JP2023050062A - Motor control device, motor control method, motor module and electric power steering device - Google Patents

Abstract

To provide a control device which can improve steering feeling an operator can feel.SOLUTION: A motor control device comprises a model following controller 230A which generates correction torque based on output of a control object that is a motor to correct input of the controlled object on the basis of the correction torque. The model following controller 230A includes: a high pass filter 233 having a first cut-off frequency; and a low pass filter 232 having a second cut-off frequency which is larger than the first cut-off frequency. When transfer functions of the low pass filter 232 and the high pass filter 233 are Q(s) and HPF(s), respectively, in a frequency band where a gain in gain characteristics of Q(s) and HPF(s) is 1, the transfer functions of the controlled object are restrained by a nominal model.SELECTED DRAWING: Figure 4

Description

The present disclosure relates to a motor control device, a motor control method, a motor module, and an electric power steering device.

A typical automobile is equipped with an electric motor (hereinafter simply referred to as "motor") and an electric power steering system (EPS) having a control device for the motor. An electric power steering device is a device that assists a driver's operation of a steering wheel (or steering wheel) by driving a motor. Conventionally, torque control realizes a motor output corresponding to the steering torque, thereby assisting the steering operation.

Patent Literatures 1 and 2 respectively disclose techniques related to disturbance observer control. In Patent Literature 1, a robust controller is used to reduce the influence of disturbances or parameter fluctuations of a controlled object on steering control. In Patent Document 2, a resonance point disturbance controller configured with a disturbance observer is used in order to suppress resonance point disturbance excited at a resonance point in the longitudinal direction of the suspension. Patent Literature 3 discloses a technique for eliminating friction torque generated by internal friction of a steering mechanism to generate a comfortable and appropriate steering reaction force according to the road surface reaction force.

JP-A-06-219310 WO2016/208665 JP-A-2005-88610

It is desired to improve the steering feel that the driver can feel when assisting the driver's steering operation.

In recent years, market demands for NVH (Noise, Vibration, Hashness), which is one of the criteria used to evaluate the comfort of automobiles, have become more and more stringent. However, conventional torque control is particularly susceptible to high-frequency disturbances and cannot suppress high-frequency torque fluctuations, making it difficult to meet market demands.

Conventionally, a friction model is constructed as a function of the angular velocity ω of the motor, and friction compensation control is performed using the constructed model. However, in general friction characteristics, there is a problem that chattering easily occurs due to a sudden reversal of the sign of the friction torque when the angular velocity ω of the motor becomes zero.

SUMMARY OF THE INVENTION The present invention has been made to solve at least one of the above problems, and improves the steering feel that a driver can feel by applying model following control and/or friction compensation control to torque control. It is an object of the present invention to provide a motor control device, a motor module including the control device, an electric power steering device including the motor module, and a motor control method.

A control device of the present disclosure, in a non-limiting exemplary embodiment, is a control device for controlling a motor, which is used in an electric power steering device having a motor. a model following controller that generates a correction torque based on an output and corrects an input of the controlled object with the correction torque, the model following controller including a high-pass filter having a first cutoff frequency; including a low-pass filter having a second cut-off frequency greater than the first cut-off frequency, wherein the transfer functions of said low-pass filter and said high-pass filter are respectively Q(s) and HPF(s), then Q(s )·HPF(s) in the frequency band where the gain in the gain characteristic is 1, the transfer function of the controlled object is constrained by the nominal model.

The motor module of the present disclosure, in a non-limiting exemplary embodiment, comprises a motor and the controller described above.

An electric power steering system of the present disclosure, in a non-limiting exemplary embodiment, includes the motor module described above.

A control method of the present disclosure, in a non-limiting exemplary embodiment, is a computer-implemented method for controlling a motor in an electric power steering system comprising a first cutoff frequency of and a lowpass filter having a second cutoff frequency greater than the first cutoff frequency, wherein the transfer functions of the lowpass filter and the highpass filter are Q( s) and HPF(s), in the frequency band where the gain in the gain characteristics of Q(s)·HPF(s) is 1, a model follower that constrains the transfer function of the controlled object, which is the motor, to a nominal model. A wing controller is used to generate a correction torque based on the output from the controlled object and cause the computer to correct the input of the controlled object with the correction torque.

According to an exemplary embodiment of the present disclosure, a motor control device capable of improving the steering feel that a driver can feel by applying model following control and/or friction compensation control to torque control; A motor module including a control device, an electric power steering device including the motor module, and a motor control method are provided.

FIG. 1 is a diagram schematically showing a configuration example of an electric power steering device according to an embodiment of the present disclosure. FIG. 2 is a block diagram showing a typical example of the configuration of the control device according to the embodiment of the present disclosure. FIG. 3 is a functional block diagram illustrating functions of a processor for controlling motors according to an embodiment of the present disclosure. FIG. 4 is a functional block diagram showing a configuration example of a model following controller in the first implementation example. FIG. 5 is a graph illustrating the gain characteristic T(s) of Q(s)·HPF(s) and the gain characteristic of the reciprocal of the modeling error Δ(s) between the plant and the nominal model P _n (s). is. FIG. 6 is a graph illustrating a gain diagram of the transfer function C(s) of the phase compensator in the torque controller. FIG. 7 is a graph illustrating a gain diagram of the transfer function HPF(s) of the high pass filter. FIG. 8 is a graph illustrating a gain diagram of the nominal model P _n (s). FIG. 9 is a graph showing measurement results of steering angle and torsion torque when model following control is not applied. FIG. 10 is a graph showing measurement results of steering angle and torsion torque when model following control is applied. FIG. 11 is a graph showing measurement results of changes in the steering angle over time when the model following control is not applied and when the model following control is applied. FIG. 12 is a functional block diagram showing a configuration example of a model following controller in the second implementation example. FIG. 13 is a graph showing simulation results of steering angle and steering torque when friction compensation control is not applied and when friction compensation control is applied. FIG. 14 is a graph showing simulation results of steering angle and steering torque when conventional friction compensation control is applied and when friction compensation control according to the second implementation example is applied.

Hereinafter, with reference to the accompanying drawings, a control device for a motor mounted in an electric power steering device of the present disclosure, a method for controlling a motor, a motor module including the control device, and an electric power steering device including the motor module Embodiments of are described in detail. However, more detailed description than necessary may be omitted. For example, detailed descriptions of well-known matters and redundant descriptions of substantially the same configurations may be omitted. This is to avoid unnecessary verbosity in the following description and to facilitate understanding by those skilled in the art.

The following embodiments are examples, and the control device and motor control method for the motor mounted in the electric power steering apparatus according to the present disclosure are not limited to the following embodiments. For example, numerical values, steps, the order of the steps, and the like shown in the following embodiments are merely examples, and various modifications are possible as long as there is no technical contradiction. The embodiments or examples described below are merely examples, and various combinations are possible as long as there is no technical contradiction.

[1. Configuration of Electric Power Steering Device 1000]
FIG. 1 schematically shows a configuration example of an electric power steering device 1000 according to an embodiment of the present disclosure.

An electric power steering system 1000 (hereinafter referred to as "EPS") has a steering system 520 and an assist torque mechanism 540 that generates an assist torque. The EPS 1000 generates an assist torque that assists the steering torque of the steering system that is generated when the driver operates the steering wheel. The assist torque reduces the driver's operating burden.

The steering system 520 includes, for example, a steering wheel 521, a steering shaft 522, universal joints 523A and 523B, a rotating shaft 524, a rack and pinion mechanism 525, a rack shaft 526, left and right ball joints 552A and 552B, tie rods 527A and 527B, and a knuckle 528A. , 528B and left and right steering wheels 529A, 529B.

The auxiliary torque mechanism 540 includes, for example, a steering torque sensor 541, a steering angle sensor 542, an automotive electronic control unit (ECU) 100, a motor 543, a reduction gear 544, an inverter 545 and a torsion bar 546. Steering torque sensor 541 detects the steering torque in steering system 520 by detecting the twist amount of torsion bar 546 . A steering angle sensor 542 detects the steering angle of the steering wheel. Note that the steering torque may be an estimated value derived by calculation instead of the value of the steering torque sensor. The steering angle can also be calculated based on the output value of the angle sensor.

The ECU 100 generates a motor drive signal based on detection signals detected by a steering torque sensor 541 , a steering angle sensor 542 , a vehicle speed sensor (not shown) mounted on the vehicle, and outputs the motor drive signal to an inverter 545 . For example, the inverter 545 converts the DC power into three-phase AC power, which is a pseudo sine wave of U-phase, V-phase and W-phase, in accordance with the motor drive signal, and supplies the three-phase AC power to the motor 543 . The motor 543 is, for example, a surface permanent magnet synchronous motor (SPMSM) or a switched reluctance motor (SRM), and receives supply of three-phase AC power to generate an assist torque corresponding to the steering torque. Motor 543 transmits the generated assist torque to steering system 520 via reduction gear 544 . Hereinafter, the ECU 100 will be referred to as the EPS control device 100 .

The control device 100 and the motor are modularized and manufactured and sold as a motor module. The motor module includes a motor and controller 100 and is suitable for EPS. Alternatively, control device 100 may be manufactured and sold as a control device for controlling the EPS independently of the motor.

[2. Configuration example of control device 100]
FIG. 2 shows a typical example of the configuration of the control device 100 according to the embodiment of the present disclosure. The control device 100 includes, for example, a power supply circuit 111, an angle sensor 112, an input circuit 113, a communication I/F 114, a drive circuit 115, a ROM 116, and a processor 200. Controller 100 may be implemented as a printed circuit board (PCB) on which these electronic components are mounted. A control device 100 is used to control a motor of an electric power steering device having a motor.

A vehicle speed sensor 300, a steering torque sensor 541, and a steering angle sensor 542 mounted on the vehicle are communicably connected to the processor 200, and the vehicle speed sensor 300, the steering torque sensor 541, and the steering angle sensor 542 respectively transmit the vehicle speed to the processor 200. , steering torque and steering angle are transmitted.

Controller 100 is electrically connected to inverter 545 (see FIG. 1). Control device 100 controls switching operations of a plurality of switch elements (eg, MOSFETs) included in inverter 545 . Specifically, control device 100 generates a control signal (hereinafter referred to as “gate control signal”) for controlling the switching operation of each switch element, and outputs it to inverter 545 .

Control device 100 generates a torque command value based on steering torque and the like, and controls the torque and rotation speed of motor 543 by vector control, for example. The control device 100 can perform not only vector control but also other closed loop control. The rotational speed is represented by the number of revolutions (rpm) at which the rotor rotates per unit time (for example, one minute) or the number of revolutions (rps) at which the rotor rotates per unit time (for example, one second). Vector control is a method of decomposing a current flowing through a motor into a current component that contributes to the generation of torque and a current component that contributes to the generation of magnetic flux, and independently controlling each orthogonal current component.

A power supply circuit 111 is connected to an external power supply (not shown) and generates a DC voltage required for each block in the circuit. The generated DC voltage is for example 3V or 5V.

Angle sensor 112 is, for example, a resolver or a Hall IC. Alternatively, the angle sensor 112 can also be implemented by a combination of an MR sensor having a magnetoresistive (MR) element and a sensor magnet. Angle sensor 112 detects the rotation angle of the rotor and outputs it to processor 200 . Instead of the angle sensor 112, the control device 100 may include a speed sensor and an acceleration sensor for detecting the rotational speed and acceleration of the motor. The processor 200 can calculate the angular velocity ω [rad/s] based on the electrical angle _θm of the motor.

The input circuit 113 receives the motor current value (hereinafter referred to as "actual current value") detected by a current sensor (not shown), and adjusts the level of the actual current value to the input level of the processor 200 as necessary. , and outputs the actual current value to the processor 200 . A typical example of the input circuit 113 is an analog-to-digital conversion circuit.

Processor 200 is a semiconductor integrated circuit and is also called a central processing unit (CPU) or microprocessor. The processor 200 sequentially executes a computer program, which is stored in the ROM 116 and describes a group of instructions for controlling motor driving, to achieve desired processing. In addition to or instead of the processor 200, the control device 100 includes an FPGA (Field Programmable Gate Array) equipped with a CPU, a GPU (Graphics Processing Unit), an ASIC (Application Specific Integrated Circuit), an ASSP (Application Specific Standard Product), or , may have a combination of two or more circuits selected from among these circuits. Processor 200 sets a current command value according to the actual current value, the rotation angle of the rotor, and the like, generates a PWM (Pulse Width Modulation) signal, and outputs it to drive circuit 115 .

The communication I/F 114 is, for example, an input/output interface for transmitting/receiving data based on an in-vehicle control area network (CAN).

Drive circuit 115 is typically a gate driver (or pre-driver). Drive circuit 115 generates a gate control signal according to the PWM signal, and applies the gate control signal to the gates of the plurality of switch elements included in inverter 545 . When the object to be driven is a motor that can be driven at a low voltage, the gate driver may not necessarily be required. In that case, the functionality of the gate driver may be implemented in processor 200 .

ROM 116 is electrically connected to processor 200 . ROM 116 is, for example, a writable memory (eg, PROM), a rewritable memory (eg, flash memory, EEPROM), or a read-only memory. ROM 116 stores a control program including a command group for causing processor 200 to control motor driving. For example, the control program is once developed in RAM (not shown) at the time of booting.

FIG. 3 shows functional blocks of a processor 200 for controlling motors according to an embodiment of the present disclosure. In the illustrated implementation, a computer, processor 200, uses a torque controller, a model following controller, a subtractor, and an adder to sequentially perform the processing (or tasks) necessary to control the motor.

Each functional block is implemented in processor 200 as software (or firmware) and/or hardware. The processing of each functional block is typically described in a computer program in units of software modules and stored in ROM 116 . However, when using an FPGA or the like, all or part of these functional blocks may be implemented as hardware accelerators. Also, the motor control method according to the embodiments of the present disclosure can be implemented by being implemented in a computer and causing the computer to perform desired operations.

The control device 100 comprises a torque controller 210, a model following controller 230, a subtractor AD1 and an adder AD2. In other words, processor 200 implements functions corresponding to torque controller 210, model following controller 230, subtractor AD1, and adder AD2.

The torque controller 210 operates based on the steering torque T _h and provides an input to a controlled object 220, which is a motor. For example, the steering torque T _h detected by the steering torque sensor 541 is input to the torque controller 210 . The torque controller 210 generates a target motor torque (or torque command value) T _ref by applying phase compensation to the steering torque T _h when the steering frequency or steering speed is within a predetermined range. input.

Torque controller 210 exemplified in FIG. 3 has base assist calculator 211 and phase compensator 212 .

Base assist calculation unit 211 acquires steering torque _Th and vehicle speed. A base assist calculation unit 211 generates a base assist torque based on the steering torque _Th and the vehicle speed. For example, the base assist calculation unit 211 may have a lookup table (LUT) that defines the correspondence between the steering torque T _h , the vehicle speed, and the base assist torque. The base assist calculation unit 211 can refer to the LUT and determine the base assist torque having a corresponding relationship based on the steering torque _Th and the vehicle speed. Further, the base assist calculation section 211 can determine the base assist gain based on the slope defined by the ratio of the amount of change in the base assist torque to the amount of change in the steering torque _Th .

ここで、ｓはラプラス変換子であり、ｆ_１は伝達関数のゼロ点の周波数（Ｈｚ）であり、ｆ_２は伝達関数の極の周波数（Ｈｚ）である。ゲイン（またはループゲイン）を縦軸にとり、周波数の対数を横軸にとったグラフはゲイン線図と呼ばれる。ゲイン線図において、ゼロ点は、ゲインカーブと０ｄＢを示す横軸との交点を意味し、極はゲインカーブの極大点を意味する。例えば、極の周波数を零点よりも大きくすることで位相進み補償を適用することができる。その周波数の間隔が大きいほど、位相進み量が多くなる。 The phase compensator 212 according to the embodiment of the present disclosure adjusts the assist gain within the possible range of the steering frequency when the driver operates the steering wheel, and compensates for the stiffness of the torsion bar. In embodiments of the present disclosure, an example of the predetermined range is 5 Hz or less. The phase compensator 212 may apply, for example, first-order phase compensation to the steering torque (torsion torque) when the steering frequency is 5 Hz or less. The first-order phase compensation is represented by the transfer function of Equation 1, for example.

where s is the Laplace transform, _f1 is the transfer function zero frequency (Hz), and _f2 is the transfer function pole frequency (Hz). A graph with the gain (or loop gain) on the vertical axis and the logarithm of frequency on the horizontal axis is called a gain diagram. In the gain diagram, the zero point means the intersection of the gain curve and the horizontal axis indicating 0 dB, and the pole means the maximum point of the gain curve. For example, phase lead compensation can be applied by making the pole frequency greater than the zero. The larger the interval between the frequencies, the greater the amount of phase advance.

ここで、ｓはラプラス変換子であり、ω_１はゼロ点の周波数であり、ω_２は極の周波数であり、ζ_１はゼロ点のダンピングであり、ζ_２は極のダンピングである。極の周波数ω_２はゼロ点の周波数ω_１よりも小さい。 Phase compensator 212 generates target motor torque T _ref based on the base assist torque and base assist gain output from base assist calculation section 211 . For example, phase compensator 212 may be a stabilizing compensator and apply stability phase compensation to the base assist torque. The phase compensator 212 can have a second-order or higher transfer function whose frequency characteristics are variable according to the base assist gain. Second-order and higher-order transfer functions are expressed using a responsiveness parameter ω and a damping parameter ζ. A second-order or higher transfer function can be represented by the following equation, for example. Damping can be given to the characteristics of the transfer function by setting the order of the transfer function to second order. It is possible to adjust the phase characteristics by changing the damping.

where s is the Laplace transform, ω ₁ is the zero point frequency, ω ₂ is the pole frequency, ζ ₁ is the zero point damping, and ζ ₂ is the pole damping. The pole frequency ω ₂ is less than the zero point frequency ω ₁ .

The model following controller 230 estimates the disturbance torque based on the motor angular velocity ω (MR angular velocity) output from the controlled object 220, calculates the estimated disturbance torque, and feeds it back to the input of the controlled object 220. Configured. The torque fed back from the model following controller 230 to the input of the controlled object 220 corresponds to the “correction torque” that corrects the input of the controlled object 220 . Model following controller 230 generates the correction torque based on the output of controlled object 220 . An example of model following controller 230 is a model following controller configured to perform model following control. A specific configuration of the model following controller 230 will be described in detail later.

Subtractor AD1 subtracts the estimated disturbance torque output from model following controller 230 from target motor torque _Tref . The output from subtractor AD1 is input to adder AD2 and model following controller 230 . The adder AD2 adds the disturbance torque _Td to the output from the subtractor AD1 and outputs the result to the controlled object 220. FIG. Here, examples of disturbances in the embodiments of the present disclosure include friction caused by mechanisms such as motors and reduction gears, torque ripple or rattling, self-aligning torque, unpaved rough roads or gravel roads, and the like. This is a disturbance that can occur when the vehicle is running. Here, the self-aligning torque means the torque acting in the direction in which the steering wheel returns due to the elasticity of the tire that is twisted when the steering wheel is turned.

[First implementation example]
A model following controller has an inverse plant model, a high pass filter and a low pass filter (or Q filter). The model following controller has a gain of 1 in the gain characteristics of Q(s) and HPF(s), where Q(s) and HPF(s) are the transfer functions of the low-pass filter and the high-pass filter, respectively. In the frequency band, the transfer function P(s) to be controlled is constrained by the nominal model P _n (s). In this specification, "the transfer function of the controlled object is constrained by the nominal model" means that, for example, when looking at the input-output relationship, the transfer function of the controlled object appears to be the transfer function of the nominal model. It means that the controlled object is controlled so that it can be seen.

FIG. 4 shows a configuration example of the model following controller 230A in the first implementation example. The model following controller 230A has a controlled object inverse model 231, a low-pass filter 232, a high-pass filter 233 and a subtractor SU1. Highpass filter 233 has a first cutoff frequency and lowpass filter 232 has a second cutoff frequency.

The angular velocity ω of the motor is input to the controlled object inverse model 231 . Subtractor SU1 subtracts the output of subtractor AD1 from the output of controlled object inverse model 231 to generate estimated disturbance torque _̂Td . The estimated disturbance torque ̂T _d is filtered in this order by a low-pass filter 232 and a high-pass filter 233 coupled in series and input to a subtractor AD1. Thus, the model following controller 230A feeds back the estimated disturbance torque ̂T _d to the input of the controlled object 220 . Note that "̂T _d " means T _d with a hat shown in FIGS. 4 and 12 .

The model following controller 230A executes model following control, which means a feedback loop using the angular velocity ω of the motor, which is the controlled object 220, in the outer loop of current control. In a first implementation, the feedback loop formed by the model following controller 230A can compensate for the angular velocity ω dependent torque ripple. The signal of the angular velocity ω used for control can be corrected for each type of motor, and the accuracy of the signal of the angular velocity ω can be improved as compared with the current signal. As a result, it is possible to apply highly accurate torque ripple compensation to torque control.

The model following controller 230A is structurally similar to a conventional disturbance estimator (or disturbance observer), but differs in intended actions and effects. A conventional disturbance estimator estimates the disturbance torque by selecting an inverse plant model with a value close to the plant model, and reduces the influence of the disturbance by adjusting the disturbance torque in advance. The frequency band targeted for this compensation is a low frequency of 4 Hz or less that can be taken by vehicle behavior.

Model following control according to embodiments of the present disclosure exploits the effect that a feedback loop constrains a plant to a nominal model defined in an inverse plant model. The frequency band that can be compensated for is about 4 Hz to 150 Hz, which is different from the frequency band of conventional disturbance estimators. For example, if the inverse plant model is defined such that there is no torque ripple, the model following control constrains the plant model to torque ripple free characteristics, and as a result, by applying torque ripple compensation, torque ripple is reduced to can be reduced. In addition, by building an inertia or viscosity model and constraining the plant model to that model, it is possible to reduce the inertia or viscosity of the plant model. By executing the model following control, in addition to the torque ripple compensation of the motor, for example, loss torque compensation or motor inertia compensation is performed.

In this specification, the controlled object 220, the nominal model (or plant model) used to constrain the controlled object 220, the inverse plant model 231 defined by the inverse plant model of the plant model, the transfer function of the low-pass filter 232, and high-pass filter 233 are denoted as P(s), P _n (s), P _n ⁻¹ (s), Q(s) and HPF(s), respectively.

A plant model (nominal model) is represented by the following equation (3), and an inverse plant model is represented by the following equation (4). A desired frequency characteristic can be imparted to P(s) of the controlled object 220 by appropriately setting J _mn and B _mn . In this embodiment, the plant model (nominal model) is a one-inertia system model.

Let T(s) be the complementary sensitivity function of the inner loop composed of the model following controller, and Δ(s) be the modeling error of the plant model. T(s) is expressed by Q(s)HPF(s), and the relationship shown in Equation 5 holds for Δ(s). Robust stability of the model following controller is guaranteed when the small gain theorem expressed by Equation 6 holds between T(s) and Δ(s). Although T(s)=1 is sufficient for disturbance suppression, it is necessary to satisfy Expression 6 in consideration of robust stability. As can be understood from this, disturbance suppression and robust stability are not compatible.

FIG. 5 illustrates a gain diagram of the transfer function of the entire steering system. In the gain diagram, the horizontal axis indicates frequency [Hz], and the vertical axis indicates gain [dB]. In the first implementation example, in order to realize disturbance suppression by frequency band, the frequency band is divided into an area I where disturbance suppression is required, where T(s)=1, and T( s) into a lowering region II. In region II, 1/Δ(s)>T(s) holds.

The gain characteristic of the transfer function of the entire steering system has peaks, for example, near 20 Hz and near 50 Hz, and the modeling error appears at one of the two peaks near 50 Hz. That is, Δ(s) has a peak near 50 Hz, and 1/Δ(s) shown in FIG. 5 has a bottom near 50 Hz. Methods of adjusting the gain characteristic include adjustment of 1/Δ(s) and adjustment of the breaking point of T(s). Adjustment of 1/Δ(s) is performed by adjusting J _mn and B _mn of the plant model, and adjustment of the break point of T(s) is performed by adjusting the second cutoff frequency of low-pass filter 232. is done in Furthermore, the sensitivity to disturbances can be adjusted by the amount of steering assistance, steering speed or vehicle speed. When the bottom frequency of the modeling error is close to the frequency of the boundary between region I and region II, as a countermeasure, the order of the low-pass filter 232 is increased to sharpen T(s) in region I where disturbance suppression is required. A drop-down method is often employed.

The control device 100 performs torque control for a low-frequency torque signal and controls a high-frequency disturbance such that the angular velocity ω≈0, thereby stabilizing the steering so that the steering wheel is not pulled. realization of To this end, control device 100 uses torque controller 210 to lower the high frequency gain of torque control, and model following controller 230A to reduce controlled object P(s) to the high frequency gain is constrained to the property that The reason for performing the latter process is to prevent the controlled object 220 from reacting to the disturbance when a disturbance such as Td shown in FIG. 4 is input to the controlled object 220 .

FIG. 6 illustrates a gain diagram of the transfer function C(s) of the phase compensator 212 in the torque controller 210. As shown in FIG. FIG. 7 illustrates a gain diagram of the transfer function HPF(s) of the high-pass filter 233. As shown in FIG. FIG. 8 illustrates a gain diagram of the nominal model P _n (s). In the gain diagram, the horizontal axis indicates frequency [Hz], and the vertical axis indicates gain [dB]. For example, if the phase compensator 212 having the gain characteristic of the transfer function C(s) shown in FIG. 6 is applied, the high-frequency gain can be lowered in the gain characteristic of the nominal model P _n (s) as shown in FIG. can. The cutoff frequency fc in the gain diagram of the transfer function C(s) is, for example, 2 Hz or more and 10 Hz or less, and the cutoff frequency fc in the gain diagram of P _n (s) is, for example, 2 Hz or more and 20 Hz or less.

The model following controller 230A constrains the transfer function P(s) of the controlled object 220 to the nominal model P _n (s) in the frequency band where the gain in the gain characteristic of Q(s)·HPF(s) is 1. configured to be The inverse plant model P _n ⁻¹ (s) is designed to give the inverse characteristic to be constrained and take advantage of the gain characteristic of Q(s)·HPF(s). By appropriately designing J _mn and B _mn of the plant model, a gain characteristic of the nominal model P _n (s) is obtained in which the gain decreases in the high frequency region, as shown in FIG. The boundary frequency between Region I and Region II (the lower limit of the frequency range defining Region I) is the maximum frequency that can be input by the driver, and is generally about 2 Hz to 10 Hz. This frequency depends on the first cutoff frequency of high pass filter 233 . Therefore, the lower limit frequency of the effective range of model following control is determined by adjusting the first cutoff frequency of high-pass filter 233 so as not to interfere with torque control.

Low pass filter 232 and high pass filter 233 are coupled in series. The low-pass filter 232 may consist of multi-stage LPFs. That is, Q(s) can be expressed as a transfer function of an n-stage LPF (where n is 1 or more). The second cutoff frequency is greater than the first cutoff frequency. The first cutoff frequency is, for example, 2 Hz or more and 10 Hz or less, and preferably 5 Hz or more and 7 Hz or less, for example. The second cutoff frequency is, for example, 3 Hz or more, preferably 50 Hz or less. However, the upper limit of the second cutoff frequency can be set to about 140 Hz to 200 Hz. A cutoff frequency fc of the gain characteristic of the nominal model P _n (s) shown in FIG. 8 depends on the first cutoff frequency and the second cutoff frequency, and is, for example, 2 Hz or more and 20 Hz or less.

The inventors confirmed the effect obtained by applying the model following control according to the embodiment of the present disclosure by performing actual vehicle measurements. In actual vehicle measurements, we measured the effect of reducing torque ripple and steering wheel pull by applying model following control to torque control. Here, the steering wheel being caught means that the steering wheel swings to the left and right when the driver climbs over a step without holding the hands.

FIG. 9 shows measurement results of steering angle and torsion torque when model following control is not applied. FIG. 10 shows measurement results of steering angle and torsion torque when model following control is applied. In the graph, the horizontal axis indicates the steering angle [deg], and the vertical axis indicates the torsion torque [Nm]. The graph shows waveforms measured when steering from end to end (turning the steering wheel from full left to full right or vice versa) at an angular velocity of 180 [deg/s].

Enlarging the portion enclosed by the dashed-dotted line in the graph shows that torque ripple can be suppressed when model following control is applied compared to when model following control is not applied. Specifically, it was found that the torsion torque fluctuation amount was reduced by about 0.1 [Nm].

FIG. 11 shows measurement results of changes in the steering angle with time when the model following control is not applied and when the model following control is applied. In the graph, the horizontal axis indicates time [sec], and the vertical axis indicates steering angle [deg]. The dashed rectangle indicates the region of the time when the vehicle has climbed over the step. It was found that by applying model following control to torque control, the fluctuation of the steering angle when the vehicle climbs over a step is suppressed, and the steering wheel shake can be appropriately reduced.

According to the first implementation example, by applying model following control to torque control, it is possible to reduce high-frequency components of disturbance. As a result, it is possible to appropriately reduce the torque ripple that may occur during steering and the steering wheel grip that may occur when the vehicle climbs over a bump.

[Second implementation example]
A model following controller according to a second implementation will now be described with reference to FIGS. 12-14. The model following controller according to the second implementation differs from the model following controller according to the first implementation in that it has a friction compensation calculator. Differences from the model following controller according to the first implementation example will be mainly described below.

Since the disturbance estimated by the model following controller includes mechanical friction such as motors and reduction gears, the model following controller according to the second implementation extracts the friction component from the estimated disturbance torque and compensates for the friction. to the estimated disturbance torque. The object of friction compensation is, for example, the friction of the motor, the friction of the reduction gear, or the friction left-right difference of the reduction gear.

When the conventional friction compensation control is applied, when the motor angular velocity ω is near zero, the change in the friction compensation torque (Nm) with respect to the motor angular velocity ω must be moderated in order to prevent chattering. In some cases, accurate friction compensation control could not be performed. According to the study of the inventor, in order to solve this problem, it is desirable to sequentially estimate and compensate for the friction.

A model following controller according to a second implementation is configured to feed back a disturbance compensating torque to an input of a controlled object. Specifically, the model following controller is connected in parallel to a high-pass filter that removes low-frequency components from the estimated disturbance torque and the high-pass filter, and applies friction compensation to the estimated disturbance torque to obtain an estimated mechanical friction torque. and an adder for generating a disturbance compensation torque by adding an estimated value of the friction torque to the estimated disturbance torque from which the low-frequency component has been removed by the high-pass filter. In the second implementation example, the estimated disturbance torque corresponds to the "first correction torque", and the disturbance compensation torque corresponds to the "second correction torque".

FIG. 12 shows a configuration example of the model following controller 230B in the second implementation example. The model following controller 230B is configured to perform model following control similar to the model following controller 230A according to the first implementation example. However, the function of model following control is not essential.

Model following controller 230B has friction compensation calculator 250 . The friction compensation calculator 250 is coupled in parallel with the high-pass filter 233 and applies friction compensation to the estimated disturbance torque ^ _Td to calculate an estimate of mechanical friction torque. Friction compensation calculator 250 has subtractor 251 , limiter 252 and gain adjuster 253 . Subtractor 251 subtracts the output value from high-pass filter 233 from the output value from low-pass filter 232 . A limiter 252 limits the output value from the subtractor 251 . Limiter 252 clips the input value to the upper or lower threshold if the input value exceeds the upper or lower threshold.

A gain adjuster 253 multiplies the output value from the limiter 252 by a gain K. FIG. The maximum value of gain K of gain adjuster 253 is determined under the condition that the transfer function of controlled object 220 is constrained to the nominal model. The maximum value of the gain K is set to, for example, about 1 to 1.2.

The estimated disturbance torque ̂T _d includes mechanical friction. In estimating the disturbance, the friction is first estimated from the transmission path of the output torque of the motor, and then the torque acting on the motor, such as self-aligning torque, is estimated. For this reason, the friction compensation calculator 250 calculates a value corresponding to the friction torque among the disturbances estimated first as an estimated value of the friction torque. In general, since moderate friction is required for EPS, high-precision friction compensation can be achieved while maintaining a moderate frictional force by using a smaller value than the actual frictional force as an estimated value of the frictional torque. It becomes possible to

In order to apply friction compensation to the estimated disturbance torque used for model following control, it is necessary to pay attention to the stability condition of model following control. This condition is that the gain in the gain characteristic of the transfer function of the friction compensation calculator 250 constrained to the characteristic considering stability does not exceed 1 according to the small gain theorem described above. This is derived from the design conditions of low-pass filter 232 . In the second implementation example, the value of the friction compensation gain, that is, the gain K is set to 1 at the maximum so as to always satisfy this condition. A device 251 is provided to apply a subtraction process. In other words, the friction compensation calculator 250 behaves as a low pass filter with a transfer function of 1-HPF(s).

The estimated disturbance torque ̂T _d includes a low frequency component ̂T _d1 , an intermediate frequency component ̂T _d2 and a high frequency component ̂T _d3 . The low-pass filter 232 removes the high-frequency component ̂T _d3 from the estimated disturbance torque ̂T _d , and the high-pass filter 233 further removes the low-frequency component ̂T _d1 from the estimated disturbance torque ̂T _d . Thus, only the intermediate frequency component ^ _Td2 of the estimated disturbance torque in the range from the first cutoff frequency of the high-pass filter 233 to the second cutoff frequency of the low-pass filter 232 is subjected to friction compensation. However, since the assumed friction included in the disturbance is a low-frequency component of the disturbance, the low-frequency component ^T _d1 is not subject to friction compensation according to the filtering process described above. Therefore, by connecting the friction compensation calculator 250 in parallel to the high-pass filter 233, the low-frequency component of the disturbance ^T _d1 that has been filtered by the high-pass filter 233 and no longer compensated is added again to the estimated disturbance torque ^T _d . Compensation is achieved. More specifically, the friction compensation calculator 250 generates the disturbance compensation torque by adding a value obtained by multiplying the low frequency component ̂T _d1 by the gain K to the intermediate frequency component ̂T _d2 . Note that “^T _d1 ” means T _d1 with a hat shown in FIG. 12, “^T _d2 ” means T d2 with a hat shown in FIG. 12, and “^T _d3 ” means T _d2 with a hat shown in FIG. means T _d3 with hat.

A vehicle equipped with an EPS can run according to a running mode having an automatic driving mode and a manual driving mode. In this case, the gain K of the gain adjuster 253 may be switched according to the running mode. The greater the gain K, the greater the degree of friction reduction. It is preferable that the gain K set in the automatic operation mode is larger than the gain K set in the manual operation mode. As a result, it is possible to apply optimal friction compensation to the automatic driving mode, which requires a greater reduction in friction.

Model following controller 230B further comprises adder AD3. Adder AD3 adds the output value from the gain adjuster to the output value from high-pass filter 233 . The output from adder AD3 is fed back to the input of controlled object 220 as disturbance compensation torque.

2. Description of the Related Art Auxiliary devices have been developed that recognize lanes such as white lines or yellow lines when traveling on expressways and assist automatic driving of vehicles that follow the lanes. In vehicles equipped with EPS and assist devices, it is known that uneven friction in the reduction gear can affect the control of the assist devices to drive the vehicle straight along the center of the lane. According to the friction compensation control according to the embodiment of the present disclosure, even if there is a left-right difference in the friction of the reduction gear, the estimated value of the friction torque can be calculated successively, so that the above problem can be solved. becomes possible. The angular velocity ω of the motor, which is the output of the plant model, includes information on the difference between the left and right friction of the reduction gear.

The present inventors confirmed the effect obtained by applying the friction compensation control by gain adjustment by conducting a simulation. Through simulation, the effect of reducing friction by friction compensation control was measured.

FIG. 13 shows simulation results of steering angle and steering torque when friction compensation control by gain adjustment is not applied and when friction compensation control by gain adjustment is applied. In the graph, the horizontal axis indicates the steering angle [deg], and the vertical axis indicates the steering torque [Nm]. The dashed line graph shows the waveform when the friction compensation control is not applied, and the solid line graph shows the waveform when the friction compensation control is applied. Arrows in the figure represent the width of steering torque, and the width corresponds to the magnitude of friction. It is found that the friction can be properly reduced by applying friction compensation control.

FIG. 14 shows simulation results of steering angle and steering torque when conventional friction compensation control is applied and when friction compensation control by gain adjustment is applied. In the graph, the horizontal axis indicates the steering angle [deg], and the vertical axis indicates the steering torque [Nm]. A graph indicated by a dashed line indicates a waveform when the conventional friction compensation control is applied, and a graph indicated by a solid line indicates a waveform when the friction compensation control by gain adjustment is applied. According to the conventional friction compensation control, as described above, when the motor angular velocity ω is near zero, the change in the friction compensation torque (Nm) with respect to the motor angular velocity ω must be moderated in order to prevent chattering. Due to this, a spike in steering torque was confirmed when the steering wheel was turned back (see the part surrounded by the dashed line circle in the figure). On the other hand, when friction compensation control by gain adjustment was applied, spikes were not confirmed, and it was found that friction could be appropriately reduced.

According to the second implementation example, by further applying friction compensation control through gain adjustment to torque control, it is possible to reduce high-frequency components of disturbances while appropriately reducing friction.

[Third implementation example]
In the third implementation example, controlled objects include a handle 521 , universal joints 523 A and 523 B, a rotating shaft 524 , a torsion bar 546 , a motor 543 and a reduction gear 544 . Since the controlled object in the third implementation example includes parts that can rotate relative to each other via the torsion bar 546, the motion of the controlled object cannot be described only by a simple equation of motion of one inertia system. The controlled object in the third implementation example changes between the one-inertia system and the two-inertia system depending on the strength with which the driver of the vehicle grips the steering wheel 521 . The more strongly the driver grips the steering wheel 521, the closer the controlled object is to the one-inertia system. The weaker the driver grips the steering wheel, the closer the controlled object is to a two-inertia system. In the third implementation example, an angular velocity corresponding to the angular velocity of the reduction gear 544 is input to the model following controller as an output to be controlled.

In the third implementation example, the plant model (nominal model) is a model having frequency characteristics between the one-inertia system and the two-inertia system. The transfer function P _n (s) of the plant model (nominal model) in the third implementation example is expressed by Equation 7, and the transfer function P _n ^-1 (s) of the inverse plant model is expressed by Equation 8. be.

7 and 8, s is the Laplace transform, J _STGn is a parameter representing the moment of inertia of the nominal model, B _STGn is a parameter representing the viscous friction coefficient of the nominal model, and ω _1n is the zero point frequency of the transfer function P _n (s), ω _2n is the pole frequency of the transfer function P _n (s), and ζ _1n is the damping ratio at the zero point of the transfer function P _n (s). and ζ _2n is the damping ratio at the poles of the transfer function P _n (s).

In the third implementation example, the nominal model is a model having frequency characteristics between the one-inertia system and the two-inertia system. Equation 7 representing the transfer function P _n (s) of the above nominal model is an equation obtained by adding an attenuation term to the equation representing the two-inertia system. The attenuation terms in Equation 7 are 2ζ _1n ω _1ns and 2ζ _2n ω _2ns . The equation obtained by removing these attenuation terms from the equation (7) becomes the equation representing the two-inertia system. The order of the transfer function P _n (s) of the nominal model in the third implementation is three.

In the third implementation example, the nominal model is a model that considers the mechanical characteristics when the driver (steerer) steers the steering wheel 521 . The more strongly the driver grips the steering wheel 521, the closer the controlled object is to the one-inertia system, and the weaker the driver grips the steering wheel 521, the closer to the two-inertia system. Therefore, the transfer function P(s) of the controlled object in the third implementation example changes between the one-inertia system and the two-inertia system depending on how the force is applied from the driver's arm to the steering wheel 521 . In the third implementation example, the nominal model is a model having frequency characteristics between the one-inertia system and the two-inertia system, so that the state of the controlled object can be any of the one-inertia system and the two-inertia system. Even in such a state, it is possible to prevent the modeling error Δ(s) between the transfer function P _n (s) of the nominal model and the transfer function P(s) of the controlled object from becoming too large. Therefore, regardless of how the driver steers the steering wheel 521, the control target can be preferably controlled using the nominal model. Thus, in the third implementation example, the nominal model is a model that takes into consideration the mechanical characteristics given to the controlled object by the way the driver grips the steering wheel 521 . By having such a nominal model as an internal model, the control device 100 in the third implementation can appropriately control the controlled object. Other configurations in the third implementation example can be similar to the other implementation examples described above.

In addition, although the control device of each implementation example described above is configured to include a torque controller that provides an input to a controlled object that is a motor, the present invention is not limited to this. A control device according to the present disclosure may not include a torque controller.

INDUSTRIAL APPLICABILITY An embodiment of the present disclosure can be used in a motor control device for controlling an EPS mounted on a vehicle.

100: control unit (ECU), 200: processor, 210: torque controller, 211: responsive phase compensator, 212: phase compensator, 220: controlled object, 230, 230A, 230B: model following controller, 231 232: Low-pass filter 233: High-pass filter 250: Friction compensation calculator 250: Friction compensation calculator 251: Subtractor 252: Limiter 253: Gain adjuster 1000: Electric power steering Apparatus, AD1: Subtractor, AD2, AD3: Adder, SU1: Subtractor

Claims (6)

A control device for controlling the motor, which is used in an electric power steering device having a motor,
a model following controller that generates a correction torque based on the output from the controlled object, which is the motor, and corrects the input of the controlled object with the corrected torque;
The model following controller comprises:
a highpass filter having a first cutoff frequency and a lowpass filter having a second cutoff frequency greater than the first cutoff frequency;
When the transfer functions of the low-pass filter and the high-pass filter are Q(s) and HPF(s), respectively, in the frequency band where the gain in the gain characteristic of Q(s)·HPF(s) is 1, the A controller configured to constrain a controlled transfer function to a nominal model. The control device according to claim 1, wherein the first cutoff frequency is 2 Hz or more and 10 Hz or less. 3. The control device according to claim 2, wherein said second cutoff frequency is 3 Hz or higher. a motor;
A control device according to any one of claims 1 to 3;
A motor module with An electric power steering apparatus comprising the motor module according to claim 4. A computer-implemented method for controlling a motor in an electric power steering system comprising:
A model following controller comprising a highpass filter having a first cutoff frequency and a lowpass filter having a second cutoff frequency greater than the first cutoff frequency, the transfer function of the lowpass filter and the highpass filter are Q(s) and HPF(s), respectively, the transfer function of the controlled object, which is the motor, is nominally A method of generating a corrective torque based on the output from the controlled object using a model following controller that constrains the model, and causing a computer to correct the input of the controlled object with the corrective torque.

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