An optimization method for power distribution system of more-electric aircraft

Abstract

The present invention discloses an optimization method for a power distribution system of a multi-electric aircraft, which belongs to the field of power distribution optimization and includes the following steps: S1, establishing an SSPC topology structure based on a DC power distribution system of a multi-electric aircraft; S2, optimizing circuits: embedding BUCK circuits and PWM circuits in the SSPC topology structure; S3, customizing a multi-modal control strategy for multiple operating conditions based on the optimized circuit; S4, simulation verification: performing simulation verification on the optimized circuit and the multi-modal control strategy, and if passed, executing step S5, otherwise returning to step S3; S5, optimizing the power distribution system of a multi-electric aircraft using the optimized circuit and the multi-modal control strategy after simulation verification. The present invention adopts the above-mentioned optimization method for the power distribution system of a multi-electric aircraft, and by adding BUCK circuits and PWM circuits to the SSPC circuit, the ability of SSPC to suppress short-circuit current is improved, and the role of short-circuit fault isolation is also mentioned.

Description

Technical Field

[0001] The present invention relates to the field of power distribution optimization, and in particular to an optimization method for a power distribution system of a multi-electric aircraft. Background Art

[0002] Under the new energy architecture, aircraft are moving towards multi-electrification, which has led to an increase in the number of power load devices in the power distribution system. In addition, in order to reduce line losses in the power distribution system, it is necessary to increase the bus voltage in the power distribution system. This makes the traditional electromechanical power distribution system using circuit breakers and relays unable to meet the requirements of fault isolation and load switching due to factors such as circuit overcurrent and slow response to short-circuit faults.

[0003] To solve the above problems, solid state power controllers (SSPC) based on MOSFET, IGBT, etc. have also emerged. Since SSPC has both the switching function of relays and the protection function of circuit breakers, and has the advantages of high reliability, small size, low loss, and no arc, SSPC has gradually replaced electromechanical relays and mechanical circuit breakers.

[0004] As the power level of DC SSPC increases, the back-end load also increases accordingly, which poses a challenge to the safe operation of SSPC. Therefore, the current limiting protection method and control strategy of SSPC when the load is short-circuited have become a research hotspot in recent years.

[0005] For example: Yang Dongping, Wang Li, and Jiang Dengyu disclosed in "Application of Gate Voltage Reduction Technology in MOSFET Driving" that a diode is connected in series with the MOSFET to detect short-circuit faults, and the resistance of the MOSFET is increased by reducing the gate-source voltage to achieve a controllable effect, but it did not consider the problem of disconnecting capacitive loads.

[0006] Liang Xiaofeng, Wu Yiran, and Yi Deying disclosed in "Research on an Overcurrent Protection Method Based on Solid-State Power Controller" that a solid-state power controller is combined with a fuse to achieve overcurrent protection. However, this method increases costs and has a low level of intelligence due to the addition of components.

[0007] Zheng Zhihong, Zhang Kaixin, and Ye Xuerong pointed out in "Design of DC solid-state power controller based on FPGA" and Ye Xuerong, Zhang Kaixin, Sun Qisen, etc. pointed out in "Inverse time overcurrent protection technology of solid-state power controller based on FPGA" that the I 2 The t curve realizes inverse time current limiting protection, but this method has weak fault isolation capability. Summary of the invention

[0008] In order to solve the above problems, the present invention provides an optimization method for a power distribution system of a multi-electric aircraft. By adding a BUCK circuit and a PWM circuit to the SSPC circuit, the SSPC's ability to suppress short-circuit current is improved, and the role of short-circuit fault isolation is also mentioned.

[0009] To achieve the above object, the present invention provides a method for optimizing a power distribution system of a more-electric aircraft, which comprises the following steps:

[0010] S1. Establish SSPC topology based on DC power distribution system of more electric aircraft;

[0011] S2, circuit optimization: embedding a BUCK circuit and a PWM circuit into the SSPC topology structure established in step S1;

[0012] S3, based on the circuit optimization in step S2, customizing a multi-modal control strategy for multiple operating conditions;

[0013] S4, simulation verification: perform simulation verification on the optimized circuit in step S2 and the multi-modal control strategy customized in step S3. If the simulation verification passes, execute step S5, otherwise, return to step S3;

[0014] S5. Optimize the power distribution system of the more-electric aircraft using the optimized circuit and multi-modal control strategy verified by simulation.

[0015] Preferably, the SSPC topology structure described in step S1 includes a synchronous generator, a passive filter, a TRU transformer rectifier, a 12-pulse diode rectifier and a low-pass filter connected in sequence, wherein an input end of a PID controller is also connected between the passive filter and the TRU transformer rectifier, and a feedback end of the PID controller is connected to the synchronous generator via an exciter, wherein the TRU transformer rectifier is composed of a star primary winding and a triangle secondary transformer winding;

[0016] The synchronous generator is used to generate AC power. After the harmonics are filtered out by the passive filter, the AC power is converted into DC power with the help of TRU transformer rectifier and 12-pulse diode rectifier, and then the high-frequency noise is filtered out by the low-pass filter before output. In this process, the output voltage is PID controlled by the PID controller.

[0017] Preferably, the PID control described in step S1 is a BP neural network PID control strategy based on particle swarm optimization, wherein the BP neural network includes input layer neurons, intermediate layer neurons and output layer neurons, the input layer neurons are the actual output value of the system, the expected output value, the system deviation and the control amount, and the output layer neurons are the proportional coefficients of the PID controller. , Integration time and derivative time ;

[0018] The steps of constructing the BP neural network for particle swarm optimization are as follows:

[0019] The first step, initialization:

[0020] Particle swarm initialization: randomly generate a particle swarm, each particle represents a possible solution of the weight and threshold of a BP neural network;

[0021] Velocity initialization: assigning an initial velocity to each particle;

[0022] Step 2: Calculate the fitness function: The difference between the actual output value and the expected output value of the BP neural network is regarded as the fitness function. The fitness value of each particle is calculated using the collected multi-electric aircraft power distribution data to determine the individual fitness and group fitness.

[0023] Step 3: Update individual optimal solution: compare the fitness of the current particle with its historical optimal solution. If the current fitness is better, update the individual optimal solution.

[0024] Step 4: Update the global optimal solution: Search for the solution with the lowest fitness value among all particles, and take the solution with the lowest fitness value as the global optimal solution, and update the global optimal solution;

[0025] Step 5: Speed ​​and position update: According to the individual optimal solution of the particle, the global optimal solution and the current speed, the speed update formula of particle swarm optimization is used to adjust the speed of each particle;

[0026] The updated velocity value is used to adjust the particle position, thereby updating the weight and threshold of the BP neural network;

[0027] Step 6: Repeat steps 3 to 5 until the preset maximum number of iterations is reached or the convergence condition is met;

[0028] Step 7. Result output: Output the BP neural network parameters corresponding to the global optimal solution and obtain the BP neural network model of particle swarm optimization.

[0029] Preferably, the optimization circuit described in step S2 includes a BUCK circuit and a PWM circuit, wherein the BUCK circuit includes a MOSFET and a freewheeling diode respectively connected to the positive and negative electrodes of the power supply to form a loop, and an output capacitor and a simulated load resistor are respectively connected in parallel at both ends of the power supply, and the output capacitor is connected to one end of the inductor, and the other end of the inductor is connected between the emitter of the MOSFET and the freewheeling diode;

[0030] The PWM circuit includes a driving circuit and a PWM generator which are sequentially connected in series with the gate of the MOSFET, and generates a PWM waveform based on the comparison result of the triangular wave generated by the PWM generator and the randomly generated ramp voltage reference.

[0031] Preferably, in step S2, the equivalent circuit design under normal conditions is as follows: first, the output capacitor is charged by using the PWM waveform duty cycle generated by the PWM circuit from 0 to 100%, and the MOSFET always works in a switching state during the charging process. After the output capacitor is charged, the MOSFET is in a 100% on state; when a short circuit is detected in the subsequent circuit, a closed-loop feedback mode is entered, and the MOSFET is PWM-controlled by using the PWM circuit, and current limiting is performed first and then shut down, and the MOSFET is in a switching state during the current limiting process;

[0032] The equivalent circuit design when the capacitive load is turned on is as follows: When the circuit is turned on, during the charging process of the capacitive load, the rise time based on the ramp voltage reference Set the charging time of the output capacitor during the turn-on process and calculate the charging current of the output capacitor :

[0033] (1);

[0034] In the formula, Indicates the capacitance value of the output capacitor; Indicates input voltage;

[0035] Input the charging current of the set output capacitor into formula (1) to calculate the rise time of the ramp voltage reference ;

[0036] At the same time, the working mode of the BUCK circuit during the output capacitor charging period is set to the continuous mode. At this time, according to the inductance value of the BUCK circuit working in the continuous mode The calculation formula is:

[0037] (2);

[0038] In the formula, Indicates the output voltage; Indicates the MOSFET turn-on time; Indicates the pulsating current on the inductor;

[0039] The output voltage , ,as well as Substituting into formula (2) we get:

[0040] (3);

[0041] In the formula, Indicates duty cycle; represents the switching cycle; Indicates the switching frequency; Indicates the output current;

[0042] Considering the continuous mode of the inductor when the duty cycle changes from 0 to 1, the inductance value of the inductor is as follows:

[0043] (4);

[0044] The equivalent circuit design for short circuit is as follows: First, enter the closed-loop feedback control mode. At this time, the output current is used as the feedback control quantity to control the change of the duty cycle, so that the SSPC enters the current limiting mode. The SSPC is equivalent to a BUCK circuit. At this time, the transfer function of the output average current loop to the duty cycle is is the power conversion stage transfer function The product of the filter transfer function consisting of the inductor and the output capacitor , and its calculation formula is as follows:

[0045] (5);

[0046] In the formula, represents the switch node voltage; Represents the series capacitor in the filter circuit; Represents the series inductance in the filter circuit; represents a complex variable; Indicates the resistance value of the simulated load resistor;

[0047] Calculating the transfer function of a PWM generator :

[0048] (6);

[0049] In the formula, Indicates the peak value of the sawtooth wave at the input end of the PWM generator;

[0050] At this point, the transfer function of the SSPC entering the closed-loop feedback control mode is for:

[0051] (7);

[0052] The transfer function of SSPC includes the following zeros: ,pole as well as pole:

[0053] (8);

[0054] (9);

[0055] Calculating the Error Amplifier Transfer Function :

[0056] (10);

[0057] In the formula, , They represent the two zero points provided by the compensation network in the low frequency band; Represents resistance; Represents compensation capacitance.

[0058] Preferably, the multiple operating conditions described in step S3 include an on state, an off state, a PCL state, an ACL state, a CC state and an OC state;

[0059] Among them, in the on state, the control strategy is as follows: when the SSPC receives the on command, it remains in the on state, controls the MOSFET of the SSPC to be turned on through the data bus, so that the current can flow through the load, and uses the main control unit to sample and monitor the load current and VDS voltage in real time, and makes the load current not exceed the maximum multiple of the rated current. At this time, when an overcurrent occurs in the output circuit, the PWM circuit is triggered to work with a fixed duty cycle, enter the PCL state, and limit the current to the set value;

[0060] In the off state, the control strategy is as follows: In the off state, the MOSFET of the SSPC is in a high-impedance state;

[0061] In the PCL state, the control strategy is as follows: when the PWM circuit starts due to rapid response to overcurrent, the current is limited to a safe level;

[0062] In the ACL state, the control strategy is as follows: the main control unit controls the current based on the processor's response time and the delay of the PWM circuit to ensure that the MOSFET is in the safe operating area;

[0063] In CC state, the control strategy is as follows: the main control unit generates a set PWM signal to make the BUCK circuit work in slow charging mode to control the current to increase gradually;

[0064] In the OC state, the control strategy is as follows: when overcurrent occurs, the main control unit performs inverse time overcurrent protection.

[0065] The present invention has the following beneficial effects:

[0066] By adding BUCK circuit and PWM circuit to the SSPC circuit, the ability of SSPC to suppress short-circuit current is improved, and the role of short-circuit fault isolation is also mentioned.

[0067] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] Figure 1 It is a flow chart of a method for optimizing a power distribution system of a more-electric aircraft according to the present invention;

[0069] Figure 2 A BP neural network structure diagram based on particle swarm optimization for a multi-electric aircraft power distribution system of the present invention;

[0070] Figure 3 An equivalent circuit diagram of a method for optimizing a power distribution system of a more-electric aircraft according to the present invention under normal operating conditions;

[0071] Figure 4 An equivalent circuit diagram of a method for optimizing a power distribution system of a multi-electric aircraft according to the present invention when a capacitive load is turned on;

[0072] Figure 5 An equivalent circuit diagram of a short-circuit protection of an optimization method for a power distribution system of a multi-electric aircraft according to the present invention;

[0073] Figure 6 The output voltage waveform diagram of the transformer and rectifier module verified by simulation of the present invention;

[0074] Figure 7 The load-end output voltage waveform diagram verified by simulation of the present invention. DETAILED DESCRIPTION

[0075] In order to make the purpose, technical scheme and advantages disclosed in the embodiments of the present invention clearer, the embodiments of the present invention are further described in detail in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the embodiments of the present invention and are not intended to limit the embodiments of the present invention. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application. Examples of the embodiments are shown in the accompanying drawings, where the same or similar reference numerals throughout represent the same or similar elements or elements with the same or similar functions.

[0076] It should be noted that the terms "include", "have" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server comprising a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to these processes, methods, products or devices.

[0077] Like reference numerals and letters denote similar items in the following drawings, and thus, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0078] like Figure 1As shown, a method for optimizing a power distribution system of a more electric aircraft comprises the following steps:

[0079] S1. Establish SSPC (solid-state power controller) topology based on DC power distribution system of more-electric aircraft;

[0080] The SSPC topology structure described in step S1 includes a synchronous generator, a passive filter, a TRU transformer rectifier, a 12-pulse diode rectifier and a low-pass filter connected in sequence, wherein an input end of a PID controller is also connected between the passive filter and the TRU transformer rectifier, and a feedback end of the PID controller is connected to the synchronous generator via an exciter, wherein the TRU transformer rectifier is composed of a star primary winding and a triangle secondary transformer winding;

[0081] The synchronous generator is used to generate AC power. After the harmonics are filtered out by the passive filter, the AC power is converted into DC power with the help of TRU transformer rectifier and 12-pulse diode rectifier, and then the high-frequency noise is filtered out by the low-pass filter before output. In this process, the output voltage is PID controlled by the PID controller.

[0082] like Figure 2 As shown, the PID control described in step S1 is a BP neural network PID control strategy based on particle swarm optimization, wherein the BP neural network includes input layer neurons, intermediate layer neurons and output layer neurons, the input layer neurons are the actual output value of the system, the expected output value, the system deviation and the control amount, and the output layer neurons are the proportional coefficients of the PID controller , Integration time and derivative time ;

[0083] The steps of constructing the BP neural network for particle swarm optimization are as follows:

[0084] The first step, initialization:

[0085] Particle swarm initialization: randomly generate a particle swarm, each particle represents a possible solution of the weight and threshold of a BP neural network;

[0086] Velocity initialization: assigning an initial velocity to each particle;

[0087] Step 2: Calculate the fitness function: The difference between the actual output value and the expected output value of the BP neural network is regarded as the fitness function. The fitness value of each particle is calculated using the collected multi-electric aircraft power distribution data to determine the individual fitness and group fitness.

[0088] Step 3: Update individual optimal solution: compare the fitness of the current particle with its historical optimal solution. If the current fitness is better, update the individual optimal solution.

[0089] Step 4: Update the global optimal solution: Search for the solution with the lowest fitness value among all particles, and take the solution with the lowest fitness value as the global optimal solution, and update the global optimal solution;

[0090] Step 5: Speed ​​and position update: According to the individual optimal solution of the particle, the global optimal solution and the current speed, the speed update formula of particle swarm optimization is used to adjust the speed of each particle;

[0091] The updated velocity value is used to adjust the particle position, thereby updating the weight and threshold of the BP neural network;

[0092] Step 6: Repeat steps 3 to 5 until the preset maximum number of iterations is reached or the convergence condition is met;

[0093] Step 7. Result output: Output the BP neural network parameters corresponding to the global optimal solution and obtain the BP neural network model of particle swarm optimization.

[0094] S2, circuit optimization: embedding a BUCK circuit and a PWM circuit into the SSPC topology structure established in step S1;

[0095] like Figure 3-Figure 5 As shown, the optimization circuit described in step S2 includes a BUCK circuit (step-down circuit) and a PWM circuit (pulse width modulation circuit), wherein the BUCK circuit includes a MOSFET and a freewheeling diode respectively connected to the positive and negative electrodes of the power supply to form a loop, and the two ends of the power supply are also respectively connected in parallel with an output capacitor and a simulated load resistor, and the output capacitor is connected to one end of the inductor, and the other end of the inductor is connected between the emitter of the MOSFET and the freewheeling diode;

[0096] The PWM circuit includes a driving circuit and a PWM generator which are sequentially connected in series with the gate of the MOSFET, and generates a PWM waveform based on the comparison result of the triangular wave generated by the PWM generator and the randomly generated ramp voltage reference.

[0097] In step S2, the equivalent circuit design under normal conditions is as follows: first, the output capacitor is charged using the PWM waveform duty cycle generated by the PWM circuit from 0 to 100%. During the charging process, the MOSFET always works in a switching state, so that it can always be in its safe working area without overload, which not only increases the reliability of the system, but also makes the selection of the MOSFET simpler. After the output capacitor is charged, the MOSFET is in a 100% conduction state. At this time, the MOSFET only generates conduction loss without switching loss, ensuring the high efficiency of the entire power supply system; when a short circuit is detected in the subsequent circuit, the closed-loop feedback mode is entered, and the PWM circuit is used to perform PWM control on the MOSFET, and current limiting is performed first and then shut down, and the MOSFET is in a switching state during the current limiting process, which reduces the loss of the MOSFET, effectively protects the solid-state power controller itself and the previous circuit, and greatly improves the reliability.

[0098] The equivalent circuit design when the capacitive load is turned on is as follows: When the circuit is turned on, during the charging process of the capacitive load, the rise time based on the ramp voltage reference Set the charging time of the output capacitor during the turn-on process and calculate the charging current of the output capacitor :

[0099] (1);

[0100] In the formula, Indicates the capacitance value of the output capacitor; Indicates input voltage;

[0101] It can be seen from formula (1) that the charging current of the output capacitor is inversely proportional to the rise time of the ramp voltage reference, so the impact current when the capacitive load is turned on can be effectively suppressed by extending the rise time of the ramp voltage reference.

[0102] Input the charging current of the set output capacitor into formula (1) to calculate the rise time of the ramp voltage reference ;

[0103] At the same time, the working mode of the BUCK circuit during the output capacitor charging period is set to the continuous mode. At this time, according to the inductance value of the BUCK circuit working in the continuous mode The calculation formula is:

[0104] (2);

[0105] In the formula, Indicates the output voltage; Indicates the MOSFET turn-on time; Indicates the pulsating current on the inductor;

[0106] The output voltage , ,as well as Substituting into formula (2) we get:

[0107] (3);

[0108] In the formula, Indicates duty cycle; represents the switching cycle; Indicates the switching frequency; Indicates the output current;

[0109] Considering the continuous mode of the inductor when the duty cycle changes from 0 to 1, the inductance value of the inductor is as follows:

[0110] (4);

[0111] The equivalent circuit design for short circuit is as follows: First, enter the closed-loop feedback control mode. At this time, the output current is used as the feedback control quantity to control the change of the duty cycle, so that the SSPC enters the current limiting mode. The SSPC is equivalent to a BUCK circuit. At this time, the transfer function of the output average current loop to the duty cycle is is the power conversion stage transfer function The product of the filter transfer function consisting of the inductor and the output capacitor , and its calculation formula is as follows:

[0112] (5);

[0113] In the formula, represents the switch node voltage; Represents the series capacitor in the filter circuit; Represents the series inductance in the filter circuit; represents a complex variable; Indicates the resistance value of the simulated load resistor;

[0114] Calculating the transfer function of a PWM generator :

[0115] (6);

[0116] In the formula, Indicates the peak value of the sawtooth wave at the input end of the PWM generator;

[0117] At this point, the transfer function of the SSPC entering the closed-loop feedback control mode is for:

[0118] (7);

[0119] The transfer function of SSPC includes the following zeros: ,pole as well as pole:

[0120] (8);

[0121] (9);

[0122] Calculating the Error Amplifier Transfer Function :

[0123] (10);

[0124] In the formula, , They represent the two zero points provided by the compensation network in the low frequency band; Represents resistance; Represents the compensation network.

[0125] S3, based on the circuit optimization in step S2, customizing a multi-modal control strategy for multiple operating conditions;

[0126] The multiple operating conditions described in step S3 include an on state, an off state, a PCL state, an ACL state, a CC state, and an OC state;

[0127] Among them, in the on state, the control strategy is as follows: when the SSPC receives the on command, it remains in the on state, controls the MOSFET of the SSPC to be turned on through the data bus, so that the current can flow through the load, and uses the main control unit to sample and monitor the load current and VDS voltage in real time, and makes the load current not exceed the maximum multiple of the rated current. At this time, when an overcurrent occurs in the output circuit, the PWM circuit is triggered to work with a fixed duty cycle, enter the PCL state, and limit the current to the set value;

[0128] In the off state, the control strategy is as follows: In the off state, the MOSFET of the SSPC is in a high-impedance state;

[0129] In the PCL (fast-response current-limiting protection state), the control strategy is as follows: when the PWM circuit starts due to fast-response overcurrent, the current is limited to a safe level;

[0130] In the ACL state (normal current limiting protection state), the control strategy is as follows: the main control unit controls the current based on the processor's response time and the delay of the PWM circuit to ensure that the MOSFET is in a safe operating area;

[0131] In CC state (constant current state), the control strategy is as follows: the main control unit generates a set PWM signal to make the BUCK circuit work in slow charging mode to control the current to increase gradually;

[0132] In the OC state (overcurrent protection state), the control strategy is as follows: when overcurrent occurs, the main control unit performs inverse time overcurrent protection.

[0133] Thus, when the main control unit responds, the system enters the ACL state from the PCL state; when the output circuit overcurrents and the current value does not exceed the PCL current threshold within the main control unit response time interval, it enters the ACL state; when the SSPC works in the ACL state, the main control unit determines whether the output is a capacitive load, short circuit or overcurrent state by monitoring the VDS voltage and dVDS / dt.

[0134] S4, simulation verification: perform simulation verification on the optimized circuit in step S2 and the multi-modal control strategy customized in step S3. If the simulation verification passes, execute step S5, otherwise, return to step S3;

[0135] In this embodiment, the simulation tool is MATLAB. Since there are complete three-phase synchronous AC generator modules and excitation generation modules in the Simulink environment of MATLAB, the existing modules are directly used to design the aircraft main generator simulation model. And the parameter configuration of the three-phase synchronous AC generator module is: the output phase voltage effective value is 115V; the frequency is 400Hz; the rated power is 50kW; the input speed and excitation voltage, the speed increases from 0 to 12000r / min within 0.001s and then remains stable, the excitation voltage is generated by the excitation generation module, and the excitation generation module generates the excitation voltage from the voltage and speed signals collected by the monitoring bus of the generator. The transformer and rectifier module outputs 270V DC to the high-voltage DC bridge, and the following is obtained. Figure 6 The real-time voltage waveform is shown.

[0136] The solid-state power controller described in the present invention is added to the load side for power distribution and short-circuit protection. The load voltage is used as feedback, compared with the reference voltage to generate an error signal, and after PID adjustment, it is compared with the triangle wave signal to generate a PWM signal to control the on and off of the switch tube, thereby controlling the voltage output. The constant voltage load chopper circuit outputs a 28 V voltage to the low-voltage sink bridge. Figure 7 As shown, when the load suddenly changes at 0.2 s, the load voltage can still quickly recover to the required 28 V. When a short circuit fault occurs at 0.3 s, the solid-state power controller can effectively remove the fault, thereby proving the effectiveness of the present invention.

[0137] S5. Optimize the power distribution system of the more-electric aircraft using the optimized circuit and multi-modal control strategy verified by simulation.

[0138] Therefore, the present invention adopts the above-mentioned optimization method of the multi-electric aircraft power distribution system, and by adding a BUCK circuit and a PWM circuit to the SSPC circuit, the SSPC's ability to suppress short-circuit current is improved, while also improving the role of short-circuit fault isolation.

[0139] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that they can still modify or replace the technical solution of the present invention with equivalents, and these modifications or equivalent replacements cannot cause the modified technical solution to deviate from the spirit and scope of the technical solution of the present invention.

Claims

1. A method for optimizing a power distribution system of a more electric aircraft, characterized in that: The following steps are involved: S1. Establish SSPC topology based on DC power distribution system of more electric aircraft; The SSPC topology structure described in step S1 includes a synchronous generator, a passive filter, a TRU transformer rectifier, a 12-pulse diode rectifier and a low-pass filter connected in sequence, wherein an input end of a PID controller is also connected between the passive filter and the TRU transformer rectifier, and a feedback end of the PID controller is connected to the synchronous generator via an exciter, wherein the TRU transformer rectifier is composed of a star primary winding and a triangle secondary transformer winding; The synchronous generator is used to generate AC power. After the AC power is filtered by the passive filter to remove harmonics, it is converted into DC power by means of the TRU transformer rectifier and the 12-pulse diode rectifier. The high-frequency noise is filtered by the low-pass filter before output. In this process, the output voltage is PID controlled by the PID controller. The PID control described in step S1 is a BP neural network PID control strategy based on particle swarm optimization, wherein the BP neural network includes input layer neurons, intermediate layer neurons and output layer neurons, the input layer neurons are the actual output value of the system, the expected output value, the system deviation and the control amount, and the output layer neurons are the proportional coefficients of the PID controller. , Integration time and derivative time ; The steps of constructing the BP neural network for particle swarm optimization are as follows: The first step, initialization: Particle swarm initialization: randomly generate a particle swarm, each particle represents a possible solution of the weight and threshold of a BP neural network; Velocity initialization: assigning an initial velocity to each particle; Step 2: Calculate the fitness function: The difference between the actual output value and the expected output value of the BP neural network is regarded as the fitness function. The fitness value of each particle is calculated using the collected multi-electric aircraft power distribution data to determine the individual fitness and group fitness. Step 3: Update individual optimal solution: compare the fitness of the current particle with its historical optimal solution. If the current fitness is better, update the individual optimal solution. Step 4: Update the global optimal solution: Search for the solution with the lowest fitness value among all particles, and take the solution with the lowest fitness value as the global optimal solution, and update the global optimal solution; Step 5: Speed ​​and position update: According to the individual optimal solution of the particle, the global optimal solution and the current speed, the speed update formula of particle swarm optimization is used to adjust the speed of each particle; The updated velocity value is used to adjust the particle position, thereby updating the weight and threshold of the BP neural network; Step 6: Repeat steps 3 to 5 until the preset maximum number of iterations is reached or the convergence condition is met; Step 7: Result output: Output the BP neural network parameters corresponding to the global optimal solution and obtain the BP neural network model of particle swarm optimization; S2, circuit optimization: embedding a BUCK circuit and a PWM circuit into the SSPC topology structure established in step S1; The optimization circuit described in step S2 includes a BUCK circuit and a PWM circuit, wherein the BUCK circuit includes a MOSFET and a freewheeling diode respectively connected to the positive and negative electrodes of the power supply to form a loop, and an output capacitor and a simulated load resistor are respectively connected in parallel at both ends of the power supply, and the output capacitor is connected to one end of the inductor, and the other end of the inductor is connected between the emitter of the MOSFET and the freewheeling diode; The PWM circuit includes a driving circuit and a PWM generator which are sequentially connected in series with the gate of the MOSFET, and realizes the generation of a PWM waveform based on the comparison result of the triangular wave generated by the PWM generator and the randomly generated ramp voltage reference; In step S2, the equivalent circuit design under normal conditions is as follows: first, the output capacitor is charged by using the PWM waveform duty cycle generated by the PWM circuit from 0 to 100%, and the MOSFET always works in the switching state during the charging process. After the output capacitor is charged, the MOSFET is in a 100% on state; when a short circuit is detected in the subsequent circuit, the closed-loop feedback mode is entered, and the PWM circuit is used to perform PWM control on the MOSFET, and current limiting is performed first and then shut down, and the MOSFET is in the switching state during the current limiting process; The equivalent circuit design when the capacitive load is turned on is as follows: When the circuit is turned on, during the charging process of the capacitive load, the rise time based on the ramp voltage reference Set the charging time of the output capacitor during the turn-on process and calculate the charging current of the output capacitor : （1） In the formula, Indicates the capacitance value of the output capacitor; Indicates input voltage; Input the charging current of the set output capacitor into formula (1) to calculate the rise time of the ramp voltage reference ; At the same time, the buck circuit operating mode during the output capacitor charging period is set to continuous mode. At this time, according to the inductance value of the buck circuit in continuous mode The calculation formula is: （2） In the formula, Indicates the output voltage; Indicates the MOSFET turn-on time; Indicates the pulsating current on the inductor; The output voltage , ,as well as Substituting into formula (2) we get: （3） In the formula, Indicates duty cycle; represents the switching cycle; Indicates the switching frequency; Indicates the output current; Considering the continuous mode of the inductor when the duty cycle changes from 0 to 1, the inductance value of the inductor is as follows: （4） The equivalent circuit design for short circuit is as follows: First, enter the closed-loop feedback control mode. At this time, the output current is used as the feedback control quantity to control the change of the duty cycle, so that the SSPC enters the current limiting mode. The SSPC is equivalent to a BUCK circuit. At this time, the transfer function of the output average current loop to the duty cycle is is the power conversion stage transfer function The product of the filter transfer function consisting of the inductor and the output capacitor , and its calculation formula is as follows: （5） In the formula, represents the switch node voltage; Represents the series capacitor in the filter circuit; Represents the series inductance in the filter circuit; represents a complex variable; Indicates the resistance value of the simulated load resistor; Calculating the transfer function of a PWM generator : （6） In the formula, Indicates the peak value of the sawtooth wave at the input end of the PWM generator; At this point, the transfer function of the SSPC entering the closed-loop feedback control mode is for: （7） The transfer function of SSPC includes the following zeros: ,pole as well as pole: （8） （9） Calculating the Error Amplifier Transfer Function : （10） In the formula, , They represent the two zero points provided by the compensation network in the low frequency band; Represents resistance; Represents compensation capacitance; S3, based on the circuit optimization in step S2, customizing a multi-modal control strategy for multiple operating conditions; The multiple operating conditions described in step S3 include an on state, an off state, a PCL state, an ACL state, a CC state, and an OC state; Among them, in the on state, the control strategy is as follows: when the SSPC receives the on command, it remains in the on state, controls the MOSFET of the SSPC to be turned on through the data bus, so that the current can flow through the load, and uses the main control unit to sample and monitor the load current and VDS voltage in real time, and makes the load current not exceed the maximum multiple of the rated current. At this time, when an overcurrent occurs in the output circuit, the PWM circuit is triggered to work with a fixed duty cycle, enter the PCL state, and limit the current to the set value; In the off state, the control strategy is as follows: In the off state, the MOSFET of the SSPC is in a high-impedance state; In the PCL state, the control strategy is as follows: when the PWM circuit starts due to rapid response to overcurrent, the current is limited to a safe level; In the ACL state, the control strategy is as follows: the main control unit controls the current based on the processor's response time and the delay of the PWM circuit to ensure that the MOSFET is in the safe operating area; In CC state, the control strategy is as follows: the main control unit generates a set PWM signal to make the BUCK circuit work in slow charging mode to control the current to increase gradually; In the OC state, the control strategy is as follows: when overcurrent occurs, the main control unit performs inverse time overcurrent protection; S4, simulation verification: perform simulation verification on the optimized circuit in step S2 and the multi-modal control strategy customized in step S3. If the simulation verification passes, execute step S5, otherwise, return to step S3; S5. Optimize the power distribution system of the more-electric aircraft using the optimized circuit and multi-modal control strategy verified by simulation.

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