Suction-Powered Pool Robot Turbine Energy Harvesting Control
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Solution Overview
Problem
Suction-powered pool cleaning robots face challenges in efficiently navigating pool surfaces, detecting obstacles, and adapting to changing suction conditions due to limitations in sensing and control systems, leading to potential sticking or ineffective cleaning.
Innovation Solution
The robot incorporates a turbine-driven electrical generator, sensors for rotation and suction information, and an electronic controller that learns propagation patterns to control its operation, including gear shifting and alert systems, to adapt to different pool conditions and obstacles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the robot uses predetermined paths and mechanical elements for navigation, then the control system is simple, but the robot cannot adapt to changing suction conditions and obstacles
Solution Approach 1:
The patent implements feedback mechanisms where sensors detect propagation parameters (suction levels, speed, direction) and feed this information back to the controller. The controller learns from this feedback and adjusts navigation in real-time, enabling adaptation to changing suction conditions while maintaining manageable system complexity through intelligent control algorithms.
Solution Approach 2:
The robot employs self-learning capabilities where the controller automatically adapts navigation patterns based on accumulated sensor data without external intervention. This self-service approach allows the system to improve its performance over time by learning optimal paths and suction utilization strategies, reducing the need for complex pre-programming.
2Productivity
If the robot follows predetermined paths, then the navigation is simple to implement, but the cleaning efficiency decreases when obstacles are present
Solution Approach 1:
The patent transforms static predetermined paths into dynamic adaptive trajectories. The navigation system continuously adjusts the robot's path based on real-time sensor inputs about obstacles and pool conditions, allowing the robot to maintain high cleaning efficiency by dynamically rerouting around obstacles while covering the entire pool surface.
Solution Approach 2:
The robot performs preliminary scanning and learning of pool characteristics before executing the main cleaning task. By预先 detecting obstacles and learning propagation patterns during initial operation, the system prepares adaptive navigation strategies that enhance cleaning efficiency without requiring overly complex real-time decision-making during the actual cleaning process.
3Productivity
If the robot operates without learning capabilities, then the device complexity is low, but the robot cannot optimize its propagation patterns
Solution Approach 1:
The electronic controller implements self-learning functionality that automatically optimizes propagation patterns by analyzing sensor data from multiple cleaning cycles. The system serves itself by continuously improving its navigation efficiency and suction utilization without requiring external reprogramming or complex manual configuration, achieving productivity optimization through autonomous adaptation.
Solution Approach 2:
The patent replaces traditional mechanical navigation systems with intelligent electronic control that uses sensor data and learning algorithms to optimize propagation patterns. This substitution of mechanical determinism with electronic intelligence enables the robot to adaptively optimize its movement patterns based on actual pool conditions, significantly improving cleaning productivity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system enables the robot to effectively navigate pool surfaces, detect obstacles, and adjust its cleaning path, improving cleaning efficiency and preventing sticking by using real-time sensor data to control its movement and suction levels.
Implementation Method 1
a turbine at least partially disposed within the fluid path so as to extract energy from flow of fluid through the fluid path
Implementation Method 2
an electrical generator for providing power thereto and adapted to be driven by the turbine
Data Source
AI summary
A suction-powered pool cleaning robot that may include a fluid outlet, adapted for connection to a suction hose; a fluid inlet, with a fluid path between the fluid inlet and the fluid outlet; a turbine at least partially disposed within the fluid path so as to extract energy from flow of fluid through the fluid path; an electrical generator for providing power thereto and adapted to be driven by the turbine; a sensor arranged to generate rotation information indicative of a speed of rotation of the turbine; and an electronic controller that is arranged to control an operation of the suction-powered pool cleaning robot in response to at least the rotation information.