Emission optimization control system and method for alternative fuel sail-aided hybrid power ship

Abstract

The embodiment of the invention discloses an alternative fuel sail-aided hybrid power ship emission optimization control system and method, and the method comprises the steps: forming a CO2 emission spatial and temporal distribution characteristic mapping table through an emission characteristic analysis unit, and solving a constructed CO2 emission optimization model through an emission optimization decision unit by employing an NSGA-III optimization algorithm, obtaining an optimization result corresponding to the lowest CO2 emission of the alternative fuel sail-aided hybrid power ship; the CO2 emission level corresponding to the optimized operation scheme of the alternative fuel sail-aided hybrid power ship is evaluated and analyzed through an emission optimization evaluation unit; meanwhile, collaborative optimization control over the alternative fuel sail-aided navigation hybrid power ship is achieved through the CO2 emission optimization control unit, and then optimization control over the alternative fuel sail-aided navigation hybrid power ship with the lowest CO2 emission is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of alternative fuel sail-assisted hybrid power ships, and in particular to an emission optimization control system and method for alternative fuel sail-assisted hybrid power ships. Background Art

[0002] Low-carbon development of ships is an inevitable trend for the shipping industry to cope with climate change and achieve green and low-carbon transformation. In order to solve the increasingly prominent drawbacks of traditional fossil fuels, reduce greenhouse gas emissions from ships, promote the transformation and upgrading of the energy structure of the shipping industry, and address pollution problems such as CO2 emissions caused by the combustion of fossil fuels, achieving energy conservation and emission reduction in ships has become an urgent need for the shipping industry. The limitations of traditional fossil fuels make it inevitable to find alternative fuels. However, alternative fuels generally have problems such as low energy density, which leads to obvious deficiencies in ship power supply and ship endurance. Therefore, it is difficult to completely solve the energy and emission problems of ships by relying solely on alternative fuels.

[0003] The introduction of wind energy, a renewable energy source, can effectively make up for the shortcomings of alternative fuels in energy density and further improve the energy efficiency of ships. However, although the application of wind energy has alleviated the problem of low energy density of alternative fuels to a certain extent, in actual operation, alternative fuel sail-assisted hybrid ships still face the problem of optimizing CO2 emissions. There are many factors affecting the CO2 emission control of alternative fuel sail-assisted hybrid ships, and the optimization and control of CO2 emissions is relatively complex. Therefore, under complex ship operating conditions, the inability to effectively coordinate the relationship between alternative fuels and wind energy, and thus ensure the continuous optimization and control of CO2 emissions, is still a technical problem that needs to be solved urgently in the current technical field. Summary of the invention

[0004] Based on this, in order to solve the shortcomings of the above technical problems, an emission optimization control system and method for an alternative fuel sail-assisted hybrid ship is proposed.

[0005] An emission optimization control system for an alternative fuel sail-assisted hybrid ship, comprising: a data acquisition and analysis unit, an emission characteristic analysis unit, an emission optimization decision unit, an emission optimization evaluation unit, and a CO2 emission optimization control unit;

[0006] The data acquisition and analysis unit is used to obtain various types of ship operation data, including but not limited to sail attack angle, ship speed, fuel mixture ratio, fuel injection pressure, fuel injection timing, wave height, wave direction, wind direction and wind speed data;

[0007] The emission characteristic analysis unit is used to obtain the mapping relationship between the ship operation data and the CO2 emission data under different spatiotemporal distribution characteristics to form a CO2 emission spatiotemporal distribution characteristic mapping table;

[0008] Among them, the emission optimization decision unit is used to solve the constructed CO2 emission optimization model through the NSGA-III optimization algorithm to obtain the optimization results of the optimal sail attack angle, ship speed, fuel mixture ratio, fuel injection pressure, and fuel injection timing corresponding to the lowest CO2 emission of the alternative fuel sail-assisted hybrid ship; the CO2 emission optimization model combines the energy consumption of the alternative fuel sail-assisted hybrid ship with the fuel carbon emission conversion coefficient to characterize the mapping relationship between the energy consumption of the alternative fuel sail-assisted hybrid ship and the CO2 emission, and calculates and obtains the CO2 emission optimization result of the alternative fuel sail-assisted hybrid ship;

[0009] wherein, an emission optimization evaluation unit is used to evaluate and analyze the CO2 emission optimization result corresponding to the optimized operation scheme of the alternative fuel sail-assisted hybrid ship based on the optimization result, and output the CO2 emission level of the optimized alternative fuel sail-assisted hybrid ship;

[0010] Among them, the CO2 emission optimization control unit is used to achieve coordinated optimization control of the alternative fuel sail-assisted hybrid ship based on the optimization result, so as to achieve the lowest CO2 emission optimization control of the alternative fuel sail-assisted hybrid ship.

[0011] Optionally, in one of the embodiments, the different spatiotemporal distribution characteristics refer to changes in CO2 emissions with the ship's navigation time and space.

[0012] Optionally, in one embodiment, the energy consumption of the alternative fuel sail-assisted hybrid ship is obtained by a pre-constructed alternative fuel sail-assisted hybrid ship energy consumption model, and the specific calculation formula is as follows:

[0013]

[0014] In the formula, q represents the energy consumption per unit distance of the ship; R represents the total resistance of the alternative fuel sail-assisted hybrid ship; F T represents the sail thrust; ω represents the wake coefficient; η S Indicates the shaft transmission efficiency; η G represents the transfer efficiency; η R represents the relative rotation efficiency of the propeller; J represents the propulsion coefficient; K Q represents the torque coefficient; t represents the thrust reduction coefficient; g main Indicates the host energy consumption rate.

[0015] Optionally, in one embodiment, the optimization objective function and constraints of the CO2 emission optimization model are as follows:

[0016]

[0017] θ min ≤θ≤θ max (3)

[0018] v min ≤v≤v max (4)

[0019] α min ≤α≤α max (5)

[0020] P min ≤P≤P max (6)

[0021]

[0022] In the formula, represents the CO2 emission of alternative fuel sail-assisted hybrid ship; k represents the fuel carbon emission conversion coefficient; θ represents the sail attack angle; v represents the ship speed; α represents the fuel mixing ratio; P represents the injection pressure; represents the injection timing, and equation (3) defines the sail angle constraint, θ min and θ max represent the minimum sail angle of attack and the maximum sail angle of attack respectively; Formula (4) defines the speed constraint of alternative fuel sail-assisted hybrid ship, v min and v max They represent the minimum speed and maximum speed of the alternative fuel sail-assisted hybrid ship respectively; Formula (5) defines the fuel mixture ratio constraint, α min and α max They represent the minimum fuel mixture ratio and the maximum fuel mixture ratio of the alternative fuel sail-assisted hybrid ship respectively; Formula (6) defines the fuel injection pressure constraint condition, P min and P max They represent the minimum fuel injection pressure and the maximum fuel injection pressure respectively; Formula (7) defines the fuel injection timing constraint condition, and Represent the minimum and maximum fuel injection timing respectively.

[0023] Optionally, in one embodiment, the step of solving the constructed CO2 emission optimization model by using the NSGA-III optimization algorithm includes:

[0024] S1. Initializing and encoding the parameters to be optimized; wherein the parameters to be optimized are the sail attack angle, the ship speed, the alternative fuel mixture ratio, the fuel injection pressure, and the fuel injection timing parameters;

[0025] S2. Randomly generate the initial population P based on the encoded parameters to be optimized t , wherein each individual represents a possible operation configuration of the alternative fuel sail-assisted hybrid ship; the possible operation configuration specifically corresponds to each data combination form corresponding to the parameters to be optimized in the CO2 emission optimization model, wherein the individual fitness is the CO2 emission of the alternative fuel sail-assisted hybrid ship, and the specific individual fitness value is obtained through the optimization objective function of the CO2 emission optimization model;

[0026] S3, based on individual fitness, the initial population P t Perform non-dominant treatment and generate offspring population Q t , that is, for the initial population P t The individuals in the non-dominated sorting are sorted, the CO2 emission fitness values ​​corresponding to the individuals are sorted from small to large, n individuals corresponding to low CO2 emissions are selected as the next generation individuals, and crossover and mutation operations are performed to obtain the offspring population Q t ;

[0027] S4, the initial population P t With the offspring population Q t Combine to generate a new generation of population R t ;

[0028] S5. Calculate population R t The individual fitness of the new individual is sorted from small to large based on the new individual fitness, and n individuals corresponding to low CO2 emissions are selected as the next generation individuals to form a new parent population P t+1 , and perform crossover and mutation operations to obtain a new offspring population Q t+1 ;

[0029] S6, the population P t+1 With Q t+1 Combine to generate a new population R t+1 , and perform cyclic iterative optimization based on the method of S5 until the preset termination condition is reached and the optimization result is output. The termination condition can be the set number of iterations;

[0030] S7, transmitting the optimization result to the emission optimization evaluation unit and the CO2 emission optimization control unit, so as to realize the evaluation and control of the CO2 emission of the alternative fuel sail-assisted hybrid ship.

[0031] Optionally, in one embodiment, the CO2 emission level of the alternative fuel sail-assisted hybrid ship calculated by the emission optimization assessment unit is calculated as follows:

[0032]

[0033] In the formula, It represents the CO2 emission index of alternative fuel sail-assisted hybrid ship, which is used to analyze the CO2 emission level of alternative fuel sail-assisted hybrid ship; M represents the load of alternative fuel sail-assisted hybrid ship; D represents the sailing distance of alternative fuel sail-assisted hybrid ship.

[0034] Optionally, in one embodiment, the control process of the collaborative optimization control includes: optimizing the control of the sail attack angle through the sail control system of the alternative fuel sail-assisted hybrid ship, optimizing the ship speed through the ship control system, and controlling the mixing ratio of the alternative fuel, the injection pressure of the fuel and the injection timing of the fuel according to the control parameters corresponding to the optimization results through the alternative fuel engine electronic control system, so that the alternative fuel sail-assisted hybrid ship can achieve the best CO2 emission control effect during navigation.

[0035] In addition, in order to solve the shortcomings of traditional technologies, an emission optimization control method based on the emission optimization control system of the alternative fuel sail-assisted hybrid ship is also proposed, and its corresponding steps include:

[0036] S81, acquiring various types of ship operation data through the data acquisition and analysis unit;

[0037] S82, by acquiring the mapping relationship between the ship operation data and the CO2 emission data under different spatiotemporal distribution characteristics, to form a CO2 emission spatiotemporal distribution characteristic mapping table;

[0038] S83. Solve the constructed CO2 emission optimization model through the NSGA-III optimization algorithm to obtain the optimization results of the optimal sail attack angle, ship speed, fuel mixture ratio, fuel injection pressure, and fuel injection timing corresponding to the lowest CO2 emission of the alternative fuel sail-assisted hybrid ship, so as to achieve the minimization optimization control of CO2 emission of the alternative fuel sail-assisted hybrid ship;

[0039] S84. Based on the optimization results, the coordinated optimization control of key parameters such as the sail attack angle, ship speed, alternative fuel mixture ratio, fuel injection pressure, and fuel injection timing of the alternative fuel sail-assisted hybrid ship is achieved through the optimization decision control unit, so that the alternative fuel sail-assisted hybrid ship can achieve the best CO2 emission control effect during navigation. At the same time, based on the optimization results, the CO2 emission index of the alternative fuel sail-assisted hybrid ship is calculated, so as to achieve the analysis and evaluation of the CO2 emission level of the alternative fuel sail-assisted hybrid ship.

[0040] In addition, the present invention also proposes a computer-readable storage medium, comprising computer instructions, and when the computer instructions are executed on a computer, the computer executes the method described.

[0041] Implementing the embodiments of the present invention will have the following beneficial effects:

[0042] This invention solves the difficulty of controlling CO2 emissions of alternative fuel sail-assisted hybrid ships. By optimizing the coordinated use of wind energy and alternative fuels, the emission control capability of ships under different working conditions is improved, thereby achieving dual optimization of ship energy efficiency and emissions. This technological breakthrough not only helps promote the green transformation of the shipping industry, but also provides new technical support for the low-carbon development of the global shipping industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0044] in:

[0045] Figure 1 This is a framework diagram of the emission optimization control system for the alternative fuel sail-assisted hybrid ship of the present invention;

[0046] Figure 2 This is a diagram of the solution process of the CO2 emission optimization model of the alternative fuel sail-assisted hybrid ship based on the NSGA-III algorithm of the present invention;

[0047] Figure 3 This is a diagram of the CO2 emission optimization control implementation process of the alternative fuel sail-assisted hybrid ship of the present invention;

[0048] Figure 4 This is a flow chart of the CO2 emission optimization control method for alternative fuel sail-assisted hybrid ship according to the present invention. DETAILED DESCRIPTION

[0049] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0050] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those generally understood by those skilled in the art of the technical field of the present invention. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. It is understood that the terms "first", "second", etc. used in the present invention can be used to describe various elements in this article, but these elements are not limited by these terms. These terms are only used to distinguish the first element from another element. For example, without departing from the scope of the present application, the first element can be referred to as the second element, and similarly, the second element can be the first element. Both the first element and the second element are elements, but they are not the same element.

[0051] In this embodiment, if Figure 1-4 As shown, an emission optimization control system for alternative fuel sail-assisted hybrid ship is proposed, including: a data acquisition and analysis unit, an emission characteristic analysis unit, an emission optimization decision unit, an emission optimization evaluation unit and a CO2 emission optimization control unit;

[0052] In some specific embodiments, the data acquisition and analysis unit integrates multiple sensor technologies to collect and obtain multiple types of ship operation data in real time, and the ship operation data includes but is not limited to key parameter data such as sail angle of attack, ship speed, fuel mixture ratio, fuel injection pressure, fuel injection timing, wave height, wave direction, wind direction and wind speed; the specific sensors involved include: such as using an angle sensor or a special angle of attack sensor to obtain the sail angle of attack, such as using a ship speedometer, such as a Doppler sonar speed meter or a water wheel speed sensor to obtain the ship speed, or using GPS to measure the speed relative to the ground; such as using a fuel-air ratio sensor, such as a wide-band oxygen sensor or an AFR sensor to obtain the fuel mixture ratio, such as using a pressure sensor installed on the fuel supply line to obtain the fuel injection pressure, such as managing multiple sensors through an engine control unit to obtain fuel injection timing, such as using a buoy wave height meter, a laser radar, an ultrasonic sensor or an accelerometer to obtain wave height, such as using a direction sensor, a buoy wave sensor to obtain wave direction, such as using a wind vane to obtain wind direction, such as using an anemometer to obtain wind speed, so as to provide subsequent units with more accurate navigation information and performance parameters.

[0053] In some specific embodiments, the emission characteristic analysis unit is used to obtain the mapping relationship between the ship operation data and CO2 emission data under different spatiotemporal distribution characteristics to form a CO2 emission spatiotemporal distribution characteristic mapping table, which reflects the relationship between the ship operation data and CO2 emissions under different time and space conditions (i.e., the navigation conditions and navigation environment corresponding to different times and navigation positions). In this way, the ship operator is guided to analyze and optimize the carbon emission performance of the ship;

[0054] The different spatiotemporal distribution characteristics refer to the changes in CO2 emissions over time and space, specifically including different operating conditions (such as different geographical locations, loads at different times, ship speeds, sail angles, fuel mixture ratios, etc.) and different navigation environment conditions (such as different geographical locations, wind speeds, wind directions, wave heights, wave directions, etc. at different times). For example, when a ship is operating under heavy load and light load, high speed and low speed, different sail angle settings and different fuel mixture ratios, its CO2 emissions will show different characteristics. For example, when a ship is sailing in different sea areas, due to changes in wind and currents, CO2 emissions may vary significantly; similarly, under different seasons or climatic conditions, the CO2 emission characteristics of ships will also be different; by integrating multiple sensor technologies to collect CO2 emission law data under different operating conditions and CO2 emission spatiotemporal distribution law data under different navigation positions and navigation environment conditions in real time, so that the decision model of the emission optimization decision unit can use these data tables to calculate the carbon emissions under different parameter combinations through the fitness function, and find the optimal solution through the NSGA-III optimization algorithm. Finally, the optimization parameters output by the CO2 emission optimization model, including the optimal sail attack angle, ship speed, fuel mixture ratio, fuel injection pressure and fuel injection timing, are applied in actual operation to achieve the lowest CO2 emissions of the sail-assisted hybrid ship.

[0055] In some specific embodiments, the emission optimization decision unit is used to solve the constructed CO2 emission optimization model through the NSGA-III optimization algorithm to obtain the optimization results of the optimal sail attack angle, ship speed, fuel mixture ratio, fuel injection pressure, and fuel injection timing corresponding to the lowest CO2 emission of the alternative fuel sail-assisted hybrid ship; the CO2 emission optimization model combines the energy consumption of the alternative fuel sail-assisted hybrid ship with the fuel carbon emission conversion coefficient to characterize the mapping relationship between the energy consumption of the alternative fuel sail-assisted hybrid ship and the CO2 emission, and calculates and obtains the CO2 emission optimization result of the alternative fuel sail-assisted hybrid ship;

[0056] The energy consumption of alternative fuel sail-assisted hybrid ships is obtained through a pre-constructed alternative fuel sail-assisted hybrid ship energy consumption model. The alternative fuel sail-assisted hybrid ship energy consumption model comprehensively considers various factors such as total ship resistance, sail thrust, shafting transmission efficiency, transmission efficiency, propeller relative rotation efficiency, and main engine energy consumption rate under different navigation environment conditions, and can realize the analysis and calculation of the energy consumption of alternative fuel sail-assisted hybrid ships. The specific calculation formula is as follows:

[0057]

[0058] In the formula, q represents the energy consumption per unit distance of the ship; R represents the total resistance of the alternative fuel sail-assisted hybrid ship; F T represents the sail thrust; ω represents the wake coefficient; η S Indicates the shaft transmission efficiency; η G represents the transfer efficiency; η R represents the relative rotation efficiency of the propeller; J represents the propulsion coefficient; K Q represents the torque coefficient; t represents the thrust reduction coefficient; g main Indicates the host energy consumption rate;

[0059] The CO2 emission optimization model is used to calculate the CO2 emission of the alternative fuel sail-assisted hybrid ship by combining the energy consumption of the alternative fuel sail-assisted hybrid ship with the fuel carbon emission conversion coefficient, so that the model can determine the optimization control scheme corresponding to reducing the CO2 emission of the alternative fuel sail-assisted hybrid ship for different sail attack angles, ship speeds, fuel mixture ratios, fuel injection pressures, fuel injection timing and other optimization parameters; specifically, the optimization objective function and constraints of the CO2 emission optimization model are as follows:

[0060]

[0061] θ min ≤θ≤θ max (3)

[0062] v min ≤v≤v max (4)

[0063] α min ≤α≤α max (5)

[0064] P min ≤P≤P max (6)

[0065]

[0066] In the formula, represents the CO2 emission of alternative fuel sail-assisted hybrid ship; k represents the fuel carbon emission conversion coefficient; θ represents the sail attack angle; v represents the ship speed; α represents the fuel mixing ratio; P represents the injection pressure; represents the injection timing, and equation (3) defines the sail angle constraint, θ min and θ max represent the minimum sail angle of attack and the maximum sail angle of attack respectively; Formula (4) defines the speed constraint of alternative fuel sail-assisted hybrid ship, v min and v max They represent the minimum speed and maximum speed of the alternative fuel sail-assisted hybrid ship respectively; Formula (5) defines the fuel mixture ratio constraint, α min and α max They represent the minimum fuel mixture ratio and the maximum fuel mixture ratio of the alternative fuel sail-assisted hybrid ship respectively; Formula (6) defines the fuel injection pressure constraint condition, P min and P max They represent the minimum fuel injection pressure and the maximum fuel injection pressure respectively; Formula (7) defines the fuel injection timing constraint condition, and Represent the minimum and maximum fuel injection timing respectively.

[0067] The fuel carbon emission conversion coefficient k is determined according to the characteristics of the specific alternative fuel. For example, for heavy oil, its carbon emission conversion coefficient is 3.114. That is, this coefficient is determined by comprehensively considering the chemical composition of the fuel, combustion efficiency and other factors. Through this conversion coefficient, the fuel consumption can be converted into the corresponding carbon emissions.

[0068] Among them, after clarifying that the target to be optimized is the CO2 emission optimization problem, that is, the main goal is to minimize CO2 emissions, the constructed CO2 emission optimization model is solved by the NSGA-III optimization algorithm to obtain the optimal solution of the optimization model, that is, the optimization solution corresponding to the lowest CO2 emission of the alternative fuel sail-assisted hybrid ship, so as to provide a basis for decision-making and assist users to build a specific CO2 emission optimization control plan according to specific application scenarios. The specific steps include:

[0069] S1. Initializing and encoding the parameters to be optimized; wherein the parameters to be optimized are optimization parameters such as sail angle of attack, speed, alternative fuel mixture ratio, fuel injection pressure, fuel injection timing, etc., and converting the parameters to be optimized into a format that can be processed by the NSGA-III optimization algorithm by encoding, usually a binary string or other types of encoding forms;

[0070] S2. Randomly generate the initial population P based on the encoded parameters to be optimizedt , where each individual represents a possible operating configuration of the alternative fuel sail-assisted hybrid ship. These possible operating configurations specifically correspond to the parameters to be optimized in the CO2 emission optimization model, such as sail attack angle, ship speed, alternative fuel mixture ratio, fuel injection pressure, fuel injection timing and other optimization parameters corresponding to each data combination form, where the individual fitness is the CO2 emission of the alternative fuel sail-assisted hybrid ship, and its specific individual fitness value is obtained through the optimization objective function of the CO2 emission optimization model;

[0071] S3, based on individual fitness, the initial population P t Perform non-dominant treatment and generate offspring population Q t , that is, for the initial population P t The individuals in the non-dominated sorting are sorted, the CO2 emission fitness values ​​corresponding to the individuals are sorted from small to large, n individuals corresponding to low CO2 emissions are selected as the next generation individuals, and crossover and mutation operations are performed to obtain the offspring population Q t ;

[0072] S4, the initial population P t and the offspring population Q t Combine to generate a new generation of population R t ;

[0073] S5. Calculate population R t The individual fitness of the new individual is sorted from small to large based on the new individual fitness, and n individuals corresponding to low CO2 emissions are selected as the next generation individuals to form a new parent population P t+1 , and perform crossover and mutation operations to obtain a new offspring population Q t+1 ;

[0074] S6, the population P t+1 With Q t+1 Combine to generate a new population R t+1 , and perform cyclic iterative optimization based on the method of S5 until the preset termination condition is reached and the optimization result is output. The termination condition can be the set number of iterations;

[0075] S7. Transmitting the optimization result to the emission optimization evaluation unit and the CO2 emission optimization control unit to achieve the evaluation and control of the CO2 emission characteristics of the alternative fuel sail-assisted hybrid ship.

[0076] In summary, solving the CO2 emission optimization model through the NSGA-III optimization algorithm can find the optimal solution under complex and changing environmental conditions, help reduce CO2 emissions and improve operational efficiency, and facilitate instant adjustment of ship operation strategies.

[0077] In some specific embodiments, the emission optimization evaluation unit is used to evaluate and analyze the CO2 emission optimization result corresponding to the optimized operation scheme of the alternative fuel sail-assisted hybrid ship based on the optimization result, and output the CO2 emission level of the optimized alternative fuel sail-assisted hybrid ship. The evaluation and analysis method is shown in the following formula:

[0078]

[0079] In the formula, It represents the CO2 emission index of alternative fuel sail-assisted hybrid ship, which is used to analyze the CO2 emission level of alternative fuel sail-assisted hybrid ship; M represents the load of alternative fuel sail-assisted hybrid ship; D represents the sailing distance of alternative fuel sail-assisted hybrid ship.

[0080] In some specific embodiments, a CO2 emission optimization control unit is used to realize the coordinated optimization control of the alternative fuel sail-assisted hybrid ship based on the optimization result, so as to realize the lowest CO2 emission optimization control of the alternative fuel sail-assisted hybrid ship. The control process of the coordinated optimization control includes: realizing the optimization control of the sail attack angle through the sail control system of the alternative fuel sail-assisted hybrid ship, realizing the optimization control of the ship speed through the ship control system, and controlling the mixing ratio of the alternative fuel, the injection pressure of the fuel and the injection timing of the fuel according to the control parameters corresponding to the optimization result through the electronic control system of the alternative fuel engine, so that the alternative fuel sail-assisted hybrid ship can achieve the best emission control effect during the navigation process.

[0081] Among them, the specific implementation steps of the emission optimization control system of alternative fuel sail-assisted hybrid ships are as follows:

[0082] S71. Receive optimization results;

[0083] S72. Based on the optimization result, the sail attack angle is adjusted by the sail control system to ensure that the alternative fuel sail-assisted hybrid ship can provide maximum propulsion force under the current wind direction and wind speed corresponding to the environmental conditions;

[0084] S73. Based on the optimization results, the ship speed is adjusted through the ship control system to achieve efficient navigation of the alternative fuel sail-assisted hybrid ship;

[0085] S74. Based on the optimization results, the mixing ratio of the alternative fuel, the injection pressure of the fuel and the injection timing of the fuel are controlled by the electronic control system of the alternative fuel engine to ensure that the fuel can be burned more completely and reduce carbon emission pollution.

[0086] Through the coordinated optimization control of the above alternative fuel sail-assisted hybrid ship, the CO2 emission reduction effect analysis of the alternative fuel sail-assisted hybrid ship is realized to achieve the best CO2 emission control effect.

[0087] Based on the same inventive concept, the present invention also proposes an emission optimization control method based on the emission optimization control system of the alternative fuel sail-assisted hybrid ship, and the corresponding steps include:

[0088] S81, obtaining, through the data acquisition and analysis unit, ship operation data required by the alternative fuel sail-assisted hybrid ship emission optimization control system in terms of ship emission optimization decision-making and control, including but not limited to sail attack angle, ship speed, fuel mixture ratio, fuel injection pressure, fuel injection timing, wave height, wave direction, wind direction and wind speed data;

[0089] S82, by obtaining the mapping relationship between the ship operation data and the CO2 emission data under different spatiotemporal distribution characteristics, to form a CO2 emission spatiotemporal distribution characteristic mapping table, and then analyze the emission characteristics of the alternative fuel sail-assisted hybrid ship through the CO2 emission spatiotemporal distribution characteristic mapping table, including the CO2 emission characteristics of the alternative fuel sail-assisted hybrid ship under different working conditions, and the CO2 emission spatiotemporal distribution characteristics under different navigation positions and navigation environment conditions;

[0090] S83. Solve the constructed CO2 emission optimization model through the NSGA-III optimization algorithm to obtain the optimization results of the optimal sail attack angle, ship speed, fuel mixture ratio, fuel injection pressure, and fuel injection timing corresponding to the lowest CO2 emission of the alternative fuel sail-assisted hybrid ship, so as to achieve the minimization optimization control of CO2 emission of the alternative fuel sail-assisted hybrid ship;

[0091] S84. Based on the optimization results, the CO2 emission optimization control unit is used to realize coordinated optimization control of key parameters such as the sail attack angle, ship speed, alternative fuel mixture ratio, fuel injection pressure, and fuel injection timing of the alternative fuel sail-assisted hybrid ship, so that the alternative fuel sail-assisted hybrid ship can achieve the best CO2 emission control effect during navigation. At the same time, based on the optimization results, the CO2 emission index of the alternative fuel sail-assisted hybrid ship is calculated, so as to realize the analysis and evaluation of the CO2 emission level of the alternative fuel sail-assisted hybrid ship.

[0092] Based on the same inventive concept, the present invention also proposes a computer-readable storage medium, comprising computer instructions, and when the computer instructions are executed on a computer, the computer executes the method described.

[0093] Implementing the embodiments of the present invention will have the following beneficial effects:

[0094] The present invention solves the difficulty of controlling CO2 emissions of alternative fuel sail-assisted hybrid ships. By optimizing the coordinated optimization control mechanism of wind energy and alternative fuels, the CO2 emission control capability of ships under different working conditions is improved, thereby optimizing ship energy efficiency and CO2 emissions. This technological breakthrough not only helps promote the green transformation of the shipping industry, but also provides new technical support for the low-carbon development of the global shipping industry.

[0095] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. An emission optimization control system for an alternative fuel sail-assisted hybrid ship, comprising: Data collection and analysis unit, emission characteristics analysis unit, emission optimization decision unit, emission optimization evaluation unit and CO2 emission optimization control unit; The data acquisition and analysis unit is used to obtain various types of ship operation data, including but not limited to sail attack angle, ship speed, fuel mixture ratio, fuel injection pressure, fuel injection timing, wave height, wave direction, wind direction and wind speed data; The emission characteristic analysis unit is used to obtain the mapping relationship between the ship operation data and the CO2 emission data under different spatiotemporal distribution characteristics to form a CO2 emission spatiotemporal distribution characteristic mapping table; Among them, the emission optimization decision unit is used to solve the constructed CO2 emission optimization model through the NSGA-III optimization algorithm to obtain the optimization results of the optimal sail attack angle, ship speed, fuel mixture ratio, fuel injection pressure, and fuel injection timing corresponding to the lowest CO2 emission of the alternative fuel sail-assisted hybrid ship; the CO2 emission optimization model combines the energy consumption of the alternative fuel sail-assisted hybrid ship with the fuel carbon emission conversion coefficient to characterize the mapping relationship between the energy consumption of the alternative fuel sail-assisted hybrid ship and the CO2 emission, and calculates and obtains the CO2 emission optimization result of the alternative fuel sail-assisted hybrid ship; wherein, an emission optimization evaluation unit is used to evaluate and analyze the CO2 emission optimization result corresponding to the optimized operation scheme of the alternative fuel sail-assisted hybrid ship based on the optimization result, and output the CO2 emission level of the optimized alternative fuel sail-assisted hybrid ship; Among them, the CO2 emission optimization control unit is used to achieve coordinated optimization control of the alternative fuel sail-assisted hybrid ship based on the optimization result, so as to achieve the lowest CO2 emission optimization control of the alternative fuel sail-assisted hybrid ship.

2. The emission optimization control system for alternative fuel sail-assisted hybrid ship according to claim 1, characterized in that: The energy consumption of the alternative fuel sail-assisted hybrid ship can be obtained through a pre-built alternative fuel sail-assisted hybrid ship energy consumption model, and the specific calculation formula is as follows: Where q represents the energy consumption per unit distance; R represents the total resistance of the alternative fuel sail-assisted hybrid ship; F T represents the sail thrust; ω represents the wake coefficient; η S Indicates the transmission efficiency of the shaft system; η G It represents the transfer efficiency; η R represents the relative rotation efficiency of the propeller; J represents the propulsion coefficient; K Q represents the torque coefficient; t represents the thrust reduction coefficient; g main Indicates the host energy consumption rate.

3. The emission optimization control system for alternative fuel sail-assisted hybrid ship according to claim 2, characterized in that: The optimization objective function and constraints of the CO2 emission optimization model are as follows: i min ≤θ≤θ max (3) in min ≤v≤v max (4) α min ≤α≤α max (5) P min ≤P≤P max (6) In the formula, represents the CO2 emission of alternative fuel sail-assisted hybrid ship; k represents the fuel carbon emission conversion coefficient; θ represents the sail attack angle; v represents the ship speed; α represents the fuel mixing ratio; P represents the injection pressure; represents the injection timing, and equation (3) defines the sail angle constraint, θ min and θ max represent the minimum sail angle of attack and the maximum sail angle of attack respectively; Formula (4) defines the speed constraint of alternative fuel sail-assisted hybrid ship, v min and v max They represent the minimum speed and maximum speed of the alternative fuel sail-assisted hybrid ship respectively; Formula (5) defines the fuel mixture ratio constraint, α min and α max They represent the minimum fuel mixture ratio and the maximum fuel mixture ratio of the alternative fuel sail-assisted hybrid ship respectively; Formula (6) defines the fuel injection pressure constraint condition, P min and P max They represent the minimum fuel injection pressure and the maximum fuel injection pressure respectively; Formula (7) defines the fuel injection timing constraint condition, and Represent the minimum and maximum fuel injection timing respectively.

4. The emission optimization control system for alternative fuel sail-assisted hybrid ship according to claim 1, characterized in that: The steps of solving the constructed CO2 emission optimization model by NSGA-III optimization algorithm include: S1. Initializing and encoding the parameters to be optimized; wherein the parameters to be optimized are the sail attack angle, the ship speed, the alternative fuel mixture ratio, the fuel injection pressure, and the fuel injection timing parameters; S2. Randomly generate the initial population P based on the encoded parameters to be optimized t , wherein each individual represents a possible operation configuration of the alternative fuel sail-assisted hybrid ship; the possible operation configuration specifically corresponds to each data combination form corresponding to the parameter to be optimized, wherein the individual fitness is the CO2 emission of the alternative fuel sail-assisted hybrid ship, and the specific individual fitness value can be obtained through the optimization objective function of the CO2 emission optimization model; S3, based on individual fitness, the initial population P t Perform non-dominant treatment and generate offspring population Q t , that is, for the initial population P t The individuals in the non-dominated sorting are sorted, the CO2 emission fitness values ​​corresponding to the individuals are sorted from small to large, n individuals corresponding to low CO2 emissions are selected as the next generation individuals, and crossover and mutation operations are performed to obtain the offspring population Q t ; S4, the initial population P t With the offspring population Q t Combine to generate a new generation of population R t ; S5. Calculate population R t The individual fitness of the new individual is sorted from small to large based on the new individual fitness, and n individuals corresponding to low CO2 emissions are selected as the next generation individuals to form a new parent population P t+1 , and perform crossover and mutation operations to obtain a new offspring population Q t+1 ; S6, the population P t+1 With Q t+1 Combine to generate a new population R t+1 , and perform cyclic iterative optimization based on the method of S5 until the preset termination condition is reached and the optimization result is output. The termination condition can be the set number of iterations; S7, transmitting the optimization result to the emission optimization evaluation unit and the CO2 emission optimization control unit, so as to realize the evaluation and control of the CO2 emission of the alternative fuel sail-assisted hybrid ship.

5. The emission optimization control system for alternative fuel sail-assisted hybrid ship according to claim 1, characterized in that: The formula for the CO2 emission level of an alternative fuel sail-assisted hybrid vessel calculated by the Emission Optimization Assessment Unit is: In the formula, I CO2 It represents the CO2 emission index of alternative fuel sail-assisted hybrid ship, which is used to analyze the CO2 emission level of alternative fuel sail-assisted hybrid ship; M represents the load of alternative fuel sail-assisted hybrid ship; D represents the sailing distance of alternative fuel sail-assisted hybrid ship.

6. The emission optimization control system for alternative fuel sail-assisted hybrid ship according to claim 1, characterized in that: The control process of the collaborative optimization control includes: optimizing the control of the sail attack angle through the sail control system of the alternative fuel sail-assisted hybrid ship, optimizing the ship speed through the ship control system, and controlling the mixing ratio of the alternative fuel, the injection pressure of the fuel and the injection timing of the fuel according to the control parameters corresponding to the optimization results through the alternative fuel engine electronic control system, so that the alternative fuel sail-assisted hybrid ship can achieve the best CO2 emission control effect during navigation.

7. An emission optimization control method based on the emission optimization control system of the alternative fuel sail-assisted hybrid ship as claimed in claim 1, characterized in that: The corresponding steps include: S81, acquiring various types of ship operation data through the data acquisition and analysis unit; S82, by acquiring the mapping relationship between the ship operation data and the CO2 emission data under different spatiotemporal distribution characteristics, to form a CO2 emission spatiotemporal distribution characteristic mapping table; S83. Solve the constructed CO2 emission optimization model through the NSGA-III optimization algorithm to obtain the optimization results of the optimal sail attack angle, ship speed, fuel mixture ratio, fuel injection pressure, and fuel injection timing corresponding to the lowest CO2 emission of the alternative fuel sail-assisted hybrid ship, so as to achieve the minimization optimization control of CO2 emission of the alternative fuel sail-assisted hybrid ship; S84. Based on the optimization results, the coordinated optimization control of key parameters such as the sail attack angle, ship speed, alternative fuel mixture ratio, fuel injection pressure, and fuel injection timing of the alternative fuel sail-assisted hybrid ship is achieved through the optimization decision control unit, so that the alternative fuel sail-assisted hybrid ship can achieve the best CO2 emission control effect during navigation; at the same time, based on the optimization results, the CO2 emission index of the alternative fuel sail-assisted hybrid ship is calculated, so as to achieve the analysis and evaluation of the CO2 emission level of the alternative fuel sail-assisted hybrid ship.

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