Vehicle Air Intake Control Using Predicted Roadside Pollution
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Solution Overview
Problem
Existing vehicle air intake systems fail to effectively predict and adjust to external air pollution levels in real-time, leading to potential health risks for occupants due to unpredictable pollutant entry.
Innovation Solution
A method using a pollution sensor and visual recording unit to identify interior pollution levels, predict external air pollution based on visual information and semantic analysis, and regulate air intake using machine learning models to minimize pollutant entry.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If external air intake is continuously adjusted based on real-time pollution sensing, then occupant health protection is improved, but system complexity increases due to multiple sensors and processing units
Solution Approach 1:
The patent combines multiple sensing functions (visual recording, pollution detection, position determination) into a unified air quality management system that processes information through a single evaluation unit, reducing overall system complexity while maintaining comprehensive monitoring capabilities
Solution Approach 2:
The patent introduces an evaluation unit as an intermediary component that processes data from multiple sensors and determines air intake adjustment decisions, simplifying the control architecture by centralizing the decision-making logic in a dedicated processing unit
2Measurement precision
If visual information processing and machine learning are used to predict pollution levels, then air quality prediction accuracy is improved, but computational load and processing time increase
Solution Approach 1:
The patent performs visual information processing and pollution prediction in advance before pollutants actually enter the interior space, allowing the system to proactively adjust air intake settings ahead of time, thereby reducing the perceived processing delay and enabling preventive action
Solution Approach 2:
The evaluation unit autonomously processes visual information and pollution sensor data without requiring external intervention, making real-time predictions and automatically adjusting air intake based on detected patterns and learned models
3Object-affected harmful factors
If external air intake is reduced or closed to prevent pollutant entry, then occupant health protection is improved, but interior air quality may deteriorate due to insufficient ventilation
Solution Approach 1:
The patent dynamically adjusts the external air intake based on real-time and predicted pollution levels, transitioning between fully open, partially restricted, and closed states as conditions change, ensuring optimal balance between preventing pollutant entry and maintaining adequate ventilation
Solution Approach 2:
The system continuously monitors interior pollution levels and uses this feedback to adjust air intake settings, ensuring that ventilation requirements are met while preventing pollutant accumulation by adapting air intake based on actual interior air quality conditions
4Measurement precision
If multiple sensors and processing units are added to the vehicle, then air quality monitoring capability is improved, but vehicle cost increases
Solution Approach 1:
The patent designs the air quality management system to perform multiple functions including visual pollution detection, chemical pollution sensing, position-based pollution prediction, and automatic air intake control, allowing a single integrated system to replace what would otherwise require multiple separate systems
Data Source
AI summary
A method for adjusting external air intake in an interior of a vehicle involves continuously identifying an interior pollution level during a driving operation of the vehicle using recorded signals of a pollution sensor arranged in the interior. A pollution level of external air on a section of road ahead of the vehicle is predicted and the external air intake is automatically regulated depending on the predicted pollution level of the external air.