CN118358386A - Control adjustment method and device of electric drive system - Google Patents
Control adjustment method and device of electric drive system Download PDFInfo
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- CN118358386A CN118358386A CN202410774554.0A CN202410774554A CN118358386A CN 118358386 A CN118358386 A CN 118358386A CN 202410774554 A CN202410774554 A CN 202410774554A CN 118358386 A CN118358386 A CN 118358386A
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Classifications
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L15/00—Methods, circuits, or devices for controlling the traction-motor speed of electrically-propelled vehicles
- B60L15/20—Methods, circuits, or devices for controlling the traction-motor speed of electrically-propelled vehicles for control of the vehicle or its driving motor to achieve a desired performance, e.g. speed, torque, programmed variation of speed
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
- H02P23/00—Arrangements or methods for the control of AC motors characterised by a control method other than vector control
- H02P23/0004—Control strategies in general, e.g. linear type, e.g. P, PI, PID, using robust control
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L2240/00—Control parameters of input or output; Target parameters
- B60L2240/40—Drive Train control parameters
- B60L2240/42—Drive Train control parameters related to electric machines
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L2240/00—Control parameters of input or output; Target parameters
- B60L2240/40—Drive Train control parameters
- B60L2240/42—Drive Train control parameters related to electric machines
- B60L2240/423—Torque
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
- H02P2205/00—Indexing scheme relating to controlling arrangements characterised by the control loops
- H02P2205/05—Torque loop, i.e. comparison of the motor torque with a torque reference
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/60—Other road transportation technologies with climate change mitigation effect
- Y02T10/72—Electric energy management in electromobility
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- Mechanical Engineering (AREA)
- Electric Propulsion And Braking For Vehicles (AREA)
Abstract
The application relates to the technical field of electric drive control, and provides a control adjustment method and device of an electric drive system, wherein the method comprises the following steps: acquiring a target control parameter for minimizing an electromagnetic torque error between a preset torque and an actual torque of a motor in an electric drive system from a control parameter set of a pre-constructed torque control model; according to the target control parameters, adjusting control parameters of a motor controller in the electric drive system; the torque control model is used for adjusting the torque of the motor, the control parameter set comprises a plurality of groups of control parameters, and one group of control parameters comprises a proportional gain parameter and an integral time parameter. The control and adjustment method of the electric drive system provided by the embodiment of the application can reduce the energy loss of the electric drive system and improve the vehicle performance.
Description
Technical Field
The application relates to the technical field of electric drive control, in particular to a control adjustment method and device of an electric drive system.
Background
An electric drive system is one of the important components of an electric vehicle, and includes a motor and a motor controller, such as a PI (proportional integral controller, linear controller) controller.
The running of the electric driving system can influence the performance of the electric automobile, such as the endurance mileage of the electric automobile, so in the related art, the energy loss of the electric driving system is reduced usually by an energy recovery mode, thereby improving the performance of the electric automobile. However, this method is limited to a specific environment, such as a vehicle deceleration working condition, and does not fully consider comprehensive optimization of the whole electric drive system, so that energy loss of the electric drive system cannot be reduced under certain working conditions, and vehicle performance is affected.
Disclosure of Invention
The present application is directed to solving at least one of the technical problems existing in the related art. Therefore, the application provides a control and adjustment method of an electric drive system, which can reduce the energy loss of the electric drive system and improve the vehicle performance.
According to an embodiment of the first aspect of the present application, a control adjustment method of an electric drive system includes:
acquiring a target control parameter for minimizing an electromagnetic torque error between a preset torque and an actual torque of a motor in an electric drive system from a control parameter set of a pre-constructed torque control model;
according to the target control parameters, adjusting control parameters of a motor controller in the electric drive system;
the torque control model is used for adjusting the torque of the motor, the control parameter set comprises a plurality of groups of control parameters, and one group of control parameters comprises a proportional gain parameter and an integral time parameter.
The target control parameter which minimizes the electromagnetic torque error between the preset torque and the actual torque of the motor in the electric drive system is obtained from the control parameter set of the torque control model for adjusting the motor torque of the electric drive system, so that the control parameter of the motor controller in the electric drive system is adjusted according to the target control parameter, the electric drive system can achieve better step response output, the accuracy of motor torque control is improved, and the energy loss of the electric drive system is reduced.
According to one embodiment of the present application, obtaining, from a control parameter set of a pre-constructed torque control model, a target control parameter that minimizes an electromagnetic torque error between a preset torque and an actual torque of a motor in an electric drive system, includes:
And adjusting a control parameter set of the torque control model for multiple times, wherein each adjustment is based on the preset torque, the electromagnetic torque error of the motor when the torque control model outputs a control signal last time, and each group of current control parameters in the control parameter set, after each torque error corresponding to each group of current control parameters one by one is obtained, determining that the minimum value of each torque error is the electromagnetic torque error of the motor when the torque control model outputs the control signal next time, and updating the control parameter set according to each group of current control parameters corresponding to each target torque error smaller than the preset error in each torque error one by one until the adjustment times of the control parameter set reach the preset times, and determining one group of current control parameters corresponding to the minimum value of each torque error as the target control parameter.
According to one embodiment of the present application, updating the control parameter set according to each set of current control parameters corresponding to each target torque error one-to-one to each torque error less than a preset error, includes:
and updating the control parameter set by adopting a particle swarm optimization algorithm according to each group of current control parameters corresponding to each target torque error one by one.
According to one embodiment of the present application, further comprising:
Obtaining a target stator flux linkage value which minimizes a loss value of the loss model from a flux linkage set of the motor according to the loss model of the motor;
Determining a stator flux linkage of the motor according to the target stator flux linkage value;
wherein the set of flux linkages comprises a plurality of stator flux linkage values.
According to one embodiment of the application, obtaining a target stator flux linkage value that minimizes the loss model from a flux linkage set of the motor according to the loss model of the motor comprises:
And inputting each stator flux linkage value of the flux linkage set into the loss model for multiple times, after each current loss value which is output by the loss model and corresponds to each stator flux linkage value one by one is obtained, updating the flux linkage set according to each stator flux linkage value which corresponds to each target loss value which is smaller than the preset loss in each current loss value one by one, until the more times of the flux linkage set reach the preset times, and determining the stator flux linkage value which corresponds to the minimum value of each current loss value as the target stator flux linkage value.
According to one embodiment of the present application, updating the flux linkage set according to each of the stator flux linkage values corresponding one to each of the target loss values of the current loss values which are smaller than a preset loss includes:
and updating the flux linkage set by adopting a particle swarm optimization algorithm according to the stator flux linkage values corresponding to the target loss values one by one.
According to one embodiment of the application, the preset torque is determined according to a vehicle model of a vehicle on which the electric drive system is mounted.
According to a second aspect of the present application, a control adjustment device for an electric drive system includes:
The control parameter acquisition module is used for acquiring target control parameters which enable the electromagnetic torque error between the preset torque and the actual torque of the motor in the electric drive system to be minimum from a control parameter set of a pre-constructed torque control model;
the control parameter adjustment module is used for adjusting the control parameters of a motor controller in the electric drive system according to the target control parameters;
the torque control model is used for adjusting the torque of the motor, the control parameter set comprises a plurality of groups of control parameters, and one group of control parameters comprises a proportional gain parameter and an integral time parameter.
An electronic device according to an embodiment of a third aspect of the present application includes a processor and a memory storing a computer program, where the processor implements the control adjustment method of the electric drive system according to any of the above embodiments when executing the computer program.
A computer-readable storage medium according to an embodiment of a fourth aspect of the present application has stored thereon a computer program which, when executed by a processor, implements the control adjustment method of the electric drive system according to any of the above-described embodiments.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments of the present application will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and should not be considered as limiting the scope, and other related drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flow chart of a control adjustment method of an electric drive system according to an embodiment of the present application;
FIG. 2 is a force analysis chart of a vehicle provided by an embodiment of the present application;
Fig. 3 is a schematic structural diagram of a control and adjustment device of an electric drive system according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
The following describes and illustrates the control adjustment method and apparatus of the electric drive system according to the embodiments of the present application in detail through several specific embodiments.
In some embodiments, a control adjustment method of an electric drive system is provided, and the method is applied to a terminal device and used for adjusting control parameters of the electric drive system. The terminal device may be electronic devices such as a desktop terminal, a mobile terminal, a vehicle-mounted terminal, and a server, and the server may be an independent server or a server cluster formed by multiple servers, or may be a cloud server that provides cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDNs, basic cloud computing services such as big data and artificial intelligent sampling point devices.
As shown in fig. 1, the control adjustment method of an electric drive system provided in this embodiment includes:
Step 101, acquiring target control parameters which minimize electromagnetic torque errors of preset torque and actual torque of a motor in an electric drive system from a control parameter set of a pre-constructed torque control model;
102, adjusting control parameters of a motor controller in the electric drive system according to the target control parameters;
the torque control model is used for adjusting the torque of the motor, the control parameter set comprises a plurality of groups of control parameters, and one group of control parameters comprises a proportional gain parameter and an integral time parameter.
In some embodiments, a vehicle model of a vehicle on which the electric drive system is mounted may be built in advance before control adjustment of the electric drive system is performed, and a torque control model for adjusting torque of a motor in the electric drive system, such as a torque control model for adjusting torque of a three-phase alternating current motor or a permanent magnet synchronous motor, may be built. Wherein, the vehicle is an electric vehicle, such as an electric automobile. The vehicle model includes a driving dynamics relation model for simulating a mechanical portion of the vehicle and an electric model for simulating an electric portion of the vehicle. The torque control model is used for simulating a motor controller in the electric drive system.
The mechanical part construction in the vehicle model, namely the construction of the driving dynamics relation model, can be used for determining the power and the energy required by the driving of the automobile according to the concepts of automobile mechanics and aerodynamics. As shown in FIG. 2, the total resistance of the vehicle to travel can be determined based on the force applied to the vehicleThe method comprises the following steps:
Wherein, The rolling resistance is indicated by the fact that,The air resistance is indicated by the air resistance,The resistance of the gradient is indicated,Indicating the weight of the vehicle and,The gradient angle is indicated as such,Which is indicative of the speed of the vehicle,Representing the coefficient of rolling resistance of the tyre,Indicating the acceleration of gravity and,The air resistance coefficient is represented by the air resistance coefficient,The area of the wind facing the wind is indicated,Is upwind speed.
Traction provided by an electric motor of a vehicleTo overcome the resistance, specifically:
; wherein, Representing the coefficient of moment of inertia.
The mechanical equation for each wheel drive of a vehicle is expressed as:
; wherein, For the motor torque,In order to be able to carry out a torque,Indicating the mechanical speed of the motor,Represents the total inertia, which is represented by the sum of the axle moment of inertia and the wheel moment of inertia, R is the wheel radius, i is the gear ratio,Is the transmission efficiency of the speed reducer.
Further, the speed reducer is calculated by the following formula:
by integrating the above formulas, the running dynamics relation model of the vehicle can be determined as follows:
For the electrical part construction in the vehicle model, i.e., the construction of the electrical model, the electrical model may be constructed based on the electric power of the vehicle and the battery state of charge. Specifically, in the actual running process of the vehicle, the open-circuit voltage of the battery changes the voltage of the motor according to the change of the state of charge, so that the motor loss is affected. At the same time, the state of charge of the battery can affect the change in battery resistance, resulting in battery loss. Thus, the constructed electrical model may be as follows:
Wherein, For the purpose of motor efficiency,For the power of the motor,For the motor torque,For the battery power to be high,For the voltage of the battery cell,For the current of the battery,For the resistance of the battery,Speed with vehicleProportional to the ratio.
In some embodiments, the torque control model may be built based on a motor controller in the electric drive system for outputting control signals to the motor. The motor controller may include a PI (Proportional-Integral Controller) controller, among others. The time domain expression of a conventional PI controller is:
Where u (t) represents a control signal output at the t-th sampling time, The proportional gain parameter is indicated as such,The parameter of the integration time is represented by,An electromagnetic torque error representing the preset torque and the actual torque. The time domain expression can be a torque control model.
The preset torque may be set according to actual conditions, for example, the torque required for the vehicle, that is, the preset torque may be predicted according to a vehicle model. For example, the motor torque determined by the driving dynamics relation model may beAs a preset torque. While when the torque control model outputs a control signal to the motor, the actual torque can be determined asWherein, the method comprises the steps of, wherein,In the form of an polar pair number,Representing the inductance of the stator,The stator current value on the dq axis is shown.
In some embodiments, a control parameter set may be pre-constructed that includes multiple sets of control parameters, each set including a proportional gain parameterAnd integration time parameter. To enable the electronic control system to achieve an optimal step response output, the objective function of the torque control model may be determined as: At this time, each set of control parameters may be substituted into the torque control model, and then, for any one set of control parameters, an electromagnetic torque error between a preset torque and an actual torque of the motor when the motor torque control is performed using the set of control parameters is obtained. Thus, electromagnetic torque errors corresponding to the respective sets of control parameters one by one can be obtained.
After the electromagnetic torque errors corresponding to the groups of control parameters one by one are obtained, the control parameter with the smallest corresponding electromagnetic torque error can be determined from the groups of control parameters and used as the target control parameter.
After the target control parameter is determined, the control parameter of the motor controller in the electric drive system can be adjusted according to the target control parameter, for example, the target control parameter is used as the control parameter of the motor controller to complete the control adjustment of the motor controller in the electric drive system, so that the motor controller generates a corresponding control signal to control the torque of the motor based on the target control parameter, thereby enabling the electric drive system to achieve better step response output and reducing the energy loss of the electric drive system.
The target control parameter which minimizes the electromagnetic torque error between the preset torque and the actual torque of the motor in the electric drive system is obtained from the control parameter set of the torque control model for adjusting the motor torque of the electric drive system, so that the control parameter of the motor controller in the electric drive system is adjusted according to the target control parameter, the electric drive system can achieve better step response output, the accuracy of motor torque control is improved, and the energy loss of the electric drive system is reduced.
In addition, through improving the accuracy to motor torque control in the electric drive system for the vehicle that carries on this electric drive system can realize faster, more stable dynamic response under the operating mode such as acceleration, deceleration, has improved stability and the reliability of vehicle, and then has promoted travelling comfort and driving experience.
In order to improve the accuracy of motor torque control, in some embodiments, obtaining a target control parameter for minimizing an electromagnetic torque error between a preset torque and an actual torque of a motor in an electric drive system from a control parameter set of a pre-constructed torque control model includes:
And adjusting a control parameter set of the torque control model for multiple times, wherein each adjustment is based on the preset torque, the electromagnetic torque error of the motor when the torque control model outputs a control signal last time, and each group of current control parameters in the control parameter set, after each torque error corresponding to each group of current control parameters one by one is obtained, determining that the minimum value of each torque error is the electromagnetic torque error of the motor when the torque control model outputs the control signal next time, and updating the control parameter set according to each group of current control parameters corresponding to each target torque error smaller than the preset error in each torque error one by one until the adjustment times of the control parameter set reach the preset times, and determining one group of current control parameters corresponding to the minimum value of each torque error as the target control parameter.
In some embodiments, the electromagnetic torque error of the motor at the kth output control signal of the torque control model is:
wherein S is a preset coefficient.
When the control signal is output for the Kth time of the torque control model, the preset torque and the current control parameters are set for any current control parameters in the control parameter set,And inputting the formula to obtain a battery torque error when the control signal is output for the K-1 th time of the torque control model according to the preset torque and the actual torque when the control signal is output for the K-1 th time of the torque control model, and taking the battery torque error as the torque error corresponding to the current control parameters of the group. Thus, when the control signal is output by the torque control model for the Kth time, each torque error corresponding to each group of current control parameters one by one can be obtained.
After each torque error is obtained, the minimum value in each torque error can be determined as the electromagnetic torque error of the motor when the control signal is output by the torque control model for the kth time, each target torque error smaller than the preset error is obtained from each torque error, each group of current control parameters corresponding to each target torque error is processed by adopting an evolutionary algorithm, and new control parameters are obtained and added into the control parameter set. If the current control parameters of each group corresponding to each target torque error are used as selected individuals for regeneration and reproduction, the genetic variation process of the living beings is simulated, offspring are generated through crossover and variation operations in a genetic algorithm, so that new control parameters are obtained and added into a control parameter set, and the k+1th output control signal of the torque control model is adjusted by utilizing the control parameters of each group in the updated control parameter set.
Exemplary, set upAndIs the parent individual and its offspringGenerated by the following crossover formula:
Wherein, Is a crossover coefficient, and determines the fusion proportion of the genetic information of the father; And Representing two sets of control parameters as parent individuals. By way of example only, and not by way of limitation,May be set to 0.7.
After updating the control parameter set, the updated control parameter set can be used as the control parameter set of the torque control model when the control signal is output for the kth time, so as to determine the electromagnetic torque error of the motor when the control signal is output for the kth+1th time of the torque control model, and the control parameter set is updated again, and the like until the update times of the control parameter set reach the preset times, if the update times reach 100 times, a group of current control parameters corresponding to the minimum value of each torque error obtained when the control signal is output by the torque control model in the control parameter set at the moment are used as target control parameters. Therefore, the target control parameters acquired from the control parameter set can further reduce the electromagnetic torque error by iterating and optimizing the control parameter set, so that the accuracy of motor torque control is improved, and the energy loss of an electric drive system is further reduced.
To further improve accuracy of motor torque control, in some embodiments, updating the control parameter set according to each set of current control parameters corresponding to each target torque error less than a preset error, includes:
and updating the control parameter set by adopting a particle swarm optimization algorithm according to each group of current control parameters corresponding to each target torque error one by one.
In some embodiments, a particle swarm optimization algorithm may be employed to update the control parameter set. The particle swarm algorithm comprises a particle swarm, wherein a particle corresponds to a set of control parameters, and the particle swarm represents a set of solutions of different control parameters. Each particle contains a position x and a velocity v. The locations of the local and global optima of the particles are expressed as:
the speed update formula of the particle individual is as follows:
the global optimal position represents a parameter value corresponding to a particle which minimizes an electromagnetic torque error of a motor in an electric drive system among all particle individuals. AndRespectively representing the individual optimal position and the global optimal position of the particle i at the t-th iteration,Indicating the speed of the ith particle at the t-th iteration,For the position of the ith particle at the t-th iteration,Indicating the individual best position of the particle i,Represents the individual best position of particle i found in the range 0, t, The acceleration factor is represented by a value representing,、As a result of the random coefficient,The inertial weight is represented, and the linear decreasing range is [0.4,0.9].
The updated positions of all particles are as follows:
。
After the kth output control signal of the torque control model determines each group of current control parameters corresponding to each target torque error one by one from the control parameter set, each group of current control parameters can be used as each particle, the global optimal position of the actual iteration is searched, the global optimal position is compared with the optimal solution of the previous iteration, the last generation optimal solution is reserved or the optimal solution is updated, so that the position of the particles is changed based on the updated optimal solution, namely, the control parameters of the last generation particles are replaced by new control parameters, and after all the particles are updated, the corresponding group of control parameters form the new control parameter set. And adjusting the control signal output by the k+1st time of the torque control model by using the new multiple groups of control parameters.
To further reduce the energy consumption of the electro-drive system, in some embodiments, the method further comprises:
Obtaining a target stator flux linkage value which minimizes the loss model from a flux linkage set of the motor according to the loss model of the motor;
Determining a stator flux linkage of the motor according to the target stator flux linkage value;
wherein the set of flux linkages comprises a plurality of stator flux linkage values.
In some embodiments, the losses of the motor include mainly winding copper losses, core losses, mechanical losses, and stray losses. A loss model of the motor may be established based on at least one of winding copper loss, core loss, mechanical loss, and stray loss.
Illustratively, when the motor is running, current flows through the motor windings, the power lost is proportional to the square of the current, and the energy is dissipated as heat, which is the copper loss of the windings. The total energy consumption can be expressed as the sum of copper losses of the three-phase stator windings, namely:
Wherein, Representing the equivalent resistance of the windings of each phase,Representing the effective value of the phase current, id and iq represent the components of the phase current on the dq axis, respectively. In the dq coordinate system motor model, the copper loss of the windings of the motor is reduced byThe heating of the resistor is expressed as:
Wherein, The sum of the inductances is the phase current dq axes between the stators；For the rotation of the rotor by an electrical angle,In order to achieve a magnetic flux linkage of the stator,The resistance of the rotor core is shown.
Stator flux linkageThe stator flux linkage on the dq coordinate system can be included, specifically:
The core loss of the motor is the loss generated by the electromagnetic effect inside the stator and rotor cores and inside the permanent magnet, and is formed by hysteresis loss Eddy current lossAdditional lossThe composition is formed. The general model of core loss is as follows:
Wherein Kh, kc, ke are hysteresis loss coefficient, eddy current loss coefficient and additional loss coefficient, f is magnetic density frequency, and Bm is amplitude of sinusoidal magnetic density. Representing the mutual inductance between the stator and the rotor,As a result of the empirical coefficient,Indicating the magnetizing current. The magnetizing current is expressed as follows:
Wherein, Representing the electrical angular velocity of the synchronous rotor,Representing the resistance of the rotor and,In order to flow to the inductance between the rotors,For the flow of rotor current.
From the above formula, the pass of the iron loss of the motor can be determinedThe heat generation of the resistor is expressed as follows:
based on the winding copper loss and the iron loss of the motor, the loss model of the motor can be determined as follows:
Due to the actual torque of the motor The expression of (2) isMeanwhile, the smaller the loss model of the motor is, the smaller the energy loss of the electric drive system is, so that the objective function of stator flux linkage and motor loss can be obtained as follows:
where ab is a coefficient concerning the rotational angular velocity of the rotor, respectively.
In some embodiments, losses of the motor at different rotation speeds, such as copper losses and iron losses of the motor at different rotation speeds, are input into a loss model of the motor in advance, and a flux linkage set of the motor is randomly initialized to obtain a flux linkage set comprising a plurality of stator flux linkage values. Then based on the objective functionAnd calculating the loss value of the loss model under any stator flux linkage value to obtain each loss value corresponding to each stator flux linkage value one by one.
After each loss value corresponding to each stator flux linkage value one by one is obtained, the stator flux linkage value corresponding to the minimum loss value in each loss value can be used as a target stator flux linkage value, and the target stator flux linkage value is used as the stator flux linkageIs a magnetic linkage value of (a). Therefore, the loss of the motor, such as iron loss and copper loss of the motor, can be reduced by optimizing the stator flux linkage of the motor, so that the energy loss of the electric drive system is reduced, and the energy utilization efficiency of the whole electric drive system is improved.
To further reduce energy loss of an electric drive system, in some embodiments, obtaining a target stator flux linkage value from a flux linkage set of the electric machine that minimizes a loss model of the electric machine, based on the loss model, includes:
And inputting each stator flux linkage value of the flux linkage set into the loss model for multiple times, after each current loss value which is output by the loss model and corresponds to each stator flux linkage value one by one is obtained, updating the flux linkage set according to each stator flux linkage value which corresponds to each target loss value which is smaller than the preset loss in each current loss value one by one, until the more times of the flux linkage set reach the preset times, and determining the stator flux linkage value which corresponds to the minimum value of each current loss value as the target stator flux linkage value.
In some embodiments, for the kth update of the flux linkage set, for any stator flux linkage value in the flux linkage set, the current actual torque of the motor and the stator flux linkage value may be input into the loss model to obtain a current loss value output by the loss model, to take the current loss value as the current loss value corresponding to the stator flux linkage value. Thus, the current loss value corresponding to each stator flux linkage value one by one in the k-th flux linkage set updating process can be obtained.
After the current loss values corresponding to the stator flux linkage values one by one are obtained, each target loss value smaller than the preset loss can be obtained from each current loss value, so that each stator flux linkage value corresponding to each target loss value is processed by adopting an evolutionary algorithm to obtain a new stator flux linkage value, the new stator flux linkage value is added into the flux linkage set, and the current loss value corresponding to each stator flux linkage value one by one in the k+1th flux linkage set updating process is determined by utilizing each stator flux linkage value in the updated flux linkage set. And similarly, determining the stator flux linkage value corresponding to the minimum value of each current loss value as a target stator flux linkage value until the more times of the flux linkage set reach the preset times. Therefore, the stator flux linkage value obtained from the flux linkage set can further reduce the motor loss through iteration and optimization of the flux linkage set, and further reduce the energy loss of the electric drive system.
In some embodiments, updating the flux linkage set according to each of the stator flux linkage values corresponding one-to-one to each of the target loss values of each of the current loss values that is less than a preset loss includes:
and updating the flux linkage set by adopting a particle swarm optimization algorithm according to the stator flux linkage values corresponding to the target loss values one by one.
In some embodiments, a particle swarm optimization algorithm may be employed to update the flux linkage set. By way of example, any one of the stator flux linkages may be defined as a particle, in which case the flux linkage set represents a group of particles.
In the kth flux linkage set updating process, after each stator flux linkage value corresponding to each target loss value is obtained, each stator flux linkage value corresponding to each target loss value can be used as a particle, the global optimal position of actual iteration is searched, the global optimal position is compared with the optimal solution of the previous iteration, the last generation of optimal solution is reserved or the optimal solution is updated, new particles are formed based on the updated position, namely, new stator flux linkage values are added to the flux linkage set, the (k+1) th flux linkage set updating is carried out by utilizing the new flux linkage set until the updating times reach the preset times, and the stator flux linkage value which enables the loss value of the loss model to be minimum is selected from the flux linkage set and used as the target flux linkage value to update the stator flux linkage of the motor.
The control adjustment device of the electric drive system provided by the application is described below, and the control adjustment device of the electric drive system described below and the control adjustment method of the electric drive system described above can be referred to correspondingly.
In one embodiment, as shown in fig. 3, there is provided a control adjustment device of an electric drive system, including:
A control parameter obtaining module 210, configured to obtain, from a control parameter set of a pre-constructed torque control model, a target control parameter that minimizes an electromagnetic torque error between a preset torque and an actual torque of a motor in the electric drive system;
A control parameter adjustment module 220, configured to adjust a control parameter of a motor controller in the electric drive system according to the target control parameter;
the torque control model is used for adjusting the torque of the motor, the control parameter set comprises a plurality of groups of control parameters, and one group of control parameters comprises a proportional gain parameter and an integral time parameter.
The target control parameter which minimizes the electromagnetic torque error between the preset torque and the actual torque of the motor in the electric drive system is obtained from the control parameter set of the torque control model for adjusting the motor torque of the electric drive system, so that the control parameter of the motor controller in the electric drive system is adjusted according to the target control parameter, the electric drive system can achieve better step response output, the accuracy of motor torque control is improved, and the energy loss of the electric drive system is reduced.
In one embodiment, the control parameter obtaining module 210 is specifically configured to:
And adjusting a control parameter set of the torque control model for multiple times, wherein each adjustment is based on the preset torque, the electromagnetic torque error of the motor when the torque control model outputs a control signal last time, and each group of current control parameters in the control parameter set, after each torque error corresponding to each group of current control parameters one by one is obtained, determining that the minimum value of each torque error is the electromagnetic torque error of the motor when the torque control model outputs the control signal next time, and updating the control parameter set according to each group of current control parameters corresponding to each target torque error smaller than the preset error in each torque error one by one until the adjustment times of the control parameter set reach the preset times, and determining one group of current control parameters corresponding to the minimum value of each torque error as the target control parameter.
In one embodiment, the control parameter obtaining module 210 is specifically configured to:
and updating the control parameter set by adopting a particle swarm optimization algorithm according to each group of current control parameters corresponding to each target torque error one by one.
In an embodiment, the control parameter adjustment module 220 is further configured to:
Obtaining a target stator flux linkage value which minimizes a loss value of the loss model from a flux linkage set of the motor according to the loss model of the motor;
Determining a stator flux linkage of the motor according to the target stator flux linkage value;
wherein the set of flux linkages comprises a plurality of stator flux linkage values.
In one embodiment, the control parameter adjustment module 220 is specifically configured to:
And inputting each stator flux linkage value of the flux linkage set into the loss model for multiple times, after each current loss value which is output by the loss model and corresponds to each stator flux linkage value one by one is obtained, updating the flux linkage set according to each stator flux linkage value which corresponds to each target loss value which is smaller than the preset loss in each current loss value one by one, until the more times of the flux linkage set reach the preset times, and determining the stator flux linkage value which corresponds to the minimum value of each current loss value as the target stator flux linkage value.
In one embodiment, the control parameter adjustment module 220 is specifically configured to:
and updating the flux linkage set by adopting a particle swarm optimization algorithm according to the stator flux linkage values corresponding to the target loss values one by one.
In one embodiment, the preset torque is determined according to a vehicle model of a vehicle on which the electric drive system is mounted.
Fig. 4 illustrates a physical schematic diagram of an electronic device, as shown in fig. 4, which may include: processor 810, communication interface (Communication Interface) 820, memory 830, and communication bus 840, wherein processor 810, communication interface 820, memory 830 accomplish communication with each other through communication bus 840. The processor 810 may call a computer program in the memory 830 to perform a control adjustment method of an electric drive system, for example, including:
acquiring a target control parameter for minimizing an electromagnetic torque error between a preset torque and an actual torque of a motor in an electric drive system from a control parameter set of a pre-constructed torque control model;
according to the target control parameters, adjusting control parameters of a motor controller in the electric drive system;
the torque control model is used for adjusting the torque of the motor, the control parameter set comprises a plurality of groups of control parameters, and one group of control parameters comprises a proportional gain parameter and an integral time parameter.
Further, the logic instructions in the memory 830 described above may be implemented in the form of software functional units and may be stored in a computer-readable storage medium when sold or used as a stand-alone product. Based on this understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method of the embodiments of the present application. And the aforementioned storage medium includes: a usb disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
In another aspect, an embodiment of the present application further provides a storage medium, where the storage medium includes a computer program, where the computer program may be stored on a non-transitory computer readable storage medium, and when the computer program is executed by a processor, the computer may execute the control adjustment method of the electric drive system provided in the foregoing embodiments.
The apparatus embodiments described above are merely illustrative, wherein elements illustrated as separate elements may or may not be physically separate, and elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on this understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method described in the respective embodiments or some parts of the embodiments.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present application, and are not limiting; although the application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application.
Claims (10)
1. A control adjustment method of an electric drive system, comprising:
acquiring a target control parameter for minimizing an electromagnetic torque error between a preset torque and an actual torque of a motor in an electric drive system from a control parameter set of a pre-constructed torque control model;
according to the target control parameters, adjusting control parameters of a motor controller in the electric drive system;
the torque control model is used for adjusting the torque of the motor, the control parameter set comprises a plurality of groups of control parameters, and one group of control parameters comprises a proportional gain parameter and an integral time parameter.
2. The control adjustment method of an electric drive system according to claim 1, wherein obtaining a target control parameter that minimizes an electromagnetic torque error between a preset torque and an actual torque of a motor in the electric drive system from a control parameter set of a pre-constructed torque control model, comprises:
And adjusting a control parameter set of the torque control model for multiple times, wherein each adjustment is based on the preset torque, the electromagnetic torque error of the motor when the torque control model outputs a control signal last time, and each group of current control parameters in the control parameter set, after each torque error corresponding to each group of current control parameters one by one is obtained, determining that the minimum value of each torque error is the electromagnetic torque error of the motor when the torque control model outputs the control signal next time, and updating the control parameter set according to each group of current control parameters corresponding to each target torque error smaller than the preset error in each torque error one by one until the adjustment times of the control parameter set reach the preset times, and determining one group of current control parameters corresponding to the minimum value of each torque error as the target control parameter.
3. The control adjustment method of an electric drive system according to claim 2, wherein updating the control parameter set according to each set of current control parameters corresponding one-to-one to each target torque error among the torque errors being smaller than a preset error, comprises:
and updating the control parameter set by adopting a particle swarm optimization algorithm according to each group of current control parameters corresponding to each target torque error one by one.
4. A control adjustment method of an electric drive system according to any one of claims 1to 3, characterized by further comprising:
Obtaining a target stator flux linkage value which minimizes a loss value of the loss model from a flux linkage set of the motor according to the loss model of the motor;
Determining a stator flux linkage of the motor according to the target stator flux linkage value;
wherein the set of flux linkages comprises a plurality of stator flux linkage values.
5. The control adjustment method of an electric drive system according to claim 4, wherein obtaining a target stator flux linkage value that minimizes a loss model of the motor from a flux linkage set of the motor according to the loss model, comprises:
And inputting each stator flux linkage value of the flux linkage set into the loss model for multiple times, after each current loss value which is output by the loss model and corresponds to each stator flux linkage value one by one is obtained, updating the flux linkage set according to each stator flux linkage value which corresponds to each target loss value which is smaller than the preset loss in each current loss value one by one, until the more times of the flux linkage set reach the preset times, and determining the stator flux linkage value which corresponds to the minimum value of each current loss value as the target stator flux linkage value.
6. The control adjustment method of an electric drive system according to claim 5, wherein updating the flux linkage set according to each of the stator flux linkage values corresponding one-to-one to each of the target loss values of each of the current loss values that is smaller than a preset loss, comprises:
and updating the flux linkage set by adopting a particle swarm optimization algorithm according to the stator flux linkage values corresponding to the target loss values one by one.
7. A control adjustment method of an electric drive system according to any one of claims 1-3, characterized in that the preset torque is determined from a vehicle model of a vehicle on which the electric drive system is mounted.
8. A control adjustment device of an electric drive system, comprising:
The control parameter acquisition module is used for acquiring target control parameters which enable the electromagnetic torque error between the preset torque and the actual torque of the motor in the electric drive system to be minimum from a control parameter set of a pre-constructed torque control model;
the control parameter adjustment module is used for adjusting the control parameters of a motor controller in the electric drive system according to the target control parameters;
the torque control model is used for adjusting the torque of the motor, the control parameter set comprises a plurality of groups of control parameters, and one group of control parameters comprises a proportional gain parameter and an integral time parameter.
9. An electronic device comprising a processor and a memory storing a computer program, characterized in that the processor implements the control adjustment method of the electric drive system according to any one of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the control adjustment method of an electric drive system according to any one of claims 1 to 7.
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| JP2011259666A (en) * | 2010-06-11 | 2011-12-22 | Jtekt Corp | Motor controller |
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| JP2011259666A (en) * | 2010-06-11 | 2011-12-22 | Jtekt Corp | Motor controller |
| CN106357185A (en) * | 2016-11-15 | 2017-01-25 | 吉林大学 | Permanent magnet synchronous motor torque control method |
| CN108551287A (en) * | 2018-03-21 | 2018-09-18 | 中国人民解放军海军工程大学 | Built-in automotive PMSM Drive System torque closed loop control method |
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