EV Trailer Drag Modeling for Accurate Towing Range Estimation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Battery electric vehicles (BEVs) face significant range reduction while towing, and the underdeveloped charging infrastructure complicates planning, leading to potential strandings due to unclear range capabilities under towing conditions.
Innovation Solution
The implementation of a system using cameras and sensors to detect trailers, determine their drag coefficient through machine learning, and estimate vehicle range, with the option to adjust vehicle parameters for improved airflow and range extension.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If BEV towing capability is enhanced to match ICE vehicles, then towing performance is improved, but range reduction becomes more significant
Solution Approach 1:
The system performs preliminary actions by detecting trailer connection status, characterizing trailer aerodynamic properties (drag coefficient and frontal area) before towing begins, and pre-calculating adjusted range estimates. This allows the BEV to account for towing conditions in advance, providing accurate range information to drivers before they embark on towing trips, thus resolving the contradiction between maintaining towing capability and preserving range.
2Ease of operation
If charging infrastructure is expanded to match gas refueling infrastructure, then charging accessibility is improved, but infrastructure development complexity increases
Solution Approach 1:
The system incorporates feedback mechanisms by continuously monitoring actual energy consumption during towing, comparing it with estimated values, and refining the aerodynamic characterization and range calculation models. This feedback loop enables the system to improve charging accessibility through software-based adaptations rather than requiring proportional infrastructure expansion, effectively resolving the contradiction between charging accessibility and infrastructure complexity.
3Measurement precision
If trailer aerodynamic properties are precisely characterized to improve range estimation, then measurement precision is improved, but system complexity increases
Solution Approach 1:
The system employs copying by creating aerodynamic profiles and drag coefficient values for different trailer types without requiring complex physical measurement equipment. Instead of directly measuring aerodynamic properties in real-time, the system uses pre-characterized data copies that can be matched to detected trailer types, achieving precise range estimation while minimizing system complexity.
4Use of energy by moving object
If vehicle parameters are adjusted to improve airflow and extend range, then energy efficiency is improved, but vehicle control complexity increases
Solution Approach 1:
The system applies dynamics by enabling adjustable ride height in air-suspended BEVs, allowing the vehicle to dynamically adapt its aerodynamic profile when towing. The system can raise or lower the vehicle body to optimize airflow underneath, improving energy efficiency while maintaining manageable control complexity through automated adjustments based on detected towing conditions.
Data Source
AI summary
Systems and methods for modeling electric vehicle towing are disclosed herein. An example method includes determining that a trailer is connected to a vehicle, generating a surface mapping of the trailer based on output of a sensor assembly of the vehicle, predicting a drag coefficient of the trailer based on the surface mapping, estimating a drag force based on the drag coefficient and the surface mapping, calculating an estimated range for the vehicle based on the drag force, and displaying the estimated range on a human machine interface of the vehicle.