Multi-motor cooperative minimum loss control method and system for linear induction motors

Abstract

The invention discloses a multi-motor cooperative minimum loss control method and system for linear induction motors, and belongs to the technical field of linear motor control. The method comprises the following steps: deducing a function relationship between thrust and total loss of a plurality of motors under the control of minimum loss according to a relationship between a primary flux linkage and loss of a single motor; defining a thrust distribution coefficient, and establishing a multi-motor thrust-total loss optimization model comprising a total thrust constraint, a thrust constraint of each motor, a voltage constraint and a normal force difference constraint of adjacent motors; taking the thrust distribution coefficient as an optimization variable, and adopting a sequential quadratic programming method to carry out optimization distribution on each motor thrust instruction; and finally, according to the optimized thrust instruction of each motor, realizing thrust tracking and loss regulation and control of each motor in combination with a single-motor minimum loss control strategy. According to the invention, cooperative minimum loss control from a single-machine system to a multi-machine system is realized, and the overall operation efficiency of the multi-motor system is effectively improved.

Description

Technical Field

[0001] This invention belongs to the field of linear motor control technology, specifically relating to a method and system for minimum loss control of multiple linear induction motors in a coordinated manner. Background Technology

[0002] High-speed maglev transportation systems with operating speeds of 140-200 km / h offer advantages such as flexible route selection, strong terrain adaptability, and relatively low construction costs. They demonstrate unique advantages in urban, intercity, and tourism scenarios, and have become an important means of connecting high-speed rail and urban rail transit. Among these systems, the use of linear induction motors for traction has become the mainstream technology choice in the industry due to its simple structure, high reliability, cost-effectiveness, and low maintenance costs.

[0003] However, actual operating data shows that the operating efficiency of linear induction motors used in high-speed maglev trains is generally low, typically below 70% of rated efficiency. This problem is mainly caused by two factors. First, due to the open-circuit structure in the primary core of the linear motor, the motor experiences severe end effects during operation: as the operating speed increases and the slip decreases, the air gap magnetic field weakens significantly, causing drastic changes in the motor's equivalent parameters and resulting in softened mechanical characteristics. Under the currently prevalent constant slip frequency control strategy, this change further increases the motor's operating losses. Second, trains often operate under light loads in actual operation, while traditional control methods typically employ a constant excitation flux ratio. This generates unnecessary copper losses under light loads, causing the motor's actual operating efficiency to be far lower than its rated efficiency. These loss problems severely restrict the energy efficiency performance of linear induction motors and limit the rapid promotion and large-scale engineering application of this technology.

[0004] To improve the operating efficiency of linear induction motors, existing research has mainly focused on establishing refined loss models and improving control strategies for individual motors, achieving some success in loss suppression at the single-motor level. However, high-speed maglev trains typically operate in multi-car formations (e.g., 3 to 6 cars), each driven by an independent linear induction motor. Existing minimum-loss control methods generally optimize for individual motors, neglecting the collaborative operation between multiple motors from the perspective of the entire vehicle system. In complex scenarios of multi-motor collaborative operation, the lack of a comprehensive strategy for optimizing the allocation of total thrust commands among motors and collaboratively suppressing total system losses leaves significant room for improvement in the overall vehicle system's energy efficiency. Therefore, a control method capable of achieving optimized collaborative operation of multiple motors under multiple constraints and effectively reducing total system losses is urgently needed. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention provides a method and system for multi-motor cooperative minimum loss control of linear induction motors. It establishes a multi-motor thrust-total loss optimization model under minimum loss control, and then combines a sequential quadratic programming algorithm to optimize the allocation of thrust commands for each motor. Based on the optimized commands, it completes thrust tracking and loss regulation for each motor, thereby achieving multi-motor cooperative control and loss suppression.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] A method for minimum loss control of multiple linear induction motors in a coordinated manner, the method comprising:

[0008] S1: Based on the functional relationship between the primary flux linkage and loss of a single linear induction motor, the functional relationship between the thrust of multiple motors and the total loss under the minimum loss control strategy is derived.

[0009] S2: Define the thrust distribution coefficient to characterize the distribution ratio of total thrust among the motors; determine the mathematical expression of total thrust constraints, thrust constraints of each motor, voltage constraints of each motor, and normal force difference constraints of adjacent motors; based on the functional relationship between the thrust of the multiple motors and the total loss, and the mathematical expression, establish a multi-motor thrust-total loss optimization model with the goal of minimizing the total system loss.

[0010] S3: Select the thrust distribution coefficient as the optimization variable, take the average distribution of total thrust as the initial value of the optimization variable, and use the sequential quadratic programming method to solve the multi-motor thrust-total loss optimization model to obtain the optimal thrust command for each motor.

[0011] S4: The optimal thrust command obtained from the optimized allocation is sent to the minimum loss controller of each motor. Each controller generates a drive signal to track the thrust command of each motor and control the loss, so as to realize the coordinated operation of multiple motors and the suppression of the total system loss.

[0012] Furthermore, the functional relationship between the thrust of the multiple motors and the total loss is expressed as follows: the total system loss is equal to the sum of the losses of each motor, where the loss of each motor is expressed as a function of the thrust of that motor, and the coefficient of the function is related to the specific loss parameters of the corresponding motor.

[0013] Furthermore, in step S2, the total thrust constraint is that the sum of the thrust allocation coefficients of all motors equals 1; the thrust constraint of each motor is that the thrust command allocated to each motor is not greater than its own maximum thrust output capability; the voltage constraint of each motor is that the terminal voltage required for each motor to operate is not greater than the maximum output voltage of its corresponding inverter; and the normal force difference constraint between adjacent motors is that the difference in normal force between any two adjacent motors does not exceed a preset allowable threshold.

[0014] Furthermore, in step S2, the multi-motor thrust-total loss optimization model is specifically: an optimization problem that uses the thrust allocation coefficient as the optimization variable, aims to minimize the total system loss function, and simultaneously satisfies the total thrust constraint, the thrust constraint of each motor, the voltage constraint of each motor, and the normal force difference constraint of adjacent motors.

[0015] Furthermore, in step S3, the process of solving the problem using the sequential quadratic programming method includes: approximating the original nonlinear constrained optimization problem as a quadratic programming subproblem at each iteration point, solving the subproblem to obtain the iteration direction and step size, updating the optimization variables, until the convergence condition is met, and outputting the optimal thrust allocation coefficient.

[0016] Furthermore, in step S4, the single-motor minimum loss control includes the core steps of primary flux and thrust observation, calculating the optimal reference primary flux based on thrust command, performing vector transformation on the reference primary flux, and generating inverter drive pulse signals using predictive flux control.

[0017] Furthermore, the method is applied to a high-speed maglev train consisting of multiple carriages, each carriage being driven by an independent linear induction motor. The state sampling module collects the current and speed information of each motor in real time, and the total thrust command is generated by the upper-level controller based on the running curve or real-time road conditions.

[0018] On the other hand, the present invention provides a multi-motor cooperative minimum loss control system for linear induction motors, applied to the aforementioned control method, including:

[0019] The status sampling module is used to sample the current and speed status quantities of the drive motors of each carriage in real time.

[0020] The total thrust command issuing module is used to generate total thrust commands for all motors based on road conditions or offline generated operating curves.

[0021] The thrust command optimization and allocation module is used to determine the thrust command of each motor based on the total thrust command, combined with the multi-motor thrust-total loss optimization model and optimization allocation algorithm.

[0022] The single-motor minimum loss control module is used to calculate the corresponding optimal primary flux linkage based on the thrust command of each motor, thereby completing the minimum loss control of each motor.

[0023] Thirdly, the present invention provides an electronic device, comprising: one or more processors; and a memory for storing one or more programs; wherein, when the one or more programs are executed by the one or more processors, the one or more processors implement the aforementioned method for multi-motor cooperative minimum loss control of linear induction motors.

[0024] Fourthly, the present invention provides a computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, enable the processor to implement the aforementioned method for minimum loss control of multiple motors in a linear induction motor.

[0025] The beneficial effects of this invention are as follows:

[0026] I. Breaking through the limitations of single-machine optimization, achieving system-level energy efficiency improvement. This invention establishes a multi-motor thrust-total loss optimization model with thrust allocation coefficient as the optimization variable, extending the loss control target from a single motor to the entire multi-motor system. This provides an accurate mathematical model for globally optimizing the allocation of thrust commands to each motor under total thrust demand, achieving a leap from "local optimum" to "system optimum".

[0027] II. The optimization method is practical and feasible, balancing efficiency and dynamic constraints. This invention employs a sequential quadratic programming method to solve optimization models with nonlinear constraints. It can efficiently handle multiple practical constraints, such as total thrust constraints, thrust and voltage limits for each motor, and differences in normal forces between adjacent motors. It transforms the complex optimization problem into a series of iterative quadratic programming subproblems, ensuring the real-time performance and convergence of the optimization algorithm. While reducing the total system loss, it also ensures the stability and safety of train operation.

[0028] Third, the control architecture is clear and easy to implement in engineering. The system architecture proposed in this invention has a clear hierarchy. Based on inheriting and utilizing the mature single-motor minimum loss control strategy, a top-level thrust optimization allocation module is added. This module can dynamically adjust the thrust commands of each motor according to the real-time operating status, and then achieve tracking through the bottom-level control, forming a collaborative control closed loop of "global optimization-local tracking". The structure is clear and easy to integrate and apply in actual train control systems. Attached Figure Description

[0029] Figure 1 This is a flowchart of the multi-motor cooperative minimum loss control method for linear induction motors according to the present invention;

[0030] Figure 2 This is a flowchart of the sequential quadratic programming algorithm provided by the present invention;

[0031] Figure 3 This is a block diagram of the multi-motor cooperative control structure provided by the present invention;

[0032] Figure 4 This is a block diagram of a single-motor minimum loss control structure implemented according to the optimized thrust command provided by the present invention;

[0033] Figure 5 This is a comparison chart of the implementation effects of traditional control and multi-motor cooperative minimum loss control provided by the present invention;

[0034] Figure 6 This is a diagram of the architecture of the linear induction motor multi-motor cooperative minimum loss control system provided by the present invention. Detailed Implementation

[0035] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0036] Figure 1 This is a flowchart of the multi-motor cooperative minimum loss control method for linear induction motors provided by the present invention, which specifically includes the following steps:

[0037] S1: Based on the functional relationship between the primary flux linkage and loss of a single motor, derive the functional relationship between the thrust of multiple motors and the total loss under minimum loss control.

[0038] Specifically, the controllable losses of a linear induction motor include primary and secondary copper losses and iron losses, and the controllable losses of a single motor... It can be represented as:

[0039] (1)

[0040] Among them, R1, R 2eq and R c These are the primary resistance, secondary resistance, and iron loss resistance, respectively. 1d and i 1q Let i be the dq-axis component of the primary current. 2d and i 2q i represents the dq-axis component of the secondary current. cd and i cq Let d be the q-axis component of the iron loss current.

[0041] By selecting the d-axis component ψ of the primary flux linkage 1d As an optimization variable, and combined with the primary magnetic field orientation condition, the loss of a single linear induction motor can be expressed as a function of the primary flux linkage as a single variable:

[0042] (2)

[0043] Among them, L1, L2 and L meq These are the primary inductance, secondary inductance, and magnetizing inductance, respectively; ω2 is the secondary angular velocity; τ is the motor pole pitch; and F... e For the electromagnetic thrust of the motor, k = R c / (R1+R c ), λ = a1, a2, and a3 are loss coefficients used to simplify the expression.

[0044] Further analysis of equation (2) reveals that the motor loss in equation (2) Let be a convex function of the primary d-axis flux linkage as a single variable, meaning that within the range of primary flux linkage in motor design, there must exist a certain primary flux linkage that minimizes motor losses. Setting the first derivative of equation (2) to 0, the analytical expression for the optimal primary flux linkage corresponding to the minimum loss of a single motor can be obtained as follows:

[0045] (3)

[0046] Under any operating condition, the primary flux linkage of the motor is guaranteed to be the optimal flux linkage |ψ by control. 1opt |, thus achieving minimum loss control for the motor. Furthermore, substituting the optimal flux linkage equation (3) into the motor loss equation (2), we obtain the functional relationship between loss and thrust for a single motor under minimum loss control as follows:

[0047] (4)

[0048] Furthermore, considering the speed and parameter differences that exist during the operation of multiple motors, the functional relationship between the thrust of multiple motors and the total loss under minimum loss control can be expressed as:

[0049] (5)

[0050] In this context, the superscript i represents the i-th motor.

[0051] S2: Define the thrust distribution coefficient to characterize the distribution ratio of total thrust among the motors; determine the mathematical representation of the total thrust constraint, the thrust constraint of each motor, the voltage constraint of each motor, and the normal force difference constraint of adjacent motors; and establish a multi-motor thrust-total loss optimization model with the goal of minimizing the total system loss based on the functional relationship between the thrust of the multiple motors and the total loss.

[0052] Specifically, the thrust distribution coefficient N is defined. i For the i-th motor, the assigned thrust command for:

[0053] (6)

[0054] Among them, F total This refers to the total thrust command issued by the upper-level control system. The thrust distribution coefficient should meet the following constraints:

[0055] (7)

[0056] Furthermore, the thrust allocated to each motor should ensure that it meets the maximum thrust output requirement. constraint :

[0057] (8)

[0058] At the same time, the required terminal voltage during operation should be guaranteed to meet the highest voltage that the inverter can output. constraint :

[0059] (9)

[0060] In the formula, u i This represents the voltage of the i-th motor;

[0061] Furthermore, to ensure smooth train operation, the difference in normal force between adjacent motors (where i and j represent motor serial number indices) should be limited to a certain range, namely:

[0062] (10)

[0063] Among them, F nor For the normal force of the motor. Equations (5)-(10) combined can express the multi-motor thrust-total loss optimization model satisfying all constraints as:

[0064] (11)

[0065] S3: Select the thrust distribution coefficient as the optimization variable, take the average distribution of total thrust as the initial value of the optimization variable, and use the sequential quadratic programming method to solve the multi-motor thrust-total loss optimization model to complete the optimized distribution of thrust commands for each motor.

[0066] Specifically, such as Figure 2 As shown, the thrust distribution coefficient matrix x = [N1, N2, …N n ] T As optimization variables, we first assume an average thrust distribution, i.e., x0 = [1 / n, 1 / n,…1 / n]. T To optimize the initial value for iteration, a sequential quadratic programming algorithm is adopted to transform the optimization problem with nonlinear constraints such as thrust and normal force represented by equation (11) into a simple quadratic programming subproblem, and the iteration step size α is updated in real time. k Iteration direction d k The optimal thrust allocation coefficient is output after the error ε meets the convergence accuracy.

[0067] S4: Based on the optimized distribution of thrust commands for each motor, and in conjunction with the existing single-motor minimum loss control, drive signals for each inverter are generated to complete the tracking of thrust commands and loss regulation for each motor, thereby achieving multi-motor collaborative control and loss suppression.

[0068] Specifically, such as Figure 3 As shown, the thrust command for each motor is determined based on the optimal thrust distribution coefficient combined with equation (6). ~ Based on the thrust command combined with formula (3), the reference primary flux linkage of each motor is determined, and the minimum loss control of a single motor is adopted to generate inverter drive pulse signals g1~g based on the thrust command and the reference primary flux linkage. n This enables the tracking of thrust commands and loss control of each motor, achieving multi-motor coordinated control and loss suppression.

[0069] Furthermore, the structural block diagram of the single-motor minimum loss control is as follows: Figure 4 As shown, this includes observations of primary flux linkage and thrust (primary flux linkage ψ1 and thrust F are observed based on primary current i1 and primary voltage u1). e ), reference flux calculation (based on thrust F) e Calculate the reference flux amplitude corresponding to the minimum loss of a single motor based on speed v2. ), Reference primary flux linkage vector transformation (obtaining the reference flux linkage vector based on the reference state and the actual state) The core components include predictive flux control (to achieve accurate control of the reference flux vector), and related technical details can be found in the method proposed in Chinese patent application CN116885998A.

[0070] The implementation effect of the method proposed in this invention is as follows: Figure 5 As shown, taking the coordinated control of four motors as an example, it can be seen that when using conventional average thrust distribution, the losses of each motor are consistent. After optimizing the thrust distribution coefficient using the method proposed in this invention, the losses of each motor are somewhat different, and the losses of some motors are larger than before. However, the total loss of the four motors can be effectively reduced compared to before optimization.

[0071] Figure 6 This is an architecture diagram of a multi-motor cooperative minimum loss control system for linear induction motors provided by the present invention. The system can execute each step of the aforementioned method, specifically including a state sampling module, a total thrust command issuance module, a thrust command optimization allocation module, and a single-motor minimum loss control module, wherein:

[0072] The status sampling module is used to sample the current and speed status quantities of the drive motors of each carriage in real time.

[0073] The total thrust command issuing module is used to generate total thrust commands for all motors based on road conditions or offline generated operating curves.

[0074] The thrust command optimization and allocation module is used to determine the thrust command of each motor based on the total thrust command, combined with the multi-motor thrust-total loss optimization model and optimization allocation algorithm.

[0075] The single-motor minimum loss control module is used to calculate the corresponding optimal primary flux linkage based on the thrust command of each motor, thereby completing the minimum loss control of each motor.

[0076] Thirdly, the present invention provides an electronic device, comprising: one or more processors; and a memory for storing one or more programs; wherein, when the one or more programs are executed by the one or more processors, the one or more processors implement the aforementioned method for multi-motor cooperative minimum loss control of linear induction motors.

[0077] Fourthly, the present invention provides a computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, enable the processor to implement the aforementioned method for minimum loss control of multiple motors in a linear induction motor.

[0078] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for coordinated minimum loss control of multiple linear induction motors, characterized in that, The method comprises: S1: based on the function relationship between the primary flux of a single linear induction motor and the loss, the function relationship between the thrust of multiple motors and the total loss under the minimum loss control strategy is derived; S2: define the thrust distribution coefficient to represent the distribution proportion of the total thrust among the motors; determine the mathematical expression forms of the total thrust constraint, the thrust constraint of each motor, the voltage constraint of each motor, and the normal force difference constraint between adjacent motors; based on the function relationship between the thrust of multiple motors and the total loss, and the mathematical expression forms, a multi-motor thrust-total loss optimization model is established to minimize the total loss of the system; S3: select the thrust distribution coefficient as the optimization variable, take the average distribution of the total thrust as the initial value of the optimization variable, and solve the multi-motor thrust-total loss optimization model by using the sequential quadratic programming method to obtain the optimal thrust command of each motor; S4: the optimal thrust command obtained by optimization distribution is respectively sent to the single motor minimum loss controller corresponding to each motor, and the driving signal is generated by each controller to complete the tracking and loss regulation of the thrust command of each motor, and the collaborative operation of multiple motors and the total loss suppression of the system are realized.

2. The method of claim 1, wherein, In step S1, the function relationship between the thrust of multiple motors and the total loss is represented as: the total loss of the system is equal to the sum of the losses of each motor, wherein the loss of each motor is represented as a function of the thrust of the motor, and the coefficients of the function are related to the specific loss parameters of the corresponding motor.

3. The method of claim 1, wherein, In step S2, the total thrust constraint is that the sum of the thrust distribution coefficients of all motors is equal to 1; the thrust constraint of each motor is that the thrust command allocated to each motor is not greater than the maximum thrust output capacity of itself; the voltage constraint of each motor is that the required terminal voltage of each motor during operation is not greater than the maximum output voltage of the corresponding inverter; and the normal force difference constraint between adjacent motors is that the normal force difference between any two adjacent motors does not exceed a preset allowable threshold.

4. The minimum loss control method for a linear induction motor multi-motor according to claim 1, characterized in that, In step S2, the multi-motor thrust-total loss optimization model is specifically: taking the thrust distribution coefficient as the optimization variable, taking the minimum of the system total loss function as the target, and simultaneously satisfying the optimization problem of the total thrust constraint, the thrust constraint of each motor, the voltage constraint of each motor, and the normal force difference constraint between adjacent motors.

5. The method of claim 1, wherein, In step S3, the solving process by using the sequential quadratic programming method includes: approximating the original nonlinear constraint optimization problem to a quadratic programming subproblem at each iteration point, solving the subproblem to obtain the iteration direction and step length, updating the optimization variable, until the convergence condition is met, and outputting the optimal thrust distribution coefficient.

6. The minimum loss control method for a linear induction motor multi-motor according to claim 1, wherein In step S4, the single motor minimum loss control includes the core links of primary flux and thrust observation, calculation of optimal reference primary flux based on thrust command, vector transformation of reference primary flux, and generation of inverter driving pulse signal by using predictive flux control.

7. The method of claim 1, wherein, The method is applied to a fast maglev train composed of multiple carriages, each carriage is driven by an independent linear induction motor, the current and speed information of each motor is collected in real time by a state sampling module, and the total thrust command is generated by an upper controller according to the running curve or real-time road conditions.

8. A system for coordinated minimum loss control of linear induction motor multi-machines, applied to the control method of any one of claims 1-7, characterized in that, It comprises: A state sampling module is configured to sample current and speed state variables of each drive motor of the carriages in real time. A total thrust instruction issuing module is configured to generate total thrust instructions of all the motors according to road conditions or an offline generated operation curve. A thrust instruction optimization distribution module is configured to determine thrust instructions of each motor according to the total thrust instructions, a multi-motor thrust-total loss optimization model and an optimization distribution algorithm. A single motor minimum loss control module is configured to calculate optimal primary fluxes corresponding to the thrust instructions of each motor, and then complete minimum loss control of each motor.

9. An electronic device, comprising: The method comprises: one or more processors; a memory for storing one or more programs; wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the linear induction motor multi-motor collaborative minimum loss control method of any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer program product has executable instructions stored thereon, which, when executed by a processor, enable the processor to implement the linear induction motor multi-motor collaborative minimum loss control method of any one of claims 1-7.

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