Vehicle System Calibration Using Distributed Weather Data
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Solution Overview
Problem
Existing vehicle systems face challenges in adapting to localized weather conditions due to imprecise weather forecasts and variations in atmospheric conditions, leading to inefficient performance and increased energy consumption.
Innovation Solution
A computer-implemented method executed by a vehicle computing system that requests and processes weather data to dynamically adjust vehicle systems, considering secondary factors, and optimizes routes based on weather conditions to enhance performance and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If weather data from remote locations is used for vehicle system calibration, then the adaptability to localized weather conditions is improved, but the measurement precision of weather data deteriorates due to distance from measurement points
Solution Approach 1:
The system segments the weather data collection by utilizing multiple vehicles as distributed measurement points. Each vehicle collects and reports local weather data, creating numerous segmented measurement locations across the service area, thereby improving both coverage and precision simultaneously
Solution Approach 2:
The system implements feedback by continuously collecting weather data from multiple vehicles, comparing it with forecast data, and using the discrepancies to improve future weather predictions and vehicle system calibrations. This feedback loop progressively enhances measurement precision while maintaining broad adaptability
2Force
If vehicle systems are adjusted based on forecasted weather data, then the predictive capability is improved, but the reliability of calibration deteriorates due to inaccuracy in weather predictions
Solution Approach 1:
The system merges forecasted weather data with actual measured weather data from multiple vehicles to create a more reliable calibration basis. By combining predictive information with empirical observations, the system maintains predictive capability while significantly improving calibration reliability through data validation
Solution Approach 2:
The system performs preliminary vehicle system adjustments based on forecasted weather conditions before the actual weather events occur. This preliminary action allows the vehicle systems to be pre-adapted to expected conditions while maintaining the flexibility to refine calibrations based on actual measured data
3Quantity of substance
If multiple vehicles contribute weather data to a service area, then the quantity of weather data is improved, but the device complexity of the data collection system deteriorates
Solution Approach 1:
Each vehicle independently collects, processes, and reports its own weather data without requiring complex centralized collection infrastructure. The vehicles self-service the data collection function by using their existing sensors and communication capabilities, thereby increasing data quantity while minimizing system complexity
Solution Approach 2:
The system uses vehicles' existing multi-functional capabilities (sensors, processors, communication systems) for weather data collection in addition to their primary transportation functions. This universal use of existing vehicle systems avoids adding dedicated complex data collection infrastructure
Data Source
AI summary
A computer-implemented method includes requesting weather data from a remote location. The illustrative embodiment further includes determining if one or more vehicle systems should be adjusted, based at least in part on the requested weather data. The illustrative embodiment additionally includes adjusting one or more vehicle systems contingent at least in part on the determining. The illustrative embodiment further includes repeating the determining and adjusting until no weather data remains for processing.