JP2019208352A - Electric motor drive control device and method, and electric motor drive control system - Google Patents

Abstract

To provide an electric motor drive control device and method that can estimate load torque with a smaller amount of information processing and can control an electric motor with model predictive control, and an electric motor drive control system.SOLUTION: An electric motor drive control device according to the present invention that controls an electric motor M driven by the output of an inverter circuit obtains the rotational speed of the electric motor M as a current rotational speed value, estimates the load torque acting on the electric motor M, and controls the electric motor M by model predictive control on the basis of the estimated load torque. When the load torque is estimated, the electric motor drive control device of the present invention estimates the load torque on the basis of the current predicted rotational speed value predicted in the past.SELECTED DRAWING: Figure 1

Description

  The present invention relates to an electric motor drive control device and an electric motor drive control method for controlling driving of an electric motor. And this invention relates to an electric motor drive control system provided with the said electric motor drive control apparatus.

  For the drive control of the electric motor, for example, feedback control using PI control is often used. In the speed control, since the responsiveness to the target speed affects the performance of the product using the electric motor, its height is required. In the feedback control, responsiveness can be improved by setting a large feedback gain, but there is a possibility that so-called overshoot or hunting may occur.

  For this reason, model responsive control (MPC) has been proposed for motor drive control (see, for example, Patent Document 1 and Patent Document 2) because higher responsiveness can be realized compared to the conventional feedback control. ). In this model predictive control, the electric motor is driven and controlled by repeatedly executing the following series of processes for each control cycle. In the series of processes, first, a future behavior of the motor is predicted for each of a plurality of candidate input voltages by using a model of the motor. Next, each prediction result (each behavior of the motor) is evaluated, a prediction result closest to the target is selected, and the motor is driven and controlled with a candidate input voltage that gives this selected prediction result. In such model predictive control, the candidate input voltage optimized based on the prediction result can be determined, so that high responsiveness exceeding the conventional feedback control can be expected.

  When speed control is performed using model predictive control, prediction is necessary as described above. In the case of an electric motor, not only the characteristic parameters of the motor itself but also information on load torque acting on the motor from the outside is necessary. . However, the load torque is generally unknown and difficult to predict in advance. Therefore, for example, there is a technique disclosed in Non-Patent Document 1. In the technique disclosed in Non-Patent Document 1 for controlling the speed of a motor by model predictive control, a load torque is estimated using a Kalman filter.

JP 2008-228419 A JP2013-62949A

Esteban Fuentes, et. al, “Cascade-Free Predictive Speed Control for Electrical Drives”, IEEE TRANSACTION ON INDUSTRIAL ELECTRONICS, Vol. 61, no. 5, MAY 2014

  The technique disclosed in Non-Patent Document 1 can control the speed of a motor by model predictive control by estimating a load torque using a Kalman filter. However, in model predictive control, most of the calculation resources are occupied by the information processing of the prediction, and it is difficult to allocate the calculation resources to other information processing such as estimation of load torque. By using, for example, an FPGA (Field Programmable Gate Array) having a relatively high arithmetic processing capability, load torque estimation in the technique disclosed in Non-Patent Document 1 is possible during execution of speed control in model predictive control. Can be expensive. If the technology disclosed in Non-Patent Document 1 is used using an information processing apparatus with relatively low arithmetic processing capacity due to cost constraints, it is difficult to control the speed in real time.

  The present invention has been made in view of the above-described circumstances, and an object of the present invention is to provide a motor drive control device and a motor drive control capable of estimating a load torque with a smaller amount of information processing and driving and controlling the motor by model predictive control. And a motor drive control system comprising the method and the motor drive control device.

  As a result of various studies, the present inventor has found that the above object is achieved by the present invention described below. That is, an electric motor drive control device according to one aspect of the present invention is an electric motor drive control device that controls an electric motor driven by an output of an inverter circuit, and a load torque estimation unit that estimates a load torque acting on the electric motor, A voltage pattern generation unit that generates a plurality of time-series voltage patterns that can be output by the inverter circuit to be different from each other, and the load torque for each of the plurality of time-series voltage patterns generated by the voltage pattern generation unit. Speed prediction for predicting the rotation speed of the motor as a rotation speed prediction value when the load torque estimated by the estimation unit is applied to the motor and the time-series voltage pattern is input to the motor And the speed prediction unit predicts from a plurality of time-series voltage patterns generated by the voltage pattern generation unit. A voltage pattern selection unit that selects a time-series voltage pattern corresponding to the highest estimated rotation speed value among the estimated rotation speed values of the electric motor, and a time-series voltage selected by the voltage pattern selection unit. An inverter control unit that controls the inverter circuit based on a voltage pattern, and the load torque estimation unit estimates the load torque based on a current predicted rotational speed value predicted in the past by the speed prediction unit. To do. Preferably, the electric motor drive control device is an electric motor drive control device that controls an electric motor driven by an output of an inverter circuit, and a speed output unit that performs a speed output process for obtaining a rotation speed of the motor as a rotation speed current value A load torque estimation unit that performs a load torque estimation process that estimates a load torque that acts on the motor, and a voltage pattern generation process that generates a plurality of time-series voltage patterns that can be output by the inverter circuit so as to be different from each other And a load torque estimated by the load torque estimating unit for each of a plurality of time-series voltage patterns generated by the voltage pattern generating unit, The rotation speed of the motor when the time-series voltage pattern is input to the motor A speed prediction unit that performs a speed prediction process that predicts a value, and each rotational speed prediction of the motor predicted by the speed prediction unit from among a plurality of time-series voltage patterns generated by the voltage pattern generation unit A voltage pattern selection unit for performing a voltage pattern selection process for selecting a time-series voltage pattern corresponding to the highest estimated rotational speed value among the values, and a time-series voltage pattern selected by the voltage pattern selection unit An inverter control unit for performing an inverter control process for controlling the inverter circuit, the speed output process, the load torque estimation process, the voltage pattern generation process, the speed prediction process, the voltage pattern selection process, and the inverter The control process includes the speed output unit, the load torque estimation unit, the voltage pattern generation unit, the speed prediction unit, and the voltage. The turn selection unit and the inverter control unit are repeatedly implemented with a predetermined control cycle, and the load torque estimation unit sets the current rotational speed prediction value predicted in the past by the speed prediction unit. Based on this, the load torque is estimated.

  Since such an electric motor drive control device uses the current predicted rotational speed value predicted in the past for estimating the load torque, the load torque can be estimated with a smaller amount of information processing than when a conventional Kalman filter is used. The motor can be driven and controlled by model predictive control even under use conditions where load torque is applied. For this reason, even when model predictive control is realized by an inexpensive arithmetic processing device having a relatively low arithmetic processing capability, the motor drive control device can drive and control the motor in substantially real time.

  In another aspect, the motor drive control device described above further includes a speed output unit that obtains the rotation speed of the motor as a rotation speed current value, and the load torque estimation unit is predicted in the past by the speed prediction unit. The load torque is estimated by integrating a difference multiplication value obtained by multiplying the difference between the current predicted rotational speed value and the current rotational speed value obtained by the speed output unit by a predetermined coefficient for each control period.

  Such an electric motor drive control device uses a difference multiplication value obtained by multiplying a difference between a current rotation speed predicted value predicted in the past by the speed prediction unit and a rotation speed current value obtained by the speed output unit by a predetermined coefficient. Since the load torque is estimated by integrating every control cycle, the load torque can be easily estimated with a smaller amount of information processing, and the drive of the motor can be controlled by model predictive control.

  In another aspect, in the above-described electric motor drive control device, the predetermined coefficient is set within a range in which a transfer function that receives the load torque and outputs an estimation error of the speed prediction unit satisfies stability. And a coefficient setting unit.

  Such an electric motor drive control device can appropriately set the coefficient so that the control system is stabilized. For this reason, it is possible to avoid in advance oscillation and instability caused by driving with an inappropriate coefficient.

  In another aspect, in the above-described electric motor drive control device, the voltage pattern selection unit performs the evaluation by using an evaluation function including the rotation speed of the control target, and determines the future based on the past actual value. A control target prediction unit that predicts the rotation speed of the control target is further provided. Preferably, in the above-described electric motor drive control device, the control target prediction unit predicts a rotational speed of a future control target based on an amount of change in the previous actual value. In another aspect, in the above-described electric motor drive control device, the control target prediction unit predicts the rotational speed of the future control target by extrapolating the actual value before the present.

  Since such an electric motor drive control device further includes a control target prediction unit, even when the rotation speed of the control target changes, it can be controlled more appropriately.

  An electric motor drive control method according to another aspect of the present invention is an electric motor drive control method for controlling an electric motor driven by an output of an inverter circuit, and a load torque estimation step for estimating a load torque acting on the electric motor, A voltage pattern generation step for generating a plurality of time-series voltage patterns that can be output by the inverter circuit so as to be different from each other, and the load torque for each of the plurality of time-series voltage patterns generated in the voltage pattern generation step Speed prediction for predicting the rotation speed of the motor as a rotation speed prediction value when the load torque estimated in the estimation step is applied to the motor and the time-series voltage pattern is input to the motor And the speed prediction process from a plurality of time-series voltage patterns generated in the voltage pattern generation step. A voltage pattern selection step for selecting a time-series voltage pattern corresponding to the highest estimated rotational speed value among the predicted rotational speed values of the electric motor predicted in step (i), and when selected in the voltage pattern selection step. An inverter control step of controlling the inverter circuit based on a series of voltage patterns, wherein the load torque estimation step includes the load torque based on a current predicted rotational speed value predicted in the past in the speed prediction step. Is estimated.

  Such an electric motor drive control method uses the current predicted rotational speed predicted in the past for the estimation of the load torque, so that the load torque can be estimated with a smaller amount of information processing than when a conventional Kalman filter is used. The motor can be driven and controlled by model predictive control even under use conditions where load torque is applied. For this reason, even when model predictive control is realized with an inexpensive arithmetic processing device having a relatively low arithmetic processing capability, the motor drive control method can drive and control the motor in substantially real time.

  An electric motor drive control system according to another aspect of the present invention includes an electric motor, an inverter circuit that drives the electric motor, and an electric motor drive control unit that controls the electric motor by controlling the inverter circuit. The drive control unit is any one of the above-described electric motor drive control devices.

  According to this, the electric motor drive control system provided with either of the above-mentioned electric motor drive control devices can be provided. Since such an electric motor drive control system includes any of the above-described electric motor drive control devices, the load torque can be estimated with a smaller amount of information processing, and the electric motor can be driven and controlled by model predictive control.

  The motor drive control device and the motor drive control method according to the present invention can estimate the load torque with a smaller amount of information processing, and can drive and control the motor by model predictive control. And according to this invention, the motor drive control system provided with this motor drive control apparatus can be provided.

It is a block diagram which shows the structure of the electric motor drive control system in embodiment. It is a block diagram which shows the structure of the MPC control part in the said motor drive control system. It is a circuit diagram which shows the structure of the inverter circuit in the said motor drive control system. It is a block diagram which shows the structure of the load torque estimation part in the said motor drive control system. It is a vector diagram which shows the voltage which can be output with the said inverter circuit. It is a figure for demonstrating an example of the time-sequential voltage pattern which can be output with the said inverter circuit. It is a figure for demonstrating the step response of the transfer function which uses load torque as an input and outputs the estimation error of rotation speed prediction. It is a flowchart which shows the operation | movement in the said motor drive control system. It is a flowchart for calculating | requiring the gain for adjusting the update amount of load torque. It is a figure which shows the simulation result of speed control. It is a figure for demonstrating the 1st modification of the said motor drive control system.

  Hereinafter, one or more embodiments of the present invention will be described with reference to the drawings. However, the scope of the invention is not limited to the disclosed embodiments. In addition, the structure which attached | subjected the same code | symbol in each figure shows that it is the same structure, The description is abbreviate | omitted suitably. In this specification, when referring generically, it shows with the reference symbol which abbreviate | omitted the suffix, and when referring to an individual structure, it shows with the reference symbol which attached the suffix.

  FIG. 1 is a block diagram illustrating a configuration of an electric motor drive control system in the embodiment. FIG. 2 is a block diagram showing a configuration of an MPC control unit in the electric motor drive control system. FIG. 3 is a circuit diagram showing a configuration of an inverter circuit in the electric motor drive control system. FIG. 4 is a block diagram showing a configuration of a load torque estimating unit in the electric motor drive control system. FIG. 5 is a vector diagram showing voltages that can be output by the inverter circuit. FIG. 6 is a diagram for explaining an example of a time-series voltage pattern that can be output by the inverter circuit. FIG. 7 is a diagram for explaining the step response of the transfer function having the load torque as an input and the rotation speed prediction estimation error as an output. The horizontal axis in FIG. 7 is the elapsed time, and the vertical axis is the estimation error of the rotational speed.

  The motor drive control system in the embodiment is a system that drives while controlling the motor, and includes a motor drive control device that controls the motor driven by the output of the inverter circuit. In the present embodiment, the motor drive control system S drives the motor while controlling it by vector control using model predictive control. For example, as shown in FIG. 1, such an electric motor drive control system S includes an electric motor M, an inverter circuit IV, a model prediction control unit MC, a three-phase two-phase conversion unit CV, and a load torque estimation unit TE. The rotation speed processing unit RSC, the current measurement unit CS, and the rotation angle measurement unit VS are provided.

  The electric motor M is an electric motor connected to the inverter circuit IV and driven by the AC output of the inverter circuit IV. For example, the motor M is a synchronous motor driven by a three-phase alternating current of U phase, V phase and W phase output from the inverter circuit IV. More specifically, in this embodiment, a permanent magnet type synchronous motor (permanent) is used. magnet synchronous motor (PMSM). The electric motor M is not limited to this, and may be other types such as an induction motor (IM) or an SR motor (Switched Reluctance motor, SRM).

  The inverter circuit IV is a circuit that is connected to the model prediction control unit MC and converts the DC power of the DC power supply Vdc into AC power having a predetermined frequency in accordance with the control of the model prediction control unit MC. For example, as shown in FIG. 3, the inverter circuit IV includes two switching elements Tr connected in series as one set, and three sets Tr1, Tr4; Tr2, Tr5; Tr3, Tr6 connected in parallel to each other. Prepare. More specifically, the inverter circuit IV includes six first to sixth switching Tr1 to Tr6. The first to sixth switching elements Tr1 to Tr6 are power semiconductor elements having a switching function for turning on and off, such as an insulated gate bipolar transistor (IGBT). Each one terminal (for example, each collector terminal) of the first to third switching elements Tr1 to Tr3 is connected to one terminal of the DC power supply Vdc. The other terminal (for example, an emitter terminal) of the first switching element Tr1 is connected to one terminal (for example, each collector terminal) of the fourth switching element Tr4. The other terminal (eg, emitter terminal) of the second switching element Tr2 is connected to one terminal (eg, each collector terminal) of the fifth switching element Tr5. The other terminal (eg, emitter terminal) of the third switching element Tr3 is connected to one terminal (eg, each collector terminal) of the sixth switching element Tr6. Each other terminal (for example, each emitter terminal) of the fourth to sixth switching elements Tr4 to Tr6 is connected to the other terminal of the DC power supply Vdc. In each of the first to sixth switching elements Tr1 to Tr6, each control terminal (for example, a gate terminal) to which a control signal for turning on / off the switching element Tr is input is connected to the model prediction control unit MC. In each of the first to sixth switching elements Tr1 to Tr6, diodes D1 to D6 each having an anode terminal connected to the other terminal are connected between the one terminal and the other terminal. And the 1st connection point which connects 1st switching element Tr1 and 4th switching element Tr4 outputs the alternating current of U phase, for example, and is connected to the input terminal which connects the U phase of the motor M. A second connection point that connects the second switching element Tr2 and the fifth switching element Tr5 is connected to an input terminal that outputs, for example, a V-phase alternating current and connects the V-phase of the electric motor M. A third connection point connecting the third switching element Tr3 and the sixth switching element Tr6 is connected to an input terminal that outputs, for example, a W-phase AC current and connects the W-phase of the electric motor M. The inverter circuit IV having such a configuration is a so-called two-level three-phase inverter circuit, in which one switching element Tr1, Tr2, Tr3 and the other switching element Tr4, Tr5, Tr6 of each set are opposite to each other. (The mode in which the other is off when one is on and the other is on when one is off) is controlled according to the control of the model predictive control unit MC, and the U phase, V phase, and W phase The three-phase alternating current is output to the motor M.

  The current measurement unit CS is connected to the three-phase / two-phase conversion unit CV and measures each of the current flowing from the inverter circuit IV to the motor M, in this embodiment, the U-phase current, the V-phase current, and the W-phase current. It is a device that outputs measurement results to the three-phase to two-phase converter CV. The current measuring unit CS is configured with, for example, an AC ammeter.

  The rotation angle measurement unit VS is connected to each of the three-phase two-phase conversion unit CV and the rotation speed processing unit RSC, measures the magnetic pole position in the electric motor M by angle, and the measurement result (rotation angle) is the three-phase two-phase conversion unit. It is a device that outputs to each of the CV and the rotation speed processing unit RSC. The rotation angle measurement unit VS includes, for example, a rotary encoder (pulse generator), a Hall IC, and the like. In the case of sensorless, the rotation angle measurement unit VS may obtain the rotation angle of the electric motor M from the current and voltage using a model of the electric motor M.

The three-phase / two-phase conversion unit CV is connected to the model prediction control unit MC and is input from the measurement result (U-phase current, V-phase current and W-phase current) input from the current measurement unit CS and the rotation angle measurement unit VS. From the measured result (rotation angle), excitation current (d-axis current) _id and torque component current (q-axis current) i _q are obtained by so-called Clarke conversion and Park conversion, and the obtained d The shaft current _id and the q-axis current _iq are output to the model prediction control unit MC.

The rotation speed processing unit RSC is connected to each of the model prediction control unit MC and the load torque estimation unit TE, and obtains the rotation speed ω _m of the electric motor M from the measurement result (rotation angle) input from the rotation angle measurement unit VS. The obtained rotation speed ω _m is output as the rotation speed current value ω _{m to each} of the model prediction control unit MC and the load torque estimation unit TE. That is, the rotation speed processing unit RSC obtains the rotation speed ω _m of the electric motor M from the measurement result (rotation angle) input from the rotation angle measurement unit VS, and uses the obtained rotation speed ω _m as the current rotation speed value ω _m. As described above, a speed output process for outputting to the model prediction control unit MC and the load torque estimation unit TE is performed. For example, the rotational speed ω _m is obtained by time-differentiating the rotational angle θ _e measured by the rotational angle measurement unit VS and multiplying by the reciprocal number of the pole pair number p of the electric motor M.

  The load torque estimation unit TE is connected to the model prediction control unit MC and estimates the load torque acting on the motor M. That is, the load torque estimation unit TE performs a load torque estimation process for estimating the load torque acting on the electric motor M. In model predictive control, due to its nature, the current rotational speed of the motor M is predicted in the past. The predicted value of the rotational speed is derived based on a voltage equation and a motion equation in which a load torque is applied to the electric motor M. Here, if there is an error between the predicted predicted rotational speed value and the actual measured rotational speed value, ignoring the error included in the model of the motor M, there is the rotational speed. It is considered that the estimated value of the load torque used for the prediction includes an error. From this idea, in this embodiment, the load torque estimation unit TE estimates the load torque based on the current predicted rotational speed value predicted in the past by the speed prediction unit 13 described later in the model prediction control unit MC. More specifically, the load torque estimating unit TE calculates the current rotational speed predicted value predicted in the past by the speed predicting unit 13 and the current rotational speed value obtained from the rotational angle measured by the rotational angle measuring unit VS. The load torque is estimated by integrating a difference multiplication value obtained by multiplying the difference by a predetermined coefficient set every control cycle.

That is, when the model predictive control unit MC repeatedly controls the electric motor M via the inverter circuit IV at a predetermined control period set in advance, the estimated load torque value in the k-th control is set to the upper (^) T ₁ (k) with an added value, J is the moment of inertia of the motor M, the predicted rotational speed in the kth control (current) is ω (k) with a hat (^), and the kth control the rotational speed present value of (current) and omega (k), the control period (time interval of the iterative learning control in the model predictive control) and T _s, as the predetermined coefficient, for adjusting the gain (amount of updated load torque When the update amount adjustment gain) is K, the estimated load torque is expressed by the following equation 1.

  More specifically, in the present embodiment, the load torque estimation unit TE calculates the subtraction unit 31, the low-pass filter unit 32, the parameter calculation unit 33, the gain from the above formula 1, for example, as shown in FIG. 4. And an arithmetic unit 34.

  The subtraction unit 31 is connected to each of the rotation speed processing unit RSC and the model prediction control unit MC, and the current rotation speed prediction obtained by the speed prediction unit 13 of the model prediction control unit MC in the past, for example, one time before the control cycle. The difference between the value (ω (k) with a hat (^) above) and the current rotational speed current value ω (k) obtained by the rotational speed processing unit RSC is obtained, and this obtained difference is obtained as a low-pass filter unit 32. To output.

The low-pass filter unit 32 removes a high-frequency component included in the difference output from the subtracting unit 31, for example, due to noise or the like, and outputs the difference obtained by removing the high-frequency component to the parameter calculation unit 33. . The low-pass filter unit 32 includes, for example, a secondary digital low-pass filter F (z) represented by the following expression 2. Here, a ₀ , a ₁ , a ₂ , b ₀ , b ₁ , and b ₂ are filter coefficients, and are appropriately set according to the specifications of the low-pass filter unit 32. The digital low-pass filter F (z) is not limited to the second order, and may be the first order or the third order or more. Further, when the high-frequency component included in the difference can be ignored, the low-pass filter unit 32 may be omitted.

The parameter calculation unit 33 multiplies the output (the difference obtained by removing the high-frequency component) of the low-pass filter unit 32 by the parameter (−J / T _s ) in Equation 1, and outputs the multiplication result to the gain calculation unit 34. Is.

The gain calculation unit 34 is connected to the model prediction control unit MC, and multiplies the output of the parameter calculation unit 33 (the difference obtained by multiplying the parameter (−J / T _s )) by the gain K of the load torque. Is output to the model prediction control unit MC.

This gain K must be set appropriately so that a vibration component is not generated in the difference between the predicted rotational speed value and the current rotational speed value, and the predicted rotational speed value does not diverge. For this reason, in the present embodiment, for example, the gain K as the predetermined coefficient is set within a range in which the transfer function that receives the load torque and outputs the estimation error of the speed prediction unit 13 satisfies the stability. Is done. More specifically, the predicted rotational speed value and the current rotational speed value follow Formula 3 and Formula 4, respectively. Here, B is a friction coefficient of the rotating body in the electric motor M, T _e (k) is an actual output torque in the electric motor M, and T _l (k) is an actual load torque acting on the electric motor M. Yes, T _e (k) with a hat (^) is an estimate of the actual output torque in the motor M, and T _l (k) with a hat (^) is an actual value that acts on the motor M. ΔT _l (k) is a load torque update amount for incrementing (or decrementing) the load torque estimated value for each control period, that is, k-th control, (k− 1) The difference added to the estimated load torque value in the first control, and is expressed by the following equation 5. Note that ω (k | k-1) with a hat (^) on the top is a predicted rotational speed value in the kth control (present) obtained in the (k-1) th control (past).

  By calculating the update amount based on the difference between the current predicted rotational speed value predicted in the past and the current rotational speed value, which is obtained by the current control, from Equation 5, the load torque is obtained by integrating each control cycle. It is estimated.

  From these equations 1 to 5, the transfer function H (z) is expressed by the following equation 6.

From this equation 6, it can be seen that the gain K contributes to the response characteristic between the load torque and the rotational speed estimation error. FIG. 7 shows the transition of the rotational speed estimation error in the model predictive control by updating the load torque estimated value with the update amount based on Expression 5 when the load torque is applied. The step response transient characteristics differ depending on the magnitude of the gain K. For the transfer function H of the formula 6 (z) is stable at all poles p _i of the transfer function H of the formula 6 (z), it is necessary to the size of 1 within is there. That is, p _i = c _i + d _i (the number of poles i = 1, 2, 3, 4 in Equation 6) and | c _i + jd _i | <1. Here, j is an imaginary unit (j ² = −1). Such a gain K may be obtained in advance by the user and set in the gain calculating unit 34 of the load torque estimating unit TE. Alternatively, the load torque estimating unit TE receives the load torque and inputs the load predicting unit TE. The transfer function that outputs the estimation error may further include a coefficient setting unit (not shown) that sets the predetermined coefficient within a range that satisfies the stability, and may be obtained by the coefficient setting unit according to a flowchart described later.

  The model prediction control unit MC performs drive control of the electric motor M via the inverter circuit IV by vector control using model prediction control. More specifically, the model prediction control unit MC includes, for example, as shown in FIG. 2, a control unit 11, a voltage pattern generation unit 12, a speed prediction unit 13, a voltage pattern selection unit 14, and an inverter control unit. 15.

  The control unit 11 controls each part of the motor drive control system S according to the function of each part, and controls the entire motor drive control system S.

The voltage pattern generation unit 12 generates a plurality of time-series voltage patterns that can be output by the inverter circuit IV so as to be different from each other. That is, the voltage pattern generation unit 12 performs a voltage pattern generation process for generating a plurality of time-series voltage patterns that can be output by the inverter circuit IV so as to be different from each other. The inverter circuit IV is, in this embodiment, as described above, since a two-level three-phase inverter, in accordance with the switching mode of the first to sixth switching elements Tr1 to Tr6, as shown in FIG. 5, 2 ³ = 8 kinds of voltages can be output. The voltage vector V ₀ is not supplied to the motor M when the first to third switching elements Tr1 to Tr3 are off and the fourth to sixth switching elements Tr4 to Tr6 are on (V ₀ = (0 , 0, 0)). Voltage vector _{V 7} are the fourth to sixth switching element Tr4~Tr6 first to third switching elements Tr1~Tr3 is an ON is off, if not fed to the motor M _(V 7 = _(0,0 , 0)). The time-series voltage pattern is determined by a predicted horizon that is the number of control cycles to be predicted and a control horizon that is the number of control cycles in which the voltage that is the control input is variable. For this reason, the prediction value of the prediction horizon and the numerical value of the control horizon are set in advance appropriately in the model prediction control unit MC according to the specification of the model prediction control and the like, and the voltage pattern generation unit 12 outputs the voltage from the inverter circuit IV. A plurality of different time-series voltage patterns are generated according to the possible voltages (eight in the above description), the predicted horizon value, and the control horizon value. In FIG. 6, as an example, all time-series voltage patterns that can be output by the inverter circuit IV when the predicted horizon is 2 and the control horizon is 1 are shown in a tree diagram. In FIG. 6, since the predicted horizon is 2 with respect to the voltage in the current Nth control, the voltage in the next (N + 1) th control and the voltage in the next (N + 2) th control are predicted. Since the control horizon is 1, all time-series voltage patterns that can be output by the inverter circuit IV are eight voltages V in the next (N + 1) th control from the voltage in the current Nth control. branches to ₀ ~V _8, further in the following (N + 2) th control, from the voltage _V 0 ~V _8, is a time-series voltage pattern of eight pairs which are respectively maintained at the voltage _V 0 ~V ₈ . As another example, when the predicted horizon is 2 and the control horizon is 2, the predicted horizon is 2 with respect to the voltage in the current N-th control, so in the next (N + 1) -th control. Since the voltage and the voltage in the next (N + 2) th control are predicted and the control horizon is 2, all time-series voltage patterns that can be output by the inverter circuit IV are the (N + 1) th control and Each of the (N + 2) -th control branches into ₈ different voltages V _{0 to} V ₈ , and is a 64 time series voltage pattern.

The speed prediction unit 13 is a case where the load torque estimated by the load torque estimation unit TE is acting on the electric motor M for each of a plurality of time-series voltage patterns generated by the voltage pattern generation unit 12, and at that time When the series voltage pattern is input to the motor M, the rotational speed of the motor M is predicted as the predicted rotational speed value. That is, the speed prediction unit 13 is a case where the load torque estimated by the load torque estimation unit TE is acting on the electric motor M for each of a plurality of time-series voltage patterns generated by the voltage pattern generation unit 12. A speed prediction process for predicting the rotation speed of the motor M as a rotation speed prediction value when the time-series voltage pattern is input to the motor M is performed. More specifically, the speed prediction unit 13 obtains the d-axis current i _d by the following expression 7 and obtains the q-axis current i _q by the following expression 8. Then, the speed estimation unit 13 obtains the output torque T _e of the motor M by the following equation 9, obtains the rotational speed prediction value according to the following equation 10 (hat above (^) with a omega _m). Here, i _d (k) is a d-axis current in the k-th control, i _q (k) is a q-axis current in the k-th control, L _d is a d-axis inductance, and L _q is a q-axis inductance. In the present embodiment, since the motor M is a permanent magnet type synchronous motor, L _d = L _q = L. R is the winding resistance of the motor M, ω _e (k) is the electrical angular velocity of the motor M in the k-th control, and v _d (k) is the d-axis voltage in the k-th control, v _q (k) is a q-axis voltage in the k-th control, ψ is a linkage magnetic flux of a permanent magnet in the electric motor M, and D is a dynamic frictional resistance of a rotor in the electric motor M.

In the above example, since the predicted horizon is 2, the speed prediction unit 13 for each of the eight sets of time-series voltage patterns, on the dq axis, up to two control cycles ahead for the current k-th control. The current predicted value [i _dq (k + 1), i _dq (k + 2)] and the rotational speed predicted value [ω (k + 1) with a hat (^) on top and ω (k + 2) with a hat (^) on top] are obtained. . The current vector i _dq (k) is [ _id (k), i _q (k)] ^T (i _dq (k) = [ _id (k), i _q (k)] ^T ).

The voltage pattern selection unit 14 has the highest evaluation among the predicted rotational speed values of the electric motor M predicted by the speed prediction unit 13 among the plurality of time-series voltage patterns generated by the voltage pattern generation unit 12. A time-series voltage pattern corresponding to the predicted rotation speed value is selected. That is, the voltage pattern selection unit 14 is the highest among the predicted rotational speed values of the electric motor M predicted by the speed prediction unit 13 from among the plurality of time-series voltage patterns generated by the voltage pattern generation unit 12. A voltage pattern selection process for selecting a time-series voltage pattern corresponding to the estimated rotational speed predicted value is performed. More specifically, the voltage pattern selection unit 14 predicts the current predicted value and the rotation speed prediction of the motor M predicted by the speed prediction unit 13 for each of a plurality of time-series voltage patterns generated by the voltage pattern generation unit 12. For example, the time series voltage pattern is quantitatively evaluated by using the value in the evaluation formula g of the following formula 11, and the highest estimated current predicted value and rotation speed are selected from the plurality of time series voltage patterns. A time-series voltage pattern corresponding to the predicted value is selected. In the evaluation formula g of Formula 11, the smaller the evaluation value, the higher the evaluation. Therefore, a time series voltage pattern corresponding to the current prediction value and the rotation speed prediction value giving the smallest evaluation value is selected as the optimum time series voltage pattern from the plurality of time series voltage patterns. It should be noted that the rotational speed ω _m ^{* of the} control target is input and set to the model predictive control unit MC from the outside.

Since the evaluation formula g of the above formula 11 is important for speed control, the speed deviation is the first term, and in the case of a permanent magnet type synchronous motor, it contributes to the generation of torque in order to prevent wasteful power feeding. since it is possible to hold the non d-axis current i _d to 0 is important, and is configured by a current deviation as a second term, linearly combining these first and second terms coefficients a, with b . Accordingly, the coefficients a and b are appropriately determined in advance according to the relative importance of the first term and the second term. In other words, the relative importance of the first and second terms can be adjusted by the coefficients a and b. That is, in the control of the motor M, when the speed deviation is relatively more important than the current deviation, the value obtained by multiplying the first term and the coefficient a in the evaluation formula g is multiplied by the second term and the coefficient b. If the coefficient a and the coefficient b are set so as to be sufficiently larger than the values, and the current deviation is relatively more important than the speed deviation in the control of the electric motor M, the second in the evaluation formula g The coefficient a and the coefficient b are set so that the value obtained by multiplying the term and the coefficient b is sufficiently larger than the value obtained by multiplying the first term and the coefficient a.

  The inverter control unit 15 controls the inverter circuit IV based on the time-series voltage pattern selected by the voltage pattern selection unit 14. That is, the inverter control unit 15 performs inverter control processing for controlling the inverter circuit IV based on the time-series voltage pattern selected by the voltage pattern selection unit 14. More specifically, the inverter control unit 15 determines the voltage in the next (k + 1) th control in the time-series voltage pattern selected by the voltage pattern selection unit 14 when the current control is the kth control. As the target voltage, each control of the first to sixth switching elements Tr1 to Tr6 in the inverter circuit IV so as to output the target U-phase current, V-phase current and W-phase current corresponding to the target voltage from the inverter circuit IV. Output a control signal to the terminal.

  Then, the control unit 11 performs the speed output process, the load torque estimation process, the voltage pattern generation process, the speed prediction process, the voltage pattern selection process, and the inverter control process. The TE, the voltage pattern generation unit 12, the speed prediction unit 13, the voltage pattern selection unit 14, and the inverter control unit 15 are repeatedly executed at a predetermined control cycle.

  The model predictive control unit MC, the three-phase / two-phase conversion unit CV, the load torque estimation unit TE, and the rotation speed processing unit RSC include a CPU (Central Processing Unit), a memory, and a peripheral circuit thereof. In the model prediction control unit MC, the control unit 11, the voltage pattern generation unit 12, the speed prediction unit 13, the voltage pattern selection unit 14, the inverter control unit, the three-phase / two-phase conversion unit CV, and the load torque estimation unit TE The subtracting unit 31, the low-pass filter unit 32, the parameter calculating unit 33 and the gain calculating unit 34, and the rotation speed processing unit RSC are functionally configured in the CPU by executing a predetermined program.

  In the present embodiment, the rotation angle measurement unit VS and the rotation speed processing unit RSC correspond to an example of a speed output unit that obtains the rotation speed of the motor as a rotation speed current value, and includes a model prediction control unit MC, a current measurement unit CS, a rotation The angle measurement unit VS, the three-phase / two-phase conversion unit CV, the load torque estimation unit TE, and the rotation speed processing unit RSC correspond to an example of an electric motor drive control unit that controls the electric motor driven by the output of the inverter circuit.

  Next, the operation of this embodiment will be described. FIG. 8 is a flowchart showing an operation in the motor drive control system. FIG. 9 is a flowchart for obtaining a gain for adjusting the update amount of the load torque. FIG. 10 is a diagram illustrating a simulation result of speed control.

First, the setting of the load torque gain K will be described. In the setting of the gain torque gain K, the gain K is initially set to an appropriate value in FIG. 9 (S31). Next, pole _{p i} is determined in the transfer function H of the equation 6 (z) (S32, in the above example, i = 1, 2, 3, 4). Then, in all poles p _i, its magnitude is determined whether or not within one (S33).

The result of this determination, in all poles p _i, in the case (Yes) its size is within 1, then the processing S34 is being carried out, at least one pole p _i, whose magnitude is 1 within If not (No), the process S36 is performed next.

  In this process S36, the gain K is subtracted by a predetermined value ΔK1 set in advance (K ← K−ΔK1), and the process returns to the process S32.

  On the other hand, in the process S34, it is determined whether or not the convergence time of the step response in the transfer function H (z) of Expression 6 is within a predetermined value Tco set in advance. The predetermined value Tco is appropriately set according to the response time allowed by the specification of the motor drive control system S.

  As a result of this determination, if the convergence time is within the predetermined value Tco (Yes), the process S35 is then performed, and if the convergence time is not within the predetermined value Tco (No), then Processing S37 is performed.

  In this process S37, the gain K is added by a preset predetermined value ΔK2 (K ← K + ΔK2), and the process returns to the process S32. The predetermined value ΔK1 and the predetermined value ΔK2 may be the same value or different values.

  On the other hand, in the process S35, the overshoot amount (maximum amplitude width of overshoot in the damped vibration) and the undershoot amount (maximum amplitude width of undershoot in the damped vibration) in the transfer function H (z) of Expression 6 Is within a predetermined value OU set in advance. The predetermined value OU is appropriately set according to the damping vibration width allowed by the specifications of the electric motor drive control system S.

  As a result of this determination, if the overshoot amount and the undershoot amount are within the predetermined value OU (Yes), the gain K is determined based on the value at this time, the processing is terminated, and the overshoot amount and undershoot amount are determined. If the shoot amount is not within the predetermined value OU (No), the process returns to the process S32 after the process S36 is performed.

  Such a setting process of the gain K for adjusting the update amount of the load torque may be performed by, for example, a user and set in the motor drive control system S, or the coefficient functionally configured in the CUP It may be automatically executed by a setting unit (not shown) and set in the motor drive control system S.

  Next, the operation of the motor drive control system S by model predictive control will be described. In such an electric motor drive control system S, when the power is turned on, initialization of each necessary part is executed and its operation is started. For example, by executing a program, the CPU is functionally configured with a model prediction control unit MC, a three-phase two-phase conversion unit CV, a load torque estimation unit TE, and a rotation speed processing unit RSC. The MC includes a control unit 11, a voltage pattern generation unit 12, a speed prediction unit 13, a voltage pattern selection unit 14, and an inverter control unit 15. The load torque estimation unit TE includes a subtraction unit 31, a low-pass filter. The unit 32, the parameter calculation unit 33, and the gain calculation unit 34 are functionally configured.

  And each process of process S11 thru | or process S17 shown in FIG. 8 is repeatedly performed by the control part 11 for every predetermined | prescribed control period until the drive of the electric motor M is stopped.

  In FIG. 8, first, the current value of each phase measured by the current measuring unit CS is acquired this time (kth), and the value of the rotation angle measured by the rotation angle measuring unit VS is acquired (S11). . The current measuring unit CS outputs the acquired current value of each phase to the three-phase / two-phase converting unit CV, and the rotation angle measuring unit VS outputs the acquired rotation angle value to the three-phase / two-phase converting unit CV and Output to each rotation speed processing unit RSC.

Subsequently, the three-phase / two-phase conversion unit CV obtains the d-axis current i _d and the q-axis current i _q from the current value and rotation angle value of each phase acquired in the process S11, and the obtained d-axis current i _{The d} and q-axis current i _q is output to the model prediction control unit MC, and the rotation speed processing unit RSC obtains the rotation speed ω _m from the current value and the rotation angle value of each phase acquired in the process S11. The rotation speed ω _m is output to the model prediction control unit MC and the load torque estimation unit TE as the rotation speed current value ω _m (= ω (k)) (S12, speed output process).

Subsequently, the load torque estimation unit TE has a current rotational speed prediction value (ω _m with a hat on top = ω (k) with a hat on top) predicted in the past by the speed prediction unit 13 of the model prediction control unit MC. ) To estimate the load torque (S13, load torque estimation process). In the present embodiment, the load torque estimation unit TE uses the current rotation speed predicted value (ω (k) with a hat on top) obtained by the subtraction unit 31 in the process S15 immediately before the control cycle and the process S12. The rotation speed processing unit RSC obtains a difference from the current rotation speed current value ω (k), and the obtained difference is filtered (filtered) by the low-pass filter unit 32. the parameter calculation unit 33, a parameter (-J / T _s) multiplied by this parameter (-J / T _s) the difference multiplied by, for adjusting the updating amount of the set load torque as described above The gain K is multiplied, and the multiplication result is output to the model prediction control unit MC.

  Subsequently, the model prediction control unit MC uses the voltage pattern generation unit 12 to change the time-series voltage patterns that can be output by the inverter circuit IV in accordance with the preset prediction horizon value and control horizon value. A plurality are generated as described above (S14, voltage pattern generation processing).

Subsequently, the model prediction control unit MC receives the load torque estimated by the load torque estimation unit TE from the speed prediction unit 13 for each of a plurality of time-series voltage patterns generated by the voltage pattern generation unit 12 to the electric motor M. In this case, the rotation speed of the motor M when the time-series voltage pattern is input to the motor M is predicted as a rotation speed prediction value (S15, speed prediction processing). More specifically, the rate prediction portion 13 obtains the d-axis current i _d by the following equation 7, obtains the q-axis current i _q by the following equation 8 to obtain the output torque T _e of the motor M by the following equation 9, A rotational speed prediction value (ω _m with a hat on top) is obtained by the following equation (10). In the above-described example, the speed prediction unit 13 for each of the eight sets of time-series voltage patterns, the current predicted value [i _dq (k + 1) on the dq axis up to two control cycles ahead with respect to the current k-th control. ), I _dq (k + 2)] and the predicted rotational speed [ω (k + 1) with a hat (^) above, ω (k + 2) with a hat (^) above].

  Subsequently, the model prediction control unit MC uses the evaluation formula g of Formula 11 by the voltage pattern selection unit 14 to perform processing S15 from among a plurality of time-series voltage patterns generated by the voltage pattern generation unit 12. Then, a time-series voltage pattern corresponding to the highest estimated rotational speed predicted value among the predicted rotational speed values of the electric motor M predicted by the speed predicting unit 13 is selected (S16, voltage pattern selecting process).

  Subsequently, the model prediction control unit MC is selected by the voltage pattern selection unit 14 by outputting control signals to the control terminals of the first to sixth switching elements Tr1 to Tr6 in the inverter circuit IV by the inverter control unit 15. Based on the time-series voltage pattern thus generated, the inverter circuit IV is controlled to drive the motor M (S17, inverter control process).

Thus, the electric motor M is controlled and driven by the model predictive control so that the target speed ω _m ^* is obtained.

  Simulation (numerical experiments) verified the effects of the motor drive control system S, the motor drive control device, and the motor drive control method mounted thereon in the present embodiment. The simulation result of the speed control of one embodiment is shown in FIG. 10 together with the comparative example. FIG. 10A shows a simulation result of speed control by the electric motor drive control system S in the present embodiment, and FIG. 10B shows a simulation result of speed control by a comparative example. Each horizontal axis in FIG. 10A and FIG. 10B is an elapsed time, and each vertical axis is a rotation speed.

  In the comparative example, the load torque is not estimated, and the term of the load torque is 0. In the comparative example, as shown in FIG. 10B, when the load torque is applied, the rotation speed is lower than the target speed, but in this embodiment, the load torque is applied as shown in FIG. 10A. However, the rotational speed is substantially the target speed. Therefore, in the present embodiment, the load torque is appropriately estimated, and the predicted rotational speed can be predicted with higher accuracy by using the formula 10 for predicting the rotational speed. As a result, in the present embodiment, an appropriate time-series voltage pattern can be selected, and the rotation speed can follow the target speed.

  As described above, the electric motor drive control system S, the electric motor drive control device, and the electric motor drive control method mounted thereon according to the present embodiment use the current predicted rotational speed value predicted in the past for the estimation of the load torque. Therefore, the load torque can be estimated with a smaller amount of information processing than in the case of using a conventional Kalman filter, and the motor can be driven and controlled by model predictive control even under use conditions where the load torque works. For this reason, even when model predictive control is realized with an inexpensive arithmetic processing device having a relatively low arithmetic processing capability, the motor drive control system S, the motor drive control device, and the motor drive control method drive the motor in substantially real time. Can be controlled.

  In the motor drive control system S, the motor drive control device, and the motor drive control method, the difference between the current predicted rotational speed value predicted in the past by the speed prediction unit 13 and the current rotational speed value is multiplied by a predetermined coefficient. Since the load torque is estimated by integrating the difference multiplication value for each control period, the load torque can be easily estimated with a smaller amount of information processing, and the motor M can be driven and controlled by model predictive control.

  As described with reference to FIG. 9, the motor drive control system S, the motor drive control device, and the motor drive control method appropriately set the gain K for adjusting the update amount of the load torque so that the control system is stabilized. Can be set. For this reason, it is possible to avoid in advance oscillation and instability that occur during driving due to an inappropriate gain K.

In the above-described embodiment, the voltage pattern selection unit 14 performs the evaluation by using the evaluation formula g of the evaluation function including the rotation speed ω _m ^* of the control target, for example, as shown in Equation 11, and performs model prediction. Although the control target rotational speed ω _m ^* is input from outside and set in the control unit MC, the present invention is not limited to this. For example, the motor drive control system S and the motor drive control device You may further provide the control target estimation part which estimates the rotational speed of a future control target based on a track record value. Such a control target prediction unit 16 is further provided in the model prediction control unit MC, for example, as shown by a broken line in FIG. 2, and is functionally configured in the CPU, for example. When the rotational speed ω _m ^* of the control target is, for example, a fixed value (constant value) or a predetermined value that is input by an operator using an operation switch, for example, the above-described embodiment can cope with it. When the rotational speed ω _m ^* of the control target is a variable value that is input by the operator so as to change, the change in the rotational speed ω _m ^* of the control target is detected and this is handled. Response delay may occur. Since the electric motor drive control system S and the electric motor drive control device further include the control target prediction unit, the response delay can be reduced and more appropriately controlled even when the rotation speed of the control target changes.

  For example, the control target prediction unit 16 predicts the rotational speed of the future control target based on the amount of change in the actual value before the present (first modified embodiment).

FIG. 11 is a diagram for explaining a first modification of the electric motor drive control system. The horizontal axis in FIG. 11 indicates the number of times of control that is repeatedly controlled in the predetermined control cycle, and the kth is the current number of times of control. The vertical axis in FIG. 11 is the rotational speed ω _m ^* of the control target. A black circle (●) indicates the rotational speed ω _m ^* of the control target that is the actual value before the present (here, each rotational speed ω _m ^* (k of the control target in each of the k-th and (k−1) -th controls). ), Ω _m ^* (k−1)), and white circles (◯) indicate the respective rotational speeds ω _m ^* of the control target in the future (here, the control target in the (k + 1) th and (k + 2) th control). Each rotational speed ω _m ^* (k + 1), ω _m ^* (k + 2)).

In the control target prediction unit 16, the rotation speed omega _m ^* of the control target is the current previous actual value ^{_{(k), ω m * (}} k-1), ··· the rotational speed of the future control target omega _m ^At least the data necessary for calculating ^* is stored. Then, the control target prediction unit 16 determines the control target per one control count from the rotational speeds ω _m ^* (k), ω _m ^* (k−1),. Determination of the amount of change in the rotation speed omega _m ^*, by changing the rotational speed omega _m ^* only control target amount of change thus determined, determine the respective rotational speed omega _m ^* of the control target in the future. More specifically, for example, as shown in FIG. 11, the amount of change in the actual value before the present is a constant value, and the rotation speed ω _m ^* of the control target in the future also changes with this constant value in the future. In this case, the control target prediction unit 16 obtains each rotation speed ω _m ^* of the control target in the future using the following equation 12.

As described above, the voltage pattern selection unit 14 uses ω _m ^* obtained by the expression 12 when the evaluation is performed using the evaluation expression g of the expression 11.

Alternatively, for example, the control target prediction unit 16 predicts the rotational speed of the future control target by extrapolating the previous actual value (second modification). More specifically, the control target prediction unit 16 obtains each rotational speed ω _m ^* of the control target in the future by using, for example, Lagrange extrapolation represented by the following equation (13).

Here, N indicates the order. For example, when the order is 2 and the prediction is performed up to two control cycles ahead, by using the equation 13, the control targets in the (k + 1) th and (k + 2) th, as in the following equations 14-1 and 14-2: The respective rotation speeds ω _m ^* (k + 1) and ω _m ^* (k + 2) are obtained. Note that the order N is not limited to 2, and may be set as appropriate according to the calculation capability of the CPU.

When the voltage pattern selection unit 14 evaluates using the evaluation formula g of Formula 11 as described above, ω _m ^* obtained by Formula 13 is used.

  In order to express the present invention, the present invention has been properly and fully described through the embodiments with reference to the drawings. However, those skilled in the art can easily change and / or improve the above-described embodiments. It should be recognized that this is possible. Therefore, unless the modifications or improvements implemented by those skilled in the art are at a level that departs from the scope of the claims recited in the claims, the modifications or improvements are not limited to the scope of the claims. To be construed as inclusive.

S motor drive control system M motor IV inverter circuit MC model prediction control unit CS current measurement unit VS rotation angle measurement unit CV three-phase two-phase conversion unit TE load torque estimation unit RSC rotation speed processing unit 11 control unit 12 voltage pattern generation unit 13 Speed prediction unit 14 Voltage pattern selection unit 15 Inverter control unit 31 Subtraction unit 32 Low-pass filter unit 33 Parameter calculation unit 34 Gain calculation unit

Claims (8)

An electric motor drive control device for controlling an electric motor driven by an output of an inverter circuit,
A load torque estimating unit for estimating a load torque acting on the electric motor;
A voltage pattern generation unit that generates a plurality of time-series voltage patterns that can be output by the inverter circuit so as to be different from each other,
For each of a plurality of time-series voltage patterns generated by the voltage pattern generation unit, the load torque estimated by the load torque estimation unit is acting on the motor, and the time-series voltage pattern is the A speed prediction unit that predicts the rotational speed of the motor when input to the motor as a rotational speed prediction value;
Corresponds to the highest estimated rotational speed predicted value among the predicted rotational speed values of the electric motor predicted by the speed predicting unit from among a plurality of time-series voltage patterns generated by the voltage pattern generating unit. A voltage pattern selection unit for selecting a time-series voltage pattern;
An inverter control unit that controls the inverter circuit based on the time-series voltage pattern selected by the voltage pattern selection unit;
The load torque estimation unit estimates the load torque based on a current rotation speed prediction value predicted in the past by the speed prediction unit,
Electric motor drive control device. A speed output unit for obtaining the rotation speed of the electric motor as a rotation speed current value;
The load torque estimating unit is configured to multiply a difference between a current rotational speed predicted value predicted in the past by the speed predicting unit and a current rotational speed value obtained by the speed output unit by a difference multiplied value by a predetermined coefficient. The load torque is estimated by integrating every control cycle.
The electric motor drive control device according to claim 1. A coefficient setting unit that sets the predetermined coefficient within a range in which a transfer function that receives the load torque as an input and outputs an estimation error of the speed prediction unit satisfies stability;
The electric motor drive control device according to claim 2. The voltage pattern selection unit performs the evaluation by using an evaluation function including a rotation speed of a control target,
A control target prediction unit that predicts the rotational speed of the future control target based on the past actual value;
The electric motor drive control device according to any one of claims 1 to 3. The control target prediction unit predicts the rotational speed of the future control target based on the amount of change in the previous actual value,
The electric motor drive control device according to claim 4. The control target prediction unit predicts the rotational speed of the future control target by extrapolating the previous actual value.
The electric motor drive control device according to claim 4. An electric motor drive control method for controlling an electric motor driven by an output of an inverter circuit,
A load torque estimating step of estimating a load torque acting on the electric motor;
A voltage pattern generation step of generating a plurality of time-series voltage patterns that can be output by the inverter circuit so as to be different from each other;
For each of a plurality of time-series voltage patterns generated in the voltage pattern generation step, the load torque estimated in the load torque estimation step is acting on the motor, and the time-series voltage pattern is the A speed prediction step of predicting the rotation speed of the motor when input to the motor as a rotation speed prediction value;
Corresponds to the highest predicted rotational speed predicted value among the predicted rotational speed values of the electric motor predicted in the speed predicting step from among a plurality of time-series voltage patterns generated in the voltage pattern generating step. A voltage pattern selection step for selecting a time-series voltage pattern; and
An inverter control step for controlling the inverter circuit based on the time-series voltage pattern selected in the voltage pattern selection step;
The load torque estimating step estimates the load torque based on a current rotation speed prediction value predicted in the past in the speed prediction step.
Electric motor drive control method. An electric motor,
An inverter circuit for driving the electric motor;
An electric motor drive control unit for controlling the electric motor by controlling the inverter circuit,
The motor drive control unit is the motor drive control device according to any one of claims 1 to 6.
Electric motor drive control system.

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