Intelligent energy management system of hybrid power tug

Abstract

The invention belongs to the technical field of tugs, and provides an intelligent energy management system of a hybrid power tug, comprising: a sensor for collecting energy consumption and generation conditions of the tug, including measuring battery voltage, current and temperature, and measuring ship speed, acceleration and direction; the data acquisition module is used for transmitting the data collected by the sensor to the processing unit in a digital form and has data synchronization and timestamp functions; the processing unit is used for automatically selecting an optimal operation mode according to the collected data and a preset algorithm; by integrating a plurality of sensors, the energy consumption and generation conditions of the tug can be monitored in real time, including key parameters such as battery voltage, current and temperature and speed and direction of a ship, the data are analyzed through a data processing algorithm, the algorithm adopts an advanced mathematical model and a machine learning technology, and the energy demand can be accurately calculated. And an energy distribution strategy is dynamically adjusted according to actual operation requirements.

Description

Technical Field

[0001] The invention belongs to the technical field of tugboats, and in particular to an intelligent energy management system for a hybrid power tugboat. Background Art

[0002] With the increasing global attention to environmental protection and sustainable development, hybrid tugboats are valued in modern port operations for their ability to reduce fossil fuel consumption and lower greenhouse gas emissions. As an important tool to reduce port pollution and improve energy efficiency, the development and application of hybrid tugboats have received widespread attention.

[0003] However, the existing energy management systems have obvious deficiencies in intelligence and automation. These systems usually adopt static control strategies and cannot be flexibly adjusted according to actual operating conditions and energy conditions. When the tugboat is assisting in berthing operations, the system sometimes cannot respond to the sudden increase in power demand in time, resulting in reduced operating efficiency; in the port firefighting mode, the system sometimes cannot accurately coordinate the operation of the main diesel engine and the propulsion motor, affecting the precise positioning and operating efficiency of the fire cannon.

[0004] The root of these problems is that the energy management system lacks the ability to monitor and analyze data on the tugboat's operating status in real time. Since it cannot accurately predict changes in energy demand and operating modes, the system often cannot optimize energy distribution at the right time. The system fails to fully utilize electric propulsion when the battery is fully charged, or fails to start the diesel engine in time when a quick response is required. This lag in energy management not only limits the performance of the tugboat, but also easily leads to energy waste and additional environmental pollution.

[0005] To this end, those skilled in the art have proposed an intelligent energy management system for a hybrid tugboat to solve the problems raised by the background technology. Summary of the invention

[0006] In order to solve the above technical problems, the present invention provides an intelligent energy management system for a hybrid tugboat to solve the problems existing in the intelligence and automation of the energy management system of a hybrid tugboat in the prior art, which not only affects the performance and operating efficiency of the tugboat, but also increases the operating costs and environmental risks.

[0007] An intelligent energy management system for a hybrid tugboat includes, sensors for collecting information about the tugboat's energy consumption and generation, including measuring battery voltage, current, temperature, and measuring vessel speed, acceleration, and direction;

[0008] The data acquisition module is used to transmit the data collected by the sensor to the processing unit in digital form and has data synchronization and time stamping functions;

[0009] A processing unit, which is used to automatically select the best operation mode based on the collected data and preset algorithms, including pure electric navigation, berthing assistance, in-harbor firefighting and berthing charging modes;

[0010] A control interface for adjusting the energy distribution and operation mode of the tugboat in real time according to the decision of the processing unit, including adjusting the power output of the motor and the operation status of the diesel engine;

[0011] A user interface that displays current energy status, operating modes, and optimization recommendations, and provides historical energy usage reports and forecasted energy savings;

[0012] The remote monitoring and maintenance module is used to realize remote monitoring and maintenance of tugboats, including remote fault diagnosis, system updates and performance monitoring.

[0013] Preferably, the processing unit calculates energy demand and optimization strategy using the following formula:

[0014] E total =E electric +E diesel , where E total is the total energy demand, E electric is the power demand, calculated based on the remaining battery power and expected operation time, E diesel is the diesel demand, calculated based on the efficiency of the diesel engine and the expected operating load.

[0015] Preferably, the processing unit also uses the following formula to calculate the battery charging strategy:

[0016] Among them, G required is the required charge, E electric is the power demand, E generated is the electricity generated by the renewable energy system, calculated based on the deceleration and braking operations of the tugboat, E stored It is the amount of electricity stored in a battery, calculated based on the battery's current state and capacity.

[0017] Preferably, the processing unit also includes a prediction algorithm for predicting future energy demand and operation mode, wherein the prediction algorithm is based on historical data and machine learning models and can be dynamically adjusted according to weather conditions, operation plan and ship status.

[0018] Preferably, the control interface also includes a feedback mechanism for adjusting the energy allocation strategy according to real-time data, wherein the feedback mechanism includes an adaptive control algorithm for automatically adjusting operating parameters according to energy consumption, operating efficiency and environmental changes.

[0019] Preferably, the user interface includes a touch screen for displaying real-time data and receiving user input, wherein the user interface also provides historical energy usage reports and predicted energy savings, and can intuitively display energy flow and efficiency through graphics and charts.

[0020] Preferably, the remote monitoring and maintenance module includes a cloud server for storing data and performing maintenance tasks, wherein the cloud server also provides data analysis and fault prediction services and is capable of sharing data with an external maintenance team through a security protocol.

[0021] Preferably, the sensors include voltage sensors, current sensors, temperature sensors and position sensors, wherein the sensor data are used to monitor the operating status and environmental conditions of the tugboat in real time, and have self-diagnosis and calibration functions.

[0022] Preferably, the data acquisition module also includes a filter for reducing noise and improving data quality, wherein the filter adopts a Kalman filter algorithm and can automatically adjust filter parameters according to data characteristics and environmental changes.

[0023] Preferably, the remote monitoring and maintenance module further comprises a mobile application for monitoring the status of the tugboat on a mobile device, wherein the mobile application provides real-time notification and remote control functions and can be securely accessed through user authentication and authorization.

[0024] Compared with the prior art, the present invention has the following beneficial effects:

[0025] 1. The present invention integrates multiple sensors to monitor the energy consumption and generation of the tugboat in real time, including key parameters such as battery voltage, current, temperature, and the speed and direction of the ship. These data are analyzed by a data processing algorithm. The algorithm uses advanced mathematical models and machine learning techniques to accurately calculate energy demand and dynamically adjust the energy allocation strategy according to actual operational needs. For example, the system can respond to the increase in power demand in a timely manner when the tugboat is performing berthing assistance operations, or accurately coordinate the operation of the main diesel engine and the propulsion motor in the port fire-fighting mode, thereby improving the adaptability to different operating modes.

[0026] 2. The present invention adjusts the energy distribution and operation mode of the tugboat in real time according to the decision of the processing unit through the control interface, ensuring that energy can be used most effectively under various operating conditions. The user interface provides intuitive data display and operation, allowing operators to easily monitor the energy status and operate according to the system's optimization suggestions. In addition, remote monitoring and maintenance of the system are achieved through cloud servers and mobile applications, allowing the maintenance team to access the tugboat's status information in real time and perform fault prediction and performance optimization in a timely manner.

[0027] 3. The present invention significantly reduces operating costs by improving energy utilization efficiency, while also reducing environmental pollution caused by energy waste. In addition, the high adaptability and reliability of the system improve operational safety and reduce the risk of accidents caused by untimely system response or improper energy allocation. The addition of remote monitoring and maintenance functions further reduces maintenance costs and reduces downtime caused by failures, thereby improving the availability and operational efficiency of the tugboat. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 A system diagram of an intelligent energy management system for a hybrid tugboat. DETAILED DESCRIPTION

[0029] The following embodiments of the present invention are described in further detail in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0030] Embodiment 1

[0031] As attached Figure 1 As shown, the present invention provides an intelligent energy management system for a hybrid tugboat, which realizes comprehensive monitoring and intelligent management of the tugboat's energy consumption through a series of highly integrated components, thereby optimizing the use of energy and improving the flexibility and safety of operations, including sensors for collecting the energy consumption and generation of the tugboat. The sensors are the data collection front end of the system. They are carefully arranged at key locations on the tugboat to monitor various energy parameters in real time, including measuring battery voltage, current, temperature, measuring ship speed, acceleration and direction;

[0032] Voltage sensors and current sensors are installed at the output of the battery pack to accurately measure the charge and discharge status of the battery, providing the system with direct data on the battery health status. Temperature sensors monitor the operating temperature of the battery and motor to ensure that the system operates within a safe temperature range. Position sensors are installed near the ship's navigation system to provide the system with dynamic information about the ship, which is essential for accurate energy management in a complex port environment.

[0033] The data acquisition module is used to transmit the data collected by the sensor to the processing unit in a digital form. It has data synchronization and time stamp functions to ensure the accuracy and traceability of the data. It can process high-frequency data streams by adopting advanced analog-to-digital conversion technology. At the same time, it reduces noise interference and improves data quality through built-in filters. The data acquisition module also has a fault detection function, which can identify and report any abnormal conditions during data transmission, thereby ensuring the stable operation of the system;

[0034] The processing unit is used to automatically select the best operating mode based on the collected data and preset algorithms, including pure electric navigation, berthing assistance, in-port firefighting and berthing charging modes. The processing unit is the brain of the system. It uses a high-performance microprocessor and advanced algorithms to quickly process large amounts of data and make intelligent decisions. These algorithms include but are not limited to machine learning, pattern recognition and predictive analysis, which enable the processing unit to automatically select the best operating mode based on real-time data and historical trends;

[0035] The control interface is used to adjust the energy distribution and operation mode of the tugboat in real time according to the decision of the processing unit, including adjusting the power output of the motor and the operation status of the diesel engine; the control interface is a bridge connecting the processing unit and the mechanical system of the tugboat. It adjusts the energy distribution and operation mode in real time according to the decision of the processing unit. The control interface adopts a high-speed communication protocol and can quickly respond to the instructions of the processing unit to adjust the power output of the motor and the operation status of the diesel engine;

[0036] The user interface is used to display the current energy status, operating mode and optimization suggestions, and provide historical energy usage reports and predicted energy savings. The user interface is the window for operators to interact with the system. It provides an intuitive graphical interface that displays the current energy status, operating mode and optimization suggestions. Operators can quickly access various system functions through the touch screen, including adjusting the operating mode, viewing historical energy usage reports and predicting energy savings.

[0037] The remote monitoring and maintenance module is used to achieve remote monitoring and maintenance of tugboats, including remote fault diagnosis, system updates and performance monitoring. The remote monitoring and maintenance module enables the maintenance team to monitor the status of the tugboat in real time from any location, and perform remote fault diagnosis and system updates. The remote monitoring and maintenance module is built on a cloud server, which can store a large amount of operating data and provide data analysis tools to help the maintenance team identify performance bottlenecks and potential failure points. Through mobile applications, the maintenance team can receive system status updates and fault alerts anytime and anywhere, so as to respond quickly and take maintenance measures.

[0038] Embodiment 2:

[0039] As attached Figure 1 As shown, this embodiment is basically the same as the previous embodiment, except that the processing unit uses the following formulas to calculate the energy demand and optimization strategy. These algorithms combine multiple factors such as the remaining battery power, expected operation time, diesel engine efficiency and expected operation load to determine the optimal energy allocation plan:

[0040] E total =E electric +E diesel , where E totalis the total energy demand, E electric is the power demand, calculated based on the remaining battery power and expected operation time, E diesel The diesel demand is calculated based on the efficiency of the diesel engine and the expected operating load, so that the processing unit can accurately calculate the total energy required under a specific operating mode, ensuring the rational allocation of energy, avoiding energy waste, and improving operating efficiency.

[0041] Specifically, the processing unit also calculates the battery charging strategy using the following formula to calculate the required charging amount:

[0042] Among them, G required is the required charge, E electric is the power demand, E generated is the electricity generated by the renewable energy system, calculated based on the deceleration and braking operations of the tugboat, E stored It is the electricity stored in the battery, calculated based on the current state and capacity of the battery. Through this formula, the battery charging strategy can be intelligently adjusted according to the actual power demand and the amount of renewable energy generated to ensure that the battery can provide sufficient power support when necessary. This optimized charging strategy not only improves the battery life, but also reduces dependence on external energy.

[0043] Furthermore, the processing unit also includes a prediction algorithm for predicting future energy demand and operation mode, wherein the prediction algorithm is based on historical data and machine learning models, and can be dynamically adjusted according to weather conditions, operation plans and ship status. When strong winds are predicted, the energy allocation strategy can be adjusted in advance to adapt to the possible increase in energy demand. This prediction capability enables the system to better adapt to environmental changes and improves the flexibility and safety of operations.

[0044] The present invention significantly improves energy utilization efficiency through precise energy demand calculation and optimized battery charging strategy. This efficient energy management method not only reduces operating costs, but also reduces environmental pollution. The application of prediction algorithms further improves the adaptability and safety of the system, enabling the tugboat to operate stably under various environmental conditions. The system's remote monitoring and maintenance functions also greatly reduce maintenance costs and downtime, thereby improving the availability and operating efficiency of the tugboat.

[0045] Embodiment three:

[0046] As attached Figure 1As shown, this embodiment is basically the same as the previous embodiment, except that the control interface also includes a feedback mechanism for adjusting the energy allocation strategy according to real-time data, wherein the feedback mechanism includes an adaptive control algorithm, which automatically adjusts the operating parameters according to energy consumption, operating efficiency and environmental changes. The algorithm can monitor energy consumption, operating efficiency and environmental changes in real time, and automatically adjust the operating parameters to optimize the energy allocation strategy. When a sudden increase in energy consumption is detected, the algorithm can quickly adjust the power output of the motor to reduce unnecessary energy waste. When the operating efficiency decreases, the algorithm can reallocate energy to improve the operating efficiency.

[0047] Specifically, the user interface includes a touch screen for displaying real-time data and receiving user input, wherein the user interface also provides historical energy usage reports and predicted energy savings, and can intuitively display energy flow and efficiency through graphics and charts. Through graphics and charts, users can intuitively understand energy flow and efficiency, so as to make more informed decisions. This enhanced function of the user interface enables operators to more conveniently monitor and manage the energy usage of the tugboat, improving the ease of use of the system and the accuracy of operation.

[0048] Furthermore, the remote monitoring and maintenance module includes a cloud server for storing data and performing maintenance tasks, wherein the cloud server also provides data analysis and fault prediction services, and is able to share data with external maintenance teams through security protocols. By analyzing the stored data, the cloud server can identify potential failure modes and performance bottlenecks, and perform maintenance in advance, thereby reducing the risk of unexpected downtime.

[0049] Furthermore, the sensors include voltage sensors, current sensors, temperature sensors and position sensors, wherein the sensor data is used to monitor the operating status and environmental conditions of the tugboat in real time, and has self-diagnosis and calibration functions. The sensors can automatically detect and correct measurement errors to ensure the accuracy of the data.

[0050] Furthermore, the data acquisition module also includes a filter for reducing noise and improving data quality, wherein the filter adopts a Kalman filtering algorithm and can automatically adjust filtering parameters according to the characteristics of the data and environmental changes. The filter adopts a Kalman filtering algorithm, which can reduce noise and improve data quality. The Kalman filtering algorithm can automatically adjust filtering parameters to adapt to the characteristics of the data and environmental changes, thereby providing more accurate and reliable data, enabling the system to more accurately analyze and predict energy demand, thereby improving the accuracy of energy management.

[0051] Furthermore, the remote monitoring and maintenance module also includes a mobile application for monitoring the status of the tugboat on a mobile device, wherein the mobile application provides real-time notification and remote control functions, so that the user can monitor the operating status of the tugboat at any location and at any time, and remotely control it when necessary, and can be securely accessed through user authentication and authorization.

[0052] The algorithm works closely with other components of the system to achieve efficient energy management. Sensors provide real-time data, the data acquisition module ensures data accuracy and synchronization, and the control interface adjusts energy distribution in real time according to the decisions of the processing unit. The user interface provides an intuitive platform for operators to monitor energy status and system performance, while also receiving system optimization suggestions and forecasting information. The remote monitoring and maintenance module enables the maintenance team to monitor the system status in real time and perform remote fault diagnosis and performance optimization.

[0053] The embodiments of the present invention are provided for the purpose of illustration and description. Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations of the present invention. Ordinary technicians in this field can change, modify, replace and deform the above embodiments within the scope of the present invention.

[0054] In the present invention, unless otherwise clearly specified and limited, a first feature being "above" or "below" a second feature may mean that the first and second features are in direct contact, or the first and second features are in indirect contact through an intermediate medium. Moreover, a first feature being "above", "above" or "above" a second feature may mean that the first feature is directly above or obliquely above the second feature, or simply means that the first feature is higher in level than the second feature. A first feature being "below", "below" or "below" a second feature may mean that the first feature is directly below or obliquely below the second feature, or simply means that the first feature is lower in level than the second feature.

[0055] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "examples", "specific examples" or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine different embodiments or examples described in this specification and the features of different embodiments or examples, unless they are contradictory.

[0056] In the drawings of the embodiments disclosed in the present invention, only the structures involved in the embodiments disclosed in the present invention are involved, and other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of the present invention can be combined with each other.

Claims

1. An intelligent energy management system for a hybrid tugboat, characterized in that: include, Sensors to collect information about the tugboat’s energy consumption and generation, including measuring battery voltage, current, temperature, and measuring vessel speed, acceleration, and direction; The data acquisition module is used to transmit the data collected by the sensor to the processing unit in digital form and has data synchronization and time stamping functions; A processing unit, which is used to automatically select the best operation mode based on the collected data and preset algorithms, including pure electric navigation, berthing assistance, in-harbor firefighting and berthing charging modes; A control interface for adjusting the energy distribution and operation mode of the tugboat in real time according to the decision of the processing unit, including adjusting the power output of the motor and the operation status of the diesel engine; A user interface that displays current energy status, operating modes, and optimization recommendations, and provides historical energy usage reports and forecasted energy savings; The remote monitoring and maintenance module is used to realize remote monitoring and maintenance of tugboats, including remote fault diagnosis, system updates and performance monitoring.

2. The intelligent energy management system for a hybrid tugboat as claimed in claim 1, characterized in that: The processing unit calculates energy demand and optimization strategy using the following formula: E total =E electric +E diesel , where E total is the total energy demand, E electric is the power demand, calculated based on the remaining battery power and expected operation time, E diesel is the diesel demand, calculated based on the efficiency of the diesel engine and the expected operating load.

3. The intelligent energy management system for a hybrid tugboat as claimed in claim 2, characterized in that: The processing unit also calculates the battery charging strategy using the following formula: Among them, G required is the required charge, E electric is the power demand, E generated is the electricity generated by the renewable energy system, calculated based on the deceleration and braking operations of the tugboat, E stored It is the amount of electricity stored in a battery, calculated based on the battery's current state and capacity.

4. The intelligent energy management system for a hybrid tugboat as claimed in claim 3, characterized in that: The processing unit also includes a prediction algorithm for predicting future energy demand and operation patterns, wherein the prediction algorithm is based on historical data and machine learning models and can be dynamically adjusted according to weather conditions, operation plans and ship status.

5. The intelligent energy management system for a hybrid tugboat as claimed in claim 4, characterized in that: The control interface also includes a feedback mechanism for adjusting the energy allocation strategy based on real-time data, wherein the feedback mechanism includes an adaptive control algorithm that automatically adjusts operating parameters based on energy consumption, operating efficiency and environmental changes.

6. The intelligent energy management system for a hybrid tugboat as claimed in claim 5, characterized in that: The user interface includes a touch screen for displaying real-time data and receiving user input, wherein the user interface also provides historical energy usage reports and predicted energy savings, and can intuitively display energy flow and efficiency through graphs and charts.

7. The intelligent energy management system for a hybrid tugboat as claimed in claim 6, characterized in that: The remote monitoring and maintenance module includes a cloud server for storing data and performing maintenance tasks, wherein the cloud server also provides data analysis and fault prediction services and is capable of sharing data with external maintenance teams through secure protocols.

8. The intelligent energy management system for a hybrid tugboat as claimed in claim 7, characterized in that: The sensors include voltage sensors, current sensors, temperature sensors and position sensors, wherein the sensor data are used to monitor the operating status and environmental conditions of the tugboat in real time, and have self-diagnosis and calibration functions.

9. An intelligent energy management system for a hybrid tugboat as claimed in claim 8, characterized in that: The data acquisition module also includes a filter for reducing noise and improving data quality, wherein the filter adopts a Kalman filter algorithm and can automatically adjust filter parameters according to data characteristics and environmental changes.

10. The intelligent energy management system for a hybrid tugboat as claimed in claim 9, characterized in that: The remote monitoring and maintenance module also includes a mobile application for monitoring the status of the tugboat on a mobile device, wherein the mobile application provides real-time notification and remote control functions and can be securely accessed through user authentication and authorization.

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