Route-Based Distance to Empty Calculation for Vehicles
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Solution Overview
Problem
Current systems lack an accurate method for predicting the distance to empty (DTE) driving range in vehicles powered by on-board batteries, especially due to inadequate charging infrastructure and varying energy consumption patterns.
Innovation Solution
A DTE prediction tool that partitions a known driving route into road segments, estimates energy consumption for each segment, and uses a feedback loop with a correction factor to provide continuous and accurate range estimates based on available battery charge and energy consumption rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a DTE prediction system is implemented using simple average energy consumption rates, then the system complexity is reduced, but the measurement precision of DTE prediction deteriorates
Solution Approach 1:
The driving route is divided into multiple road segments, each with its own energy consumption characteristics. The system partitions the route based on factors like elevation changes, traffic conditions, and road type, then calculates energy consumption for each segment individually rather than using a single average rate for the entire journey.
Solution Approach 2:
The system applies different energy consumption rates to different road segments based on local conditions. Each segment is assigned a specific energy consumption rate that reflects its unique characteristics (e.g., uphill segments consume more energy, highway segments consume less), providing locally optimized predictions rather than a uniform global average.
2Measurement precision
If real-time feedback loops with correction factors are implemented, then the measurement precision of DTE prediction improves, but the device complexity increases
Solution Approach 1:
The system implements a feedback loop that continuously monitors actual energy consumption against predicted consumption. A correction factor is calculated based on the difference between actual and predicted values, then applied to subsequent DTE predictions. This feedback mechanism progressively refines the accuracy of predictions without requiring complete system redesign.
3Loss of information
If continuous DTE predictions are provided throughout the journey, then the information availability for drivers improves, but the loss of time for calculations increases
Solution Approach 1:
The system performs preliminary calculations by pre-processing route data and identifying key road segments with significant energy consumption characteristics before the journey begins. This allows the system to provide rapid DTE updates during travel without performing complete recalculations, reducing real-time computational burden while maintaining continuous information availability.
Data Source
AI summary
A vehicle may include: at least one power source; a plurality of wheels; a motor configured to drive at least one of the plurality of wheels with energy stored in the power source; and at least one processor configured to: break a received route into a plurality of segments; and calculate a route energy consumption rate correction factor (RECF) of a current segment as a function of the following received values: a RECF of a previous segment, an observed energy consumption rate, and an estimated energy consumption rate.