Distance Until Charge Estimation Using GPS Location Data
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Solution Overview
Problem
The fuel economy of plug-in hybrid electric vehicles (PHEVs) is not optimized due to inefficient battery usage, as existing methods lack an accurate method to predict the exact distance until the next charging event, leading to suboptimal operation between charge depleting and charge sustaining modes.
Innovation Solution
A method and system that estimate the 'Distance until Charge' (DUC) value using stored information from past charging events, incorporating GPS location data and historical driving patterns to adapt battery usage, extending the charge depleting mode to the exact distance until the next charging event.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If the PHEV operates in charge depleting mode to maximize electric energy usage, then fuel economy is improved, but the battery may be depleted before the next charging event, requiring premature switch to charge sustaining mode
Solution Approach 1:
The system performs preliminary estimation of the Distance Until Charge (DUC) value before the next charging event occurs. By predicting the DUC value based on historical charging location data and current trip information, the vehicle can proactively adjust battery usage in CD mode to ensure the battery reaches but does not fall below the charge sustaining threshold exactly when needed, preventing premature mode switching.
Solution Approach 2:
The system continuously monitors actual charging behavior and compares it with predicted DUC values. Historical data from previous charging events is fed back into the estimation algorithm to improve future predictions. This feedback mechanism allows the system to learn from actual user charging patterns and optimize battery usage strategies to maximize fuel economy while maintaining reliable charge availability.
2Reliability
If the PHEV switches to charge sustaining mode early to ensure battery availability, then reliability is maintained, but fuel economy deteriorates due to earlier engine operation
Solution Approach 1:
The system calculates the predicted DUC value in advance and uses it to determine the optimal point for switching from CD mode to CS mode. By knowing the estimated distance to the next charging event beforehand, the vehicle can maintain CD mode operation for the maximum possible distance, delaying engine operation and improving fuel economy while ensuring the battery will be available when needed.
3Measurement precision
If the system uses location-based historical data to estimate DUC value, then prediction accuracy is improved, but device complexity increases due to data storage and processing requirements
Solution Approach 1:
The system extracts only the essential elements needed for DUC estimation: geographic locations of charging events and distances traveled between them. By focusing on these key parameters rather than storing complete trip profiles or unnecessary vehicle operation data, the system achieves accurate prediction while minimizing data storage requirements and processing complexity.
Solution Approach 2:
The system creates a simplified probabilistic model that copies the essential patterns of charging behavior from historical data. Instead of storing and analyzing all raw historical data for each prediction, the system builds a probabilistic representation of charging patterns that can be efficiently queried and updated, reducing computational complexity while maintaining prediction accuracy.
Data Source
AI summary
A method and a system augment or improve a distance until charge (DUC) estimation for a vehicle such as a plug-in hybrid electric vehicle (PHEV) by using location information. Such location information may be provided by a global positioning system (GPS) or the like associated with the vehicle. The method and the system generally estimate the DUC value as a function of past driving pattern historical data that is relevant to a current driving situation. To this end, the method and the system ignore past driving pattern historical data that is not relevant to the current driving situation when estimating the DUC value.