A six-phase electric drive reconfiguration type vehicle-mounted charging system model predictive control method

Abstract

This invention provides a model predictive control method for a six-phase electric drive reconfigurable on-board charging system, belonging to the field of power electronics and electric drive technology. It solves the problems of high current ripple and heavy computational burden on the system. The technical solution includes the following steps: S1: Obtaining the q-axis current setpoint; S2: Obtaining the real-time 0 / 1 axis current setpoint; S3: Acquiring the six-phase current of the six-phase symmetrical permanent magnet synchronous motor; S4: Calculating the predicted current for the next cycle; S5: Selecting the voltage vector for the next cycle; S6: Obtaining the on / off state of the switching transistors in the next cycle; S7: Realizing the operation mode of the six-phase electric drive reconfigurable on-board charging system based on the drive signal of the six-phase inverter. The beneficial effects of this invention are: it can improve the dynamic and steady-state performance of the system while reducing the computational burden and lowering zero-sequence current ripple, and has broad application prospects.

Description

Technical Field

[0001] This invention relates to the fields of power electronics and electric drive technology, and in particular to a model predictive control method for a six-phase electric drive reconfigurable on-board charging system. Background Technology

[0002] In recent years, new energy electric vehicles have developed rapidly due to their advantages of zero emissions and no consumption of fossil energy. New energy electric vehicles use green energy as auxiliary power energy, and convert green energy into electrical energy through new energy power generation technology to charge electric vehicles. The paper: Luo Xiao, Yu Feng, Peng Yong. Six-phase electric drive reconfigurable charger for solar electric vehicles [J]. Power Electronics Technology, 2022, 56(06):78-81. It is written that the current research on new energy power generation technology in my country focuses on photovoltaic power generation, wind power generation, etc., converting solar and wind energy into DC power to charge new energy electric vehicles. Among them, the research on photovoltaic power generation technology is more mature, and it has advantages such as simple mechanical structure, no noise, and low consumption, making the application of photovoltaic power generation technology to the field of electric vehicles a reality. However, when photovoltaic power generation technology is applied to new energy electric vehicles, in order to achieve maximum power point tracking on the photovoltaic side and raise the output voltage of the photovoltaic panel to match the voltage level of the power battery, additional power devices need to be connected between the power battery and the input side, which affects the overall performance of the electric vehicle. The papers "Luo Xiao, Yu Feng, Peng Yong. Six-phase electric drive reconfigurable charger for solar electric vehicles [J]. Power Electronics Technology, 2022, 56(06):78-81" and "Tong Minghao, Cheng Ming, Xu Zhiyuan, Wen Honghui, Hua Wei, Zhu Xiaoyong. Several key technical issues and solutions for on-board integrated charging systems for electric vehicles [J]. Journal of Electrical Engineering, 2021, 36(24):5125-5142" state that: Based on this, research on on-board charging systems is indispensable in order to solve the cost consumption and performance of additional power devices.

[0003] Electric drive reconfigurable on-board charging systems achieve rectification and inversion functions by reconfiguring and reusing motor windings and power devices. Patent CN111987954B, entitled "A Control Method for a Six-Phase Photovoltaic-Storage-Drive System for Electric Vehicles," describes how electric drive reconfiguration technology converts the output current control of photovoltaic panels in new energy electric vehicles into the current control of the motor's 0 and 1 axes, thereby eliminating the need for additional power devices. However, currently commonly used electric drive reconfigurable on-board charging control systems employ vector control strategies that require multiple coordinate transformations during the control of a six-phase motor, consuming significant computation time. Furthermore, the integral term of the PI controller also affects the system's response speed and reduces dynamic performance.

[0004] To address the problems of difficult PI parameter tuning, multiple coordinate transformations, and excessive computation time associated with traditional vector control strategies, model predictive control (MDC) is introduced. MDC offers advantages such as fast response, applicability to nonlinear systems, and flexible design. The paper "Space-Vector-Optimized Predictive Control for Dual Three-Phase PMSM With Quick Current Response" (IEEE Transactions on Power Electronics, 2022, 37(4):4453-4462) states that multiple subspaces can be controlled simultaneously using a value function. However, traditional MDC still suffers from heavy computational burden and large harmonic currents when applied to multiphase motors. Therefore, reducing the computational burden and lowering current ripple is a major challenge.

[0005] How to solve the above problems is the challenge faced by this invention. Summary of the Invention

[0006] The purpose of this invention is to provide a model predictive control method for a six-phase electric drive reconfigurable on-board charging system. This method does not require a large number of coordinate transformations and reduces the work of PI parameter optimization and tuning. It can improve the dynamic and steady-state performance of the system while reducing the computational burden and current ripple.

[0007] To achieve the above-mentioned objectives, the present invention employs the following technical solution: the positive terminal of the photovoltaic panel is connected to the neutral point O1 of the winding phases ABC of the six-phase symmetrical permanent magnet synchronous motor, the negative terminal of the photovoltaic panel is connected to the neutral point O2 of the winding phases UVW of the six-phase symmetrical permanent magnet synchronous motor, a mode switch SW is connected between the positive terminal of the photovoltaic panel and the neutral point O1 of the motor, the winding ports of the six-phase symmetrical permanent magnet synchronous motor are connected to a six-phase inverter, and the six-phase inverter is controlled using a model predictive control method; the input port of the six-phase inverter is connected in parallel with the capacitor at the output terminal of the battery.

[0008] A model predictive control method for a six-phase electric drive reconfigurable on-board charging system includes the following steps:

[0009] S1: Based on the motor speed setting value n * The q-axis current setpoint i is obtained after the speed n of the six-phase symmetrical permanent magnet synchronous motor is collected and processed by the speed controller. q * The q-axis current is controlled to stabilize the rotational speed at the set value.

[0010] S2: In the same control cycle, the output voltage V of the photovoltaic panel is collected. P With output current I P The real-time current setpoint i for axes 0 and 1 is calculated using the MPPT controller. 01 * Control the 0 and 1 axis currents to stabilize at a given value;

[0011] S3: Collect the six-phase current I of the six-phase symmetrical permanent magnet synchronous motor. A I B I C I U I V I W By decoupling coordinate transformations in vector space, the d-axis, q-axis, and 0 / 1 axis currents i are obtained. d i q i 01 The current obtained after coordinate transformation is used as the d-axis, q-axis, and 0 / 1-axis current values ​​i at the current moment. d (k), i q (k), i 01 (k) provides the current value at the current moment for the current prediction calculation of the model predictive controller;

[0012] S4: Convert the output voltage V of the photovoltaic panel P Battery voltage u b Motor-related parameters, current value i at the current moment d (k), i q (k), i 01 (k) The input is fed into the model predictive controller, and the reference voltage u corresponding to the d-axis, q-axis, and 01-axis is obtained through the vector space coordinate transformation matrix and the switching states of the six-phase inverter. d u q u 01 Then, calculate the predicted current i for the next cycle. d (k+1),i q (k+1),i 01 (k+1) serves as the optimization condition for the value function;

[0013] S5: Combine the predicted current for the next cycle calculated in step S4 with the given reference values ​​i for the d-axis, q-axis, and 0 / 1-axis. q * i d * i 01 * The input is fed into the value function. After calculation using the traversal method and the value function, the voltage vector to be used in the next cycle is selected, and the state of the switching transistor corresponding to the selected voltage vector can be clearly identified.

[0014] S6: By selecting the voltage vector, the on / off state of the switching transistor in the next cycle is obtained, which serves as the drive signal for the six-phase inverter, thereby controlling the operating state of the six-phase electric drive reconfigurable on-board charging system in the next cycle.

[0015] S7: Based on the drive signal of the six-phase inverter, the six-phase electric drive reconfigurable on-board charging system can operate in charging mode, driving mode and charging while driving mode.

[0016] In step S4, the model predictive controller predicts the current i d i q i 01 Perform closed-loop control, and input the relevant motor parameters and the current value i for the current cycle. d (k), i q (k), i 01 (k) and reference voltage value u d u q u 01 The predicted current i for the next cycle is calculated using discretization formula (1). d (k+1),i q (k+1),i 01 (k+1), where the d-axis and q-axis components control the electromechanical energy of the motor, and the 01-axis components utilize the zero-sequence channel to charge the battery using the photovoltaic panel. The current discretization formula is expressed as:

[0017]

[0018] In the formula, R s The stator internal resistance of a six-phase symmetrical permanent magnet synchronous motor; L d The d-axis inductance of a six-phase symmetrical permanent magnet synchronous motor; L q L0 is the q-axis inductance of the six-phase symmetrical permanent magnet synchronous motor; L0 is the leakage inductance of the six-phase symmetrical permanent magnet synchronous motor; ω e The electric angular velocity of the three-phase permanent magnet synchronous motor; Indicates permanent magnet flux linkage; T s Indicates the sampling period.

[0019] In step S5, the voltage vector V used by the model predictive controller i From the zero vector V0 and the fundamental vector V Mk k = 1, 2, 3, 4, 5, 6; and the fundamental large vector V Lk The voltage vectors consist of 13 vectors, k = 1, 2, 3, 4, 5, 6, among which the selected basic large vector V... Lk After removing the harmonic components of the xy subspace, and preserving the current prediction of the xy subspace in the calculation, the value function J is expressed as:

[0020]

[0021] In the formula, i d * λ is the given value for the d-axis current, which is always kept at 0, and λ is the weighting coefficient.

[0022] In step S7, when the system is operating in charging mode, the speed setpoint n of the six-phase symmetrical permanent magnet synchronous motor is... * When the system is in drive mode, the system is powered by the battery because the neutral point of the motor is disconnected. At this time, the weight coefficient λ is set to 0, and the system value function is equivalent to formula (3).

[0023]

[0024] When the system operates in a run-and-charge mode, the constructed model predicts the current i for the next cycle using a predictive controller. d (k+1),i q (k+1),i 01 (k+1) enables the photovoltaic panel to charge the battery through the zero-sequence channel under normal driving conditions of the six-phase permanent magnet synchronous motor.

[0025] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0026] (1) Compared to the traditional PWM control scheme, which requires multiple PI controllers in a six-phase electric drive reconfigurable on-board charging system and suffers from difficulties in parameter tuning and the need for a large number of coordinate changes, the model predictive control scheme adopted in this invention only requires one PI controller to modulate the q-axis current setpoint i. q * This reduces the work of parameter optimization and tuning, and eliminates the need for additional coordinate inverse transformations.

[0027] (2) Compared with the traditional model predictive controller with 64 voltage vectors, which has problems such as heavy computational burden and large harmonic current, the 13 voltage vectors used in this invention have a smaller computational burden when comparing each predicted value by adopting the ergodic method. The optimal voltage vector can be obtained quickly through the value function, and the harmonic components of the xy subspace can be effectively suppressed to improve the steady-state performance of the system.

[0028] (3) The model predictive control scheme of the six-phase electric drive reconfigurable vehicle charging system proposed in this invention, which takes into account zero-sequence injection, controls the motor operation through the d-axis and q-axis and controls the photovoltaic panel to charge the power battery through the 01-axis without adding power devices. It can realize the electric drive reconfigurable vehicle charging system to operate in charging mode, electric drive mode and running charging mode. In addition, by changing the value function in different modes, it can improve the dynamic and steady-state performance of the system and reduce the zero-sequence current ripple, which has broad application prospects. Attached Figure Description

[0029] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used together with the embodiments of the invention to explain the invention and do not constitute a limitation thereof.

[0030] Figure 1 This is a block diagram illustrating the principle of a model predictive control method for a six-phase electric drive reconfigurable on-board charging system according to the present invention.

[0031] Figure 2 This is a simplified circuit topology diagram of the six-phase electric drive reconfigurable on-board charging system in this invention;

[0032] Figure 3 This is a vector diagram of 64 voltages in the α-β subspace of the six-phase inverter in this invention;

[0033] Figure 4 These are the 13 voltage vector diagrams used in the α-β subspace for the six-phase inverter in this invention;

[0034] Figure 5 This is a schematic diagram of the simulation results of motor speed and torque in this invention;

[0035] Figure 6 This is a schematic diagram of the simulation results of the motor phase current of the present invention;

[0036] Figure 7 This is a schematic diagram of the simulation results of the d-axis and q-axis currents of the motor of the present invention;

[0037] Figure 8 This is a schematic diagram showing the simulation results of the photovoltaic panel output voltage and current of the present invention;

[0038] Figure 9 This is a schematic diagram of the simulation results of battery current, voltage, and 0-axis and 1-axis current of the present invention;

[0039] Figure 10 This is a schematic diagram of the simulation results of the battery capacity of the invention. Detailed Implementation

[0040] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. Of course, the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0041] Example 1

[0042] The present invention provides a technical solution as follows: a model of a six-phase electric drive reconfigurable on-board charging system, the principle block diagram of which is shown below. Figure 1 As shown, the positive terminal of the photovoltaic panel is connected to the neutral point O1 of the winding phases ABC of the six-phase symmetrical permanent magnet synchronous motor, and the negative terminal of the photovoltaic panel is connected to the neutral point O2 of the winding phases UVW of the six-phase symmetrical permanent magnet synchronous motor. A mode switch SW is connected between the positive terminal of the photovoltaic panel and the neutral point O1 of the motor. The winding ports of the six-phase symmetrical permanent magnet synchronous motor are connected to the six-phase inverter. The six-phase inverter is controlled using model predictive control. The input port of the six-phase inverter is connected in parallel with the capacitor at the output terminal of the battery.

[0043] like Figure 1 As shown, a model predictive control method for a six-phase electric drive reconfigurable on-board charging system includes the following steps:

[0044] Step 1: Based on the motor speed setting value n * The q-axis current setpoint i is obtained after the speed n of the six-phase symmetrical permanent magnet synchronous motor is collected and processed by the speed controller. q * Specifically:

[0045] The speed setting value n of the six-phase symmetrical permanent magnet synchronous motor * The difference between the collected six-phase symmetrical permanent magnet synchronous motor speed n and the actual speed n is used by a speed PI controller to obtain the real-time q-axis current setpoint i. q * .

[0046] Step 2: During the same control cycle, collect the output voltage V of the photovoltaic panel. P With output current I P The real-time current setpoint i for axes 0 and 1 is calculated using the MPPT controller. 01 * Specifically:

[0047] The output voltage V of the solar panel P Output current I P The input is fed into the MPPT controller, where the optimal output current value of the photovoltaic panel is obtained through a maximum power point tracking algorithm based on the perturbation and observation method. This current value is then used as the 0-axis and 1-axis current setpoint i. 01 * .

[0048] Step 3: Collect the six-phase current I of the six-phase symmetrical permanent magnet synchronous motor. A I B I C I U I V I W By decoupling coordinate transformations in vector space, the d-axis, q-axis, and 0 / 1 axis currents i are obtained. d i q i 01 The current obtained after coordinate transformation is used as the d-axis, q-axis, and 0 / 1-axis current values ​​i at the current moment. d (k), i q (k), i 01 (k), specifically:

[0049] Using a vector space decoupled coordinate transformation method, the components of each variable in the natural coordinate system transformed to the d-axis, q-axis, and 0 / 1-axis are represented as follows:

[0050] [i d i q i 01 ] T =T DQ [I A I B I C I U I V I W ] T (1)

[0051] In the formula, the transformation matrix T DQ for:

[0052]

[0053] Where, θ e The value is the electrical angle of the rotor position.

[0054] The current obtained after coordinate transformation is used as the d-axis, q-axis, and 0 / 1-axis current values ​​i at the current moment. d (k), i q (k), i 01 (k).

[0055] Step 4: Convert the output voltage V of the photovoltaic panel P Battery voltage u b Motor-related parameters, current value i at the current moment d (k), i q (k), i 01(k) The input is fed into the model predictive controller, and the reference voltage u corresponding to the d-axis, q-axis, and 01-axis is obtained through the vector space coordinate transformation matrix and the switching states of the six-phase inverter. d u q u 01 Then, calculate the predicted current i for the next cycle. d (k+1),i q (k+1),i 01 (k+1), specifically:

[0056] Reference voltage u d u q u 01 This invention obtains voltage vectors through calculation, based on the 64 voltage vectors of a six-phase inverter in the α-β subspace, such as... Figure 3 As shown, 13 voltage vectors V are selected. i It contains a zero vector V0 and six fundamental vectors V0. Mk k = 1, 2, 3, 4, 5, 6; and the six fundamental large vectors V Lk k = 1, 2, 3, 4, 5, 6; for example Figure 4 As shown, the selected 13 voltage vectors V i Both can utilize the output voltage V of the photovoltaic panel P Battery voltage u b The voltage vector V is obtained from the vector space coordinate transformation matrix and the switching states of the six-phase inverter. i Represented as:

[0057]

[0058] In the formula, V i This represents the components of 13 voltage vectors along the α-axis, β-axis, and 0 / 1-axis, where i = 1, 2, ..., 13, j = 1, 2, ..., 6, and S(j,i) represents the selected voltage vector V. i The corresponding six-phase inverter switching states, transformation matrix T αβ0 for:

[0059]

[0060] Since the transformation matrix represents the components corresponding to the α-axis, β-axis, and 0 / 1-axis, in order to obtain the reference voltage u corresponding to the d-axis, q-axis, and 0 / 1-axis... d u q u 01 It is necessary to perform Park transformation on the α-axis and β-axis components corresponding to each voltage vector to obtain the reference voltage u corresponding to each voltage vector. d u q u 01 Represented as:

[0061]

[0062] Next, the current value i at the current moment is... d (k), i q (k), i 01 (k) and the reference voltage value u corresponding to the voltage vector d u q u 01 The predicted current i for the next cycle is calculated using a discretization formula. d (k+1),i q (k+1),i 01 (k+1), where the d-axis and q-axis components control the electromechanical energy of the motor, and the 01-axis components utilize the zero-sequence channel to charge the battery using the photovoltaic panel. The current discretization formula is expressed as:

[0063]

[0064] In the formula, R s The stator internal resistance of a six-phase symmetrical permanent magnet synchronous motor; L d The d-axis inductance of a six-phase symmetrical permanent magnet synchronous motor; L q L0 is the q-axis inductance of the six-phase symmetrical permanent magnet synchronous motor; L0 is the leakage inductance of the six-phase symmetrical permanent magnet synchronous motor; ω e The electric angular velocity of the three-phase permanent magnet synchronous motor; Indicates permanent magnet flux linkage; T s Indicates the sampling period.

[0065] Step 5: Compare the predicted current for the next cycle calculated in Step 4 with the given reference values ​​i for the d-axis, q-axis, and 0 / 1-axis. q * i d * i 01 * The input is fed into the value function, and after calculation using the traversal method and the value function, the voltage vector to be used in the next cycle is selected, specifically as follows:

[0066] The reference voltage u corresponding to the 13 voltage vectors d u q u 01 It can calculate the predicted current i for the next cycle of each voltage vector. d (k+1),i q (k+1),i 01 (k+1), the predicted current i for the next cycle is obtained. d (k+1),i q (k+1),i 01 (k+1) and the given reference value i for each axisq * i d * i 01 * The input is fed into the value function, and the value functions corresponding to the 13 voltage vectors are calculated. The minimum value of the value function is selected to obtain the optimal voltage vector. Since the selected basic large vector V... Lk By removing the harmonic components of the xy subspace, and thus preserving the current prediction of the xy subspace in the calculation, the value function can be expressed as:

[0067]

[0068] In the formula, i d * λ is the given value for the d-axis current, which is always kept at 0, and λ is the weighting coefficient.

[0069] Step 6: By selecting the voltage vector, obtain the on / off state of the switching transistors in the next cycle, which will serve as the drive signal for the six-phase inverter. Specifically:

[0070] The optimal voltage vector is selected by the value function under different modes, and the switching state of the switch in the next cycle corresponding to the optimal voltage vector is obtained. This state is used as the drive signal for the six-phase inverter. The six-phase inverter drive signal output by the model predictive controller is input into the six-phase inverter module, thereby realizing the control of the d-axis, q-axis and O1-axis of the six-phase electric drive reconfigurable on-board charging system.

[0071] Step 7: Based on the drive signal of the six-phase inverter, the six-phase electric drive reconfigurable on-board charging system is implemented to operate in charging mode, driving mode, and driving-while-charging mode, specifically as follows:

[0072] When the system is operating in charging mode, the speed setpoint n of the six-phase symmetrical permanent magnet synchronous motor is... * 0; When the system is working in drive mode, the mode switch SW is in the open state because the neutral point of the motor is disconnected, and a zero-sequence current loop cannot be formed. At this time, the system is powered by the battery, the weight coefficient λ is set to 0, and the system value function is equivalent to formula (6).

[0073]

[0074] When the system operates in a running-while-charging mode, as described in steps 1-6 above, the current i in the next cycle is predicted by the constructed model predictive controller. d (k+1),i q (k+1),i 01 (k+1) Under the condition that the six-phase permanent magnet synchronous motor is driven normally by controlling the d-axis and q-axis currents, the photovoltaic panel can charge the battery through the zero-sequence channel.

[0075] To verify the technical problem of the present invention, based on Figure 2 The simplified circuit topology of the six-phase electric drive reconfigurable on-board charging system shown is used to simulate and verify the model predictive control method for the six-phase electric drive reconfigurable on-board charging system proposed in this invention under a running-while-charging mode. In this embodiment, the maximum output power of the solar panel is 800W, the battery is a 50AH / 144V lithium battery, and the motor speed is set from 500r / min to 700r / min at 0.5s.

[0076] In this invention, the motor speed n and torque T are simulated. e The results are as follows Figure 5 As shown, the motor speed can quickly follow the given value at 0.5s and complete the speed adjustment within 0.02s. During the speed adjustment process, the motor output torque recovers rapidly, completing the motor speed adjustment. Under steady-state conditions, the motor output torque is constant at 3 N·m. The motor phase current I during motor rotation... A and I U The change diagram is as follows Figure 6 As shown, due to the injection of the 01 axis current, the phase current I U The current is less than 0, and the motor current stabilizes rapidly during motor speed regulation, demonstrating the superior dynamic performance of the proposed method. Simulation graphs of the d-axis and q-axis currents are shown below. Figure 7 As shown, under stable rotational speed conditions, the q-axis current i q The current remains at 0, with the d-axis current holding at 5A. After an increase in rotational speed over 0.5 seconds, both the d-axis and q-axis currents quickly return to their original values. The output voltage V of the photovoltaic panel... P Current I P Simulation results are as follows Figure 8 As shown in the figure, the solar panel output power is approximately 790W, proving that MPPT has been achieved. Furthermore, the solar panel output power remains unaffected during motor speed adjustment, and the output current I... P The ripple is small. Battery current I b Voltage V b 01 axis current i 01 Simulated waveforms such as Figure 9 As shown, throughout the process, the battery voltage V b The current remains constant. Due to the increased motor speed, the energy consumed by the motor increases, and the battery current changes from -3.5A to -3A. The battery charging current decreases, and during the motor speed adjustment process, the current of the 0 and 1 axes hardly fluctuates. The simulated battery capacity waveform is as follows: Figure 10As shown, it can be seen that the battery capacity is constantly increasing when the motor is running normally. At this time, the photovoltaic panel charges the battery through the zero-sequence channel, indicating that the system can charge the battery in normal electric drive mode, realizing the system can run and charge at the same time.

[0077] The above description is only a preferred embodiment of the present invention and is 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 predictive control method for a six-phase electric drive reconfigurable on-board charging system, characterized in that, The system model predictive control method includes the following steps: S1: Based on the motor speed setting value n * The q-axis current setpoint i is obtained after the speed n of the six-phase symmetrical permanent magnet synchronous motor is collected and processed by the speed controller. q * ; S2: In the same control cycle, the output voltage V of the photovoltaic panel is collected. P With output current I P The real-time current setpoint i for axes 0 and 1 is calculated using the MPPT controller. 01 * ; S3: Collect the six-phase current I of the six-phase symmetrical permanent magnet synchronous motor. A I B I C I U I V I W By decoupling coordinate transformations in vector space, the d-axis, q-axis, and 0 / 1 axis currents i are obtained. d i q i 01 The current obtained after coordinate transformation is used as the d-axis, q-axis, and 0 / 1-axis current values ​​i at the current moment. d (k), i q (k), i 01 (k); S4: Convert the output voltage V of the photovoltaic panel P Battery voltage u b Motor-related parameters, current value i at the current moment d (k), i q (k), i 01 (k) The input is fed into the model predictive controller, and the reference voltage u corresponding to the d-axis, q-axis, and 01-axis is obtained through the vector space coordinate transformation matrix and the switching states of the six-phase inverter. d u q u 01 Then, calculate the predicted current i for the next cycle. d (k+1),i q (k+1),i 01 (k+1); S5: Combine the predicted current for the next cycle calculated in step S4 with the given reference values ​​i for the d-axis, q-axis, and 0 / 1-axis. q * i d * i 01 * The input is fed into the value function, and after calculation using the traversal method and the value function, the voltage vector to be used in the next cycle is selected. The value function J is expressed as: (2)； In the formula, i d * The d-axis current is given a value that is always kept at 0, and λ is a weighting coefficient. S6: By selecting the voltage vector, the on / off state of the switching transistors in the next cycle is obtained and used as the drive signal for the six-phase inverter; S7: Based on the drive signal of the six-phase inverter, the six-phase electric drive reconfigurable on-board charging system can operate in charging mode, driving mode and driving-while-charging mode; In step S7, when the system is operating in charging mode, the speed setpoint n of the six-phase symmetrical permanent magnet synchronous motor is... * When the system is in drive mode, the system is powered by the battery because the neutral point of the motor is disconnected. At this time, the weight coefficient λ is set to 0, and the system value function is equivalent to formula (3). (3)； When the system operates in a run-and-charge mode, the constructed model predicts the current i for the next cycle using a predictive controller. d (k+1),i q (k+1),i 01 (k+1) enables the photovoltaic panel to charge the battery through the zero-sequence channel under normal driving conditions of the six-phase permanent magnet synchronous motor.

2. The model predictive control method for a six-phase electric drive reconfigurable on-board charging system according to claim 1, characterized in that, In step S4, the model predictive controller predicts the current i d i q i 01 Perform closed-loop control, and input the relevant motor parameters and the current value i for the current cycle. d (k), i q (k), i 01 (k) and reference voltage value u d u q u 01 The predicted current i for the next cycle is calculated using discretization formula (1). d (k+1),i q (k+1),i 01 (k+1), where the d-axis and q-axis components control the electromechanical energy of the motor, and the 01-axis components utilize the zero-sequence channel to charge the battery using the photovoltaic panel. The current discretization formula is expressed as: (1)； In the formula, R s The stator internal resistance of a six-phase symmetrical permanent magnet synchronous motor; L d The d-axis inductance of a six-phase symmetrical permanent magnet synchronous motor; L q L0 is the q-axis inductance of the six-phase symmetrical permanent magnet synchronous motor; L0 is the leakage inductance of the six-phase symmetrical permanent magnet synchronous motor; ω e φ is the electrical angular velocity of the three-phase permanent magnet synchronous motor. f Indicates permanent magnet flux linkage; T s Indicates the sampling period.

3. The model predictive control method for a six-phase electric drive reconfigurable on-board charging system according to claim 1, characterized in that, In step S5, the voltage vector V used by the model predictive controller i From the zero vector V0 and the fundamental vector V Mk k=1,2,3,4,5,6; and the fundamental large vector V Lk The voltage vectors consist of 13 vectors, k=1,2,3,4,5,6, among which the selected basic large vector V... Lk， The harmonic components of the xy subspace are stored in the current prediction of the xy subspace during the calculation.

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