Vehicle Sensor-Cleaning System Using Multi-Wavelength Obstruction Classification
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Solution Overview
Problem
Vehicles face inefficiencies in cleaning sensors due to the resource-intensive nature of current cleaning methods, which expend air and washer fluid without distinguishing between types of obstructions, leading to excessive resource consumption.
Innovation Solution
A system that uses multiple lamps emitting different wavelengths to classify obstructions and selectively activate cleaning components, such as air and liquid nozzles, based on the type of obstruction, optimizing resource usage by minimizing the application of the most resource-consumptive cleaning actions for less difficult obstructions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the same cleaning actions are selected for all types of obstructions, then the most difficult type of obstruction can be removed, but resource consumption increases excessively
Solution Approach 1:
The system applies different cleaning actions based on the specific type of obstruction detected. By classifying obstructions into different types (e.g., water, dust, insects, snow) and selecting appropriate cleaning methods for each type, the system provides locally optimized cleaning quality rather than applying a uniform high-resource cleaning method to all cases.
Solution Approach 2:
The system changes the parameters of the cleaning process by selecting different cleaning actions (air blowing, washer fluid application, heating) based on the detected obstruction type. This parameter adaptation allows the system to use minimal resources for simple obstructions like water droplets while allocating more resources for stubborn obstructions like insect remains or snow.
2Reliability
If multiple cleaning components are activated simultaneously, then comprehensive cleaning is achieved, but resource expenditure increases
Solution Approach 1:
The cleaning system is segmented into multiple independent cleaning components (air nozzles, washer fluid nozzles, heating elements) that can be selectively activated. The control system divides the cleaning task by activating only the necessary components based on obstruction type, rather than running all components simultaneously for every cleaning event.
Solution Approach 2:
The system applies partial cleaning action by selecting only the necessary cleaning components for each specific obstruction type. For example, water droplets require only air blowing or heating, while insect remains may require both washer fluid and air blowing. This partial action approach avoids the excessive resource consumption of activating all cleaning components for every situation.
3Loss of substance
If classification of obstruction types is implemented, then resource usage is optimized, but system complexity increases
Solution Approach 1:
The system introduces an intermediary classification mechanism that analyzes sensor data to identify obstruction types before triggering appropriate cleaning actions. This intermediary layer (obstruction detection and classification system) acts as a mediator between the sensor and cleaning components, enabling intelligent resource allocation without requiring complex mechanical modifications to the cleaning hardware itself.
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
This approach reduces resource expenditure by tailoring cleaning actions to the specific type of obstruction, ensuring precise and efficient cleaning while conserving air and washer fluid, thereby enhancing sensor cleanliness and operational efficiency.
Implementation Method 1
at least three lamps positioned to illuminate the window; Each lamp is configured to generate different ranges of wavelengths than the other lamps
Data Source
AI summary
A system includes a sensor including a window; at least three lamps positioned to illuminate the window and be able to generate different ranges of wavelengths than one another; a cleaning component positioned to clean the window; and a computer communicatively coupled to the sensor, the lamps, and the cleaning component. The computer is programmed to activate the lamps and actuate the cleaning component based on data generated by the sensor during the activations of the lamps.