CN113595465A - Energy consumption optimization control method and system for motor driving system - Google Patents

Energy consumption optimization control method and system for motor driving system Download PDF

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CN113595465A
CN113595465A CN202110908818.3A CN202110908818A CN113595465A CN 113595465 A CN113595465 A CN 113595465A CN 202110908818 A CN202110908818 A CN 202110908818A CN 113595465 A CN113595465 A CN 113595465A
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inverter
energy consumption
motor
level state
sampling period
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彭涛
黄啸林
杨超
徐琰淞
廖宇新
徐立恩
韩露
陶宏伟
高锦秋
樊欣宇
陈志文
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Central South University
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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
    • H02P21/00—Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
    • H02P21/22—Current control, e.g. using a current control loop
    • 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
    • H02P21/00—Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
    • H02P21/14—Estimation or adaptation of machine parameters, e.g. flux, current or voltage
    • 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
    • H02P27/00—Arrangements or methods for the control of AC motors characterised by the kind of supply voltage
    • H02P27/04—Arrangements or methods for the control of AC motors characterised by the kind of supply voltage using variable-frequency supply voltage, e.g. inverter or converter supply voltage
    • H02P27/06—Arrangements or methods for the control of AC motors characterised by the kind of supply voltage using variable-frequency supply voltage, e.g. inverter or converter supply voltage using dc to ac converters or inverters

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Abstract

The invention discloses an energy consumption optimization control method and system of a motor driving system, which are characterized in that a predicted motor current of the next period and energy consumption of each inverter power device of the next period are obtained by obtaining a real-time motor current and a reference motor current of the current period of the motor driving system and respectively inputting the real-time motor current into a motor current prediction model and an energy consumption prediction model of each inverter power device; inputting the reference motor current, the predicted motor current and the energy consumption of each inverter power device into a multi-target optimization control model taking minimum current tracking, total inverter energy consumption reduction and inverter energy consumption balance as optimal control strategies to obtain the optimal control strategy for regulating and controlling the real-time motor current value to the reference motor current value; and controlling the motor driving system according to the switching state of each inverter bridge arm corresponding to the optimal control strategy. The method can ensure higher current control performance of the motor driving system, reduce the total energy consumption of the inverter and improve the energy consumption balance performance of the inverter.

Description

Energy consumption optimization control method and system for motor driving system
Technical Field
The invention relates to the technical field of power electronics, in particular to a method and a system for optimally controlling energy consumption of a motor driving system.
Background
Safe and reliable operation of high-speed trains is an important problem in rail transit development. However, the running environment of the high-speed train is severe, and aging of the parts and the like which may be caused by long-term running brings serious potential safety hazards to the running of the rail transit vehicle. The motor driving system is known as the heart of rail transit equipment/system, not only is the core power unit of the whole high-speed train, but also is one of the key systems for safe and reliable operation. The key components of the inverter, the motor and the like are high-fault sources of a motor driving system, wherein an Insulated Gate Bipolar Transistor (IGBT) of a power device is one of the weakest devices in the inverter, so that the problem of loss reduction research of the power device, the motor and the like is not negligible.
The power device IGBT becomes a device with the highest fault occurrence rate due to the influence of junction temperature fluctuation and the like, the IGBT loss is often closely related to the junction temperature, the IGBT conduction duration and the switching times are different, and the energy consumption and the service life consumption are different. The bonding wire of a certain power device in the inverter is aged and broken to cause the inverter to break down, and after the power device with the fault is replaced, other devices are easily damaged due to the fact that the service life consumption degree of the power device is different from that of other power devices which are not replaced, and the inverter breaks down again. In order to ensure the safe and reliable operation of the inverter, all power devices are usually replaced at one time due to the failure of one power device, which causes great waste of equipment and resources. As the core equipment of the motor driving system, the motor can cause the motor winding and the rotor to generate heat due to the increase of copper loss and iron loss of the motor, so that the resistance of the armature winding of the motor is increased, the inductance of the winding is reduced, the loss of the whole motor driving system is further increased, and when the heat is serious, the insulation of the armature winding is damaged, the motor can be burnt, and the fault or even the failure of train equipment is caused. How to realize the reduction of the motor loss, the balance of the inverter energy consumption and the reduction of the energy consumption under the condition of not influencing the control performance of a motor driving system becomes a key technology to be solved urgently.
Disclosure of Invention
The invention provides an energy consumption optimization control method and system for a motor driving system, which are used for solving the technical problem that the existing motor driving system cannot give consideration to both control performance and inverter energy consumption balance/energy consumption reduction.
In order to solve the technical problems, the technical scheme provided by the invention is as follows:
an energy consumption optimization control method for a motor driving system comprises the following steps:
acquiring a real-time motor current and a reference motor current of the motor driving system in the current period, and respectively inputting the real-time motor current into a motor current prediction model and each inverter power device energy consumption prediction model to obtain a predicted motor current of the next period and each inverter power device energy consumption of the next period;
inputting the reference motor current, the predicted motor current and the energy consumption of each inverter power device into a multi-target optimization control model taking minimum current tracking, total inverter energy consumption reduction and inverter energy consumption balance as optimal control strategies to obtain an optimal control strategy for regulating and controlling the real-time motor current value to a reference motor current value;
and controlling the motor driving system according to the switching state of each inverter bridge arm corresponding to the optimal control strategy.
Preferably, the multi-objective optimization control model includes: the system comprises a motor current tracking control optimization model, an inverter total energy consumption control optimization model, an inverter energy consumption balance control optimization model and a reward function optimization model for multi-objective optimization control of the motor current tracking control optimization model, the inverter total energy consumption control optimization model and the inverter energy consumption balance control optimization model.
Preferably, the motor current tracking control optimization model is as follows:
Ji[k](mi)＝min{gi[k](m)}
gi[k](m)＝{gi[k](m1),gi[k](m2),…,gi[k](mn),…,gi[k](mN)}
gi[k](mn)＝λd·|id_full[k]-id[k+1](mn)|+λq·|iq_full[k]-iq[k+1](mn)|
in the formula, Ji[k](mi) Is the k th]Level state combination m in one system sampling periodiMotor current tracking control target minimum function value miIs the corresponding level state combination when the motor current tracking control objective function value is minimum, mi∈m；m＝{m1,m2,…,mn,…,mNN is 1,2, …, N is the total number of level state combinations, m represents the set composed of all possible level state combinations of each phase bridge arm of the inverter, and min { g {i[k](m) represents a value of a corresponding control objective function selected among all possible level state combinations m of the inverters of the total number N so that the control objective function value is minimum; k denotes the number of sampling periods, gi[k](mn) For the corresponding n level state combination m in the k system sampling periodnTracking the value of the control objective function by the motor current; lambda [ alpha ]d、λqAre d and q axes respectivelyWeight of absolute value of tracking error of motor current, id_full[k]、iq_full[k]Reference values of stator currents of d and q axes of the motor in a k system sampling period are respectively set; i.e. id[k+1](mn)、iq[k+1](mn) Respectively corresponding to the nth level state combination m in the (k + 1) th system sampling periodnPredicted motor current values of d and q axis stator currents.
Preferably, the model for optimizing the total energy consumption control of the inverter is as follows:
Jet[k](met)＝min{get[k](m)}
get[k](m)＝{get[k](m1),get[k](m2),…,get[k](mn),…,get[k](mN)}
Figure BDA0003202916740000021
wherein, Jet[k](met) For the level state combination m in the k system sampling periodetMinimum function value m of total energy consumption control target of inverteretThe corresponding level state combination is used when the total energy consumption control objective function value of the inverter is minimum; m iset∈m，m＝{m1,m2,…,mn,…, m N1,2, …, N, m represents a set composed of all possible level state combinations of inverter phase legs, get[k](mn) For the corresponding n level state combination m in the k system sampling periodnThe value of the control objective function of the total energy consumption control amount of the inverter of (1), Abs (·) is a total energy consumption control objective function based on an absolute value;
Figure BDA0003202916740000022
combining m for the jth power device of the ith phase bridge arm of the inverter in the corresponding nth level state in the (k + 1) th system sampling periodnJ is 1,2, …, J is the total number of bridge arm power devices of each phase of the inverter.
Preferably, the inverter energy consumption balance control optimization model is as follows:
Jeb[k](meb)＝min{geb[k](m)}
geb[k](m)＝{geb[k](m1),geb[k](m2),…,geb[k](mn),…,geb[k](mN)}
Figure BDA0003202916740000031
wherein, Jeb[k](meb) Is the k th]Level state combination m in one system sampling periodebLower inverter energy consumption balance control target minimum function value mebM is the corresponding level state combination when the inverter energy consumption balance control objective function value is minimumeb∈m；m＝{m1,m2,…,mn,…, m N1,2, …, N, m represents a set composed of all possible level state combinations of inverter phase legs, geb[k](mn) Is the k th]Corresponding n level state combination m in one system sampling periodnThe value of the control objective function of the inverter energy consumption balance control quantity is Var (-) which is the l-th phase bridge arm energy consumption balance control objective function based on the energy consumption variance;
Figure BDA0003202916740000032
combining m for the jth power device of the ith phase bridge arm of the inverter in the corresponding nth level state in the (k + 1) th system sampling periodnJ is 1,2, …, J is the total number of bridge arm power devices of each phase of the inverter.
Preferably, the reward function optimization model is as follows:
J[k](mz)＝max{H[k](m,mi,met,meb)}
H[k](m，mi,met,meb)＝{H[k](m1,mi,met,meb),H[k](m2,mi,met,meb),…,H[k](mn,mi,met,meb),…,H[k](mN,mi,met,meb)}
Figure BDA0003202916740000033
wherein, J [ k ]](mz) Represents the k th]Level state combination m in one system sampling periodzThe maximum function value of the following reward functions; m iszIs the combination of the level states, m, corresponding to the maximum value of the reward functionz∈m；m＝{m1,m2,…,mn,…, m N1,2, …, N, m represents a set composed of all possible level state combinations of each phase bridge arm of the inverter, m representsiM is a combination of level states corresponding to the minimum motor current tracking control objective function valueetM is a combination of level states corresponding to the minimum value of the target function of the total energy consumption control of the inverterebThe corresponding level state combination is used for ensuring that the inverter energy consumption balance control objective function value is minimum; h [ k ]](mn，mi，met，meb) Is the corresponding n level state combination m in the k system sampling periodnValue of the reward function of, mnRepresents the nth level state combination, max { H [ k ] k, in all possible level state combinations m of each phase bridge arm of the inverter](m，mi，met,meb) Expressing the value of a corresponding reward function when the value of the reward function is maximum in all possible level state combinations m of the inverters with the total number of N; lambda [ alpha ]i、βet、βebRespectively representing the weights of reward items of a current tracking control target, an inverter total energy consumption control target and an inverter energy consumption balance control target; gi[k](mn) For the corresponding n level state combination m in the k system sampling periodnTracking the value of the control objective function by the motor current; j. the design is a squarei[k](mi) For the level state combination m in the k system sampling periodiTracking the minimum function value of a control target by the current of the lower motor; get[k](mn) For the corresponding n level state combination m in the k system sampling periodnThe value of the control objective function of the total inverter energy consumption control amount of (1); j. the design is a squareet[k](met) For the level state combination m in the k system sampling periodetThe minimum function value of the total energy consumption control target of the inverter is obtained; geb[k](mn) For the corresponding n level state combination m in the k system sampling periodnThe value of the control objective function of the inverter energy consumption balance control quantity; j. the design is a squareeb[k](meb) For the level state combination m in the k system sampling periodebAnd balancing and controlling the target minimum function value of the energy consumption of the inverter.
Preferably, the motor current prediction model is expressed as:
Figure BDA0003202916740000041
wherein, tsIs the sampling time of the system; m isnRepresents the nth level state combination in all possible level state combinations m of each phase bridge arm of the inverter, wherein m is { m ═ m1,m2,…,mn,…,mNN is 1,2, …, N is the total number of level state combinations,
Figure BDA0003202916740000042
Figure BDA0003202916740000043
respectively representing the level states of the inverter U, V, W phase legs corresponding to the nth combination of level states in the kth system sampling period,
Figure BDA0003202916740000044
l is the bridge arm of the inverter, 1,2, 3; i.e. id[k+1](mn)、iq[k+1](mn) Respectively corresponding to the nth level state combination m in the (k + 1) th system sampling periodnPredicting the stator current of d and q axes; u. ofd[k](mn)、uq[k](mn) Are respectively at the k-thCorresponding n level state combination m in one system sampling periodnCalculated values of d and q axis voltages of the motor; i.e. id[k]、iq[k]Respectively, the calculated values of the stator currents of the d and q axes of the motor in the k system sampling period are expressed as follows:
Figure BDA0003202916740000051
wherein, θ [ k ]]Representing the electrical angle of the system during the kth system sampling period; i.e. ia[k]、ib[k]、ic[k]Respectively representing the current measurement values flowing through the U, V, W phase bridge arm of the inverter in the kth system sampling period;
wherein u isd[k](mn)、uq[k](mn) The calculation formula is as follows:
Figure BDA0003202916740000052
wherein, UdcIn order to control the dc voltage of the inverter,
Figure BDA0003202916740000053
is mnThe transpose of (a) is performed,
Figure BDA0003202916740000054
preferably, the energy consumption prediction model of the inverter power device is as follows:
Figure BDA0003202916740000055
in the formula (I), the compound is shown in the specification,
Figure BDA0003202916740000056
combining m for the jth power device of the ith phase bridge arm of the inverter in the corresponding nth level state in the (k + 1) th system sampling periodnJ is 1,2, …, J is the total of each phase bridge arm power device of the inverterCounting;
Figure BDA0003202916740000057
is shown at [ k ]]Level state i of the I-phase bridge arm of the inverter corresponding to the n-th level state combination in each system sampling periodl[k+1](mn) For the corresponding n level state combination m in the k +1 system sampling periodnThe predicted value of the current flowing through the first phase bridge arm of the inverter is obtained; t islj[k]The junction temperature of the jth power device of the ith phase bridge arm in the kth system sampling period;
Figure BDA0003202916740000058
and
Figure BDA0003202916740000059
respectively serving as a conduction loss function and a switching loss function of the jth power device of the ith phase bridge arm of the inverter and a current predicted value i flowing through the ith phase bridge arm of the inverter in the (k + 1) th system sampling periodl[k+1](mn) And the self junction temperature T of the power device in the k system sampling periodlj[k](ii) related;
Figure BDA00032029167400000510
and
Figure BDA00032029167400000511
respectively judging whether the jth power device generates conduction loss and switching loss; wherein il[k+1](mn) (l ═ 1,2,3) the formula:
Figure BDA00032029167400000512
preferably, the reference motor current is a reference motor current in a full-speed range, and the full-speed range refers to a range from 0 to a rated speed of the motor, and includes a low-speed range and a high-speed range; the low speed range refers to the time when the running speed of the motor is lower than 30% of the rated speed; the high-speed range refers to the time when the running speed of the motor is higher than 30% of the rated speed and lower than the rated speed; the reference motor current in the full-speed domain is obtained through the following model:
Figure BDA0003202916740000061
wherein id_full[k]、iq_full[k]Respectively in the full-speed domain]Reference values of stator currents of d and q axes of the motor in a system sampling period; omega [ k ]]Is the [ k ]]Actual electrical angular velocity within a system sampling period; omegasIs the nominal electrical angular velocity; i.e. id_mtpa[k]、iq_mtpa[k]Respectively in the low speed range]Reference values of stator currents of d and q axes of the motor in a system sampling period; i.e. id_lmc[k]、iq_lmc[k]Respectively in the high speed range]Reference values of stator currents of d and q axes of the motor in a system sampling period;
wherein the content of the first and second substances,
Figure BDA0003202916740000062
wherein, Te[k]Is the [ k ]]Motor torque and actual electrical angular velocity ω k within a system sampling period](ii) related; a. thed、Bd、CdAnd DdRespectively reflecting motor torque T of a motor d-axis stator current reference value in a low-speed rangee[k]Coefficients of the cubic term, quadratic term, primary term, and constant term of (d); a. theq、Bq、CqAnd DqRespectively reflecting motor torque T of a motor q-axis stator current reference value in a low-speed rangee[k]Coefficients of the cubic term, quadratic term, primary term, and constant term of (d);
wherein the content of the first and second substances,
Figure BDA0003202916740000063
wherein psifIs a flux linkage; n ispIs the number of pole pairs of the motor; l isd、LqInductors of d and q axes respectively; rcIs an equivalent iron loss resistance; γ is a weighted average parameter, expressed as:
Figure BDA0003202916740000064
in the formula, RsIs the armature winding resistance.
A computer system comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the steps of the method being performed when the computer program is executed by the processor.
The invention has the following beneficial effects:
1. according to the energy consumption optimization control method and system for the motor driving system, the real-time motor current and the reference motor current of the current period of the motor driving system are obtained, and the real-time motor current is respectively input into a motor current prediction model and energy consumption prediction models of inverter power devices, so that the predicted motor current of the next period and the energy consumption of the inverter power devices of the next period are obtained; inputting the reference motor current, the predicted motor current and the energy consumption of each inverter power device into a multi-target optimization control model taking minimum current tracking, total inverter energy consumption reduction and inverter energy consumption balance as optimal control strategies to obtain the optimal control strategy for regulating and controlling the real-time motor current value to the reference motor current value; and controlling the motor driving system according to the switching state of each inverter bridge arm corresponding to the optimal control strategy. The method can ensure higher current control performance of the motor driving system, reduce the total energy consumption of the inverter and improve the energy consumption balance performance of the inverter.
2. In the preferred scheme, the invention constructs a full-speed domain motor current reference value calculation model and dynamically sets the reference value of current tracking optimization control; on the basis, the optimization aims of high system current control performance, low motor loss, high inverter energy consumption balance performance and low inverter energy consumption are taken as optimization targets, and the energy consumption optimization control of the motor driving system is realized. The method is easy to implement, additional hardware equipment is not needed, the energy consumption of the motor, the inverter and even the motor driving system can be reduced, the running reliability level of the motor driving system is improved, and the equipment maintenance cost is reduced.
In addition to the objects, features and advantages described above, other objects, features and advantages of the present invention are also provided. The present invention will be described in further detail below with reference to the accompanying drawings.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the invention and, together with the description, serve to explain the invention and not to limit the invention. In the drawings:
fig. 1 is a flow chart of a method and a system for optimizing and controlling energy consumption of a motor driving system according to the present invention.
Fig. 2 is a topological structure diagram of a motor drive system according to an embodiment of the present invention.
Fig. 3 is a schematic block diagram of the overall control of the motor drive system according to the embodiment of the present invention.
Fig. 4 is a schematic diagram of changes of copper loss and iron loss before and after the energy consumption optimization control method for the motor driving system is adopted in the embodiment of the present invention.
Fig. 5 is a schematic diagram of energy consumption change of 4 power devices of the front and rear U-phase bridge arms by using the energy consumption optimization control method of the motor drive system in the embodiment of the present invention.
Fig. 6 is a schematic diagram of temperature fluctuations of 4 power devices of the front and rear U-phase bridge arms by using a method for optimizing and controlling energy consumption of the motor driving system in the embodiment of the present invention.
Detailed Description
The embodiments of the invention will be described in detail below with reference to the drawings, but the invention can be implemented in many different ways as defined and covered by the claims.
The first embodiment is as follows:
the implementation discloses an energy consumption optimization control method for a motor driving system, which comprises the following steps:
the method comprises the steps of obtaining a real-time motor current and a reference motor current of a current period of a motor driving system, and respectively inputting the real-time motor current into a motor current prediction model and energy consumption prediction models of inverter power devices to obtain a predicted motor current of a next period and energy consumption of the inverter power devices of the next period;
inputting the reference motor current, the predicted motor current and the energy consumption of each inverter power device into a multi-target optimization control model taking minimum current tracking, total inverter energy consumption reduction and inverter energy consumption balance as optimal control strategies to obtain the optimal control strategy for regulating and controlling the real-time motor current value to the reference motor current value;
and controlling the motor driving system according to the switching state of each inverter bridge arm corresponding to the optimal control strategy. In this embodiment, the switching state of each inverter leg specifically refers to a switching level of each inverter leg.
In addition, in the embodiment, a computer system is also disclosed, which includes a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the computer program, the steps of the method are implemented.
According to the energy consumption optimization control method and system for the motor driving system, the real-time motor current and the reference motor current of the current period of the motor driving system are obtained, and the real-time motor current is respectively input into a motor current prediction model and energy consumption prediction models of inverter power devices, so that the predicted motor current of the next period and the energy consumption of the inverter power devices of the next period are obtained; inputting the reference motor current, the predicted motor current and the energy consumption of each inverter power device into a multi-target optimization control model taking minimum current tracking, total inverter energy consumption reduction and inverter energy consumption balance as optimal control strategies to obtain the optimal control strategy for regulating and controlling the real-time motor current value to the reference motor current value; and controlling the motor driving system according to the switching state of each inverter bridge arm corresponding to the optimal control strategy. The method can ensure higher current control performance of the motor driving system, and simultaneously reduce the total energy consumption of the inverter/improve the energy consumption balance performance of the inverter.
Example two:
the second embodiment is the preferred embodiment of the first embodiment, and the difference between the first embodiment and the second embodiment is that the specific steps of the energy consumption optimization control method of the motor driving system are refined:
in this embodiment, referring to a three-level permanent magnet synchronous motor driving system of a certain high-speed train, a topological structure of the motor driving system is shown in fig. 2, and the motor driving system includes: drive controller, permanent magnet synchronous machine and three-phase three-level inverter, wherein drive controller includes: a reference value setter, an optimization controller and a current/speed sensor. In this embodiment, energy consumption performance optimization control of a three-phase three-level inverter is taken as an example for explanation, a motor driving system adopts a rotating speed-current double closed-loop control structure, a control outer loop is a rotating speed loop, and a given value of electromagnetic torque of the system can be obtained through a lookup table according to rotating speed feedback; obtaining reference values of d-axis current and q-axis current of a motor stator through a full-speed domain motor current reference value calculation model, and taking the reference values as given input of a current inner loop control strategy; the method is characterized in that a level state combination which enables a reward function value to be maximum is selected as a system control instruction to be output according to a minimum current tracking strategy, an inverter energy consumption balancing strategy and an energy consumption reduction optimization strategy, so that the purposes of high system current control performance, low motor loss, high inverter energy consumption balancing performance and low inverter energy consumption optimization are achieved, and a control principle block diagram is shown in fig. 3.
TABLE 1 Main parameters of three-level inverter System
Parameter(s) Numerical value
Stator resistance Rs 0.07Ω
Stator d-axis inductance Ld 0.0037H
Stator q-axis inductance Lq 0.0096H
Permanent magnet flux linkage psif 0.625Wb
Number of pole pairs np 4
Given DC voltage 3600V
Rated power of embedded permanent magnet synchronous motor 600kW
System sampling period ts 40μs
As shown in fig. 1, the method and system for optimally controlling energy consumption of a motor driving system provided by the embodiment of the present application includes the following steps:
step S1: constructing a full-speed domain motor current reference value calculation model; the reference value is used for dynamically setting the motor current tracking optimization control in each sampling period;
it should be noted that, as shown in fig. 3, the energy consumption optimization control method of the motor driving system in this embodiment is in a current loop control link in a rotating speed-current double closed-loop control structure. More specifically, the full-speed-domain motor current reference value calculation model constructed in this embodiment is located in a current outer loop control link in a rotating speed-current double closed-loop control structure, and the energy consumption optimization strategy for the minimum-equalization inverter is located in a current inner loop control link in the rotating speed-current double closed-loop control structure. Therefore, the system control amount in the embodiment is d-axis current and q-axis current of the stator of the permanent magnet synchronous motor and energy consumption of the inverter.
S11, constructing a full-speed domain motor current reference value calculation model, which is expressed as:
Figure BDA0003202916740000091
wherein id_full[k]、iq_full[k]Reference values of stator currents of d and q axes of the motor in a kth system sampling period in a full-speed domain respectively; omega [ k ]]Is the actual electrical angular velocity in the kth system sampling period; omegasIs the nominal electrical angular velocity; i.e. id_mtpa[k]、iq_mtpa[k]Reference values of stator currents of d and q axes of the motor in a kth system sampling period in a low-speed range respectively; i.e. id_lmc[k]、iq_lmc[k]Reference values of stator currents of d and q axes of the motor in a kth system sampling period in a high-speed range respectively;
s12, constructing a first motor current reference value calculation model in a low-speed range, wherein the first motor current reference value calculation model is expressed as:
Figure BDA0003202916740000101
wherein T ise[k]Is the [ k ]]Motor torque and actual electrical angular velocity ω k within a system sampling period](ii) related; a. thed、Bd、CdAnd DdRespectively reflecting motor torque T of a motor d-axis stator current reference value in a low-speed rangee[k]Coefficients of the cubic term, quadratic term, primary term, and constant term of (d); a. theq、Bq、CqAnd DqRespectively reflecting motor torque T of a motor q-axis stator current reference value in a low-speed rangee[k]The third, second, first and constant terms of the coefficient.
In the present embodiment, the given value T is based on the electromagnetic torque of the systeme[k]Through the lookup table, the coefficient values of the respective parameters in the first parameter of the table can be obtained, and the first motor current reference value calculation model is expressed as:
Figure BDA0003202916740000102
and S13, constructing a second motor current reference value calculation model in a high-speed range, wherein the second motor current reference value calculation model is expressed as:
Figure BDA0003202916740000103
wherein psifIs a flux linkage; n ispIs the number of pole pairs of the motor; l isd、LqInductors of d and q axes respectively; rcIs an equivalent iron loss resistance; β is a weighted average parameter, expressed as:
Figure BDA0003202916740000104
in the formula RsIs the armature winding resistance.
Step S2: constructing a motor current prediction model and an inverter power device energy consumption prediction model;
s21: constructing a motor current prediction model expressed as:
Figure BDA0003202916740000105
wherein t issIs the sampling time of the system; m isnRepresents the nth level state combination in all possible level state combinations m of each phase bridge arm of the inverter, wherein m is { m ═ m1,m2,…,mn,…,mNN is 1,2, …, N is the total number of level state combinations,
Figure BDA0003202916740000111
Figure BDA0003202916740000112
respectively representing the level states of the inverter U, V, W phase legs corresponding to the nth combination of level states in the kth system sampling period,
Figure BDA0003202916740000113
l is the bridge arm of the inverter, 1,2, 3; i.e. id[k+1](mn)、iq[k+1](mn) Respectively corresponding to the N (N is 1,2, …, N) level state combination m in the k +1 system sampling periodnPredicting the stator current of d and q axes; u. ofd[k](mn)、uq[k](mn) Are respectively at the k-th]Corresponding N (N is 1,2, …, N) level state combination m in one system sampling periodnCalculated values of d and q axis voltages of the motor; i.e. id[k]、iq[k]Respectively, the calculated values of the stator currents of the d and q axes of the motor in the k system sampling period are expressed as follows:
Figure BDA0003202916740000114
wherein θ [ k ]]Representing the electrical angle of the system during the kth system sampling period; i.e. ia[k]、ib[k]、ic[k]Respectively represent the k-th]The current measurements flowing through the inverter U, V, W phase leg during each system sampling period.
ud[k](mn)、uq[k](mn) The calculation formula is as follows:
Figure BDA0003202916740000115
wherein, UdcIn order to control the dc voltage of the inverter,
Figure BDA0003202916740000116
is mnThe transpose of (a) is performed,
Figure BDA0003202916740000117
s22: constructing an energy consumption prediction model of the inverter power device, wherein the expression is as follows:
Figure BDA0003202916740000118
in the formula (I), the compound is shown in the specification,
Figure BDA0003202916740000119
corresponding to the nth (N is 1,2, …, N) level state combination m in the (k + 1) th system sampling period for the jth power device of the ith phase bridge arm of the inverternJ is 1,2, …, J is the total number of bridge arm power devices of each phase of the inverter; i.e. il[k+1](mn) For the N (N is 1,2, …, N) th level state combination m in the k +1 th system sampling periodnThe predicted value of the current flowing through the first phase bridge arm of the inverter is obtained; t islj[k]The junction temperature of the jth power device of the ith phase bridge arm in the kth system sampling period;
Figure BDA0003202916740000121
and
Figure BDA0003202916740000122
respectively serving as a conduction loss function and a switching loss function of the jth power device of the ith phase bridge arm of the inverter and a current predicted value i flowing through the ith phase bridge arm of the inverter in the (k + 1) th system sampling periodl[k+1](mn) And the self junction temperature T of the power device in the k system sampling periodlj[k](ii) related;
Figure BDA0003202916740000123
and
Figure BDA0003202916740000124
respectively judging whether the jth power device generates conduction loss and switching loss;
il[k+1](mn) (l ═ 1,2,3) the formula:
Figure BDA0003202916740000125
in the present embodiment, the expression
Figure BDA0003202916740000126
And
Figure BDA0003202916740000127
the expression of (a) may be a fitting function, the fitted data being from a power module vendor user data manual.
In this embodiment, the function of determining whether the conduction loss and the switching loss are generated is determined
Figure BDA0003202916740000128
And
Figure BDA0003202916740000129
the expression of (a) may be consistent with the description in the prior art, and is not described herein.
In this embodiment, the three-level inverter has three-phase arms (l ═ 1,2, and 3), which are a U-phase arm, a V-phase arm, and a W-phase arm, respectively, each of the three-phase arms is composed of four power devices, and J ═ 1,2, …, J, and J ═ 4, as shown in fig. 2. Normally, each bridge arm has three level states, in this embodiment,
Figure BDA00032029167400001210
the level states of the inverter U, V, W phase bridge arms corresponding to the nth level state combination in the kth system sampling period respectively. Specifically, in this embodiment, the level state of the l-th phase bridge arm in the k-th system sampling period corresponding to the n-th level state combination
Figure BDA00032029167400001211
Can be expressed as:
Figure BDA00032029167400001212
in the formula (I), the compound is shown in the specification,
Figure BDA00032029167400001213
and
Figure BDA00032029167400001214
the control signals respectively represent the control signals for determining the on-off states of the 1 st, 2 nd, 3 th and 4 th power devices of the l-th phase bridge arm under the corresponding nth level state combination in the kth system sampling period, wherein "1" represents that the control power device is in an on state, and "0" represents that the control power device is in an off state, and the corresponding relation is shown in fig. 2.
Step S3: respectively constructing a motor current tracking control objective function, an inverter total energy consumption control objective function and an inverter energy consumption balance control objective function;
s31: constructing a motor current tracking control objective function, wherein the expression of the motor current tracking control objective function is as follows:
gi[k](mn)＝λd·|id_full[k]-id[k+1](mn)|+λq·|iq_full[k]-iq[k+1](mn)|
in the formula (I); gi[k](mn) Is the k th]Corresponding N (N is 1,2, …, N) level state combination m in one system sampling periodnTracking the value of the control objective function by the motor current; lambda [ alpha ]d、λqWeights of absolute values of current tracking errors of the d-axis motor and the q-axis motor are respectively used;
the absolute value of the tracking error of the motor current is minimum, and the absolute value is taken as an optimization target of 'higher current control performance and lower motor loss', and the expression is as follows:
Ji[k](mi)＝min{gi[k](m)}
wherein, Ji[k](mi) Is the k th]Level state combination m in one system sampling periodiMotor current tracking control target minimum function value miIs the corresponding level state combination when the motor current tracking control objective function value is minimum, miE is m; min {. cndot.) represents a value of the corresponding control objective function selected from all possible level state combinations m of the inverters of which the total number is N so that the control objective function value is the minimum; gi[k](m)＝{gi[k](m1),gi[k](m2),…，gi[k](mn)，…，gi[k](mN)}。
In this embodiment, λ is defined asd＝0.3，λq＝0.7。
S32: constructing an inverter total energy consumption control objective function, wherein the expression is as follows:
Figure BDA0003202916740000131
in the formula, get[k](mn) Is the k th]Corresponding N (N is 1,2, …, N) level state combination m in one system sampling periodnThe value of the control objective function of the total energy consumption control amount of the inverter of (1), Abs (·) is a total energy consumption control objective function based on an absolute value;
the absolute value of the total energy consumption error of the inverter is minimum, and the absolute value is used as the minimum optimization target of the total energy consumption of the inverter, and the expression is as follows:
Jet[k](met)＝min{get[k](m)}
wherein Jet[k](met) Is the k th]Level state combination m in one system sampling periodetMinimum function value m of total energy consumption control target of inverteretIs the corresponding level state combination when the inverter total energy consumption control objective function value is minimum, met∈m；get[k](m)＝{get[k](m1),get[k](m2),…,get[k](mn),…,get[k](mN)}。
S33: constructing an inverter energy consumption balance control objective function, wherein the expression is as follows:
Figure BDA0003202916740000132
in the formula, geb[k](mn) Is the k th]Corresponding to N (N is 1,2, …, N, …, N) level state combination m in a system sampling periodnThe value of the control objective function of the inverter energy consumption balance control quantity is Var (-) which is the energy consumption balance control objective of the l-th phase bridge arm based on the energy consumption varianceA function;
the sum of energy consumption variances of bridge arms of the inverter is minimum, and the sum is used as an optimal control target for energy consumption balance of the inverter, and the expression is as follows:
Jeb[k](meb)＝min{geb[k](m)}
wherein, Jeb[k](meb) For the level state combination m in the k system sampling periodebLower inverter energy consumption balance control target minimum function value mebM is the corresponding level state combination when the inverter energy consumption balance control objective function value is minimumeb∈m；geb[k](m)＝{geb[k](m1),geb[k](m2),…,geb[k](mn),…,geb[k](mN)}。
Step S4: constructing a reward function; and selecting the level state combination which enables the value of the reward function to be maximum as the control output of the system, and realizing the energy consumption optimization control of the motor driving system.
S41: constructing a reward function, wherein the expression of the reward function is as follows:
Figure BDA0003202916740000141
in the formula, H [ k ]](m,mi,met,meb) Is the corresponding N (N is 1,2, …, N, …, N) level state combination m in the k system sampling periodnOf the reward function, λi、βet、βebAnd respectively representing the weights of the reward items of the current tracking control target, the inverter total energy consumption control target and the inverter energy consumption balance control target.
In this embodiment, λi＝1、βet＝0.2、βeb0.9. This is by way of example only and not by way of limitation.
S42: the reward function value is maximized and is used as the optimization target of higher current control performance of the motor driving system, lower motor loss, higher energy consumption balance performance of the inverter and lower total energy consumption of the inverter, and the expression of the reward function value is as follows:
J[k](mz)＝max{H[k](m,mi,met,meb)}
in the formula, J [ k ]](mz) Represents the k th]Level state combination m in one system sampling periodzThe maximum function value of the following reward functions; m iszIs the combination of the level states, m, corresponding to the maximum value of the reward functionzE is m; max {. cndot.) represents the value of the corresponding reward function when the value of the reward function is maximized by selecting all possible level state combinations m of the inverters with the total number of N; h [ [ k ]](m,mi,met,meb)＝{H[k](m1,mi,met,meb),H[k](m2,mi,met,meb),…,H[[k](mn,mi,met,meb),…,H[[k](mN,mi,met,meb)}。
In the k system sampling period, i is obtained by system sensor samplinga[k]、ib[k]、ic[k]、θ[k]And ω [ k ]](ii) a Further, i can be obtained by the outer loop control strategy of the systemd_full[k]And iq_full[k](ii) a In addition, ω can be obtained by system reference command/user setting*[k]。
Specifically, in this embodiment, when the system is operated at a certain stable speed (200km/h), no energy consumption optimization control method/strategy for the motor driving system is adopted (a full-speed-domain motor current reference value calculation model is adopted; and a corresponding weight coefficient λ is adopted)i＝1、βet＝0、βeb0) and motor drive system energy consumption optimization control method/strategy (full speed domain motor current reference value calculation model; corresponding weight coefficient lambdai＝1、βet＝0.2、βeb0.9) and the loss variation of the motor copper loss and the iron loss and the energy consumption variation of the U-phase four power modules, as shown in fig. 4 and 5. In order to better observe the equalization effect, the energy consumption change is converted into the temperature change, and the temperature change of the U-phase four power modules is observed, as shown in fig. 6. Therefore, compared with a motor driving system which does not adopt the energy consumption optimization control method/strategy of the motor driving system, the method can reduce the motor lossAnd meanwhile, the energy consumption distribution of the inverter system is more uniform, and the energy consumption of each power module of the bridge arm tends to be consistent. Compared with a motor driving system which does not adopt a motor driving system energy consumption optimization control method/strategy, the control method can reduce the motor loss and enable the energy consumption of each power module of the inverter to be similar. According to the relevant research results, the service life of the motor is prolonged, the service life consumption of each power module of the inverter tends to be similar, and the overall service life of the inverter can effectively avoid the effect of 'wooden barrel short plates', so that the service life of the inverter is prolonged.
In this optional embodiment, making the energy consumption difference among the power devices in the inverter module tend to be uniform means reducing the average energy consumption difference among the power devices in the inverter module. The total energy consumption of the power devices in the inverter module to be tested is reduced, the energy consumption difference among the power devices tends to be consistent, or the average energy consumption of a single power module is reduced, so that the average energy consumption difference of the power devices in the module is reduced to a preset threshold value. For example, the energy consumption generated by the power module in the inverter and the current path and voltage in the inverter can be regulated so as to regulate the energy consumption in the module, so that the energy consumption optimization of the inverter can be realized.
In summary, the energy consumption optimization control method of the motor driving system of the invention dynamically sets the reference value of current tracking optimization control by constructing a full-speed domain motor current reference value calculation model; on the basis, the optimization aims of high system current control performance, low motor loss, high inverter energy consumption balance performance and low inverter energy consumption are taken as optimization targets, and the energy consumption optimization control of the motor driving system is realized. The method is easy to implement, additional hardware equipment is not needed, the energy consumption of the motor, the inverter and even the motor driving system can be reduced, the running reliability level of the motor driving system is improved, and the equipment maintenance cost is reduced.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (10)

1. The energy consumption optimization control method of the motor driving system is characterized by comprising the following steps:
acquiring a real-time motor current and a reference motor current of the motor driving system in the current period, and respectively inputting the real-time motor current into a motor current prediction model and each inverter power device energy consumption prediction model to obtain a predicted motor current of the next period and each inverter power device energy consumption of the next period;
inputting the reference motor current, the predicted motor current and the energy consumption of each inverter power device into a multi-target optimization control model taking minimum current tracking, total inverter energy consumption reduction and inverter energy consumption balance as optimal control strategies to obtain an optimal control strategy for regulating and controlling the real-time motor current value to a reference motor current value;
and controlling the motor driving system according to the switching state of each inverter bridge arm corresponding to the optimal control strategy.
2. The motor drive system energy consumption optimization control method of claim 1, wherein the multi-objective optimization control model comprises: the system comprises a motor current tracking control optimization model, an inverter total energy consumption control optimization model, an inverter energy consumption balance control optimization model and a reward function optimization model for multi-objective optimization control of the motor current tracking control optimization model, the inverter total energy consumption control optimization model and the inverter energy consumption balance control optimization model.
3. The method for optimizing control of energy consumption of a motor drive system according to claim 2, wherein the motor current tracking control optimization model is:
Ji[k](mi)＝min{gi[k](m)}
gi[k](m)＝{gi[k](m1),gi[k](m2),…,gi[k](mn),…,gi[k](mN)}
gi[k](mn)＝λd·|id_full[k]-id[k+1](mn)|+λq·|iq_full[k]-iq[k+1](mn)|
in the formula, Ji[k](mi) Is the k th]Level state combination m in one system sampling periodiMotor current tracking control target minimum function value miIs the corresponding level state combination when the motor current tracking control objective function value is minimum, mi∈m；m＝{m1,m2,…,mn,…,mNN is 1,2, …, N is the total number of level state combinations, m represents the set composed of all possible level state combinations of each phase bridge arm of the inverter, and min { g {i[k](m) represents a value of a corresponding control objective function selected among all possible level state combinations m of the inverters of the total number N so that the control objective function value is minimum; k denotes the number of sampling periods, gi[k](mn) For the corresponding n level state combination m in the k system sampling periodnTracking the value of the control objective function by the motor current; lambda [ alpha ]d、λqWeights i of absolute values of current tracking errors of d-axis and q-axis motors respectivelyd_full[k]、iq_full[k]Reference values of stator currents of d and q axes of the motor in a k system sampling period are respectively set; i.e. id[k+1](mn)、iq[k+1](mn) Respectively corresponding to the nth level state combination m in the (k + 1) th system sampling periodnPredicted motor current values of d and q axis stator currents.
4. The motor drive system energy consumption optimization control method according to claim 2, wherein the inverter total energy consumption control optimization model is:
Jet[k](met)＝min{get[k](m)}
get[k](m)＝{get[k](m1),get[k](m2),…,get[k](mn),…,get[k](mN)}
Figure FDA0003202916730000021
wherein, Jet[k](met) For the level state combination m in the k system sampling periodetMinimum function value m of total energy consumption control target of inverteretThe corresponding level state combination is used when the total energy consumption control objective function value of the inverter is minimum; m iset∈m，m＝{m1,m2,…,mn,…,mN1,2, …, N, m represents a set composed of all possible level state combinations of inverter phase legs, get[k](mn) For the corresponding n level state combination m in the k system sampling periodnThe value of the control objective function of the total energy consumption control amount of the inverter of (1), Abs (·) is a total energy consumption control objective function based on an absolute value;
Figure FDA0003202916730000022
combining m for the jth power device of the ith phase bridge arm of the inverter in the corresponding nth level state in the (k + 1) th system sampling periodnJ is 1,2, …, J is the total number of bridge arm power devices of each phase of the inverter.
5. The method for optimally controlling the energy consumption of the motor driving system according to claim 2, wherein the optimal model for controlling the energy consumption balance of the inverter is as follows:
Jeb[k](meb)＝min{geb[k](m)}
geb[k](m)＝{geb[k](m1),geb[k](m2),…,geb[k](mn),…,geb[k](mN)}
Figure FDA0003202916730000023
wherein, Jeb[k](meb) Is the k th]Level state combination m in one system sampling periodebLower inverter energy consumption balance control target minimum function value mebM is the corresponding level state combination when the inverter energy consumption balance control objective function value is minimumeb∈m；m＝{m1,m2,…,mn,…,mN1,2, …, N, m represents a set composed of all possible level state combinations of inverter phase legs, geb[k](mn) Is the k th]Corresponding n level state combination m in one system sampling periodnThe value of the control objective function of the inverter energy consumption balance control quantity is Var (-) which is the l-th phase bridge arm energy consumption balance control objective function based on the energy consumption variance;
Figure FDA0003202916730000024
combining m for the jth power device of the ith phase bridge arm of the inverter in the corresponding nth level state in the (k + 1) th system sampling periodnJ is 1,2, …, J is the total number of bridge arm power devices of each phase of the inverter.
6. The method of claim 2, wherein the reward function optimization model is:
J[k](mz)＝max{H[k](m,mi,met,meb)}
H[k](m,mi,met,meb)＝{H[k](m1,mi,met,meb),H[k](m2,mi,met,meb),…,H[k](mn,mi,met,meb),…,H[k](mN,mi,met,meb)}
Figure FDA0003202916730000031
wherein, J [ k ]](mz) Represents the k th]Level state combination m in one system sampling periodzThe maximum function value of the following reward functions; m iszIs the combination of the level states, m, corresponding to the maximum value of the reward functionz∈m；m＝{m1,m2,…,mn,…,mN1,2, …, N, m represents a set composed of all possible level state combinations of each phase bridge arm of the inverter, m representsiM is a combination of level states corresponding to the minimum motor current tracking control objective function valueetM is a combination of level states corresponding to the minimum value of the target function of the total energy consumption control of the inverterebThe corresponding level state combination is used for ensuring that the inverter energy consumption balance control objective function value is minimum; h [ k ]](mn,mi,met,meb) Is the corresponding n level state combination m in the k system sampling periodnValue of the reward function of, mnRepresents the nth level state combination, max { H [ k ] k, in all possible level state combinations m of each phase bridge arm of the inverter](m,mi,met,meb) Expressing the value of a corresponding reward function when the value of the reward function is maximum in all possible level state combinations m of the inverters with the total number of N; lambda [ alpha ]i、βet、βebRespectively representing the weights of reward items of a current tracking control target, an inverter total energy consumption control target and an inverter energy consumption balance control target; gi[k](mn) For the corresponding n level state combination m in the k system sampling periodnTracking the value of the control objective function by the motor current; j. the design is a squarei[k](mi) For the level state combination m in the k system sampling periodiTracking the minimum function value of a control target by the current of the lower motor; get[k](mn) For the corresponding n level state combination m in the k system sampling periodnThe value of the control objective function of the total inverter energy consumption control amount of (1); j. the design is a squareet[k](met) For the level state combination m in the k system sampling periodetThe minimum function value of the total energy consumption control target of the inverter is obtained; geb[k](mn) For the corresponding nth system sampling periodLevel state combination mnThe value of the control objective function of the inverter energy consumption balance control quantity; j. the design is a squareeb[k](meb) For the level state combination m in the k system sampling periodebAnd balancing and controlling the target minimum function value of the energy consumption of the inverter.
7. The method of claim 1, wherein the motor current prediction model is expressed as:
Figure FDA0003202916730000041
wherein, tsIs the sampling time of the system; m isnRepresents the nth level state combination in all possible level state combinations m of each phase bridge arm of the inverter, wherein m is { m ═ m1,m2,…,mn,…,mNN is 1,2, …, N is the total number of level state combinations,
Figure FDA0003202916730000042
Figure FDA0003202916730000043
respectively representing the level states of the inverter U, V, W phase legs corresponding to the nth combination of level states in the kth system sampling period,
Figure FDA0003202916730000044
l is the bridge arm of the inverter, 1,2, 3; i.e. id[k+1](mn)、iq[k+1](mn) Respectively corresponding to the nth level state combination m in the (k + 1) th system sampling periodnPredicting the stator current of d and q axes; u. ofd[k](mn)、uq[k](mn) Respectively corresponding to the nth level state combination m in the kth system sampling periodnCalculated values of d and q axis voltages of the motor; i.e. id[k]、iq[k]Respectively determining d and q axes of the motor in the k system sampling periodCalculated values of the sub-currents, expressed as:
Figure FDA0003202916730000045
wherein, θ [ k ]]Representing the electrical angle of the system during the kth system sampling period; i.e. ia[k]、ib[k]、ic[k]Respectively representing the current measurement values flowing through the U, V, W phase bridge arm of the inverter in the kth system sampling period;
wherein u isd[k](mn)、uq[k](mn) The calculation formula is as follows:
Figure FDA0003202916730000046
wherein, UdcIn order to control the dc voltage of the inverter,
Figure FDA0003202916730000047
is mnThe transpose of (a) is performed,
Figure FDA0003202916730000048
8. the method of claim 1, wherein the model for predicting inverter power device energy consumption is:
Figure FDA0003202916730000049
in the formula (I), the compound is shown in the specification,
Figure FDA0003202916730000051
combining m for the jth power device of the ith phase bridge arm of the inverter in the corresponding nth level state in the (k + 1) th system sampling periodnJ is 1,2, …, and J is the bridge arm work of each phase of the inverterThe total number of rate devices;
Figure FDA0003202916730000052
is shown at [ k ]]Level state i of the I-phase bridge arm of the inverter corresponding to the n-th level state combination in each system sampling periodl[k+1](mn) For the corresponding n level state combination m in the k +1 system sampling periodnThe predicted value of the current flowing through the first phase bridge arm of the inverter is obtained; t islj[k]The junction temperature of the jth power device of the ith phase bridge arm in the kth system sampling period;
Figure FDA0003202916730000053
and
Figure FDA0003202916730000054
respectively serving as a conduction loss function and a switching loss function of the jth power device of the ith phase bridge arm of the inverter and a current predicted value i flowing through the ith phase bridge arm of the inverter in the (k + 1) th system sampling periodl[k+1](mn) And the self junction temperature T of the power device in the k system sampling periodlj[k](ii) related;
Figure FDA0003202916730000055
and
Figure FDA0003202916730000056
respectively judging whether the jth power device generates conduction loss and switching loss; wherein il[k+1](mn) (l ═ 1,2,3) the formula:
Figure FDA0003202916730000057
9. the method for optimally controlling the energy consumption of the motor drive system according to claim 1, wherein the reference motor current is a reference motor current in a full-speed range, and the full-speed range refers to a range from 0 to a rated speed of the motor, and includes a low-speed range and a high-speed range; the low speed range refers to the time when the running speed of the motor is lower than 30% of the rated speed; the high-speed range refers to the time when the running speed of the motor is higher than 30% of the rated speed and lower than the rated speed; the reference motor current in the full-speed domain is obtained through the following model:
Figure FDA0003202916730000058
wherein id_full[k]、iq_full[k]Respectively in the full-speed domain]Reference values of stator currents of d and q axes of the motor in a system sampling period; omega [ k ]]Is the [ k ]]Actual electrical angular velocity within a system sampling period; omegasIs the nominal electrical angular velocity; i.e. id_mtpa[k]、iq_mtpa[k]Respectively in the low speed range]Reference values of stator currents of d and q axes of the motor in a system sampling period; i.e. id_lmc[k]、iq_lmc[k]Respectively in the high speed range]Reference values of stator currents of d and q axes of the motor in a system sampling period;
wherein the content of the first and second substances,
Figure FDA0003202916730000061
wherein, Te[k]Is the [ k ]]Motor torque and actual electrical angular velocity ω k within a system sampling period](ii) related; a. thed、Bd、CdAnd DdRespectively reflecting motor torque T of a motor d-axis stator current reference value in a low-speed rangee[k]Coefficients of the cubic term, quadratic term, primary term, and constant term of (d); a. theq、Bq、CqAnd DqRespectively reflecting motor torque T of a motor q-axis stator current reference value in a low-speed rangee[k]Coefficients of the cubic term, quadratic term, primary term, and constant term of (d);
wherein the content of the first and second substances,
Figure FDA0003202916730000062
wherein psifIs a flux linkage; n ispIs the number of pole pairs of the motor; l isd、LqInductors of d and q axes respectively; rcIs an equivalent iron loss resistance; γ is a weighted average parameter, expressed as:
Figure FDA0003202916730000063
in the formula, RsIs the armature winding resistance.
10. A computer system comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the steps of the method of any one of claims 1 to 9 are performed when the computer program is executed by the processor.
CN202110908818.3A 2021-08-09 2021-08-09 Energy consumption optimization control method and system for motor driving system Pending CN113595465A (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117075647A (en) * 2023-10-17 2023-11-17 合肥焕智科技有限公司 Control method and device for stacker
CN117477613A (en) * 2023-12-26 2024-01-30 中南大学 Control method and system for urban rail transit vehicle-mounted energy storage system

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117075647A (en) * 2023-10-17 2023-11-17 合肥焕智科技有限公司 Control method and device for stacker
CN117075647B (en) * 2023-10-17 2024-01-12 合肥焕智科技有限公司 Control method and device for stacker
CN117477613A (en) * 2023-12-26 2024-01-30 中南大学 Control method and system for urban rail transit vehicle-mounted energy storage system
CN117477613B (en) * 2023-12-26 2024-04-23 中南大学 Control method and system for urban rail transit vehicle-mounted energy storage system

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