EV Range Prediction for Idle Battery Drain and No-Start Risk
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Solution Overview
Problem
Battery electric vehicles (BEVs) face range anxiety due to 'vampire drain,' where high-voltage batteries lose charge when idle, potentially depleting both high and low voltage batteries, leading to concerns about available range and startability upon return.
Innovation Solution
The system uses a vehicle's electronic control unit to predict range and state of charge based on current and future environmental conditions, providing users with actionable feedback through a human machine interface, including predictive range estimations and automated dispatching of charging services to ensure the vehicle remains operational during extended absences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Duration of action of stationary object
If the BEV is left unattended for extended periods, then the vehicle remains parked and accessible, but the battery loses charge due to vampire drain
Solution Approach 1:
The system performs preliminary actions by predicting future battery charge levels based on historical vampire drain data and environmental conditions before the vehicle is actually left unattended. This allows the system to proactively notify users of potential no-start conditions and automatically dispatch charging services in advance, preventing complete battery depletion.
Solution Approach 2:
The system implements continuous feedback by monitoring actual vampire drain against predicted values, using sensor data from the vehicle's electronic control unit to track battery charge levels, temperature, and usage patterns. This feedback loop enables the system to refine predictions and adjust automated charging dispatch timing to optimize battery maintenance while minimizing unnecessary charging operations.
2Measurement precision
If the battery charge is monitored continuously to predict range, then accurate predictions can be provided, but system complexity increases
Solution Approach 1:
The system leverages existing vehicle electronic control units and onboard sensors to perform self-monitoring of battery charge levels, temperature, and usage patterns. By utilizing already-present vehicle systems rather than adding dedicated external monitoring equipment, the patent achieves accurate range predictions while minimizing additional system complexity.
Solution Approach 2:
The electronic control unit performs multiple functions: it monitors battery charge levels, tracks vampire drain patterns, predicts future range, and triggers automated charging dispatch. This multi-functionality consolidates what could be separate complex systems into a single integrated unit, reducing overall system complexity while maintaining measurement precision.
3Reliability
If automated charging services are dispatched, then the vehicle remains operational, but additional services and infrastructure are required
Solution Approach 1:
The system introduces a communication interface as an intermediary between the vehicle's electronic control unit and external charging services. This interface translates vehicle needs into standardized charging requests and receives status updates, enabling automated charging dispatch without requiring direct integration with specific charging infrastructure providers, thus maintaining versatility.
Solution Approach 2:
The system dynamically adjusts charging parameters such as dispatch timing, charge amount, and charging rate based on predicted battery depletion timelines and environmental conditions. By optimizing these parameters, the system ensures vehicle operability while minimizing the frequency and duration of charging service interventions, reducing infrastructure demands.
Data Source
AI summary
Electric vehicle predictive range estimating systems and methods are provided herein. An example method includes determining an initial state of charge (SOC) for an energy source of a vehicle at a first point in time; determining one or more boundary conditions for the vehicle during a time frame extending from the first point in time to a second point in time, the one or more boundary conditions causing a loss in the energy source during the time frame; determining a predicted future SOC for the energy source based on the one or more boundary conditions and the initial SOC; and predicting an availability of a vehicle operating condition based on the predicted future SOC for the energy source.