Vehicle Battery Charging Judgment via Consumption History Correlation
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Solution Overview
Problem
Users of electric and hybrid vehicles face difficulty in determining the necessity of battery charging due to the lack of comprehensive information beyond battery remaining capacity in existing information providing apparatuses.
Innovation Solution
An information providing apparatus that generates charge necessity judgment information based on power consumption history and correlates it with battery remaining capacity, providing users with a clear indication of whether battery charging is necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If only battery remaining capacity is provided to the user, then the information providing apparatus is simple, but the user cannot properly judge whether battery charging is necessary
Solution Approach 1:
The power consumption amount history is segmented by day attributes (weekday/weekend, season, weather) to create multiple separate history datasets. This segmentation allows the system to select and compare relevant historical data without processing all possible data simultaneously, reducing computational complexity while providing comprehensive charging judgment information.
Solution Approach 2:
The system pre-calculates and stores power consumption amount histories for different day attributes before they are needed for charging judgment. By preparing this historical data in advance and organizing it by attributes, the system enables rapid comparison with current power consumption to determine charging necessity, without requiring complex real-time analysis.
2Measurement precision
If power consumption history data is collected and processed, then charging necessity judgment accuracy is improved, but information processing time and computational load increase
Solution Approach 1:
The system applies different historical data selection strategies based on the specific day attribute being evaluated. By matching only the relevant attributes (e.g., comparing current weekday power consumption with historical weekday data under similar weather conditions), the system achieves high judgment accuracy while minimizing the amount of data that needs to be processed.
Solution Approach 2:
The system compares current power consumption with historical data for each day attribute separately, performing partial comparisons rather than a comprehensive analysis of all historical data at once. This approach provides sufficient accuracy for charging judgment while significantly reducing processing time and computational resources required.
Data Source
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AI summary
An information providing apparatus for vehicle has a remaining capacity detecting section 110 that detects a remaining capacity of a battery; a power consumption amount detecting section 130 that detects a power consumption amount of the battery; a power consumption amount history generating section 130 that generates a power consumption amount history on the basis of the power consumption amount detected by the power consumption amount detecting section 130; a charge necessity judgment information generating section 130 that generates, on the basis of the power consumption amount history generated by the power consumption amount history generating section 130, charge necessity judgment information which is information foruser's judgment about whether or not charging of the battery is necessary; and a providing section 150 that provides information of the remaining capacity of the battery and the charge necessity judgment information with these information correlated with each other to the user. The information providing apparatus can properly provide the information for user' s judgment about whether or not charging of the battery to the user.