Magnetohydrodynamic generator output optimization method based on active disturbance rejection control

Abstract

The application discloses a kind of based on self-disturbance control's magnetohydrodynamic generator output optimization method, for solving the technical problem that traditional magnetohydrodynamic generator is unstable when output changes, belongs to new energy power generation control technical field.This method includes the following steps: step one, data acquisition and state monitoring;Step two, self-disturbance control operation;Control system will collect output voltage and current as controlled variable, based on self-disturbance control algorithm, utilize extended state observer to magnetohydrodynamic system internal parameter change, external environment change and external load disturbance carry out real-time estimation and compensation, and calculate the specific value of control quantity, simultaneously generate control signal;Step three, according to control signal adjustment actuator.

Description

Technical Field

[0001] This invention belongs to the field of new energy power generation control technology, specifically a method for optimizing the output of a magnetohydrodynamic generator based on active disturbance rejection control. Background Technology

[0002] With the increasing global energy demand, especially for green and renewable energy, hydrogen energy, as an ideal clean energy source, has received widespread attention. Hydrogen fuel cells generate electricity through the electrochemical reaction of hydrogen and oxygen; however, the efficiency and stability of hydrogen fuel cells still face challenges in practical applications. Experiments show that by utilizing the conductivity of magnetohydrodynamics and its interaction with a magnetic field, the energy conversion efficiency of hydrogen fuel cells can be effectively improved, thereby enhancing their energy efficiency and stability.

[0003] Magnetohydrodynamic (MHD) generators convert the chemical energy of hydrogen fuel into electrical energy by utilizing the motion of magnetohydrodynamic fluids in an electromagnetic field through a magnetohydrodynamic system. This system specifically includes a control system and an execution system. However, existing MHD power generation technologies suffer from the following problems:

[0004] 1. Voltage and current fluctuations: In existing magnetohydrodynamic generators, it is difficult to guarantee the stability of voltage and current when the load or working environment changes, resulting in unstable output power and affecting actual performance.

[0005] 2. Low power density: Due to improper adjustment of the magnetic field strength and magnetohydrodynamic flow of the electromagnetic field, existing magnetohydrodynamic generators are unable to maintain sufficient power density under high loads, resulting in limited power generation efficiency and power output.

[0006] 3. Poor adaptability to external environment: Under different working conditions, the output power of traditional magnetohydrodynamic generators is difficult to maintain stability, especially under high temperature, low temperature or instantaneous load fluctuations, the output performance fluctuates greatly. Summary of the Invention

[0007] The purpose of this invention is to provide a method for optimizing the output of a magnetohydrodynamic (MHD) generator based on active disturbance rejection control, which can solve the technical problem of unstable output of traditional MHD generators under load changes.

[0008] This invention is achieved using the following technical solution:

[0009] A method for optimizing the output of a magnetohydrodynamic generator based on active disturbance rejection control includes the following steps:

[0010] Step 1: Data Acquisition and Status Monitoring;

[0011] The system uses sensors to monitor in real time the output voltage, current, flow rate, concentration, and magnetic field strength of the magnetohydrodynamic system. The collected real-time data is then sent to the control system for monitoring the state of the magnetohydrodynamic system.

[0012] Step 2: Active Disturbance Rejection Control Calculation;

[0013] The control system uses the collected output voltage and current as the controlled variables. Based on the active disturbance rejection control algorithm, it uses an extended state observer to estimate and compensate for changes in internal parameters of the magnetohydrodynamic system, changes in the external environment, and external load disturbances in real time, and calculates the specific value of the control quantity, while generating a control signal.

[0014] Step 3: Adjust the actuator according to the control signal;

[0015] Based on the control signal generated in step two, the control system adjusts the actuator of the magnetohydrodynamic system to change the flow rate and concentration of the magnetohydrodynamic fluid and the magnetic field strength of the electromagnetic field until the output voltage and current reach the preset target values.

[0016] By optimizing the flow rate, concentration, and magnetic field strength of the magnetohydrodynamic (MHD) fluid, this invention improves the power density of the generator. Under high load conditions, the MHD generator based on active disturbance rejection control (ADRC) can maintain high output power, and it can still operate stably under temperature changes or other external environmental influences, thus improving the reliability and long-term economic efficiency of the MHD system.

[0017] This invention monitors the operating status of a magnetohydrodynamic (MHD) generator based on active disturbance rejection control (ADRC) in real time using sensors. It uses an extended state observer in the ADRC algorithm to estimate internal and external disturbances of the MHD system, and employs a multivariate decoupling strategy to calculate the optimal control quantity. This collaboratively adjusts the flow rate, concentration, and magnetic field strength of the MHD system, thereby improving the dynamic response speed and energy conversion efficiency of the MHD system.

[0018] Further preferably, in step three, by adjusting the flow rate and concentration of the magnetofluid, the flow state of the magnetofluid inside the generator can be changed, optimizing the interaction between the electromagnetic field and the magnetofluid. If the flow rate of the magnetofluid is too fast or too slow, it will affect the electromagnetic conversion efficiency, while the change in the concentration of the magnetofluid will affect the conductivity and fluidity of the magnetofluid. By controlling the flow rate and concentration of the magnetofluid in real time, the fluidity of the magnetofluid is ensured to be in the optimal state.

[0019] In a further preferred embodiment, in step three, by adjusting the magnetic field strength of the electromagnetic field, the magnetofluid can maximize its electromagnetic effect in the electromagnetic field; changes in the magnetic field strength of the electromagnetic field can affect the motion state of the magnetofluid, thereby affecting the energy conversion efficiency; combined with the adjustment of the magnetofluid's fluidity, the magnetic field strength of the electromagnetic field is dynamically adjusted to ensure stable output voltage and current, and optimize power generation efficiency.

[0020] Further preferred, the working principle of the active disturbance rejection control algorithm in step two is as follows: A tracking differentiator is used to extract the differential signal of the target voltage / current signal to avoid overshoot of the magnetohydrodynamic system caused by sudden changes in the setpoint; an extended state observer is used to observe the changes in internal parameters and external load disturbances of the magnetohydrodynamic system in real time; in the magnetohydrodynamic system, the extended state observer considers the strong coupling effect between the flow velocity, concentration, and magnetic field strength of the magnetohydrodynamic fluid, as well as fluid turbulence, temperature drift, and load jumps, as the extended state of the magnetohydrodynamic system for real-time estimation; finally, the disturbance estimate output by the extended state observer is used for dynamic compensation in the feedforward channel.

[0021] In a further preferred embodiment, the changes in internal parameters of the magnetohydrodynamic system in step two specifically refer to the nonlinear drift of the magnetohydrodynamic conductivity with temperature and the change in flow resistance, while the external load disturbances specifically refer to load steps and environmental magnetic field interference.

[0022] This invention introduces a control system based on active disturbance rejection (ADRR) to adjust the flow rate, concentration, and magnetic field strength of the magnetohydrodynamic (MHD) generator according to changes in its operating state and external environment, thereby optimizing energy conversion efficiency during power generation. Specifically, this invention employs ADRR as the core algorithm, effectively overcoming the technical challenges of strong coupling and the difficulty in accurately establishing nonlinear mathematical models in hydrogen fuel cell MHD power generation systems. This method uses an extended state observer to define the changes in internal parameters of the MHD system, along with external environmental and load disturbances, as a unified "total disturbance" for real-time estimation. Dynamic compensation is then achieved using a feedforward channel, thus realizing approximately decoupled control of the flow rate, concentration, and magnetic field strength of the magnetohydrodynamic (MHD). Furthermore, this method can adapt to different load variations and environmental conditions, ensuring stable power output from the hydrogen fuel cell MHD generator under various conditions. In addition, this invention can be combined with existing hydrogen fuel cell technology to further improve the overall performance of the MHD generator, providing a more efficient and stable solution for new energy power generation technology, and has broad application prospects. Attached Figure Description

[0023] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0024] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0025] Figure 1 This is a flowchart illustrating the method of the present invention.

[0026] Figure 2 This is a flowchart illustrating the closed-loop control process of the present invention.

[0027] Figure 3 This is a schematic diagram illustrating the principle of the Active Disturbance Rejection Algorithm. Detailed Implementation

[0028] To better understand the above-mentioned objectives, features, and advantages of the present invention, the solutions of the present invention will be further described below. It should be noted that, unless otherwise specified, the embodiments of the present invention and the features thereof can be combined with each other.

[0029] Many specific details are set forth in the following description in order to provide a full understanding of the invention, but the invention may also be practiced in other ways different from those described herein; obviously, the embodiments in the specification are only some embodiments of the invention, and not all embodiments.

[0030] The specific embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0031] Example 1

[0032] A method for optimizing the output of a magnetohydrodynamic generator based on active disturbance rejection control includes the following steps:

[0033] Step 1: Data Acquisition and Status Monitoring;

[0034] The system uses sensors to monitor the output voltage, current, flow rate, concentration, and magnetic field strength of the magnetohydrodynamic system in real time. When the load changes or the working environment changes, the sensors will feed the real-time monitoring data back to the control system. The control system uses integrated sensors to collect the output voltage, current, flow rate, concentration, and magnetic field strength data in real time and transmits them to the control system.

[0035] This step establishes a real-time sensing network to acquire dynamic operating data of the hydrogen fuel magnetohydrodynamic (MHD) system. Specifically, high-precision Hall voltage and current sensors are configured at the output end of the power generation channel to monitor the terminal voltage and load current of the MHD generator under active disturbance rejection control in real time. Electromagnetic flowmeters and online concentration detectors (such as conductivity sensors or optical refractometers) are installed at key nodes in the MHD circulation loop to monitor the fluid dynamic velocity and active substance concentration of the MHD fluid within the pipeline in real time. Simultaneously, a gaussmeter probe is positioned at the excitation coil or the center of the power generation channel to monitor the real-time magnetic field strength. When the load connected to the MHD system experiences a sudden impedance change or when the operating environment temperature or pressure drifts, the aforementioned sensors convert the captured physical quantity changes into analog electrical signals and feed them back to the front-end acquisition module of the control system in real time via shielded cables. The control system synchronously acquires, converts analog data to digital data and pre-processes filtering data from the above-mentioned multi-source heterogeneous data through integrated sensors. The processed data of voltage, current, flow rate of magnetofluid, concentration of magnetofluid and magnetic field strength of electromagnetic field are transmitted to the central control unit through a high-speed bus, providing accurate state observation basis for subsequent control calculations. In this embodiment, the control system and the control unit have the same meaning.

[0036] Step 2: Active Disturbance Rejection Control Calculation;

[0037] The control system uses the collected output voltage and current as controlled variables. Based on the active disturbance rejection control algorithm, it uses an extended state observer (ESO) to estimate and compensate for changes in internal parameters, external environment, and external load disturbances of the magnetohydrodynamic system in real time, calculates the specific value of the control quantity, and generates a control signal.

[0038] The working principle of the active disturbance rejection control algorithm is as follows: A tracking differentiator is used to extract the differential signal of the target voltage / current signal to avoid overshoot of the magnetohydrodynamic system caused by sudden changes in the setpoint. An extended state observer is used to observe the changes in internal parameters and external load disturbances of the magnetohydrodynamic system in real time. In the magnetohydrodynamic system, the extended state observer considers the strong coupling between the flow velocity, concentration, and magnetic field strength of the magnetohydrodynamic fluid, as well as fluid turbulence, temperature drift, and load jumps, as a unified extended state of the magnetohydrodynamic system for real-time estimation. Finally, the disturbance estimate output by the extended state observer is used for dynamic compensation in the feedforward channel.

[0039] After receiving real-time monitoring data, the control unit executes operational logic based on active disturbance rejection control. Specifically, the flow velocity, concentration, and magnetic field strength of the magnetohydrodynamic (MHD) system are considered as control inputs, while the actual output voltage and current are set as controlled variables. An extended state observer designed for the nonlinear characteristics of MHD power generation is built within the control unit. This observer does not rely on a precise mathematical model of the controlled object but instead defines changes in internal parameters (such as nonlinear drift of fluid conductivity with temperature and changes in flow resistance), external environmental changes, and disturbances from external loads (such as load steps and environmental magnetic field interference) as the system's "total disturbance." The extended state observer tracks and outputs an estimate of this total disturbance in real time. Subsequently, the estimated total disturbance value is used for compensation in the feedforward channel, thereby decoupling the complex relationship between the flow field, concentration field, and electromagnetic field during MHD power generation into several relatively independent single-input single-output subsystems. Based on this, the optimal control quantity that can eliminate the error of the magnetohydrodynamic system and cancel the total disturbance is calculated using a nonlinear state error feedback law, and command signals are generated for each actuator. The specific process of active disturbance rejection control is as follows: Figure 3 As shown.

[0040] Figure 3 middle, For the expected input (given instructions); For the TD tracking differentiator The reference signal obtained after smooth tracking; for The estimated rate of change / derivative. , , For the output of the ESO extended state observer, where The estimated value of the controlled variable. It is an estimate of its first derivative (state quantity). This is an estimate of the total system disturbance. Error signal. and They are respectively , The NLSEF nonlinear control law is based on... , Generate control quantity . The estimated value of the input channel gain of the controlled object is used to achieve disturbance compensation and input normalization; by The actual control input is obtained by combining it with the disturbance compensation term. and will Apply to the controlled object. The controlled object outputs: , As a feedback signal, it is input to the ESO extended state observer for updating. , , This enables online estimation and compensation of disturbances, thereby improving the system's tracking performance and anti-disturbance capability.

[0041] Step 3: Adjust the actuator according to the control signal;

[0042] Based on the control signal generated in step two, the control system adjusts the actuator of the magnetohydrodynamic system to change the flow rate and concentration of the magnetohydrodynamic fluid and the magnetic field strength of the electromagnetic field until the output voltage and current reach the preset target values.

[0043] By adjusting the flow rate and concentration of the magnetofluid, the flow state of the magnetofluid inside the generator can be changed, optimizing the interaction between the electromagnetic field and the magnetofluid. If the flow rate of the magnetofluid is too fast or too slow, it will affect the electromagnetic conversion efficiency, while the change in the magnetofluid concentration will affect the conductivity and fluidity of the magnetofluid. By controlling the flow rate and concentration of the magnetofluid in real time, the fluidity of the magnetofluid can be ensured to be in the optimal state.

[0044] By adjusting the magnetic field strength of the electromagnetic field, the magnetohydrodynamic fluid can maximize its electromagnetic effects within the field. Changes in the magnetic field strength affect the fluid's motion state, thus influencing energy conversion efficiency. By combining the adjustment of the magnetohydrodynamic fluid's flowability with dynamic adjustment of the electromagnetic field strength, output voltage and current stability are ensured, and power generation efficiency is optimized. The specific process is as follows: Figure 2 As shown.

[0045] This step aims to transform the abstract control quantity calculated in step two into precise actions of the actuators, achieving closed-loop control of the electromagnetic-hydrodynamic state. Based on the decoupled calculation of the control commands, the control unit drives the actuators of the magnetohydrodynamic circulation system and the excitation system in parallel: on one hand, it adjusts the speed of the variable frequency pump by outputting a variable frequency speed control signal to change the pressure difference across the pipe, thereby adjusting the flow rate of the magnetohydrodynamic fluid; and on the other hand, it controls the injection pump to inject high-concentration magnetohydrodynamic stock solution or diluent into the circulation loop according to the concentration command, adjusting the concentration of the magnetohydrodynamic fluid participating in power generation; simultaneously, it outputs a pulse width modulation (PWM) signal to the excitation power supply drive circuit to adjust the magnitude of the DC current in the excitation coil, thereby changing the magnetic field strength of the electromagnetic field within the power generation channel. The above three variables (magnetohydrodynamic flow rate, magnetohydrodynamic concentration, and electromagnetic field strength) are coordinated and regulated under the command of the control system.

[0046] The control system refers to a system with a built-in active disturbance rejection algorithm and control command generation. These commands are sent to the system's actuators via signal transmission lines. The actuators specifically include a variable frequency pump and a syringe pump for regulating the magnetohydrodynamic fluid, and an excitation power supply for regulating the electromagnetic field characteristics. During closed-loop control, the control system drives the aforementioned actuators according to the commands output by the active disturbance rejection algorithm. Specifically, it adjusts the flow rate of the magnetohydrodynamic fluid in the power generation channel by regulating the variable frequency pump, adjusts the concentration of the magnetohydrodynamic fluid by controlling the syringe pump, and controls the magnetic field strength by modulating the excitation power supply, thereby achieving the adjustment and real-time optimization of multiple parameters of the active disturbance rejection control magnetohydrodynamic generator.

[0047] This invention can adjust the fluidity of the magnetohydrodynamic fluid and the magnetic field strength of the electromagnetic field through an active disturbance rejection control algorithm, thereby achieving stability and optimization of the output voltage, current and power of the hydrogen fuel magnetohydrodynamic generator and improving the overall power generation performance.

[0048] This method is used to improve the power generation efficiency and output stability of hydrogen fuel magnetohydrodynamic generators. By dynamically adjusting the flow rate, concentration, and magnetic field strength of the magnetohydrodynamic fluid, the electromagnetic conversion efficiency of the generator can be optimized in real time, maintaining the stability of output voltage and current, increasing battery power density, and enhancing overall power generation performance. In particular, it can maintain efficient and stable power output under load fluctuations or different working environments.

[0049] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement the present invention. Although detailed descriptions have been provided with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments, and they should all be covered within the protection scope of the claims.

Claims

1. A method for optimizing the output of a magnetohydrodynamic generator based on active disturbance rejection control, characterized in that: Includes the following steps: Step 1: Data Acquisition and Status Monitoring; The system uses sensors to monitor in real time the output voltage, current, flow rate, concentration, and magnetic field strength of the magnetohydrodynamic system. The collected real-time data is then sent to the control system for monitoring the state of the magnetohydrodynamic system. Step 2: Active Disturbance Rejection Control Calculation; The control system uses the collected output voltage and current as the controlled variables. Based on the active disturbance rejection control algorithm, it uses an extended state observer to estimate and compensate for changes in internal parameters of the magnetohydrodynamic system, changes in the external environment, and external load disturbances in real time, and calculates the specific value of the control quantity, while generating a control signal. The active disturbance rejection control algorithm works as follows: a tracking differentiator is used to extract the differential signal of the target voltage / current signal to avoid overshoot of the magnetohydrodynamic system caused by sudden changes in the setpoint; an extended state observer is used to observe the changes in the internal parameters of the magnetohydrodynamic system and external load disturbances in real time; in the magnetohydrodynamic system, the extended state observer considers the strong coupling between the flow velocity, concentration and magnetic field strength of the magnetohydrodynamic fluid, as well as fluid turbulence, temperature drift and load jump, as the extended state of the magnetohydrodynamic system for real-time estimation; finally, the disturbance estimate output by the extended state observer is used for dynamic compensation in the feedforward channel. The internal parameter changes of the magnetohydrodynamic system specifically refer to the nonlinear drift of the magnetohydrodynamic conductivity with temperature and the change of flow resistance, while the external load disturbances specifically refer to load steps and environmental magnetic field interference. Step 3: Adjust the actuator according to the control signal; Based on the control signal generated in step two, the control system adjusts the actuator of the magnetohydrodynamic system to change the flow rate and concentration of the magnetohydrodynamic fluid and the magnetic field strength of the electromagnetic field until the output voltage and current reach the preset target values.

2. The method for optimizing the output of a magnetohydrodynamic generator based on active disturbance rejection control according to claim 1, characterized in that: In step three, by adjusting the flow rate and concentration of the magnetofluid, the flow state of the magnetofluid inside the generator can be changed, optimizing the interaction between the electromagnetic field and the magnetofluid. If the flow rate of the magnetofluid is too fast or too slow, it will affect the electromagnetic conversion efficiency, while the change in the concentration of the magnetofluid will affect the conductivity and fluidity of the magnetofluid. By controlling the flow rate and concentration of the magnetofluid in real time, the fluidity of the magnetofluid can be ensured to be in the optimal state.

3. The method for optimizing the output of a magnetohydrodynamic generator based on active disturbance rejection control according to claim 2, characterized in that: In step three, by adjusting the magnetic field strength of the electromagnetic field, the magnetofluid can maximize its electromagnetic effect in the electromagnetic field. Changes in the magnetic field strength of the electromagnetic field can affect the motion state of the magnetofluid, thereby affecting the energy conversion efficiency. By combining the adjustment of the magnetofluid's fluidity, the magnetic field strength of the electromagnetic field is dynamically adjusted to ensure stable output voltage and current and optimize power generation efficiency.

Images