Fluid Vehicle Route Optimization for Submarine Stealth and Range
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Solution Overview
Problem
Route planning for fluid vehicles, such as submarines, is complex due to their ability to operate in three-dimensional space without a fixed path and varying propulsion modes, which complicates range calculation and detection avoidance, differing significantly from land vehicles.
Innovation Solution
A method for calculating an optimal route for fluid vehicles that determines boundary parameters including mission profile, target position, environmental information, and internal state, while avoiding areas not to be traversed based on dynamic and static environmental data, and adjusting for detection probability and vehicle category.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Duration of action of moving object
If a submarine uses diesel drive for long range, then range is improved, but detection probability increases when snorkelling
Solution Approach 1:
The system dynamically adjusts the deployment profile and operating mode based on real-time conditions. The submarine transitions between different drive modes (diesel, electric, fuel cell) and deployment profiles (submerged, snorkelling, surface) to optimize the trade-off between range and detection probability. The route planning continuously adapts to changing environmental and mission parameters.
Solution Approach 2:
The system changes operational parameters such as deployment profile, drive mode, speed, and depth to resolve the contradiction. By adjusting these parameters dynamically, the submarine can extend range while minimizing detection risk through optimized operational states.
2Object-affected harmful factors
If a submarine uses electric drive for stealth, then detection probability decreases, but range is limited
Solution Approach 1:
The submarine is equipped with multiple drive systems (diesel, electric, fuel cell) that can be used interchangeably depending on mission requirements. This multi-functionality allows the vehicle to switch between stealth-oriented electric mode and range-oriented diesel/fuel cell modes, resolving the contradiction between detection probability and range.
Solution Approach 2:
The system dynamically selects and switches between different drive modes based on real-time mission parameters, environmental conditions, and remaining range. This dynamic adaptation allows optimization of both stealth and range throughout the mission.
3Adaptability or versatility
If route planning considers three-dimensional space freedom, then route flexibility increases, but calculation complexity increases
Solution Approach 1:
The three-dimensional route planning problem is segmented into multiple two-dimensional route segments at different depth levels. Each segment is calculated independently based on local constraints and objectives, then combined to form the complete three-dimensional route. This segmentation reduces calculation complexity while maintaining route flexibility.
Solution Approach 2:
The system utilizes the vertical dimension (depth) as an additional degree of freedom to resolve horizontal routing conflicts and optimize the overall route. By distributing route calculation across multiple depth levels and using depth transitions, the system achieves three-dimensional route flexibility while managing computational complexity through layered processing.
4Duration of action of moving object
If a submarine uses fuel cell for underwater travel, then range underwater is improved, but top speed is reduced
Solution Approach 1:
The system dynamically adjusts speed and power output based on the selected drive mode and mission phase. When operating on fuel cells, the system optimizes speed within the reduced power envelope, while transitioning to diesel or electric modes when higher speeds are required. This dynamic adaptation resolves the contradiction between underwater range and top speed.
Solution Approach 2:
The submarine employs periodic alternation between different drive modes and speed regimes. High-speed segments use diesel or electric propulsion, while low-speed endurance segments use fuel cells, optimizing the overall mission profile by matching propulsion mode to speed requirements.
Data Source
AI summary
The invention relates to a method for calculating an optimal route for a fluid vehicle, in particular an underwater vehicle, comprising the following method steps: a) determining the edge parameters, and b) determining the optimal route. In step a), in particular three-dimensional environment information is acquired and further fluid vehicles are searched by means of a sensor and detected as a dynamic environment information. In step b), regions which are not to be passed through are determined on the basis of this information.