameters, are extracted from the mathematical model.
The present invention in a preferred example may be further configured to: the estimating of the A-type parameters comprises converting the mathematical model into a relational expression A, obtaining the A-type parameters, and obtaining the estimated A-type parameters through recursion.
By adopting the technical scheme, the mathematical model is converted into the relational expression A to estimate a plurality of parameters, wherein the parameters comprise A-type parameters and B-type parameters, and the A-type parameters can be directly obtained by a recursion method if the air gap saturation degree of the joint motor for the cooperative robot is not changed greatly, so that the stability of the A-type parameters is ensured.
The present invention in a preferred example may be further configured to: judging whether the estimated class A parameters meet preset conditions comprises the following steps: and if the difference value between the estimated A-type parameter and the offline measured value is less than a preset value, the preset condition is met.
By adopting the technical scheme, the A-type parameters are monitored in real time, if the difference value between the A-type parameters and the off-line measurement value is smaller than the preset value, the estimation result is judged to be accurate, the preset condition is met, and the estimated A-type parameters can be directly used.
The present invention in a preferred example may be further configured to: adjusting the class B parameter according to the estimated class A parameter, wherein the obtaining of the adjusted class B parameter comprises: and bringing the estimated A-type parameters into the mathematical model, adjusting adjustable parameters in the mathematical model to make the mathematical model converge to a real model, acquiring the estimated adjustable parameters, and acquiring the adjusted B-type parameters according to the relationship between the estimated adjustable parameters and the B-type parameters.
By adopting the technical scheme, when the estimated A-type parameters meet the preset conditions, the estimated A-type parameters can be brought into the mathematical model, the adjustable parameters in the mathematical model are adjusted, so that the output of the adjustable model is consistent with that of the real model, the adjustable model is consistent with the real model at the moment, the estimated adjustable parameters can be finally obtained, and the adjusted B-type parameters can be conveniently calculated according to the relation between the adjustable parameters and the B-type parameters.
The present invention in a preferred example may be further configured to: and when the difference value between the estimated A-type parameters and the offline measured value is larger than a preset value, cutting out the A-type parameter estimation method, and using the latest reasonable A-type parameters as input results.
By adopting the technical scheme, the estimated A-type parameters obtained by the A-type parameter estimation method are monitored in real time and compared with the offline measured values, if the difference value between the A-type parameters and the offline measured values is larger than a preset value, the A-type parameters are judged to be dispersed, the A-type parameter estimation method needs to be switched out in time, and the recently estimated reasonable value is used as the input of the adjustable model, so that the stability of the B-type parameters is ensured.
The present invention in a preferred example may be further configured to: the method further comprises the following steps: after a period of time, the class A parameter estimation method is switched in again, and the estimation result is monitored.
By adopting the technical scheme, after a period of time, the class-A parameter estimation method is tried to be switched in again, if convergence is found, the switching-in is kept, and once the convergence is found, the switching-out is needed to ensure the stability of the class-B parameter.
The present invention in a preferred example may be further configured to: the method further comprises the following steps: and if the difference value between the continuously estimated A-type parameters and the offline measured value is larger than a preset value, judging that the motor does not normally operate any more, and sending alarm information in time.
By adopting the technical scheme, if the method for estimating the A-type parameters fails after multiple continuous cut-ins, the motor is possibly out of the normal operation range, and alarm information needs to be sent out in time to prompt a worker to maintain the motor.
The second purpose of the application is to provide a system for on-line estimation of joint motor parameters, which has the characteristic of improving the estimation accuracy of the joint motor parameters.
The second purpose of the present application is achieved by the following technical scheme: a system for online estimation of joint motor parameters, the system comprising:
the device comprises an acquisition device and a control device, wherein the acquisition device is used for acquiring joint parameters for describing the motor, wherein the types of the joint parameters comprise two types, one type is a type A parameter which is less influenced by temperature but is more influenced by the saturation degree of an air gap of the motor; one is a B-type parameter which is greatly influenced by temperature but is less influenced by the saturation degree of the air gap of the motor;
the first estimation device is used for estimating the A-type parameters, and if the estimated A-type parameters meet preset conditions, the estimated A-type parameters are obtained;
the second estimation device is used for adjusting the B-type parameters according to the estimated A-type parameters to obtain the adjusted B-type parameters;
the monitoring device is used for switching out the A-type parameter estimation method if the difference value between the estimated A-type parameter and the offline measured value is larger than a preset value, using the latest reasonable A-type parameter as an input result, switching in the A-type parameter estimation method again after a period of time, and monitoring the estimation result;
and if the difference value between the continuously estimated A-type parameters and the offline measured value is larger than a preset value, the warning device judges that the motor does not normally operate any more, and needs to send out warning information in time.
By adopting the technical scheme, joint parameters for describing the motor are determined and obtained firstly, wherein the joint parameters comprise A-type parameters and B-type parameters, so that offline measurement values can be conveniently made, the A-type parameters are estimated, and if preset conditions are met, the estimated A-type parameters are obtained and can be directly used; estimating B-class parameters with different leading influence factors by using different estimation methods, and adjusting the B-class parameters according to the estimated A-class parameters to obtain the adjusted B-class parameters; the method can estimate the motor parameters with different leading influence factors by different methods so as to improve the estimation accuracy of the joint motor parameters.
The third purpose of the application is to provide a device for online estimation of joint motor parameters, which has the characteristic of improving the estimation accuracy of the joint motor parameters.
The third purpose of the present application is achieved by the following technical solutions: an apparatus for online estimation of joint motor parameters, the apparatus comprising:
the motor control device comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for acquiring joint parameters for describing a motor, the types of the joint parameters comprise two types, one type is an A-type parameter which is less influenced by temperature but is more influenced by the saturation degree of an air gap of the motor; one is a B-type parameter which is greatly influenced by temperature but is less influenced by the saturation degree of the air gap of the motor;
the first estimation module is used for estimating the A-type parameters, and if the estimated A-type parameters meet preset conditions, the estimated A-type parameters are obtained;
the second estimation module is used for adjusting the B-type parameters according to the estimated A-type parameters to obtain the adjusted B-type parameters;
the monitoring module is used for switching out the A-type parameter estimation method if the difference value between the estimated A-type parameter and the offline measured value is larger than a preset value, using the latest reasonable A-type parameter as an input result, switching in the A-type parameter estimation method again after a period of time, and monitoring the estimation result;
and the warning module is used for judging that the motor does not normally operate any more and sending out alarm information in time if the difference value between the continuously estimated A-type parameters and the offline measured value is larger than a preset value.
By adopting the technical scheme, joint parameters for describing the motor are determined and obtained firstly, wherein the joint parameters comprise A-type parameters and B-type parameters, so that offline measurement values can be conveniently made, the A-type parameters are estimated, and if preset conditions are met, the estimated A-type parameters are obtained and can be directly used; estimating B-class parameters with different leading influence factors by using different estimation methods, and adjusting the B-class parameters according to the estimated A-class parameters to obtain the adjusted B-class parameters; the method can estimate the motor parameters with different leading influence factors by different methods so as to improve the estimation accuracy of the joint motor parameters.
In summary, the present application includes at least one of the following beneficial technical effects:
1. in the scheme, motor parameters with different leading influence factors are estimated by different methods, so that the estimation accuracy of joint motor parameters is improved;
2. in the scheme, the cooperative robot can directly use the A-type parameters to obtain the A-type parameters by a recursion method if the air gap saturation degree of the joint motor for the cooperative robot is not changed greatly, so that the stability of the A-type parameters is ensured;
3. in the scheme, the estimated A-type parameters are monitored in real time, when the A-type parameters are diverged, an A-type parameter estimation method needs to be switched out in time, and a recently estimated reasonable value is used as the input of an adjustable model, so that the stability of the B-type parameters is ensured.
Drawings
Fig. 1 is a block diagram of a flow chart in a first embodiment of the present application.
Fig. 2 is a system flow diagram in a third embodiment of the present application.
Fig. 3 is a block diagram of the fourth embodiment of the present application.
Detailed Description
The present application is described in further detail below with reference to figures 1-3.
The present embodiment is only for explaining the present invention, and it is not limited to the present invention, and those skilled in the art can make modifications of the present embodiment without inventive contribution as needed after reading the present specification, but all of them are protected by patent law within the scope of the claims of the present invention.
The first embodiment is as follows:
the embodiment of the application discloses a method for online estimation of joint motor parameters. Referring to fig. 1, the method includes:
101. acquiring joint parameters for describing a motor;
the joint parameters include two types, one type is a type A parameter which is less influenced by temperature but more influenced by the saturation degree of the motor air gap; one is a B-type parameter which is greatly influenced by temperature but is less influenced by the saturation degree of the air gap of the motor;
acquiring joint parameters for describing the motor comprises:
and establishing a mathematical model under a dq axis coordinate system, and extracting required joint parameters, wherein the joint parameters comprise A-type parameters and B-type parameters.
102. Estimating the A-type parameters, and if the estimated A-type parameters meet preset conditions, acquiring the estimated A-type parameters;
estimating the class a parameters includes:
and converting the mathematical model into a relational expression A, obtaining A-type parameters, and obtaining the estimated A-type parameters through recursion.
Judging whether the estimated A-type parameters meet preset conditions comprises the following steps:
and if the difference value between the estimated A-type parameter and the offline measured value is less than the preset value, the preset condition is met.
103. Adjusting the B-type parameters according to the estimated A-type parameters to obtain the adjusted B-type parameters;
specifically, the method comprises the following steps:
and bringing the estimated A-type parameters into the mathematical model, adjusting adjustable parameters in the mathematical model to make the mathematical model converge to a real model, acquiring the estimated adjustable parameters, and acquiring the adjusted B-type parameters according to the relationship between the estimated adjustable parameters and the B-type parameters.
104. When the difference value between the estimated A-type parameters and the offline measured value is larger than a preset value, cutting out the A-type parameter estimation method, and using the latest reasonable A-type parameters as input results;
105. after a period of time, switching in the A-type parameter estimation method again, and monitoring the estimation result;
106. if the difference value between the continuously estimated A-type parameters and the offline measured value is larger than the preset value, the motor is judged not to be in the normal operation range any more, and alarm information needs to be sent out in time.
Example two:
the embodiment of the application discloses a method for online estimation of joint motor parameters. Referring to fig. 1, the method specifically includes:
201. acquiring joint parameters for describing a motor;
the joint parameters include two types, one type is a type A parameter which is less influenced by temperature but more influenced by the saturation degree of the motor air gap; one is a B-type parameter which is greatly influenced by temperature but is less influenced by the saturation degree of the air gap of the motor;
acquiring joint parameters for describing the motor comprises:
and establishing a mathematical model under a dq axis coordinate system, and extracting required joint parameters, wherein the joint parameters comprise A-type parameters and B-type parameters.
The d axis is a straight axis in the motor, the q axis is a quadrature axis, on the central line of the rotor magnetic pole in the synchronous motor, the direction of the straight axis is, on the perpendicular bisector between two adjacent magnetic poles, the direction of the quadrature axis is the basis for learning and analyzing the DC motor and the synchronous motor;
specifically, the dq-axis inductance L of the joint motor is obtained in advanced0And Lq0Phase resistance R0Permanent magnet flux linkage psif0And the like.
In order to enable the motor to be in a normal operation state, an FOC vector control system of the joint motor needs to be built, wherein a current loop and a speed loop of a controller are controlled by conventional PID. The purpose of this step is to simulate the operating conditions of the real system motor and to provide operating information that can be used to estimate the parameters.
The method comprises the steps of collecting three-phase voltages Ua, Ub and Uc of a motor in an operating state, and obtaining Ud and Uq in a dq axis coordinate system rotating together with a rotor after the three-phase voltages are converted by Clark and Park respectively. Due to the discrete characteristic of the SVPWM modulation method, the acquired dq axis voltage presents the characteristic of a square wave with unequal amplitude, so that a Butterworth filtering module is required to be connected to the output voltage, and the acquired dq axis voltage is continuous.
Collecting three-phase voltages Ia, Ib and Ic of the motor in an operating state, and obtaining Id and Iq in a dq axis coordinate system rotating together with the rotor after the three-phase currents are converted by Clark and Park respectively. In order to make the collected current and voltage have the same hysteresis characteristic, a filter which is the same as the voltage filter is also added, so that the voltage and current in the dq axis system can be ensured to be the synchronous collection result.
The rotating speed information directly output by the simulation model is the mechanical rotating speed omega of the motormThe speed requirement in the model is however the motor electrical speed ωeTherefore, the mechanical rotation speed ω needs to be adjustedmConversion into an electrical rotational speed omegaeThe conversion formula is as follows:
ωe＝Pnωm
wherein, PnThe number of pole pairs of the motor is indicated. Likewise, the velocity is also passed through the same filter to ensure that the phase difference obtained from the acquisition is minimal.
Thereby establishing a mathematical model of the joint motor and extracting the required joint parameters. The mathematical model of the joint motor in the dq axis coordinate system is shown as follows:
wherein R is phase resistance, LdAnd LqRespectively, dq-axis inductance,. psifThe permanent magnet flux linkages are all parameters to be estimated.
The parameters to be estimated are divided into two types, one is influenced by temperature with small influence factor but influenced by the saturation degree of the air gap of the motorWith greater class A, i.e. class A parameters, including dq-axis inductance Ld，LqAnd permanent magnet flux linkage psifThe parameters are estimated by a method based on recursive least squares; the other type is B type which is greatly influenced by temperature but is less influenced by the saturation degree of the motor air gap, namely B type parameters are motor phase resistance R, and the parameters are estimated by using a model reference self-adaptive method. The purpose of this step is to estimate parameters with different dominant influencing factors using different methods.
202. Estimating the A-type parameters, and if the estimated A-type parameters meet preset conditions, acquiring the estimated A-type parameters;
estimating the class a parameters includes:
and converting the mathematical model into a relational expression A, obtaining A-type parameters, and obtaining the estimated A-type parameters through recursion.
Judging whether the estimated A-type parameters meet preset conditions comprises the following steps:
and if the difference value between the estimated A-type parameter and the offline measured value is less than the preset value, the preset condition is met.
Specifically, the mathematical model structure is converted into a relation A:
wherein y (n) is a matrix of measurable variables,
as a system matrix, θ (n-1) is a band estimation parameter matrix. Are respectively represented by the following formula:
wherein the content of the first and second substances,
is a system matrix calculated by using the acquired current dq axis current, the electric rotating speed of the motor and other information, wherein iqAnd idThe initial values of (A) can all be taken as 0, and the calculated system matrix
The current value is indicated.
The method can estimate four parameters simultaneously, and the stability of the A-type parameters can be ensured aiming at the characteristic that the air gap saturation degree of the joint motor for the cooperative robot is not changed much, so that the method can be directly used. However, for the class B parameters, because the parameters are greatly influenced by temperature (including ambient temperature and temperature change caused by motor heating), a closed-loop estimation method with better following performance, namely a model reference adaptive method, is required;
substituting the mathematical model established in the steps into the method according to a recursion least square method calculation formula with forgetting factors, selecting the parameters to be estimated as A-type parameters which are not influenced much by temperature, and recurrently estimating the A-type parameters:
specifically, a system error matrix (n) can be obtained by acquiring dq-axis voltage information and calculating system matrix information, and a calculation formula is given by the following formula:
wherein the content of the first and second substances,
the result of the last estimation is shown, and the initial value can be taken as 0;
current gain matrices k (n) and p (n) of the least squares method are calculated, respectively:
p (n-1) in the above formula can select a maximum value as an initial value, such as 1e6, λ is a forgetting factor, and can be 0.999, and the factor can well avoid oversaturation of parameters and prevent the parameters from having static error;
through the matrix results calculated in the steps, the online iterative estimation result based on the least square method with forgetting factors can be calculated:
the calculation formula of recursion is finally obtained as follows:
namely, the estimated A-type parameters and the dq-axis inductance L of the joint motor are measured in advance by using external measuring equipment such as a meter and the liked0And Lq0Permanent magnet flux linkage psif0Comparing the parameters, and respectively comparing the estimated A-type parameters with the offline measured values one by oneCorrespondingly, if the corresponding difference is less than 40%, the preset condition is met, and the A-type parameters can be directly used.
203. Adjusting the B-type parameters according to the estimated A-type parameters to obtain the adjusted B-type parameters;
and bringing the estimated A-type parameters into the mathematical model, adjusting adjustable parameters in the mathematical model to make the mathematical model converge to a real model, acquiring the estimated adjustable parameters, and acquiring the adjusted B-type parameters according to the relationship between the estimated adjustable parameters and the B-type parameters.
Specifically, the same adjustable mathematical model as that in step 2011 is established, the B-type parameter with a larger temperature change is selected as the parameter, and the a-type parameter in the model is estimated by using RLS, that is, an a-type parameter estimation method. The class B parameter can be set to an initial value, and the initial value can be derived from an offline value measured in advance and used for comparing with a real model measurement result in real time. From the motor model, an adjustable mathematical model of the construction can be obtained as follows:
in the above formula, the first and second carbon atoms are,
for adjustable parameters, i.e. phase resistance R and d-axis inductance LdAnd the other estimated values are the results of the real-time estimation in step 202.
Firstly, discretizing the adjustable parameter model by using a first-order Euler method, wherein the discretization result is as follows:
wherein, T is the discrete time,
and
the initial value of (a) is taken as 0. Substituting the least square method estimation result with forgetting factor into the formula to calculate the output estimation current value of the current adjustable model
And
calculating adjustable parameters in the model reference adaptive rate, wherein the calculation formula is as follows:
edand eqThe difference between the collected current value and the estimated value can be calculated by the following formula:
by adjusting an adjustable parameter K in the adaptation ratepAnd KiSo that the output of the adjustable model is consistent with that of the real model, and finally the estimated adjustable parameters can be obtained
The adjusted B-type parameters are obtained through the relationship between the estimated adjustable parameters and the B-type parameters, and the motor phase resistance estimated value parameters, namely the B-type parameters, can be conveniently calculated as follows:
204. when the difference value between the estimated A-type parameters and the offline measured value is larger than a preset value, cutting out the A-type parameter estimation method, and using the latest reasonable A-type parameters as input results;
specifically, the A-type parameters estimated based on the A-type parameter estimation method are monitored in real time and compared with an offline measurement result, if the difference is larger than 40%, the A-type parameters are considered to be diverged, the RLS method needs to be removed in time, and a recently estimated reasonable value is used as the input of an adjustable model to ensure the stability of the B-type parameters.
205. After a period of time, switching in the A-type parameter estimation method again, and monitoring the estimation result;
specifically, after a period of time, re-cut-in is attempted to the RLS-based estimation method, if convergence is found, cut-in is maintained while real-time monitoring of class a parameters is maintained, and once re-divergence is detected, it is indicated that cut-out is required, and steps 204 and 205 are cycled to always ensure stability of class B parameters.
206. If the difference value between the continuously estimated A-type parameters and the offline measured value is larger than the preset value, the motor is judged not to be in the normal operation range any more, and alarm information needs to be sent out in time
Specifically, if the continuous multiple cut-in fails, that is, the difference between the continuously estimated class a parameter and the offline measured value is greater than 40%, it indicates that the motor may not be in the normal operating range, and an alarm message needs to be sent out in time to prompt an employee to maintain the motor.
The implementation principle of the method for the online estimation of the joint motor parameters in the embodiment of the application is as follows: firstly, determining and acquiring joint parameters for describing a motor, wherein the joint parameters comprise A-type parameters and B-type parameters so as to facilitate offline measurement;
the A-type parameters are slightly influenced by temperature, but are greatly influenced by the air gap saturation degree of the motor, and aiming at the characteristic that the air gap saturation degree of the joint motor for the cooperative robot is not changed greatly, the A-type parameters are estimated by using a calculation formula of a recursion least square method with a forgetting factor, so that the stability of the A-type parameters can be ensured, the forgetting factor can well avoid the supersaturation of the parameters, and the static error of the parameters is prevented;
then, monitoring the estimated A-type parameters in real time, and performing relevant processing when the A-type parameters are too different from the off-line values so as to ensure the continuous stability of the A-type parameters;
the B-type parameters are greatly influenced by temperature, but are slightly influenced by the saturation degree of the air gap of the motor, and because the B-type parameters are greatly influenced by the temperature, a closed-loop estimation method with better following performance is needed, and the parameters are estimated by using a model reference self-adaptive method; establishing an adjustable model, bringing the estimated A-type parameters into the adjustable model, adjusting the adjustable model to make the adjustable model converge to a real model so as to estimate B-type parameters, and monitoring the A-type parameters in real time to ensure the stability of the B-type parameters;
the method can estimate the motor parameters with different leading influence factors by different methods so as to improve the estimation accuracy of the joint motor parameters.
Example three:
the embodiment of the present application discloses a system for online estimation of joint motor parameters, with reference to fig. 2, the system includes:
the acquisition device 301 acquires joint parameters for describing the motor, wherein the types of the joint parameters include two types, one type is a type A parameter which is less influenced by temperature but more influenced by the saturation degree of the air gap of the motor; one is a B-type parameter which is greatly influenced by temperature but is less influenced by the saturation degree of the air gap of the motor;
specifically, a mathematical model under a dq axis coordinate system is established, and required joint parameters are extracted, wherein the joint parameters comprise A-type parameters and B-type parameters;
the first estimation device 302 is used for estimating the class A parameters, and if the estimated class A parameters meet preset conditions, the estimated class A parameters are obtained;
specifically, if the difference between the estimated class a parameter and the offline measured value is smaller than a preset value, a preset condition is met;
specifically, the mathematical model is converted into a relational expression A, a class A parameter is obtained, and the estimated class A parameter is obtained through recursion;
specifically, when the difference between the estimated A-type parameter and the offline measured value is greater than a preset value, a A-type parameter estimation method is switched out, and the latest reasonable A-type parameter is used as an input result;
a second estimating device 303, configured to adjust the class B parameter according to the estimated class a parameter, and obtain an adjusted class B parameter;
specifically, the estimated class a parameters are brought into the mathematical model, adjustable parameters in the mathematical model are adjusted to make the mathematical model converge to a real model, the estimated adjustable parameters are obtained, and adjusted class B parameters are obtained through the relationship between the estimated adjustable parameters and the class B parameters;
the monitoring device 304 switches out the class A parameter estimation method if the difference value between the estimated class A parameter and the offline measured value is larger than a preset value, and switches in the class A parameter estimation method again after a period of time by using the latest reasonable class A parameter as an input result, and simultaneously monitors the estimation result;
if the difference between the continuously estimated class a parameters and the offline measured values is greater than the preset value, the warning device 305 determines that the motor is no longer in the normal operation range, and needs to send out warning information in time.
Example four:
the embodiment of the present application discloses a device for online estimation of joint motor parameters, with reference to fig. 3, the device includes:
the acquiring module 401 acquires joint parameters for describing a motor, wherein the types of the joint parameters include two types, one type is a type a parameter which is less influenced by temperature but is more influenced by the saturation degree of an air gap of the motor; one is a B-type parameter which is greatly influenced by temperature but is less influenced by the saturation degree of the air gap of the motor;
specifically, a mathematical model under a dq axis coordinate system is established, and required joint parameters are extracted, wherein the joint parameters comprise A-type parameters and B-type parameters;
a first estimation module 402, configured to estimate the class a parameter, and if the estimated class a parameter meets a preset condition, obtain the estimated class a parameter;
specifically, if the difference between the estimated class a parameter and the offline measured value is smaller than a preset value, a preset condition is met;
specifically, the mathematical model is converted into a relational expression A, a class A parameter is obtained, and the estimated class A parameter is obtained through recursion;
specifically, when the difference between the estimated A-type parameter and the offline measured value is greater than a preset value, a A-type parameter estimation method is switched out, and the latest reasonable A-type parameter is used as an input result;
a second estimation module 403, configured to adjust the class B parameter according to the estimated class a parameter, and obtain an adjusted class B parameter;
specifically, the estimated class a parameters are brought into the mathematical model, adjustable parameters in the mathematical model are adjusted to make the mathematical model converge to a real model, the estimated adjustable parameters are obtained, and adjusted class B parameters are obtained through the relationship between the estimated adjustable parameters and the class B parameters;
a monitoring module 404, switching out the class a parameter estimation method if the difference between the estimated class a parameter and the offline measurement value is greater than a preset value, and switching in the class a parameter estimation method again after a period of time by using the most recent reasonable class a parameter as an input result, and monitoring the estimation result;
and the warning module 405 determines that the motor is no longer in the normal operation range if the difference between the continuously estimated class a parameters and the offline measured values is greater than a preset value, and needs to send out warning information in time.
It should be noted that: in the above embodiment, when the online joint motor parameter estimation apparatus and system are used to perform the online joint motor parameter estimation method, only the division of the above functional modules is taken as an example, and in practical applications, the above functions may be distributed to different functional modules according to needs, that is, the internal structures of the device and the apparatus are divided into different functional modules, so as to complete all or part of the above described functions. In addition, the embodiments of the method, the system and the device for online estimation of joint motor parameters provided in the above embodiments belong to the same concept, and specific implementation processes thereof are described in detail in the embodiments of the method and are not described herein again.
It will be understood by those skilled in the art that all or part of the steps for implementing the above embodiments may be implemented by hardware, or may be implemented by a program instructing relevant hardware, where the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.
The above description is only exemplary of the present application and should not be taken as limiting the present application, as any modification, equivalent replacement, or improvement made within the spirit and principle of the present application should be included in the protection scope of the present application.
Claims (10)
1. A method for online estimation of joint motor parameters is characterized by comprising the following steps:
acquiring joint parameters for describing a motor, wherein the types of the joint parameters comprise two types, one type is a type A parameter which is less influenced by temperature but more influenced by the saturation degree of an air gap of the motor; one is a B-type parameter which is greatly influenced by temperature but is less influenced by the saturation degree of the air gap of the motor;
estimating the A-type parameters, and if the estimated A-type parameters meet preset conditions, acquiring the estimated A-type parameters;
and adjusting the B-type parameters according to the estimated A-type parameters to obtain the adjusted B-type parameters.
2. The method for on-line estimation of joint motor parameters according to claim 1, wherein the obtaining joint parameters for describing a motor comprises: and establishing a mathematical model under a dq axis coordinate system, and extracting required joint parameters, wherein the joint parameters comprise A-type parameters and B-type parameters.
3. The method for on-line estimation of joint motor parameters according to claim 2, wherein the estimating of class a parameters comprises: and converting the mathematical model into a relational expression A to obtain A-type parameters, and obtaining the estimated A-type parameters through recursion.
4. The method for on-line estimation of joint motor parameters according to claim 2, wherein judging whether the estimated class a parameters satisfy preset conditions comprises: and if the difference value between the estimated A-type parameter and the offline measured value is less than a preset value, the preset condition is met.
5. The method for online estimation of joint motor parameters according to claim 4, wherein the adjusting the class B parameters according to the estimated class A parameters comprises: and bringing the estimated A-type parameters into the mathematical model, adjusting adjustable parameters in the mathematical model to make the mathematical model converge to a real model, acquiring the estimated adjustable parameters, and acquiring the adjusted B-type parameters according to the relationship between the estimated adjustable parameters and the B-type parameters.
6. The method for on-line estimation of joint motor parameters according to claim 4, wherein: and when the difference value between the estimated A-type parameters and the offline measured value is larger than a preset value, cutting out the A-type parameter estimation method, and using the latest reasonable A-type parameters as input results.
7. The method for on-line estimation of joint motor parameters according to claim 6, further comprising: after a period of time, the class A parameter estimation method is switched in again, and the estimation result is monitored.
8. The method for on-line estimation of joint motor parameters according to claim 7, further comprising: and if the difference value between the continuously estimated A-type parameters and the offline measured value is larger than a preset value, judging that the motor does not normally operate any more, and sending alarm information in time.
9. A system for online estimation of joint motor parameters, the system comprising:
the device comprises an acquisition device and a control device, wherein the acquisition device is used for acquiring joint parameters for describing the motor, wherein the types of the joint parameters comprise two types, one type is a type A parameter which is less influenced by temperature but is more influenced by the saturation degree of an air gap of the motor; one is a B-type parameter which is greatly influenced by temperature but is less influenced by the saturation degree of the air gap of the motor;
the first estimation device is used for estimating the A-type parameters, and if the estimated A-type parameters meet preset conditions, the estimated A-type parameters are obtained;
the second estimation device is used for adjusting the B-type parameters according to the estimated A-type parameters to obtain the adjusted B-type parameters;
the monitoring device is used for switching out the A-type parameter estimation method if the difference value between the estimated A-type parameter and the offline measured value is larger than a preset value, using the latest reasonable A-type parameter as an input result, switching in the A-type parameter estimation method again after a period of time, and monitoring the estimation result;
and if the difference value between the continuously estimated A-type parameters and the offline measured value is larger than a preset value, the warning device judges that the motor does not normally operate any more, and needs to send out warning information in time.
10. An apparatus for online estimation of joint motor parameters, the apparatus comprising:
the motor control device comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for acquiring joint parameters for describing a motor, the types of the joint parameters comprise two types, one type is an A-type parameter which is less influenced by temperature but is more influenced by the saturation degree of an air gap of the motor; one is a B-type parameter which is greatly influenced by temperature but is less influenced by the saturation degree of the air gap of the motor;
the first estimation module is used for estimating the A-type parameters, and if the estimated A-type parameters meet preset conditions, the estimated A-type parameters are obtained;
the second estimation module is used for adjusting the B-type parameters according to the estimated A-type parameters to obtain the adjusted B-type parameters;
the monitoring module is used for switching out the A-type parameter estimation method if the difference value between the estimated A-type parameter and the offline measured value is larger than a preset value, using the latest reasonable A-type parameter as an input result, switching in the A-type parameter estimation method again after a period of time, and monitoring the estimation result;
and the warning module is used for judging that the motor does not normally operate any more and sending out alarm information in time if the difference value between the continuously estimated A-type parameters and the offline measured value is larger than a preset value.
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