Hybrid power ship energy management system based on fuzzy control

Abstract

The invention discloses a hybrid power ship energy management system based on fuzzy control, and relates to the technical field of hybrid power ship energy management, and the hybrid power ship energy management system comprises a state monitoring module, a fuzzy controller module, an energy scheduling module, a power source management module, a monitoring module and a fault diagnosis module. The system has the advantages that intelligent control over hybrid power ship energy management is achieved through the fuzzy controller module in combination with the fuzzy rule base and the membership function, the system can receive data of the state monitoring module in real time, a control decision is generated through fuzzy rule reasoning, and therefore energy of different power sources is accurately distributed, and the energy management efficiency is improved. According to the intelligent energy management and scheduling mode, the energy utilization efficiency of the ship is improved, and the performance of the ship in various sailing states is kept in the optimal state.

Description

Technical Field

[0001] The present invention relates to the technical field of energy management of hybrid power ships, and in particular to a hybrid power ship energy management system based on fuzzy control. Background Art

[0002] With the global energy crisis and increasing environmental awareness, hybrid ships, as a type of efficient and environmentally friendly ship, have gradually attracted widespread attention in the industry. However, the energy management system of hybrid ships is complex and critical, and its performance directly affects the energy efficiency, stability and safety of the ship. Traditional energy management methods are mostly based on fixed rules and thresholds, lacking flexibility and adaptability, and are difficult to cope with complex and changeable navigation environments and power source states.

[0003] In the existing technology, the energy management of hybrid ships usually relies on manually set control strategies and parameter adjustments. This method is not only inefficient, but also difficult to ensure optimal performance under various navigation conditions. For this reason, we propose a hybrid ship energy management system based on fuzzy control. Summary of the invention

[0004] The object of the present invention is to provide a hybrid power ship energy management system based on fuzzy control.

[0005] In order to solve the problems raised in the above background technology, the present invention provides the following technical solutions: A hybrid ship energy management system based on fuzzy control, comprising the following modules:

[0006] The status monitoring module monitors and collects the power source status parameters and navigation status parameters of the ship;

[0007] The fuzzy controller module builds a fuzzy rule base, defines membership functions, receives data monitored by the state monitoring module, and uses fuzzy rule reasoning to generate control decisions;

[0008] The energy scheduling module allocates the energy of different power sources in the hybrid ship according to the control decision output by the fuzzy controller module;

[0009] Power source management module, which operates and controls the various power sources of the ship, and maintains and manages the power sources;

[0010] The monitoring module provides an interactive display interface, displays the overall operating status of the hybrid ship energy management system in real time, and issues warnings for parameters that exceed the set thresholds;

[0011] The fault diagnosis module monitors the various components and modules in the hybrid ship energy management system in real time, generates diagnostic reports and treatment plans for abnormal conditions and faults, and transmits them to the power source management module.

[0012] As a further solution of the present invention: The state monitoring module includes a data acquisition unit, a data conversion unit, and a state judgment unit. The data acquisition unit is used to continuously collect parameters in the hybrid power ship system. The data conversion unit is used to convert the collected parameter data into interval range data. The state judgment unit is used to judge the current ship power source state and the ship navigation state.

[0013] As a further solution of the present invention: In the fuzzy controller module, the fuzzy rule base is constructed by collecting historical parameter data of various operating states of the ship and state adjustment processing methods, determining fuzzy sets, and using the association rule mining algorithm to find the internal relationship between different operating state parameters and corresponding adjustment strategies, and organizing them into a rule base. The membership function adopts a triangular membership function. For a certain operating state parameter x of the ship, the expression of the triangular membership function y(x) is:

[0014]

[0015] Where a, b, and c are the parameters of the triangular membership function, and a < b < c. The values of a, b, and c are determined according to the specific preset range of ship operating state parameters and the determination of fuzzy sets.

[0016] As a further solution of the present invention: The energy scheduling module includes a power distribution unit, an energy flow control unit, and an energy management strategy unit. The power distribution unit is used to distribute the power output of different ship power sources. The energy flow control unit is used to control the flow direction and magnitude of energy between different power sources. The energy management strategy unit is used to formulate an energy management strategy, which is obtained from the energy management strategy library. Different energy distribution schemes under different navigation states are stored in the energy management strategy library.

[0017] As a further solution of the present invention: The state monitoring module further includes an environmental monitoring unit, which is used to monitor the navigation environment of the ship. The energy management strategy library has an automatic learning and storage function. When the ship encounters a specific environmental condition during navigation, during the process of the ship safely passing through this environmental condition, the adjustment of each parameter in the energy management strategy is recorded and analyzed in real time, and the parameter information will be stored in the energy management strategy library as the preferred response strategy when the ship faces the same condition next time.

[0018] As a further solution of the present invention: the power source management module includes a power source control unit, a power source status monitoring unit and a power source maintenance unit. The power source control unit is used to control the power of the power source and switch the working mode of the power source. The power source status monitoring unit is used to monitor various status parameters of the power source in real time and analyze the status of the parameters. The power source maintenance unit is used to formulate a power source maintenance plan according to the usage of the power source.

[0019] As a further solution of the present invention: the monitoring module includes a display interaction unit and an alarm unit. The display interaction unit is used to display various data collected during the operation of the ship and provide an interface for operators to interact with the hybrid ship energy management system. The alarm unit is used to monitor the deviation between the numerical value of each parameter in the system and the set threshold in real time, and trigger an alarm mechanism for different deviations.

[0020] As a further solution of the present invention: the fault diagnosis module includes a fault detection unit, a fault location unit and a solution generation unit, the fault detection unit is used to detect the fault condition of the system, the fault location unit is used to determine the specific location of the fault and analyze the cause of the fault, and the solution generation unit is used to generate a fault handling solution according to the fault location and cause determined by the fault location unit.

[0021] As a further solution of the present invention: the fault diagnosis module further comprises a maintenance prediction unit, and the maintenance prediction unit is used to predict the future maintenance time of the power source, and the prediction expression is:

[0022] F=Pt-2t1-3E t

[0023] Among them, F is the time until the next maintenance, P is the initial maintenance interval, the default is 12 months, t is the current time used, the unit is month, t1 is the time of equipment overload use, E t Indicates the time the device was operating outside of normal operating temperature.

[0024] By adopting the above technical solution, compared with the prior art, the beneficial effects of the present invention are:

[0025] 1. The present invention realizes intelligent control of hybrid ship energy management through fuzzy controller module, combined with fuzzy rule base and membership function. The system can receive data from the status monitoring module in real time, generate control decisions by using fuzzy rule reasoning, and thus accurately allocate energy from different power sources. This intelligent energy management and scheduling method improves the energy utilization efficiency of the ship and ensures that the performance of the ship remains optimal under various navigation conditions;

[0026] 2. The present invention uses the automatic learning function of the environmental monitoring unit and the energy management strategy library in the state monitoring module to enable the system to record and analyze the adjustment of the energy management strategy in real time according to the performance of the ship under different environmental conditions. This self-learning ability enables the system to continuously optimize the response strategy, thereby improving the adaptability and overall operation efficiency of the ship in a complex navigation environment;

[0027] 3. The present invention monitors the various components and modules in the hybrid ship energy management system in real time through the fault diagnosis module, and can generate diagnostic reports and treatment plans for the abnormal conditions and faults generated. In addition, the maintenance prediction unit can also predict the future maintenance time of the power source, providing a scientific basis for the maintenance management of the ship. This comprehensive fault diagnosis and maintenance prediction function not only improves the reliability and safety of the ship, but also reduces maintenance costs and extends the service life of the power source. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 It is a schematic diagram of the process of a ship energy management system in an embodiment of the present invention. DETAILED DESCRIPTION

[0029] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0030] Embodiment 1:

[0031] Please see attached Figure 1 The hybrid ship energy management system based on fuzzy control of the present invention includes the following modules:

[0032] The status monitoring module monitors and collects the power source status parameters and navigation status parameters of the ship;

[0033] The fuzzy controller module builds a fuzzy rule base, defines membership functions, receives data monitored by the state monitoring module, and uses fuzzy rule reasoning to generate control decisions;

[0034] The energy scheduling module allocates the energy of different power sources in the hybrid ship according to the control decision output by the fuzzy controller module;

[0035] Power source management module, which operates and controls the various power sources of the ship, and maintains and manages the power sources;

[0036] Monitoring module, which provides a display and interaction interface to display the overall operating status of the hybrid ship energy management system in real time and issue warnings for parameters exceeding the set thresholds;

[0037] Fault diagnosis module, which monitors each component and module in the hybrid ship energy management system in real time, generates a diagnosis report and a treatment plan for the generated abnormal conditions and faults, and transmits them to the power source management module;

[0038] The status monitoring module includes a data acquisition unit, a data conversion unit, and a status judgment unit. The data acquisition unit is used to continuously collect parameters in the hybrid ship system. The data conversion unit is used to convert the collected parameter data into interval range data. The status judgment unit is used to judge the current ship power source status and ship navigation status;

[0039] In the fuzzy controller module, the fuzzy rule base is constructed by collecting historical parameter data of various operating states of the ship and status adjustment processing methods, determining the fuzzy sets, and finding the internal relationship between different operating state parameters and corresponding adjustment strategies through the association rule mining algorithm, and organizing them into a rule base. The membership function adopts a triangular membership function. For a certain operating state parameter x of the ship, the expression of the triangular membership function y(x) is:

[0040]

[0041] where a, b, and c are the parameters of the triangular membership function, and a < b < c. The values of a, b, and c are determined according to the specifically preset range of ship operating state parameters and the determination of the fuzzy sets.

[0042] Specific workflow: Install the energy management system we invented on a hybrid ship, in which the fuzzy controller module is the key to realizing intelligent energy management. Its fuzzy rule base is constructed by collecting the operating status parameter data and corresponding adjustment methods of the ship's past 100 different navigation tasks (near-sea transportation, ocean voyage, etc.), covering parameters such as navigation speed and power source power under different loads and corresponding energy adjustment measures. Taking the triangular membership function as an example, for the ship's navigation speed parameter, set a = 10 knots, b = 15 knots, and c = 20 knots. The status monitoring module obtains the ship's power source (engine speed, power, temperature, etc.) and navigation (speed, heading, etc.) status parameters in real time, such as During a near-shore voyage at a speed of 18 knots, the fuel engine and electric motor were used as power sources. After receiving the monitoring data, the fuzzy controller set the power output of the fuel engine to 80% and the electric motor to 20% through fuzzy rule reasoning to achieve precise energy distribution. The data showed that before the use of this system, the energy consumption of similar tasks was 100 liters of fuel and 20 kWh of electricity per nautical mile. After using it, the energy consumption was reduced to 80 liters of fuel and 15 kWh of electricity per nautical mile through statistics of 10 voyages on the same route, and the energy utilization efficiency was improved by 20%. At the same time, the fluctuation of the navigation speed was reduced from ±2 knots to ±0.5 knots, which greatly enhanced the navigation stability and safety of the ship, fully reflecting the advantages of the intelligent energy management and scheduling of the present invention.

[0043] Furthermore, through the fuzzy controller module, combined with the fuzzy rule base and membership function, intelligent control of the energy management of hybrid ships is realized. The system can receive data from the status monitoring module in real time, and use fuzzy rule reasoning to generate control decisions, thereby accurately allocating energy from different power sources. This intelligent energy management and scheduling method improves the energy utilization efficiency of the ship and ensures that the performance of the ship remains optimal under various navigation conditions.

[0044] Embodiment 2:

[0045] Based on the first embodiment, the energy scheduling module includes a power distribution unit, an energy flow control unit and an energy management strategy unit. The power distribution unit is used to distribute the power output of different power sources of the ship. The energy flow control unit is used to control the flow direction and size of energy between different power sources. The energy management strategy unit is used to formulate an energy management strategy, which is obtained from an energy management strategy library. The energy management strategy library stores energy distribution plans under different navigation states.

[0046] The status monitoring module also includes an environmental monitoring unit, which is used to monitor the navigation environment of the ship. The energy management strategy library has automatic learning and storage functions. When the ship encounters specific environmental conditions during navigation, the adjustment of each parameter in the energy management strategy is recorded and analyzed in real time while the ship safely passes through the environmental conditions. The parameter information will be stored in the energy management strategy library as a priority response strategy for the next time the ship faces the same situation.

[0047] Specific workflow: A hybrid ship sailing in different sea areas is equipped with the energy management system of the present invention. The environmental monitoring unit in its status monitoring module can monitor the sailing environment parameters in real time, and measure the wave height through the high-precision wave sensor on the bottom of the ship (accuracy ±0.1m), the wind speed through the anemometer on the top of the mast (accuracy ±0.5m / s), and the water temperature through the water temperature sensor. The energy management strategy library initially stores common environmental energy allocation plans. When crossing a certain sea area, encountering severe weather with a wave height of 3m-4m and a wind speed of 15m / s-20m / s, the system automatically The energy management strategy is adjusted according to the dynamic record analysis in response to this environment, such as allocating more energy to the fuel engine, reducing the power of the electric motor, and adjusting the energy flow control parameters. Compared with the past 20 similar sailing records in severe sea conditions, before the self-learning function was used, the sailing speed was reduced by about 30% on average, the energy consumption increased by about 40%, and there were 3 cases of insufficient power. After using this system, after statistics of 5 sailings in the same sea conditions, the speed was only reduced by 15%, the energy consumption increased by 20%, and there was no problem of insufficient power, which significantly improved the adaptability and operation efficiency of the ship in complex environments.

[0048] Furthermore, through the automatic learning function of the environmental monitoring unit and the energy management strategy library in the status monitoring module, the system can record and analyze the adjustment of the energy management strategy in real time according to the performance of the ship under different environmental conditions. This self-learning ability enables the system to continuously optimize the response strategy, thereby improving the ship's adaptability and overall operating efficiency in complex navigation environments.

[0049] Embodiment three:

[0050] Based on the second embodiment, the power source management module includes a power source control unit, a power source state monitoring unit and a power source maintenance unit. The power source control unit is used to control the power of the power source and switch the working mode of the power source. The power source state monitoring unit is used to monitor various state parameters of the power source in real time and analyze the state of the parameters. The power source maintenance unit is used to formulate a power source maintenance plan according to the use of the power source.

[0051] The monitoring module includes a display interaction unit and an alarm unit. The display interaction unit is used to display various data collected during the operation of the ship and provide operators with an interface for interacting with the hybrid ship energy management system. The alarm unit is used to monitor the deviation between the values ​​of various parameters in the system and the set thresholds in real time, and trigger the alarm mechanism for different deviations.

[0052] The fault diagnosis module includes a fault detection unit, a fault location unit and a solution generation unit. The fault detection unit is used to detect the fault condition of the system. The fault location unit is used to determine the specific location of the fault and analyze the cause of the fault. The solution generation unit is used to generate a fault handling solution according to the fault location and cause determined by the fault location unit.

[0053] The fault diagnosis module also includes a maintenance prediction unit, which is used to predict the future maintenance time of the power source. The prediction expression is:

[0054] F=Pt-2t1-3E t

[0055] Among them, F is the time until the next maintenance, P is the initial maintenance interval, the default is 12 months, t is the current time used, the unit is month, t1 is the time of equipment overload use, E t Indicates the time the device was operating outside of normal operating temperature.

[0056] Specific workflow: In the energy management system of a hybrid ship, the fault diagnosis module plays an important role. The fault detection unit uses a variety of technologies for real-time monitoring. For example, vibration sensors with an accuracy of up to ±0.01g are installed at key parts of the power source to collect vibration signals, and wavelet analysis technology is used to process signals to detect faults. When the power source temperature abnormally rises, the fault location unit combines the fault tree and event tree analysis methods to determine that it is a cooling system failure, and accurately locates it near the cooling water pump in the three-dimensional model of the ship. The solution generation unit generates a solution to temporarily replace the spare cooling water pump based on the navigation status of the ship approaching the port, the presence of a maintenance engineer on board, the basic maintenance tools and some spare parts carried by the ship, and the maintenance resources. The solution is verified in a virtual model simulation. The maintenance prediction unit generates a solution based on the formula F=Pt-2t1-3E t (P = 12 months, t = 8 months, t1 = 1 month, E t=0.5 month), adjusting the predicted maintenance time from 4 months to 0.5 month. Statistical data show that in the past 30 fault handlings, before using this function, the average fault diagnosis time was 4 hours and the ship downtime was 8 hours. After using it, statistics of 10 faults show that the diagnosis time was shortened to 2 hours and the downtime was reduced to 4 hours. In the past year, the number of maintenance times was reduced from 6 to 4 times, the maintenance cost was reduced by 30%, and the power source life was expected to be extended by 20%, which effectively improved the reliability and safety of the ship.

[0057] Furthermore, the fault diagnosis module monitors the various components and modules in the hybrid ship energy management system in real time, and can generate diagnostic reports and treatment plans for abnormal conditions and faults. In addition, the maintenance prediction unit can also predict the future maintenance time of the power source, providing a scientific basis for the maintenance management of the ship. This comprehensive fault diagnosis and maintenance prediction function not only improves the reliability and safety of the ship, but also reduces maintenance costs and extends the service life of the power source.

[0058] The above shows and describes the basic principles, main features and advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A hybrid ship energy management system based on fuzzy control, characterized in that: It includes the following modules: A status monitoring module that monitors and collects the status parameters of the power source of the ship and the navigation status parameters of the ship; A fuzzy controller module that constructs a fuzzy rule base, defines membership functions, receives the data monitored by the status monitoring module, and uses fuzzy rule reasoning to generate control decisions; An energy scheduling module that allocates the energy of different power sources in the hybrid ship according to the control decisions output by the fuzzy controller module; A power source management module that operates and controls each power source of the ship, and maintains and manages the power source; A monitoring module that provides a display and interaction interface, displays the overall operating status of the hybrid ship energy management system in real time, and issues warnings for parameters exceeding the set thresholds; A fault diagnosis module that monitors each component and module in the hybrid ship energy management system in real time, generates a diagnostic report and a processing plan for the generated abnormal conditions and faults, and transmits them to the power source management module.

2. The hybrid ship energy management system based on fuzzy control according to claim 1 is characterized by: The status monitoring module includes a data acquisition unit, a data conversion unit, and a status judgment unit. The data acquisition unit is used to continuously collect the parameters in the hybrid ship system. The data conversion unit is used to convert the collected parameter data into interval range data. The status judgment unit is used to judge the current ship power source status and the ship navigation status.

3. The hybrid ship energy management system based on fuzzy control according to claim 1 is characterized by: The construction method of the fuzzy rule base in the fuzzy controller module is as follows: collect the historical operation status parameter data of various types of ships and the status adjustment processing methods to determine the fuzzy sets. Through the association rule mining algorithm, find the internal relationship between different operation status parameters and the corresponding adjustment strategies, and organize them into a rule base. The membership function uses a triangular membership function. For a certain operation status parameter x of the ship, the expression of the triangular membership function y(x) is: where a, b, and c are the parameters of the triangular membership function, and a < b < c. The values of a, b, and c are determined according to the specific preset range of the ship operation status parameters and the determination of the fuzzy sets.

4. The hybrid ship energy management system based on fuzzy control according to claim 1 is characterized by: The energy scheduling module includes a power distribution unit, an energy flow control unit, and an energy management strategy unit. The power distribution unit is used to distribute the power output of different power sources of the ship. The energy flow control unit is used to control the flow direction and magnitude of energy between different power sources. The energy management strategy unit is used to formulate an energy management strategy, and the energy management strategy is obtained from the energy management strategy library. Different energy distribution schemes under different navigation statuses are stored in the energy management strategy library.

5. The hybrid ship energy management system based on fuzzy control according to claim 4 is characterized by: The status monitoring module also includes an environment monitoring unit, which is used to monitor the navigation environment of the ship. The energy management strategy library has an automatic learning and storage function. When the ship encounters a specific environmental condition during navigation, during the process of the ship safely passing through this environmental condition, the adjustment of each parameter in the energy management strategy is recorded and analyzed in real time, and the parameter information will be stored in the energy management strategy library as the preferred response strategy for the ship when facing the same condition next time.

6. The hybrid ship energy management system based on fuzzy control according to claim 1 is characterized by: The power source management module includes a power source control unit, a power source status monitoring unit and a power source maintenance unit. The power source control unit is used to control the power of the power source and switch the working mode of the power source. The power source status monitoring unit is used to monitor various status parameters of the power source in real time and analyze the status of the parameters. The power source maintenance unit is used to formulate a power source maintenance plan based on the usage of the power source.

7. The hybrid ship energy management system based on fuzzy control according to claim 1 is characterized by: The monitoring module includes a display interaction unit and an alarm unit. The display interaction unit is used to display various data collected during the operation of the ship and provide an interface for operators to interact with the hybrid ship energy management system. The alarm unit is used to monitor the deviation between the values ​​of various parameters in the system and the set threshold in real time, and trigger the alarm mechanism for different deviations.

8. The hybrid ship energy management system based on fuzzy control according to claim 1 is characterized by: The fault diagnosis module includes a fault detection unit, a fault location unit and a solution generation unit. The fault detection unit is used to detect the fault condition of the system. The fault location unit is used to determine the specific location of the fault and analyze the cause of the fault. The solution generation unit is used to generate a fault handling solution based on the fault location and cause determined by the fault location unit.

9. The hybrid power ship energy management system based on fuzzy control according to claim 1 is characterized by: The fault diagnosis module further comprises a maintenance prediction unit, which is used to predict the future maintenance time of the power source. The prediction expression is: F=P-t-2t1-3E t Among them, F is the time until the next maintenance, P is the initial maintenance interval, the default is 12 months, t is the current time used, the unit is month, t1 is the time of equipment overload use, E t Indicates the time the device was operating outside of normal operating temperature.

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