EV Range Prediction Using Weather and Mobility Profiles
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Solution Overview
Problem
Extreme temperatures significantly impact the range of electric vehicles (EVs) due to their effect on battery performance, making it challenging for users to predict and prepare for variations in driving range, especially in extreme weather conditions.
Innovation Solution
A system that predicts the range of an electric vehicle based on weather conditions by integrating future location data, mobility profiles, and weather forecasts, providing users with notifications and recommendations to optimize their journeys and avoid unexpected range reductions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If weather forecast data is integrated into range prediction, then prediction accuracy is improved, but system complexity increases
Solution Approach 1:
The system performs preliminary actions by obtaining weather forecast data in advance for future time periods and locations, and pre-calculating the impact on EV range before the user needs the information. This allows the complex weather-related calculations to be completed beforehand, reducing real-time computational requirements while maintaining high prediction accuracy.
Solution Approach 2:
The system introduces an intermediary component that acts as a bridge between weather forecast data and range prediction. This intermediary processes and translates complex weather information into standardized parameters that can be easily integrated with the EV's battery model, simplifying the overall system architecture while improving prediction accuracy.
2Reliability
If future location prediction is used to calculate range forecast, then user preparedness is improved, but computational requirements increase
Solution Approach 1:
The system uses preliminary action by determining future location predictions in advance based on historical usage data and user patterns. By pre-calculating where the EV will be located in future time periods and obtaining corresponding weather forecasts for those locations beforehand, the system reduces computational burden during actual use while providing reliable range forecasts for user planning.
Solution Approach 2:
The system applies partial action by focusing computational resources on calculating range forecasts for specific future time periods and locations that are most relevant to the user's needs, rather than performing exhaustive calculations for all possible scenarios. This selective approach provides sufficient user preparedness information without requiring excessive computational power.
3Measurement precision
If weather conditions are considered in range prediction, then range accuracy in extreme weather is improved, but data processing complexity increases
Solution Approach 1:
The system applies local quality by tailoring the range prediction processing to specific weather conditions and locations. Different processing methods and parameters are used depending on the local weather forecast data and geographic location, allowing the system to accurately handle extreme weather conditions in each specific context without requiring a single complex universal processing framework.
Data Source
AI summary
A method, apparatus, and computer program product are provided for predicting range of an electric vehicle. The system may comprise at least one memory configured to store computer program code and at least one processor configured to execute the computer program code to at least determine future location prediction data for the electric vehicle based on a mobility profile, wherein the mobility profile comprises with historical usage data for the electric vehicle. The computer program code further comprises code to retrieve weather data from a weather service provider, wherein the weather data is associated with the future location prediction data of the electric vehicle and the weather data includes at least temperature data associated with the future location prediction data of the electric vehicle. Further, the computer program code comprises code to calculate a range prediction value for the electric vehicle based on the future location prediction data and the weather data, for predicting the range of the electric vehicle. Also, the computer program code comprises code to provide a notification associated with the predicted range of the electric vehicle to a user device.