Vehicle Energy Efficiency Guidance Using Driving Pattern Analysis
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Solution Overview
Problem
Conventional vehicle systems lack guidance for drivers to improve energy efficiency, as they only display energy efficiency values without providing insights into driving behaviors affecting energy consumption.
Innovation Solution
An energy efficiency management service providing server and system that analyze energy consumption rates of vehicles, identify driving patterns, and provide personalized improvement guides to enhance energy efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional energy efficiency display methods are used to show energy efficiency values to drivers, then drivers can grasp the energy efficiency of the vehicle, but drivers receive no guidance on how to improve energy efficiency
Solution Approach 1:
The system segments energy consumption analysis by electronic component (motor, air conditioning, other electronics) and by driving pattern type, providing targeted guidance for each segment rather than generic advice. This resolves the contradiction by delivering specific improvement guidance without requiring complete system redesign.
Solution Approach 2:
The system implements feedback by analyzing energy consumption data, determining driving patterns, and providing improvement guides that tell drivers how to adjust their behavior. This closes the information loop, transforming static display into dynamic guidance that helps drivers improve energy efficiency through actionable feedback.
2Loss of information
If detailed per-electronic component energy consumption analysis is provided to guide driver behavior, then energy efficiency improvement guidance is enhanced, but system complexity increases
Solution Approach 1:
The system divides overall energy consumption into segments by electronic component (motor, air conditioning, other electronics) and calculates separate consumption ratios for each. This segmentation enables detailed component-specific analysis while managing complexity through modular data processing for each component type.
Solution Approach 2:
The system applies local quality by providing different types of analysis and guidance tailored to specific driving patterns and component behaviors. Each component's energy consumption is analyzed with appropriate metrics and recommendations specific to that component's characteristics and usage patterns.
Data Source
AI summary
An energy efficiency management service providing server may include a communication module configured to communicate with external devices, and a processor operatively connected to the communication module and configured to determine per-electronic component energy consumption ratios relative to battery energy consumed over a predetermined time period based on energy efficiency-related data of a vehicle, determine a driving pattern type based on the per-electronic component energy consumption ratios, and generate an energy efficiency improvement guide based on the driving pattern type.