EV Range Estimation Using Route-Based Battery SOC Prediction
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Solution Overview
Problem
Range anxiety in electric vehicles is exacerbated by limited driving range estimates due to uncertainties in driving conditions, battery state, and inaccuracies in current and state of charge measurements, leading to sub-optimal operating decisions and accelerated battery aging.
Innovation Solution
A method and system for range estimation in electric vehicles that utilizes a controller to simulate battery consumption along potential routes, considering factors like traffic, grade, and curvature, and displays a battery SOC consumption map with range indicators, iteratively refining predictions based on vehicle location and battery state.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional SOC estimation methods are used based on current and voltage measurements, then the estimation process is simple, but the accuracy is insufficient due to measurement errors and battery non-linearity
Solution Approach 1:
The patent introduces a prediction model as an intermediary between raw measurements and SOC estimation. This model uses multiple inputs including current, voltage, temperature, and driving conditions to compute SOC, thereby improving accuracy while managing complexity through a structured computational approach rather than direct measurement
Solution Approach 2:
The system performs preliminary actions by pre-processing measurement data and running prediction models before final SOC determination. This includes filtering sensor inputs, predicting future SOC based on driving patterns, and preparing correction factors in advance to improve real-time estimation accuracy
2Reliability
If drivers reserve a buffer of battery capacity due to range anxiety, then range uncertainty is reduced, but trip continuity is interrupted and battery aging accelerates
Solution Approach 1:
The patent implements feedback mechanisms where the system continuously monitors actual driving conditions, compares predicted SOC with actual SOC, and adjusts range predictions accordingly. This feedback loop builds driver confidence in the accuracy of range estimates, reducing the need for conservative buffer reservations and enabling more efficient battery utilization
Solution Approach 2:
The system dynamically changes the parameters used in SOC estimation based on driving conditions, battery state, and environmental factors. By adapting the estimation model parameters in real-time, the system provides more accurate and reliable range predictions across varying operating conditions, reducing range anxiety without requiring excessive battery buffers
3Measurement precision
If detailed route simulation is performed for multiple potential destinations, then range estimation accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent segments the range estimation process into hierarchical levels: quick estimates for immediate decisions and detailed simulations for longer-term planning. The system divides potential destinations into zones based on current SOC and performs appropriate levels of analysis for each, reducing overall computational burden while maintaining accuracy where needed
Solution Approach 2:
The system performs partial simulation for all potential destinations and excessive (detailed) simulation only for selected candidates. This approach provides sufficient accuracy for decision-making without the full computational cost of exhaustive detailed simulation of every possible destination
Data Source
AI summary
Methods and systems for estimating driving range for an electric vehicle. With a given vehicle at a given location and given battery state, which may include battery state of charge, a control system identifies a plurality of potential destinations or routes in different directions from the vehicle. For each destination or route, the control system then uses terrain, traffic and/or other data, along with the battery state, an expected battery state of charge trajectory is calculated. These calculations are used to map the potential range for driving the vehicle. Analogous methods and systems are disclosed for fueled vehicles.