JP7383370B2 - Motor temperature prediction method and device - Google Patents

Description

The present invention relates to a method and apparatus for predicting motor temperature.

Generally, in the case of a belt conveyor that transports coal at a coal-fired power plant, if it is detected that foreign matter such as metal pieces is mixed in with the coal, the belt conveyor is temporarily stopped and the belt conveyor is stopped. After removing the foreign matter, the belt conveyor is restarted.

Therefore, the electric motor used in the belt conveyor is repeatedly started, operated, stopped, and restarted.

The electric motor generates a large amount of heat, especially when started, and heat accumulates when the electric motor is repeatedly operated, stopped, and restarted. Therefore, it is necessary to provide a certain amount of standby time after stopping the electric motor before restarting the electric motor.

Conventionally, the stop time until the electric motor is restarted is set to the longest time with some margin.

Note that, for example, Patent Document 1 shows the general state of the art related to a device that calculates the stop time of an electric motor.

Japanese Patent Application Publication No. 8-191537

However, if we set the stop time before restarting the motor to the longest expected time, as in the past, there is a risk that the period during which the motor cannot be operated will be longer than necessary, which will hinder overall operation. was desired.

Furthermore, the device disclosed in Patent Document 1 simply uses preset thermal time constants during operation, thermal time constants during stoppage, and allowable number of starts of the motor, so that It has become difficult to respond to the changing ambient temperature and load conditions of the motor.

The present invention was made in view of the above-mentioned conventional problems, and it is possible to reduce the stop time to the necessary minimum depending on the ambient temperature and load condition of the motor, and to grasp the restartable time with high precision. The present invention aims to provide a method and apparatus for predicting motor temperature.

In order to achieve the above object, the motor temperature prediction method of the present invention includes an ambient temperature measuring step of measuring the ambient temperature θ ₀ at the location where the motor is installed;
a motor temperature measurement step of measuring motor temperature θ;
A load factor calculation step of calculating a load factor δ based on the ratio I/I _{R of the current value I to the rated current value I R or} the ratio P/ _{PR of the power value P to the rated power value P R during} operation of the electric motor;
a learning operation step of performing a learning operation of the electric motor to obtain a heat generation coefficient Q and a thermal time constant T;
A prediction curve for determining a prediction curve of the motor temperature θ during normal operation based on the heat generation coefficient Q and thermal time constant T acquired in the learning operation process, the current ambient temperature θ ₀ , the motor temperature θ, and the load factor δ. It has a calculation process and
The temperature change Δθ of the electric motor in a minute time Δt is based on the heat generation coefficient Q, thermal time constant T, motor temperature θ, and ambient temperature θ ₀ Δθ={Q-1/T(θ-θ ₀ )}Δt
=Q・Δt−{1/T(θ−θ ₀ )}・Δt
The heat generation coefficient Q is calculated based on the preset starting coefficient α and specific heat generation coefficient _Q0 , and the load factor δ obtained in the load factor calculation step.Q=α・δ・_Q0
Since it is expressed as
Δθ={α・δ・Q ₀ −1/T(θ−θ ₀ )}Δt
= α・δ・Q ₀・Δt−{1/T(θ−θ ₀ )}・Δt
Then,
In the learning operation step, the heat generation coefficient Q is obtained, and the thermal time is calculated from a plurality of data including the ambient temperature θ ₀ measured in the ambient temperature measurement step and the motor temperature θ measured in the motor temperature measurement step. Get the constant T,
The ratio of the current value I to the rated current value I _R or the ratio of the power value P to the rated power value P _R is I/I _R =0 [%]
P/P _R =0 [%]
If , the motor is determined to be stopped, and the load factor δ is δ=0
The heat generation coefficient Q when stopped is Q=α・δ・Q ₀
=0
Therefore, the thermal time constant T at the time of stopping is T=T _s
is set,
I/I _R ≧110 [%]
P/P _R ≧110 [%]
If , the motor is determined to be starting, and the load factor δ is δ=1
is set, and the starting coefficient α at startup is 2 or 3.
The heat generation coefficient Q at startup is Q=α・δ・Q ₀
= α・Q ₀
Therefore, the thermal time constant T at startup is T=T _d
is set,
I/I _R <110 [%]
P/P _R <110 [%]
If , the motor is determined to be in operation (within the rated range), and the starting coefficient α is α=1
The heat generation coefficient Q during operation is set as Q=α・δ・Q ₀
=δ・Q ₀
Then, it is determined from the load factor δ based on the ratio I/I _R of the current value I to the rated current value I _R or the ratio P/P _R of the power value P to the rated power value P _R and the specific heat generation coefficient Q ₀ during operation. Therefore, the thermal time constant T during operation is approximately equal to that during startup, so
T=T _d (However, T _s > T _d )
It can be set as follows.

On the other hand, the motor temperature prediction device of the present invention includes an ambient temperature meter that measures the ambient temperature θ ₀ at the location where the motor is installed;
a motor thermometer that measures motor temperature θ;
a measuring device that measures a current value I or a power value P during operation of the electric motor;
The load factor δ is determined based on the ratio I/I _R of the current value I to the rated current value I _R or the ratio P/PR _R of the power value P to the rated power value P _R measured by the measuring device, and the learning of the motor is performed. When operating, the heat generation coefficient Q and thermal time constant T are acquired, and normal operation is performed based on the heat generation coefficient Q and thermal time constant T, the current ambient temperature θ ₀ , motor temperature θ, and load factor δ. and an arithmetic device for calculating a prediction curve of motor temperature θ at
The temperature change Δθ of the electric motor in a minute time Δt is based on the heat generation coefficient Q, thermal time constant T, motor temperature θ, and ambient temperature θ ₀ Δθ={Q-1/T(θ-θ ₀ )}Δt
=Q・Δt−{1/T(θ−θ ₀ )}・Δt
The heat generation coefficient Q is calculated based on the preset starting coefficient α and specific heat generation coefficient _Q0 , and the load factor δ . Q=α・δ・_Q0
Since it is expressed as
Δθ={α・δ・Q ₀ −1/T(θ−θ ₀ )}Δt
= α・δ・Q ₀・Δt−{1/T(θ−θ ₀ )}・Δt
Then,
In the arithmetic device, during the learning operation, a heat generation coefficient Q is obtained, and from a plurality of data including an ambient temperature θ ₀ measured by the ambient temperature meter and a motor temperature θ measured by the motor thermometer. Obtain the thermal time constant T,
The ratio of the current value I to the rated current value I _R or the ratio of the power value P to the rated power value P _R is I/I _R =0 [%]
P/P _R =0 [%]
If , the motor is determined to be stopped, and the load factor δ is δ=0
The heat generation coefficient Q when stopped is Q=α・δ・Q ₀
=0
Therefore, the thermal time constant T at the time of stopping is T=T _s
is set,
I/I _R ≧110 [%]
P/P _R ≧110 [%]
If , the motor is determined to be starting, and the load factor δ is δ=1
is set, and the starting coefficient α at startup is 2 or 3.
The heat generation coefficient Q at startup is Q=α・δ・Q ₀
=α・Q ₀
Therefore, the thermal time constant T at startup is T=T _d
is set,
I/I _R <110 [%]
P/P _R <110 [%]
If , the motor is determined to be in operation (within the rated range), and the starting coefficient α is α=1
The heat generation coefficient Q during operation is set as Q=α・δ・Q ₀
=δ・Q ₀
Then, it is determined from the load factor δ based on the ratio I/I _R of the current value I to the rated current value I _R or the ratio P/P _R of the power value P to the rated power value P _R and the specific heat generation coefficient Q ₀ during operation. Therefore, the thermal time constant T during operation is approximately equal to that during startup, so
T=T _d (However, T _s > T _d )
It can be set as follows.

According to the motor temperature prediction method and device of the present invention, the stop time can be minimized according to the ambient temperature and load condition of the motor, and the time when restarting is possible can be grasped with high precision. It can be effective.

1 is a system configuration diagram showing an embodiment of a motor temperature prediction method and apparatus of the present invention. 1 is a flowchart showing an embodiment of a motor temperature prediction method and apparatus of the present invention. 2 is a flowchart showing how to allocate heat generation coefficient Q and thermal time constant T in an embodiment of the motor temperature prediction method and device of the present invention. FIG. 3 is a diagram showing a predicted curve of motor temperature θ in an embodiment of the motor temperature prediction method and apparatus of the present invention.

Embodiments of the present invention will be described below with reference to the accompanying drawings.

1 to 4 are examples of the motor temperature prediction method and apparatus of the present invention.

In FIG. 1, 10 indicates a motor, and the motor temperature prediction device of this embodiment includes an ambient thermometer 20, a motor thermometer 30, a measuring device 40, an arithmetic device 50, and a display device 60. .

The ambient temperature meter 20 is adapted to measure the ambient temperature θ ₀ at the location where the electric motor 10 is installed.

The motor thermometer 30 is adapted to measure the motor temperature θ.

The measuring device 40 is an ammeter or a wattmeter, and is adapted to measure the current value I or the power value P of the electric motor 10.

The calculation device 50 calculates the load factor δ based on the current value I or the power value P measured by the measuring device 40, and calculates the load factor δ based on the current value I or the power value P measured by the measuring device 40, and when performing a learning operation of the electric motor 10, the The heat generation coefficient Q and the thermal time are determined based on the temperature θ ₀ , the motor temperature θ measured by the motor thermometer 30, the load factor δ, and the preset starting coefficient α and specific heat generation coefficient Q ₀ of the electric motor 10. A constant T is obtained, and a predicted curve of the motor temperature θ during normal operation is obtained based on the heat generation coefficient Q and thermal time constant T, the current ambient temperature θ ₀ , the motor temperature θ, and the load factor δ. It has become.

The display device 60 displays a predicted curve of the motor temperature θ determined by the arithmetic device 50 (see FIG. 4).

During the learning operation of the electric motor 10, the following theoretical formula is used. That is, the temperature change Δθ of the electric motor 10 in the minute time Δt is:
[Number 1]
Δθ={Q-1/T(θ-θ ₀ )}Δt
is required. Here, the heat generation coefficient Q in the formula [Equation 1] is
[Number 2]
Q=α・δ・Q ₀
Therefore, the formula [Math. 1] is
[Number 3]
Δθ={α・δ・Q ₀ −1/T(θ−θ ₀ )}Δt
becomes.

The starting coefficient α and the specific heat generation coefficient _Q0 are preset values, and the load factor δ is obtained based on the current value I or the power value P. Therefore, a plurality of data are measured during the learning operation of the electric motor 10. By solving the simultaneous equations substituted into the above theoretical equation, the heat generation coefficient Q and the thermal time constant T can be obtained.

Further, as shown in FIG. 2, the motor temperature prediction method of this embodiment includes an ambient temperature measurement step (step S10), a motor temperature measurement step (step S20), a load factor calculation step (step S30), and a learning operation. The process includes a step (step S40) and a prediction curve calculation step (step S50).

The ambient temperature measuring step is a step of measuring the ambient temperature θ ₀ at the location where the electric motor 10 is installed.

The motor temperature measuring step is a step of measuring the motor temperature θ.

The load factor calculation step is a step of calculating the load factor δ based on the current value I or the power value P of the electric motor 10.

In the learning operation step, a learning operation of the electric motor 10 is performed, and the ambient temperature θ ₀ measured in the ambient temperature measurement step, the motor temperature θ measured in the motor temperature measurement step, and the load factor calculation step are determined. This is a step of obtaining a heat generation coefficient Q and a thermal time constant T based on the obtained load factor δ, the preset starting coefficient α and the specific heat generation coefficient _Q0 of the electric motor 10.

The prediction curve calculation step calculates the motor temperature θ during normal operation based on the heat generation coefficient Q and thermal time constant T acquired in the learning operation step, the current ambient temperature θ ₀ , the motor temperature θ, and the load factor δ. This is the process of finding a predicted curve.

The predicted curve of the motor temperature θ obtained in the predicted curve calculation step is displayed on the display device 60 (see FIG. 1), for example, as shown in FIG. 4, and in the flowchart of FIG. After it is determined that the update time has elapsed in the determination of whether or not the operation has been completed (see step S60), if the operation is not completed in the determination of whether or not the operation has been completed (see step S70), the step of calculating the predicted curve is performed. A new prediction curve for motor temperature θ is now determined. The update time can be set to about 1 minute, for example, but is not limited to 1 minute and may be changed as necessary.

In the arithmetic unit 50, during the learning operation (learning operation process) of the electric motor 10, the heat generation coefficient Q and the thermal time constant T are, as shown in FIG. 3, the ratio of the current value I to the rated current value _IR , or Based on the ratio of the power value P to the rated power value _PR , the power is acquired separately at the time of stop, the time of start, and the time of operation. This is because it is necessary to select different heat generation coefficients Q and thermal time constants T depending on the transition of the operating state of the electric motor 10 (stopping, starting, running).

Incidentally, the thermal time constant T is a constant representing the degree of responsiveness to temperature changes, that is, the time required for the electric motor 10 to change from one temperature to another, and is a constant that represents the degree of responsiveness to temperature changes, that is, the time required for the electric motor 10 to change from one temperature to another. The thermal time constant T _s at the time of stopping is larger than the thermal time constant T _d during operation (at the time of starting). This is because the cooling fan (not shown) is stopped when the electric motor 10 is stopped, and the cooling fan is driven when the electric motor 10 is operated (started). For example, if the electric motor 10 is stopped at a temperature higher than the ambient temperature θ ₀ , the cooling fan will also stop, so the temperature will gradually decrease and it will take time to cool down, whereas the electric motor 10 will be at a temperature higher than the ambient temperature θ ₀ . If operation is continued from this state, the cooling fan will also be running, so the temperature will drop faster and the cooling time will be shorter than when it is stopped.

Next, the operation of the above embodiment will be explained.

The ambient temperature θ ₀ at the location where the electric motor 10 is installed is measured by the ambient temperature meter 20 (see the ambient temperature measurement step in step S10 in FIG. 2), and the motor temperature θ is measured by the motor thermometer 30 (see the step S20 in FIG. 2). The current value I or the power value P of the electric motor 10 is measured by the measuring device 40 and inputted to the calculation device 50, and the current value I or the power value P measured by the measuring device 40 is The load factor δ is determined based on the power value P (see the load factor calculation step in step S30 in FIG. 2).

First, a learning operation of the electric motor 10 is performed (see the learning operation process in step S40 in FIG. 2). During the learning operation of the electric motor 10, the ambient temperature θ ₀ measured by the ambient temperature meter 20, the motor temperature θ measured by the motor thermometer 30, the load factor δ, and the preset temperature of the electric motor 10 are determined. A heat generation coefficient Q and a thermal time constant T are obtained based on the starting coefficient α and the intrinsic heat generation coefficient _Q0 . During the learning operation of the electric motor 10, various assumed operations are performed, a plurality of data are measured and substituted into the formula [Equation 1], and the heat generation coefficient Q and thermal time constant T are calculated by solving the simultaneous equations. is obtained.

As shown in FIG. 3, the heat generation coefficient Q and the thermal time constant T are determined at the time of stopping and starting, respectively, based on the ratio of the current value I to the rated current value _IR or the ratio of the power value P to the rated power value _PR . It is obtained separately for when driving and when driving.

The ratio of the current value I to the rated current value I _R or the ratio of the power value P to the rated power value P _R is I/I _R =0 [%]
P/P _R =0 [%]
If , the electric motor 10 is determined to be stopped, and the load factor δ is δ=0
The heat generation coefficient Q when stopped is Q=α・δ・Q ₀
=0
Therefore, the thermal time constant T at the time of stopping is T=T _s
is set.

Further, the ratio of the current value I to the rated current value I _R or the ratio of the power value P to the rated power value P _R is I/I _R ≧110 [%]
P/P _R ≧110 [%]
If so, it is determined that the electric motor 10 is starting, and the load factor δ is δ=1
The heat generation coefficient Q at startup is Q=α・δ・Q ₀
=α・Q ₀
Therefore, the thermal time constant T at startup is T=T _d
is set. Note that the starting coefficient α at the time of starting is set as a numerical value such as 2 or 3, for example.

Furthermore, the ratio of the current value I to the rated current value I _R or the ratio of the power value P to the rated power value P _R is I/I _R <110 [%]
P/P _R <110 [%]
If so, it is determined that the electric motor 10 is in operation (within the rated range), and the starting coefficient α is α=1
The heat generation coefficient Q during operation is set as Q=α・δ・Q ₀
=δ・Q ₀
Therefore, the thermal time constant T during operation is approximately equal to that during startup, so
T= _Td
is set.

Then, a predicted curve of the motor temperature θ during normal operation is determined based on the heat generation coefficient Q and thermal time constant T, the current ambient temperature θ ₀ , the motor temperature θ, and the load factor δ (step S50 in FIG. 2). (See prediction curve calculation process).

The predicted curve of the motor temperature θ obtained by the calculation device 50 is displayed on the display device 60, and in the flowchart of FIG. 2, it is determined whether a preset update time has elapsed (see step S60). If it is determined that the update time has elapsed, it is determined whether or not the operation has ended at that point (see step S70), and if the operation has not ended, the process proceeds to the predicted curve calculation step of step S50. Then, a new prediction curve for the motor temperature θ is determined.

The predicted curve of the motor temperature θ displayed on the display device 60 is, for example, as shown in FIG. That is, the motor temperature θ increases from the start of starting, and after the completion of starting, the cooling fan is also rotating, so the temperature increase gradient gradually becomes gentler. If the electric motor 10 is stopped at a certain point (for example, about 50 minutes after starting) and restarted immediately after, the motor temperature θ will rise from the temperature at the time of stop (approximately 70 [°C] in the example of FIG. 4). Although the maximum allowable temperature (for example, 95 [° C.]) is reached, the motor temperature θ continues to decrease due to the operation of the cooling fan. Thereafter, when the electric motor 10 is stopped at a certain point (for example, 90 minutes after starting), the cooling fan is also stopped, so the electric motor temperature θ gradually decreases at a gentler gradient than during operation. Here, for example, if the electric motor 10 is temporarily stopped after approximately 65 minutes have elapsed from the start of startup through stopping and restarting (motor temperature θ is approximately 76 [°C]) and then restarted immediately after, the motor temperature θ will be It can be seen that the temperature rises to nearly 100 [°C], exceeding the maximum allowable temperature. Thereby, the operator can accurately grasp the time when the motor can be stopped and restarted from the predicted curve of the motor temperature θ.

As a result, in the case of this embodiment, unlike the conventional case where the stop time before restarting the electric motor 10 is set to the longest expected time, the time when the motor 10 cannot be operated becomes longer than necessary. is avoided, and the overall operation is carried out efficiently.

Furthermore, unlike the device disclosed in Patent Document 1, the present invention does not simply use preset thermal time constants during operation, thermal time constants during stoppage, and allowable number of starts of the electric motor 10; In this example, a prediction curve of the motor temperature θ during normal operation is created based on the heat generation coefficient Q and thermal time constant T obtained in the learning operation, the current ambient temperature θ ₀ , the motor temperature θ, and the load factor δ. Since it is obtained in the prediction curve calculation process, it is possible to respond with high precision in consideration of the constantly changing ambient temperature and load condition of the electric motor 10.

In this way, the stop time can be minimized depending on the ambient temperature and load condition of the electric motor 10, and the restartable time can be determined with high accuracy.

It should be noted that the motor temperature prediction method and device of the present invention are not limited to the above-described embodiments, and it goes without saying that various changes can be made without departing from the gist of the present invention.

10 Electric motor 20 Ambient thermometer 30 Motor thermometer 40 Measuring device 50 Arithmetic device 60 Display device

Claims (2)

an ambient temperature measurement step of measuring ambient temperature θ ₀ at the location where the electric motor is installed;
a motor temperature measurement step of measuring motor temperature θ;
A load factor calculation step of calculating a load factor δ based on the ratio I/I _{R of the current value I to the rated current value I R or} the ratio P/ _{PR of the power value P to the rated power value P R during} operation of the electric motor;
a learning operation step of performing a learning operation of the electric motor to obtain a heat generation coefficient Q and a thermal time constant T;
A prediction curve for determining a prediction curve of the motor temperature θ during normal operation based on the heat generation coefficient Q and thermal time constant T acquired in the learning operation process, the current ambient temperature θ ₀ , the motor temperature θ, and the load factor δ. It has a calculation process and
The temperature change Δθ of the electric motor in a minute time Δt is based on the heat generation coefficient Q, thermal time constant T, motor temperature θ, and ambient temperature θ ₀ Δθ={Q-1/T(θ-θ ₀ )}Δt
=Q・Δt−{1/T(θ−θ ₀ )}・Δt
The heat generation coefficient Q is calculated based on the preset starting coefficient α and specific heat generation coefficient _Q0 , and the load factor δ obtained in the load factor calculation step.Q=α・δ・_Q0
Since it is expressed as
Δθ={α・δ・Q ₀ −1/T(θ−θ ₀ )}Δt
= α・δ・Q ₀・Δt−{1/T(θ−θ ₀ )}・Δt
Then,
In the learning operation step, the heat generation coefficient Q is obtained, and the thermal time is calculated from a plurality of data including the ambient temperature θ ₀ measured in the ambient temperature measurement step and the motor temperature θ measured in the motor temperature measurement step. Get the constant T,
The ratio of the current value I to the rated current value I _R or the ratio of the power value P to the rated power value P _R is I/I _R =0 [%]
P/P _R =0 [%]
If , the motor is determined to be stopped, and the load factor δ is δ=0
The heat generation coefficient Q when stopped is Q=α・δ・Q ₀
=0
Therefore, the thermal time constant T at the time of stopping is T=T _s
is set,
I/I _R ≧110 [%]
P/P _R ≧110 [%]
If , the motor is determined to be starting, and the load factor δ is δ=1
is set, and the starting coefficient α at startup is 2 or 3.
The heat generation coefficient Q at startup is Q=α・δ・Q ₀
=α・Q ₀
Therefore, the thermal time constant T at startup is T=T _d
is set,
I/I _R <110 [%]
P/P _R <110 [%]
If , the motor is determined to be in operation (within the rated range), and the starting coefficient α is α=1
The heat generation coefficient Q during operation is set as Q=α・δ・Q ₀
=δ・Q ₀
Then, it is determined from the load factor δ based on the ratio I/I _R of the current value I to the rated current value I _R or the ratio P/P _R of the power value P to the rated power value P _R and the specific heat generation coefficient Q ₀ during operation. Therefore, the thermal time constant T during operation is approximately equal to that during startup, so
T=T _d (However, T _s > T _d )
A motor temperature prediction method that is set as follows. an ambient temperature meter that measures ambient temperature θ ₀ at the location where the electric motor is installed;
a motor thermometer that measures motor temperature θ;
a measuring device that measures a current value I or a power value P during operation of the electric motor;
The load factor δ is determined based on the ratio I/I _R of the current value I to the rated current value I _R or the ratio P/PR _R of the power value P to the rated power value P _R measured by the measuring device, and the learning of the motor is performed. When operating, the heat generation coefficient Q and thermal time constant T are acquired, and normal operation is performed based on the heat generation coefficient Q and thermal time constant T, the current ambient temperature θ ₀ , motor temperature θ, and load factor δ. and an arithmetic device for calculating a prediction curve of motor temperature θ at
The temperature change Δθ of the electric motor in a minute time Δt is based on the heat generation coefficient Q, thermal time constant T, motor temperature θ, and ambient temperature θ ₀ Δθ={Q-1/T(θ-θ ₀ )}Δt
=Q・Δt−{1/T(θ−θ ₀ )}・Δt
The heat generation coefficient Q is calculated based on the preset starting coefficient α and specific heat generation coefficient _Q0 , and the load factor δ . Q=α・δ・_Q0
Since it is expressed as
Δθ={α・δ・Q ₀ −1/T(θ−θ ₀ )}Δt
= α・δ・Q ₀・Δt−{1/T(θ−θ ₀ )}・Δt
Then,
In the arithmetic device, during the learning operation, a heat generation coefficient Q is obtained, and from a plurality of data including an ambient temperature θ ₀ measured by the ambient temperature meter and a motor temperature θ measured by the motor thermometer. Obtain the thermal time constant T,
The ratio of the current value I to the rated current value I _R or the ratio of the power value P to the rated power value P _R is I/I _R =0 [%]
P/P _R =0 [%]
If , the motor is determined to be stopped, and the load factor δ is δ=0
The heat generation coefficient Q when stopped is Q=α・δ・Q ₀
=0
Therefore, the thermal time constant T at the time of stopping is T=T _s
is set,
I/I _R ≧110 [%]
P/P _R ≧110 [%]
If , the motor is determined to be starting, and the load factor δ is δ=1
is set, and the starting coefficient α at startup is 2 or 3.
The heat generation coefficient Q at startup is Q=α・δ・Q ₀
=α・Q ₀
Therefore, the thermal time constant T at startup is T=T _d
is set,
I/I _R <110 [%]
P/P _R <110 [%]
If , the motor is determined to be in operation (within the rated range), and the starting coefficient α is α=1
The heat generation coefficient Q during operation is set as Q=α・δ・Q ₀
=δ・Q ₀
Then, it is determined from the load factor δ based on the ratio I/I _R of the current value I to the rated current value I _R or the ratio P/P _R of the power value P to the rated power value P _R and the specific heat generation coefficient Q ₀ during operation. Therefore, the thermal time constant T during operation is approximately equal to that during startup, so
T=T _d (However, T _s > T _d )
A motor temperature prediction device that is set as

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