CN118399567B - Fuzzy logic control-based multi-source energy system oriented to simulated ray of bata submersible - Google Patents
Fuzzy logic control-based multi-source energy system oriented to simulated ray of bata submersible Download PDFInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
- H02J7/34—Parallel operation in networks using both storage and other DC sources, e.g. providing buffering
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B63—SHIPS OR OTHER WATERBORNE VESSELS; RELATED EQUIPMENT
- B63G—OFFENSIVE OR DEFENSIVE ARRANGEMENTS ON VESSELS; MINE-LAYING; MINE-SWEEPING; SUBMARINES; AIRCRAFT CARRIERS
- B63G8/00—Underwater vessels, e.g. submarines; Equipment specially adapted therefor
- B63G8/001—Underwater vessels adapted for special purposes, e.g. unmanned underwater vessels; Equipment specially adapted therefor, e.g. docking stations
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/0205—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric not using a model or a simulator of the controlled system
- G05B13/021—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric not using a model or a simulator of the controlled system in which a variable is automatically adjusted to optimise the performance
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- G—PHYSICS
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/0265—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion
- G05B13/0275—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion using fuzzy logic only
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
- H02J7/0047—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries with monitoring or indicating devices or circuits
- H02J7/0048—Detection of remaining charge capacity or state of charge [SOC]
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
- H02J7/007—Regulation of charging or discharging current or voltage
- H02J7/00712—Regulation of charging or discharging current or voltage the cycle being controlled or terminated in response to electric parameters
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
- H02J7/32—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries for charging batteries from a charging set comprising a non-electric prime mover rotating at constant speed
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
- H02J7/34—Parallel operation in networks using both storage and other DC sources, e.g. providing buffering
- H02J7/35—Parallel operation in networks using both storage and other DC sources, e.g. providing buffering with light sensitive cells
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02N—ELECTRIC MACHINES NOT OTHERWISE PROVIDED FOR
- H02N1/00—Electrostatic generators or motors using a solid moving electrostatic charge carrier
- H02N1/04—Friction generators
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Abstract
The embodiment of the application relates to the technical field of energy systems, in particular to a multi-source energy system for a simulated ray of light diving device based on fuzzy logic control, which comprises the following components: the solar photovoltaic cell panel, the ocean current energy friction power generation device and the flexible lithium battery pack are respectively arranged at the back, the abdomen and the inside of the pectoral fin of the simulated ray diving apparatus, the DC/DC conversion module is connected with the solar photovoltaic cell panel and the ocean current energy friction power generation device, the MPPT controller is connected with the DC/DC conversion module, and the fuzzy logic control module is connected with the MPPT controller, the flexible lithium battery pack and the output power grid; the fuzzy logic control module is used for performing fuzzy logic control based on the current power consumption of the simulated ray of the light diving device and the current SOC value of the flexible lithium battery pack so as to adjust the working state of the multi-source energy system, thereby setting different energy management strategies in combination with actual working conditions, improving the working utilization rate of multi-source cooperative work and meeting the electricity demand of the simulated ray of the light diving device.
Description
Technical Field
The embodiment of the application relates to the technical field of energy systems, in particular to a multi-source energy system based on fuzzy logic control and oriented to a simulated ray diving device.
Background
In the present stage, the power battery is the main energy supply mode of the UUV (Unmanned Underwater Vehicle ), and the UUV driven by the power battery as the energy source has the advantages of flexibility and freedom and being capable of completing various tasks, wherein the lithium ion battery is most widely applied by virtue of the superior characteristics.
However, the conventional UUV has a relatively single energy system, and is usually mainly a conventional lithium battery pack in a battery compartment, and the conventional lithium battery usually adopts a fixed hard material, for example, a metal oxide is used as a positive electrode, graphite or silicon is used as a negative electrode, and lithium ions are transferred through a liquid electrolyte, so that the space is greatly limited, and the effective electric quantity is difficult to further improve.
In order to cope with the problem, a novel simulated ray of the bata diving device is generated, the simulated ray of the bata diving device is different from the regular enveloping space of the traditional diving device, the simulated ray of the bata diving device adopts a wing body fusion shape and a flapping pectoral fin structure, and the available regular loading space in a cavity is obviously reduced, so that the electricity requirement of the simulated ray of the bata diving device cannot be met by the traditional centralized battery pack.
Disclosure of Invention
The embodiment of the application mainly aims to provide a multi-source energy system for a baton-like diving device based on fuzzy logic control, which aims to overcome the limitation of the traditional battery pack on capacity and electric quantity, and combines different energy management strategies with actual working conditions, thereby improving the work utilization rate of various energy sources when in cooperative work and meeting the electricity demand of the baton-like diving device.
To achieve the above object, an embodiment of the present application provides a multi-source energy system for a simulated-light-ray diving apparatus based on fuzzy logic control, the multi-source energy system comprising: the solar photovoltaic cell panel, the ocean current energy friction power generation device, the DC/DC conversion module, the MPPT (Maximum Power Point Tracking ) controller, the fuzzy logic control module and the flexible lithium battery pack are energy harvesting devices of a multi-source energy system; the solar photovoltaic cell panel is arranged at the back of the simulated ray diving device, the ocean current energy friction power generation device is arranged at the abdomen of the simulated ray diving device, and the flexible lithium battery pack is arranged in the pectoral fin of the simulated ray diving device; the electric energy output of the solar photovoltaic panel and the ocean current energy friction power generation device is connected with a DC/DC conversion module, the positive and negative electric energy output of the DC/DC conversion module is connected with a fuzzy logic control module through an MPPT controller, and the fuzzy logic control module is also connected with a flexible lithium battery pack and an output power grid respectively; the AC/DC conversion module is used for converting the electric energy output by the energy harvesting device into direct-current voltage, and the MPPT controller is used for stabilizing voltage, performing overvoltage protection and realizing maximum power point tracking; the fuzzy logic control module is used for performing fuzzy logic control based on the current power consumption Of the simulated ray diving apparatus and the current State Of Charge (SOC) value Of the flexible lithium battery pack, outputting a control signal based on the maximization Of the energy utilization ratio and adjusting the working State Of the energy harvesting device.
The multi-source energy system for the bata-simulated diving device based on fuzzy logic control provided by the embodiment of the application is provided with two energy capturing devices, namely a solar photovoltaic panel and a ocean current energy friction power generation device, which are effectively and conformally carried on the back and the abdomen of the bata-simulated diving device, so that solar energy and ocean current energy can be fully utilized, multi-source energy capture is realized, and the energy acquisition efficiency of the bata-simulated diving device is effectively improved. The bending-resistant flexible lithium battery pack is designed on the basis of meeting load requirements and is arranged in the complex heterogeneous space of the pectoral fins of the simulated ray-light diving device, so that the space utilization rate of the simulated ray-light diving device is improved, the energy load is effectively increased, and a more efficient energy storage device is provided for the simulated ray-light diving device. The fuzzy logic control module capable of carrying out energy management based on fuzzy logic control is arranged in combination with the actual working condition of the simulated ray diving device, so that the energy utilization rate is effectively improved, the long-time self-holding of the simulated ray diving device is realized, and the simulated ray diving device can be ensured to operate efficiently and stably in various working modes.
Drawings
FIG. 1 is a schematic diagram of a multi-source energy system for a simulated ray-guided bats submersible based on fuzzy logic control in accordance with one embodiment of the present application;
FIG. 2 is a schematic illustration of a simulated ray of light submersible provided in one embodiment of the application;
FIG. 3 is a flowchart of a fuzzy logic control module according to an embodiment of the present application, wherein the fuzzy logic control module performs fuzzy logic control based on the current power consumption of the baton-like submersible and the current SOC value of the flexible lithium battery pack, and outputs a control signal based on the maximization of the energy utilization, so as to adjust the working state of the energy harvesting device;
FIG. 4 is a schematic diagram of membership functions of power consumption of a simulated bata ray submersible provided in one embodiment of the application;
FIG. 5 is a schematic diagram of membership functions of SOC values of a flexible lithium battery pack provided in one embodiment of the application;
FIG. 6 is a graphical representation of membership functions of output utilization of energy harvesting devices provided in one embodiment of the application;
FIG. 7 is a schematic diagram of a fuzzy logic control decision tree provided in one embodiment of the application;
FIG. 8 is a schematic diagram of the components of a fuzzy logic control module provided in one embodiment of the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the embodiments of the present application will be described in detail below with reference to the accompanying drawings. However, it will be understood by those of ordinary skill in the art that in various embodiments of the present application, numerous specific details are set forth in order to provide a thorough understanding of the present application. The claimed application may be practiced without these specific details and with various changes and modifications based on the following embodiments. The following embodiments are divided for convenience of description, and should not be construed as limiting the specific implementation of the present application, and the embodiments can be mutually combined and referred to without contradiction.
In order to solve the technical problem that the conventional centralized battery pack cannot meet the electricity demand of the simulated batray diving apparatus, an embodiment of the application provides a multi-source energy system based on fuzzy logic control and facing the simulated batray diving apparatus, and implementation details of the multi-source energy system based on fuzzy logic control and facing the simulated batray diving apparatus, which are provided in the embodiment, are specifically described below, but the following is only implementation details provided for facilitating understanding, and are not necessary for implementing the embodiment.
The specific structure of the multi-source energy system for the batray-simulating submersible based on fuzzy logic control according to this embodiment may be as shown in fig. 1, where the multi-source energy system includes: the solar photovoltaic cell panel 11, the ocean current energy friction power generation device 12, the DC/DC conversion module 13, the MPPT controller 14, the fuzzy logic control module 15 and the flexible lithium battery pack 16. The solar photovoltaic cell panel 11 and the ocean current energy friction power generation device 12 are energy harvesting devices of the multi-source energy system, and the flexible lithium battery pack 16 is an energy storage device of the multi-source energy system.
As shown in fig. 2, the solar photovoltaic panel is disposed on the back of the simulated ray diving apparatus, the ocean current energy friction power generation device is disposed on the abdomen of the simulated ray diving apparatus, and the flexible lithium battery pack is disposed inside the pectoral fins of the simulated ray diving apparatus.
As shown in fig. 1, the electric energy outputs of the solar photovoltaic panel 11 and the ocean current energy friction power generation device 12 are connected with the DC/DC conversion module 13, the positive and negative electric energy outputs of the DC/DC conversion module 13 are connected with the fuzzy logic control module 15 through the MPPT controller 14, the fuzzy logic control module 15 is also connected with the flexible lithium battery pack 16 and the output power grid 21 respectively, and besides, the fuzzy logic control module 15 is also connected with the solar photovoltaic panel 11 and the ocean current energy friction power generation device 12 in a communication manner respectively. The DC/DC conversion module 13 is configured to convert energy captured by the energy capturing device (i.e., the solar photovoltaic panel 11 and the ocean current energy friction power generation device 12) into a direct current voltage, the MPPT controller 14 is configured to perform voltage stabilization, overvoltage protection, and maximum power point tracking, and the fuzzy logic control module 15 is configured to perform fuzzy logic control based on the current power consumption of the artificial bata diving device and the current SOC value of the flexible lithium battery pack 16, output a control signal based on the maximization of the energy utilization ratio, and send the control signal to the energy capturing device (i.e., the solar photovoltaic panel 11 and the ocean current energy friction power generation device 12), so as to adjust the working state of the energy capturing device.
As can be seen in fig. 1, the solar photovoltaic panel 11, the ocean current energy triboelectric power generation device 12 and the flexible lithium battery pack 16 can all supply power to the output grid. The solar photovoltaic cell panel 11 captures solar energy and converts the solar energy into electric energy, and the electric energy is stored in the flexible lithium battery pack 16 or is input into the output power grid 21 after passing through the DC/DC conversion module 13, the MPPT controller 14 and the fuzzy logic control module 15. Ocean current energy friction power generation device 12 captures ocean current energy and converts the ocean current energy into electric energy, and the electric energy is stored in flexible lithium battery pack 16 or input into output power grid 21 after passing through DC/DC conversion module 13, MPPT controller 14 and fuzzy logic control module 15. When the flexible lithium battery pack 16 needs to be discharged, the electric energy stored by the flexible lithium battery pack is input into the output power grid 21 through the fuzzy logic control module 15.
In one example, the solar photovoltaic panel may be gallium arsenide solar photovoltaic panel, which has high energy harvesting efficiency, and the size and shape of the designed solar photovoltaic panel can maximize the utilization rate of the back surface of the simulated ray diving apparatus and ensure that solar energy can be captured under different angles and different illumination conditions.
In one example, the ocean current energy friction power generation device is designed by utilizing a streamline structure special for a bata-ray-simulated submersible, has the characteristics of low resistance and high efficiency, and can effectively capture ocean current energy at different flow rates. Considering that the ocean current energy friction power generation device has corrosion resistance and long-term running stability, the ocean current energy friction power generation device is waterproof packaged by adopting a high polymer organic material.
In one example, when designing the streamline structure and the ocean current energy friction power generation device of the simulated ray-light diving apparatus, CFD (Computational Fluid Dynamics ) technology can be used for simulating and analyzing the fluid dynamics performance of the simulated ray-light diving apparatus under different water flow conditions, and the streamline design of the simulated ray-light diving apparatus is optimized to reduce the water flow resistance and improve the movement efficiency. The pressure-bearing structure, the optimal carrying position and the optimal shape of the ocean current energy friction power generation device are designed through three-dimensional simulation modeling, simulated flow velocity, flow direction and fluid properties are set, a continuous fluid domain is discretized into a series of discrete points or units by using the FVM (Finite Volume Method ), and a fluid dynamics equation is solved on the discrete points. In the CFD simulation process, design iteration and optimization are performed based on simulation results, so that the integral streamline of the simulated bata ray diving apparatus is effectively maintained after the energy harvesting device is mounted, and meanwhile, the energy collection is maximized.
In one example, the external surface of the simulated ray of the diving apparatus (comprising the solar photovoltaic panel and the position of the ocean current energy friction power generation device) is provided with a drag reduction material, such as a low friction coating or a microstructure surface, and the arrangement of the drag reduction material can further reduce the water flow resistance and improve the travelling speed and the working efficiency of the simulated ray of the diving apparatus.
In one example, the flexible lithium battery pack needs to meet the load requirement and resist bending, and the material of the flexible lithium battery pack can be selected from materials with high flexibility and excellent electrochemical performance, so that the bending and twisting of the flexible lithium battery pack in the movement process of the simulated ray diving device can not damage the performance of the flexible lithium battery pack, and the safety and stability under the dynamic environment can be ensured. When the flexible lithium battery pack is arranged in the pectoral fins of the simulated ray-ray diving apparatus, the internal structure of the pectoral fins of the simulated ray-ray diving apparatus is firstly modeled by utilizing preset three-dimensional modeling software, the space size and the shape which can be used for installing the flexible lithium battery pack are determined, different installation positions and distribution modes of the flexible lithium battery pack in the internal pectoral fins of the simulated ray-ray diving apparatus are simulated according to the overall design and the performance requirements of the simulated ray-ray diving apparatus, and the optimal installation positions and the distribution modes are determined by combining the gravity center positions, the buoyancy distribution and the influence of water flow on the stability of the simulated ray-diving apparatus, and corresponding brackets and clamps are designed at the optimal installation positions so as to firmly install the flexible lithium battery pack.
In one example, the fuzzy logic control module performs fuzzy logic control based on the current power consumption of the batray-simulating submersible and the current SOC value of the flexible lithium battery pack, outputs a control signal based on the maximization of the energy utilization rate, and adjusts the working state of the energy harvesting device, which may be implemented through the steps shown in fig. 3, specifically including:
Step 301, determining the current working mode of the simulated ray diving device based on the current motion state of the simulated ray diving device.
In specific implementation, the fuzzy logic control module firstly needs to determine the current working mode of the simulated batlight ray diving device based on the current motion state of the simulated batlight ray diving device, and the fuzzy logic control module divides the simulated batlight ray diving device into four working modes, namely a water surface floating mode, an arched gliding mode, a flapping wing maneuvering mode and a benthonic residence mode when in work. In a water surface floating mode, the simulated solar ray diving device floats on the water surface and mainly relies on a solar photovoltaic cell panel to capture energy. Under the arch-shaped gliding mode, the flapping wing maneuvering mode and the benthonic residence mode, the simulated bata diving device mainly depends on a ocean current energy friction power generation device to capture energy and supply energy. In the arch-shaped gliding mode, the simulated ray diving device glides in the water in an arch-shaped track, and the energy consumption is moderate. Under the flapping wing maneuvering mode, the simulated bated ray diving device maneuvers rapidly through flapping pectoral fins, and the energy consumption is high. In the benthic residence mode, the simulated ray diving device resides on the seabed for a long time, and the energy consumption is low.
Step 302, a fuzzy logic control rule set is formulated based on different working modes, different power consumption of the simulated batlight diving device and different SOC values of the flexible lithium battery pack.
In a specific implementation, the fuzzy logic control module can estimate the energy consumption in each working mode, set an upper threshold and a lower threshold of the energy demand, and then determine the energy reserve requirement in each mode according to the power consumption and the expected working time of the simulated bata diving device. That is, a fuzzy logic control rule set can be formulated based on different working modes, different power consumption of the simulated batlight ray diving apparatus and different SOC values of the flexible lithium battery pack. The formulated fuzzy logic control rule set comprises a priority rule of the energy harvesting device and an adjustment rule of the working state of the energy harvesting device.
In one example, the priority rules of the energy harvesting device set by the fuzzy logic control module are: when the working mode of the simulated ray diving device is a water surface floating mode, the solar photovoltaic cell panel is preferentially utilized to capture energy; when the working mode of the simulated ray of the submarine is an arch gliding mode, a flapping wing maneuvering mode or a benthonic residence mode, the ocean current energy friction power generation device is preferentially utilized to capture energy.
In one example, the fuzzy logic control module takes the power consumption of the simulated bata ray diving apparatus as a first fuzzy input variable and designs a fuzzy subset of the power consumption of the simulated bata ray diving apparatus asWherein, the method comprises the steps of, wherein,Indicating a small power consumption and,Represents a medium-power consumption of the power supply,Indicating a high power consumption and,. The fuzzy logic control module takes the SOC value of the flexible lithium battery pack as a second fuzzy input variable, and designs a fuzzy subset of the SOC value of the flexible lithium battery pack asWherein, the method comprises the steps of, wherein,Indicating a low SOC-value that is to be determined,The SOC value in the representation is set to,The high SOC value is indicated as such,. The fuzzy logic control module takes the output utilization rate of the energy harvesting device as a fuzzy output variable, and designs a fuzzy subset of the output utilization rate of the energy harvesting device asWherein, the method comprises the steps of, wherein,Indicating low output utilization, i.e. turning off the energy harvesting device,Output utilization in the representation, i.e. charging the flexible lithium battery pack preferentially,Represented by a high output utilization, i.e. charging the flexible lithium battery pack while supplying power to the output grid,. It is noted that the flexible lithium battery pack supplies power to the output power grid regardless of whether the energy harvesting device is turned off, the flexible lithium battery pack is charged preferentially, or the flexible lithium battery pack is charged and simultaneously supplies power to the output power grid.
In one example, the adjustment rules of the working states of the energy harvesting devices set by the fuzzy logic control module are shown in table 1.
Table 1: regulation rule of working state of energy harvester
As can be seen from Table 1, if the first fuzzy input variable falls withinAnd the second fuzzy input variable falls intoThe first fuzzy input variable falls intoAnd the second fuzzy input variable falls intoThe first fuzzy input variable falls intoAnd the second fuzzy input variable falls intoThe first fuzzy input variable falls intoAnd the second fuzzy input variable falls intoThe first fuzzy input variable falls intoAnd the second fuzzy input variable falls intoThe corresponding fuzzy output is; If the first fuzzy input variable falls intoAnd the second fuzzy input variable falls intoThe corresponding fuzzy output is; If the first fuzzy input variable falls intoAnd the second fuzzy input variable falls intoThe first fuzzy input variable falls intoAnd the second fuzzy input variable falls intoThe first fuzzy input variable falls intoAnd the second fuzzy input variable falls intoThe corresponding fuzzy output is。
Step 303, establishing membership functions for the power consumption of the simulated ray of the light, the SOC value of the flexible lithium battery pack and the output utilization rate of the energy harvesting device, and establishing a fuzzy reasoning system based on the membership functions of the power consumption of the simulated ray of the light, the SOC value of the flexible lithium battery pack and the output utilization rate of the energy harvesting device and a fuzzy logic control rule set.
In specific implementation, the fuzzy logic control module needs to establish membership functions for the power consumption of the bata-ray-simulating submersible, the SOC value of the flexible lithium battery pack and the output utilization rate of the energy harvesting device respectively, and the membership functions in the form of triangles can be expressed as follows:
Wherein, An argument representing a triangle membership function,AndThe legs of the triangle membership function are represented,The peaks representing the triangle membership functions,Representing a first fuzzy input variable, i.e. representing the power consumption of the simulated ray of the light diving apparatus,Representing a second fuzzy input variable, namely representing the SOC value of the flexible lithium battery pack,Representing the fuzzy output variable, i.e., representing the output utilization of the energy harvesting device, for different independent variables,There are differences in the values of (c) and, for different fuzzy subsets of the same argument,And the values of (2) are different.
The main parameters of the triangle membership function comprise two peak points (feet) and an inflection point (peak), the parameters can be adjusted according to practical conditions, the optimization is relatively easy, when the input variable changes in the area with concentrated membership function distribution density, the change of membership is obvious, and the response degree and the sensitivity degree of the fuzzy logic control module to the fuzzy input variable are increased.
The fuzzy logic control module can optimize key parameters (two peak points and an inflection point) of membership functions of each variable by adopting a genetic algorithm, and select an individual with highest fitness, wherein the membership function corresponding to the individual is an optimal solution, so that the optimal fuzzy control logic is established.
In one example, membership functions for power consumption of a simulated ray of a diving apparatus, a fuzzy subset thereofThe membership function of (2) can be expressed asFuzzy subsetThe membership function of (2) can be expressed asFuzzy subsetThe membership function of (2) can be expressed as. The membership function of the power consumption of the simulated ray diving apparatus may be as shown in fig. 4. Membership function for SOC value of flexible lithium battery pack, fuzzy subset thereofThe membership function of (2) can be expressed asFuzzy subsetThe membership function of (2) can be expressed asFuzzy subsetThe membership function of (2) can be expressed as. The membership function of the SOC value of the flexible lithium battery pack may be as shown in fig. 5. Membership function for output utilization of energy harvesting device, fuzzy subset thereofThe membership function of (2) can be expressed asFuzzy subsetThe membership function of (2) can be expressed asFuzzy subsetThe membership function of (2) can be expressed as. The membership function of the output utilization of the energy harvesting device may be as shown in fig. 6.
In a specific implementation, after the membership functions are respectively established for the power consumption of the simulated bata diving device, the SOC value of the flexible lithium battery pack and the output utilization rate of the energy capturing device, the fuzzy logic control module can establish a fuzzy reasoning system based on the membership functions of the power consumption of the simulated bata diving device, the SOC value of the flexible lithium battery pack and the output utilization rate of the energy capturing device and the fuzzy logic control rule set.
Step 304, inputting the current power consumption of the simulated ray diving apparatus and the current SOC value of the flexible lithium battery pack into a fuzzy reasoning system to obtain fuzzy output of the fuzzy reasoning system based on the maximization of the energy utilization rate.
In specific implementation, after the fuzzy logic control module establishes the fuzzy inference system, the current power consumption of the simulated ray diving device and the current SOC value of the flexible lithium battery pack can be input into the fuzzy inference system, the current power consumption of the simulated ray diving device is used as a first fuzzy input variable, a fuzzy subset in which the current power consumption of the simulated ray diving device falls is determined, the current SOC value of the flexible lithium battery pack is used as a second fuzzy input variable, the fuzzy subset in which the current SOC value of the flexible lithium battery pack falls is determined, and then based on the fuzzy logic control rule set, the corresponding fuzzy output based on the maximum energy utilization rate is determined according to the fuzzy subset in which the current power consumption of the simulated ray diving device falls and the fuzzy subset in which the current SOC value of the flexible lithium battery pack falls. The fuzzy logic control decision tree of the fuzzy inference system may be as shown in fig. 7.
And 305, performing fuzzy output de-fuzzy processing to obtain a control strategy for the energy harvesting device, converting the control strategy into a control signal and transmitting the control signal to the energy harvesting device.
In a specific implementation, after the fuzzy logic control module obtains the fuzzy output, the fuzzy output can be subjected to fuzzy treatment to obtain a control strategy for the energy harvesting device, the control strategy is converted into a control signal and the control signal is sent to the energy harvesting device, so that the work of the solar photovoltaic panel and/or the ocean current energy friction power generation device is adjusted, the intelligent allocation and management of energy sources are realized, and the efficient and stable operation of the simulated-light ray diving device under various working modes is ensured.
In one example, the fuzzy logic control module performs a defuzzification process on the fuzzy output to obtain a control strategy for the energy harvesting device, and then calculates a control strategy evaluation value based on the current power consumption of the artificial bata submersible, the current discharge power of the flexible lithium battery pack (the current output power of the flexible lithium battery pack) and the current energy harvesting power of the energy harvesting device (the current output power of the energy harvesting device), and if the calculated control strategy evaluation value is greater than a preset evaluation threshold, converts the control strategy into a control signal and sends the control signal to the energy harvesting device.
In one example, the fuzzy logic control module calculates the control strategy evaluation value based on the current power consumption of the simulated batray submersible, the current discharge power of the flexible lithium battery pack, and the current energy harvesting power of the energy harvesting device, by the following formula:
Wherein, Representing the current power consumption of the simulated ray diving apparatus,Indicating the current discharge power of the flexible lithium battery pack,Representing the current energy harvesting power of the energy harvesting device,The calculated control strategy evaluation value is represented.
In one example, the components of the fuzzy logic control module may be as shown in fig. 8, and the fuzzification interface may receive the current power consumption of the fuzzy logic simulated ray diving apparatus and the current SOC value of the flexible lithium battery pack, and convert the current power consumption and the current SOC value into fuzzy input variables, where a database and a rule base are provided in a knowledge base, and the rule base stores a fuzzy logic control rule set, and the inference engine is responsible for performing fuzzy inference to obtain a fuzzy output based on the maximization of the energy utilization, and outputs the fuzzy output from the defuzzification interface.
According to the embodiment, the multi-source energy system is provided with the solar photovoltaic cell panel and the ocean current energy friction power generation device, the solar photovoltaic cell panel and the ocean current energy friction power generation device are effectively and conformally mounted on the back and the abdomen of the simulated bata diving device, solar energy and ocean current energy can be fully utilized, capture of multi-source energy is achieved, and energy acquisition efficiency of the simulated bata diving device is effectively improved. The bending-resistant flexible lithium battery pack is designed on the basis of meeting load requirements and is arranged in the complex heterogeneous space of the pectoral fins of the simulated ray-light diving device, so that the space utilization rate of the simulated ray-light diving device is improved, the energy load is effectively increased, and a more efficient energy storage device is provided for the simulated ray-light diving device. The fuzzy logic control module capable of carrying out energy management based on fuzzy logic control is arranged in combination with the actual working condition of the simulated ray diving device, so that the energy utilization rate is effectively improved, the long-time self-holding of the simulated ray diving device is realized, and the simulated ray diving device can be ensured to operate efficiently and stably in various working modes.
It should be noted that, each module involved in this embodiment is a logic module, and in practical application, one logic unit may be one physical unit, or may be a part of one physical unit, or may be implemented by a combination of multiple physical units. In addition, in order to highlight the innovative part of the present application, units less closely related to solving the technical problem presented by the present application are not introduced in the present embodiment, but it does not indicate that other units are not present in the present embodiment.
It will be understood by those of ordinary skill in the art that the foregoing embodiments are specific examples of carrying out the application and that various changes in form and details may be made therein without departing from the spirit and scope of the application.
Claims (7)
1. A multi-source energy system for a ray-simulated diving device based on fuzzy logic control, the multi-source energy system comprising: the solar photovoltaic cell panel, the ocean current energy friction power generation device, the DC/DC conversion module, the MPPT controller, the fuzzy logic control module and the flexible lithium battery pack are energy harvesting devices of a multi-source energy system;
the solar photovoltaic cell panel is arranged at the back of the simulated ray diving device, the ocean current energy friction power generation device is arranged at the abdomen of the simulated ray diving device, and the flexible lithium battery pack is arranged in the pectoral fin of the simulated ray diving device;
The electric energy output of the solar photovoltaic panel and the ocean current energy friction power generation device is connected with a DC/DC conversion module, the positive and negative electric energy output of the DC/DC conversion module is connected with a fuzzy logic control module through an MPPT controller, and the fuzzy logic control module is also connected with a flexible lithium battery pack and an output power grid respectively;
The DC/DC conversion module is used for converting the electric energy output by the energy harvesting device into direct-current voltage, and the MPPT controller is used for stabilizing voltage, performing overvoltage protection and realizing maximum power point tracking;
The fuzzy logic control module is used for performing fuzzy logic control based on the current power consumption of the simulated ray diving apparatus and the current SOC value of the flexible lithium battery pack, outputting a control signal based on the maximization of the energy utilization rate, and adjusting the working state of the energy harvesting device;
The present power consumption based on the simulated ray diving apparatus and the present SOC value of the flexible lithium battery pack are subjected to fuzzy logic control, a control signal based on the maximization of the energy utilization rate is output, and the working state of the energy harvesting device is adjusted, and the method comprises the following steps:
Determining the current working mode of the simulated ray diving device based on the current motion state of the simulated ray diving device; wherein the working mode is a water surface floating mode, an arched gliding mode, a flapping wing maneuvering mode or a benthonic residence mode;
formulating a fuzzy logic control rule set based on different working modes, different power consumption of the simulated ray diving apparatus and different SOC values of the flexible lithium battery pack; the fuzzy logic control rule set comprises a priority rule of the energy harvesting device and an adjustment rule of the working state of the energy harvesting device;
Establishing a membership function for the power consumption of the simulated ray of the light, the SOC value of the flexible lithium battery pack and the output utilization rate of the energy harvesting device respectively, and establishing a fuzzy reasoning system based on the membership function of the power consumption of the simulated ray of the light, the SOC value of the flexible lithium battery pack and the output utilization rate of the energy harvesting device and a fuzzy logic control rule set;
Inputting the current power consumption of the simulated ray diving device and the current SOC value of the flexible lithium battery pack into a fuzzy reasoning system to obtain fuzzy output of the fuzzy reasoning system based on the maximization of the energy utilization rate;
Performing defuzzification processing on the fuzzy output to obtain a control strategy for the energy harvesting device, converting the control strategy into a control signal and transmitting the control signal to the energy harvesting device;
the priority rule of the energy harvesting device is set as follows:
when the working mode of the simulated ray diving device is a water surface floating mode, the solar photovoltaic cell panel is preferentially utilized to capture energy;
when the working mode of the simulated ray of the diving apparatus is an arc gliding mode, a flapping wing maneuvering mode or a benthonic residence mode, the ocean current energy friction power generation device is preferentially utilized to capture energy;
Taking the power consumption of the simulated ray diving device as a first fuzzy input variable, and designing a fuzzy subset of the power consumption of the simulated ray diving device as ; Wherein, Indicating a small power consumption and,Represents a medium-power consumption of the power supply,Indicating a high power consumption and,；
Taking the SOC value of the flexible lithium battery pack as a second fuzzy input variable, and designing a fuzzy subset of the SOC value of the flexible lithium battery pack as; Wherein, Indicating a low SOC-value that is to be determined,The SOC value in the representation is set to,The high SOC value is indicated as such,；
The output utilization rate of the energy harvesting device is used as a fuzzy output variable, and a fuzzy subset of the output utilization rate of the energy harvesting device is designed as; Wherein, Indicating that the energy harvesting device is turned off,Indicating that the flexible lithium battery pack is charged preferentially,Represented as a flexible lithium battery pack charging while supplying power to the output grid,；
The adjustment rule for setting the working state of the energy harvesting device is as follows:
if the first fuzzy input variable falls into And the second fuzzy input variable falls intoThe first fuzzy input variable falls intoAnd the second fuzzy input variable falls intoThe first fuzzy input variable falls intoAnd the second fuzzy input variable falls intoThe first fuzzy input variable falls intoAnd the second fuzzy input variable falls intoThe first fuzzy input variable falls intoAnd the second fuzzy input variable falls intoThe corresponding fuzzy output is；
If the first fuzzy input variable falls intoAnd the second fuzzy input variable falls intoThe corresponding fuzzy output is；
If the first fuzzy input variable falls intoAnd the second fuzzy input variable falls intoThe first fuzzy input variable falls intoAnd the second fuzzy input variable falls intoThe first fuzzy input variable falls intoAnd the second fuzzy input variable falls intoThe corresponding fuzzy output is。
2. The fuzzy logic control based multi-source energy system of a baton-oriented submersible as recited in claim 1, wherein the membership function is a triangular membership function expressed by the formula:
Wherein, An argument representing a triangle membership function,AndThe legs of the triangle membership function are represented,The peaks representing the triangle membership functions,Representing the power consumption of a first fuzzy input variable, namely a ray-simulated diving device,Representing a second fuzzy input variable, namely the SOC value of the flexible lithium battery pack,Representing the fuzzy output variable, i.e., the output utilization of the energy harvesting device, for different independent variables,There are differences in the values of (c) and, for different fuzzy subsets of the same argument,The values of (2) are different.
3. The fuzzy logic control-based multi-source energy system for a batray-simulating submersible of claim 2, wherein the inputting the current power consumption of the batray-simulating submersible and the current SOC value of the flexible lithium battery pack into the fuzzy inference system to obtain the fuzzy output of the fuzzy inference system based on the maximization of the energy utilization comprises:
Taking the current power consumption of the simulated ray diving device as a first fuzzy input variable, and determining a fuzzy subset in which the current power consumption of the simulated ray diving device falls;
taking the current SOC value of the flexible lithium battery pack as a second fuzzy input variable, and determining a fuzzy subset in which the current SOC value of the flexible lithium battery pack falls;
Based on the fuzzy logic control rule set, corresponding fuzzy output is determined according to a fuzzy subset in which the current power consumption of the simulated ray diving device falls and a fuzzy subset in which the current SOC value of the flexible lithium battery pack falls.
4. The fuzzy logic control based multi-source energy system of a simulated ray-light submersible as claimed in claim 3, wherein said defuzzifying said fuzzy output to obtain a control strategy for an energy harvesting device, converting said control strategy into a control signal and transmitting said control signal to said energy harvesting device, comprising:
performing defuzzification processing on the fuzzy output to obtain a control strategy for the energy harvesting device;
Calculating a control strategy evaluation value based on the current power consumption of the simulated ray of the submersible, the current discharge power of the flexible lithium battery pack and the current energy harvesting power of the energy harvesting device;
if the control strategy evaluation value is larger than a preset evaluation threshold value, converting the control strategy into a control signal and sending the control signal to an energy harvesting device;
The control strategy evaluation value is calculated based on the current power consumption of the simulated ray diving apparatus, the current discharge power of the flexible lithium battery pack and the current energy harvesting power of the energy harvesting device, and is realized by the following formula:
Wherein, Representing the current power consumption of the simulated ray of the vehicle,Indicating the current discharge power of the flexible lithium battery pack,Representing the current energy harvesting power of the energy harvesting device,The control policy evaluation value is represented.
5. The multi-source energy system for a simulated bata diving device based on fuzzy logic control of any of claims 1-4, wherein said solar photovoltaic panel is a gallium arsenide solar photovoltaic panel, said solar photovoltaic panel being sized and shaped to maximize the utilization of the back surface of said simulated bata diving device, enabling capturing solar energy under different angles and different lighting conditions.
6. The fuzzy logic control based multi-source energy system of a baton-like submersible as recited in any one of claims 1 to 4, wherein the ocean current energy friction power generation device is waterproof packaged with a high molecular organic material, and the outer surface of the baton-like submersible is provided with a drag-reducing material, which is a low friction coating or a micro-structured surface.
7. The multi-source energy system for a baton-based diving apparatus based on fuzzy logic control as claimed in any one of claims 1 to 4, wherein when the flexible lithium battery pack is arranged inside the pectoral fins of the baton-based diving apparatus, the internal structure of the pectoral fins of the baton-based diving apparatus is firstly modeled by using preset three-dimensional modeling software, the space size and shape for installing the flexible lithium battery pack are determined, and different installation positions and distribution modes of the flexible lithium battery pack inside the pectoral fins of the baton-based diving apparatus are simulated according to the overall design and performance requirements of the baton-based diving apparatus, and the effects of the gravity center position, the buoyancy distribution and the water flow of the baton-based diving apparatus on the baton-based diving apparatus are combined, so that the optimal installation positions and distribution modes are determined, and corresponding brackets and clamps are designed at the optimal installation positions to firmly install the flexible lithium battery pack.
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