A ship rotating cylinder wind sail control system and an optimal control method thereof

Abstract

The application discloses a ship rotating cylinder wind sail control system and an optimal control method thereof. A main controller, a network switch and a serial communication module are installed in the control box. The serial communication module receives wind speed and wind direction real-time information detected by a wind speed / wind direction sensor and ship posture information detected by a gyroscope. Meanwhile, the serial communication module receives ship navigation speed information sent by a ship navigation system and sends motor rotating speed and steering information calculated in real time through network communication. A motor driving box receives rotating speed and steering instructions sent by the main control box to drive the motor to rotate. Energy feedback value is fed back to the main power grid in the braking and deceleration process, so that energy recovery is realized. The ship rotating cylinder wind sail control system and the control method have high integration, intelligence and strong robustness. The system can comprehensively process multi-source information, make real-time decisions through an optimization algorithm and has a perfect safety management mechanism, so that oil saving potential of the rotating cylinder wind sail is converted into stable and reliable ship energy saving benefits.

Description

Technical Field

[0001] This invention relates to the field of marine energy conservation technology, and more specifically, to a marine rotary sail control system and its optimized control method. Background Technology

[0002] Currently, facing increasingly stringent regulations on ship energy efficiency and emission reduction, utilizing wind power for assisted propulsion has become an important development direction for green shipping. Among these, rotor sails (also known as rotary sails) generate thrust through the Magnus effect, offering advantages such as high efficiency and a wide range of wind angles, attracting industry attention. However, their energy-saving effect is highly dependent on the performance of the control system. In actual navigation, ships face complex conditions with constantly changing wind speed, wind direction, and ship speed. An excellent control system needs to calculate the optimal rotor speed and steering in real time to maximize thrust or overall energy efficiency while ensuring ship maneuvering safety and equipment operational reliability.

[0003] Among existing related patent technologies, such as the marine rotary sail system based on an energy storage device disclosed in patent document (CN117864366A), a system framework including wind turbine, power, energy storage, data acquisition, and analysis units is included. However, its core "analysis unit" control logic is too crude and rigid. It fails to consider the nonlinear characteristics of the Magnus effect: the thrust of the rotary sail depends on the ratio of the linear velocity of the rotary surface to the apparent wind speed (the vector synthesis of ship speed and actual wind speed) (i.e., the rotation rate). This patent only uses simple step-by-step adjustments (such as "increasing by 10%, 20%, 30%" or multiplying by fixed coefficients of 1.2, 1.25), completely neglecting to establish a hydrodynamic model based on real-time apparent wind speed and direction. This "blind adjustment" cannot ensure that the rotary sail always operates within the "optimal rotation rate" range of maximum thrust coefficient or highest energy efficiency. The analysis unit of this patent is highly dependent on a single threshold (such as ship speed 25 / 35 / 45 km / h, included angle 45° / 135°). In real-world marine environments, wind speed, wind direction, and ship speed fluctuate frequently. When ship speed or angle fluctuates around threshold points (such as 25 km / h or 45°), the system frequently jumps between different decision logics. This leads to frequent abrupt changes in the power of the rotary drum motor and engine, not only failing to save energy but also exacerbating fatigue wear in the mechanical transmission system and even causing power grid fluctuations. The decision logic in this patent only considers the "wind" factor, completely ignoring key factors that determine ship speed in actual navigation, such as wave drag, ocean currents, and hull fouling. This results in incorrectly increasing engine load or blindly adjusting the rotary drum, which not only fails to solve the problem but may also lead to engine overload shutdown or equipment damage. The system also lacks a real-time estimation model for the ship's hydrodynamic resistance.

[0004] Therefore, there is an urgent need to develop a highly integrated, intelligent, and robust marine rotary sail control system that can comprehensively process multi-source information, make real-time decisions through optimization algorithms, and have a sound safety management mechanism, thereby transforming the fuel-saving potential of rotary sails into stable and reliable energy-saving benefits for actual ships. Summary of the Invention

[0005] The purpose of this invention is to propose a marine rotary sail control system and its optimization control method. This marine rotary sail control system is highly integrated, intelligent, and robust. It can comprehensively process multi-source information, make real-time decisions through optimization algorithms, and has a sound safety management mechanism, thereby transforming the fuel-saving potential of rotary sails into stable and reliable energy-saving benefits for actual ships.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] A ship's rotary sail control system includes a main control box, a motor drive box, a bridge control panel, a wind speed / direction sensor, and a gyroscope. The control box houses a main controller, a network switch, and a serial communication module. The serial communication module receives real-time wind speed and direction information from the wind speed / direction sensor and ship attitude information from the gyroscope. It also receives ship speed information from the ship's navigation system and transmits real-time calculated motor speed and steering information via network communication. The motor drive box receives speed and steering commands from the main control box to drive the motor. During braking and deceleration, it feeds energy back to the main grid, achieving energy recovery.

[0008] Furthermore, the drive unit with AFE function is installed in the motor drive box to form a closed loop with the encoder connected to the tail end of the motor.

[0009] Furthermore, the control panel in the cab is a 21-inch touchscreen display used to show the status of the rotary sail, start / stop operations, and parameter settings in real time.

[0010] Furthermore, the cab control panel is equipped with an emergency stop button to immediately stop operation in an emergency.

[0011] A method for optimizing the control of a ship's rotary sail, based on the aforementioned ship rotary sail control system, comprises the following steps: Step S1, Initialization: Initialize the filter program, wind speed / direction, PID parameters, and motor command signals; Step S2, Data Acquisition and Verification: This includes wind speed / direction information acquisition and verification, and ship attitude information acquisition and verification; Step S3, data filtering: Adopting moving average filtering, the arithmetic mean value of wind speed collected in a recent period of time is used to represent the wind speed value at the current moment to suppress random high-frequency noise; Step S4, wind field data fusion: Realize data verification, fault diagnosis and weighted fusion of dual wind speed / wind direction sensors, with the core objective of providing reliable ambient wind field data for the Flettner rotor sail control system; Step S5, optimal rotation speed calculation: Including two parts of establishing an optimization table and optimization searching. The optimization table is established by fitting CFD simulation combined with model wind tunnel test data to form a data table containing relative wind speed, relative wind direction, current ship speed, optimal rotation speed, and expected efficiency; the optimization searching is based on multi-dimensional parameters including wind speed, wind direction angle, and ship speed, to quickly match the optimal rotor rotation speed and direction from the predefined "optimization table", and improve the accuracy through interpolation.

[0012] Further, in step S2, the wind speed verification range is 0m / s<Wind Speed<90m / s, a wind speed error will be reported if the range is exceeded; the wind direction verification range is 0°<Wind Direction<360°, a wind direction error will be reported if the range is exceeded; for ship speed information collection and verification, the ship speed range is 0kn<Ship Speed<30kn, a ship speed error will be reported if the range is exceeded; for ship attitude information collection and verification, the roll range is -45°<Roll Angle<45°, excessive roll will be reported if the range is exceeded; the pitch range is -30°<Pitch Angle<30°, excessive pitch will be reported if the range is exceeded.

[0013] Further, in step S3, the formula for the arithmetic mean value is:

[0014] Wherein: is the filtered output value is the sliding window size, is the original wind speed value; since wind direction is an angle with discontinuities at 0° and 360°, the unit vector averaging method must be used to convert each wind direction angle to a point on the unit circle ( ), average the coordinates of these points, and then inversely calculate the average angle from the average coordinates through the atan function, the formula of which is: (1) Calculate the average sine and cosine:

[0015]

[0016] In the formula: is the sliding window size,

[0017] (2) Calculate the average wind direction: .

[0018] In the formula: , .

[0019] Furthermore, the specific steps for wind field data fusion in step S4 are as follows: S4.1 Data Acquisition and Preprocessing: Read raw data from two sensors, including wind speed. ,wind direction and hardware status; S4.2 Data rationality judgment: filter and eliminate outliers by measuring range and rate of change: sensor failure, signal jump; S4.3 Consistency check: Calculate the difference between the two sensors to determine whether they are affected by local interference or malfunction. Wind speed difference:

[0020] Wind direction difference: ;

[0021] S4.4 Dynamic weight allocation, basic weight ; S4.5, Vector Weighted Fusion Polar coordinates to rectangular coordinates:

[0022]

[0023]

[0024] Weighted composition:

[0025]

[0026]

[0027]

[0028]

[0029]

[0030] Integrated wind speed:

[0031]

[0032]

[0033]

[0034]

[0035] Integration Trends:

[0036]

[0037]

[0038] S4.6 Output Processing Wind speed clamping:

[0039] Wind direction converges: .

[0040]

[0041] Furthermore, the specific steps for calculating the optimal speed in step S5 are as follows: S5.1 Parameter Input: Combined wind speed ,wind direction speed of the boat And load the optimization table, which contains the optimal speed under each operating condition. Efficiency η; S5.2 Weighted Distance Search: Calculate the weighted Euclidean distance between the current parameter and each record in the table, find the index corresponding to the minimum distance, and the best matching point; Weighted Euclidean distance, used to quantify the current parameter wind speed. ,wind direction speed of the boat With the table The smaller the distance between the records, the more similar they are.

[0042] In the formula:

[0043]

[0044] S5.3, Nearest Neighbor Matching Rule: Traverse the entire table to find the minimum distance. and its index ;

[0045] Divisor condition: Otherwise, it is considered an invalid match; S5.4, Inverse distance weighted difference, if For values ​​not at the end of the table and requiring interpolation, take neighboring points as the center and calculate the rotational speed by weighting the values ​​by the inverse of the distance. Neighboring point domain:

[0046] Perform interpolation:

[0047] In the formula:

[0048]

[0049] ; S5.5 Output Judgment Logic Match successful: .

[0050] Compared with the prior art, the present invention has the following significant advantages: This invention employs a highly integrated, intelligent, and robust marine rotary sail control system that can comprehensively process multi-source information, make real-time decisions through optimization algorithms, and possess a robust safety management mechanism, thereby transforming the fuel-saving potential of rotary sails into stable and reliable energy-saving benefits for actual ships. Attached Figure Description

[0051] Figure 1 This is a schematic diagram of the control system of the present invention; Figure 2 This is a block diagram of the optimized control method of the present invention. Detailed Implementation

[0052] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments.

[0053] like Figure 1 As shown in the figure, the ship's rotary sail control system provided in this embodiment of the invention mainly includes one main control box, one motor drive box, one bridge control panel, two wind speed / direction sensors, and one gyroscope.

[0054] The control box is the core of the rotary sail control system. It contains a high-performance main controller, a network switch, and a serial communication module. The serial communication module receives real-time wind speed and direction information from wind speed / direction sensors, ship attitude information from gyroscopes, and ship speed information from the ship navigation system. It also sends real-time calculated motor speed and steering information via network communication.

[0055] A drive unit with AFE function is installed in the motor drive box to form a closed loop with the encoder connected to the tail end of the motor, and at the same time receives the rotation speed and rotation direction commands sent by the main control box to drive the motor to rotate. During braking and deceleration processes, energy can be fed back to the main power grid to realize energy recovery.

[0056] The cab operation panel is a 21-inch display with touch function, which is mainly used for real-time display of the status of the rotor sail, start / stop operation, parameter setting, etc., and is equipped with an emergency stop button that can immediately stop the operation in case of emergency.

[0057] As Figure 2 shown, the processing flow of the control method of the present invention includes: S1, initialization, S2, data acquisition and verification, S3, data filtering, S4, wind field data fusion, S5, optimal rotation speed calculation.

[0058] Step S1, initialization mainly includes initialization of the filtering program, wind speed / wind direction initialization, PID parameter initialization, and motor command signal initialization.

[0059] Step S2, data acquisition and verification mainly includes wind speed / wind direction information acquisition and verification, the wind speed verification range is 0m / s<Wind Speed<90m / s, if it exceeds the range, a wind speed error is reported, the wind direction verification range is 0°<Wind Direction<360°, if it exceeds the range, a wind direction error is reported; ship speed information acquisition and verification, the ship speed range is 0kn<Ship Speed<30kn, if it exceeds the range, a ship speed error is reported; ship attitude information acquisition and verification, the roll angle range is -45°<Roll Angle<45°, if it exceeds the range, an excessive roll error is reported; the pitch angle range is -30°<Pitch Angle<30°, if it exceeds the range, an excessive pitch error is reported.

[0060] Step S3, data filtering adopts moving average filtering. For wind speed, its core idea is to use the arithmetic average value collected in a recent period of time to represent the wind speed value at the current moment, so as to suppress random high-frequency noise. The formula is:

[0061] Wherein: ---Filtered output value ---Sliding window size ---Original wind speed value Wind direction is an angle, and there are discontinuity points at 0° and 360°, so arithmetic average cannot be performed directly. The unit vector averaging method must be used. The core is to convert each wind direction angle Convert to a point on the unit circle ( The coordinates of these points are averaged, and then the average angle is calculated from the average coordinates using the atan function. The formula is as follows: 1. Calculate the mean sine and cosine:

[0062]

[0063] In the formula: To adjust the sliding window size,

[0064] 2. Calculate the average wind direction: .

[0065] In the formula: , .

[0066] Step S4: Wind field data fusion enables data verification, fault diagnosis, and weighted fusion of dual wind speed / direction sensors. The core objective is to provide reliable environmental wind field data for the rotary sail control system.

[0067] S4.1 Data Acquisition and Preprocessing: Read raw data from two sensors (wind speed) ,wind direction (and hardware status).

[0068] S4.2 Data rationality judgment: filter and eliminate outliers (such as sensor failure, signal jump) by measuring range and rate of change.

[0069] S4.3 Consistency check: Calculate the difference between the two sensors to determine whether there is local interference or malfunction.

[0070] Wind speed difference:

[0071] Wind direction difference:

[0072]

[0073] S4.4 Dynamic Weight Allocation, Base Weight

[0074]

[0075] S4.5 Vector Weighted Fusion Polar coordinates to rectangular coordinates:

[0076]

[0077]

[0078] Weighted composition:

[0079]

[0080]

[0081]

[0082]

[0083]

[0084] Integrated wind speed:

[0085]

[0086]

[0087]

[0088]

[0089] Integration Trends:

[0090]

[0091]

[0092] S4.6 Output Processing Wind speed clamping:

[0093] Wind direction converges: .

[0094]

[0095] Step S5, Optimal Speed ​​Calculation, includes two parts: establishing an optimization table and optimization search. The optimization table is a data table that is created by fitting CFD simulation and model wind tunnel test data, and includes relative wind speed, relative wind direction, current ship speed, optimal rotational speed, and expected efficiency.

[0096] Optimization is based on multi-dimensional parameters (wind speed, wind angle, ship speed) to quickly match the optimal rotor speed and direction from a predefined "OptTable," and improves accuracy through interpolation when necessary. The process is as follows: S5.1 Parameter Input: Combined wind speed ,wind direction speed of the boat And load the optimization table (containing the optimal speed under each operating condition). Efficiency η. S5.2 Weighted Distance Search: Calculate the weighted Euclidean distance between the current parameter and each record in the table, and find the index (best matching point) corresponding to the minimum distance. Weighted Euclidean distance, used to quantify the current parameter wind speed. ,wind direction speed of the boat With the table The smaller the distance between the records, the more similar they are.

[0097]

[0098] In the formula:

[0099]

[0100] S5.3 Nearest Neighbor Matching Rule: Traverse the entire table and find the minimum distance. and its index .

[0101]

[0102] Divisor condition: Otherwise, it is considered an invalid match.

[0103] S5.4 Inverse distance weighted difference, if For non-end of the table and requiring interpolation, take neighboring points (1 before and 2 after) as the center, and calculate the rotational speed by weighting the reciprocal of the distance.

[0104] Neighboring point domain:

[0105] Perform interpolation:

[0106] In the formula:

[0107]

[0108] ; S5.5 Output Judgment Logic Match successful: .

[0109] The embodiments described above are merely preferred embodiments of the present invention and are not intended to limit the invention. Those skilled in the art can make various changes and modifications without departing from the concept and scope of the present invention. Therefore, all technical solutions obtained by equivalent substitution or equivalent transformation fall within the protection scope of the present invention.

Claims

1. A ship's rotary sail control system, characterized in that: comprising a main control box, a motor drive box, a cab operation panel, a wind speed / wind direction sensor, and a gyroscope. A main controller, a network switch and a serial communication module are installed inside the main control box. The serial communication module receives real-time wind speed and wind direction information detected by the wind speed / wind direction sensor and ship attitude information detected by the gyroscope, and also receives ship speed information sent by the ship navigation system, and sends the real-time calculated motor speed and steering information via network communication; The motor drive box receives the speed and steering instructions sent by the main control box to drive the motor to rotate, and feeds energy back to the main power grid during braking and deceleration processes to realize energy recovery.

2. The ship rotary sail control system according to claim 1, characterized in that: A drive unit with AFE function is installed in the motor drive box to form a closed loop with the encoder connected to the tail end of the motor.

3. The ship rotary sail control system according to claim 1, characterized in that: The cab operation panel is a display with touch function, which is used for real-time display of the state of the rotor sail, start / stop operation and parameter setting.

4. The ship rotary sail control system according to claim 3, characterized in that: The cab operation panel is provided with an emergency stop button to stop the operation immediately in emergency situations.

5. A method for optimizing the control of a ship's rotary sail, based on the ship's rotary sail control system according to any one of claims 1-4, characterized in that, Its steps are as follows: Step S1, Initialization: initialization of filter program, initialization of wind speed / wind direction, initialization of PID parameters, initialization of motor command signal; Step S2, Data acquisition and verification: including wind speed / wind direction information acquisition and verification, ship attitude information acquisition and verification; Step S3, Data filtering: moving average filtering is adopted. For wind speed, the arithmetic mean value collected in a recent period of time is used to represent the wind speed value at the current moment, so as to suppress random high-frequency noise; Step S4, Wind field data fusion: realize data verification, fault diagnosis and weighted fusion of dual wind speed / wind direction sensors, with the core goal of providing reliable ambient wind field data for the rotor sail control system; Step S5, Optimal speed calculation: including two parts of establishing an optimization table and optimization searching. The optimization table is a data table containing relative wind speed, relative wind direction, current ship speed, optimal speed and expected efficiency established by CFD simulation combined with data fitting of model wind tunnel test; the optimization searching is based on multi-dimensional parameters, including wind speed, wind direction angle and ship speed, to quickly match the optimal rotor speed and direction from the predefined "optimization table", and improve the accuracy through interpolation.

6. The method according to claim 5, characterized in that, In step S2, the wind speed verification range is 0m / s<Wind Speed<90m / s, if the range is exceeded, a wind speed error is reported; the wind direction verification range is 0°<Wind Direction<360°, if the range is exceeded, a wind direction error is reported; for ship speed information acquisition and verification, the ship speed range is 0kn<Ship Speed<30kn, if the range is exceeded, a ship speed error is reported; for ship attitude information acquisition and verification, the roll range is -45°<Roll Angle<45°, if the range is exceeded, an excessive roll alarm is reported; the pitch range is -30°<Pitch Angle<30°, if the range is exceeded, an excessive pitch alarm is reported.

7. The method according to claim 5, characterized in that, In step S3, the formula for the arithmetic mean value is: in: The filtered output value To adjust the sliding window size, This is the original wind speed value; since wind direction is an angle, there are discontinuities at 0° and 360°, so a unit vector averaging method must be used to average each wind direction angle. Convert to a point on the unit circle ( The coordinates of these points are averaged, and then the average angle is calculated from the average coordinates using the atan function. The formula is as follows: (1) Calculate the average sine and cosine: In the formula: To adjust the sliding window size, (2) Calculate the average wind direction: 。 In the formula: , .

8. The method according to claim 5, characterized in that, The specific steps of wind field data fusion in step S4 are as follows: S4.1 Data Acquisition and Preprocessing: Read raw data from two sensors, including wind speed. ,wind direction and hardware status; S4.2, Data rationality judgment, screening and eliminating abnormal values through range and change rate: sensor fault, signal jump; S4.3 Consistency check: Calculate the difference between the two sensors to determine whether they are affected by local interference or malfunction. Wind speed difference: Wind direction difference: ; S4.4 Dynamic weight allocation, basic weight ; S4.5, Vector Weighted Fusion Polar coordinates to rectangular coordinates: Weighted composition: Integrated wind speed: Integration Trends: S4.6 Output Processing Wind speed clamping: Wind direction converges: .

9. The method according to claim 5, characterized in that, Step S5, Calculation of Optimal Speed: The specific steps are as follows: S5.1 Parameter Input: Combined wind speed ,wind direction speed of the boat And load the optimization table, which contains the optimal speed under each operating condition. Efficiency η; S5.2 Weighted Distance Search: Calculate the weighted Euclidean distance between the current parameter and each record in the table, find the index corresponding to the minimum distance, and the best matching point; Weighted Euclidean distance, used to quantify the current parameter wind speed. ,wind direction speed of the boat With the table The smaller the distance between the records, the more similar they are. In the formula: S5.3, Nearest Neighbor Matching Rule: Traverse the entire table to find the minimum distance. and its index ; Divisor condition: Otherwise, it is considered an invalid match; S5.4, Inverse distance weighted difference, if For values ​​not at the end of the table and requiring interpolation, take neighboring points as the center and calculate the rotational speed by weighting the values ​​by the inverse of the distance. Neighboring point domain: Perform interpolation: In the formula: ； S5.5 Output Judgment Logic Match successful: .

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