Pressure self-adaptive regulation and control system of deep sea self-pressure-bearing battery

Abstract

The invention relates to the technical field of deep sea batteries, and discloses a pressure self-adaptive regulation and control system of a deep sea self-pressure-bearing battery. The system comprises a battery body, a pressure adjusting module and a control module, a distributed optical fiber sensor array is arranged on the inner wall of a shell of the battery body, and the pressure adjusting module comprises a graphene reinforced rubber flexible air bag and a piezoelectric driving micro air pump. The control module generates differential pressure parameters according to battery starting, working and dormancy stages through the multi-stage parameter generation unit, calculates historical pressure deviation index optimization basic parameters through the historical deviation optimization unit, and dynamically adjusts pressure based on pressure influence factors and similarity matching in combination with the real-time adjustment unit. And the environment temperature influence is corrected through the temperature compensation unit, and underwater acoustic communication remote monitoring is supported. The system realizes + / -0.3% high-precision regulation and control of deep sea pressure, prolongs the service life of the battery by more than 50%, adapts to extreme environments of deep sea of 11000 meters, and has high efficiency and environmental adaptability.

Description

Technical Field

[0001] The present invention belongs to the field of deep-sea energy technology, and in particular relates to a pressure adaptive control system for a deep-sea self-contained pressure battery. Background Art

[0002] Deep-sea exploration and resource development require energy systems to adapt to extreme environments. At 11,000 meters deep, the ocean presents challenges such as 110 MPa hydrostatic pressure, low temperatures of 0-4°C, and complex chemical corrosion. Currently, deep-sea batteries generally use metal pressure-resistant casings to passively resist pressure. For example, CN118539025B discloses a dynamic pressure adjustment system for square sodium-ion battery modules. Although this system uses hydraulic actuators and multimodal sensors (voltage / current / temperature sensors) to achieve pressure regulation, its neural network algorithm and conventional rubber airbags are only suitable for conventional pressure scenarios on land and cannot solve the core problems in deep-sea environments:

[0003] The contradiction between static pressure resistance and dynamic regulation: the weight of the metal shell increases exponentially with depth (the weight of the shell at 10,000 meters deep sea is three times that of the battery body), and it cannot adapt to the pressure gradient changes during diving (increases by 10 MPa every 1,000 meters);

[0004] Insufficient real-time pressure control: The existing AI algorithm has a response time of >100ms, which cannot match the rapid pressure fluctuations during charging and discharging of deep-sea batteries (for example, the expansion of the battery cell during the discharge phase causes a sudden pressure increase of 5MPa / s);

[0005] Lack of environmental adaptability: It does not take into account the gas contraction caused by low temperatures in the deep sea (the volume of the air sac shrinks by 3% when the temperature drops from 4°C to 2°C), and lacks a temperature and pressure coupling compensation mechanism.

[0006] In view of this, the present invention is proposed. Summary of the Invention

[0007] The technical problem to be solved by the present invention is to overcome the deficiencies of the prior art and provide a pressure adaptive control system for a deep-sea self-contained pressure battery, thereby solving the problems raised in the above-mentioned background technology.

[0008] In order to solve the above technical problems, the basic concept of the technical solution adopted by the present invention is:

[0009] A pressure adaptive control system for a deep-sea self-contained pressure battery, comprising:

[0010] The battery body, the shell of the battery body is made of multi-layer composite materials, and the inner wall is provided with a pressure sensor array; the pressure sensor array is a distributed optical fiber sensor with a sampling frequency of ≥100Hz, and is evenly arranged along the circumference of the inner wall of the shell, with a spacing of ≤10cm;

[0011] A pressure regulating module includes a flexible airbag and a micro air pump, and the flexible airbag is connected to the micro air pump; the flexible airbag adopts a graphene-reinforced rubber composite material with a compressive strength of ≥110MPa, and the micro air pump adopts a piezoelectric drive with a response time of ≤50ms;

[0012] The control module is electrically connected to the pressure regulating module and includes:

[0013] The acquisition unit is used to collect the operating status information of the battery body and the pressure data of the pressure sensor;

[0014] a multi-stage parameter generation unit, the multi-stage parameter generation unit being configured to determine a first pressure parameter, a second pressure parameter, and a third pressure parameter according to the battery startup, working, and sleep stages, respectively, wherein the third pressure parameter is smaller than the first pressure parameter, and the first pressure parameter is smaller than the second pressure parameter;

[0015] The historical deviation optimization unit is used to calculate the historical pressure deviation index based on historical operating data and optimize the basic pressure parameters according to the index. When the historical deviation optimization unit calculates the historical pressure deviation index, the formula is:

[0016] Among them, HPI is the historical pressure deviation index, R i is the operational impact factor of the i-th pressure-related abnormal operational behavior, fab i Its frequency, F cb is the historical normal operation frequency, F nb is the frequency of abnormal behavior, β is the weight coefficient, n represents the number of historical abnormal operating behaviors associated with pressure; the operating impact factor R i The calculation method is as follows: extract the actual operating pressure corresponding to the abnormal behavior, calculate the first pressure difference between it and the ideal operating pressure, and the second pressure difference between it and the historical normal operating minimum pressure, and determine R based on the difference. i ;

[0017] The real-time adjustment unit is used to calculate the pressure influence factor based on the pressure data and adjust the pressure parameters according to the factor. When the real-time adjustment unit calculates the pressure influence factor, the formula is: Among them, PI is the pressure influence factor, P max 、P min 、P avg are the maximum, minimum and average pressure in the pressure data, P ideal is the ideal operating pressure;

[0018] Similarity matching unit, the similarity matching unit is used to calculate the similarity between the current pressure influencing factor and the historical data. The similarity formula is: Among them, S j is the similarity between the jth historical pressure influencing factor and the current factor, PIH j is a historical factor; the similarity matching unit determines an adjustment coefficient based on the maximum similarity. The adjustment coefficient includes three levels: when the maximum similarity is less than or equal to a first threshold, a first adjustment coefficient is used; when the maximum similarity is greater than the first threshold and less than or equal to a second threshold, a second adjustment coefficient is used; and when the maximum similarity is greater than the second threshold, a third adjustment coefficient is used.

[0019] Temperature compensation unit, the temperature compensation unit is used to correct the pressure parameters according to the temperature change of the deep sea environment. The correction formula is: P cor =P adj ·(1+k·ΔT), where P cor is the corrected pressure, Pad j To adjust the pressure, k is the temperature influence coefficient, and ΔT is the temperature change;

[0020] Remote monitoring interface, the remote monitoring interface is used to transmit pressure data and control status to shore-based equipment in real time through underwater acoustic communication protocol.

[0021] After adopting the above technical solution, the present invention has the following beneficial effects compared with the prior art. Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described below at the same time:

[0022] The present invention provides an adaptive pressure control system for deep-sea self-contained pressure batteries. This system uses a distributed optical fiber sensor array (sampling frequency ≥ 100 Hz, spacing ≤ 10 cm) to achieve high-precision pressure field monitoring. It also utilizes a hardware combination of a graphene-enhanced rubber flexible airbag (pressure resistance ≥ 110 MPa) and a piezoelectric-driven micro air pump (response time ≤ 50 ms) to construct a multi-stage dynamic pressure control system. The control module generates gradient pressure parameters according to the startup / operation / sleep stages through a multi-stage parameter generation unit. A historical deviation optimization unit uses a double-difference algorithm to calculate the historical pressure deviation index (HPI) to optimize basic parameters. This system, combined with a real-time adjustment unit's three-dimensional calculation model for pressure influencing factors and a three-level similarity matching adjustment coefficient, achieves a pressure control accuracy of ±0.3%. A temperature compensation unit addresses pressure correction issues in deep-sea low-temperature environments, and an underwater acoustic communication remote monitoring interface supports real-time transmission of data at depths of 10,000 meters. Compared to traditional solutions, this system improves battery operating efficiency by 30%, extends cycle life by more than 50%, and reduces weight by 40%, significantly enhancing adaptability and reliability in extreme deep-sea environments.

[0023] The specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The drawings described below are only some embodiments. A person skilled in the art can derive other drawings based on these drawings without inventive effort. In the drawings:

[0025] Figure 1 This is a module diagram of the overall architecture of the system of the present invention;

[0026] Figure 2 This is the internal logical connection diagram of the control module of the present invention.

[0027] It should be noted that these drawings and textual descriptions are not intended to limit the conceptual scope of the present invention in any way, but rather to illustrate the concept of the present invention for those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0028] The present invention will now be described in further detail with reference to the accompanying drawings.

[0029] See also Figure 1-2 As shown, in this embodiment, a pressure adaptive control system for a deep-sea self-contained pressure battery is provided, comprising:

[0030] The battery body, the shell of the battery body adopts a three-layer composite structure: the outer layer is carbon fiber reinforced resin (tensile strength ≥3000MPa), the middle layer is titanium alloy (thickness 3mm), the inner layer is a polyurethane buffer layer, and the inner wall is embedded with a distributed optical fiber pressure sensor array (model OFDR-P100); the pressure sensor array is a distributed optical fiber sensor with a sampling frequency of ≥100Hz, evenly arranged along the circumference of the inner wall of the shell, with a spacing of ≤10cm; it monitors the internal pressure distribution of the battery in real time; the internal battery cell adopts a high-pressure resistant packaging structure to adapt to the deep-sea static pressure environment;

[0031] The pressure regulation module includes a flexible airbag and a micro air pump, and the flexible airbag is connected to the micro air pump. The flexible airbag is made of graphene-reinforced rubber composite material, which is molded and has a thickness of 2mm. The pressure test shows that its deformation is ≤1% under a static pressure of 120MPa, the burst pressure is ≥150MPa, and the compressive strength is ≥110MPa. The micro air pump adopts a piezoelectric drive (model PMP-01), with an input voltage of 12V, a maximum inflation flow rate of 50mL / min, a response time of ≤50ms, and a power consumption of ≤0.5W, supporting fast inflation / exhaust operations. The flexible airbag and the micro air pump are connected by a high-pressure hose (pressure resistance ≥110MPa). The driving frequency of the micro air pump is adjusted in real time by the control module.

[0032] The control module is electrically connected to the pressure regulating module and includes:

[0033] The acquisition unit is used to collect the operating status information (voltage, current, temperature, etc.) of the battery during startup, operation, and sleep stages, as well as the pressure data of the pressure sensor;

[0034] A multi-stage parameter generation unit is used to determine a first pressure parameter, a second pressure parameter, and a third pressure parameter according to the battery startup, working, and dormant stages, respectively, and the third pressure parameter is less than the first pressure parameter, and the first pressure parameter is less than the second pressure parameter; wherein the third pressure parameter is less than the first pressure parameter, and the first pressure parameter is less than the second pressure parameter; the second pressure parameter is 1.2-1.5 times the first pressure parameter, and the third pressure parameter is 0.8-0.9 times the first pressure parameter; the parameter values ​​are dynamically corrected according to the deep sea depth gradient, and the second pressure parameter increases by 5% for every 1000-meter increase in depth;

[0035] Taking the 10,000-meter deep-sea exploration mission as an example, the parameter generation logic for the battery operation phase is as follows:

[0036] Startup phase (0-5 minutes after battery activation): The multi-stage parameter generation unit sets the first pressure parameter to 100 MPa. At this time, the micro air pump inflates the flexible airbag at 50% power, causing the internal pressure to quickly reach 100 MPa, adapting to the initial static pressure of the deep sea (100 MPa).

[0037] Working stage (detection equipment is in operation): Based on the starting stage pressure of 100MPa, the second pressure parameter is generated as 1.3×100MPa=130MPa to compensate for the volume expansion of the battery cell during discharge. At this time, the air pump maintains the airbag pressure at 130±0.5MPa;

[0038] Dormant stage (when the device is on standby): the third pressure parameter is generated as 0.85×100MPa=85MPa, and the air pump exhausts to reduce the internal pressure and reduce energy consumption;

[0039] The historical deviation optimization unit is used to calculate the historical pressure deviation index (HPI) based on historical operating data and optimize the basic pressure parameters according to the index; wherein, when the historical deviation optimization unit calculates the historical pressure deviation index, the formula is:

[0040] Among them, HPI is the historical pressure deviation index, R i is the operational impact factor of the i-th pressure-related abnormal operational behavior, fab i Its frequency, F cb is the historical normal operation frequency, F nb is the abnormal behavior frequency, β (0≤β≤1) is the weight coefficient, n represents the number of pressure-related historical abnormal operation behaviors; the operation impact factor R iThe calculation method is as follows: extract the actual operating pressure corresponding to the abnormal behavior, calculate the first pressure difference between it and the ideal operating pressure, and the second pressure difference between it and the historical normal operating minimum pressure, and determine R based on the difference. i ; Operation impact factor R i Calculation steps:

[0041] The first pressure difference: ΔP1=|P actual -P ideal |

[0042] Among them, P actual is the actual operating pressure corresponding to the abnormal behavior, P ideal It is the preset ideal operating pressure;

[0043] The second pressure difference: ΔP2=|P actual -P min_normal |

[0044] Among them, P min_normal is the minimum pressure value in historical normal operation behavior;

[0045] Weighted calculation R i :R i =0.6×ΔP1+0.4×ΔP2;

[0046] Taking a deep-sea battery as an example after three months of operation, the historical database records show:

[0047] When a certain pressure abnormal behavior occurs, the actual operating pressure P actual =135MPa, ideal pressure P ideal =130MPa, the historical minimum pressure for normal operation P min_normal =125MPa;

[0048] The frequency of abnormal behavior fab i =0.08, historical normal operation frequency F cb =0.92, weight coefficient β = 0.6;

[0049] Calculate the operation impact factor: ΔP1 = |135-130| = 5MPa, ΔP2 = |135-125| = 10MPa, Ri = 0.6×5+0.4×10=7, historical pressure deviation index: HPI = (7×0.08) / (0.92+0.6×0.08)≈0.58, preset threshold HT = 0.5. Since HPI>HT, the optimization unit is triggered to adjust the second pressure parameter to 1.35×the first pressure parameter (100MPa) = 135MPa

[0050] The real-time adjustment unit is used to calculate the pressure influence factor based on the pressure data and adjust the pressure parameters according to the factor. When the real-time adjustment unit calculates the pressure influence factor, the formula is: Among them, PI is the pressure influence factor, P max 、P min 、P avg are the maximum, minimum and average pressure in the pressure data, P ideal is the ideal operating pressure;

[0051] During the working phase, the distributed optical fiber sensor collects pressure data as follows:

[0052] Maximum pressure P max =132MPa, minimum pressure P min =128MPa, average pressure P avg =130MPa, ideal pressure P ideal =130MPa;

[0053] Calculate the pressure influence factor: PI = ((132-130) 2 +(128-130) 2 +(130-130) 2 ) / 3=(4+4+0) / 3≈2.67;

[0054] Similar pressure influencing factors PIH exist in the historical database j =2.5, calculate similarity: S j =1-(|2.67-2.5|) / 2.67≈0.94;

[0055] Set the first threshold value ST1 = 0.6, the second threshold value ST2 = 0.8, because S max =0.94>ST2, adopt the third adjustment coefficient A3=1.05, the adjusted pressure parameter=130×1.05=136.5MPa;

[0056] Similarity matching unit, the similarity matching unit is used to calculate the similarity between the current pressure influencing factor and the historical data. The similarity formula is: Among them, S j is the similarity between the jth historical pressure influencing factor and the current factor, PIH j is a historical factor; the similarity matching unit determines an adjustment coefficient based on the maximum similarity. The adjustment coefficient includes three levels: when the maximum similarity is less than or equal to a first threshold, a first adjustment coefficient is used; when the maximum similarity is greater than the first threshold and less than or equal to a second threshold, a second adjustment coefficient is used; and when the maximum similarity is greater than the second threshold, a third adjustment coefficient is used.

[0057] Temperature compensation unit, the temperature compensation unit is used to correct the pressure parameters according to the temperature change of the deep sea environment. The correction formula is: P cor =P adj ·(1+k·ΔT), where P cor is the corrected pressure, Pad j To adjust the pressure, k is the temperature influence coefficient (value is 0.002 / °C), and ΔT is the temperature change;

[0058] For example, a battery is placed at a depth of 5,000 meters in the ocean (ambient temperature 2°C) and the temperature drops to 0°C during operation:

[0059] Temperature change ΔT = 0-2 = -2°C, temperature influence coefficient k = 0.002 / °C;

[0060] Corrected pressure: P cor =136.5×(1+0.002×(-2))=136.5×0.996=135.954MPa

[0061] The control module sends a command to the micro air pump to increase the exhaust volume by 10%, stabilizing the airbag pressure at 135.95±0.3MPa;

[0062] Remote monitoring interface, used to transmit real-time pressure data and control status to shore-based equipment via underwater acoustic communication protocols (such as DS-Link). At depths of 10,000 meters, the control module packages pressure data at a 10Hz frequency and transmits it to the shore-based control center via an underwater acoustic modem, with a transmission delay of ≤5s and a data packet loss rate of ≤0.1%. Shore-based equipment can remotely issue parameter correction commands, such as temporarily adjusting the temperature influence coefficient k from 0.002 / °C to 0.0025 / °C to adapt to special sea environments.

[0063] The shore-based control center sends instructions to the deep-sea battery through the underwater acoustic communication protocol:

[0064] Issue a pressure parameter correction instruction: adjust the second pressure parameter of the working phase from 130MPa to 135MPa;

[0065] After receiving the command, the battery control module parses the data segment and verifies the check code, and responds with a confirmation signal within 50ms;

[0066] The air pump adjusts the inflation volume according to the new parameters, and the sensor sends real-time pressure data (such as P current =135.2MPa) is transmitted back to the shore at a frequency of 10Hz, with a transmission delay of 4.8s.

[0067] The present invention provides an adaptive pressure control system for deep-sea self-contained pressure batteries. This system uses a distributed optical fiber sensor array (sampling frequency ≥ 100 Hz, spacing ≤ 10 cm) to achieve high-precision pressure field monitoring. It also utilizes a hardware combination of a graphene-enhanced rubber flexible airbag (pressure resistance ≥ 110 MPa) and a piezoelectric-driven micro air pump (response time ≤ 50 ms) to construct a multi-stage dynamic pressure control system. The control module generates gradient pressure parameters according to the startup / operation / sleep stages through a multi-stage parameter generation unit. A historical deviation optimization unit uses a double-difference algorithm to calculate the historical pressure deviation index (HPI) to optimize basic parameters. This system, combined with a real-time adjustment unit's three-dimensional calculation model for pressure influencing factors and a three-level similarity matching adjustment coefficient, achieves a pressure control accuracy of ±0.3%. A temperature compensation unit addresses pressure correction issues in deep-sea low-temperature environments, and an underwater acoustic communication remote monitoring interface supports real-time transmission of data at depths of 10,000 meters. Compared to traditional solutions, this system improves battery operating efficiency by 30%, extends cycle life by more than 50%, and reduces weight by 40%, significantly enhancing adaptability and reliability in extreme deep-sea environments.

[0068] The present invention is not limited to the above-described embodiments. Any structural changes made under the guidance of the present invention, which have the same or similar technical solutions as the present invention, should be understood to fall within the scope of protection of the present invention. The technologies, shapes, and structural parts not described in detail in the present invention are all well-known technologies.

Claims

1. A pressure adaptive control system for deep-sea self-contained pressure batteries, characterized in that: include: The battery body, the outer shell of the battery body is made of multi-layer composite materials, and the inner wall is provided with a pressure sensor array; A pressure regulating module includes a flexible airbag and a micro air pump, wherein the flexible airbag is connected to the micro air pump; The control module is electrically connected to the pressure regulating module and includes: The acquisition unit is used to collect the operating status information of the battery body and the pressure data of the pressure sensor; a multi-stage parameter generation unit, the multi-stage parameter generation unit being configured to determine a first pressure parameter, a second pressure parameter, and a third pressure parameter according to the battery startup, working, and sleep stages, respectively, wherein the third pressure parameter is smaller than the first pressure parameter, and the first pressure parameter is smaller than the second pressure parameter; A historical deviation optimization unit is used to calculate a historical pressure deviation index based on historical operating data and optimize basic pressure parameters according to the index; The real-time adjustment unit is used to calculate the pressure influence factor based on the pressure data and adjust the pressure parameters according to the factor.

2. The pressure adaptive control system for a deep-sea self-contained pressure battery according to claim 1, characterized in that: When the historical deviation optimization unit calculates the historical pressure deviation index, the formula is: Among them, HPI is the historical pressure deviation index, R i is the operational impact factor of the i-th pressure-related abnormal operational behavior, fab i Its frequency, F cb is the historical normal operation frequency, F nb is the frequency of abnormal behavior, β is the weight coefficient, and n represents the number of historical abnormal operating behaviors associated with pressure.

3. The pressure adaptive control system for a deep-sea self-contained battery according to claim 2, characterized in that: Operation impact factor R i The calculation method is as follows: extract the actual operating pressure corresponding to the abnormal behavior, calculate the first pressure difference between it and the ideal operating pressure, and the second pressure difference between it and the historical normal operating minimum pressure, and determine R based on the difference. i .

4. The pressure adaptive control system for a deep-sea self-contained pressure battery according to claim 1, characterized in that: When the real-time adjustment unit calculates the pressure influence factor, the formula is: Among them, PI is the pressure influence factor, P max 、P min 、P avg are the maximum, minimum and average pressure in the pressure data, P ideal is the ideal operating pressure.

5. The pressure adaptive control system for a deep-sea self-contained pressure battery according to claim 1, characterized in that: The control module also includes: Similarity matching unit, the similarity matching unit is used to calculate the similarity between the current pressure influencing factor and the historical data. The similarity formula is: Among them, S j is the similarity between the jth historical pressure influencing factor and the current factor, PIH j For historical factors.

6. The pressure adaptive control system for a deep-sea self-contained pressure battery according to claim 5, characterized in that: The similarity matching unit determines an adjustment coefficient based on the maximum similarity. The adjustment coefficient includes three levels: when the maximum similarity is less than or equal to a first threshold, a first adjustment coefficient is adopted; when the maximum similarity is greater than the first threshold and less than or equal to a second threshold, a second adjustment coefficient is adopted; and when the maximum similarity is greater than the second threshold, a third adjustment coefficient is adopted.

7. The pressure adaptive control system for a deep-sea self-contained pressure battery according to claim 1, characterized in that: The pressure sensor array is a distributed optical fiber sensor with a sampling frequency of ≥100 Hz, which is evenly arranged along the circumference of the inner wall of the shell with a spacing of ≤10 cm.

8. The pressure adaptive control system for a deep-sea self-contained pressure battery according to claim 1, characterized in that: The flexible airbag is made of graphene-reinforced rubber composite material with a compressive strength of ≥110MPa, and the micro air pump is piezoelectrically driven with a response time of ≤50ms.

9. The pressure adaptive control system for a deep-sea self-contained pressure battery according to claim 1, characterized in that: The control module also includes a temperature compensation unit, which is used to correct the pressure parameters according to the temperature change of the deep sea environment. The correction formula is: P cor =P adj ·(1+k·ΔT), where P cor is the corrected pressure, Pad j To adjust the pressure, k is the temperature influence coefficient, and ΔT is the temperature change.

10. The pressure adaptive control system for a deep-sea self-contained pressure battery according to claim 1, characterized in that: The control module also includes a remote monitoring interface, which is used to transmit pressure data and control status to shore-based equipment in real time through an underwater acoustic communication protocol.

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