Energy consumption optimization control method and system for motor drive system

Abstract

The present invention discloses a motor drive system energy consumption optimization control method and system, which obtains the real-time motor current and reference motor current of the current cycle of the motor drive system, and inputs the real-time motor current into the motor current prediction model and the energy consumption prediction model of each inverter power device respectively, so as to obtain the predicted motor current of the next cycle and the energy consumption of each inverter power device of the next cycle; inputs the reference motor current, the predicted motor current and the energy consumption of each inverter power device into a multi-objective optimization control model with the optimal control strategy of minimizing current tracking, reducing the total energy consumption of the inverter and balancing the energy consumption of the inverter, so as to obtain the optimal control strategy of adjusting the real-time motor current value to the reference motor current value; and controls the motor drive system according to the switch state of each inverter bridge arm corresponding to the optimal control strategy. It can ensure a higher current control performance of the motor drive system, while reducing the total energy consumption of the inverter and improving the energy consumption balancing performance of the inverter.

Description

Technical Field

[0001] The present invention relates to the field of power electronics technology, and in particular to an energy consumption optimization control method and system for a motor drive system. Background Art

[0002] The safe and reliable operation of high-speed trains is an important issue in the development of rail transit. However, the harsh operating environment of high-speed trains and the aging of components that may result from long-term operation pose serious safety hazards to the operation of rail transit vehicles. The motor drive system is known as the "heart" of rail transit equipment / systems. It is not only the core power unit of the entire high-speed train, but also one of the key systems for its safe and reliable operation. Key components such as inverters and motors are the most frequent sources of failure in motor drive systems. Among them, the power device Insulated Gate Bipolar Transistor (IGBT) is one of the most vulnerable devices in the inverter. Therefore, the research on loss reduction of power devices, motors, etc. is an issue that cannot be ignored.

[0003] The power device IGBT is subjected to the influence of junction temperature fluctuations, which makes it the device with the highest failure rate. The IGBT loss is often closely related to the junction temperature. The energy consumption and life consumption of the IGBT are different due to the different conduction time and opening and closing times. The aging and breaking of the bonding wire of a power device in the inverter will cause the inverter to fail. After replacing the faulty power device, due to the different life consumption of other power devices that have not been replaced, it is very easy to cause damage to other devices, causing the inverter to fail 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 a power device, resulting in a great waste of equipment and resources. As the core equipment of the motor drive system, the motor will cause the motor winding and rotor to heat up due to the increase of its copper loss and iron loss, making the motor armature winding resistance larger and the winding inductance smaller, thereby increasing the loss of the entire motor drive system. When the heat is severe, the armature winding insulation is damaged, which may burn the motor, causing the train equipment to fail or even fail. How to reduce the motor loss and balance and reduce the energy consumption of the inverter without affecting the control performance of the motor drive system has become a key technology that needs to be solved urgently. Summary of the invention

[0004] The present invention provides a motor drive system energy consumption optimization control method and system, which are used to solve the technical problem that the existing motor drive system cannot take into account both control performance and inverter energy consumption balancing / energy consumption reduction at the same time.

[0005] In order to solve the above technical problems, the technical solution proposed by the present invention is:

[0006] A method for optimizing energy consumption of a motor drive system comprises the following steps:

[0007] Obtaining the real-time motor current and the reference motor current of the current cycle of the motor drive system, and inputting the real-time motor current into the motor current prediction model and the energy consumption prediction model of each inverter power device, respectively, to obtain the predicted motor current of the next cycle and the energy consumption of each inverter power device of the next cycle;

[0008] Inputting the reference motor current, the predicted motor current and the energy consumption of each inverter power device into a multi-objective optimization control model with minimization of current tracking, reduction of total inverter energy consumption and inverter energy consumption balancing as the optimal control strategy, to obtain an optimal control strategy for regulating the real-time motor current value to the reference motor current value;

[0009] The motor drive system is controlled according to the switching state of each inverter bridge arm corresponding to the optimal control strategy.

[0010] Preferably, the multi-objective optimization control model includes: a motor current tracking control optimization model, an inverter total energy consumption control optimization model, an inverter energy consumption balancing 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 balancing control optimization model.

[0011] Preferably, the motor current tracking control optimization model is:

[0012] J i [k](m i )=min{g i [k](m)}

[0013] g i [k](m)={g i [k](m1),g i [k](m2),…,g i [k](m n ),…,g i [k](m N )}

[0014] g i [k](m n )=λ d ·|i d_full [k]-i d [k+1](m n )|+λ q ·|i q_full [k]-i q [k+1](m n )|

[0015] In the formula, J i [k](mi ) is the level state combination m in the [k]th system sampling period i The minimum function value of the motor current tracking control objective under i is the level state combination that minimizes the motor current tracking control objective function value, m i ∈m; m={m1,m2,…,m n ,…,m N}, n = 1, 2, ..., N, N is the total number of level state combinations, m represents the set of all possible level state combinations of each phase bridge arm of the inverter, min{g i [k](m)} represents the value of the control objective function that minimizes the control objective function value among all possible combinations of inverter level states m, with a total number of N. k represents the serial number of the sampling period, g i [k](m n ) is the nth level state combination m corresponding to the kth system sampling period n The value of the motor current tracking control objective function; λ d , q are the weights of the absolute values ​​of the d-axis and q-axis motor current tracking errors, i d_full [k]、i q_full [k] are the reference values ​​of the motor d-axis and q-axis stator currents in the k-th system sampling period; i d [k+1](m n ),i q [k+1](m n ) are respectively the nth level state combination m in the k+1th system sampling period. n The d and q axis stator currents predict the motor current values.

[0016] Preferably, the inverter total energy consumption control optimization model is:

[0017] J et [k](m et )=min{g et [k](m)}

[0018] g et [k](m)={g et [k](m1),g et [k](m2),…,g et [k](m n ),…,g et [k](m N )}

[0019]

[0020] Among them, Jet [k](m et ) is the level state combination m in the kth system sampling period et The minimum function value of the total energy consumption control target of the inverter under et is the level state combination that minimizes the total energy consumption control objective function value of the inverter; m et ∈m, m={m1,m2,…,m n ,…,m N}, n=1,2,…,N, m represents the set of all possible level state combinations of each phase bridge arm of the inverter, g et [k](m n ) is the nth level state combination m corresponding to the kth system sampling period n The value of the control objective function of the total energy consumption control amount of the inverter, Abs(·) is the total energy consumption control objective function based on the absolute value; The jth power device of the lth phase bridge arm of the inverter corresponds to the nth level state combination m in the k+1th system sampling period n The predicted value of the overall energy consumption is j=1,2,…,J, where J is the total number of power devices in each phase arm of the inverter.

[0021] Preferably, the inverter energy consumption balance control optimization model is:

[0022] J eb [k](m eb )=min{g eb [k](m)}

[0023] g eb [k](m)={g eb [k](m1),g eb [k](m2),…,g eb [k](m n ),…,g eb [k](m N )}

[0024]

[0025] Among them, J eb [k](m eb ) is the level state combination m in the [k]th system sampling period eb The minimum function value of the inverter energy consumption balance control objective under eb is the level state combination that minimizes the inverter energy consumption balance control objective function value, m eb ∈m; m={m1,m2,…,m n ,…,m N}, n=1,2,…,N, m represents the set of all possible level state combinations of each phase bridge arm of the inverter, g eb [k](m n ) is the level state combination m corresponding to the nth level state combination m in the [k]th system sampling period n The value of the control objective function of the inverter energy consumption balance control quantity, Var(·) is the energy consumption balance control objective function of the l-th phase bridge arm based on the energy consumption variance; The jth power device of the lth phase bridge arm of the inverter corresponds to the nth level state combination m in the k+1th system sampling period n The predicted value of the overall energy consumption is j=1,2,…,J, where J is the total number of power devices in each phase arm of the inverter.

[0026] Preferably, the reward function optimization model is:

[0027] J[k](m z )=max{H[k](m,m i ,m et ,m eb )}

[0028] H[k](m,m i ,m et ,m eb )={H[k](m1,m i ,m et ,m eb ),H[k](m2,m i ,m et ,m eb ),…,H[k](m n ,m i ,m et ,m eb ),…,H[k](m N ,m i ,m et ,m eb )}

[0029]

[0030] Among them, J[k](m z ) represents the level state combination m in the [k]th system sampling period z The maximum function value of the reward function under z is the level state combination that maximizes the reward function value, m z ∈m; m={m1,m2,…,m n ,…,m N}, n = 1, 2, ..., N, m represents the set of all possible level state combinations of each phase bridge arm of the inverter, m i is the level state combination that minimizes the motor current tracking control objective function value, m et is the level state combination that minimizes the total energy consumption control objective function value of the inverter, m eb The corresponding level state combination when the inverter energy consumption balance control objective function value is minimized; H[k](m n , m i , m et , m eb ) is the nth level state combination m corresponding to the kth system sampling period n The value of the reward function, m n represents the nth level state combination among all possible level state combinations m of each phase bridge arm of the inverter, max{H[k](m,m i , m et ,m eb )} represents the value of the reward function corresponding to the maximum reward function value selected from all possible level state combinations m of the inverter with a total number of N; λ i , β et , β eb They represent 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 respectively; g i [k](m n ) is the nth level state combination m corresponding to the kth system sampling period n The value of the motor current tracking control objective function; J i [k](m i ) is the level state combination m in the kth system sampling period i The minimum function value of the motor current tracking control objective under g et [k](m n ) is the nth level state combination m corresponding to the kth system sampling period n The value of the control objective function of the total energy consumption control quantity of the inverter; J et [k](m et ) is the level state combination m in the kth system sampling period et The minimum function value of the total energy consumption control target of the inverter under g eb [k](m n ) is the nth level state combination m corresponding to the kth system sampling period n The value of the control objective function of the inverter energy consumption balance control quantity; J eb [k](m eb ) is the level state combination m in the kth system sampling periodeb The minimum function value of the inverter energy consumption balance control objective under .

[0031] Preferably, the motor current prediction model is expressed as:

[0032]

[0033] Among them, t s is the sampling time of the system; m n represents the nth level state combination among all possible level state combinations m of each phase bridge arm of the inverter, m={m1,m2,…,m n ,…,m N}, n = 1, 2, ..., N, N is the total number of level state combinations, They respectively represent the level states of the U, V, and W phase bridge arms of the inverter corresponding to the n-th level state combination in the k-th system sampling period, l is the bridge arm of the inverter, l = 1, 2, 3; i d [k+1](m n ),i q [k+1](m n ) are respectively the nth level state combination m in the k+1th system sampling period. n The predicted value of d and q axis stator current; u d [k](m n )、u q [k](m n ) are respectively the nth level state combination m corresponding to the kth system sampling period n The calculated values ​​of the motor d and q axis voltages; i d [k]、i q [k] are the calculated values ​​of the stator currents of the motor d and q axes in the kth system sampling period, respectively, expressed as:

[0034]

[0035] Where θ[k] represents the electrical angle of the system in the kth system sampling period; i a [k]、i b [k]、i c [k] represents the measured current values ​​flowing through the U, V, and W phase bridge arms of the inverter in the kth system sampling period;

[0036] Among them, u d [k](m n )、u q [k](m n ) is calculated as:

[0037]

[0038] Among them, U dc is the DC terminal voltage of the inverter, is m n The transpose of

[0039] Preferably, the energy consumption prediction model of the inverter power device is:

[0040]

[0041] In the formula, The jth power device of the lth phase bridge arm of the inverter corresponds to the nth level state combination m in the k+1th system sampling period n The total energy consumption prediction value of , j = 1, 2, ..., J, J is the total number of power devices in each phase bridge arm of the inverter; represents the level state of the inverter phase l bridge arm corresponding to the nth level state combination in the [k]th system sampling period, i l [k+1](m n ) is the level state combination m corresponding to the nth level state combination m in the k+1th system sampling period n The predicted value of the current flowing through the lth phase bridge arm of the inverter; T lj [k] is the junction temperature of the jth power device in the lth phase bridge arm during the kth system sampling period; and are the conduction loss function and switching loss function of the jth power device in the lth phase bridge arm of the inverter, respectively, and the predicted current value i flowing through the lth phase bridge arm of the inverter in the k+1th system sampling period l [k+1](m n ) and the junction temperature T of the power device itself during the kth system sampling period lj [k] related to; and are functions for determining whether the jth power device generates conduction loss and switching loss respectively; where i l [k+1](m n )(l=1,2,3)The formula is:

[0042]

[0043] Preferably, the reference motor current is a reference motor current in the full speed domain, the full speed domain refers to the motor running speed from 0 to the rated speed, including a low speed range and a high speed range; the low speed range refers to when the motor running speed is lower than 30% of the rated speed; the high speed range refers to when the motor running speed 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 by the following model:

[0044]

[0045] Among them, i d_full [k]、i q_full [k] are the reference values ​​of the stator currents of the motor d and q axes in the [k]th system sampling period in the full speed domain; ω[k] is the actual electrical angular velocity in the [k]th system sampling period; ω s is the rated electrical angular velocity; i d_mtpa [k]、i q_mtpa [k] are the reference values ​​of the stator currents of the motor d and q axes in the [k]th system sampling period in the low speed range; i d_lmc [k]、i q_lmc [k] are the reference values ​​of the motor d-axis and q-axis stator currents in the [k]th system sampling period in the high-speed range;

[0046] in,

[0047] Among them, T e [k] is the motor torque in the [k]th system sampling period, which is related to the actual electrical angular velocity ω[k]; A d , B d , C d and D d They are the motor torque T reflecting the stator current reference value of the motor d axis in the low speed range. e The coefficients of the cubic, quadratic, linear and constant terms of [k]; A q , B q , C q and D q They are the motor torque T reflecting the motor q-axis stator current reference value in the low speed range. e The coefficients of the cubic, quadratic, linear, and constant terms of [k];

[0048] in,

[0049] Among them, ψ f is the magnetic linkage; n p is the number of motor pole pairs; L d , L q are the inductances of the d and q axes respectively; R c is the equivalent iron loss resistance; γ is the weighted average parameter, expressed as:

[0050]

[0051] In the formula, R s is the armature winding resistance.

[0052] A computer system comprises a memory, a processor and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the above method are implemented.

[0053] The present invention has the following beneficial effects:

[0054] 1. The energy consumption optimization control method and system of the motor drive system in the present invention obtains the real-time motor current and reference motor current of the current cycle of the motor drive system, and inputs the real-time motor current into the motor current prediction model and the energy consumption prediction model of each inverter power device, respectively, to obtain the predicted motor current of the next cycle and the energy consumption of each inverter power device in the next cycle; inputs the reference motor current, predicted motor current and energy consumption of each inverter power device into a multi-objective optimization control model with the optimal control strategy of minimizing current tracking, reducing the total energy consumption of the inverter and balancing the energy consumption of the inverter, to obtain the optimal control strategy for adjusting the real-time motor current value to the reference motor current value; and controls the motor drive system according to the switch state of each inverter bridge arm corresponding to the optimal control strategy. It can ensure a higher current control performance of the motor drive system, reduce the total energy consumption of the inverter, and improve the energy consumption balancing performance of the inverter.

[0055] 2. In the preferred embodiment, the present invention constructs a full-speed motor current reference value calculation model and dynamically sets the reference value of current tracking optimization control; on this basis, with higher system current control performance, lower motor loss, higher inverter energy consumption balance performance, and lower inverter energy consumption as optimization goals, the motor drive system energy consumption optimization control is realized. The method is easy to implement, does not require additional hardware equipment, can reduce the energy consumption of motors, inverters and even motor drive systems, improve the reliability of motor drive system operation, and reduce equipment maintenance costs.

[0056] In addition to the above-described purposes, features and advantages, the present invention has other purposes, features and advantages. The present invention will be further described in detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] The drawings constituting a part of this application are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0058] Figure 1 The invention discloses an energy consumption optimization control method for a motor drive system and a system flow chart.

[0059] Figure 2 4 is a topological structure diagram of the motor drive system according to an embodiment of the present invention.

[0060] Figure 3It is a block diagram of the overall control principle of the motor drive system according to an embodiment of the present invention.

[0061] Figure 4 It is a schematic diagram of the changes in copper loss and iron loss before and after the motor drive system energy consumption optimization control method is adopted in an embodiment of the present invention.

[0062] Figure 5 It is a schematic diagram of energy consumption changes of four power devices in the front and rear U-phase bridge arms of the motor drive system energy consumption optimization control method adopted in an embodiment of the present invention.

[0063] Figure 6 It is a schematic diagram of temperature fluctuations of four power devices of the front and rear U-phase bridge arms of the motor drive system energy consumption optimization control method adopted in an embodiment of the present invention. DETAILED DESCRIPTION

[0064] The embodiments of the present invention are described in detail below with reference to the accompanying drawings, but the present invention can be implemented in many different ways as defined and covered by the claims.

[0065] Embodiment 1:

[0066] This embodiment discloses a method for optimizing energy consumption of a motor drive system, comprising the following steps:

[0067] Obtain the real-time motor current and reference motor current of the current cycle of the motor drive system, and input the real-time motor current into the motor current prediction model and the energy consumption prediction model of each inverter power device, respectively, to obtain the predicted motor current of the next cycle and the energy consumption of each inverter power device in the next cycle;

[0068] The reference motor current, predicted motor current and energy consumption of each inverter power device are input into a multi-objective optimization control model with the optimal control strategy of minimizing current tracking, reducing total inverter energy consumption and balancing inverter energy consumption, and the optimal control strategy of adjusting the real-time motor current value to the reference motor current value is obtained;

[0069] The motor drive system is controlled according to the switch state of each inverter bridge arm corresponding to the optimal control strategy. In this embodiment, the switch state of each inverter bridge arm specifically refers to the switch level of each inverter bridge arm.

[0070] In addition, in this embodiment, a computer system is also disclosed, including a memory, a processor, and a computer program stored in the memory and executable on the processor, and the steps of the above method are implemented when the processor executes the computer program.

[0071] The energy consumption optimization control method and system of the motor drive system in the present invention obtains the real-time motor current and reference motor current of the current cycle of the motor drive system, and inputs the real-time motor current into the motor current prediction model and the energy consumption prediction model of each inverter power device, respectively, to obtain the predicted motor current of the next cycle and the energy consumption of each inverter power device in the next cycle; inputs the reference motor current, the predicted motor current and the energy consumption of each inverter power device into a multi-objective optimization control model with the optimal control strategy of minimizing current tracking, reducing the total energy consumption of the inverter and balancing the energy consumption of the inverter, to obtain the optimal control strategy for adjusting the real-time motor current value to the reference motor current value; and controls the motor drive system according to the switch state of each inverter bridge arm corresponding to the optimal control strategy. It can ensure a higher current control performance of the motor drive system, and reduce the total energy consumption of the inverter / improve the energy consumption balancing performance of the inverter.

[0072] Embodiment 2:

[0073] Embodiment 2 is a preferred embodiment of Embodiment 1. The difference between Embodiment 2 and Embodiment 1 is that the specific steps of the method for optimizing the control of energy consumption of a motor drive system are refined:

[0074] This embodiment refers to a three-level permanent magnet synchronous motor drive system for a certain type of high-speed train. The topology of the motor drive system is as follows: Figure 2 As shown, the motor drive system includes: a drive controller, a permanent magnet synchronous motor and a three-phase three-level inverter, wherein the drive controller includes: a reference value setter, an optimization controller and a current / speed sensor. This embodiment will take the energy consumption performance optimization control of a three-phase three-level inverter as an example for explanation. The motor drive system adopts a speed-current dual closed-loop control structure, and the outer control loop is a speed loop. According to the speed feedback, the given value of the system electromagnetic torque can be obtained through a lookup table; through the full-speed domain motor current reference value calculation model, the reference values ​​of the motor stator d-axis current and the stator q-axis current are obtained, and this is used as the given input of the current inner loop control strategy; by minimizing current tracking, inverter energy consumption balance and energy consumption reduction optimization strategy, the level state combination that maximizes the reward function value is selected as the system control instruction output, so as to achieve higher system current control performance, lower motor loss, higher inverter energy consumption balance performance, and lower inverter energy consumption optimization goals. Its control principle block diagram is shown as follows Figure 3 shown.

[0075] Table 1 Main parameters of three-level inverter system

[0076] parameter Numeric <![CDATA[Stator resistance R s > 0.07Ω <![CDATA[Stator d-axis inductance L d > 0.0037H <![CDATA[Stator q-axis inductance L q > 0.0096H <![CDATA[Permanent magnet flux linkage ψ f > 0.625Wb <![CDATA[Number of pole pairs n p > 4 Given DC voltage 3600V Rated power of embedded permanent magnet synchronous motor 600kW <![CDATA[System sampling period t s > 40μs

[0077] like Figure 1 As shown, a motor drive system energy consumption optimization control method and system provided in an embodiment of the present application includes the following steps:

[0078] Step S1: construct a full-speed domain motor current reference value calculation model; used to dynamically set the reference value of motor current tracking optimization control in each sampling cycle;

[0079] It should be noted that if Figure 3 As shown, the motor drive system energy consumption optimization control method in this embodiment is in the current loop control link in the speed-current dual closed-loop control structure. More specifically, the full-speed domain motor current reference value calculation model constructed in this embodiment is in the current outer loop control link in the speed-current dual closed-loop control structure, and the minimized balanced inverter energy consumption optimization strategy is in the current inner loop control link in the speed-current dual closed-loop control structure. Therefore, the system control quantity in this embodiment is the stator d-axis current and stator q-axis current of the permanent magnet synchronous motor and the energy consumption of the inverter.

[0080] S11: Construct a full-speed domain motor current reference value calculation model, expressed as:

[0081]

[0082] where i d_full [k]、i q_full [k] are the reference values ​​of the stator currents of the motor d and q axes in the kth system sampling period in the full speed domain; ω[k] is the actual electrical angular velocity in the kth system sampling period; ω s is the rated electrical angular velocity; i d_mtpa [k]、i q_mtpa [k] are the reference values ​​of the stator currents of the motor d and q axes in the kth system sampling period in the low speed range; i d_lmc [k]、i q_lmc [k] are the reference values ​​of the motor d-axis and q-axis stator currents in the k-th system sampling period in the high-speed range;

[0083] S12: In the low speed range, a first motor current reference value calculation model is constructed, which is expressed as:

[0084]

[0085] Where T e [k] is the motor torque in the [k]th system sampling period, which is related to the actual electrical angular velocity ω[k]; A d , B d , C d and D d They are the motor torque T reflecting the stator current reference value of the motor d axis in the low speed range. e The coefficients of the cubic, quadratic, linear and constant terms of [k]; A q , B q , C q and Dq They are the motor torque T reflecting the motor q-axis stator current reference value in the low speed range. e The coefficients of the cubic, quadratic, linear, and constant terms of [k].

[0086] In this embodiment, according to the given value T of the system electromagnetic torque e [k] By looking up the table, the coefficient values ​​under the parameters in Table 1 can be obtained, and the calculation model of the first motor current reference value is expressed as:

[0087]

[0088] S13: In the high-speed range, a second motor current reference value calculation model is constructed, which is expressed as:

[0089]

[0090] where ψ f is the magnetic linkage; n p is the number of motor pole pairs; L d , L q are the inductances of the d and q axes respectively; R c is the equivalent iron loss resistance; β is the weighted average parameter, expressed as:

[0091]

[0092] Where R s is the armature winding resistance.

[0093] Step S2: constructing a motor current prediction model and an inverter power device energy consumption prediction model;

[0094] S21: Construct a motor current prediction model, expressed as:

[0095]

[0096] where t s is the sampling time of the system; m n represents the nth level state combination among all possible level state combinations m of each phase bridge arm of the inverter, m={m1,m2,…,m n ,…,m N}, n = 1, 2, ..., N, N is the total number of level state combinations, They respectively represent the level states of the U, V, and W phase bridge arms of the inverter corresponding to the n-th level state combination in the k-th system sampling period, l is the bridge arm of the inverter, l = 1, 2, 3; i d [k+1](m n ),i q [k+1](mn ) are respectively the nth (n=1,2,…,N)th level state combination m in the k+1th system sampling period. n The predicted value of d and q axis stator current; u d [k](m n )、u q [k](m n ) are respectively the nth (n=1,2,…,N) level state combination m corresponding to the [k]th system sampling period n The calculated values ​​of the motor d and q axis voltages; i d [k]、i q [k] are the calculated values ​​of the stator currents of the motor d and q axes in the kth system sampling period, respectively, expressed as:

[0097]

[0098] Where θ[k] represents the electrical angle of the system in the kth system sampling period; i a [k]、i b [k]、i c [k] represents the measured current values ​​flowing through the U, V, and W phase bridge arms of the inverter in the [k]th system sampling period.

[0099] u d [k](m n )、u q [k](m n ) is calculated as:

[0100]

[0101] Among them, U dc is the DC terminal voltage of the inverter, is m n The transpose of

[0102] S22: Construct an inverter power device energy consumption prediction model, the expression of which is:

[0103]

[0104] In the formula, The jth power device of the lth phase bridge arm of the inverter corresponds to the nth (n=1, 2, ..., N)th level state combination m in the k+1th system sampling period n The total energy consumption prediction value of is, j = 1, 2, ..., J, J is the total number of power devices in each phase bridge arm of the inverter; i l [k+1](m n ) is the nth (n=1,2,…,N)th level state combination m corresponding to the k+1th system sampling periodn The predicted value of the current flowing through the lth phase bridge arm of the inverter; T lj [k] is the junction temperature of the jth power device in the lth phase bridge arm during the kth system sampling period; and are the conduction loss function and switching loss function of the jth power device in the lth phase bridge arm of the inverter, respectively, and the predicted current value i flowing through the lth phase bridge arm of the inverter in the k+1th system sampling period l [k+1](m n ) and the junction temperature T of the power device itself during the kth system sampling period lj [k] related to; and are functions for determining whether the j-th power device generates conduction loss and switching loss respectively;

[0105] i l [k+1](m n )(l=1,2,3)The formula is:

[0106]

[0107] In this embodiment, the expression and The expression can be a fitting function, and the fitting data comes from the user data manual of the power module manufacturer.

[0108] In this embodiment, the function for determining whether conduction loss and switching loss occur is and The expression of can be consistent with the description in the prior art and will not be repeated here.

[0109] In this embodiment, the three-level inverter has three-phase bridge arms (l=1, 2, 3), namely, a U-phase bridge arm, a V-phase bridge arm and a W-phase bridge arm. Each phase bridge arm is composed of four power devices, j=1, 2, ..., J, J=4. Figure 2 As shown. Under normal circumstances, each bridge arm has three level states. In this embodiment, The level states of the U, V, and W phase bridge arms of the inverter corresponding to the n-th level state combination in the k-th system sampling period are respectively corresponding. Specifically, in this embodiment, the level state of the l-th phase bridge arm under the n-th level state combination in the k-th system sampling period is It can be expressed as:

[0110]

[0111] In the formula, and They respectively represent the control signals for determining the on / off states of the 1st, 2nd, 3rd, and 4th power devices of the 1st phase bridge arm under the nth level state combination in the kth system sampling period. "1" indicates that the control power device is in the on state, and "0" indicates that the control power device is in the off state. The corresponding relationship is as follows: Figure 2 shown.

[0112] Step S3: constructing a motor current tracking control objective function, an inverter total energy consumption control objective function, and an inverter energy consumption balancing control objective function respectively;

[0113] S31: Construct the motor current tracking control objective function, which is expressed as:

[0114] g i [k](m n )=λ d ·|i d_full [k]-i d [k+1](m n )|+λ q ·|i q_full [k]-i q [k+1](m n )|

[0115] Where: g i [k](m n ) is the nth (n=1,2,…,N)th level state combination m corresponding to the [k]th system sampling period n The value of the motor current tracking control objective function; λ d , q are the weights of the absolute values ​​of the d-axis and q-axis motor current tracking errors, respectively;

[0116] Taking the minimum absolute value of the motor current tracking error as the optimization goal of "higher current control performance and lower motor loss", its expression is:

[0117] J i [k](m i )=min{g i [k](m)}

[0118] Among them, J i [k](m i ) is the level state combination m in the [k]th system sampling period i The minimum function value of the motor current tracking control objective under i is the level state combination that minimizes the motor current tracking control objective function value, m i∈m; min{·} represents the value of the control objective function corresponding to the minimum value of the control objective function when selecting the value of the control objective function from all possible level state combinations m of the inverter with a total number of N; g i [k](m)={g i [k](m1),g i [k](m2),…,g i [k](m n ), …, g i [k](m N )}.

[0119] It should be noted that, in this embodiment, λ d =0.3,λ q =0.7.

[0120] S32: Construct the inverter total energy consumption control objective function, which is expressed as:

[0121]

[0122] In the formula, g et [k](m n ) is the nth (n=1,2,…,N)th level state combination m corresponding to the [k]th system sampling period n The value of the control objective function of the total energy consumption control amount of the inverter, Abs(·) is the total energy consumption control objective function based on the absolute value;

[0123] The absolute value of the inverter total energy consumption error is minimized as the optimization target for the inverter total energy consumption minimum. The expression is:

[0124] J et [k](m et )=min{g et [k](m)}

[0125] Among them J et [k](m et ) is the level state combination m in the [k]th system sampling period et The minimum function value of the total energy consumption control target of the inverter under et is the level state combination that minimizes the total energy consumption control objective function value of the inverter, m et ∈m;g et [k](m)={g et [k](m1),g et [k](m2),…,g et [k](m n ),…,g et [k](m N )}.

[0126] S33: Construct the inverter energy consumption balance control objective function, which is expressed as:

[0127]

[0128] In the formula, g eb [k](m n ) is the nth (n=1,2,…,n,…,N)th level state combination m corresponding to the [k]th system sampling period n The value of the control objective function of the inverter energy consumption balance control quantity, Var(·) is the energy consumption balance control objective function of the l-th phase bridge arm based on the energy consumption variance;

[0129] The minimum sum of the inverter bridge arm energy consumption variance is taken as the optimal control target of inverter energy consumption balance, and its expression is:

[0130] J eb [k](m eb )=min{g eb [k](m)}

[0131] Among them, J eb [k](m eb ) is the level state combination m in the kth system sampling period eb The minimum function value of the inverter energy consumption balance control objective under eb is the level state combination that minimizes the inverter energy consumption balance control objective function value, m eb ∈m;g eb [k](m)={g eb [k](m1),g eb [k](m2),…,g eb [k](m n ),…,g eb [k](m N )}.

[0132] Step S4: construct a reward function; select the level state combination that maximizes the reward function value as the control output of the system to achieve energy consumption optimization control of the motor drive system.

[0133] S41: Construct a reward function, which is expressed as:

[0134]

[0135] In the formula, H[k](m,m i ,m et ,m eb ) is the nth (n=1,2,…,n,…,N)th level state combination m in the kth system sampling period n The value of the reward function, λi , β et , β eb They respectively represent 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.

[0136] In this embodiment, λ i =1, β et =0.2, β eb =0.9. This is just an example and not a limitation.

[0137] S42: In order to maximize the reward function value, as the optimization goal of "higher motor drive system current control performance, lower motor loss, higher inverter energy consumption balance performance, and lower inverter total energy consumption", its expression is:

[0138] J[k](m z )=max{H[k](m,m i ,m et ,m eb )}

[0139] In the formula, J[k](m z ) represents the level state combination m in the [k]th system sampling period z The maximum function value of the reward function under z is the level state combination that maximizes the reward function value, m z ∈m; max{·} represents the value of the reward function when the reward function value is maximized among all possible combinations of inverter level states m with a total number of N; H[[k](m,m i ,m et ,m eb )={H[k](m1,m i ,m et ,m eb ),H[k](m2,m i ,m et ,m eb ),…,H[[k](m n ,m i ,m et ,m eb ),…,H[[k](m N ,m i ,m et ,m eb )}.

[0140] In the kth system sampling cycle, the system sensor samples to obtain i a [k]、i b [k]、i c[k], θ[k] and ω[k]; further, the system outer loop control strategy can be used to obtain i d_full [k] and i q_full [k]; In addition, ω can be obtained through system reference instructions / user settings * [k].

[0141] Specifically, in this embodiment, when the system runs at a certain stable speed (200 km / h), the motor drive system energy consumption optimization control method / strategy (using the full-speed domain motor current reference value calculation model; corresponding weight coefficient λ i =1, β et =0, β eb =0) and the energy consumption optimization control method / strategy of the motor drive system (using the full-speed domain motor current reference value calculation model; corresponding weight coefficient λ i =1, β et =0.2, β eb =0.9) and the energy consumption of the four power modules of phase U. Figure 4 , Figure 5 In order to better observe the balancing effect, the energy consumption change is converted into temperature change, and the temperature change of the four power modules of phase U is observed, as shown in Figure 6 As shown. It can be seen that compared with the motor drive system that does not adopt the motor drive system energy consumption optimization control method / strategy, the method of the present invention can reduce the motor loss. At the same time, 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 the motor drive system that does not adopt the motor drive system energy consumption optimization control method / strategy, the control method of the present invention can reduce the motor loss and make the energy consumption of each power module of the inverter similar. According to relevant research results, in this case, the service life of the motor will be extended and the life consumption of each power module of the inverter will also tend to be similar. The overall service life of the inverter will effectively avoid the "short board of the barrel" effect, thereby achieving the extension of its overall service life.

[0142] In this optional implementation, making the energy consumption differences between the power devices in the inverter module tend to be consistent means reducing the average energy consumption differences between the power devices in the inverter module. By reducing the total energy consumption of the power devices in the inverter module to be tested, and making the energy consumption differences between the power devices tend to be consistent, or reducing the average energy consumption of a single power module, the average energy consumption difference of the power devices in the module is reduced to a preset threshold. 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 to adjust the energy consumption in the module, so that the energy consumption of the inverter can be optimized.

[0143] In summary, the above-mentioned motor drive system energy consumption optimization control method of the present invention dynamically sets the reference value of current tracking optimization control by constructing a full-speed motor current reference value calculation model; on this basis, with higher system current control performance, lower motor loss, higher inverter energy consumption balance performance, and lower inverter energy consumption as optimization goals, the motor drive system energy consumption optimization control is realized. The method is easy to implement, does not require additional hardware equipment, can reduce the energy consumption of motors, inverters and even motor drive systems, improve the reliability level of motor drive system operation, and reduce equipment maintenance costs.

[0144] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for optimizing energy consumption of a motor drive system, characterized in that: The following steps are involved: Obtaining the real-time motor current and the reference motor current of the current cycle of the motor drive system, and inputting the real-time motor current into the motor current prediction model and the energy consumption prediction model of each inverter power device, respectively, to obtain the predicted motor current of the next cycle and the energy consumption of each inverter power device of the next cycle; Inputting the reference motor current, the predicted motor current and the energy consumption of each inverter power device into a multi-objective optimization control model with minimization of current tracking, reduction of total inverter energy consumption and inverter energy consumption balancing as the optimal control strategy, to obtain an optimal control strategy for regulating the real-time motor current value to the reference motor current value; Controlling the motor drive system according to the switch states of each inverter bridge arm corresponding to the optimal control strategy; The multi-objective optimization control model includes: 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; The motor current tracking control optimization model is: J i [k](m i )=min{g i [k](m)} g i [k](m)={g i [k](m1),g i [k](m2),…,g i [k](m n ),…,g i [k](m N )} g i [k](m n )=λ d ·|i d_full [k]-i d [k+1](m n )|+λ q ·|i q_full [k]-i q [k+1](m n )| In the formula, J i [k](m i ) is the level state combination m in the [k]th system sampling period i The minimum function value of the motor current tracking control objective under i is the level state combination that minimizes the motor current tracking control objective function value, m i ∈m; m={m1,m2,…,m n ,…,m N }, n = 1, 2, ..., N, N is the total number of level state combinations, m represents the set of all possible level state combinations of each phase bridge arm of the inverter, min{g i [k](m)} represents the value of the control objective function that minimizes the control objective function value among all possible combinations of inverter level states m, with a total number of N. k represents the serial number of the sampling period, g i [k](m n ) is the nth level state combination m corresponding to the kth system sampling period n The value of the motor current tracking control objective function; λ d , q are the weights of the absolute values ​​of the d-axis and q-axis motor current tracking errors, i d_full [k]、i q_full [k] are the reference values ​​of the motor d-axis and q-axis stator currents in the k-th system sampling period; i d [k+1](m n ),i q [k+1](m n ) are respectively the nth level state combination m in the k+1th system sampling period. n The d and q axis stator currents predict the motor current values.

2. The method for optimizing the control of the energy consumption of a motor drive system according to claim 1, characterized in that: The inverter total energy consumption control optimization model is: J et [k](m et )=min{g et [k](m)} g et [k](m)={g et [k](m1),g et [k](m2),…,g et [k](m n ),…,g et [k](m N )} Among them, J et [k](m et ) is the level state combination m in the kth system sampling period et The minimum function value of the total energy consumption control target of the inverter under et is the level state combination that minimizes the total energy consumption control objective function value of the inverter; m et ∈m, m={m1,m2,…,m n ,…,m N }, n=1,2,…,N, m represents the set of all possible level state combinations of each phase bridge arm of the inverter, g et [k](m n ) is the nth level state combination m corresponding to the kth system sampling period n The value of the control objective function of the total energy consumption control amount of the inverter, Abs(·) is the total energy consumption control objective function based on the absolute value; The jth power device of the lth phase bridge arm of the inverter corresponds to the nth level state combination m in the k+1th system sampling period n The predicted value of the overall energy consumption is j = 1, 2, …, J, where J is the total number of power devices in each phase arm of the inverter.

3. The method for optimizing the control of the energy consumption of a motor drive system according to claim 1, characterized in that: The inverter energy consumption balance control optimization model is: J eb [k](m eb )=min{g eb [k](m)} g eb [k](m)={g eb [k](m1),g eb [k](m2),…,g eb [k](m n ),…,g eb [k](m N )} Among them, J eb [k](m eb ) is the level state combination m in the [k]th system sampling period eb The minimum function value of the inverter energy consumption balance control objective under eb is the level state combination that minimizes the inverter energy consumption balance control objective function value, m eb ∈m; m={m1,m2,…,m n ,…,m N }, n=1,2,…,N, m represents the set of all possible level state combinations of each phase bridge arm of the inverter, g eb [k](m n ) is the level state combination m corresponding to the nth level state combination m in the [k]th system sampling period n The value of the control objective function of the inverter energy consumption balance control quantity, Var(·) is the energy consumption balance control objective function of the l-th phase bridge arm based on the energy consumption variance; The jth power device of the lth phase bridge arm of the inverter corresponds to the nth level state combination m in the k+1th system sampling period n The predicted value of the overall energy consumption is j = 1, 2, …, J, where J is the total number of power devices in each phase arm of the inverter.

4. The method for optimizing the control of energy consumption of a motor drive system according to claim 1, characterized in that: The reward function optimization model is: J[k](m z )=max{H[k](m,m i ,m et ,m eb )} H[k](m,m i ,m et ,m eb )={H[k](m1,m i ,m et ,m eb ),H[k](m2,m i ,m et ,m eb ),…,H[k](m n ,m i ,m et ,m eb ),…,H[k](m N ,m i ,m et ,m eb )} Among them, J[k](m z ) represents the level state combination m in the [k]th system sampling period z The maximum function value of the reward function under z is the level state combination that maximizes the reward function value, m z ∈m; m={m1,m2,…,m n ,…,m N }, n = 1, 2, ..., N, m represents the set of all possible level state combinations of each phase bridge arm of the inverter, m i is the level state combination that minimizes the motor current tracking control objective function value, m et is the level state combination that minimizes the total energy consumption control objective function value of the inverter, m eb The corresponding level state combination when the inverter energy consumption balance control objective function value is minimized; H[k](m n ,m i ,m et ,m eb ) is the nth level state combination m corresponding to the kth system sampling period n The value of the reward function, m n represents the nth level state combination among all possible level state combinations m of each phase bridge arm of the inverter, max{H[k](m,m i ,m et ,m eb )} represents the value of the reward function corresponding to the maximum reward function value selected from all possible level state combinations m of the inverter with a total number of N; λ i , β et , β eb They represent 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 respectively; g i [k](m n ) is the nth level state combination m corresponding to the kth system sampling period n The value of the motor current tracking control objective function; J i [k](m i ) is the level state combination m in the kth system sampling period i The minimum function value of the motor current tracking control objective under g et [k](m n ) is the nth level state combination m corresponding to the kth system sampling period n The value of the control objective function of the total energy consumption control quantity of the inverter; J et [k](m et ) is the level state combination m in the kth system sampling period et The minimum function value of the total energy consumption control target of the inverter under g eb [k](m n ) is the nth level state combination m corresponding to the kth system sampling period n The value of the control objective function of the inverter energy consumption balance control quantity; J eb [k](m eb ) is the level state combination m in the kth system sampling period eb The minimum function value of the inverter energy consumption balance control objective under .

5. The method for optimizing the control of energy consumption of a motor drive system according to claim 1, characterized in that: The motor current prediction model is expressed as: Among them, t s is the sampling time of the system; m n represents the nth level state combination among all possible level state combinations m of each phase bridge arm of the inverter, m={m1,m2,…,m n ,…,m N }, n = 1, 2, ..., N, N is the total number of level state combinations, They respectively represent the level states of the U, V, and W phase bridge arms of the inverter corresponding to the n-th level state combination in the k-th system sampling period, l is the bridge arm of the inverter, l = 1, 2, 3; i d [k+1](m n ),i q [k+1](m n ) are respectively the nth level state combination m in the k+1th system sampling period. n The predicted value of d and q axis stator current; u d [k](m n )、u q [k](m n ) are respectively the nth level state combination m corresponding to the kth system sampling period n The calculated values ​​of the motor d and q axis voltages; i d [k]、i q [k] are the calculated values ​​of the stator currents of the motor d and q axes in the kth system sampling period, respectively, expressed as: Where θ[k] represents the electrical angle of the system in the kth system sampling period; i a [k]、i b [k]、i c [k] represents the measured current values ​​flowing through the U, V, and W phase bridge arms of the inverter in the kth system sampling period; Among them, u d [k](m n )、u q [k](m n ) is calculated as: Among them, U dc is the DC terminal voltage of the inverter, is m n The transpose of 6. The method for optimizing the control of energy consumption of a motor drive system according to claim 1, characterized in that: The energy consumption prediction model of inverter power devices is: In the formula, The jth power device of the lth phase bridge arm of the inverter corresponds to the nth level state combination m in the k+1th system sampling period n The total energy consumption prediction value of , j = 1, 2, ..., J, J is the total number of power devices in each phase bridge arm of the inverter; represents the level state of the inverter phase l bridge arm corresponding to the nth level state combination in the [k]th system sampling period, i l [k+1](m n ) is the level state combination m corresponding to the nth level state combination m in the k+1th system sampling period n The predicted value of the current flowing through the lth phase bridge arm of the inverter; T lj [k] is the junction temperature of the jth power device in the lth phase bridge arm during the kth system sampling period; and are the conduction loss function and switching loss function of the jth power device in the lth phase bridge arm of the inverter, respectively, and the predicted current value i flowing through the lth phase bridge arm of the inverter in the k+1th system sampling period l [k+1](m n ) and the junction temperature T of the power device itself during the kth system sampling period lj [k] related to; and are functions for determining whether the jth power device generates conduction loss and switching loss respectively; where i l [k+1](m n )(l=1,2,3)The formula is:

7. The method for optimizing the control of energy consumption of a motor drive system according to claim 1, characterized in that: The reference motor current is the reference motor current in the full speed domain. The full speed domain refers to the motor running speed from 0 to the rated speed, including a low speed range and a high speed range. The low speed range refers to the motor running speed being lower than 30% of the rated speed. The high speed range refers to the motor running speed being higher than 30% of the rated speed and lower than the rated speed. The reference motor current in the full speed domain is obtained by the following model: Among them, i d_full [k]、i q_full [k] are the reference values ​​of the stator currents of the motor d and q axes in the [k]th system sampling period in the full speed domain; ω[k] is the actual electrical angular velocity in the [k]th system sampling period; ω s is the rated electrical angular velocity; i d_mtpa [k]、i q_mtpa [k] are the reference values ​​of the stator currents of the motor d and q axes in the [k]th system sampling period in the low speed range; i d_lmc [k]、i q_lmc [k] are the reference values ​​of the motor d-axis and q-axis stator currents in the [k]th system sampling period in the high-speed range; in, Among them, T e [k] is the motor torque in the [k]th system sampling period, which is related to the actual electrical angular velocity ω[k]; A d , B d , C d and D d They are the motor torque T reflecting the stator current reference value of the motor d axis in the low speed range. e The coefficients of the cubic, quadratic, linear and constant terms of [k]; A q , B q , C q and D q They are the motor torque T reflecting the motor q-axis stator current reference value in the low speed range. e The coefficients of the cubic, quadratic, linear, and constant terms of [k]; in, Among them, ψ f is the magnetic linkage; n p is the number of motor pole pairs; L d , L q are the inductances of the d and q axes respectively; R c is the equivalent iron loss resistance; γ is the weighted average parameter, expressed as: In the formula, R s is the armature winding resistance.

8. A computer system comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

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