Driving method of permanent magnet synchronous motor system with bidirectional DC / DC converter

Abstract

The present application discloses a driving method for a permanent magnet synchronous motor system with a bidirectional DC / DC converter, which relates to the field of permanent magnet synchronous motors. The method is aimed at a permanent magnet synchronous motor system that adds a bidirectional DC / DC converter to reduce voltage fluctuations of a power supply battery. According to the operating point of the permanent magnet synchronous motor system, the operating constraints of the motor torque are considered, and the generalized Lagrange multiplier method is used to iteratively solve the system operating parameters that maximize the system efficiency. The optimal system operating parameters are determined by automatic optimization, and the motor is driven according to the optimal system operating parameters. This method can enable the permanent magnet synchronous motor system to operate at the optimal operating point and have the maximum system efficiency, thereby achieving the effect of increasing the cruising range.

Description

Technical Field

[0001] The present application relates to the field of permanent magnet synchronous motors, and in particular to a driving method for a permanent magnet synchronous motor system with a bidirectional DC / DC converter. Background Art

[0002] Permanent Magnetic Synchronous Machines (PMSMs) are widely used in new energy vehicles due to their simple structure, high efficiency, high power density, and high reliability. In industries such as new energy vehicles, marine power generation, and metal cutting, where high-speed motor operation is required, traditional vector-controlled PMSM systems cannot meet these demands. However, flux-weakening control inherits the closed-loop control properties of vector control while also offering a wide speed regulation range and smooth flux-weakening transitions. This allows PMSMs to achieve a wider speed regulation range, thus enabling wide speed regulation for new energy vehicles.

[0003] However, for permanent magnet synchronous motor systems, the DC bus voltage varies with the operating conditions of the permanent magnet synchronous motor and the charge level of the power supply battery. Under weak magnetic field control, voltage limitations reduce the motor's efficiency and current dynamic performance. Excessive back EMF also poses the risk of high-speed runaway. Especially when the power supply battery uses a battery with softer output characteristics, such as the new sodium-ion battery, the DC bus voltage fluctuates more widely, reducing the motor's output and affecting the normal operation and control of the permanent magnet synchronous motor system. By adding a bidirectional DC / DC converter to the inverter stage of the permanent magnet synchronous motor system, the voltage fluctuations of the power supply battery can be effectively isolated, and the high-speed performance of the permanent magnet synchronous motor can be improved, reducing the risk of high-speed runaway of the motor and the risk of high-speed permanent magnet synchronous motor runaway.

[0004] However, after adding the bidirectional DC / DC converter, the system efficiency of the permanent magnet synchronous motor system is jointly affected by the bidirectional DC / DC converter, inverter and permanent magnet synchronous motor. Theoretically, the permanent magnet synchronous motor has an infinite number of DC bus voltage values, but the system efficiency is different under different DC bus voltage values, which can easily reduce the system efficiency and affect the vehicle's endurance. Summary of the Invention

[0005] In response to the above-mentioned problems and technical requirements, the applicant has proposed a driving method for a permanent magnet synchronous motor system with a bidirectional DC / DC converter. The technical solution of this application is as follows:

[0006] A driving method for a permanent magnet synchronous motor system with a bidirectional DC / DC converter, wherein the permanent magnet synchronous motor system comprises a power supply battery, a bidirectional DC / DC converter, an inverter, and a permanent magnet synchronous motor connected in sequence, wherein a DC bus capacitor C is connected across the positive and negative poles of the DC bus of the inverter. bus , the driving method includes:

[0007] Establishing operational optimization objectives and operational constraints. The operational optimization objectives include maximizing the system efficiency of the permanent magnet synchronous motor system, and the operational constraints include maintaining a constant motor torque. Both the motor torque and the system efficiency are related to the system operational parameters of the permanent magnet synchronous motor system to be optimized.

[0008] The generalized Lagrange multiplier method is used to iteratively solve the operation optimization target under the operation constraints, and determine the system operation parameters that maximize the system efficiency;

[0009] The switching tubes in the bidirectional DC / DC converter and the switching tubes in the inverter are controlled according to the system operating parameters.

[0010] Its further technical solution is to run the optimization target to the d-axis current I of the permanent magnet synchronous motor d , q-axis current I q and the DC bus voltage U dc As the variable to be optimized, the generalized Lagrange multiplier method is used to iteratively solve the d-axis current I that maximizes the system efficiency. d , q-axis current I q and DC bus voltage U dc .

[0011] Its further technical solution is to construct the operation optimization target as The constructed running constraints are T e (I d ,I q ,U dc )=T e0 ;

[0012] Among them, η(I d ,I q ,U dc ) represents the d-axis current I d , q-axis current I q and DC bus voltage U dc Influence of system efficiency, T e (I d ,I q ,U dc ) represents the d-axis current I d , q-axis current I q and DC bus voltage Udc The motor torque affected is ω, the motor speed of the permanent magnet synchronous motor, U b is the supply voltage of the battery, I b is the supply current of the battery, T e0 Indicates the constant value that the motor torque is to reach.

[0013] A further technical solution is to use the generalized Lagrange multiplier method to iteratively solve the operation optimization target under the operation constraints, including:

[0014] According to the operation constraints, the operation optimization objective is converted into an unconstrained equivalent optimization objective. The gradient descent method is used to iteratively solve the system operation parameters that meet the equivalent optimization objective. The equivalent optimization objective is to obtain the minimum value of L(x,λ):

[0015]

[0016] Where η(x) represents the system efficiency under the system operating parameter x, T e (x) represents the motor torque under the system operating parameter x, T e0 represents the constant value that the motor torque is to reach, λ represents the Lagrange multiplier, and ρ represents the penalty factor.

[0017] Its further technical solution is to optimize the system efficiency η(x) and motor torque T in the equivalent optimization target. e (x) and the constant value T that the motor torque needs to reach e0 Complete the per-unit processing.

[0018] A further technical solution is to use the gradient descent method to iteratively solve the equivalent optimization target, including:

[0019] When the n-th iteration value of the Lagrange multiplier λ remains unchanged, the gradient descent method is used to iteratively solve the equivalent optimization objective to obtain the n-th iteration value of the system operation parameter x;

[0020] When the iteration termination condition is not met, the n+1th iteration value of the Lagrange multiplier λ is updated in combination with the penalty factor ρ, and n=n+1 is set to execute again. Under the condition that the nth iteration value of the Lagrange multiplier λ remains unchanged, the steps of iteratively solving the equivalent optimization objective using the gradient descent method are performed;

[0021] When the iteration termination condition is met, the value of the nth iteration is taken as the system operation parameter that meets the equivalent optimization goal.

[0022] A further technical solution is to use the gradient descent method to iteratively solve the equivalent optimization target, including:

[0023] Initialize the first iteration value λ1 of the Lagrange multiplier λ, and initialize the initial value of the system operation parameter x at the (n + 1)-th iteration. Initialize the penalty factor ρ.

[0024] Initialize the iteration number n = 1 and initialize the inner loop iteration number m = 1.

[0025] Calculate the gradient of

[0026] When it is determined that the inner loop termination condition is not satisfied, update to obtain Let m = m + 1 and execute the step of calculating the gradient of again, where α is the iteration step size and ε L is the gradient error limit.

[0027] When it is determined that the inner loop termination condition is satisfied, take as the (n)-th iteration value of the system operation parameter x and calculate

[0028] When ΔT [[ID=3�]] n > ε T or it is determined that the iteration termination condition is not satisfied, update to obtain λ n+1 = λ n + ρ·ΔT n , reset m = 1 and take as the initial value of the parameter at the (n + 1)-th iteration Let n = n + 1 and execute the step of calculating the gradient of again, where ε T is the torque error limit.

[0029] When ΔT n ≤ ε T and it is determined that the iteration termination condition is satisfied, and take the (n)-th iteration value of the system operation parameter x at this time as the system operation parameter that satisfies the equivalent optimization goal.

[0030] A further technical solution thereof is that the method of iteratively solving the equivalent optimization goal by using the gradient descent method further includes:

[0031] In any (n)-th iteration, when and m < M, it is determined that the inner loop termination condition is not satisfied, and when or m ≥ M, it is determined that the inner loop termination condition is satisfied, where M is the maximum iteration number of the inner loop iteration number m.

[0032] A further technical solution thereof is that the method for iteratively solving the equivalent optimization objective by using the gradient descent method further includes:

[0033] Determine that the iteration termination condition is satisfied when the error requirement is met or n ≥ N, and determine that the iteration termination condition is not met when the error requirement is not met and n < N; where, when ΔT n ≤ ε T and it is determined that the error requirement is met, otherwise it is determined that the error requirement is not met, and N is the maximum number of iterations of the iteration number n.

[0034] A further technical solution thereof is that the method for controlling the switching tubes in the bidirectional DC / DC converter and the switching tubes in the inverter according to the system operating parameters includes:

[0035] Controlling the switching tubes in the bidirectional DC / DC converter according to the duty cycle corresponding to the DC bus voltage U dc that makes the system efficiency reach the maximum value;

[0036] Controlling the switching tubes in the inverter according to the duty cycle corresponding to the d-axis current I d and the q-axis current I q that makes the system efficiency reach the maximum value.

[0037] The beneficial technical effects of this application are:

[0038] This application discloses a driving method for a permanent magnet synchronous motor system with a bidirectional DC / DC converter. On the basis of adding a bidirectional DC / DC converter in the permanent magnet synchronous motor system to reduce the voltage fluctuation of the power supply battery, the system operating parameters that make the system efficiency reach the maximum are determined through automatic optimization, and the driving is performed according to the determined system operating parameters, so that the permanent magnet synchronous motor system can operate at the optimal operating point and has the maximum system efficiency, thereby achieving the effect of increasing the cruising range.

[0039] The driving method of this application is based on the operating point of the permanent magnet synchronous motor system and considers the corresponding constraint conditions. Through the generalized Lagrange multiplier method, it iteratively searches for the system operating parameters when the system efficiency reaches the optimum. This search algorithm is divided into two levels of inner and outer search iterations, which simplifies the complexity of the optimization algorithm and can quickly search for the optimal result under different voltages of the power supply battery and motor speeds. Brief Description of the Drawings

[0040] Figure 1 It is the system topology diagram and control block diagram of the permanent magnet synchronous motor system in an embodiment of this application.

[0041] Figure 2It is an iterative flow chart for iteratively solving the system operating parameters that maximize the system efficiency in one embodiment of the present application. DETAILED DESCRIPTION

[0042] The specific implementation of this application will be further described below with reference to the accompanying drawings.

[0043] This application discloses a driving method for a permanent magnet synchronous motor system with a bidirectional DC / DC converter. Figure 1 The topology diagram and control block diagram of the permanent magnet synchronous motor system shown in FIG. 1 are shown in FIG. 2 . The permanent magnet synchronous motor system to which the driving method is applicable includes power supply batteries U connected in sequence. b , bidirectional DC / DC converter, inverter and permanent magnet synchronous motor PMSM. In the bidirectional DC / DC converter, the collector of the switch tube S2 is connected to the positive pole of the DC bus of the inverter, the emitter of the switch tube S2 is connected to the collector of the switch tube S1, and the emitter of the switch tube S1 is connected to the negative pole of the DC bus of the inverter and the power supply battery U b The collector of the switch tube S1 is connected to the power supply battery U through the energy storage inductor L and the load resistor R. b The positive pole of the inverter DC bus is connected to the DC bus capacitor C. bus The common inverters can be used as follows. Figure 1 The three-phase bridge inverter shown in FIG. 1 has its bridge arms connected to the three-phase windings in the permanent magnet synchronous motor system.

[0044] The driving method of this application includes:

[0045] 1. Establish operation optimization objectives and operation constraints.

[0046] The operation optimization goal includes the system efficiency η of the permanent magnet synchronous motor system reaching the maximum value. The operation constraint conditions include the motor torque T of the permanent magnet synchronous motor. e The maximum torque is reached and the value is constant. Assume that the constant value is T e0 . Motor torque T e and system efficiency η are both related to the system operating parameters to be optimized of the permanent magnet synchronous motor system.

[0047] In one embodiment, the system operating parameters to be optimized include the d-axis current I of the permanent magnet synchronous motor. d , q-axis current I q and the DC bus voltage U dc . Then run the optimization target with I d , I q and U dc is the variable to be optimized, affected by the d-axis current I d , q-axis current Iq and DC bus voltage U dc The system efficiency affected can be written as η(I d ,I q ,U dc ). Similarly, the motor torque is also I d , I q and U dc is the variable to be optimized, affected by the d-axis current I d , q-axis current I q and DC bus voltage U dc The affected motor torque can be written as T e (I d ,I q ,U dc ), then the running constraint can be written as T e (I d ,I q ,U dc )=T e0 , T e0 Indicates the constant value that the motor torque is to reach. Motor torque T e It is usually obtained by a torque observer or motor calibration method, which is not described in detail in this application.

[0048] In one embodiment, the system efficiency is calculated by measuring the voltage and current, and the calculation formula is: Where, ω is the motor speed of the permanent magnet synchronous motor, U b is the supply voltage of the battery, I b is the supply current of the power supply battery. In the above formula, the d-axis current I of the permanent magnet synchronous motor d and q-axis current I q The three-phase current i passing through the permanent magnet synchronous motor a 、i b 、i c It can be converted by performing Park transformation on the rotor angle θ.

[0049] 2. After constructing the operation optimization target and operation constraints, the generalized Lagrange multiplier method can be used to iteratively solve the operation optimization target under the operation constraints, that is, to optimize the optimal system efficiency and maximum motor torque, and determine the system operation parameters that maximize the system efficiency. In this application, the d-axis current I that maximizes the system efficiency is obtained by iterative solution. d , q-axis current I q and DC bus voltage U dc .

[0050] When a permanent magnet synchronous motor operates at a certain motor speed ω, solving the operational optimization objective under operational constraints is an optimization problem that includes equality constraints. This application utilizes the generalized Lagrange multiplier method for iterative solution, avoiding the problem of traditional penalty function methods where the penalty factor increases continuously as the problem is solved, leading to ill-conditioned problems. This method has better applicability.

[0051] When using the generalized Lagrange multiplier method to solve the problem, the operation optimization objective is first converted into an unconstrained equivalent optimization objective based on the operation constraints. The equivalent optimization objective is to obtain the minimum value of L(x,λ):

[0052]

[0053] Where η(x) represents the system efficiency under the system operating parameter x, T e (x) represents the motor torque under the system operating parameter x, λ represents the Lagrange multiplier, and ρ represents the penalty factor. The system operating parameter x here includes I d , I q and U dc It should be noted that the system efficiency η(x) and motor torque T in the equivalent optimization objectives e (x) and the constant value T that the motor torque needs to reach e0 Complete per-unit processing to avoid data level differences caused by different dimensions.

[0054] Then, the gradient descent method is used to iteratively solve the system operating parameters that meet the equivalent optimization goal, that is, to obtain the system operating parameters that maximize the system efficiency. The iterative solution method includes:

[0055] First, under the condition that the n-th iteration value of the Lagrange multiplier λ remains unchanged, the gradient descent method is used to iteratively solve the equivalent optimization objective and obtain the n-th iteration value of the system operating parameter x. When the iteration termination condition is not met, the n+1-th iteration value of the Lagrange multiplier λ is updated in combination with the penalty factor ρ, and n=n+1 is set to execute again the step of iteratively solving the equivalent optimization objective under the condition that the n-th iteration value of the Lagrange multiplier λ remains unchanged using the gradient descent method. When the iteration termination condition is met, the n-th iteration value is used as the system operating parameter that meets the equivalent optimization objective. Please refer to Figure 2 As shown in the flowchart, the iterative solution process includes:

[0056] (1) Initialize the Lagrange multiplier λ to the value λ1 for the first iteration, and initialize the system operation parameter x to the initial value of the parameter at the n+1th iteration Initialization and penalty factor ρ.

[0057] (2) Initialize the iteration count n = 1 and initialize the inner loop iteration count m = 1.

[0058] (3) Calculate the gradient of

[0059] (4) When it is determined that the inner loop termination condition is not satisfied, update to obtain let m = m + 1 and return to execute step (3) again. α is the iteration step size, and ε L is the gradient error limit.

[0060] (5) When it is determined that the inner loop termination condition is satisfied, take as the nth iteration value of the system operating parameter x and calculate

[0061] In one embodiment, to avoid difficulty in jumping out of the inner loop, the inner loop iteration count m also has a corresponding maximum iteration count M. Then, in any iteration, when and m < M, it is determined that the inner loop termination condition is not satisfied. When or m ≥ M, it is determined that the inner loop termination condition is satisfied. That is, even if the condition of is not satisfied, when the inner loop iteration count m reaches the maximum iteration count M, the inner loop is directly jumped out.

[0062] (6) When ΔT n > ε T or (1) Calculate the gradient of while determining that the error requirement is not satisfied, it is determined that the iteration termination condition is not satisfied, update to obtain λ n+1 = λ n + ρ·ΔT n , reset m = 1 and take as the parameter initial value for the (n + 1)th iteration let n = n + 1 and return to step (3) to enter the next outer loop. ε the gradient of T is the torque error limit.

[0063] (7) When ΔT n ≤ ε T and while determining that the error requirement is satisfied, it is determined that the iteration termination condition is satisfied, and take the nth iteration value of the system operating parameter x at this time as the system operating parameter that satisfies the equivalent optimization objective.

[0064] Similarly, the number of iterations n of the outer loop also has a corresponding maximum number of iterations N. When the error requirement is not met and n < N, it is determined that the iteration termination condition is not met and the next iteration is entered. When it is determined that the error requirement is met or n ≥ N, it is determined that the iteration termination condition is met. That is, even if the error requirement is not met, when the number of iterations n of the outer loop reaches the maximum number of iterations N, the outer loop is immediately exited and the traversal ends.

[0065] 3. Control the switching tubes in the bidirectional DC / DC converter and the switching tubes in the inverter according to the system operating parameters. This includes: according to the DC bus voltage U that makes the system efficiency reach the maximum value dc Control the switching tubes in the bidirectional DC / DC converter according to the corresponding duty cycle d1. According to the d-axis current I that makes the system efficiency reach the maximum value d and the q-axis current I q Control the switching tubes in the inverter according to the corresponding duty cycle d2. The duty cycles d1 and d2 can be obtained through existing common modulation algorithms, and this application will not elaborate further.

[0066] Based on the driving method provided in this application, in one example, assume that the motor speed ω of the permanent magnet synchronous motor is 2000 rpm, the supply voltage U of the power supply battery b = 250V, and the constant value T that the motor torque needs to reach e0 = 100 Nm. Theoretically, there are infinitely many values of the DC bus voltage U dc for this permanent magnet synchronous motor system, but the system efficiency of the permanent magnet synchronous motor system is different for different values of the DC bus voltage U dc . Using the driving method of this application, it is determined that I d = -53A, I q = 160A, and U dc = 391V that make the system efficiency reach the maximum value. Then, controlling the permanent magnet synchronous motor system according to this value can make the system efficiency the highest. In this example, the comparison of the system efficiency of the permanent magnet synchronous motor system under different system operating parameters is shown in the following table. It can be seen from the comparison that when I d = -53A, I q = 160A, and U dc = 391V, the system efficiency η reaches the maximum value of 94.7%. When under other system operating parameters, the system efficiency is relatively lower.

[0067] <![CDATA[U b (V)]]> <![CDATA[U dc (V)]]> <![CDATA[T e (Nm)]]> <![CDATA[I d (A)]]> <![CDATA[I q (A)]]> η(%) 250 391 100 -53 160 94.7 250 344 100 -90 171 92.2 250 280 100 -126 182 90.3

[0068] The above description is only a preferred embodiment of the present application, and the present application is not limited to the above embodiments. It is understood that other improvements and variations directly derived or imagined by those skilled in the art without departing from the spirit and concept of the present application should be considered to be included in the scope of protection of the present application.

Claims

1. A method for driving a permanent magnet synchronous motor system with a bidirectional DC / DC converter, wherein the permanent magnet synchronous motor system comprises a power supply battery, a bidirectional DC / DC converter, an inverter, and a permanent magnet synchronous motor connected in sequence, wherein a DC bus capacitor is connected across the positive and negative poles of the DC bus of the inverter. , characterized in that, The driving method includes: Constructing an operation optimization target and an operation constraint condition, wherein the operation optimization target includes that the system efficiency of the permanent magnet synchronous motor system reaches a maximum value, and the operation constraint condition includes that the motor torque of the permanent magnet synchronous motor is a constant value; the motor torque and the system efficiency are both related to the system operation parameters to be optimized of the permanent magnet synchronous motor system; the operation optimization target is based on the d-axis current of the permanent magnet synchronous motor , q-axis current and the DC bus voltage of the inverter is the variable to be optimized; the operation optimization target constructed is , the constructed operating constraints are ;in, Indicates that the d-axis current , q-axis current and DC bus voltage Affects system efficiency, Indicates that the d-axis current , q-axis current and DC bus voltage The impact of motor torque, is the motor speed of the permanent magnet synchronous motor, is the supply voltage of the power supply battery, is the supply current of the power supply battery, Indicates the constant value that the motor torque is to reach; The operation optimization target is converted into an unconstrained equivalent optimization target according to the operation constraint condition, and the system operation parameters that meet the equivalent optimization target are iteratively solved by the gradient descent method. The system operation parameters that make the system efficiency reach the maximum value are determined, including the d-axis current that makes the system efficiency reach the maximum value. , q-axis current and DC bus voltage ; The equivalent optimization objective is Get the minimum value: ;in, Indicates system operating parameters The system efficiency under Indicates system operating parameters The motor torque under Indicates the constant value that the motor torque is to reach. represents the Lagrange multiplier, represents the penalty factor; The switch tubes in the bidirectional DC / DC converter and the switch tubes in the inverter are controlled according to the system operating parameters.

2. The driving method according to claim 1, wherein: System efficiency in the equivalent optimization objective , motor torque and the constant value that the motor torque needs to reach Complete the per-unit processing.

3. The driving method according to claim 1, wherein: The method of iteratively solving the equivalent optimization target using the gradient descent method includes: In the Lagrange multiplier No. When the iteration value remains unchanged, the gradient descent method is used to iteratively solve the equivalent optimization target and obtain the system operation parameters. No. Iteration value; When the iteration termination condition is not met, combined with the penalty factor Update to get the Lagrange multiplier No. Iterate the value and let Again, the Lagrange multiplier No. When the iteration value remains unchanged, the gradient descent method is used to iteratively solve the equivalent optimization target; When the iteration termination condition is met, the The values taken in the iterations are used as the system operating parameters that meet the equivalent optimization objectives.

4. The driving method according to claim 3, wherein: The method of iteratively solving the equivalent optimization target using the gradient descent method includes: Initialize the Lagrange multiplier The first iteration value of , initialize system operating parameters In the Initial values of parameters for iterations , initialization and penalty factors ; Initialization iteration count And initialize the number of inner loop iterations ; calculate Gradient ; when When it is determined that the inner loop termination condition is not met, the update is obtained ,make and perform the calculation again Gradient Steps, is the iteration step length, is the gradient error limit; when When the inner loop termination condition is met, As system operating parameters No. Iterations take values and calculate ; when or When it is determined that the iteration termination condition is not met, the update is obtained , reset and will As the first Initial values of parameters for iterations ,make and perform the calculation again Gradient Steps, is the torque error limit; when and When the iteration termination condition is met, the system operating parameters at this time are No. The values taken in the iterations are used as the system operating parameters that meet the equivalent optimization objectives.

5. The driving method according to claim 4, wherein: The method of iteratively solving the equivalent optimization target using the gradient descent method also includes: In any In the iterations, when and When the inner loop termination condition is not met, Time or When the inner loop termination condition is met, is the number of inner loop iterations The maximum number of iterations.

6. The driving method according to claim 4, wherein: The method of iteratively solving the equivalent optimization target using the gradient descent method also includes: When the error requirements are met or When the iteration termination condition is met, it is determined that It is determined that the iteration termination condition is not met when and When the error requirement is met, it is determined that the error requirement is met; otherwise, it is determined that the error requirement is not met. is the number of iterations The maximum number of iterations.

7. The driving method according to claim 1, wherein: The method for controlling the switch tube in the bidirectional DC / DC converter and the switch tube in the inverter according to the system operating parameters includes: According to the DC bus voltage that makes the system efficiency reach the maximum The corresponding duty cycle controls the switch tube in the bidirectional DC / DC converter; According to the d-axis current that maximizes the system efficiency and q-axis current The corresponding duty cycle controls the switch tube in the inverter.

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