EV Range Estimation Using Real-Time Sensor Data
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Solution Overview
Problem
Existing electric vehicle autonomy estimation systems fail to accurately account for the driver's actual driving style and require extensive data on route topology, leading to unreliable range calculations.
Innovation Solution
A method that calculates optimized energy consumption based solely on vehicle sensor data, comparing actual energy use to a reference driving style, providing the driver with insights into potential range gains by adapting their driving habits without needing external database information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing autonomy estimation systems use route topology data and driver behavior characterization, then the reliability of calculated autonomy is improved, but the device complexity and data requirements increase
Solution Approach 1:
The patent extracts only the essential elements needed for autonomy estimation - specifically actual energy consumption data and basic driving style parameters - while eliminating the need for complex route topology databases and extensive sensor systems. This extraction approach maintains reliability by focusing on the most critical factors while reducing system complexity.
Solution Approach 2:
The system uses the vehicle's existing sensor data and onboard computer resources to perform autonomy estimation without requiring external databases or additional complex infrastructure. The vehicle essentially serves itself by utilizing its own operational data, thereby reducing device complexity while maintaining estimation reliability.
2Ease of operation
If prospective estimation of range on planned route is performed using predefined driving modes, then the driver can plan journeys, but the estimation accuracy deteriorates because neither driving mode corresponds exactly to actual driving behavior
Solution Approach 1:
Instead of using static predefined driving modes, the patent implements a dynamic approach that continuously characterizes the driver's actual driving style based on real-time sensor data. This dynamic characterization adapts to the driver's actual behavior patterns, providing accurate autonomy estimation for the specific driving mode being used while maintaining journey planning capabilities.
Solution Approach 2:
The system incorporates feedback mechanisms that continuously monitor actual energy consumption and driving parameters, then use this information to refine autonomy estimates. This feedback loop ensures that the estimation reflects the driver's actual behavior rather than relying on inaccurate predefined modes, thereby improving measurement precision while preserving ease of operation.
3Loss of information
If extensive data on route topology is collected for autonomy calculation, then the completeness of route information is improved, but the loss of time and computational resources increases
Solution Approach 1:
The patent extracts only the most relevant factors for autonomy estimation - primarily actual energy consumption data and basic driving parameters - while eliminating the need for extensive route topology databases. This selective extraction maintains sufficient information completeness for accurate estimation while dramatically reducing data collection and processing time.
Data Source
AI summary
The invention relates to a motor vehicle driving assistance method comprising at least one electric motor (4) powered by a battery (2) and capable of driving the drive wheels of the vehicle, wherein the method involves calculating an optimized consumption (Creal-Cexcès) for the vehicle from the actual power consumption (UI) of the vehicle and from values collected by sensors of the vehicle (Pchauff, Pclim, N, Text, br), over the same path that the vehicle is in the process of traveling, the optimized consumption corresponding to a reference driving style, and informing the driver of the distance (D) that he/she could travel using the power supply (Wdisp) available on-board the vehicle if he/she were to adopt the reference driving style, or else the driver is informed of the energy savings per unit of distance traveled that he/she might obtain if the reference driving style were adopted.