A hybrid power system and its distributed control method

Abstract

This invention discloses a hybrid power system and its distributed control method. The system includes a device controller and multiple distributed control modules, each controlling a motor drive unit. Each distributed control module communicates bidirectionally with the device controller via a multi-redundant bus and includes a distributed reliable instruction generator, a fixed-time disturbance observer, and a timed controller. The distributed reliable instruction generator generates reliable control instructions through comparison and differentiation of multi-redundant instructions. The fixed-time disturbance observer uses an extended state observation method to estimate the system's lumped disturbance in real time. The timed controller is based on a nonlinear backstepping method and a dynamic inverse method, combined with a time-varying scaling function to design the control law, ensuring that the motor state accurately tracks the target instruction within a preset time. This invention, through its distributed control architecture design, effectively improves the control reliability, consistency, and anti-interference capability of the hybrid power system.

Description

Technical Field

[0001] This invention belongs to the field of hybrid power control, and relates to hybrid power system control technology, particularly to a hybrid power system and its distributed control method. By combining distributed reliable command generation technology, disturbance fixed-time observation technology, and specified-time control technology, it fully considers the requirements of hybrid power system for reliability and consistency of command response, and performs feedforward compensation for disturbances, further improving the dynamic and static performance of command response. It has the advantages of reliable communication, fast disturbance estimation and compensation, closed-loop stability, and good control performance. Background Technology

[0002] As the core power unit of an aircraft, the importance of the propulsion system is self-evident. Currently, the mainstream aircraft propulsion solutions include pure electric, fuel-powered, hybrid, and hydrogen-powered systems, each with its own advantages. Pure electric systems are clean, flexible, and quiet, but have shorter flight time and weaker payload capacity; traditional fuel-powered systems have the advantages of high payload capacity and long flight time, but are slow to respond, environmentally unfriendly, and difficult to control; hybrid systems combine the advantages of pure electric systems while compensating for the shorter range; hydrogen-powered systems are still in the early stages of development and are expected to be first applied to larger aircraft. Currently, major aircraft manufacturers are all pursuing pure electric / hybrid routes; therefore, optimizing the design of hybrid power systems and their control schemes is of great significance.

[0003] In hybrid power systems, especially series hybrid systems, whether electric-turbine engine hybrids or electric-internal combustion engine hybrids, the turbine engine or internal combustion engine typically generates electricity, which is then fed to various electric motors. These motors are physically controlled by different drives and are installed in different locations on the aircraft, making it a typical distributed system. This type of hybrid system is a complex electromechanical system composed of engines, generators, AC / DC converters, battery packs, battery management systems, power distribution management, and multiple electric motors. These components communicate with each other via a communication network, and traditional lumped control methods still have room for improvement in terms of reliability and consistency. Furthermore, various complex factors exist in the subsystems of hybrid power systems, especially in the electric motors, including unmodeled dynamics, uncertainties, and external disturbances. These uncertainties can be uniformly described using lumped disturbances. The presence of lumped disturbances inevitably affects the control performance of the motors, making it difficult for the system to simultaneously meet the control requirements of stability, speed, accuracy, robustness, and reliability, thus impacting the control quality of the aircraft.

[0004] Traditional control methods typically assume that the system model is precisely known and that disturbances are negligible or easily compensated. However, in reality, lumped disturbances have a significant impact on system dynamics. If these disturbances are not adequately considered during control system design, a large deviation between the system output and the desired value may occur. This deviation not only degrades the quality of the control system but may also jeopardize its stability. Although various advanced control methods, such as adaptive or robust control methods, have been developed, they still have limitations. For example, adaptive control methods are usually based on the assumption of slowly varying system parameters, while robust control methods rely on the assumption of bounded disturbances. These assumptions are often difficult to meet in the actual operation of hybrid power systems because the motors are installed in different locations, resulting in significantly different model perturbations caused by their external environments, and external disturbances also vary considerably. Therefore, controllers designed based on traditional methods are often highly conservative, especially in hybrid power systems, where further optimization is still possible.

[0005] In summary, hybrid power systems suffer from strong coupling between their subsystems and command response delays in distributed actuators. Existing methods have numerous shortcomings, particularly in handling complex operating environments, where there is room for optimization in terms of reliability, command response consistency, and interference suppression capabilities. Therefore, addressing the issues of strong coupling, command response delays in distributed actuators, and insufficient interference suppression capabilities in hybrid power systems by achieving decoupling, consistent command response, and strong anti-interference, while simultaneously improving the dynamic and static performance and robustness of the control system, is a pressing technical challenge in the field of hybrid power system control. Summary of the Invention

[0006] (I) Purpose of the Invention

[0007] To address the aforementioned deficiencies and shortcomings of existing hybrid power systems and their control methods, this invention aims to provide a hybrid power system and its distributed control method. This method achieves distributed reliable command generation through a multi-redundant network, designs a fixed-time disturbance observer to monitor the lumped disturbances of each distributed module in real time, and designs a specified-time controller based on backstepping and specified-time convergence techniques, thereby achieving consistent, reliable, and high-performance control of the entire hybrid power system. This control method effectively handles uncertainties caused by system parameter perturbations, unmodeled dynamics, and external load fluctuations, and possesses advantages such as reliable communication, specified-time convergence, rapid disturbance estimation and compensation, closed-loop stability, and good control performance.

[0008] (II) Technical Solution

[0009] To achieve the objective of this invention and solve its technical problems, the present invention adopts the following technical solution:

[0010] The first objective of this invention is to provide a hybrid power system for distributed cooperative control of multiple motors in a hybrid power system, comprising a device controller and multiple distributed control modules, each distributed control module corresponding to control a motor drive unit, and each motor drive unit comprising a motor and a matching motor driver, specifically:

[0011] The device controller communicates bidirectionally with each distributed control module through a multi-redundant bus and sends control commands based on the operating requirements of the hybrid power system.

[0012] Each of the distributed control modules includes at least a distributed reliable instruction generator, a fixed-time disturbance observer, and a predetermined-time controller, wherein:

[0013] The distributed reliable instruction generator is used to receive control instructions from multiple channels in a multi-redundant bus and generate redundant and fault-tolerant distributed reliable control instructions through weighted average fusion processing.

[0014] The fixed-time disturbance observer estimates the system's lumped disturbance in real time based on the state and control variables of the corresponding motor using a fixed-time extended state observation method, and outputs the estimated value of the lumped disturbance.

[0015] The specified time controller is used for error feedback based on motor state and differentiation of reliable control commands. It designs virtual control quantities using a nonlinear backstepping method combined with a time-varying scaling function, and designs a specified time control law based on a dynamic inverse method combined with lumped disturbance estimation to achieve tracking control of motor state within a set time. The time-varying scaling function adjusts the error convergence rate according to a preset stabilization time.

[0016] The device controller continuously acquires the status information of each distributed control module through a multi-redundant bus, and dynamically triggers a closed loop of control command updates, fixed-time disturbance observation, and specified-time control.

[0017] The second objective of this invention is to provide a distributed control method suitable for hybrid power systems. Based on the hybrid power system provided in the first objective, the control method, when implemented, includes at least the following steps:

[0018] SS1. Constructing a nonlinear dynamic model of the motor drive unit

[0019] For each motor drive unit, a nonlinear dynamic model is constructed based on reliable control commands, state feedback, and disturbance compensation to describe the dynamic characteristics of the motor and the impact of control input on the system state:

[0020]

[0021] Where i = 1, 2, ..., N, N is the number of distributed control modules, x i Let x represent the state variables of distributed control module i and x i =[x i1 x i2 ] T x i1 Indicates motor M i rotational speed, x i2 Indicates motor M i The rotational acceleration; u i Let d be the output control quantity of the i-th time controller. i For the lumped disturbance of distributed control module i, y is the estimated value of the lumped disturbance of distributed control module i. i The output y of distributed control module i represents i =x i1 f i (x i ), g i (x i All are about the state vector x i Nonlinear functions;

[0022] SS2. Distributed Reliable Instruction Generation

[0023] For instructions transmitted from multiple redundant buses, the instructions from each bus are compared and distinguished, and the control instructions from all reliable channels are weighted, averaged, and fused to generate distributed reliable instructions:

[0024]

[0025] In the formula, r i For reliable control commands of distributed control module i, r ij This represents the control command transmitted from the j-th bus in a multi-redundant bus system to the distributed control module i, where j = 1, 2, ..., C, and C represents the number of reliable channels in the multi-redundant bus system, determined based on the real-time communication status of the bus. The weighting coefficients w... j Dynamically adjust based on the reliability of historical data for each channel;

[0026] SS3. Fixed-time interference observation

[0027] Based on the fixed-time extended state disturbance observation method, by designing the observer gain and sign function, and combining the nonlinear functions of the state variables and control quantities, the lumped disturbance is estimated within a fixed time. The calculation formula is as follows:

[0028]

[0029] in, Corresponding to xi2 ,d i The observed values, Indicates observation error. for Differentials with respect to time, ρ1∈(0,1), δ1,δ2>1, Let be a suitable positive number, representing the observer gain. It is a symbolic function;

[0030] SS4. Calculation of Specified Time Control

[0031] First, a virtual control quantity x is designed using a nonlinear backstepping method and based on error feedback from the motor state and the derivative of reliable control commands. i2 Expected value x i2d Its expression is:

[0032]

[0033] Where, k i11 k i12 e is a positive gain parameter. i1 =x i1 -x i1d x represents the tracking error between the current state and the target state. i1d The expected value of the system output and x i1d =r i , x represents i1d The derivative with respect to time; μ(t) is the time-varying scaling function, specifically:

[0034]

[0035] Where 0 < κ < < 1 is the gain of the time-varying scaling function, and T s The system settling time is defined by n, where n represents the system order.

[0036] Secondly, based on the dynamic inverse method and combined with the observed output of the fixed-time disturbance, a time-defined control law is designed to achieve tracking control of the distributed control module:

[0037]

[0038] Where, k i21 >0, k i22 ≥1 represents the control law gain; e i2 =x i2 -x i2d , representing x i2 Its expected value x i2d The error; x represents i2d Differential with respect to time; g i-1 (x i ) represents g i (x i The reciprocal of )

[0039] SS5. Closed-loop control judgment

[0040] The system performs closed-loop control checks to determine if a control termination command has been received. If yes, control is terminated; otherwise, the process jumps to step SS2 for repeated execution to continue tracking control and disturbance observation, ensuring that the hybrid power system maintains stable control performance under complex operating conditions.

[0041] (III) Technical Effects

[0042] Compared with the prior art, the hybrid power system and its distributed control method of the present invention have the following significant technical effects:

[0043] (1) Closed-loop stability: Compared with traditional model-free control methods such as PID, this invention can theoretically demonstrate the bounded stability of the system. Through a fixed-time disturbance observer, this invention can quickly and accurately describe and compensate for internal and external disturbances in the hybrid power system. Compared with traditional asymptotically convergent observers, it has a definite convergence time and superior dynamic performance, thus ensuring that the system can maintain stable operation even when facing complex disturbances. The fixed-time disturbance observation and compensation mechanism guarantees the theoretically uniform bounded stability of the system, improving the robustness and reliability of the control system.

[0044] (2) Good control performance: This invention improves the control performance of the entire hybrid power system by adopting a distributed control method for hybrid power systems based on specified-time convergence technology and combining it with fixed-time disturbance observation technology to achieve rapid disturbance estimation. This design exhibits good dynamic and static performance under different operating conditions, especially when facing complex and nonlinear disturbances, ensuring efficient and accurate control performance.

[0045] (3) High reliability: This invention improves the reliability of the hybrid power system by adopting a reliable communication architecture based on multiple redundant buses, avoiding the situation where the entire system is paralyzed due to a single point of failure. Attached Figure Description

[0046] Figure 1 This is a schematic block diagram of the hybrid power system of the present invention;

[0047] Figure 2 This is a schematic block diagram of the distributed control module in the hybrid power system of the present invention.

[0048] Figure 3This is a flowchart of the distributed control method for hybrid power systems according to the present invention. Detailed Implementation

[0049] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of the embodiments of this invention will be described in more detail below with reference to the accompanying drawings. The described embodiments are some, but not all, of the embodiments of this invention. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the invention, and should not be construed as limiting the invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0050] This invention aims to provide a hybrid power system and its distributed control method. Based on the actual physical configuration of the hybrid power system, it introduces distributed reliable command generation technology, fixed-time disturbance observation technology, and specified-time control technology to fully consider the requirements of the hybrid power system for reliability and consistency of command response. It also performs feedforward compensation for disturbances, further improving the dynamic and static performance of command response. It has the advantages of reliable communication, fast disturbance estimation and compensation, closed-loop stability, and good control performance.

[0051] Example 1: Hybrid Power System

[0052] As a specific example, such as Figure 1 As shown, in terms of physical configuration, the hybrid power system provided by this invention includes at least the following components:

[0053] Equipment Controller: As the core control unit of the entire hybrid power system, it is responsible for bidirectional communication with other equipment based on the operational requirements of specific applications such as aircraft / vehicles. It receives real-time status information from other equipment and generates global control commands by combining power demand, energy distribution strategies, and health management strategies. Control signals are then sent to various distributed control modules, engine / generator integrated controllers, battery management systems, etc., via a multi-redundant bus. In practice, this can be implemented as an autopilot, a VCU (Vehicle Control Unit), or a dedicated flight control computer.

[0054] Engine: Generates mechanical energy by burning common fuel / gas to drive a power generation device to generate electricity. Specifically, it can be a turbine engine, an internal combustion engine, or a hybrid power engine, etc.

[0055] Generator: Driven by the engine, it generates electrical energy and outputs it to the AC / DC converter to power the power battery pack and motor drive unit. It can be a permanent magnet synchronous generator, an asynchronous generator or a doubly-fed induction generator to improve energy conversion efficiency.

[0056] Engine / generator integrated controller: It is responsible for simultaneously controlling the engine speed and generator output, and has the necessary fault diagnosis and protection functions. It can automatically adjust or switch to a safe mode under abnormal conditions to improve system reliability.

[0057] AC / DC converter: responsible for converting the alternating current output from the generator into direct current of appropriate voltage level, and outputting it to the bus distribution manager for redistribution to each motor driver to drive each motor to work;

[0058] Power battery pack: As an auxiliary energy unit, it can store / output necessary electrical energy. It can be used to store electrical energy during power generation and to provide electrical energy to the system when the power generation system has a problem.

[0059] Battery Management System: Features bidirectional DC / DC conversion, power battery pack unit management, charge / discharge management, and essential battery protection functions for the operation and management of the power battery pack.

[0060] Busbar power distribution manager: It has the function of power distribution management for the entire hybrid power system, and is used for energy management, overvoltage, overcurrent, undervoltage, undercurrent and other monitoring and protection of the power DC bus;

[0061] Multi-redundant bus: It has bidirectional high-speed, multi-redundant peer-to-peer communication capabilities, used for information exchange in hybrid power systems, and has real-time status monitoring, command synchronization and fault redundancy switching functions.

[0062] Distributed control module 1 to distributed control module N: Each distributed control module is responsible for independently controlling a motor drive unit. It combines distributed reliable instruction generation, fixed-time disturbance observation and specified time control strategy to achieve precise dynamic control of the motor. Each control module can receive instructions through a multi-redundant bus and feed back the motor status to the equipment controller in real time.

[0063] Motor driver 1 to motor driver N: Responsible for receiving control commands from the multi-redundant bus and controlling the corresponding motors M1 to M2. N The operation of the system, where N is the number of motor drives, needs to be determined based on the specific application of the aircraft / vehicle, etc.

[0064] Motor M1 ~ Motor M N It has the function of converting electrical energy into mechanical energy, and is driven by motor driver 1 to motor driver N, where N is the number of motors, which also needs to be determined according to the actual situation of the specific application of aircraft / vehicles, etc.

[0065] More specifically, such as Figure 1As shown, in the hybrid power system proposed in this embodiment of the invention, the device controller is connected to the integrated engine / generator controller, battery management system, motor driver 1 to motor driver N, and bus power distribution manager through a multi-redundant bus, which can realize bidirectional communication, thereby obtaining the status information of each component, and sending control commands according to the needs of motion control and health management.

[0066] The input terminals of the integrated engine / generator controller are connected to the sensors of the engine and the AC / DC converter to measure the necessary signals; the output terminals are connected to the actuators of the engine and the excitation current regulator of the generator to control the engine and generator; the communication port of the integrated engine / generator controller is connected to other devices such as the equipment controller, battery management system, motor driver 1 to motor driver N, and bus power distribution manager through a multi-redundant bus.

[0067] The engine's input is connected to the integrated engine / generator controller to ensure reliable, safe, and efficient engine operation; its output is also connected to the integrated engine / generator controller to output key signals such as pressure, temperature, speed, and vibration; the engine and generator are mechanically connected to drive the generator to produce electrical energy.

[0068] The generator's input terminal is connected to the output terminal of the integrated engine / generator controller to regulate the generator's operating status; its electrical energy output is sent to the AC / DC converter; the generator and engine are mechanically connected. The power battery pack's electrical energy input and output terminals are connected to the battery management system for outputting electrical energy or charging; its signal measurement output terminal is sent to the battery management system for monitoring and protecting the status of each battery cell in the power battery pack.

[0069] One input terminal of the battery management system is connected to the signal measurement output terminal of the power battery pack, which is used to monitor and protect the status of each battery cell in the power battery pack. One power input / output terminal is connected to the power battery pack, which is used to manage the charging and discharging of the power battery pack. The other power input / output terminal is connected to the bus distribution manager, which is used for bidirectional power input / output.

[0070] The output of the AC / DC converter is connected to one input of the integrated engine / generator controller to monitor the status of the generator and the AC / DC converter. Its power input is connected to the power output of the generator for AC power input. Its power output is connected to the power DC bus of the bus distribution manager to provide DC power at the appropriate voltage level.

[0071] The bus power distribution manager includes a power DC bus and a power distribution management unit. The power DC bus is connected to the power output terminal of the AC / DC converter, the power input and output terminals of the battery management system, and the power input terminals of motor driver 1 to motor driver N, and is used to realize power input and output management and necessary protection.

[0072] The power input terminals of motor drivers 1 to N are connected to the DC power bus in the bus distribution manager for driving the motors; their communication terminals are connected to the multi-redundant bus and the corresponding distributed control module for bidirectional communication with the equipment controller and the corresponding distributed control module. Motors M1 to M... N The input terminal is connected to the motor output terminal of motor driver 1 to motor driver N, and is driven by motor driver 1 to motor driver N to convert electrical energy into mechanical energy.

[0073] Example 2: Distributed Control

[0074] Based on the hybrid power system shown in Embodiment 1 above, as a further supplement, such as Figure 2 As shown, the present invention also provides a distributed control system and method applicable to the above-mentioned hybrid power system and based on a predetermined time convergence technique. Logically, the distributed control system mainly includes a device controller and multiple distributed control modules. Each distributed control module controls a motor drive unit, and each motor drive unit includes a motor and a matching motor driver.

[0075] Equipment controller: It communicates bidirectionally with each distributed control module through a multi-redundant bus and sends control commands based on the operating requirements of the hybrid power system;

[0076] Each of the distributed control modules includes at least a distributed reliable instruction generator, a fixed-time disturbance observer, and a predetermined-time controller, wherein:

[0077] A distributed reliable command generator receives control commands from multiple channels on a redundant bus, compares and distinguishes them, and generates appropriate dynamic and redundant fault-tolerant distributed reliable control commands.

[0078] A time-defined controller is used to achieve high-performance control of the motor based on reliable control commands input from a distributed reliable command generator and error feedback of the motor state.

[0079] A fixed-time disturbance observer is used to estimate the lumped disturbance in real time within a fixed time period based on the motor's status and the output of a time controller, and then outputs the estimated lumped disturbance value to the time controller.

[0080] Corresponding to the aforementioned distributed control system, this invention also provides a distributed control method for a hybrid power system based on a predetermined time convergence technique, such as... Figure 3 As shown, the control method, when implemented, includes at least the following steps:

[0081] SS1. Constructing a nonlinear dynamic model of the motor drive unit

[0082] For motors M1 to M in each motor drive unit N A nonlinear dynamic model is constructed based on reliable control commands, state feedback, and disturbance compensation to describe the dynamic characteristics of the motor and the influence of control input on the system state. Its mathematical model can be written in the following form:

[0083]

[0084] Where i = 1, 2, ..., N, N is the number of distributed control modules, x i Let x represent the state variables of distributed control module i and x i =[x i1 x i2 ] T x i1 Indicates motor M i rotational speed, x i2 Indicates motor M i The rotational acceleration; u i Let d be the output control quantity of the i-th time controller. i For the lumped disturbance of distributed control module i, y is the estimated value of the lumped disturbance of distributed control module i. i The output y of distributed control module i represents i =x i1 f i (x i ), g i (x i All are about the state vector x i Nonlinear functions;

[0085] SS2. Distributed Reliable Instruction Generation

[0086] For instructions transmitted from multiple redundant buses, distributed reliable instructions are generated by comparing and identifying instructions from each bus and calculating the instructions according to the following formula:

[0087]

[0088] In the formula, r i For reliable control commands of distributed control module i, r ijThis represents the control command transmitted from the j-th bus in the multi-redundant bus to the distributed control module i, where j = 1, 2, ..., C, and C represents the number of reliable channels in the multi-redundant bus, which is determined based on the real-time communication status of the bus.

[0089] Alternatively, distributed reliable instructions can be generated by weighted averaging and fusing control instructions from all reliable channels in a multi-redundant bus. The calculation formula is as follows: Each weighting coefficient w j The system is dynamically adjusted based on the reliability of historical data for each channel.

[0090] SS3. Fixed-time interference observation

[0091] Based on the fixed-time extended state disturbance observation method, by designing the observer gain and sign function, and combining the nonlinear functions of the state variables and control variables, fixed-time disturbance observation is achieved, and the estimated value of the lumped disturbance of the distributed control module i is obtained. Specifically:

[0092]

[0093] in, Corresponding to x i2 ,d i The observed values, Indicates observation error. for Differentials with respect to time, ρ1∈(0,1), δ1,δ2>1, Let be a suitable positive number, representing the observer gain. From equation (5), the d of the distributed control module i can be observed. i Its output is In the above symbols, i = 1, 2, ..., N.

[0094] SS4. Calculation of Specified Time Control

[0095] First, a nonlinear backstepping method is used, and the virtual control quantity x is designed based on the system's error feedback and the differential of the dynamic command signal. i2 Expected value x i2d Its expression is:

[0096]

[0097] Where k i11 k i12 Here, μ(t) is a positive gain parameter, and μ(t) is a time-varying scaling function, specifically:

[0098]

[0099] e i1 =xi1 -x i1d , representing the tracking error between the current state and the target state, x i1d For the expected value of the system output, x is specifically chosen in this invention. i1d =r i ; x represents i1d Differential with respect to time; 0 < κ << 1 is the gain of the time-varying scaling function, T s The system settling time is defined by n, where n represents the system order.

[0100] Secondly, based on the dynamic inverse method and combined with the observed output of the fixed-time disturbance, a time-defined control law is designed to achieve closed-loop control of distributed control module i:

[0101]

[0102] Where k i21 >0, k i22 ≥1 represents the control law gain; e i2 =x i2 -x i2d , representing x i2 Its expected value x i2d The error; x represents i2d Differential with respect to time; g i -1 (x i ) represents g i (x i The reciprocal of ).

[0103] SS4. Closed-loop control judgment

[0104] The system performs closed-loop control checks to determine if a control termination command has been received. If yes, control is terminated; otherwise, the process jumps to step SS2 for repeated execution to continue tracking control and disturbance observation, ensuring that the hybrid power system maintains stable control performance under complex operating conditions.

[0105] The above embodiments 1 and 2 provide a detailed description of the hybrid power system and its distributed control method proposed in this invention. Compared with the prior art, the hybrid power system and its distributed control method proposed in this invention have significant technical effects such as reliable communication, convergence within a specified time, rapid disturbance estimation and compensation, closed-loop stability, and good control performance. It also has the following innovations: ① It proposes a distributed hybrid power system distributed control method based on specified time convergence technology, and combines it with fixed-time disturbance observation technology to achieve rapid disturbance estimation and compensation, thereby improving the control performance of the entire hybrid power system. ② The reliable communication architecture based on multi-redundant buses improves the reliability of the hybrid power system, avoiding the situation where the entire system is paralyzed due to a single point of failure.

[0106] The objectives of this invention have been fully and effectively achieved through the above embodiments. Those skilled in the art will understand that this invention includes, but is not limited to, the contents described in the accompanying drawings and the specific embodiments described above. Although the invention has been described with reference to what is currently considered the most practical and preferred embodiments, it should be understood that the invention is not limited to the disclosed embodiments, and any modifications that do not depart from the functional and structural principles of the invention will be included within the scope of the claims.

Claims

1. A hybrid power system, comprising a device controller and multiple distributed control modules, each distributed control module corresponding to control a motor drive unit, each motor drive unit comprising a motor and a matching motor driver, characterized in that: The device controller communicates bidirectionally with each distributed control module through a multi-redundant bus and sends control commands based on the operating requirements of the hybrid power system. Each of the distributed control modules includes at least a distributed reliable instruction generator, a fixed-time disturbance observer, and a predetermined-time controller, wherein: The distributed reliable instruction generator is used to receive control instructions from multiple channels in a multi-redundant bus and generate redundant and fault-tolerant distributed reliable control instructions through weighted average fusion processing. The fixed-time disturbance observer estimates the system's lumped disturbance in real time based on the state and control variables of the corresponding motor using a fixed-time extended state observation method, and outputs the estimated value of the lumped disturbance. The specified time controller is used for error feedback based on motor state and differentiation of reliable control commands. It designs virtual control quantities using a nonlinear backstepping method combined with a time-varying scaling function, and designs a specified time control law based on a dynamic inverse method combined with lumped disturbance estimation to achieve tracking control of motor state within a set time. The time-varying scaling function adjusts the error convergence rate according to a preset stabilization time. The device controller continuously acquires the status information of each distributed control module through a multi-redundant bus, and dynamically triggers a closed loop of control command updates, fixed-time disturbance observation, and specified-time control. Furthermore, the specified time controller employs a nonlinear backstepping method and designs the virtual control quantity x based on error feedback from the motor state and the derivative of reliable control commands. i2 Expected value x i2d : Where, k i11 k i12 e is a positive gain parameter. i1 =x i1 -x i1d x represents the tracking error between the current state and the target state. i1 Indicates motor M i rotational speed, x i1d The expected value of the system output and x i1d =r i r i Reliable control commands for distributed control module i. x represents i1d Differential with respect to time; Let be the time-varying scaling function, 0 < κ << 1 be the gain of the time-varying scaling function, and T be the gain of the time-varying scaling function. s The system settling time is defined by n, where n represents the system order.

2. The hybrid power system according to claim 1, characterized in that, The multi-redundant bus is a bus with bidirectional high-speed and multi-redundant peer-to-peer communication capabilities, used for information exchange in hybrid power systems, and includes at least two independent redundant communication channels, each of which supports bidirectional data transmission and has instruction verification and fault tolerance mechanisms.

3. The hybrid power system according to claim 1, characterized in that, Each motor drive unit constructs a nonlinear dynamic model based on reliable control commands, state feedback, and disturbance compensation to describe the dynamic characteristics of the motor and the impact of control input on the system state. Where i = 1, 2, ..., N, N is the number of distributed control modules, x i Let x represent the state variables of distributed control module i and x i =[x i1 x i2 ] T x i1 Indicates motor M i rotational speed, x i2 Indicates motor M i rotational acceleration, x i1 x i2 Differential with respect to time; u i Let d be the output control quantity of the i-th time controller. i For the lumped disturbance of distributed control module i, y i f represents the output of distributed control module i. i (x i ), g i (x i All are about the state vector x i Nonlinear functions.

4. The hybrid power system according to claim 3, characterized in that, The distributed reliable instruction generator compares and distinguishes instructions from multiple channels in a multi-redundant bus, and performs a weighted average fusion of control instructions from all reliable channels to generate reliable control instructions, thereby reducing the impact of single channel anomalies on system control accuracy. Where, r i For reliable control commands of distributed control module i, r ij For the control command transmitted to the i-th distributed control module via the j-th reliable channel in a multi-redundant bus, w j Let be the weight coefficient of the j-th reliable channel and j = 1, 2, ..., C, where C is the number of reliable channels and is determined based on the real-time communication status of the bus. Each weighting coefficient w... j The system is dynamically adjusted based on the reliability of historical data for each channel.

5. The hybrid power system according to claim 4, characterized in that, The fixed-time disturbance observer estimates the lumped disturbance within a fixed time period by designing the observer gain and sign function, and combining the nonlinear functions of the state variables and control quantities. in respectively corresponding to x i2 ,d i The observed values, This represents the observation error of the observer. for Regarding the differential of time, Let ρ1 ∈ (0, 1), δ1, δ2 >

1. This indicates that the observer's adjustable gain parameter is an appropriate positive number.

6. The hybrid power system according to claim 5, characterized in that, The specified time controller further designs a specified time control law based on the dynamic inverse method and combined with the observation output of the fixed-time disturbance to achieve tracking control of the distributed control module: Where: k i21 >0, k i22 ≥1 represents the control law gain; e i2 =x i2 -x i2d x represents i2 Its expected value x i2d The error; x represents i2d Differential with respect to time; g i -1 (x i ) represents g i (x i The reciprocal of ).

7. The hybrid power system according to claim 6, characterized in that, The hybrid power system also includes an engine, a generator, an integrated engine / generator controller, an AC / DC converter, a power battery pack, a battery management system, and a bus power distribution manager. The integrated engine / generator controller is used to simultaneously control the engine speed and generator output. The bus power distribution manager is electrically connected to the AC / DC converter, the battery management system, and each motor driver via the power DC bus to realize power input and output management and necessary protection functions.

8. The hybrid power system according to claim 6, characterized in that, The input of the integrated engine / generator controller is connected to the sensors of the engine and AC / DC converter, and the output is connected to the actuator of the engine and the excitation current regulation device of the generator. The communication port is connected to the equipment controller, battery management system, motor driver and bus distribution manager through a multi-redundant bus.

9. A distributed control method for a hybrid power system, based on the hybrid power system according to any one of claims 1 to 8, characterized in that, include: SS1. For each motor drive unit, a nonlinear dynamic model is constructed based on reliable control commands, state feedback, and disturbance compensation to describe the influence of motor dynamic characteristics and control input on the system state: Where i = 1, 2, ..., N, N is the number of distributed control modules, x i Let x represent the state variables of distributed control module i and x i =[x i1 x i2 ] T x i1 Indicates motor M i rotational speed, x i2 Indicates motor M i The rotational acceleration; u i Let d be the output control quantity of the i-th time controller. i For the lumped disturbance of distributed control module i, y is the estimated value of the lumped disturbance of distributed control module i. i The output y of distributed control module i represents i =x i1 f i (x i ), g i (x i All are about the state vector x i Nonlinear functions; SS2. For instructions transmitted from multiple redundant buses, the instructions from each bus are compared and distinguished, and the control instructions from all reliable channels are weighted, averaged, and fused to generate distributed reliable instructions: In the formula, r i For reliable control commands of distributed control module i, r ij This represents the control command transmitted from the j-th bus in a multi-redundant bus to the distributed control module i, where j = 1, 2, ..., C, and C represents the number of reliable channels in the multi-redundant bus, determined based on the real-time communication status of the bus. The weighting coefficients w... j Dynamically adjust based on the reliability of historical data for each channel; SS3. Based on the fixed-time extended state disturbance observation method, by designing the observer gain and sign function, and combining the nonlinear functions of the state variables and control quantities, the lumped disturbance is estimated within a fixed time. The calculation formula is as follows: in, Corresponding to x i2 ,d i The observed values, Indicates observation error. for Differentials with respect to time, ρ1∈(0,1), δ1,δ2>1, Let be a suitable positive number, representing the observer gain. It is a symbolic function; SS4. First, a virtual control quantity x is designed using a nonlinear backstepping method and based on error feedback from the motor state and the derivative of reliable control commands. i2 Expected value x i2d Its expression is: Where, k i11 k i12 e is a positive gain parameter. i1 =x i1 -x i1d x represents the tracking error between the current state and the target state. i1d The expected value of the system output and x i1d =r i , For x i1d The derivative with respect to time; μ(t) is the time-varying scaling function, and its calculation formula is: Where 0 < κ < < 1 is the gain of the time-varying scaling function, and T s The system settling time is defined by n, where n represents the system order. Secondly, based on the dynamic inverse method and combined with the observed output of the fixed-time disturbance, a time-defined control law is designed to achieve tracking control of the distributed control module: Where, k i21 >0, k i22 ≥1 represents the control law gain; e i2 =x i2 -x i2d , representing x i2 Its expected value x i2d The error; x represents i2d Differential with respect to time; g i -1 (x i ) represents g i (x i The reciprocal of ) SS5. Determine whether the closed-loop control of the system has been received. If yes, end the control. If no, jump to step SS2 and continue tracking control and disturbance observation to ensure that the hybrid power system maintains stable control performance under complex operating conditions.

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