JP7632089B2 - Motor magnet temperature estimation method - Google Patents

Description

The disclosed technology relates to a method for estimating the magnet temperature of a motor.

In recent years, the number of vehicles that run on electricity, such as hybrid cars and electric cars, has been increasing. Typically, such vehicles are equipped with a permanent magnet synchronous motor (also simply called a motor) as a drive source. In such motors, a permanent magnet (also simply called a magnet) is installed on the rotor. An alternating current controlled by an inverter is passed through the stator of the motor. This causes the rotor to rotate due to the effect of the changing magnetic field, and the motor is driven.

When the motor runs, the magnet generates heat. Therefore, if the motor runs continuously for a long period of time, the magnet becomes hot. However, the maximum magnetic flux of the magnet is temperature dependent. When the temperature of the magnet exceeds a certain upper limit, the magnet's magnetic force drops sharply and the dropped magnetic force does not return to normal. In other words, the magnet becomes irreversibly demagnetized.

Therefore, while the motor is running, the magnet temperature must be strictly controlled so that it does not exceed the upper limit. To do this, the magnet temperature must be measured, but the rotor is rotating. It is difficult to directly measure the magnet temperature using a temperature sensor, etc.

Therefore, conventionally, the magnet temperature has been estimated indirectly based on the stator temperature, induced voltage, etc. (for example, see Patent Document 1).

Furthermore, prior art related to an application example of the technology disclosed here is Patent Document 2, which discloses a technology for estimating the temperature of a motor, specifically, the transient temperature of a coil.

Patent Document 2 also discloses a block diagram of state feedback control in which a full-state observer is used. The error between the actual thermistor temperature obtained by measuring the temperature of the coil of the actual motor, which is the system, and the estimated thermistor temperature output from the simulation model, which is the observer, is multiplied by a feedback gain and added to the input of the simulation model, thereby correcting the estimated thermistor temperature.

A predetermined value is used for the feedback gain (paragraph 0040).

WO2014-057558 publication JP 2016-082698 A

There is a risk of a large error in the estimated value. Therefore, when managing the magnet temperature based on the estimated value, this error must be taken into consideration, and the magnet temperature must be managed at a temperature that is excessively lower than the upper limit. As a result, the motor is currently not able to perform to its full potential. There is a need to improve the accuracy of magnet temperature estimation.

In this regard, estimating the magnet temperature based on the induced voltage has the advantage that it can be achieved with a relatively simple structure and can provide relatively high accuracy. On the other hand, this estimation method has the disadvantage of lacking in responsiveness. For example, in the above-mentioned Patent Document 1, the current flowing through the motor is set to "0" in order to detect the induced voltage.

When the current flowing through the motor is set to zero, the torque output by the motor also becomes zero. Moreover, it takes a certain amount of time for the current flowing through the motor to become zero. For this reason, the estimation method of Patent Document 1 cannot be used when the motor is outputting torque. It can only be used during the deceleration period of the vehicle. In other words, it is limited by the operating state of the motor and lacks quick response.

The technology disclosed here aims to realize a motor magnet temperature estimation method with excellent estimation accuracy and responsiveness by improving the conventional estimation method based on induced voltage. This makes it possible to realize highly accurate estimation of magnet temperature regardless of the operating state of the motor.

The disclosed technology relates to a magnet temperature estimation method for a motor in which magnets constituting magnetic poles are installed in a rotor, and which rotates by passing an AC current formed by controlling the on/off of switching elements of an inverter through multiple coils of a stator. The magnet temperature estimation method executes the following processes:

While the motor is in operation, the switching element is controlled to turn off to momentarily interrupt the flow of current to the coil. An interruption current value, which is the current value at the time of the interruption, and a transient coil voltage value, which is the voltage value of the coil during the interruption transient, are obtained. An induced voltage is calculated using a predetermined formula formulated based on the voltage change in the coil after the interruption, and the interruption current value and the transient coil voltage value. The temperature of the magnet is then estimated based on the calculated induced voltage.

In other words, this magnet temperature estimation method involves an instantaneous stop (momentary interruption or momentary power outage). Therefore, it has almost no effect on the torque output by the motor. A momentary interruption can be performed regardless of the operating state of the motor. It can be performed not only during deceleration periods of the vehicle, but also during acceleration periods, providing excellent responsiveness.

Then, at the time of the interruption, the current value at the interruption and the coil voltage value at the transient are acquired, and the induced voltage is calculated using these and a specified formula. This formula is formulated based on the change in coil voltage after the interruption, so by using this formula, it is possible to calculate the induced voltage after the transient. The current value at the interruption and the coil voltage value at the transient are then actually measured, and the values are substituted into the formula to calculate the induced voltage. After that, the magnet temperature can be estimated based on the calculated induced voltage.

Therefore, by applying this magnet temperature estimation method, it becomes possible to estimate the magnet temperature with high accuracy, regardless of the operating state of the motor. As a result, it becomes easier to properly manage the temperature of the magnet, allowing the motor to perform at its full potential and reducing fuel and/or battery consumption.

The magnet temperature estimation method may also be such that the coils are configured into three coil groups consisting of U-phase, V-phase, and W-phase, the inverter is configured to control the power supplied from a DC power source to each of the coil groups to pass AC currents of different phases, and the following formula is used as the formula:

Here, V _emf is induced voltage, V _f is forward voltage of the diode connected inversely parallel to the switching element, V is voltage of the DC power supply, L is inductance, i is current, the subscripts P ₁ , P ₂ , P ₃ are indications identifying the phases U, V, and W, ω is angular velocity of rotation, φ is phase of the current at the time of momentary interruption in the phase corresponding to P ₁ , R is internal resistance of the DC power supply, R _l is resistance of the switching element at the time of momentary interruption, and t is time elapsed after momentary interruption.

In other words, the motor to which this magnet temperature estimation method is applied is a so-called three-phase motor. The power supplied from a DC power source is converted to AC current by an inverter and then passed through the motor. Therefore, this method is suitable for vehicle-mounted motors.

The formula shown here is a circuit equation formulated based on an equivalent circuit model during a momentary interruption transient, and expresses the transient state after a momentary interruption. Therefore, by performing calculations using this formula, it is possible to estimate the induced voltage.

The magnet temperature estimation method may also use the following formula as the formula:
V _emf = Ka・V _P (t)+Kb・I ₀ +Kc
Here, V _P (t) is the coil voltage value during a transient state, I ₀ is the current value during an instantaneous interruption, and Ka, Kb, and Kc are predetermined coefficients including variables.

The formula shown here is a generalized circuit equation that expresses the transient state after a momentary interruption. Therefore, by performing calculations using this formula, it is possible to estimate the induced voltage relatively easily. It is highly versatile and convenient.

Furthermore, the magnet temperature estimation method may also involve storing the predetermined coefficients Ka, Kb, and Kc in a database by digitizing them, and calculating the induced voltage using the database.

In this way, by referencing the database, it is possible to simplify complex calculations that occur when coefficients include variables. This reduces the burden of calculation processing and speeds up the calculation process.

The magnet temperature estimation method may also use a constant value L for the inductances Lu, Lv, and Lw of the coils of each phase.

By doing so, the inductance can be made a common constant value, simplifying the calculation process. This reduces the burden on the calculation process and speeds up the calculation process.

The magnet temperature estimation method may also formulate a simplified formula based on an equivalent circuit model that does not take into account the leakage current flowing through the switching element when the switching element is turned off, and calculate the induced voltage using the simplified formula.

When the switching element is controlled to be off, leakage current actually exists. Therefore, if estimation accuracy is a priority, it is preferable to take this effect into consideration. However, formulating an equation taking the effect of leakage current into consideration makes the equation complicated and increases the burden of computational processing. In contrast, a simplified equation can be formulated based on an equivalent circuit model that does not take leakage current into consideration. Using this equation can reduce the burden of computational processing and speed up computational processing.

The magnet temperature estimation method may also involve: an interruption occurs when the current phase is 90°; two transient coil voltage values are obtained when ωt = nπ (ω is the rotational angular velocity, t is the time elapsed after the interruption, and n is a natural number); a simplified equation is formulated by calculating the difference between the two transient coil voltage values in the equation; and the induced voltage is calculated using the simplified equation.

By formulating the formula in this way, terms containing trigonometric functions can be omitted. This simplifies the complex formula, reducing the burden of calculation processing and speeding up the calculation process.

The magnet temperature estimation method may also involve converting at least some of the terms constituting the formula, including variables, into data and storing them in a database, and then calculating the induced voltage using the database.

By doing this, complex calculations involving variables can be simplified by referencing the database. This reduces the burden of calculation processing and makes the processing faster.

The disclosed technology enables highly accurate estimation of magnet temperature regardless of the operating state of the motor. As a result, proper temperature management of the magnet becomes easier, allowing the motor to perform at its full potential and reducing fuel and/or battery consumption.

1 is a simplified diagram of a motor system suitable for application of the disclosed technology; This is a simplified diagram of the electric circuit of the motor system. The upper diagram shows the motor in operation, and the lower diagram shows the motor in stopped state. 10A and 10B are diagrams for explaining a change in current during off control of a switching element. 6 is a graph for explaining a change in voltage of a coil immediately after the motor is stopped. FIG. 13 is a diagram showing an equivalent circuit model of a motor system during a momentary interruption transition. This is a list of characters used in mathematical expressions, etc. FIG. 2 is a diagram showing Equation (1) corresponding to the explanation. FIG. 13 is a diagram for explaining the formula (2). FIG. 11 is a diagram showing formulas (3) and (4) corresponding to the explanation. FIG. 1 is a diagram showing formulas (5) to (7) corresponding to the explanation. FIG. 1 is a diagram showing formulas (8) to (11) corresponding to the explanation. 4 is a flowchart of a process for estimating a magnet temperature. FIG. 1 is a block diagram showing a conventional observer model (upper diagram) and a modified observer model (lower diagram). FIG. 11 is a schematic configuration diagram of a magnet temperature estimation system to which a magnet temperature estimation method of an application example is applied. FIG. 1 is a diagram illustrating an example of a thermal model in a simplified manner. 10 is a diagram for explaining the correspondence relationship between a feedback gain K and a current and a voltage. FIG. 13 is a flowchart of a process for estimating a magnet temperature in an application example. 1 is a graph showing an outline of the results of a demonstration test.

Below, an embodiment of the disclosed technology is described in detail with reference to the drawings. However, the following description is merely exemplary in nature. For convenience, mathematical expressions related to the disclosed technology are shown in both the specification and the drawings. Common letters are used in the mathematical expressions (see the table in Figure 6).

<Motor system>
1 shows a simplified diagram of a motor system 1 suitable for application of the disclosed technology. This motor system 1 is mounted on a vehicle (electric vehicle) capable of running using electric power, such as a hybrid vehicle or an electric vehicle. The motor system 1 is composed of a drive motor 2, an inverter 3, a motor control unit (MCU 4), and the like.

The motor 2 is a permanent magnet type synchronous motor. The motor 2 is equipped with a rotor 20 and a stator 21. The rotor 20 is disposed inside the stator 21. The rotor 20 may be disposed outside the stator 21, but this motor 2 is an inner rotor type. A shaft 22 is fixed to the center of the rotor 20. The shaft 22 is rotatably supported by a motor case that houses the rotor 20 and the stator 21. The rotational power of the motor 2 is output via the shaft 22. In other words, the motor 2 is driven. This causes the vehicle to run.

A permanent magnet 23 (also simply referred to as magnet 23) is installed on the outer periphery of the rotor 20. The magnets 23 form the magnetic poles of the rotor 20. That is, the magnets 23 are arranged on the outer periphery of the rotor 20 so that the south poles and north poles are alternately arranged at equal intervals in the circumferential direction. The number, arrangement, shape, etc. of the magnets 23 are set according to the specifications of the motor 2. For example, multiple plate-shaped magnets 23 may be installed, or one ring-shaped magnet 23 having multiple magnetic poles may be installed.

The stator 21 is arranged around the rotor 20 with a small gap (gap 24) between them. The stator 21 has a stator core 21a and multiple coils 25. The multiple coils 25 are formed by winding electric wires in a predetermined order around multiple teeth that radiate from the inside of the stator core 21a.

The shape of the stator core 21a, the number and arrangement of the coils 25, etc. are set according to the specifications of the motor 2. In the case of this motor 2, these coils 25 form three coil groups 25U, 25V, 25W consisting of U-phase, V-phase, and W-phase. Each of these coil groups 25U, 25V, 25W is connected to the inverter 3 via a connection cable 26.

The inverter 3 is connected to a DC power source 5 via a power supply cable 30. Specific examples of the DC power source 5 include a low-voltage battery with a rated voltage of 50 V or less, and a high-voltage battery with a rated voltage of 300 V or more. The DC power source 5 supplies power to the inverter 3.

The inverter 3 is also connected to the MCU 4 via a harness 40. The MCU 4 is composed of hardware such as a processor, memory, and interface, and software such as a control program. The combination of this hardware and software gives the MCU 4 the following functional components: an inverter control unit 41, a magnet temperature estimation unit 42, and a database 43.

The inverter control unit 41 drives the motor 2 by controlling the inverter 3. The magnet temperature estimation unit 42 estimates the temperature of the magnet 23 using a predetermined mathematical formula (circuit equation, etc.) described below. The database 43 stores data used to control the inverter 3 and estimate the temperature of the magnet 23. The data is in various formats, and the data is stored in the database 43 in a format according to the application, such as numerical values, mathematical formulas, maps, and tables. The inverter control unit 41 and magnet temperature estimation unit 42 use this data as necessary.

Figure 2 shows a simplified electrical circuit of the motor system 1. The inverter 3 has a known inverter circuit 31 built in. The inverter 3 converts the power of the DC power supply 5 into a three-phase AC current using the inverter circuit 31, and energizes each of the coil groups 25U, 25V, and 25W of the motor 2. This creates a periodically changing magnetic field between the magnetic poles of the rotor 20 and each of the coil groups 25U, 25V, and 25W of the stator 21. The rotor 20 and shaft 22 rotate in response to the change in the magnetic field, and the motor 2 is driven.

In the DC power supply 5, R represents the internal resistance, and V represents the DC voltage. The inverter circuit 31 built into the inverter 3 has three arms 31a corresponding to the U, V, and W phases. These arms 31a are connected to the high voltage (positive) side and low voltage (negative) side of the DC power supply 5 via power supply cables 30.

Two switching elements (upstream switching element 33U and downstream switching element 33L) are connected in series to each of these arms 31a. The switching elements 33U and 33L are, for example, semiconductor switches such as MOS-FETs and IGBTs. In addition, two diodes 34 are connected in anti-parallel to each of the switching elements 33U and 33L in each of the arms 31a. These diodes 34 are so-called freewheel diodes.

A connection cable 26 is connected between the upstream switching element 33U and the downstream switching element 33L, which is connected to the coil groups 25U, 25V, and 25W of each phase of the motor 2. In each of the coil groups 25U, 25V, and 25W, r represents the internal resistance, and L represents the inductance of the coil 25 of each phase. The inverter circuit 31 generates an AC current by controlling the on/off of these switching elements 33U and 33L, and energizes the coil groups 25U, 25V, and 25W of each phase of the motor 2.

The upper diagram in Figure 2 shows a specific state when the motor 2 is operating. Here, the upstream switching element 33U of the U phase, the downstream switching element 33L of the V phase, and the downstream switching element 33L of the W phase are controlled to be on. On the other hand, the downstream switching element 33L of the U phase, the upstream switching element 33U of the V phase, and the upstream switching element 33U of the W phase are controlled to be off.

As a result, current flows through the coil groups 25U, 25V, and 25W of each phase, as shown by the dashed arrows. Current flows into the motor 2 through the U-phase connecting cable 26, and current flows out of the motor 2 through the V-phase and W-phase connecting cables 26 (the U-phase current is positive, and the V-phase and W-phase currents are negative). The inverter control unit 41 controls the on/off of each switching element 33U, 33L at a predetermined timing. By doing so, the current flow of each phase is switched so that, for example, the V-phase current is positive and the W-phase and U-phase currents are negative. Alternating currents of different phases are passed through the coil groups 25U, 25V, and 25W of each phase.

The lower diagram in Figure 2 shows the state when the current is cut off from the state shown in the upper diagram and the operation of the motor 2 is stopped. In other words, the upstream switching element 33U of the U phase, the downstream switching element 33L of the V phase, and the downstream switching element 33L of the W phase, which were controlled to be on, are controlled to be off. At this time, induced power is generated in the coil groups 25U, 25V, and 25W of each phase, and a current (induced current) flows for a short period of time, as indicated by the dashed arrows.

When switching elements 33U and 33L are controlled to be turned off, ideally they switch from the on state to the off state without any time lag. However, in reality, there is a transition state between the on state and the off state. Figure 3 shows the current change before and after the on/off control of switching elements 33U and 33L. The off control occurs at timing t0.

In ideal off control, as shown by the dashed line, the current becomes zero at time t0. There is no transient state. In contrast, in actual off control, as shown by the solid line, the current does not become zero at time t0, but becomes zero at a specified time after t0 (current falling). In other words, the current continues to flow for a certain period of time after t0.

Therefore, in the case of actual off control, the current flow in the motor system 1 immediately after the motor 2 stops flows not only through the current path indicated by the dashed arrow in the lower diagram of Figure 2, but also through the path indicated by the solid arrow (this current is also called "leakage current").

<Magnet temperature estimation>
When the motor 2 is driven, the magnet 23 generates heat. Therefore, if the motor 2 is driven continuously for a long period of time, the magnet 23 becomes hot. Meanwhile, the maximum magnetic flux of the magnet 23 is temperature dependent. When the temperature of the magnet 23 (hereinafter also referred to as the magnet temperature) rises, the magnetic flux density decreases. Then, when the magnet temperature exceeds a predetermined upper limit, the magnetic force of the magnet 23 drops sharply, and the dropped magnetic force does not return to normal. In other words, the magnet 23 is irreversibly demagnetized.

Therefore, while the motor 2 is running, the temperature of the magnet 23 must be strictly controlled so that the upper limit is not exceeded. To do this, the magnet temperature must be measured, but the magnet 23 is attached to the rotating rotor 20. Therefore, it is difficult to measure the magnet temperature directly. The magnet temperature can only be estimated in an indirect manner.

Therefore, the MCU 4 is provided with a magnet temperature estimation unit 42. The magnet temperature estimation unit 42 estimates the magnet temperature based on the induced voltage (also simply called induced voltage) caused by the magnetic flux of the magnet 23. Since there is a correlation between the induced voltage and the magnet temperature, if the induced voltage (more specifically, the maximum value of the induced voltage, etc.) can be detected with high accuracy, the magnet temperature can also be estimated with high accuracy.

However, conventional methods for detecting induced voltage require stopping the motor 2 and waiting for a certain amount of time to pass. This has the disadvantage of being slow to respond.

Figure 4 shows an example of the voltage change in coil 25 immediately after motor 2 is stopped, that is, immediately after current to coil 25 is stopped. Motor 2 is stopped at time t0. The solid line graph Gy represents the induced voltage, and the dashed line graph Gz represents the terminal voltage applied to coil 25 (the sum of the induced voltage and the back electromotive force).

As described above, when motor 2 is stopped, an induced current flows and a back electromotive force is generated in coil 25. As a result, the coil voltage immediately after motor 2 is stopped is the sum of the back electromotive force and the induced voltage. Then, as time passes and the induced current stops flowing and the back electromotive force becomes zero (timing t1), the coil voltage becomes only the induced voltage, and the induced voltage can be detected.

In other words, the conventional method of detecting induced voltage detects the induced voltage at a timing after t1, which limits the operation of motor 2. For example, if induced voltage detection is performed while motor 2 is operating, there will be a time when torque cannot be output. This will cause a torque shock and the vehicle will not be able to run smoothly. In order to avoid adversely affecting the running of the vehicle, the method can only be used when a time when torque is not output can be secured, for example, during the deceleration period of the vehicle. In other words, the conventional method of detecting induced voltage is limited by the operating state of motor 2 and therefore lacks quick response.

In response to this, the magnet temperature estimation unit 42 momentarily stops (interrupts) the flow of current to the coil 25 by controlling the switching elements 33U and 33L to be off, for example, between t0 and t2. The time for which the flow of current is interrupted by the interruption is, for example, 10 milliseconds (ms) or less. 5 ms or less is preferable. Then, the induced voltage is estimated using a formula such as a predetermined circuit equation that has been newly formulated.

In detail, it is obtained by actually measuring the current value (current value during momentary interruption) at the time of momentary interruption (at or around t0) and the voltage value (coil voltage value during transient) of coil 25 at the time of momentary interruption (the period from momentary interruption until a steady state is reached, between t0 and t1). Then, these current value during momentary interruption and coil voltage value during transient are substituted into a predetermined circuit equation (more specifically, an analytical solution equation derived from the circuit equation). In this way, the induced voltage is estimated.

In other words, the induced voltage is detected by a momentary stop (instantaneous interruption) that has almost no effect on the operation of the motor 2. Since it is only necessary to momentarily stop the current supply to the coil 25, there is almost no effect on the torque output by the motor 2. Therefore, the induced voltage can be detected regardless of the operating state of the motor 2. Since the induced voltage can be detected not only during the deceleration period of the vehicle but also during the acceleration period, it has excellent responsiveness.

<Circuit Equation>
(Basic circuit equation)
Fig. 5 shows an equivalent circuit model of the motor system 1 during a momentary interruption transient. This equivalent circuit model corresponds to Fig. 2. Note that common letters are used in the following formulas, including Fig. 5 (see the table shown in Fig. 6).

That is, it represents a case where a momentary interruption occurs when the U-phase current is positive and the V-phase and W-phase currents are negative. In the equivalent circuit model where a momentary interruption occurs when the V-phase or W-phase has a positive current, the part corresponding to the U-phase is simply replaced with the respective phase. Therefore, for convenience, the phase that was carrying a positive current at the time of the momentary interruption (also called the current-carrying phase during momentary interruption) will be described hereafter as being the U-phase unless otherwise specified.

This diagram also takes into account the leakage current mentioned above. The induced voltage Vemf of each phase is shown in a simplified manner. If the induced voltage of each phase were shown precisely, it would be as follows.

Induced voltage of U phase: V _emf sin(ωt)
V-phase induced voltage: V _emf sin(ωt-2π/3)
W-phase induced voltage: V _emf · sin(ωt + 2π/3).

Based on this equivalent circuit model, we have formulated a new circuit equation (basic circuit equation). Figure 7 shows the basic circuit equation as formula (1). This basic circuit equation expresses the transient state after an instantaneous interruption, and shows the basic circuit equation with U-phase as the current-carrying phase during an instantaneous interruption.

The solution to this basic circuit equation can be analytically found using the Laplace transform. If the analytical solution equation obtained from the basic circuit equation is rearranged and simplified for the induced voltage, it can be expressed as the following equation.

V _emf = Ka・V _P (t)+Kb・I ₀ +Kc ... General formula (1)
Here, _Vp (t) is a transient coil voltage value of the energized phase at the time of the instantaneous interruption, and _I0 is a current value at the time of the instantaneous interruption. Ka, Kb, and Kc are predetermined coefficients. Ka, Kb, and Kc are coefficients determined by the contents of the circuit equation and include variables.

In other words, if the current value during an instantaneous interruption and the coil voltage value during a transient are obtained, the induced voltage can be estimated by using the basic circuit equation. Therefore, the basic circuit equation or a formula obtained from the basic circuit equation can be stored in the MCU 4. The current value during an instantaneous interruption and the coil voltage value during a transient can be obtained by actually measuring them using the inverter 3, and the data can be output to the MCU 4. This allows the MCU 4 to estimate the induced voltage.

In addition, instead of using the current value during an interruption and the coil voltage value during a transient in the basic circuit equation, the induced voltage may be estimated using the slope of the coil voltage of the current-carrying phase during an interruption, as described below.

<Simplification of basic circuit equations>
Estimating the induced voltage using the basic circuit equations can estimate the induced voltage with high accuracy, but it places a heavy burden on the computational processing when calculating the analytical solution. This requires a high-performance processor, and even a high-performance processor has difficulty performing calculations in a short time. Therefore, it is not efficient to estimate the induced voltage using the basic circuit equations themselves every time the magnet temperature is estimated.

In contrast, in practice, a certain degree of error in the estimation accuracy of the induced voltage is often tolerable. Also, depending on the operating state of the motor 2, the basic circuit equation may be simplified. In such cases, it is therefore preferable to use a simplified version of the basic circuit equation described above. This reduces the burden of calculation processing and increases the processing speed. Next, a method for simplifying the basic circuit equation will be described.

(Data conversion of variable-containing terms)
As shown in Fig. 7, the basic circuit equation has terms that include variables (variable-containing terms). For example, induced current is a variable because it changes during a momentary interruption transient. Inductance changes with the rotation angle of the motor 2 and also with the temperature of the coil 25. Therefore, when these are taken into consideration, inductance is also a variable. The resistance of the switching elements 33U and 33L also changes over time, so when this is taken into consideration, the resistance of the switching elements 33U and 33L is also a variable.

When performing calculations using basic circuit equations, the more variables there are, the greater the burden of calculation processing. Therefore, it is preferable to convert variables that can be replaced with numerical values, etc., through experiments, etc., into data in advance and store them in database 43. The entire variable-containing term may be converted into data, or only a portion of the variable-containing term may be converted into data. The data format may be selected appropriately depending on the application.

(First Simplified Circuit Equation)
The basic circuit equation is formulated taking into consideration the actual off control in which leakage current occurs. In contrast, as shown in the upper part of Fig. 8, by assuming that the resistance Rl of the switching elements 33U and 33L is infinite, it is possible to express ideal off control in which no leakage current occurs. This makes it possible to simplify the equivalent circuit model shown in Fig. 5. The simplified equivalent circuit model is shown in the middle part of Fig. 8.

By formulating a circuit equation based on this simplified equivalent circuit model, a simplified circuit equation that does not take leakage current into account (first simplified circuit equation) is obtained. The first simplified circuit equation is shown in the lower part of Figure 8 as equation (2). Note that, for simplification, the resistance r of coil 25 is not taken into account in equation (2) (if it is taken into account, R can be replaced with R + 2r).

(Constant inductance)
As described above, the inductance changes depending on the rotation angle of the motor 2, the temperature of the coil 25, etc. However, if the degree of this change can be ignored in practical use, the inductance of the coil 25 of each phase may be made a constant. Specifically, in the basic circuit equations or simplified circuit equations, the same constant value L is used for the inductances Lu, Lv, and Lw of the coil 25 of each phase, as shown in the upper part of Fig. 9.

As an example, the equation in which the inductance of the coil 25 of each phase is constant in the first simplified circuit equation is shown as equation (3) in Figure 9.

(Derivation of analytical solution)
Next, the derivation of the analytical solution will be described using the first simplified circuit equation shown in Equation (3).

The current is derived from the first simplified circuit equation shown in formula (3) by Laplace transformation. Then, the U-phase coil voltage VU(t) is found from the relationship v = L di/dt. The analytical solution obtained from this is shown in Figure 9 as formula (4).

In formula (4), α is 2R/3L. t is the time that has elapsed since the momentary interruption. The transient coil voltage value can be calculated by substituting the time that has elapsed since the momentary interruption, t, from the time that the transient coil voltage value was acquired, into formula (4).

Note that equation (4) is an analytical solution derived using the first simplified circuit equation shown in equation (3). Therefore, leakage current is not taken into consideration. If leakage current is taken into consideration, an equation in which V and other factors are replaced in equation (4) can be used, as shown as equation (5) in FIG. 10. Furthermore, if the internal resistance r of coil 25 is taken into consideration, an equation in which R is replaced with R+2r can be used.

When formula (4) is further solved for the induced voltage V _emf , the formula shown in formula (6) in Fig. 10 is obtained. This formula can be rewritten as formula (7) in Fig. 10. That is, it becomes the above-mentioned general formula (1). However, Ka, Kb, and Kc here are shown as annexed to formula (7).

Therefore, the induced voltage can be estimated by acquiring the current value during the momentary interruption and the coil voltage value during the transient, and by using the first simplified circuit equation (more specifically, an equation derived from the first simplified circuit equation) together with the time t that has elapsed since the momentary interruption until the transient coil voltage value was acquired.

(Selection of detection timing)
The circuit equation can be simplified by selecting the timing of the momentary interruption and the timing of acquiring the transient coil voltage value.

Specifically, the interruption occurs when the phase of the current becomes 90°. In other words, the interruption occurs when the AC current flowing through the U-phase at the time of the interruption becomes maximum. Then, two transient coil voltage values are obtained when ωt = nπ (n is a natural number). The difference is then calculated using the two transient coil voltage values in the circuit equation. In this way, a simplified circuit equation (second simplified circuit equation) can be formulated.

Figure 11 shows the first simplified circuit equation as equation (8) when a momentary interruption occurs when the current phase is 90°. By setting the current phase to 90°, the trigonometric function terms can be simplified (see equation (4) in Figure 9).

Furthermore, two transient coil voltage values are obtained at the timing when ωt = nπ, and the difference is calculated using these two transient coil voltage values in the equation shown in formula (8). An example of the second simplified circuit equation thus formulated is shown in Figure 11 as formula (9). In this way, the trigonometric function terms can be eliminated. Therefore, the circuit equation can be further simplified.

When this method is used, the transient coil voltage value is obtained at two points separated by a rotation interval. Therefore, the higher the rotation speed of the motor 2, the shorter the time it takes to estimate the induced voltage. Therefore, this method is effective when the motor 2 is operating at high rotation speed.

(Estimation of induced voltage based on the gradient of coil voltage during momentary interruption)
The induced voltage can also be estimated by using the gradient (amount of change with respect to time) of the coil voltage of the energized phase during an instantaneous interruption in the above circuit equation. Since only the instantaneous interruption is taken into consideration, and not the transient period, the induced voltage can be estimated in a short time.

However, with this method, it is necessary to actually measure the slope of the coil voltage during a momentary interruption. Therefore, it is effective to use this method when motor 2 is operating at low speed.

A simplified circuit equation (third simplified circuit equation) formulated by applying this method to the first simplified circuit equation is shown as formula (10) in Fig. 11. Since t = 0, the equation can be simplified. When formula (10) is further rearranged with respect to the induced voltage V _emf , the equation shown in formula (11) in Fig. 11 is obtained. Therefore, even by using the actual measured value of the gradient of the coil voltage during an instantaneous interruption, the induced voltage can be estimated while reducing the burden of calculation processing and increasing the speed.

The MCU 4 selects such equations, that is, the basic circuit equations, the simplified circuit equations, or equations derived from these, according to the specifications of the motor system 1, and stores them in the magnet temperature estimation unit 42 or the database 43. It may store multiple equations or a single equation.

Then, among the terms that make up the formula, it is preferable to convert the parts containing variables into numerical values or the like in advance through experiments or the like, and to store the data in database 43. In this way, by using database 43 when estimating the induced voltage, it is possible to simplify and speed up complex calculation processing.

In particular, it is preferable to store the above-mentioned general formula (1) in the MCU 4. Then, the coefficients Ka, Kb, and Kc are converted into numerical values or the like and converted into data, and the data of these coefficients is stored in the database 43 in the form of a table or the like.

In this way, when estimating the induced voltage, if the current value during the momentary interruption and the coil voltage value during the transient are obtained, the induced voltage can be estimated simply by extracting appropriate digitized coefficients from database 43 and substituting them into general formula (1).

<Example of magnet temperature estimation>
A specific flow of the process for estimating the magnet temperature is illustrated in Fig. 12. The MCU 4 (inverter control unit 41) momentarily interrupts the operation of the motor 2 by controlling the inverter 3. Then, the MCU 4 (magnet temperature estimator 42) acquires the current value at that time, i.e., the current value during the momentary interruption (step S1).

Specifically, the current to the motor 2 is momentarily cut off (instantaneous interruption) by momentarily controlling the switching elements 33U and 33L, which are controlled to be on, to be controlled to be off (see Figure 2). As this is only an instantaneous interruption, it has almost no effect on the torque output by the motor 2. Therefore, the current can be interrupted as necessary regardless of the operating state of the motor 2. The instantaneous interruption may be constant while the motor 2 is operating, or may be at regular intervals for a predetermined period while the motor 2 is operating. Since the induced voltage can be detected not only during deceleration periods of the vehicle but also during acceleration periods, it has excellent responsiveness.

In the case of a vehicle, magnet temperature is often particularly high during acceleration periods. Being able to estimate the magnet temperature at such times is effective in managing the temperature of the magnet 23. Moreover, it can be estimated with high accuracy in a short time. The magnet temperature can be estimated as much as necessary, when necessary. Therefore, appropriate temperature management of the magnet 23 becomes easier than ever before. As a result, the performance of the motor 2 can be fully utilized, thereby reducing fuel and/or battery consumption.

In this case, if the second simplified circuit equation is used as the formula, it is sufficient to carry out the above-mentioned predetermined timing. Also, if the third simplified circuit equation is used as the formula, it is sufficient to obtain the slope of the coil voltage by actually measuring it at the time of the momentary interruption.

When an instantaneous interruption occurs, the MCU 4 acquires the coil voltage at a predetermined timing during the transient period (step S2). Specifically, the MCU 4 (magnet temperature estimator 42) acquires the coil voltage of the energized phase during the instantaneous interruption, i.e., the transient coil voltage value, during the instantaneous interruption period. This can be done at any timing during the transient period.

In this case, if the second simplified circuit equation is used as the formula, it is sufficient to perform this process twice at the specified timing described above. Also, if the third simplified circuit equation is used as the formula, this process is not necessary.

When the MCU4 (magnet temperature estimation unit 42) acquires the current value during an instantaneous interruption and the coil voltage value during a transient, it estimates the induced voltage by using these values in a formula together with the time at which the coil voltage value during a transient was acquired (step S3). The formula to be used can be appropriately selected according to the specifications. It may be a basic circuit equation or a simplified circuit equation. It may also be a formula modified based on these. When the third simplified circuit equation is used as the formula, it is sufficient to use the current value during an instantaneous interruption and the value of the slope of the coil voltage during an instantaneous interruption.

At this time, as described above, it is preferable to convert the part of the formula containing variables into data and store it in the database 43 as much as possible. In this way, when estimating the induced voltage, the magnet temperature estimation unit 42 can use the database 43, thereby reducing the burden of the calculation process and speeding up the calculation process.

After estimating the induced voltage, the MCU4 (magnet temperature estimation unit 42) estimates the magnet temperature based on the correlation between the induced voltage and the magnet temperature (step S4). Data specifying the correlation between the induced voltage and the magnet temperature is obtained in advance by experiments or the like and stored in the database 43. By comparing the estimated induced voltage with that data, the magnet temperature can be easily estimated.

In this way, according to the motor system 1 to which the disclosed technology is applied, a circuit equation is formulated based on an equivalent circuit model of the motor system 1 that represents the behavior during a momentary interruption transient, and the circuit equation or a formula obtained from the circuit equation is used when estimating the induced voltage. As a result, the induced voltage can be detected simply by causing a momentary interruption while the motor 2 is in operation and measuring the current value during the momentary interruption and the coil voltage value during the transient.

This allows for highly accurate estimation of the magnet temperature regardless of the operating state of the motor 2. As a result, proper temperature management of the magnet 23 is facilitated, allowing the motor 2 to perform at its full potential and reducing fuel and/or battery consumption.

=Application example of magnet temperature estimation method=
In the magnet temperature estimation method described above, the current value during an instantaneous interruption and the coil voltage value during a transient are actually measured, and the magnet temperature is estimated based on these values. Such measurements require high sensitivity and high accuracy. Therefore, various noises are superimposed on these actual measurements, as well as on state quantities related to the estimation of the magnet temperature, such as the induced voltage and magnet temperature obtained from these actual measurements. Noise affects the estimation accuracy of the magnet temperature.

It is possible to process (remove) noise using a low-pass filter (LPF), but increasing accuracy comes at the expense of reduced responsiveness. For this reason, ensuring accuracy through noise processing using an LPF requires a certain amount of time. Therefore, when estimating magnet temperature in an extremely short time, it is not possible to achieve both the appropriate responsiveness and accuracy. For this reason, it is not advisable to use an LPF to process noise in magnet temperature estimation due to momentary interruptions.

In particular, when the motor 2 is mounted on a vehicle, there is a wide variety of noise. Depending on the noise, the amplitude of the noise also varies greatly. If the magnet temperature is estimated using a state quantity on which such noise is superimposed, the estimation accuracy may decrease, and it may become impossible to properly manage the temperature of the magnet 23.

In contrast, in this application example, a magnet temperature estimation method is devised that uses an observer or the like to achieve both responsiveness and accuracy while also being able to properly process noise, even when estimating magnet temperature for an extremely short period of time due to a momentary interruption.

<Application Overview>
The block diagram of a conventional observer model is shown in the upper diagram of Figure 13. u is the input, x is the state quantity, and y is the output. A, B, C, and K are matrix elements that configure the observer model, and K is the observer gain. The notation "^" on the characters represents an estimated value. 1/s is an integral element.

The part above the dashed line L1 in the block diagram corresponds to the system to be controlled, and the part below the dashed line L1 corresponds to the simulator (observer) that estimates the state quantity. The difference between the system output y and the simulator output y^ (estimated value), i.e., the estimation error, is multiplied by the observer gain K and fed back (error feedback) to the simulator. This makes it possible to converge the estimation error of the state quantity. The speed of convergence can be adjusted by selecting the observer gain K.

In other words, the larger the observer gain K, the faster the convergence of the estimation error of the state quantity. Therefore, it is preferable to have a large observer gain K, but if the observer gain K is made large, the convergence becomes unstable when there is a lot of noise. Furthermore, if the observer gain K is made too large, divergence will occur. Therefore, the observer gain K needs to be set to an appropriate value taking into account convergence and stability.

Therefore, this time, as shown in the lower diagram of Figure 13, we modified the observer model and created a new observer model (modified observer model) so that the observer gain K can be changed predictively based on the input u. In the magnet temperature estimation method of the application example, this modified observer model is used to estimate the magnet temperature.

<Specific examples of applications>
Fig. 14 shows a schematic configuration of a magnet temperature estimation system 420 to which the magnet temperature estimation method of the applied example is applied. The portion indicated by dashed line L2 in Fig. 14 is the main portion of the magnet temperature estimation system 420, in which a modified observer model is used. The magnet temperature estimation system 420 is made up of a first magnet temperature estimation unit 421, a second magnet temperature estimation unit 422, etc. K is a feedback gain (correction coefficient) equivalent to the observer gain.

The functional components of the magnet temperature estimation system 420 can be implemented as software in the MCU 4 by extending the magnet temperature estimation unit 42 described above.

State quantities related to the estimation of the magnet 23 are input to the motor 2. The state quantities input from the inverter 3 to the motor 2 include at least the current and voltage (more specifically, the phase and power of these). Various noises are superimposed on these state quantities.

The first magnet temperature estimation unit 421 corresponds to the magnet temperature estimation unit 42 described above. The first magnet temperature estimation unit 421 uses such state quantities to execute a process (first magnet temperature estimation process) to estimate the magnet temperature based on the motor 2 (actual machine).

Specifically, like the magnet temperature estimation unit 42, the first magnet temperature estimation unit 421 momentarily interrupts the supply of current to the coil 25 while the motor 2 is in operation, and acquires the current value during the momentary interruption and the coil voltage value during the transient period as state quantities input from the inverter 3 to the motor 2. Then, the induced voltage is estimated using a formula such as the circuit equation described above, and the current value during the momentary interruption and the coil voltage value during the transient period. The magnet temperature is estimated based on the estimated induced voltage.

On the other hand, the second magnet temperature estimation unit 422 executes a process (second magnet temperature estimation process) to estimate the magnet temperature based on a thermal model of the motor 2. The thermal model is a dynamic heat transfer model designed to correspond to the actual motor 2. The thermal model can be designed appropriately according to the specifications of the motor 2.

An example of the thermal model is shown in a simplified form in FIG. 15. P represents a heat source. The heat source is a state quantity (a state quantity that generates heat, such as a current or voltage) input to the motor 2. The unit of the heat source is "W". Cm represents the heat capacity of the magnet 23 in "J/K". Cs represents the heat capacity of the stator 21 in "J/K". Hg and Hc each represent the heat transfer coefficient in "W/K". And Tc represents the temperature of the motor case in "K". Hg corresponds to the gap 24 between the rotor 20 and the stator 21.

Tm is the temperature of the magnet 23 in "K" and Ts is the temperature of the stator 21 in "K". The temperature Tm of the magnet 23 and the temperature Ts of the stator 21 are input to the heat capacity of each of the magnet 23 and the stator 21. Based on this dynamic heat transfer model, the second magnet temperature estimator 422 estimates the magnet temperature.

As shown in FIG. 14, when a state quantity such as current is input from the inverter 3 to the motor 2, in the first magnet temperature estimation process, an induced voltage is estimated by calculation using a circuit equation or the like based on that state quantity, and the magnet temperature is estimated based on that induced voltage. In contrast, in the second magnet temperature estimation process, the magnet temperature is estimated by calculation using a heat transfer model based on that state quantity.

The magnet temperature estimated by the first magnet temperature estimation process is then set as a first estimated value, and the magnet temperature estimated by the second magnet temperature estimation process is set as a second estimated value, and the difference between the first and second estimated values, i.e., the estimation error, is calculated. In accordance with this estimation error, the state quantity used in the second magnet temperature estimation process is corrected by the feedback gain K (error feedback). Note that the first and second estimated values are not limited to magnet temperatures, and may be any comparable estimated values.

Specifically, the estimation error is multiplied by the feedback gain K and then added to the state quantity used in the second magnet temperature estimation process. At this time, if the feedback gain K is of an appropriate magnitude relative to the estimation error, the estimation error will converge quickly. Both convergence and stability can be ensured. As a result, the magnet temperature can be estimated quickly and accurately.

(The effects of noise and its countermeasures)
As described above, the first magnet temperature estimation unit 421 momentarily interrupts the power supply to the coil 25 while the motor 2 is in operation, and acquires the current value during momentary interruption and the coil voltage value during transient as state quantities input from the inverter 3 to the motor 2. These state quantities must be measured with high accuracy in an extremely short period of time, and therefore require highly sensitive measurement.

Moreover, the magnet temperature is estimated while the vehicle is running. As a result, a wide variety of noises are superimposed on the state quantity. If the magnet temperature is estimated using a state quantity on which such a wide variety of noises are superimposed, the accuracy of the first estimated value may decrease due to the influence of the noise. If the accuracy of the first estimated value decreases, the estimation error increases. As a result, the feedback gain K may become excessively large relative to the estimation error, and the error feedback may become inappropriate.

Therefore, in this application example, as described above, the modified observer model is used to estimate the magnet temperature. Specifically, the magnet temperature estimation system 420 predicts the noise superimposed on the state quantity and changes the magnitude of the feedback gain K according to the noise (corresponding to so-called feedforward compensation).

(noise)
Noise that becomes a problem in estimating the magnet temperature can be roughly divided into noise generated by the inverter 3 itself (intrinsic noise) and noise originating from outside the inverter 3 (external noise). Internal noise can be predicted based on the internal noise factors that are its cause. External noise can be predicted based on the external noise factors that are its cause.

The inherent noise factors include power, current, and voltage, among others. Various electronic components are densely packed inside the inverter 3, and large currents flow through it. Therefore, highly sensitive measurements inside the inverter 3 are easily affected by these factors. As the power input and output to and from the inverter 3 increases, the noise also increases accordingly.

Motor power can also be an inherent noise factor. In other words, the greater the output of the motor 2, the greater the power input and output to the inverter 3. Furthermore, since motor power changes according to the accelerator opening of the vehicle, the accelerator opening can also be an inherent noise factor. Noise based on the accelerator opening can be predicted at an earlier timing than noise based on the motor power.

Shift commands to the transmission can also be an inherent noise factor. That is, the torque of the motor 2 may fluctuate when the gear ratio is switched, for example. Torque fluctuations affect the power input and output to the inverter 3. Deterioration of electronic components inside the inverter 3 over time can also be an inherent noise factor. For example, changes in the characteristics of the low-pass filter of the inverter 3 can affect noise.

On the other hand, an example of an external noise factor is the power of electrical equipment installed in the vehicle. For example, the motor system 1 described above is equipped with power units such as a boost converter in addition to the inverter 3. The power input and output to these can also affect noise.

The power of the auxiliary system (a 12V voltage system using a lead-acid battery) can also be an external noise factor. Because the auxiliary system is also electrically connected to the motor system 1, large fluctuations in its power can affect noise. For example, when the power windows are operating, a relatively large amount of power is consumed, which can easily affect noise.

Furthermore, vehicles travel in a variety of environments. Therefore, noise (specific environmental noise) may occur due to a specific environment. For example, a vehicle may travel in an environment with a strong electric field, such as near a radio tower. In such cases, the noise may be affected. Therefore, the specific environment may also be an external noise factor.

From these internal and external noise factors, the noise factors to be predicted are appropriately selected and set in advance in the magnet temperature estimation system 420. The magnet temperature estimation system 420 predicts the noise superimposed on the state quantity based on the set noise factors. The magnet temperature estimation system 420 then changes the feedback gain K according to the noise.

For example, power, current, and voltage are state quantities input from the inverter 3 to the motor 2, and are direct inherent noise factors. If the power, etc., increases, the noise superimposed on them increases accordingly. If the power, etc., decreases, the noise superimposed on them decreases accordingly. In other words, there is a positive correlation between the magnitude of the power, etc. and the magnitude of the noise superimposed on them.

Therefore, in the magnet temperature estimation system 420, as shown in FIG. 14, the feedback gain K is changed when power, etc. is input from the inverter 3 to the motor 2. Specifically, the feedback gain K is changed so that it becomes smaller as the current and/or voltage becomes larger.

Figure 16 shows the correspondence between the feedback gain K and the current and voltage. K1 is the feedback gain corresponding to the current (first feedback gain), and K2 is the feedback gain corresponding to the voltage (second feedback gain). The feedback gain K in this application example is composed of the product of the first feedback gain K1 and the second feedback gain K2.

The first feedback gain K1 is changed so that it becomes smaller as the current increases. The second feedback gain K2 is also changed so that it becomes smaller as the voltage increases. The ratio of the change in the first feedback gain K1 to the change in current, i.e., the slope of graph G1, is set appropriately according to the specifications of the motor system 1. Similarly, the ratio of the change in the second feedback gain K2 to the change in voltage, i.e., the slope of graph G2, is set appropriately according to the specifications of the motor system 1. Note that these graphs G1 and G2 are not limited to straight lines and may be curved lines.

The slopes of graphs G1 and G2 may be the same or different. However, since current is more susceptible to large noise superimposition than voltage, it is preferable that the slope of the graph for current is greater than that for voltage. Data such as a table specifying such a correspondence is stored in database 43 of MCU 4 and is used as necessary when estimating the magnet temperature.

As shown by the solid line L3 in FIG. 14, the feedback gain K is changed predictively based on the state quantity input to the magnet temperature estimation system 420. Therefore, even if noise is superimposed on the state quantity, the feedback gain K can be changed according to the magnitude of the noise before error feedback is performed. This allows the error feedback to be performed appropriately. Even if large noise is superimposed on the state quantity, it is possible to achieve both convergence and stability in an appropriate state. As a result, the magnet temperature can be estimated quickly and accurately.

Even if the noise factor to be predicted is other than power, etc., the approach to noise is the same as for power, etc. In other words, data specifying the correspondence between the noise factor and the noise magnitude is obtained in advance by experiments, etc., and stored in the database 43 of the MCU 4.

Then, when estimating the magnet temperature, the magnet temperature estimation system 420 predicts the noise that will be superimposed on the state quantity based on that data, and changes the magnitude of the feedback gain K in response to that noise, as shown by the two-dot chain line L4 in FIG. 14.

<Specific examples of magnet temperature estimation in application examples>
17 illustrates a process flow for estimating the magnet temperature in the application example. When the vehicle starts to drive and an output of the motor 2 is required, the MCU 4 (inverter control unit 41) controls the inverter 3 to start the operation of the motor 2 (step S10).

When magnet temperature estimation is requested, the MCU4 (magnet temperature estimation system 420) estimates the magnet temperature (step S11). As described above, magnet temperature estimation can be performed regardless of the operating state of the motor 2.

When estimating the magnet temperature, the MCU4 executes a first magnet temperature estimation process and a second magnet temperature estimation process (steps S12 and S13). As described above, the MCU4 also predicts noise superimposed on the power, etc., and determines whether or not the feedback gain K needs to be changed (step S14). It is preferable to perform the processes of steps S12, S13, and S14 simultaneously in parallel.

If it is determined that the feedback gain K needs to be changed, the MCU 4 changes the magnitude of the feedback gain K according to the magnitude of the noise (step S15). At this time, if the magnitude of the feedback gain K is to be changed according to the magnitude of the power, etc., it may be changed according to the magnitude of the power, etc. input to the motor 2, as described above. In this case, the determination of the necessity of the change can be omitted. It is sufficient to change the magnitude of the feedback gain K according to the predicted noise. On the other hand, if the MCU 4 determines that it is not necessary to change the feedback gain K, it proceeds directly to the next step S17.

The MCU4 also acquires an estimation error by executing the first magnet temperature estimation process and the second magnet temperature estimation process (step S16). Then, the MCU4 performs error feedback using the acquired estimation error and feedback gain K, and corrects the state quantity used in the second magnet temperature estimation process (step S17).

By doing so, the estimation error converges stably and quickly, and the magnet temperature is estimated quickly and accurately (step S18). Because the feedback gain K is changed to an appropriate value according to the magnitude of the noise, the magnet temperature can be estimated quickly and accurately even if a large noise is superimposed on the power, etc.

The MCU 4 also compares the estimated magnet temperature with a predetermined threshold value Tm (step S19). The threshold value Tm is a value close to the upper limit of the magnet temperature and is stored in the database 43 of the MCU 4. In other words, the magnet temperature can be estimated quickly and accurately, making it possible to manage the temperature at a value close to the upper limit of the magnet temperature.

As a result, if it is determined that the estimated magnet temperature is greater than the threshold Tm, the MCU 4 limits the amount of current in the inverter 3 (step S20). This suppresses the rise in magnet temperature and prevents the magnet temperature from reaching the upper limit.

In this way, according to the motor system 1 of the application example to which the disclosed technology is applied, in addition to the magnet temperature estimation method based on the momentary interruption described above, noise superimposed on the power, etc. is predicted and appropriately processed, so that the effect of noise on the estimation of the magnet temperature in an extremely short period of time can be suppressed.

This allows for more accurate estimation of the magnet temperature, regardless of the operating state of the motor 2. As a result, it becomes easier to properly manage the temperature of the magnet 23, allowing the motor 2 to perform at its full potential and reducing fuel and/or battery consumption.

<Demonstration test>
A test was conducted to verify the effect of the disclosed technology. In the test, a specified testing machine was used and a telemeter was attached to the motor so that the magnet temperature could be measured.

In the test, the motor was rotated at 1000 rpm, and in that state, short interruptions of several ms were repeated at intervals of ms. Then, for each short interruption, the magnet temperature was estimated using the magnet temperature estimation system 420 described above. Note that since this was a test machine, there was no significant noise that would be a problem. Therefore, the feedback gain K was not changed. An outline of the test results is shown in Figure 18.

The graph of actual measurements shown in FIG. 18 represents the change over time in the actual measured magnet temperature. The graph of estimated values represents the change over time in the estimated magnet temperature estimated by the magnet temperature estimation system 420. These changes over time are measured in seconds.

As these graphs show, there was a tendency for the estimated values to gradually approach the actual measured values. Furthermore, the maximum error in this demonstration test was approximately 5°C. Therefore, it was demonstrated that the use of the disclosed technology makes it possible to estimate the magnet temperature with high accuracy, regardless of the operating state of the motor.

The disclosed technology is not limited to the above-described embodiments, but also includes various other configurations.

For example, in the above-described embodiment, an in-vehicle motor system is illustrated, but the motor systems to which the disclosed technology can be applied are not limited to in-vehicle motor systems.

In the above-described embodiment, multiple simplified circuit equations are shown by applying a specific simplification method to the basic circuit equation, but these are merely examples. By appropriately combining the simplification methods explained with the basic circuit equation, simplified circuit equations other than those shown as examples can be formulated. The simplified circuit equations can be appropriately selected according to the specifications of the motor system. In addition, the exemplified equations themselves do not have to be used. The exemplified equations may be appropriately modified before use.

The intrinsic and extrinsic noise factors listed in the application examples are just examples. Anything that causes noise superimposed on the state quantities related to the estimation of the magnet temperature can be a noise factor.

1 Motor system 2 Motor 3 Inverter 4 Motor control unit (MCU)
Reference Signs List 5 DC power supply 20 Rotor 21 Stator 22 Shaft 23 Magnet 24 Gap 25 Coil 26 Connection cable 30 Power supply cable 31 Inverter circuit 33U, 33L Switching element 34 Diode 41 Inverter control unit 42 Magnet temperature estimation unit 43 Database 420 Magnet temperature estimation system 421 First magnet temperature estimation unit 422 Second magnet temperature estimation unit

Claims (6)

A magnet temperature estimation method for a motor in which magnets constituting magnetic poles are installed in a rotor and rotated by passing AC current formed by controlling switching elements of an inverter through a plurality of coils of a stator, comprising the steps of:
the coils constitute three coil groups consisting of a U-phase, a V-phase, and a W-phase, and the inverter is configured to control power supplied from a DC power source to each of the coil groups to pass AC currents of different phases;
During operation of the motor, the switching element is turned off to momentarily cut off current to the coil;
Acquire an instantaneous interruption current value, which is a current value at the time of the instantaneous interruption, and a transient coil voltage value, which is a voltage value of the coil at the time of the instantaneous interruption transient,
Calculating an induced voltage using a predetermined formula established based on a voltage change in the coil after the instantaneous interruption, the instantaneous interruption current value, and the transient coil voltage value;
Estimating a temperature of the magnet based on the calculated induced voltage ;
A magnet temperature estimation method using the following formula as the formula :

Here, V _emf is induced voltage, V _f is forward voltage of the diode connected inversely parallel to the switching element, V is voltage of the DC power supply, L is inductance, i is current, the subscripts P ₁ , P ₂ , P ₃ are indications identifying the phases U, V, and W, ω is angular velocity of rotation, φ is phase of the current at the time of momentary interruption of the phase corresponding to P ₁ , R is internal resistance of the DC power supply, R _l is resistance of the switching element at the time of momentary interruption, and t is time elapsed after momentary interruption. A magnet temperature estimation method for a motor in which magnets constituting magnetic poles are installed in a rotor and rotated by passing AC current formed by controlling switching elements of an inverter through a plurality of coils of a stator, comprising the steps of:
During operation of the motor, the switching element is turned off to momentarily cut off current to the coil;
Acquire an instantaneous interruption current value, which is a current value at the time of the instantaneous interruption, and a transient coil voltage value, which is a voltage value of the coil at the time of the instantaneous interruption transient,
Calculating an induced voltage using a predetermined formula established based on a voltage change in the coil after the instantaneous interruption, the instantaneous interruption current value, and the transient coil voltage value;
Estimating a temperature of the magnet based on the calculated induced voltage;
A magnet temperature estimation method comprising: formulating a simplified formula based on an equivalent circuit model that does not take into account a leakage current flowing through the switching element when the switching element is controlled to be off; and calculating an induced voltage using the simplified formula . A magnet temperature estimation method for a motor in which magnets constituting magnetic poles are installed in a rotor and rotated by passing AC current formed by controlling switching elements of an inverter through a plurality of coils of a stator, comprising the steps of:
During operation of the motor, the switching element is turned off to momentarily cut off current to the coil;
Acquire an instantaneous interruption current value, which is a current value at the time of the instantaneous interruption, and a transient coil voltage value, which is a voltage value of the coil at the time of the instantaneous interruption transient,
Calculating an induced voltage using a predetermined formula formulated based on a voltage change in the coil after the instantaneous interruption, the instantaneous interruption current value, and the transient coil voltage value;
Estimating a temperature of the magnet based on the calculated induced voltage;
The current is interrupted at the timing when the phase of the current becomes 90°.
The two transient coil voltage values are obtained at a timing when ωt=nπ (ω is the rotational angular velocity, t is the elapsed time after the instantaneous interruption, and n is a natural number),
A magnet temperature estimation method comprising: formulating a simplified equation by calculating a difference between the two transient coil voltage values in the equation; and calculating an induced voltage using the simplified equation . 2. The magnet temperature estimation method according to claim 1,
A magnet temperature estimation method using the following formula as the formula.

V _emf = Ka・V _P (t)+Kb・I ₀ +Kc

Here, V _P (t) is the coil voltage value during a transient state, I ₀ is the current value during an instantaneous interruption, and Ka, Kb, and Kc are predetermined coefficients including variables. 5. The magnet temperature estimation method according to claim 4,
The predetermined coefficients Ka, Kb, and Kc are converted into data and stored in a database;
A magnet temperature estimation method, comprising: calculating an induced voltage using the database. The magnet temperature estimation method according to claim 1 or 4,
A magnet temperature estimation method in which a constant value L is used as the inductances Lu, Lv, and Lw of the coils of each phase.

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