Optimized dispatching system for energy consumption of touch-net electric ship navigation

Abstract

The application provides a touch-net electric ship shipping energy consumption optimization scheduling system and relates to the technical field of electric ship shipping. The application comprises an acquisition module, which is used for planning a navigation path containing a touch-net power supply section and an offline navigation section based on an electronic river map and multi-sensor fusion positioning information according to the starting point and the ending point of a target voyage. A prediction module is used for identifying touch-net power supply continuous sections and obstacle sections requiring offline navigation along the navigation path, and predicting the length and energy consumption demand of each offline navigation section. A construction module is used for establishing a dynamic evaluation area with three fixed navigation buoys in the channel as the vertex when the ship is in the touch-net power supply section according to the predicted offline navigation section energy consumption demand and the current state of charge of the battery pack. The application realizes accurate matching between supply and demand of touch-net power supply and battery energy storage.

Description

Technical Field

[0001] This invention relates to the field of electric ship navigation technology, and in particular to a power consumption optimization and scheduling system for electric ship navigation using a contact wire system. Background Technology

[0002] Driven by the demand for green shipping transformation, the catenary-type trackless electric ship, with its dual-source architecture of overhead catenary as the main power source and battery as the auxiliary redundancy, has solved the problems of serious pollution of traditional fuel ships and insufficient range of pure battery ships. It has been gradually applied to scenarios such as inland waterway passenger transport, but the existing shipping energy consumption scheduling mode still has obvious limitations.

[0003] Taking a certain inland waterway intercity passenger route as an example, the route has many obstacles such as bridges and shoals that require offline navigation. The current system mostly adopts a charging strategy with preset fixed parameters, charging the battery at a fixed power in the power supply section. This cannot dynamically adjust the charging rhythm according to the real-time navigation situation such as the curvature of the waterway and changes in water flow, nor can it accurately match the actual energy consumption demand of each offline section. As a result, the ship either wastes energy due to overcharging or faces the risk of power interruption during offline navigation due to insufficient charging, exposing the technical defects of insufficient adaptability of energy consumption scheduling to actual navigation scenarios. Summary of the Invention

[0004] The technical problem to be solved by this invention is to provide an optimized scheduling system for energy consumption of catenary-powered ships, so as to achieve precise matching of supply and demand between catenary power supply and battery energy storage.

[0005] To solve the above-mentioned technical problems, the technical solution of the present invention is as follows: The first aspect is the energy consumption optimization and scheduling system for electric ships, including: The acquisition module is used to plan a navigation path that includes a power supply segment and an offline navigation segment based on the starting point and ending point of the target voyage and the fusion positioning information of electronic river map and multi-sensor. The prediction module is used to identify the continuous power supply sections and obstacle sections that need to be offline along the route based on the navigation path, and to predict the length and energy consumption requirements of each offline navigation section. The module is used to establish a dynamic evaluation area with three pre-set fixed navigation buoys in the waterway as vertices when the ship is in the catenary power supply section, based on the predicted energy consumption demand of the offline navigation section and the current state of charge of the battery pack. The quantization module is used to extract the boundary curves of the dynamic evaluation area, and obtain curvature analysis results by analyzing the curvature characteristics of the boundary curves. Based on the curvature analysis results, the navigation situation and spatial distribution relationship within the evaluation area are quantitatively analyzed to obtain the corresponding charging strategy optimization parameters. The control module is used to dynamically control the charging process of the battery pack by optimizing the parameters of the charging strategy, so that the battery pack can store enough electrical energy to meet the needs of the segment of navigation and have a safety redundancy before entering the offline navigation segment. The processing module is used to monitor the status of the catenary and the power grid in real time during the ship's navigation. When the power supply is sufficient, it will prioritize driving and charging the catenary via cable. When entering the offline zone or when the power supply is interrupted, it will automatically switch to battery power and adjust the propulsion power in real time according to the remaining range and power, so as to achieve energy consumption optimization scheduling.

[0006] Furthermore, based on the starting and ending points of the target voyage, and using electronic river charts and multi-sensor fusion positioning information, a navigation path is planned that includes a power supply segment and an offline navigation segment, including: It receives the start and end information of the target voyage and simultaneously acquires pre-stored electronic river map data and multi-sensor fusion positioning information reported through the shipborne terminal; Based on electronic river map data, the waterway is analyzed and processed to identify and mark all available catenary power supply sections and known obstacle sections in the waterway, generating waterway feature information containing power supply and obstacle attributes; Based on the waterway feature information, and using the starting point, the ending point, and the real-time positioning reported by the shipboard terminal as spatial constraints, combined with the waterway feature information, the navigation route is initially planned on the electronic river chart to obtain a continuous navigation baseline from the starting point to the ending point. The continuous trajectory traversed by the coherent navigation baseline is matched, segmented, and associated with the power supply section and obstacle section in the channel feature information. Finally, a detailed navigation path consisting of alternating overhead power supply sections and offline navigation sections is planned and output.

[0007] Furthermore, based on the navigation path, continuous power supply sections along the route and obstacle sections requiring offline navigation are identified, and the length and energy consumption requirements of each offline navigation section are predicted, including: Based on the detailed navigation path, the detailed navigation path is parsed and processed to obtain a sequence of navigation segments consisting of alternating power supply segments and offline navigation segments; By analyzing and processing the navigation segment sequence, all continuous power supply segments are identified, and power supply segments that are interrupted by offline navigation segments are logically merged. At the same time, all obstacle segments that need to be offline are identified, resulting in a structured list of continuous power supply segments and a list of obstacle segments. Based on the list of obstacle segments, for each offline navigation obstacle segment in the list, its corresponding navigation trajectory data is called to calculate and predict the navigation length of each obstacle segment. Based on the predicted navigation length of each obstacle section, combined with the preset ship navigation performance parameters and historical energy consumption data, the energy consumption required for the ship to pass through each obstacle section is predicted and calculated, thus obtaining the length and energy consumption requirement of each offline navigation section.

[0008] Furthermore, based on the predicted energy consumption demand for the offline navigation section and the current state of charge of the battery pack, when the ship is in the catenary power supply section, a dynamic evaluation area is established with three pre-set fixed navigation buoys in the channel as vertices, including: The system receives the length and energy consumption requirements of each offline navigation segment and simultaneously obtains the current state of charge of the battery pack reported through the shipboard terminal, thereby obtaining comprehensive input data that includes predicted energy consumption requirements and current battery status. Based on comprehensive input data and detailed navigation path, combined with real-time ship location information, the attributes of the current navigation segment of the ship are judged and processed to determine the specific catenary power supply segment in which the ship is currently located. Based on a specific catenary power supply section, the coordinate information of three pre-set fixed navigation buoys within that specific catenary power supply section is queried and extracted from the pre-stored waterway facility database; Based on the coordinate information of the three fixed navigation buoys extracted, and combined with the real-time position and heading information of the ship, a dynamic polygonal evaluation area covering the current navigation situation is established.

[0009] Furthermore, the boundary curves of the dynamic evaluation area are extracted, and the curvature characteristics of the boundary curves are analyzed to obtain curvature analysis results. Based on the curvature analysis results, the relationship between the navigation status and spatial distribution within the evaluation area is quantitatively analyzed to obtain the corresponding charging strategy optimization parameters, including: Based on the established dynamic polygon evaluation region, the spatial data of the dynamic polygon is geometrically processed to extract and generate the boundary curves of the spatial data of the dynamic polygon. By performing geometric feature analysis on the extracted boundary curves, the curvature values ​​of each point on the boundary curves are calculated and identified, and the curvature feature analysis results describing the boundary morphology changes are obtained. Based on the curvature feature analysis results and combined with the real-time status information of the ship in the dynamic assessment area, the quantitative relationship between the channel curvature, obstacle spatial distribution and navigation path complexity in the area is analyzed and calculated, and quantitative analysis results of navigation status and spatial distribution are generated. Based on the quantitative analysis results, combined with the received comprehensive input data including predicted energy consumption demand and current battery status, calculations are performed according to the preset optimization strategy, and finally, the charging strategy optimization parameters for dynamically regulating the charging process of the battery pack are output.

[0010] Furthermore, based on the curvature feature analysis results and combined with the real-time status information of the vessel within the dynamic assessment area, the quantitative relationship between channel curvature, obstacle spatial distribution, and navigation path complexity within the area is analyzed and calculated, generating quantitative analysis results of navigation status and spatial distribution, including: By receiving the curvature feature analysis results and simultaneously acquiring the real-time status information of the ship within the dynamic evaluation area, comprehensive analysis data including channel boundary morphology features and the real-time status of the ship is obtained. The comprehensive analysis data is processed to identify the curvature extrema and their distribution characteristics on the boundary curves, which serve as key channel curvature points; at the same time, the spatial relationship between the ship's current position and heading and the key points is determined. Based on the distribution characteristics of key channel curvature points and the relative spatial relationships of ships, combined with obstacle data in electronic river charts, quantitative indicators characterizing channel curvature, obstacle spatial distribution density, and navigation path complexity are calculated. By performing comprehensive calculations and normalization on the quantitative indicators, structured quantitative analysis results are generated to describe the relationship between the navigation situation and spatial distribution within the current assessment area.

[0011] Furthermore, the charging process of the battery pack is dynamically controlled by optimizing charging strategy parameters, so that the battery pack stores enough electrical energy to meet the needs of the segment's navigation and has a safety redundancy before entering the offline navigation segment, including: The charging strategy optimizes parameters and simultaneously acquires comprehensive input data on predicted energy consumption demand and current battery status, as well as detailed flight paths, as the basis for dynamic charging control decisions. Based on the charging strategy optimization parameters and decision-making criteria, and combined with the detailed navigation path, the remaining navigation distance of the ship in the current catenary power supply section is calculated as a constraint condition for determining the charging window. Based on the constraints of the rechargeable window and the optimization parameters of the charging strategy, combined with the charging characteristics of the battery pack, the required charging power command before entering the next offline navigation segment is calculated. The calculated charging current command is sent to the shipboard terminal for execution, and the battery status feedback is continuously received during the charging process until the battery pack's state of charge reaches the target value that meets the energy consumption requirements of the next offline navigation segment and leaves a safety redundancy.

[0012] Furthermore, during ship navigation, the system monitors the catenary status and grid capacity in real time. When power supply is sufficient, it prioritizes cable-driven operation and charging; when entering offline zones or experiencing power outages, it automatically switches to battery power and adjusts propulsion power in real time based on remaining range and battery charge, achieving optimized energy consumption scheduling, including: During the ship's navigation, it continuously receives real-time data on the ship's location, contact network connection status, and real-time load capacity of the power grid from the ship's onboard terminal, and processes this data synchronously with the detailed navigation path to generate comprehensive monitoring data on the current navigation status and power grid capacity. Based on comprehensive monitoring data, the feasibility of the ship's current power supply mode is assessed in real time. If the assessment result is that the contact wire connection is normal and the power grid capacity is sufficient, an instruction to use cable drive and execute charging is generated. If the assessment result is that the ship enters the offline zone or the power supply is interrupted, an instruction to switch to battery power is generated. After the command to switch to battery power is executed, the remaining distance from the ship's current position to the next recoverable net power point or the end of the voyage is calculated based on the detailed navigation path. Combined with the real-time state of charge of the battery pack, the target propulsion power range required to meet the remaining distance is calculated. Based on the calculated target propulsion power range, a real-time propulsion power adjustment command is generated and sent to the shipboard power unit for execution, while continuously returning to the execution status to form a closed-loop energy consumption optimization scheduling.

[0013] In a second aspect, a computing device includes: One or more processors; A storage device for storing one or more programs that, when executed by one or more processors, cause the one or more processors to execute the system.

[0014] Thirdly, a computer-readable storage medium storing a program that, when executed by a processor, performs the system.

[0015] The above-described solution of the present invention has at least the following beneficial effects: Based on path planning using electronic river charts and multi-sensor fusion positioning, accurate prediction of offline section energy consumption, construction of a dynamic evaluation area with three pre-set fixed navigation buoys as vertices in the waterway, quantitative analysis of the curvature characteristics of the boundary curve of the dynamic evaluation area, dynamic control of the battery pack charging process, and seamless switching between catenary and battery power supply modes during navigation, as well as real-time adjustment of propulsion power, this integrated technology effectively overcomes the technical problems in the energy consumption scheduling of existing catenary-powered ships, such as fixed charging strategies, insufficient scenario adaptability, inaccurate offline energy consumption prediction, and energy waste and offline navigation power interruption caused by the imbalance between catenary power supply and energy storage. This achieves precise matching of supply and demand between catenary power supply and battery energy storage, improves the energy utilization efficiency of the entire voyage, ensures the continuity and safety of power during offline navigation, enhances the system's adaptability to complex waterway scenarios, and further strengthens the economy, reliability, and green low-carbon attributes of catenary-powered ships. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the overhead contact line ship energy consumption optimization scheduling system provided in an embodiment of the present invention.

[0017] Figure 2 This is a flowchart illustrating the process of extracting the boundary curve of the dynamic evaluation area in the energy consumption optimization scheduling system for electric ships provided by an embodiment of the present invention. By analyzing the curvature characteristics of the boundary curve, curvature analysis results are obtained. Based on the curvature analysis results, the navigation status and spatial distribution relationship within the evaluation area are quantitatively analyzed to obtain the corresponding charging strategy optimization parameters. Detailed Implementation

[0018] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0019] like Figure 1 As shown, embodiments of the present invention propose a power-assisted ship navigation energy consumption optimization scheduling system, comprising: The acquisition module is used to plan a navigation path that includes a power supply segment and an offline navigation segment based on the starting point and ending point of the target voyage and the fusion positioning information of electronic river map and multi-sensor. The prediction module is used to identify the continuous power supply sections and obstacle sections that need to be offline along the route based on the navigation path, and to predict the length and energy consumption requirements of each offline navigation section. The module is used to establish a dynamic evaluation area with three pre-set fixed navigation buoys in the waterway as vertices when the ship is in the catenary power supply section, based on the predicted energy consumption demand of the offline navigation section and the current state of charge of the battery pack. The quantization module is used to extract the boundary curves of the dynamic evaluation area, and obtain curvature analysis results by analyzing the curvature characteristics of the boundary curves. Based on the curvature analysis results, the navigation situation and spatial distribution relationship within the evaluation area are quantitatively analyzed to obtain the corresponding charging strategy optimization parameters. The control module is used to dynamically control the charging process of the battery pack by optimizing the parameters of the charging strategy, so that the battery pack can store enough electrical energy to meet the needs of the segment of navigation and have a safety redundancy before entering the offline navigation segment. The processing module is used to monitor the status of the catenary and the power grid in real time during the ship's navigation. When the power supply is sufficient, it will prioritize driving and charging the catenary via cable. When entering the offline zone or when the power supply is interrupted, it will automatically switch to battery power and adjust the propulsion power in real time according to the remaining range and power, so as to achieve energy consumption optimization scheduling.

[0020] In this embodiment of the invention, an integrated technical approach based on electronic river chart and multi-sensor fusion positioning for hybrid path planning between the catenary and offline systems, offline segment energy consumption prediction, dynamic evaluation area construction with three pre-set fixed navigation buoys in the waterway as vertices, quantitative analysis of the curvature characteristics of the area boundary curve, dynamic control of battery pack charging, seamless switching between catenary and battery power supply during navigation, and real-time adjustment of propulsion power effectively overcomes the technical problems in the energy consumption scheduling of existing catenary electric ships, such as fixed charging strategies, insufficient scenario adaptability, inaccurate offline energy consumption prediction, and energy waste and offline navigation power interruption caused by the imbalance between catenary power supply and energy storage. This achieves precise matching of supply and demand between catenary power supply and battery energy storage, improves the energy utilization efficiency of the entire voyage, ensures the continuity and safety of power during the offline navigation phase, enhances the system's adaptability to complex waterway scenarios, and further strengthens the zero-emission environmental protection attributes, operational economy, and navigation reliability of the catenary electric ship.

[0021] In a preferred embodiment of the present invention, based on the starting and ending points of the target voyage and the fusion positioning information of electronic river chart and multi-sensor data, a navigation path including a power supply segment and an offline navigation segment is planned, comprising: The system receives the start and end point information of the target voyage and simultaneously acquires pre-stored electronic river map data and multi-sensor fusion positioning information reported through the shipboard terminal. Specifically, this includes: firstly, receiving the geographic coordinates of the start and end points of the target voyage manually input by the operator through the shipboard control terminal, ensuring that the location descriptions of the start and end points accurately correspond to the actual locations of the inland waterway; and secondly, retrieving the complete pre-stored electronic river map data from the ship's locally stored database. The electronic river map data covers comprehensive information such as the geographical outline of the inland waterway, water depth distribution, navigation restrictions, layout of riverside facilities, and planned routes for power supply facilities. The shipborne terminal synchronously integrates real-time data collected by global positioning equipment, Beidou satellite navigation equipment, inertial navigation equipment, speed sensors, and heading sensors. Through a stable wired communication network inside the ship, the multi-sensor fusion positioning information, after time registration and unified spatial coordinate processing, is continuously reported. The received origin and destination information, electronic river chart data, and multi-sensor fusion positioning information are synchronously verified to ensure that all types of data are consistent in format and transmitted completely. The multi-sensor fusion positioning information must include key parameters such as the ship's current precise geographical location, real-time heading, speed, and hull attitude.

[0022] Based on electronic river map data, the waterway is analyzed and processed to identify and mark all available overhead catenary power supply sections and known obstacle sections, generating waterway feature information containing power supply and obstacle attributes. Specifically, this includes: performing layered analysis and in-depth processing on the acquired electronic river map data; firstly, extracting core geographic information such as the waterway's spatial coordinate boundary data, water depth variation data, and navigation width restriction data; then, retrieving pre-stored overhead catenary power supply facility ledger data, which contains detailed information on the location of all completed and operational overhead catenaries, power supply voltage levels, power supply coverage, and equipment operating status. Detailed information is obtained by precisely comparing the locations of the catenary power supply facilities in the ledger with the channel coordinates on the electronic river chart. This identifies all continuous sections in the channel with stable power supply capabilities that can meet the catenary power supply needs of ships, clearly marking the start and end geographical coordinates, power supply coverage boundaries, and power supply stability level of each catenary power supply section. Simultaneously, based on the geographical feature data recorded on the electronic river chart, sections containing known obstacles such as bridges, shoals, reefs, wharves, and construction areas are identified, determining key information such as the spatial distribution range, obstacle type, and navigation restrictions for each obstacle section. The identified catenary power supply sections and obstacle sections are then marked with geographical coordinate ranges and classified by attributes. Attributes such as power supply capacity, power supply duration, obstacle type, and avoidance requirements are linked and bound to the corresponding section's coordinate range, ultimately integrating them to form a complete and detailed channel feature information system containing both power supply and obstacle attributes.

[0023] Based on waterway characteristic information, and using the starting point, ending point, and real-time positioning reported by the ship's terminal as spatial constraints, a preliminary navigation route is planned on the electronic river chart to obtain a continuous navigation baseline from the starting point to the ending point. Specifically, this includes: using the starting point coordinates, ending point coordinates, and the ship's current positioning coordinates reported by the ship's terminal as core spatial constraints, and deeply integrating them with the generated waterway characteristic information; strictly adhering to inland waterway navigation safety management requirements, ship navigation performance limitations, and the principle of optimizing navigation efficiency during the route planning process, prioritizing routes with good navigation conditions and continuous power supply sections; conducting a comprehensive route search within the waterway area of ​​the electronic river chart, and comprehensively evaluating the navigation safety, distance rationality, and power supply accessibility of multiple potential navigation routes to avoid unnavigable or unsuitable areas such as core obstacle areas, shallow water areas with insufficient depth, and areas with limited navigation width. Meanwhile, the search range is dynamically adjusted based on the ship's real-time positioning information to ensure a smooth connection between the planned route and the ship's current position. The searched route is smoothed through path optimization logic to eliminate unreasonable sections such as sharp bends and broken lines, generating a continuous navigation baseline connecting the starting point and the end point.

[0024] The continuous trajectory traversed by the coherent navigation baseline is matched, segmented, and associated with the power supply and obstacle sections in the channel feature information. Finally, a detailed navigation path consisting of alternating catenary power supply and offline navigation sections is planned and output. Specifically, this involves: dividing the initially planned coherent navigation baseline into segments at fixed intervals to form a series of continuous short-distance trajectory segments, each containing clearly defined start and end geographic coordinates; subsequently, comparing the coordinate range of each trajectory segment with the coordinate ranges of the catenary power supply and obstacle sections in the channel feature information one by one. When all coordinates of a trajectory segment fall within the coordinate range of the catenary power supply segment, and the power supply status of that segment meets the ship's requirements, the trajectory segment is marked as a catenary power supply segment; when all coordinates of a trajectory segment fall within the coordinate range of the obstacle section, or when the segment needs to avoid obstacles and cannot use catenary power supply, the trajectory segment is marked as an offline navigation segment. For continuously distributed contact power supply segments without intermediate obstructions, the entire segment is marked to clarify its continuous power supply capability. For adjacent offline navigation segments, attribute markings are performed according to obstacle type and avoidance requirements. Simultaneously, connection node information between each contact power supply segment and adjacent offline navigation segments is established, clearly defining key information such as the precise geographical coordinates when switching segments, navigation speed adjustment requirements, and power supply mode switching trigger conditions. Finally, all marked contact power supply segments, offline navigation segments, and connection node information are integrated and associated to form a detailed navigation path with a clear structure and complete information. This path clearly presents the alternating distribution order of contact power supply segments and offline navigation segments, the specific coordinate range, length, and connection requirements of each segment, providing accurate path basis for subsequent offline energy consumption prediction and charging strategy optimization.

[0025] In this embodiment of the invention, the system receives the starting and ending points of the target voyage, pre-stored electronic river chart data, and shipborne multi-sensor fusion positioning information. First, based on the electronic river chart, it identifies and marks all available catenary power supply sections and known obstacle sections within the waterway to generate waterway feature information containing power supply and obstacle attributes. Then, it plans a coherent navigation baseline using the starting point, ending point, and real-time positioning as spatial constraints. Finally, through the technical means of matching, segmenting, and associating the baseline with the waterway feature information, it effectively overcomes the technical problem that existing path planning does not fully integrate waterway power supply attributes and obstacle information, resulting in the planned path being unable to adapt to the dual-source power supply requirements of catenary-powered ships, and easily leading to catenary power supply interruption or insufficient offline navigation preparation. Thus, it accurately outputs a detailed navigation path that alternates between catenary power supply sections and offline navigation sections.

[0026] In a preferred embodiment of the present invention, based on the navigation path, continuous power supply sections along the route and obstacle sections requiring offline navigation are identified, and the length and energy consumption requirements of each offline navigation section are predicted, including: Based on the detailed navigation path, the path is parsed to obtain a sequence of navigation segments consisting of alternating catenary power supply and offline navigation segments. Specifically, this involves: first, obtaining the output detailed navigation path, which includes complete information such as the alternating distribution order of the catenary power supply and offline navigation segments, the specific coordinate range and length of each segment, and connection requirements; then, disassembling and parsing the detailed navigation path segment by segment, extracting key data such as attribute identifiers, start and end geographic coordinates, length information, and connection node coordinates for each segment; finally, classifying and sorting all segments according to the actual navigation sequence from the starting point to the end point, ensuring that adjacent segments are identified by catenary power supply and offline navigation respectively, forming a sequentially continuous sequence of alternating attributes for the navigation segments.

[0027] By analyzing the navigation segment sequence, all continuous catenary power supply segments were identified, and power supply segments interrupted by offline navigation segments were logically merged. Simultaneously, all obstacle segments requiring offline navigation were identified, resulting in a structured list of continuous power supply segments and a list of obstacle segments. Specifically, this involved: comprehensively traversing and analyzing the navigation segment sequence according to the ship's navigation sequence, determining the attribute identifier of each segment; when multiple consecutive segments all had the attribute identifier of catenary power supply, the segment was determined as a continuous catenary power supply segment, and its overall start and end geographical coordinates, total length, and intermediate connections were recorded. Information such as nodes; when two or more contactless power supply sections are separated by one or more offline navigation sections, these physically discontinuous but attribute-consistent contactless power supply sections are logically merged, and the original information of each component of each merged power supply section and the associated information of the intermediate offline navigation sections are marked; at the same time, during the traversal, all sections marked as offline navigation are identified, and the obstacle type, start and end geographic coordinates, contactless power supply section identifiers, and other information of each offline navigation section are clarified; finally, a structured list of continuous power supply sections and a list of obstacle sections are formed.

[0028] Based on the list of obstacle segments, for each offline navigation obstacle segment in the list, its corresponding navigation trajectory data is retrieved to calculate and predict the navigation length of each obstacle segment. Specifically, this includes: retrieving the generated list of obstacle segments and selecting each offline navigation obstacle segment in the order listed; for each selected obstacle segment, retrieving the navigation trajectory data of the corresponding segment from the generated detailed navigation path, which includes the continuous coordinate point set path curve data of the ship's navigation within the obstacle segment; preprocessing the retrieved navigation trajectory data to remove invalid displacement points caused by environmental disturbances such as anchoring status, and retaining the valid coordinate points of the ship's actual navigation; connecting the valid coordinate points in the navigation sequence to decompose them into multiple continuous short-distance line segments, calculating the length of each short-distance line segment and summing them; by summing the lengths of all short-distance line segments, the actual navigation length of each offline navigation obstacle segment is obtained, completing the prediction calculation of the navigation length of each obstacle segment and ensuring that the length data accurately reflects the actual navigation distance of the ship in the obstacle segment.

[0029] Based on the predicted navigation length of each obstacle section, combined with preset ship navigation performance parameters and historical energy consumption data, the energy consumption required for the ship to pass through each obstacle section is predicted and calculated, resulting in the length and energy consumption requirements of each offline navigation section. Specifically, this includes: collecting and retrieving preset ship navigation performance parameters, including basic data reflecting the ship's navigation capabilities such as rated power, propulsion system efficiency, navigation resistance coefficient, design speed, load parameters, and hull draft; and retrieving historical energy consumption data of the ship under similar obstacle types, similar speeds, and load conditions in the same inland waterway. This data includes energy consumption per unit distance, energy loss ratios corresponding to different obstacle types, and the impact of water flow changes on energy consumption. Information such as the impact coefficient of energy consumption is collected; the predicted navigation length of each obstacle section is deeply integrated with the above-mentioned ship navigation performance parameters and historical energy consumption data for calculation; firstly, the theoretical energy consumption value is calculated based on the navigation length, ship rated power and propulsion efficiency, and then combined with the energy consumption correction coefficients in the same or similar scenarios in the historical energy consumption data, considering factors such as the resistance change corresponding to the channel curvature of the obstacle section, the impact of water flow speed on navigation resistance, and the increase in energy consumption caused by obstacle avoidance operations, the theoretical energy consumption value is dynamically corrected; through the comprehensive calculation and correction of multi-dimensional data, the accurate actual energy consumption demand of each offline navigation obstacle section is obtained, and finally the navigation length and corresponding energy consumption demand of each obstacle section are integrated.

[0030] In this embodiment of the invention, a technical approach is adopted to first parse the detailed navigation path to obtain the sequence of alternating sections of the catenary power supply segment and the offline navigation segment. Then, by analyzing the sequence, all continuous catenary power supply segments are identified and logically merged. Obstacle segments are identified simultaneously to form a structured list. Subsequently, the navigation trajectory data of each obstacle segment is called to calculate and predict its navigation length. Finally, the energy consumption demand of each obstacle segment is predicted by combining preset ship navigation performance parameters and historical energy consumption data. This technical approach effectively overcomes the technical problems in the prior art, such as the fragmented division of catenary power supply segments and offline obstacle segments, and the fuzzy prediction of offline navigation-related parameters, which leads to the inability to provide accurate data support for the battery charging strategy and thus causes an imbalance in offline navigation energy reserves. This approach accurately obtains a structured list of continuous power supply segments, a list of obstacle segments, and the length and energy consumption demand data of each offline navigation segment, ensuring the energy consumption adaptability and power continuity of the catenary-powered ship.

[0031] In a preferred embodiment of the present invention, based on the predicted energy consumption demand of the offline navigation section and the current state of charge of the battery pack, when the ship is in the catenary power supply section, a dynamic evaluation area is established with three pre-set fixed navigation buoys in the waterway as vertices, including: The system receives the length and energy consumption requirements of each offline navigation segment and simultaneously acquires the current state of charge (SBC) of the battery pack reported via the shipboard terminal. This results in comprehensive input data containing predicted energy consumption requirements and the current battery status. Specifically, this includes: first, receiving detailed information on each offline navigation segment, including the actual navigation length and accurately predicted energy consumption requirements for each segment. This information covers key data for all obstacle-prone sections that require disconnection from the power grid and reliance on battery power; second, continuously acquiring current operating data of the battery pack through the shipboard terminal equipment. This data includes key parameters reflecting the battery's current performance and energy reserves, such as remaining battery capacity, SBC value, battery health status, and charge / discharge cycle count. The system synchronously collects and processes both types of data, verifying the complete correspondence between the length and energy consumption requirements of each offline navigation segment, checking the integrity and accuracy of the transmitted data related to the current SBC of the battery pack, removing abnormal data, and supplementing the data collection. Finally, all valid data is integrated and summarized to form comprehensive input data containing information such as the length of each offline navigation segment, energy consumption requirements, and the current remaining battery capacity, SBC, and health status.

[0032] Based on comprehensive input data and detailed navigation paths, combined with the ship's real-time position information, the attributes of the ship's current navigation segment are determined to identify the specific catenary power supply segment in which the ship is currently located. This process includes: retrieving the previously planned detailed navigation path, which clearly includes the alternating distribution order of catenary power supply segments and offline navigation segments, the start and end geographic coordinate range of each segment, and the location of connecting nodes; associating and matching the navigation-related information contained in the comprehensive input data with the detailed navigation path, while also combining it with the real-time position coordinate information obtained by the ship through positioning equipment, including precise geographic longitude and latitude data; comparing the ship's real-time position coordinates with the coordinate range of each segment in the detailed navigation path one by one to determine which segment's coordinate range the ship's current position falls within, thereby determining whether the current segment is a catenary power supply segment or an offline navigation segment; once the current segment is confirmed to be a catenary power supply segment, further extracting detailed information about this specific catenary power supply segment, including start and end coordinates, total length, internal channel characteristics, identification of connecting offline navigation segments, and corresponding energy consumption requirements.

[0033] Based on a specific contactless power supply section, the coordinate information of three pre-defined fixed navigation buoys within that specific contactless power supply section is queried and extracted from a pre-stored waterway facility database. Specifically, this involves: retrieving the pre-stored waterway facility database, which contains detailed information on all fixed facilities within inland waterways, including unique identifiers, specific geographical coordinates, waterway sections, construction dates, and maintenance records for facilities such as navigation buoys, beacons, and bridge piers; performing precise queries and filtering within the waterway facility database based on the detailed information of the determined specific contactless power supply section, including the start and end coordinate ranges and the waterway number; identifying three pre-defined fixed navigation buoys within the specific contactless power supply section that are intended for establishing an assessment area, ensuring that these three buoys are facilities planned and installed by the waterway management department, with fixed locations and accurate coordinates; extracting the precise geographical coordinate information of each of these three fixed navigation buoys, including the longitude and latitude data of each buoy, while verifying that the buoy identification information matches the database records, confirming that the coordinate data has not shifted or is incorrect, and finally forming a dataset containing complete coordinate information for the three fixed navigation buoys.

[0034] Based on the extracted coordinate information of three fixed navigation buoys, and combined with the ship's real-time position and heading information, a dynamic polygonal evaluation area covering the current navigation situation is established. Specifically, this includes: using the precise geographic coordinates of the three fixed navigation buoys as the basis, marking these three coordinate points as initial vertices within the corresponding channel area on the electronic river chart; simultaneously, acquiring the ship's current real-time position coordinates and real-time heading information, including key data such as the ship's current direction of travel angle and speed; adjusting the triangular range formed by the three buoy vertices based on the ship's real-time position to ensure the ship's current position is within the triangular area, and that the area covers the channel segment the ship will traverse in its subsequent short-distance voyage; further optimizing the coverage area based on the ship's real-time heading information, so that the dynamic polygonal evaluation area fits the ship's navigation trajectory and comprehensively covers the channel environment under the current navigation situation, including key scenarios such as channel bends and potential areas of changing current; and constructing a clearly defined and appropriately sized dynamic polygonal evaluation area through the comprehensive integration of the three buoy vertex coordinates with the ship's real-time position and heading information.

[0035] In this embodiment of the invention, a comprehensive input data is formed by receiving energy consumption demand for each offline navigation segment and the current state of charge of the battery pack. This data is combined with detailed navigation paths and the ship's real-time position to determine the specific contactless power supply segment currently in which the ship is located. The coordinate information of three preset fixed navigation buoys within the contactless power supply segment is extracted from the waterway facility database. Then, the ship's real-time position and heading are integrated to establish a dynamic polygonal evaluation area covering the current navigation situation. This effectively overcomes the technical problem of existing technologies that fail to dynamically link offline energy consumption demand, real-time battery status, and navigation scenarios, lacking a targeted evaluation carrier, which leads to charging strategy optimization being divorced from the actual navigation situation. This provides spatial support that fits the current navigation scenario for quantitative analysis of waterway characteristics and generation of accurate charging strategy optimization parameters, improving the scenario adaptability and accuracy of energy consumption scheduling.

[0036] like Figure 2 As shown, in another preferred embodiment of the present invention, the boundary curve of the dynamic evaluation area is extracted, and the curvature analysis result is obtained by analyzing the curvature characteristics of the boundary curve; based on the curvature analysis result, the relationship between the navigation situation and spatial distribution within the evaluation area is quantitatively analyzed to obtain the corresponding charging strategy optimization parameters, including: Based on the established dynamic polygon evaluation area, the spatial data of the dynamic polygon is geometrically processed to extract and generate the boundary curve of the dynamic polygon spatial data. Specifically, this includes: first, acquiring the complete spatial data of the previously established dynamic polygon evaluation area, which includes the precise geographic coordinates of all vertices in the area, the connection relationships between vertices, and the information on the waterway range covered by the area; performing systematic geometric processing on the spatial data, first arranging the vertex coordinates of the polygon in a clockwise direction to ensure that the contour formed by the connection of vertices can accurately fit the actual boundary of the evaluation area, avoiding boundary distortion caused by disordered vertex order; then, supplementing a sufficient number of intermediate coordinate points between adjacent vertex coordinates to transform the original boundary of the area, which was composed of polylines, into a smooth and continuous curve; during the interpolation process, strictly following the actual geographic characteristics of the waterway, ensuring that the supplemented intermediate points accurately reflect the shoreline trend, shoal edges, and other natural terrain contours, and finally extracting and generating a complete, smooth boundary curve that can truly represent the boundary morphology of the dynamic polygon evaluation area.

[0037] By performing geometric feature analysis on the extracted boundary curves, the curvature values ​​of each point on the boundary curves are calculated and identified, resulting in curvature feature analysis results describing the changes in boundary morphology. Specifically, this includes: a comprehensive geometric feature analysis of the extracted boundary curves; firstly, dividing the boundary curves into multiple continuous curve segments at fixed length intervals, each segment containing clearly defined start and end point coordinates; for each curve segment, selecting several key sampling points within the segment, calculating the angle of change of the tangent direction formed by each sampling point and its adjacent sampling points, and combining this with the arc distance between sampling points, calculating the curvature value of each sampling point point by point; during the calculation process, smoothing abnormally fluctuating curvature data and eliminating extreme values ​​caused by data errors to ensure that the curvature values ​​accurately reflect the curvature degree of the curve; and finally, organizing the curvature values ​​of all sampling points to form curvature feature analysis results containing information such as the curvature value of each point, the curvature change trend, and the location of curvature extreme points.

[0038] Based on the curvature feature analysis results and combined with the real-time status information of the ship within the dynamic assessment area, the quantitative relationships between channel curvature, obstacle spatial distribution, and navigation path complexity within the area are analyzed and calculated to generate quantitative analysis results of navigation status and spatial distribution. Specifically, this includes: first, receiving the obtained curvature feature analysis results and simultaneously acquiring the ship's real-time status information within the dynamic assessment area. This information includes the ship's current precise position coordinates, real-time heading angle, speed, hull roll and pitch attitude, propulsion system operating status, and other key data, forming a comprehensive analysis dataset that includes channel boundary morphology features and the ship's real-time status; then, performing deep processing on the comprehensive analysis dataset to identify all curvature extreme points from the curvature feature analysis results, clarifying the coordinate position, curvature value, and distribution density of each extreme point, and using these extreme points as key... The system identifies key channel curvature points and determines the spatial orientation and distance of the vessel's current position and course relative to each key curvature point through coordinate comparison. It then combines obstacle data recorded in the electronic river chart within the assessment area, including obstacle type, location coordinates, and size, to calculate quantitative indicators characterizing channel curvature, obstacle spatial distribution density, and navigation path complexity. Channel curvature is quantified by the ratio of the number of key curvature points to the total length of the boundary curves; obstacle spatial distribution density is quantified by the ratio of the total number of obstacles within the assessment area to the area of ​​the region; and navigation path complexity is calculated by weighting the channel curvature, obstacle distribution density, and the angle between the vessel's course and the key curvature points. These quantitative indicators are then standardized to unify the different dimensions of the indicators within the same numerical range, ultimately generating structured quantitative analysis results.

[0039] Based on the quantitative analysis results, combined with the received comprehensive input data including predicted energy consumption demand and current battery status, calculations are performed according to the preset optimization strategy. The final output is the charging strategy optimization parameters for dynamically regulating the battery pack charging process. Specifically, this includes: first, integrating the generated navigation situation and spatial distribution quantitative analysis results, along with previously acquired comprehensive input data including predicted energy consumption demand for each offline navigation segment, current battery pack state of charge, and battery health status; then, retrieving the preset charging optimization strategy, which is formulated based on extensive inland waterway navigation scenario data, clearly defining different channel curvatures, obstacle distribution densities, path complexity, and battery... The charging control logic is tailored to different conditions. For example, when the channel has high curvature or high path complexity, the charging power needs to be increased to store more energy, while the charging power can be appropriately reduced when the battery's current state of charge is sufficient to avoid waste. The various indicators in the quantitative analysis results are correlated and matched with the comprehensive input data. Based on the preset optimization strategy, the charging control parameters are calculated, and combined with the predicted energy consumption demand of the offline navigation section, the target state of charge that the battery pack needs to achieve is calculated. A reasonable charging power is determined based on the remaining navigation distance and charging time of the current contact power supply section. A charging rhythm adjustment plan is formulated with reference to the channel complexity index to ensure that sufficient charging is completed in advance in the contact power supply section corresponding to complex channels. During the calculation process, the charging characteristics and safe operation requirements of the battery are fully considered to avoid overcharging or damage to the battery due to excessively fast charging rates. The final output includes charging strategy optimization parameters containing the target state of charge, final charging power, charging rhythm adjustment interval, and charging stop threshold.

[0040] In this embodiment of the invention, a technical approach is adopted to first extract the boundary curves of the dynamic polygon evaluation area and analyze their curvature characteristics, then combine the real-time status information of the ship in the area to quantitatively calculate the channel curvature, obstacle spatial distribution and navigation path complexity, and finally integrate the comprehensive input data of predicted energy consumption demand and current battery status to calculate and output charging strategy optimization parameters according to a preset optimization strategy. This approach effectively overcomes the technical problems of existing technologies that cannot accurately correlate channel spatial morphology, navigation status and energy consumption reserve demand, lack quantitative basis for charging strategy optimization, resulting in poor parameter adaptability and inability to match the energy consumption demand of complex navigation scenarios, thereby generating accurate charging strategy optimization parameters that fit the actual navigation scenario.

[0041] In a preferred embodiment of the present invention, based on the curvature feature analysis results and combined with the real-time status information of the ship within the dynamic evaluation area, the quantitative relationship between the channel curvature, obstacle spatial distribution, and navigation path complexity within the area is analyzed and calculated to generate quantitative analysis results of navigation status and spatial distribution, including: By receiving the curvature feature analysis results and simultaneously acquiring the real-time status information of the vessel within the dynamic assessment area, comprehensive analytical data containing channel boundary morphology features and the vessel's real-time status is obtained. Specifically, this includes: firstly, the curvature feature analysis results, containing complete information such as the curvature values ​​of each sampling point on the boundary curve, curvature change trends, coordinate positions of curvature extrema, and distribution density; secondly, the real-time status information of the vessel within the dynamic assessment area is simultaneously acquired, covering key data reflecting the vessel's real-time operating conditions, such as the vessel's current precise geographic coordinates, real-time heading angle, speed, hull roll angle, hull trim angle, propulsion system operating power, and pantograph contact status; thirdly, the two types of data are synchronously integrated, and the timestamps of the curvature feature data and the vessel's real-time status data are checked one by one to ensure accurate correspondence between the two types of data in the time dimension, avoiding analytical bias caused by data asynchrony; finally, all valid data are summarized and organized to form comprehensive analytical data containing channel boundary morphology features and the vessel's real-time status.

[0042] The comprehensive analysis data is processed to identify the curvature extrema and their distribution characteristics on the boundary curves, which serve as key channel bends. Simultaneously, the spatial relationship between the ship's current position and heading relative to these key points is determined. Specifically, this involves: performing in-depth processing on the generated comprehensive analysis data, focusing on extracting the curvature numerical sequence of the boundary curves; filtering out points with curvature values ​​higher or lower than the surrounding curvature values ​​by traversing all curvature values; these points are the curvature extrema, where maximum curvature points correspond to sharp bends in the channel, and minimum curvature points correspond to gentle bends or straight transitions in the channel; and recording each curvature extrema. By accurately determining the geographic coordinates, corresponding curvature values, and distances between adjacent extreme points, and analyzing the distribution density and patterns of these extreme points on the boundary curve, the curvature extreme points are clearly identified as critical channel bends. Based on this, using the coordinates of the critical channel bends as a benchmark, the spatial orientation of the ship's current position relative to each critical bend is determined by calculating the straight-line distance between the ship's current geographic coordinates and the coordinates of each critical bend, the angle between the ship's real-time heading and the line connecting the ship to the critical bend, and the compatibility between the ship's navigation direction and the channel segment where the critical bend is located.

[0043] Based on the distribution characteristics of key channel curvature points and the relative spatial relationships of vessels, combined with obstacle data from the electronic river chart, quantitative indicators characterizing channel curvature, obstacle spatial distribution density, and navigation path complexity are calculated. Specifically, this includes: calculating quantitative indicators characterizing channel curvature based on the distribution characteristics of identified key channel curvature points, including the total number of key curvature points, the average distance between adjacent key curvature points, and distribution density, combined with the spatial relationship between the vessel's current position and the key curvature points; specifically, calculating the ratio of the total number of key channel curvature points to the total length of the boundary curves within the dynamic assessment area, with a larger ratio indicating a higher degree of channel curvature; simultaneously, retrieving obstacle data from the dynamic assessment area within the electronic river chart, including obstacle types, By accurately measuring geographic coordinates, dimensions, and navigation restrictions, the total number of obstacles in the area is statistically assessed. Combined with the actual area of ​​the dynamically assessed region, a quantitative index of obstacle spatial distribution density is calculated by the ratio of the total number of obstacles to the area area. The larger the ratio, the denser the obstacle distribution. Furthermore, by integrating quantitative indices of channel curvature, obstacle spatial distribution density, the angle between the ship's real-time course and the line connecting key curvature points, and the impact of ship speed on path selection, a quantitative index characterizing the complexity of the navigation path is obtained through weighted calculation. Channel curvature and obstacle distribution density have higher weights, while the angle and speed have relatively lower weights. Finally, three independent quantitative indices that comprehensively reflect the navigation characteristics of the region are obtained.

[0044] By comprehensively calculating and normalizing quantitative indicators, a structured quantitative analysis result describing the navigation situation and spatial distribution relationship within the current assessment area is generated. Specifically, this includes: comprehensively calculating three quantitative indicators: channel curvature, obstacle spatial distribution density, and navigation path complexity; firstly, weighted summing of the three indicators according to preset navigation scenario importance weights to obtain a comprehensive value reflecting the navigation situation and spatial distribution relationship within the current assessment area; then, normalizing the comprehensive value and the three independent quantitative indicators separately, mapping all indicator values ​​to a uniform range of zero to one, making indicators of different dimensions comparable; during the normalization process, referencing a large amount of historical data from inland waterways, determining the maximum and minimum value benchmarks for each indicator to ensure the normalization result accurately reflects the characteristic differences of the current area relative to conventional waterways; finally, integrating the normalized values ​​of the three independent quantitative indicators, the comprehensive value, the original calculation data of each indicator, and the basis for normalization processing to generate a clearly structured and complete structured quantitative analysis result.

[0045] In this embodiment of the invention, a comprehensive analysis data is formed by receiving curvature feature analysis results and real-time status information of the ship in the dynamic assessment area. By processing the data, the extreme points of the curvature of the boundary curve are identified and the spatial relationship between the ship and key points is determined. Combined with obstacle data from the electronic river chart, quantitative indicators of channel curvature, obstacle spatial distribution density, and navigation path complexity are calculated. Then, the quantitative indicators are comprehensively calculated and normalized to generate structured quantitative analysis results. This technical means effectively overcomes the technical problems of existing technologies that cannot accurately capture key curvature features of the channel and are difficult to quantify obstacle distribution and path complexity, resulting in a lack of structured data support for navigation situation analysis and insufficient targeting of subsequent charging strategy optimization. As a result, a structured quantitative result that can accurately describe the navigation situation and spatial distribution relationship in the current assessment area is obtained.

[0046] In a preferred embodiment of the present invention, the charging process of the battery pack is dynamically controlled by optimizing the charging strategy parameters, so that the battery pack stores enough electrical energy to meet the needs of the segment's navigation and has a safety redundancy before entering the offline navigation segment, including: By optimizing charging strategy parameters and simultaneously acquiring comprehensive input data including predicted energy consumption demand and current battery status, as well as detailed navigation paths, a decision-making basis for dynamic charging control is formed. Specifically, this includes: first, acquiring the output charging strategy optimization parameters, which include detailed information such as the target state of charge, optimal charging power, charging rhythm adjustment interval, and charging stop threshold; simultaneously retrieving previously aggregated comprehensive input data, which covers key information such as predicted energy consumption demand for each offline navigation segment, current battery state of charge, battery health status, and number of charge / discharge cycles; and simultaneously acquiring the planned detailed navigation path, which clearly defines the start and end coordinates, total length, subsequent offline navigation segment identifiers, and corresponding energy consumption demand of the current grid-connected power supply segment; and comprehensively integrating and verifying these three types of data, checking the matching of energy consumption demand and battery status between the charging strategy optimization parameters and the comprehensive input data, checking the completeness of information on the current grid-connected power supply segment in the detailed navigation path, eliminating invalid or abnormal data, and supplementing and improving it. Finally, a complete decision-making basis is formed, including core charging control parameters, basic energy consumption and battery data, and navigation path constraint information.

[0047] Based on the optimized charging strategy parameters and decision-making criteria, and combined with the detailed navigation path, the remaining navigation distance of the vessel in the current catenary-powered segment is calculated as a constraint condition for determining the available charging window. Specifically, this includes: extracting the total length, starting coordinates, and ending coordinates of the current catenary-powered segment from the integrated optimized charging strategy parameters and decision-making criteria; obtaining the vessel's precise geographical coordinates through real-time positioning equipment, and calculating the spatial distance between the precise geographical coordinates and the ending coordinates of the current catenary-powered segment to obtain the remaining distance the vessel still needs to navigate within the current catenary-powered segment; fully considering the channel characteristics of the current segment in the detailed navigation path, including channel curvature and navigable width, to ensure that the remaining distance calculation results accurately reflect the actual navigation mileage; this remaining distance directly determines the time window available for charging within the current catenary-powered segment, i.e., the time required for the vessel to travel the remaining distance at the current navigation speed. This remaining navigation distance is used as the core constraint condition for determining the available charging window, ensuring that the charging operation must be completed before the vessel leaves the current catenary-powered segment.

[0048] Based on the constraints of the rechargeable window and the optimization parameters of the charging strategy, combined with the charging characteristics of the battery pack, the required charging power command before entering the next offline navigation segment is calculated. Specifically, this includes: first, determining the constraints of the rechargeable window, i.e., the rechargeable time corresponding to the remaining navigation distance of the current power supply segment; second, combining the target state of charge in the obtained optimization parameters of the charging strategy, and the current state of charge of the battery pack in the comprehensive input data, calculating the total amount of energy required to upgrade from the current state of charge to the target state of charge; and third, retrieving the charging characteristic data of the battery pack, including data for different states of charge. The charging efficiency, maximum allowable charging power, and charging rate variation patterns under different charging states are considered. For example, higher charging power can be used when the battery is low in charge, while the charging power needs to be reduced when the battery is close to full charge to avoid overcharging. Based on the total amount of energy to be replenished, the available charging time, and the charging characteristics of the battery pack, the charging power required to reach the target state of charge within the current grid power supply segment is comprehensively calculated. The charging power must take into account both charging efficiency and battery safety, ensuring that the required energy replenishment is completed within the charging window without exceeding the maximum allowable charging power of the battery pack and the grid power supply capacity, ultimately forming a clear charging power instruction.

[0049] The calculated charging current command is sent to the shipboard terminal for execution, and battery status feedback is continuously received during the charging process until the battery pack's state of charge reaches the target value that meets the energy consumption requirements of the next offline navigation segment and leaves a safety redundancy. Specifically, this includes: converting the calculated charging power command into a corresponding charging current command, and sending it to the shipboard terminal equipment through a stable internal communication network to ensure complete and delay-free command transmission; after receiving the command, the shipboard terminal initiates the charging operation of the battery pack, charging according to the current intensity required by the command. During the charging process, the battery management system continuously collects real-time status data of the battery pack, including the current state of charge, battery temperature, charging current, and charging speed. Key parameters such as battery voltage are monitored and fed back to the control center in real time. The control center monitors and analyzes the feedback data in real time to determine whether the state of charge of the battery pack is gradually approaching the target value, and at the same time checks whether parameters such as battery temperature and voltage are within the safe range. If the battery temperature is found to be too high or the voltage is abnormal, the charging current command is adjusted in time to ensure the safe and stable charging process. When the feedback data shows that the state of charge of the battery pack has reached the target value, the target value has fully met the energy consumption requirements of the next offline navigation segment and has reserved a safety redundancy. The control center issues a charging stop command or switches to float charging mode to stop high-power charging operation, avoid energy waste and battery damage, and completes the entire dynamic charging control process.

[0050] In this embodiment of the invention, a comprehensive input data consisting of integrated charging strategy optimization parameters, predicted energy consumption demand, and current battery status, along with a detailed navigation path, is used as the basis for charging control decisions. The remaining distance of the current contact power supply segment is calculated based on the detailed navigation path to determine the charging window constraint. Then, based on this constraint, the charging strategy optimization parameters, and the battery pack charging characteristics, the required charging power command before entering the next offline navigation segment is calculated and sent to the shipborne terminal for execution. The system continuously receives battery status feedback until the target state of charge is reached. This effectively overcomes the technical problems in existing technologies where charging control does not fully consider the charging window limitation and the adaptability of battery charging characteristics to offline energy consumption demand, leading to unreasonable charging power, inaccurate matching of battery state of charge with offline navigation needs, and a tendency for overcharging to waste energy or undercharging to lack safety redundancy. This achieves precise dynamic control of the battery pack charging process, ensuring that the ship has sufficient energy reserves to meet energy consumption demands and maintain safety redundancy before entering the offline navigation segment.

[0051] In a preferred embodiment of the present invention, during ship navigation, the status of the contact wire and the grid capacity are monitored in real time. When power supply is sufficient, cable driving and charging are prioritized. When entering an offline zone or when power is interrupted, the system automatically switches to battery power and adjusts the propulsion power in real time based on the remaining range and battery charge to achieve optimized energy consumption scheduling, including: During the ship's voyage, the system continuously receives real-time data on the ship's location, overhead contact line connection status, and real-time grid load capacity from the ship's onboard terminal. This data is then processed synchronously with the detailed navigation path to generate comprehensive monitoring data on the current navigation status and grid capacity. Specifically, this includes: continuously receiving various key data from the ship's onboard terminal throughout the entire voyage from origin to destination; this includes real-time location-related data such as the ship's precise geographic coordinates, real-time speed, and heading angle; overhead contact line connection status data covering information reflecting the reliability of the connection, such as the contact pressure between the pantograph and the overhead cable, the magnitude of the contact current, and the duration of contact stability; and real-time grid load capacity data. Load capacity data includes parameters reflecting the power grid's supply capacity, such as the current overhead cable supply voltage, supply current, overall grid load factor, and remaining power supply capacity. Simultaneously, the planned detailed navigation path is retrieved, and the real-time received vessel position data is compared synchronously with the segment coordinates and attributes within the detailed navigation path to determine whether the vessel is currently in a connected or offline navigation segment. The connected cable status data, real-time grid load capacity data, and the vessel's current segment information are integrated and correlated, eliminating outliers and invalid data generated during data transmission, ultimately generating comprehensive monitoring data that fully reflects the current navigation status and grid supply capacity.

[0052] Based on comprehensive monitoring data, the feasibility of the ship's current power supply mode is assessed in real time. If the assessment result indicates that the contact wire connection is normal and the power grid capacity is sufficient, a command to use cable drive and execute charging is generated. If the assessment result indicates entering the offline zone or power interruption, a command to switch to battery power is generated. Specifically, this includes: comprehensively analyzing the generated comprehensive monitoring data to assess the feasibility of the current power supply mode in real time; firstly, analyzing the contact wire connection status data; if the contact pressure between the pantograph and the overhead cable is within a stable range, the contact current remains within the normal range, and there are no frequent interruptions, the contact wire connection is determined to be normal; then, analyzing the real-time load capacity data of the power grid; if the power grid supply voltage and current are stable within the standard range, and the power grid load factor is lower than [a certain value], [the following steps are taken]. If the preset safety threshold indicates that the remaining power supply capacity can simultaneously meet the ship's propulsion needs and battery charging needs, then the power grid capacity is deemed sufficient. When both the contact wire connection and the power grid capacity are deemed sufficient, an instruction is generated to drive the ship using cables and execute charging according to a predetermined charging strategy, ensuring that the ship fully utilizes the power grid in the contact wire power supply section while replenishing the battery power. If the comprehensive monitoring data shows that the ship's current position has fallen within the coordinate range of the offline navigation section marked in the detailed navigation path, or if the contact wire connection status data shows abnormal contact pressure, interrupted contact current, and the duration exceeds the set time, it is determined that the ship has entered the offline zone or the power supply has been interrupted. In this case, an instruction is immediately generated to switch to battery power supply to ensure that the ship's power is not interrupted.

[0053] Upon executing the command to switch to battery power, the remaining distance from the ship's current position to the next recoverable catamaran power point or the destination is calculated based on the detailed navigation path. Combined with the real-time state of charge of the battery packs, the target propulsion power range required to cover the remaining distance is calculated. Specifically, this includes: immediately retrieving the detailed navigation path after executing the command to switch to battery power, determining the ship's precise current position coordinates and the coordinates of the next recoverable catamaran power point; if there are no subsequent catamaran power supply segments, the destination coordinates are used as the target; and incorporating channel characteristics in the detailed navigation path, including channel curvature, navigable width, and water depth variations. The actual remaining distance from the ship's current position to the next recoverable net power point or the end of the voyage is calculated. The distance must accurately reflect the actual mileage required for the ship's voyage. At the same time, the real-time state of charge of the battery pack is obtained through the battery management system, including key data such as remaining charge, current charge percentage, battery output power capacity, and health status. Based on the remaining voyage distance, combined with the previously predicted energy consumption requirements for this segment of the voyage, and referring to the ship's navigation performance parameters and historical navigation energy consumption data, the target propulsion power range that meets the remaining voyage requirements without causing energy waste is calculated by comprehensively considering the real-time state of charge of the battery pack.

[0054] Based on the calculated target propulsion power range, a real-time propulsion power adjustment command is generated and sent to the ship's propulsion unit for execution. At the same time, the execution status is continuously returned, forming a closed-loop energy consumption optimization scheduling. Specifically, this includes: generating specific real-time propulsion power adjustment commands based on the calculated target propulsion power range and the ship's current sailing speed, hull attitude, and other real-time status. The command is transmitted to the ship's propulsion system via a reliable internal communication network. The propulsion system includes dual-motor propellers or waterjet propulsion units, ensuring rapid and accurate transmission and execution of the command. During command execution, the propulsion system continuously collects execution status data such as actual output propulsion power, real-time ship speed, and changes in ship attitude, and feeds this data back to the control center in real time. The feedback execution status data is continuously compared and analyzed with the target propulsion power range, remaining range, and real-time battery charge status. If the actual propulsion power exceeds the target range, the ship speed is inconsistent with expectations, or the battery charge consumption rate is too fast, the propulsion power adjustment command is adjusted promptly and re-transmitted to the propulsion system. Through this cyclical pattern of command issuance, status feedback, and command adjustment, a closed-loop energy consumption optimization scheduling is formed, ensuring that the ship navigates with the most reasonable propulsion power during battery-powered phases. This maximizes energy conservation while ensuring smooth navigation, avoiding premature battery depletion due to excessive power or reduced navigation efficiency due to insufficient power.

[0055] In this embodiment of the invention, a technical means is adopted to continuously receive real-time location, contact network connection status, and real-time grid load capacity data reported by the ship's onboard terminal during the ship's navigation. This data is processed synchronously with the detailed navigation path to generate comprehensive monitoring data. Based on this data, the feasibility of the power supply mode is determined in real time. After switching to battery power, the remaining range and real-time state of charge are calculated to determine the target propulsion power range. Then, a real-time power adjustment command is generated, issued, and executed to form a closed-loop scheduling. This effectively overcomes the technical problems in the prior art, such as delayed power supply mode switching, lack of dynamic adaptation of propulsion power, and failure to combine real-time navigation and energy status for closed-loop control, which leads to energy waste, inefficient use of offline navigation power, or power interruption. This achieves seamless coordinated switching between contact network power and battery power, and precise matching of propulsion power with the remaining range and power reserve requirements, forming a closed-loop energy consumption optimization scheduling throughout the entire process. This ensures the continuity and safety of navigation power, maximizes energy utilization efficiency, and further enhances the operational economy and green low-carbon attributes of the contact network electric ship.

[0056] Embodiments of the present invention also provide a computing device, including: a processor and a memory storing a computer program, wherein the computer program, when executed by the processor, performs the system as described above. All implementations in the above system embodiments are applicable to this embodiment and can achieve the same technical effects.

[0057] Embodiments of the present invention also provide a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the system as described above. All implementations in the above system embodiments are applicable to this embodiment and can achieve the same technical effects.

[0058] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A system for optimizing and scheduling energy consumption in ship navigation using electric catenary systems, characterized in that: include: The acquisition module is used to plan a navigation path that includes a power supply segment and an offline navigation segment based on the starting point and ending point of the target voyage and the fusion positioning information of electronic river map and multi-sensor. The prediction module is used to identify the continuous power supply sections and obstacle sections that need to be offline along the route based on the navigation path, and to predict the length and energy consumption requirements of each offline navigation section. The module is used to establish a dynamic evaluation area with three pre-set fixed navigation buoys in the waterway as vertices when the ship is in the catenary power supply section, based on the predicted energy consumption demand of the offline navigation section and the current state of charge of the battery pack. The quantization module is used to extract the boundary curves of the dynamic evaluation region and obtain curvature analysis results by analyzing the curvature characteristics of the boundary curves. Based on the curvature analysis results, a quantitative analysis of the relationship between the navigation status and spatial distribution within the evaluation area is performed to obtain the corresponding charging strategy optimization parameters; The control module is used to dynamically control the charging process of the battery pack by optimizing the parameters of the charging strategy, so that the battery pack can store enough electrical energy to meet the needs of the segment of navigation and have a safety redundancy before entering the offline navigation segment. The processing module is used to monitor the status of the catenary and the power grid in real time during the ship's navigation. When the power supply is sufficient, it will prioritize driving and charging the catenary via cable. When entering the offline zone or when the power supply is interrupted, it will automatically switch to battery power and adjust the propulsion power in real time according to the remaining range and power, so as to achieve energy consumption optimization scheduling.

2. The catenary-connected electric ship navigation energy consumption optimization and scheduling system according to claim 1, characterized in that, Based on the starting and ending points of the target voyage, and using electronic river charts and multi-sensor fusion positioning information, a navigation path is planned that includes a power supply segment and an offline navigation segment, including: It receives the start and end information of the target voyage and simultaneously acquires pre-stored electronic river map data and multi-sensor fusion positioning information reported through the shipborne terminal; Based on electronic river map data, the waterway is analyzed and processed to identify and mark all available catenary power supply sections and known obstacle sections in the waterway, generating waterway feature information containing power supply and obstacle attributes; Based on the waterway feature information, and using the starting point, the ending point, and the real-time positioning reported by the shipboard terminal as spatial constraints, combined with the waterway feature information, the navigation route is initially planned on the electronic river chart to obtain a continuous navigation baseline from the starting point to the ending point. The continuous trajectory traversed by the coherent navigation baseline is matched, segmented, and associated with the power supply section and obstacle section in the channel feature information. Finally, a detailed navigation path consisting of alternating overhead power supply sections and offline navigation sections is planned and output.

3. The catenary-connected electric ship navigation energy consumption optimization and scheduling system according to claim 2, characterized in that, Based on the flight path, identify continuous power supply sections along the route and obstacle sections requiring offline flight, and predict the length and energy consumption requirements of each offline flight section, including: Based on the detailed navigation path, the detailed navigation path is parsed and processed to obtain a sequence of navigation segments consisting of alternating power supply segments and offline navigation segments; By analyzing and processing the navigation segment sequence, all continuous power supply segments are identified, and power supply segments that are interrupted by offline navigation segments are logically merged. At the same time, all obstacle segments that need to be offline are identified, resulting in a structured list of continuous power supply segments and a list of obstacle segments. Based on the list of obstacle segments, for each offline navigation obstacle segment in the list, its corresponding navigation trajectory data is called to calculate and predict the navigation length of each obstacle segment. Based on the predicted navigation length of each obstacle section, combined with the preset ship navigation performance parameters and historical energy consumption data, the energy consumption required for the ship to pass through each obstacle section is predicted and calculated, thus obtaining the length and energy consumption requirement of each offline navigation section.

4. The catenary-connected electric ship navigation energy consumption optimization and scheduling system according to claim 3, characterized in that, Based on the predicted energy consumption requirements of the offline navigation section and the current state of charge of the battery pack, when the ship is in the catenary power supply section, a dynamic evaluation area is established with three pre-set fixed navigation buoys in the channel as vertices, including: The system receives the length and energy consumption requirements of each offline navigation segment and simultaneously obtains the current state of charge of the battery pack reported through the shipboard terminal, thereby obtaining comprehensive input data that includes predicted energy consumption requirements and current battery status. Based on comprehensive input data and detailed navigation path, combined with real-time ship location information, the attributes of the current navigation segment of the ship are judged and processed to determine the specific catenary power supply segment in which the ship is currently located. Based on a specific catenary power supply section, the coordinate information of three pre-set fixed navigation buoys within that specific catenary power supply section is queried and extracted from the pre-stored waterway facility database; Based on the coordinate information of the three fixed navigation buoys extracted, and combined with the real-time position and heading information of the ship, a dynamic polygonal evaluation area covering the current navigation situation is established.

5. The catenary-powered ship navigation energy consumption optimization and scheduling system according to claim 4, characterized in that, The boundary curves of the dynamic evaluation region are extracted, and the curvature analysis results are obtained by analyzing the curvature characteristics of the boundary curves. Based on the curvature analysis results, a quantitative analysis of the relationship between the navigation status and spatial distribution within the assessment area is performed to obtain the corresponding charging strategy optimization parameters, including: Based on the established dynamic polygon evaluation region, the spatial data of the dynamic polygon is geometrically processed to extract and generate the boundary curves of the spatial data of the dynamic polygon. By performing geometric feature analysis on the extracted boundary curves, the curvature values ​​of each point on the boundary curves are calculated and identified, and the curvature feature analysis results describing the boundary morphology changes are obtained. Based on the curvature feature analysis results and combined with the real-time status information of the ship in the dynamic assessment area, the quantitative relationship between the channel curvature, obstacle spatial distribution and navigation path complexity in the area is analyzed and calculated, and quantitative analysis results of navigation status and spatial distribution are generated. Based on the quantitative analysis results, combined with the received comprehensive input data including predicted energy consumption demand and current battery status, calculations are performed according to the preset optimization strategy, and finally, the charging strategy optimization parameters for dynamically regulating the charging process of the battery pack are output.

6. The catenary-powered ship navigation energy consumption optimization and scheduling system according to claim 5, characterized in that, Based on the curvature feature analysis results and combined with the real-time status information of the vessel within the dynamic assessment area, the quantitative relationships between channel curvature, obstacle spatial distribution, and navigation path complexity within the area are analyzed and calculated, generating quantitative analysis results of navigation status and spatial distribution, including: By receiving the curvature feature analysis results and simultaneously acquiring the real-time status information of the ship within the dynamic evaluation area, comprehensive analysis data including channel boundary morphology features and the real-time status of the ship is obtained. The comprehensive analysis data is processed to identify the curvature extrema and their distribution characteristics on the boundary curves, which serve as key channel curvature points; at the same time, the spatial relationship between the ship's current position and heading and the key points is determined. Based on the distribution characteristics of key channel curvature points and the relative spatial relationships of ships, combined with obstacle data in electronic river charts, quantitative indicators characterizing channel curvature, obstacle spatial distribution density, and navigation path complexity are calculated. By performing comprehensive calculations and normalization on the quantitative indicators, structured quantitative analysis results are generated to describe the relationship between the navigation situation and spatial distribution within the current assessment area.

7. The catenary-powered ship navigation energy consumption optimization and scheduling system according to claim 6, characterized in that, By optimizing charging strategy parameters, the charging process of the battery pack is dynamically controlled, ensuring that the battery pack stores sufficient electrical energy for the segment's navigation needs and has a safety margin before entering the offline navigation segment. This includes: The charging strategy optimizes parameters and simultaneously acquires comprehensive input data on predicted energy consumption demand and current battery status, as well as detailed flight paths, as the basis for dynamic charging control decisions. Based on the charging strategy optimization parameters and decision-making criteria, and combined with the detailed navigation path, the remaining navigation distance of the ship in the current catenary power supply section is calculated as a constraint condition for determining the charging window. Based on the constraints of the rechargeable window and the optimization parameters of the charging strategy, combined with the charging characteristics of the battery pack, the required charging power command before entering the next offline navigation segment is calculated. The calculated charging current command is sent to the shipboard terminal for execution, and the battery status feedback is continuously received during the charging process until the battery pack's state of charge reaches the target value that meets the energy consumption requirements of the next offline navigation segment and leaves a safety redundancy.

8. The catenary-connected electric ship navigation energy consumption optimization and scheduling system according to claim 7, characterized in that, During the ship's voyage, the status of the contact wire and the power grid capacity are monitored in real time. When the power supply is sufficient, the cable is used for driving and charging. When entering the offline zone or experiencing a power outage, the system automatically switches to battery power and adjusts propulsion power in real time based on remaining range and battery level to achieve optimized energy consumption scheduling, including: During the ship's navigation, it continuously receives real-time data on the ship's location, contact network connection status, and real-time load capacity of the power grid from the ship's onboard terminal, and processes this data synchronously with the detailed navigation path to generate comprehensive monitoring data on the current navigation status and power grid capacity. Based on comprehensive monitoring data, the feasibility of the ship's current power supply mode is assessed in real time. If the assessment result is that the contact wire connection is normal and the power grid capacity is sufficient, an instruction to use cable drive and execute charging is generated. If the assessment result is that the ship enters the offline zone or the power supply is interrupted, an instruction to switch to battery power is generated. After the command to switch to battery power is executed, the remaining distance from the ship's current position to the next recoverable net power point or the end of the voyage is calculated based on the detailed navigation path. Combined with the real-time state of charge of the battery pack, the target propulsion power range required to meet the remaining distance is calculated. Based on the calculated target propulsion power range, a real-time propulsion power adjustment command is generated and sent to the shipboard power unit for execution, while continuously returning to the execution status to form a closed-loop energy consumption optimization scheduling.

9. A computing device, characterized in that, include: One or more processors; A storage device for storing one or more programs, which, when executed by the one or more processors, cause the one or more processors to perform the system as described in any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a program that, when executed by a processor, performs the system as described in any one of claims 1 to 8.

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