278results about "Modelling/simulations for control" patented technology

The invention discloses a degradation trend prediction method for a brushless direct current motor, and relates to the technical field of motor control, current, temperature and vibration signals of motor operation are collected, a characteristic signal transmission path model of a winding, a bearing and magnetic steel is constructed, and the degradation trend of the brushless direct current motor is predicted by analyzing the reflection characteristics and attenuation conditions of degradation signals of all parts. Extracting characteristic quantities of mutual influence among current, temperature and vibration; according to the method, a multi-component characteristic signal transmission path model is constructed, degradation signals are regarded as fluctuation quantity transmitted and reflected among different components, mutual influence of current, temperature and vibration signals is comprehensively analyzed, false characteristics are separated in combination with heat transfer lag characteristics and cooperative change critical points, accurate extraction of real degradation characteristics is realized, and the accuracy of the degradation characteristic extraction is improved. The problem that weak degradation signals are covered by interference is solved.

The invention relates to the technical field of motor control, and discloses an axial magnetic flux hybrid excitation synchronous motor field weakening control system based on multi-source feedback. According to the system, a motor digital twinborn model is constructed, and real-time operation data are collected by using a multi-source sensor and synchronized to the model; establishing a three-dimensional electromagnetic field state space based on the model, extracting features through a manifold neural operator, and generating a multi-dimensional excitation state feature set; determining an excitation anomaly feature index set according to the feature set distribution density; collecting data in real time, extracting current excitation characteristic parameters, mapping the current excitation characteristic parameters to a three-dimensional electromagnetic field state space, calculating spatial correlation with the abnormal index set, and outputting weak magnetic demand correlation factors; and finally, according to the correlation factor, the feature set and real-time data iteration updating operator parameters, a control instruction is generated to dynamically adjust the coupling proportion of the electrical excitation component and the permanent magnet excitation component. According to the system, comprehensive perception and accurate regulation and control of the motor operation state are realized, and the adaptability and reliability of field weakening control are improved.

The invention relates to the technical field of motor control, discloses a direct current brushless motor control method and system based on current prediction, and aims to solve the problems of large torque ripple, low efficiency and poor stability caused by current loop lag in the prior art. The method comprises the following steps: acquiring a motor operation state signal in real time; determining a sector and an electrical angular velocity based on the rotor position and the rotational speed; inputting related parameters into the mixed current prediction model to obtain a three-phase current prediction value of the next period; a prediction error is calculated in combination with a current instruction, and an optimal voltage vector enabling a cost function to be minimum is solved through a model prediction control algorithm; and finally, a space vector pulse width modulation signal is generated to drive an inverter. According to the method, advanced control is realized by fusing a physical model and a data-driven prediction mechanism, the torque ripple is remarkably reduced, and the energy efficiency and robustness are improved.

The invention provides an efficiency optimization control method of a permanent magnet synchronous motor and related equipment. The method comprises the following steps: acquiring an output current of an inverter; constructing an inverter loss model based on the output current of the inverter and the inverter loss coefficient; constructing a total loss model based on the electromagnetic loss model, the inverter loss model and an equivalent conversion method; constructing a current population by taking the plurality of d-axis current values as individuals; and performing optimization solution based on the total loss model, the current population, a PID search algorithm and an artemisinin optimization algorithm to obtain a global optimal solution and control the permanent magnet synchronous motor. According to the scheme, the driver loss is added into the total loss model, and efficiency optimization can be carried out on the whole motor driving system; in order to solve the problem that a traditional method is not suitable for an IPMSM, a PID search algorithm and an artemisinin optimization algorithm are combined, parameter search is carried out on a motor efficiency optimal point by simulating an incremental PID controller adjusting mechanism, a global optimal solution is obtained, and therefore optimal control over the click efficiency is achieved.

The invention provides a permanent magnet synchronous motor sliding mode control method and system based on disturbance compensation, and the method comprises the steps: constructing a first motor state equation based on a permanent magnet synchronous motor mathematical model containing disturbance; secondly, on the basis of a sliding mode control theory, a novel adaptive reaching law and a non-singular fast terminal sliding mode surface are constructed, stability proving is completed, and the fast convergence capability is analyzed; designing a novel speed ring controller through the state equation, the reaching law and the sliding mode surface; designing a sliding mode disturbance observer for a disturbance part in the speed loop controller; and finally, carrying out FOC speed regulation control on the permanent magnet synchronous motor by using the designed speed ring controller and the disturbance observer. Compared with an existing well-known sliding mode control scheme, the hybrid control method of the speed loop controller and the sliding mode disturbance observer is adopted, system buffeting is effectively weakened, meanwhile, the dynamic response speed is considered, and the system robustness is improved.

The invention discloses a rapid calculation method for electromagnetic vibration of a permanent magnet synchronous motor, and belongs to the technical field of electromagnetic field calculation. According to the method, a magnetic potential and magnetic conductance method is innovatively combined with an improved sub-domain method, the problem of complexity of electromagnetic field distribution of a nonlinear material is effectively solved through the magnetic potential and magnetic conductance method, and the capture precision of electromagnetic field changes is remarkably improved by dividing a computational domain into a plurality of sub-domains through the improved sub-domain method. According to the method, the influence of the tangential electromagnetic force wave and the harmonic current is fully considered, and high-precision calculation of the electromagnetic force can be realized. On the basis, a stator core shell equivalent theoretical model is established, the inherent frequency of the stator is calculated by adopting an energy method, and the accuracy of the model is verified through a modal experiment. Furthermore, by determining the frequency response function of the stator in the low-order mode, the acceleration spectrum and electromagnetic force wave distribution of the prototype stator in each mode are obtained based on the linear superposition principle. Compared with a traditional electromagnetic-structure coupling finite element model, the method has the advantages that the calculation efficiency is remarkably improved while the calculation precision is guaranteed, the calculation time is shortened by 59.3%, and efficient and reliable technical support is provided for optimization design of electromagnetic equipment.

The invention discloses an improved multi-vector combined model predictive control method and device for a permanent magnet synchronous motor. The method comprises the following steps: acquiring a three-phase current of each sampling period, and converting the three-phase current into a d-axis current and a q-axis current; performing one-beat delay compensation on the current, predicting a reference voltage of a next beat, and judging a sector where the reference voltage is located; selecting a corresponding voltage vector output combination in the reconstructed voltage vector selection table by combining the sector and the previous period zero vector; solving a cost function only containing voltage vectors and action time by using the KKT theorem, and calculating the action time of each voltage vector; and generating a pulse signal according to the action time for driving the output of an inverter of the permanent magnet synchronous motor. According to the method, the advantages of fast dynamic response, easy processing of multiple constraints and the like of model prediction control are maintained, and meanwhile, lower calculation complexity, fixed switching frequency and higher reliability are realized, so that the comprehensive performance of a permanent magnet synchronous motor control system is improved.

The invention discloses a motor multi-parameter identification method based on sampling noise excitation and bias compensation, and the method comprises the steps: firstly obtaining the voltage and sampling current of a motor, and enabling the sampling current to comprise sampling noise; then constructing an information evaluation index, and adjusting a proportional parameter of a current controller to improve the identification information amount; then, shaft voltage feed-forward compensation is constructed to suppress electromagnetic torque pulsation; recursion is carried out by adopting a least square method based on the discrete linear parameterization model to obtain a parameter initial value and a covariance matrix; secondly, estimating offset-containing parameters on line, and calculating a sampling noise variance by using an estimated residual error; and finally, obtaining unbiased parameter estimation according to bias compensation iteration updating so as to output online estimation values of stator resistance, direct-axis inductance Ld, quadrature-axis inductance Lq and permanent magnet flux linkage.

The invention discloses a discrete modeling and position-free control method for a low-carrier-ratio long-cable permanent magnet motor, and belongs to the field of motors. In order to solve the problem that the precision of a conventional mean voltage model is reduced due to the remarkable resistance characteristic of a low-carrier-ratio long-cable permanent magnet synchronous motor, a switching period is decomposed into a plurality of zero-order holding voltage excitation sections according to the discrete characteristic of the output pulse width modulation voltage of a converter; a motor accurate discrete model considering resistance characteristics is established by solving accurate current response of the permanent magnet motor segment by segment, a dead-beat current controller and a motor back electromotive force observer are further established based on the discrete model, and sensorless operation of the low-carrier-ratio long-cable permanent magnet synchronous motor system is realized. The discrete modeling precision of the low-carrier-ratio long-cable permanent magnet synchronous motor is improved, and the position-free control performance of the permanent magnet synchronous motor system under the working condition is improved.

The invention belongs to the technical field of permanent magnet synchronous motor control, and particularly discloses a permanent magnet synchronous motor finite time switching active-disturbance-rejection rotating speed control method, which comprises the following steps: acquiring a reference rotating speed and an actual rotating speed of a permanent magnet synchronous motor; the absolute value of the error between the reference rotating speed and the actual rotating speed is calculated and compared with a preset first threshold value and a preset second threshold value, and the stage of the permanent magnet synchronous motor is judged; constructing a finite time cascade expansion state observer comprising a first-stage finite time ESO and a second-stage linear ESO to observe the state and lumped disturbance of the permanent magnet synchronous motor; and based on the stage of the permanent magnet synchronous motor, selecting a composite state of the observation value of the first-stage finite time ESO, the observation value of the second-stage linear ESO or the observation value of the first-stage observer and the observation value of the second-stage observer generated based on the Bezier curve to generate the rotating speed loop control law of the permanent magnet synchronous motor. According to the invention, the problems that the transient anti-interference capability is weak and the current performance is reduced due to the fact that transient control and steady-state control are not distinguished in the prior art are solved.

The invention discloses a brushless motor control system and control method, and belongs to the technical field of motor control and driving. Comprising a real-time detection module, a control, regulation and control analysis module and a self-adaptive compensation module, multi-source operation data of the brushless motor are collected in real time, the control, regulation and control analysis module carries out depth correlation analysis, potential characteristics such as parameter sensitivity, observer coupling degree and stability attenuation index are mined, potential influences are quantified through analog simulation, and a comprehensive influence value is obtained. And the self-adaptive compensation module intelligently selects a compensation type according to the numerical value, calculates an accurate compensation data value, and performs dynamic closed-loop correction on controller parameters. According to the method, the problems of insufficient adaptive capacity and compensation lag caused by difficulty in coping with parameter time variation and potential coupling in the prior art are solved, the conversion from passive response to active prevention is realized, and the robustness, the control precision and the long-term operation stability under complex working conditions are improved.

The invention relates to the technical field of automation control, and discloses a brushless motor energy-saving control adjustment method and system, a controller and a storage medium, and the method comprises the following steps: S1, collecting the operation state information of a motor: collecting the operation state information, including current, voltage, temperature and load data, of the brushless motor in real time; s2, dynamic modeling and numerical solution: constructing a dynamic model of the brushless motor system based on the acquired running state information, and modeling by adopting a high-order differential equation set; s3, constructing a control cost function; s4, deducing an optimal control strategy; s5, approximately solving a control strategy; s6, adjusting and executing control parameters; and S7, performing feedback and parameter correction. By introducing the low-pass filter, the control change rate constraint and the rolling optimization mechanism, the dynamic closed-loop control effect of more stable control, more accurate feedback and more synchronous response is realized.

The invention relates to the field of power system modeling and parameter identification, and provides a synchronous generator parameter identification method based on an improved tuna swarm optimization algorithm. Dividing the full parameter set of the to-be-identified synchronous generator into a d-axis parameter subset, a q-axis parameter subset and a mechanical parameter subset according to the internal physical association of the to-be-identified synchronous generator; performing multiple improvements on the tuna swarm algorithm to obtain an improved tuna swarm optimization algorithm; integrating the to-be-identified parameters in the d-axis parameter subset and the q-axis parameter subset into a high-dimensional parameter vector, constructing a target function based on the comprehensive test data, and performing multi-parameter synchronous global identification based on the target function by adopting an improved tuna swarm optimization algorithm to obtain an identification result; and carrying out model verification and validity analysis on the identification result. According to the method, the problem of parameter correlation distortion of traditional step-by-step identification is solved, the global optimization ability and convergence efficiency of the algorithm are improved, and the method can adapt to the accurate identification requirement of the high-dimensional strong coupling parameters of the synchronous generator.

The invention discloses a model-free predictive current control method based on an improved observer, and belongs to the technical field of permanent magnet synchronous motor control. The control method comprises the following steps: firstly, by analyzing the frequency characteristic of ESO, selecting an extended state observer order for obtaining balance between the anti-interference capability and the noise suppression capability; secondly, designing a model-free predictive current loop controller, and calculating the observer gain through a bandwidth method; then, a judgment mechanism of a current loop controller is constructed, the mechanism judges whether the system is in a steady state or not at the moment according to the current deviation value in the current state, and therefore the observer order with the better control effect is selected. According to the model-free predictive current control method based on the improved observer, the anti-interference performance of the system and the noise suppression capability of the current are remarkably improved, it is guaranteed that the improved observer has rapid tracking response and excellent steady-state performance, and the robustness of the control system is enhanced.

The invention discloses a five-phase permanent magnet synchronous motor current control method based on virtual impedance. Comprising the following steps: obtaining stability boundaries of virtual impedance of each axis in d1-q1 and d3-q3 synchronous rotating coordinate systems, and obtaining optimal virtual impedance of each axis through simulation; according to the optimal virtual impedance of each coordinate axis, obtaining a proportional-integral control parameter; in the operation process of the five-phase permanent magnet synchronous motor, reference currents and actual currents of all shafts in d1-q1 and d3-q3 synchronous rotating coordinate systems are obtained in real time and input into corresponding two-degree-of-freedom current controllers respectively, and control voltages of all the shafts are obtained; and generating a driving signal according to the control voltage of all coordinate axes in the d1-q1 and d3-q3 synchronous rotating coordinate systems, and controlling the five-phase permanent magnet synchronous motor. According to the method, high-performance harmonic suppression and dynamic response optimization control of the five-phase permanent magnet synchronous motor under the influence of multiple odd harmonic currents is realized.

An electromagnetic transient modeling method and system for a high-efficiency synchronous machine, and, a device. The method comprises: predicting, of a synchronous machine, a first rotor angular velocity, a first rotor angle, and a first current q component of and a first current d component of an armature current, establishing a first Norton circuit for simulating the synchronous machine, and solving at the same time a second Norton circuit after equivalent transformation and a network conductance matrix so as to obtain a three-phase voltage of a synchronous machine port; according to the three-phase voltage, obtaining a second current q component, a second current d component, a second rotor angular velocity and a second rotor angle; and by means of error-controlled iterative solving, determining an electromagnetic transient simulation calculation result of the synchronous machine.

The invention provides an MRAS permanent magnet synchronous motor parameter online identification method based on BP neural network optimization, and the method comprises the steps: constructing two BP neural network models, carrying out the offline training optimization of the two models, and obtaining an optimal neural network model which can accurately predict the flux linkage of a rotor and the inductance of a stator; based on an MRAS step-by-step identification strategy, two-stage motor parameter step-by-step identification units are built, the two optimal neural network models are embedded into the corresponding motor parameter step-by-step identification units, and based on the problem that the stator resistance identification effect of the BP neural network is poor, the two optimal neural network models are embedded into the corresponding motor parameter step-by-step identification units; according to the invention, the BP neural network and the adaptive rate unit are established in the second MRAS parameter identification unit, and the online dynamic identification of the stator resistance and the stator inductance is realized through the combination of the BP neural network and the adaptive rate unit. According to the method, an off-line training-on-line identification mode is adopted, the complex parameter setting process in a traditional method is avoided, the identification efficiency is remarkably improved, and the identification result is accurate.

The invention relates to the field of permanent magnet motors, and particularly discloses a thickness-adjustable back electromotive force sinusoidal permanent magnet motor and a parameter optimization method thereof. The rotor comprises a rotating shaft, a rotor iron core and a combined magnetic pole, the outer layer is made of aluminum-nickel-cobalt, the thickness of the outer layer is high-low-high centrosymmetric along the magnetic pole, the inner layer is made of neodymium iron boron, the thickness of the inner layer is low-high-low centrosymmetric permanent magnets along the magnetic pole, adjacent magnetic poles are magnetized oppositely, and the stator comprises an iron core and an armature winding. The specific parameter optimization method comprises the following steps: S1, determining an optimization variable and a target function; s2, performing global optimization by using a lion group optimization algorithm to obtain an optimal parameter; and S3, substituting the optimal parameter into the finite element model for solving, and comparing with a motor air-gap magnetic field modeling result for verification. According to the method, the problems of back electromotive force parallel waves, large torque pulsation, complex optimization process, low calculation efficiency and the like of a traditional surface-mounted permanent magnet motor are effectively solved, and the back electromotive force sine degree, the motor stability and the optimization efficiency are improved.

The invention provides a permanent magnet synchronous motor rotating speed control method and system, and belongs to the technical field of motor control. The method comprises the following steps: firstly, constructing a discrete time mathematical model of a motor and an external source system comprising a lumped reference signal and lumped interference, and establishing a composite system model according to the discrete time mathematical model; then, constructing a dimensionality reduction observer to estimate an external source signal, and performing state and input transformation in combination with a regulator equation; thirdly, constructing a constraint set of the transformation system, and decomposing a state variable into a nominal component, a deterministic error component and an uncertain error component; a time-varying constraint tightening set is dynamically constructed according to the error, a model prediction control optimization problem with dynamic tightening constraint is solved online, and a nominal control quantity is obtained; and finally, combining the nominal control quantity and the estimated external source signal to synthesize an actual control voltage. According to the method, interference can be effectively suppressed, system security constraints are strictly ensured, recursion feasibility and closed-loop stability of control are ensured, and the dynamic response speed is increased.

The invention discloses a torque ripple suppression method for a permanent magnet synchronous motor under a limited voltage, and belongs to the technical field of power generation, power transformation or power distribution. The method comprises the following steps: acquiring torque data changing along with a rotor position under different excitation currents, and establishing a torque three-dimensional look-up table model of the torque about a shaft current and the rotor position; respectively establishing optimization targets for a low-rotating-speed working condition and a high-rotating-speed working condition, and establishing a stator current two-dimensional table look-up model under the low-rotating-speed working condition and a stator current three-dimensional table look-up model under the high-rotating-speed working condition in combination with the torque three-dimensional table look-up model; an optimized stator current algorithm model is established according to the stator current look-up table model, the stator current two-dimensional look-up table model or the stator current three-dimensional look-up table model is switched according to the criterion of direct current voltage out-of-limit, and the query value of the optimized stator current is used as a stator current reference value for vector control of the permanent magnet synchronous motor. While low-speed copper loss reduction and high-speed speed regulation range expansion are taken into consideration, overall torque harmonic suppression under a voltage limited working condition is realized.

A current profile of an excitation current supplied to an electric coil of a switched reluctance machine is controlled to reduce acoustic noise. Multiple potential current waveforms may be evaluated to select a desired waveform that reduces the acoustic noise level of the switched reluctance machine. A cumulative sound pressure level of the switched reluctance machine may be determined for each potential current waveform. The cumulative sound pressure level may be determined based on multiple harmonic sound pressure levels expected to result from the potential current waveform. A desired current waveform may be identified as the potential current waveform associated with an optimal cumulative sound pressure level. The desired current waveform may then be applied to a corresponding phase coil of the switched reluctance machine to operate the switched reluctance machine while reducing acoustic noise without sacrificing other motor performance criteria.

Disclosed are systems and methods for motor control using optimal efficiency reference generation. An electronic controller can determine current values of a motor in a rotating reference frame. Each current value can be associated with a dimension of a set of dimensions of the rotating reference frame. The electronic controller can further determine flux linkage values for each dimension of the set of dimensions of the rotating reference frame based on the current values using an optimization cost function that accounts for motor speed, copper loss, and core loss. The electronic controller can further determine target flux linkage values for each dimension of the set of dimensions of the rotating reference frame. The electronic controller can then control a power switch network coupled between a power source and the motor based on the flux linkage values and the target flux linkage values.

The invention relates to a permanent magnet synchronous motor model prediction control method under an improved discrete domain voltage equation, in particular to a motor control method, and particularly relates to a control method for a permanent magnet synchronous motor under a high-speed and low-carrier-ratio working condition. According to a traditional motor voltage equation, in a single control period of a discrete domain, a dq axis is in a static state, and the position is kept as a rotor position at the beginning of the period. Considering actual rotation of a dq axis in the process, voltage components of current, flux linkage and a basic vector are reduced to the dq axis synchronously rotating along with a rotor from the original static dq axis through coordinate transformation, and considering contradiction between continuous change and control discretization of each quantity in a single period, equivalent values of the quantities are taken in one period, and the quantity is calculated to be the equivalent value of the dq axis. And obtaining a new motor voltage equation as a predictive control model. According to the method, the dq-axis voltage equation of the motor is precise, the effect is particularly remarkable under the working condition of high speed and low carrier wave ratio, and the steady-state error of the d-axis current can be eliminated.

The disclosure relates to calibrating electric motors for use with a heating, ventilating, and air conditioning (HVAC) system. Example embodiments include a method of calibrating a motor assembly, the method comprising: selecting (204) an electric motor (110) and a motor controller (111) for the motor assembly; obtaining (206) at least one electric motor parameter of the electric motor (110); determining (208) a correction factor for the electric motor (110) based upon the at least one electric motor parameter; and programming (212) the motor controller (111) with the correction factor.

The invention relates to the field of computer technology application, in particular to a brushless generator dynamic performance optimization method and system, and the method comprises the steps: constructing a whole-process closed-loop system of dynamic model modeling, control strategy optimization, hardware characteristic modeling, mechanical and heat dissipation parameter construction, simulation testing and iterative correction; and collaborative optimization of multi-domain parameters is realized. According to the invention, the dynamic response speed and control precision of the brushless generator can be improved, and the system stability can be enhanced.

The embodiment of the invention provides a permanent magnet synchronous motor rotor position estimation method, system and device and a medium, and belongs to the technical field of mechatronics. The method comprises the following steps: constructing a first voltage equation of the permanent magnet synchronous motor in a synchronous rotating coordinate system under an ideal condition based on an estimated angle output by a flux observer; determining disturbance information corresponding to related parameters related to the permanent magnet synchronous motor, and correcting the first voltage equation according to the disturbance information to obtain a second voltage equation; determining an internal disturbance model, and processing the second voltage equation according to the internal disturbance model to obtain an augmented system; and determining an augmented disturbance observer, and performing state estimation and parameter adjustment on the augmented system according to the augmented disturbance observer to obtain a position estimation result corresponding to position estimation of the permanent magnet synchronous motor rotor.

The invention relates to a method for controlling an inverter which is electrically connected to an electric motor, having the following steps: defining a modulated voltage (S1) for the inverter, said voltage being based on a first switching frequency, for operating the electric motor with a current, wherein the current has an electric frequency; determining the electric frequency (S2); changing the first switching frequency (S4) on which the modulated voltage is based to a second switching frequency if a value pair consisting of electric frequency and first switching frequency, or a value pair consisting of electric frequency and a sideband of the first switching frequency, is within at least one defined disturbance range (S3).

The invention relates to a dual three-phase permanent magnet synchronous motor model-free prediction repetitive control method and system based on a double-subspace virtual vector, and the method comprises the steps: decomposing the vector of a motor into a fundamental wave subspace and a harmonic wave subspace which are orthogonal to each other based on an obtained operation parameter, and constructing an independent super-local model in the two subspaces; constructing a linear expansion state observer in the fundamental wave subspace, and constructing a repetitive expansion state observer based on repetitive control in the harmonic wave subspace; respectively synthesizing an independent virtual voltage vector set and a decoupling virtual voltage vector set in the two subspaces; and calculating reference voltage vectors of the two subspaces, selecting an optimal virtual voltage vector and an optimal decoupling virtual voltage vector, respectively calculating optimal duty ratios, synthesizing control signals applied to each bridge arm of the inverter, and driving the dual three-phase permanent magnet synchronous motor. According to the method, model-free control of double sub-spaces is realized, model parameters of a motor system of an algorithm are controlled, and better robustness is shown when the parameters are mismatched.

This application relates to a motor driving method, apparatus, computer device, and storage medium. The method includes: acquiring motor parameters of a target motor and constructing a digital twin model of the motor; initializing an initial reinforcement learning model and a backup reinforcement learning model; constructing a training dataset based on the motor digital twin model and the initial reinforcement learning model, and based on preset motor commands; adjusting the initial reinforcement learning model according to the training dataset, the initial reinforcement learning model, and the backup reinforcement learning model; adjusting the backup reinforcement learning model according to the adjusted initial reinforcement learning model; until the initial reinforcement learning model meets preset conditions, obtaining a target reinforcement learning model; and deploying the target reinforcement learning model to the target motor to achieve high-performance driving of the motor. This method provides an efficient and low-cost solution for driving motors.

A synchronous motor driving device which accurately estimates and limits direct current (DC), without a dedicated current detection sensor. The device includes a first DC calculation unit that calculates a first DC based on a first voltage command value, a current value of a winding of a synchronous motor, and a battery voltage; a second DC calculation unit that calculates a second DC based on a current value of the winding of the synchronous motor, a rotation speed of the synchronous motor, and a predetermined motor characteristic; a model error extraction unit calculating inverter efficiency based on the first and second DC; a DC correction unit that calculates an estimated DC on the basis of the first and second DC, and the inverter efficiency; and a DC limiting unit that corrects a current command value of the winding based on the estimated DC and a predetermined DC limit value.