Control methods, storage media and electronic equipment for three-level inverters in electric vehicles

Abstract

This invention discloses a control method, storage medium, and electronic device for a three-level inverter in an electric vehicle, comprising: real-time acquisition of capacitor voltage and three-phase current; calculation of the midpoint potential deviation based on the capacitor voltage, and comparison of the midpoint potential deviation with a preset deviation threshold to obtain the midpoint potential error; calculation of a distribution factor based on the midpoint potential error using a PI control algorithm; receiving torque commands from the vehicle controller and calculating the target voltage vector based on the three-phase current; inputting the target voltage vector into a preset motor-inverter deep coupling model to obtain the sector region of the target voltage vector; determining the original action time corresponding to the three basic voltage vectors based on the sector region; dynamically adjusting the action time of the positive and negative small vectors based on the distribution factor and the original action time to generate a pulse width modulation signal and control the switching action of the three-level inverter. This invention effectively suppresses midpoint potential drift through a software algorithm.

Description

Technical Field

[0001] This invention relates to the field of automotive technology, and in particular to a control method, storage medium, and electronic device for a three-level inverter in an electric vehicle. Background Technology

[0002] Permanent magnet synchronous motors (PMSMs) have become the preferred motor type for drive systems in new energy vehicles due to their high power density, high efficiency, and excellent control performance. The core of their drive control system is the inverter, which converts the direct current (DC) from the power battery into the three-phase alternating current (AC) required by the motor. Overall development in this technology revolves around achieving lower output harmonics, higher efficiency, higher DC voltage utilization, and greater reliability.

[0003] Neutral point clamped (NPC) three-level inverters are widely used due to their advantages such as low output harmonics and low device voltage stress. However, the NPC three-level topology inherently suffers from DC-side neutral point potential drift. This is because when the inverter is at the output neutral level (0 potential), the load current flows into or out of the neutral point of the DC bus capacitor, causing the upper and lower voltage divider capacitors to drift. , The uneven charging and discharging process causes fluctuations in the midpoint potential. This leads to output waveform distortion and system instability. Severe imbalance in the midpoint potential distorts the output voltage waveform, introducing low-order harmonics, which negates the waveform quality advantages of the three-level topology and can even cause control instability and overcurrent faults in extreme cases. Simultaneously, uneven voltage stress distribution shortens the lifespan of capacitors and switching devices, affecting the long-term reliability of the system. Furthermore, under the dynamic operating conditions of frequent acceleration and deceleration and drastic load changes in new energy vehicles, fixed modulation strategies cannot adapt to rapid changes in the midpoint potential, resulting in deteriorated control performance.

[0004] Existing technologies typically address DC-side midpoint potential drift by adding complex hardware, which not only increases system cost and size and reduces reliability but also introduces additional losses. Therefore, finding a control scheme that can accurately, quickly, and adaptively compensate for the midpoint potential through software algorithms without adding external hardware, and without sacrificing the inherent performance advantages of a three-level inverter, has become a pressing technical challenge in this field. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of existing technologies that solve the problem of DC side midpoint potential drift by adding complex hardware, which not only increases system cost and size and reduces reliability, but also introduces additional losses. The invention provides a control method, storage medium and electronic device for a three-level inverter for electric vehicles.

[0006] The technical solution of the present invention provides a control method for a three-level inverter in an electric vehicle, comprising: Real-time acquisition of capacitor voltages of the upper and lower capacitors on the DC bus of the three-level inverter and three-phase current of the permanent magnet synchronous motor; The midpoint potential deviation is calculated based on the capacitor voltage, and the midpoint potential deviation is compared with a preset deviation threshold to obtain the midpoint potential error. A proportional-integral feedback control algorithm is used to calculate the allocation factor based on the midpoint potential error, wherein the value range of the allocation factor is [-1, 1]. Upon receiving the torque command from the vehicle controller, the target voltage vector is calculated based on the three-phase current; The target voltage vector is input into a preset motor-inverter deep coupling model to obtain the sector region of the target voltage vector; The original action time corresponding to the three basic voltage vectors is determined based on the sector region. The three basic voltage vectors include a large vector, a medium vector, and a small vector. The small vector includes a positive small vector and a negative small vector. The action times of the positive small vector and the negative small vector are dynamically adjusted according to the allocation factor and the original action time, while keeping the action times of the large vector and the medium vector unchanged. A pulse width modulation signal is generated based on the adjusted action time of each vector. The switching transistors of the three-level inverter are controlled according to the pulse width modulation signal.

[0007] Furthermore, the method employs a proportional-integral feedback control algorithm to calculate the allocation factor based on the midpoint potential error, and then further includes: Based on the motor-inverter deep coupling model, according to the three-phase current and the target voltage vector, the midpoint current generated by the switching state of the three-level inverter in the current control cycle is predicted, and the prediction allocation factor for offsetting the midpoint current is calculated. The predicted allocation factor and the allocation factor are superimposed to generate the target allocation factor, and the target allocation factor is subjected to amplitude limiting so that the value of the target allocation factor is within the range of [-1, 1]. The step of dynamically adjusting the action time of the positive small vector and the negative small vector according to the allocation factor and the original action time includes: The duration of action of the positive and negative small vectors is adjusted according to the target allocation factor.

[0008] Furthermore, calculating the feedforward allocation factor to offset the predicted midpoint current includes: Based on the volt-second balance principle, a small vector time allocation ratio is calculated to make the average value of the midpoint current within one pulse width modulation cycle zero, which is then used as the feedforward compensation amount.

[0009] Furthermore, the proportional-integral feedback control algorithm is used to calculate the allocation factor based on the midpoint potential error, including: The allocation factor is calculated using the following formula: , in, The allocation factor; The midpoint potential error; This is the proportionality coefficient; are integral coefficients, and and Dynamic gain scheduling is performed based on the real-time speed and load torque of the permanent magnet synchronous motor.

[0010] Furthermore, the motor-inverter deep coupling model is constructed using the following method: A high-order nonlinear mathematical model of the permanent magnet synchronous motor is established in the rotor synchronous rotation coordinate system; A mapping relationship between the switching state and the midpoint current of a midpoint clamped three-level inverter is established to obtain the deep coupling model of the motor-inverter.

[0011] Furthermore, the higher-order nonlinear mathematical model is as follows: , in, and These are the d-axis and q-axis voltages; and These are the d-axis and q-axis currents; Stator resistance; and For d-axis and q-axis inductance; Electric angular velocity; It is a permanent magnet flux linkage.

[0012] Furthermore, the step of inputting the target voltage vector into a preset motor-inverter deep coupling model to obtain the sector region of the target voltage vector includes: The target voltage vector is input into the motor-inverter deep coupling model; The large region in which the target voltage vector is located is determined based on the angle of the target voltage vector. The sector region is obtained by determining the small region in which the target voltage vector is located based on the linear inequality geometric relationship of the projections of the target voltage vector onto the α-axis and β-axis.

[0013] Furthermore, the step of dynamically adjusting the action times of the positive small vector and the negative small vector based on the allocation factor and the original action time includes: The action time of the positive small vector and the negative small vector is dynamically adjusted using the following method: , in, The duration of action of the negative small vector; The duration of action of the positive small vector; As the allocation factor; The total duration of action of the small vector.

[0014] The present invention also provides a computer-readable storage medium that stores computer instructions, which, when executed by a computer, are used to perform all steps of the three-level inverter control method for electric vehicles as described above.

[0015] The present invention also provides an electronic device, comprising: At least one processor; and, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the electric vehicle three-level inverter control method as described above.

[0016] The above technical solution has the following beneficial effects: 1) Effectively suppressing midpoint potential drift: By dynamically adjusting the action time of the positive and negative small vectors, this method can compensate for the midpoint current in real time, significantly reduce the fluctuation amplitude of the midpoint potential, keep the voltage difference between the upper and lower capacitors within the allowable range, and improve system stability.

[0017] 2) Improved output waveform quality: Due to the effective balance of the midpoint potential, the harmonic content of the output current and voltage is significantly reduced, and the waveform distortion rate is reduced, making it suitable for applications with high current quality requirements, such as electric vehicles and precision servo systems.

[0018] 3) Enhance system adaptability and reliability: This method is based on software algorithms and can maintain the midpoint potential balance under a wide range of load and speed changes without increasing hardware costs, thus extending the life of capacitors and switching devices and improving the overall system reliability.

[0019] 4) High control precision and fast response: The closed-loop PI control strategy is adopted, combined with the high-resolution characteristics of SVPWM modulation, to achieve microsecond-level dynamic compensation, ensuring the accuracy of motor torque control and the dynamic response performance of the system.

[0020] 5) Strong engineering applicability: It is compatible with existing three-level inverter hardware platforms, has a high degree of algorithm modularity, is easy to integrate into motor control systems, and has good portability and promotion value. It is especially suitable for medium and high voltage, high power permanent magnet synchronous motor drive scenarios. Attached Figure Description

[0021] The disclosure of this invention will become more readily understood by referring to the accompanying drawings. It should be understood that these drawings are for illustrative purposes only and are not intended to limit the scope of protection of this invention. In the drawings: Figure 1 A flowchart illustrating the workflow of a three-level inverter control method for electric vehicles according to an embodiment of the present invention; Figure 2 This is a signal flow diagram of a permanent magnet synchronous motor provided in an embodiment of the present invention; Figure 3 This is a spatial voltage vector region partitioning diagram of a three-level inverter provided in an embodiment of the present invention; Figure 4 A schematic diagram of the target voltage vector provided in an embodiment of the present invention; Figure 5 The basic voltage vector action time diagram of sector I provided in this embodiment of the invention; Figure 6 This is a switch sequence diagram of different regions within Region I provided in an embodiment of the present invention; Figure 7 The SVPWM modulation waveform diagram provided in the embodiment of the present invention; Figure 8 A flowchart illustrating a preferred embodiment of the present invention provides a control method for a three-level inverter in an electric vehicle. Figure 9 This is a schematic diagram of the hardware structure of an electronic device for controlling a three-level inverter in an electric vehicle, provided as an embodiment of the present invention. Detailed Implementation

[0022] The specific embodiments of the present invention will be further described below with reference to the accompanying drawings.

[0023] It is readily understood that, based on the technical solution of this invention, various structural and implementation methods can be interchanged by those skilled in the art without altering the essential spirit of the invention. Therefore, the following detailed embodiments and accompanying drawings are merely illustrative examples of the technical solution of this invention and should not be considered as the entirety of the invention or as limitations or restrictions on the technical solution of the invention.

[0024] The directional terms such as up, down, left, right, front, back, front, back, top, and bottom mentioned or possibly used in this specification are defined relative to the structures shown in the accompanying drawings. They are relative concepts and may therefore vary depending on their location and usage. Therefore, these or other directional terms should not be interpreted as restrictive.

[0025] like Figure 1 As shown, an embodiment of the present invention provides a three-level inverter control method for electric vehicles, comprising: Step S101: Real-time acquisition of the capacitor voltage of the upper and lower capacitors of the DC bus of the three-level inverter and the three-phase current of the permanent magnet synchronous motor; Step S102: Calculate the midpoint potential deviation based on the capacitor voltage, and compare the midpoint potential deviation with a preset deviation threshold to obtain the midpoint potential error; Step S103: Using a proportional-integral feedback control algorithm, calculate the allocation factor based on the midpoint potential error, wherein the value range of the allocation factor is [-1, 1]; Step S104: Receive the torque command from the vehicle controller and calculate the target voltage vector based on the three-phase current; Step S105: Input the target voltage vector into a preset motor-inverter deep coupling model to obtain the sector region of the target voltage vector; Step S106: Determine the original action time corresponding to the three basic voltage vectors according to the sector region. The three basic voltage vectors include a large vector, a medium vector, and a small vector. The small vector includes a positive small vector and a negative small vector. Step S107: Dynamically adjust the action time of the positive small vector and the negative small vector according to the allocation factor and the original action time, while keeping the action time of the large vector and the medium vector unchanged; Step S108: Generate pulse width modulation signals based on the adjusted action times of each vector; Step S109: Control the switching transistors of the three-level inverter to operate according to the pulse width modulation signal.

[0026] Specifically, the electric vehicle three-level inverter control method provided by this invention is mainly applied to NPC three-level inverters. The system mainly includes a permanent magnet synchronous motor, an NPC three-level inverter, a sensing unit, and a control unit, with the permanent magnet synchronous motor as the controlled object. The NPC three-level inverter, as the core power conversion unit, has a DC bus consisting of two series-connected filter capacitors. , The system is composed of a current sensor, a voltage sensor, and a position sensor. The current sensor is used to detect the three-phase current of the motor. The midpoint O is the key monitoring point. , , The voltage sensor is used to detect the total voltage of the DC bus. and midpoint potential deviation Position sensors (such as encoders) are used to detect the rotor position θ and speed ω. The control unit is used to perform the following steps: In step S101, the capacitor voltages of the upper and lower capacitors on the DC bus are acquired in real time. The three-phase current of a permanent magnet synchronous motor; In step S102, based on the capacitor voltage Calculate the midpoint potential deviation and the midpoint potential deviation The midpoint potential error is obtained by comparing it with the deviation threshold. The preferred deviation threshold is 0.

[0027] In step S103, the midpoint potential error is... Input a proportional-integral (PI) controller to calculate the allocation factor. .

[0028] In one embodiment, to further improve accuracy, a proportional-integral feedback control algorithm is employed to calculate the allocation factor based on the midpoint potential error, including: The allocation factor is calculated using the following formula: , in, The allocation factor; The midpoint potential error; This is the proportionality coefficient; are integral coefficients, and and Dynamic gain scheduling is performed based on the real-time speed and load torque of the permanent magnet synchronous motor.

[0029] To ensure system stability, the allocation factor... Limit the amplitude to ensure that its value is within the range of [-1, 1], thereby obtaining the allocation factor for the current control cycle.

[0030] In step S104, a torque command is received from the vehicle controller, and the three-phase current is subjected to Clark and Park transformations to obtain the feedback current in the rotating dq coordinate system. and Then, the PI controllers in the speed loop (outer loop) and current loop (inner loop) calculate the dq-axis reference voltage required for the current control cycle. and After undergoing the inverse Park transformation, a static state is obtained. α-β Target voltage vector in coordinate system .

[0031] In step S105, based on the target voltage vector The motor-inverter deep coupling model executes the traditional three-level space vector pulse width modulation (SVPWM) algorithm to obtain the target voltage vector. The sector area.

[0032] In one embodiment, the step of inputting the target voltage vector into a preset motor-inverter deep coupling model to obtain the sector region of the target voltage vector includes: The target voltage vector is input into the motor-inverter deep coupling model; The large region in which the target voltage vector is located is determined based on the angle of the target voltage vector. The sector region is obtained by determining the small region in which the target voltage vector is located based on the linear inequality geometric relationship of the projections of the target voltage vector onto the α-axis and β-axis.

[0033] Specifically, the purpose of region determination is mainly to identify the three basic vectors of the synthesized reference voltage vector. The SVPWM algorithm divides the entire vector space into six large regions based on the three-level basic space vector diagram, and then divides each large region into six smaller regions, as shown in the diagram below. Figure 3 As shown. The large area is divided into 60° sections, thus allowing for the calculation based on the target voltage vector. First, determine the large area where the target is located based on the angle, then determine the target voltage vector. The angle and the geometric relationship between its projection on the α-axis and β-axis determine the small region in which it is located.

[0034] by Figure 4 The target voltage vector shown For example, to determine its location, let Firstly, by angle It can be determined that it is located in Region I, and then let it be in shaft and The projections of the axes are respectively , Then there is , .

[0035] 1) When 0° < At <30°, the target voltage vector Located within I1, I3, and I5.

[0036] when At that time, the target voltage vector Located in region I1; when At that time, the target voltage vector Located in area I5; when and At that time, the target voltage vector Located in region I3.

[0037] 2) When 30° < When <60°, the target voltage vector Located within I2, I4, and I6.

[0038] when At that time, the target voltage vector Located in area I2; when At that time, the target voltage vector Located in area I6; when and At that time, the target voltage vector Located in area I4.

[0039] In step S106, the target voltage vector is determined. Within the given region, the composite target voltage vector is found using the Nearest Three Vector (NTV) rule. The three basic vectors , , , and the target voltage vector Substituting all the equations into the volt-second equilibrium system:

[0040] by Figure 4 Target voltage vector For example, let , , Substituting, we get:

[0041] in .

[0042] Similarly, the target voltage vector can be obtained. The initial duration of the fundamental voltage vector when located in other regions. The total duration of the positive and negative small vectors is... The initial duration of the basic voltage vector in different regions within region I is as follows: Figure 5 As shown.

[0043] In step S107, the target voltage vector is selected. The three basic voltage vectors required for synthesis , , And calculate the duration of action of the three basic voltage vectors. , , Then, based on the allocation factor k Readjust the duration of the positive and negative small vectors. When ΔV>0 (the voltage of the upper capacitor is too high). When >0, increase the duration of action of the negative small vector. Reduce the duration of action of small positive vectors Use more negative small vectors to lower the midpoint potential; when ΔV<0 (lower capacitor voltage is too high). When <0, increase the duration of action of the small positive vector. Reduce the duration of action of negative small vectors Use more positive small vectors to raise the midpoint potential; when ΔV=0, When =0, = = To maintain the balance of the midpoint potential. For example, if ΔV > 0 (the voltage across the upper capacitor is too high), the PI controller may output... =0.6, then the duration of action of the negative small vector is... Extended to 0.8 The duration of action of the positive small vector Reduced to 0.2 This means that the system will use the small negative vector that lowers the midpoint potential for a longer period within this cycle, thereby actively correcting the deviation. The duration of action of the large and medium vectors remains unchanged.

[0044] In one embodiment, to dynamically adjust the action time of the positive and negative small vectors in real time, achieving precise, rapid, and adaptive compensation for the midpoint potential and avoiding DC-side midpoint potential drift, the step of dynamically adjusting the action time of the positive and negative small vectors based on the allocation factor and the original action time includes: The action time of the positive small vector and the negative small vector is dynamically adjusted using the following method: , in, The duration of action of the negative small vector; The duration of action of the positive small vector; As the allocation factor; The total duration of action of the small vector.

[0045] In step S108, the switching sequence is designed using seven-segment SVPWM modulation. The seven-segment SVPWM modulation has two basic principles: first, a small vector is used as the starting vector for each sampling period; second, the output state of one and only one phase bridge arm changes each time the switch is switched.

[0046] Continue with Figure 4 Target voltage vector Taking the design of the switching sequence as an example, the switching sequences of different regions within region I are as follows: Figure 6 As shown.

[0047] Three basic voltage vectors are selected based on the spatial voltage vector region where the modulating wave is located at the modulation time. , , And calculate the three basic voltage vectors. , , Duration of action , , Then, by comparing it with a triangular or sawtooth carrier wave, the pulse width modulation (PWM) signal of the three-level inverter can be obtained. Figure 4 Target voltage vector Taking this as an example, by performing region determination, selecting the basic voltage vector and calculating the vector action time, and designing the switching sequence, a 12-channel SVPWM modulation waveform can be obtained, such as... Figure 7 As shown.

[0048] In step S109, the PWM signal is amplified by the drive circuit and controls the switching transistor of the NPC three-level inverter to drive the permanent magnet synchronous motor to run. The cycle is executed to start the adjustment of the next control cycle, so as to realize the continuous closed-loop control of the midpoint potential.

[0049] The order of steps S101-S103 and steps S104-S106 can be interchanged. The control unit can also execute steps S104-S106 first and then execute steps S101-S103 as needed. Alternatively, steps S101-S103 and steps S104-S106 can be executed simultaneously. The execution order of steps S301-S303 and steps S304-S306 does not affect the effect that the present invention can achieve.

[0050] In this embodiment, by calculating the allocation factor and dynamically adjusting the duration of positive and negative small vectors, the midpoint current is compensated in real time, significantly reducing the fluctuation amplitude of the midpoint potential and keeping the voltage difference between the upper and lower capacitors within the allowable range, thus improving system stability. Furthermore, since the midpoint potential is effectively balanced, the harmonic content of the output current and voltage is significantly reduced, and the waveform distortion rate decreases, making it suitable for applications with high current quality requirements, such as electric vehicles and precision servo systems. At the same time, the precise dynamic balance of the midpoint potential is achieved through software algorithms, maintaining the midpoint potential balance under a wide range of load and speed variations without increasing hardware costs, extending the lifespan of capacitors and switching devices, and improving the overall reliability of the system.

[0051] In one embodiment, the proportional-integral feedback control algorithm is used to calculate the allocation factor based on the midpoint potential error, and then the method further includes: Based on the motor-inverter deep coupling model, according to the three-phase current and the target voltage vector, the midpoint current generated by the switching state of the three-level inverter in the current control cycle is predicted, and the prediction allocation factor for offsetting the midpoint current is calculated. The predicted allocation factor and the allocation factor are superimposed to generate the target allocation factor, and the target allocation factor is subjected to amplitude limiting so that the value of the target allocation factor is within the range of [-1, 1]. The step of dynamically adjusting the action time of the positive small vector and the negative small vector according to the allocation factor and the original action time includes: The duration of action of the positive and negative small vectors is adjusted according to the target allocation factor.

[0052] Specifically, the three-phase current of the permanent magnet synchronous motor is collected in real time and input into the motor-inverter deep coupling model. The midpoint current generated by the switching state of the three-level inverter in the current control cycle is predicted, and the prediction allocation factor is calculated. The prediction allocation factor is used to offset the midpoint current, forming a closed-loop control mechanism of "feedforward prediction + PI feedback". Then, the target allocation factor is formed by superimposing the prediction allocation factor and the allocation factor. The target allocation factor is subjected to amplitude limiting processing so that the value of the target allocation factor is within the range of [-1, 1], which can effectively eliminate the steady-state error of the midpoint potential and achieve zero steady-state error regulation.

[0053] In one embodiment, to further improve accuracy, the calculation of the feedforward allocation factor for offsetting the predicted midpoint current includes: Based on the volt-second balance principle, a small vector time allocation ratio is calculated to make the average value of the midpoint current within one pulse width modulation cycle zero, which is then used as the feedforward compensation amount.

[0054] In one embodiment, the motor-inverter deep coupling model is constructed using the following method: A high-order nonlinear mathematical model of the permanent magnet synchronous motor is established in the rotor synchronous rotation coordinate system; A mapping relationship between the switching state and the midpoint current of a midpoint clamped three-level inverter is established to obtain the deep coupling model of the motor-inverter.

[0055] Specifically, a high-order nonlinear mathematical model of the permanent magnet synchronous motor is established in the dq coordinate system under synchronous rotor rotation. For example... Figure 2 As shown, Figure 2 This demonstrates the signal transmission relationship in the mathematical model of a permanent magnet synchronous motor in a synchronously rotating dq coordinate system, showing the stator voltage. , Stator current , Rotor angular velocity Permanent magnet magnetic flux The dynamic coupling relationship between key physical quantities, and the d-axis inductance q-axis inductance Stator resistance Understanding the influence path of motor parameters on system dynamics provides an intuitive physical basis for establishing precise motor control in the future.

[0056] In one embodiment, to further improve accuracy, the higher-order nonlinear mathematical model is: , in, and These are the d-axis and q-axis voltages; and These are the d-axis and q-axis currents; Stator resistance; and For d-axis and q-axis inductance; Electric angular velocity; It is a permanent magnet flux linkage.

[0057] like Figure 8 As shown, a preferred embodiment of the present invention provides a three-level inverter control method for electric vehicles, comprising: Step S801: Establish a high-order nonlinear mathematical model of the permanent magnet synchronous motor in the rotor synchronous rotation coordinate system; Step S802: Establish the mapping relationship between the switching state and the midpoint current of the midpoint clamped three-level inverter to obtain the deep coupling model of motor-inverter; Step S803: Real-time acquisition of capacitor voltage and three-phase current of the upper and lower capacitors of the DC bus; Step S804: Calculate the midpoint potential deviation based on the capacitor voltage, and compare the midpoint potential deviation with the preset deviation threshold to obtain the midpoint potential error; Step S805: Using a PI control algorithm, calculate the allocation factor based on the midpoint potential error; Step S806: Based on the deep coupling model of motor-inverter, predict the midpoint current generated by the switching state of the three-level inverter in the current control cycle according to the three-phase current and the target voltage vector, and calculate the prediction allocation factor used to offset the midpoint current. Step S807: Superimpose the predicted allocation factor and the allocation factor to generate the target allocation factor, and perform amplitude limiting on the target allocation factor so that the value of the target allocation factor is within [-1, 1]. Step S808: Receive the torque command from the vehicle controller and calculate the target voltage vector based on the three-phase current; Step S809: Input the target voltage vector into the preset motor-inverter deep coupling model to obtain the sector region of the target voltage vector; Step S810: Determine the original application time corresponding to the three basic voltage vectors based on the sector region; Step S811: Adjust the action time of the positive small vector and the negative small vector according to the target allocation factor, while keeping the action time of the large vector and the medium vector unchanged; Step S812: Generate PWM signals based on the adjusted action times of each vector; Step S813: Control the switching transistors of the three-level inverter according to the PWM signal; Step S814: Determine whether the task is complete; Specifically, in step S814, if a stop command or fault command is received, it is determined to be completed and the entire control process ends; otherwise, it is determined to be incomplete and step S803 is executed.

[0058] One embodiment of the present invention provides a computer-readable storage medium for storing computer instructions, which, when executed by a computer, are used to perform all steps of the electric vehicle three-level inverter control method as described in any of the above method embodiments.

[0059] like Figure 9 As shown, a hardware structure diagram of an electronic device for controlling a three-level inverter in an electric vehicle, according to an embodiment of the present invention, includes: At least one processor 901; and, A memory 902 is communicatively connected to at least one processor 901; wherein, The memory 902 stores instructions that can be executed by at least one processor 901, which enables the at least one processor 901 to perform the electric vehicle three-level inverter control method as described in any of the above method embodiments.

[0060] Figure 9 Take the 901 processor as an example.

[0061] The electronic device is preferably an electronic control unit (ECU).

[0062] The electronic device may also include an input device 903 and an output device 904.

[0063] The processor 901, memory 902, input device 903 and output device 904 can be connected by a bus or other means. The figure shows an example of connection by bus.

[0064] The memory 902, as a non-volatile computer-readable storage medium, can be used to obtain non-volatile software programs, non-volatile computer-executable programs, and modules, such as the program instructions / modules corresponding to the three-level inverter control method for electric vehicles in the embodiments of this application, for example, Figure 1 , Figure 8 The method flow is shown. The processor 901 executes various functional applications and data processing by running non-volatile software programs, instructions, and modules acquired in the memory 902, thereby realizing the electric vehicle three-level inverter control method in the above embodiment.

[0065] The memory 902 may include a program acquisition area and a data acquisition area, wherein the program acquisition area may acquire an operating system and an application program required for at least one function; the data acquisition area may acquire data created according to the use of the electric vehicle three-level inverter control method, etc. Furthermore, the memory 902 may include high-speed random access memory and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some embodiments, the memory 902 may optionally include memory remotely located relative to the processor 901, and these remote memories may be connected via a network to the apparatus performing the electric vehicle three-level inverter control method. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0066] The input device 903 can receive user clicks and generate signal inputs related to user settings and function control of the three-level inverter control method for electric vehicles. The output device 904 may include display devices such as a display screen.

[0067] When the one or more modules are accessed in the memory 902 and are run by the one or more processors 901, the electric vehicle three-level inverter control method in any of the above method embodiments is executed.

[0068] The above-described product can perform the methods provided in the embodiments of this application, and has the corresponding functional modules and beneficial effects for performing the methods. Technical details not described in detail in this embodiment can be found in the methods provided in the embodiments of this application.

[0069] The above embodiments are only used to illustrate the technical solutions of the embodiments of the present invention, and are not intended to limit them. Although the embodiments of the present invention have been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A control method of a three-level inverter for an electric vehicle, characterized by, include: Real-time acquisition of capacitor voltages of the upper and lower capacitors on the DC bus of the three-level inverter and three-phase current of the permanent magnet synchronous motor; The midpoint potential deviation is calculated based on the capacitor voltage, and the midpoint potential deviation is compared with a preset deviation threshold to obtain the midpoint potential error. A proportional-integral feedback control algorithm is used to calculate the allocation factor based on the midpoint potential error, wherein the value range of the allocation factor is [-1, 1]. Upon receiving the torque command from the vehicle controller, the target voltage vector is calculated based on the three-phase current; The target voltage vector is input into a preset motor-inverter deep coupling model to obtain the sector region of the target voltage vector; The original action time corresponding to the three basic voltage vectors is determined based on the sector region. The three basic voltage vectors include a large vector, a medium vector, and a small vector. The small vector includes a positive small vector and a negative small vector. The action times of the positive small vector and the negative small vector are dynamically adjusted according to the allocation factor and the original action time, while keeping the action times of the large vector and the medium vector unchanged. A pulse width modulation signal is generated based on the adjusted action time of each vector. The switching transistors of the three-level inverter are controlled according to the pulse width modulation signal.

2. The electric vehicle three-level inverter control method of claim 1, wherein, The proportional-integral feedback control algorithm is used, and the allocation factor is calculated based on the midpoint potential error. The method then includes: Based on the motor-inverter deep coupling model, according to the three-phase current and the target voltage vector, the midpoint current generated by the switching state of the three-level inverter in the current control cycle is predicted, and the prediction allocation factor for offsetting the midpoint current is calculated. The predicted allocation factor and the allocation factor are superimposed to generate the target allocation factor, and the target allocation factor is subjected to amplitude limiting so that the value of the target allocation factor is within the range of [-1, 1]. The step of dynamically adjusting the action time of the positive small vector and the negative small vector according to the allocation factor and the original action time includes: The duration of action of the positive and negative small vectors is adjusted according to the target allocation factor.

3. The electric vehicle three-level inverter control method of claim 2, wherein, The calculation of the feedforward allocation factor used to offset the predicted midpoint current includes: Based on the volt-second balance principle, a small vector time allocation ratio is calculated to make the average value of the midpoint current within one pulse width modulation cycle zero, which is then used as the feedforward compensation amount.

4. The electric vehicle three-level inverter control method of claim 1, wherein, The proportional-integral feedback control algorithm is used to calculate the allocation factor based on the midpoint potential error, including: The allocation factor is calculated using the following formula: ， wherein, is the allocation factor; is the midpoint potential error; is a proportional coefficient; is an integral coefficient, and and Dynamic gain scheduling is performed according to the real-time rotational speed and load torque of the permanent magnet synchronous motor.

5. The electric vehicle three-level inverter control method of claim 1, wherein, The motor-inverter deep coupling model is constructed using the following method: A high-order nonlinear mathematical model of the permanent magnet synchronous motor is established in the rotor synchronous rotation coordinate system; A mapping relationship between the switching state and the midpoint current of a midpoint clamped three-level inverter is established to obtain the deep coupling model of the motor-inverter.

6. The electric vehicle three-level inverter control method of claim 5, wherein, The higher-order nonlinear mathematical model is as follows: ， in, and These are the d-axis and q-axis voltages; and These are the d-axis and q-axis currents; Stator resistance; and For d-axis and q-axis inductance; Electric angular velocity; It is a permanent magnet flux linkage.

7. The electric vehicle three-level inverter control method as described in claim 1, characterized in that, The step of inputting the target voltage vector into a preset motor-inverter deep coupling model to obtain the sector region of the target voltage vector includes: The target voltage vector is input into the motor-inverter deep coupling model; The large region in which the target voltage vector is located is determined based on the angle of the target voltage vector. The sector region is obtained by determining the small region in which the target voltage vector is located based on the linear inequality geometric relationship of the projections of the target voltage vector onto the α-axis and β-axis.

8. The electric vehicle three-level inverter control method as described in claim 1, characterized in that, The step of dynamically adjusting the action time of the positive small vector and the negative small vector according to the allocation factor and the original action time includes: The action time of the positive small vector and the negative small vector is dynamically adjusted using the following method: ， in, The duration of action of the negative small vector; The duration of action of the positive small vector; As the allocation factor; The total duration of action of the small vector.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that, when executed by a computer, are used to perform all the steps of the electric vehicle three-level inverter control method as described in any one of claims 1-8.

10. An electronic device, characterized in that, include: At least one processor; as well as, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the electric vehicle three-level inverter control method as described in any one of claims 1-8.

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