Battery Vehicle Range Estimation Using Weighted Energy Loss Models
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Solution Overview
Problem
There is a need for accurate prediction of the range of battery-powered vehicles, especially in areas with limited charging infrastructure, to avoid unexpected charging needs.
Innovation Solution
A method and system for estimating energy consumption by a vehicle for a trip based on trip data, which includes identifying distance, duration, ambient temperature, and speed, and calculating energy consumption as a weighted sum of energy losses due to friction, temperature control, and air resistance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional range estimation methods are used, then the system is simple to operate, but the range prediction accuracy is insufficient
Solution Approach 1:
The patent segments the range estimation problem into multiple independent components: friction energy loss calculation, temperature control energy loss calculation, air resistance energy loss calculation, and auxiliary energy loss calculation. Each component is calculated separately using specific formulas and then summed to obtain the total energy consumption, improving accuracy without overwhelming system complexity
Solution Approach 2:
The system incorporates real-time vehicle sensor data (speed, temperature, location) and historical trip data to continuously refine and update the energy consumption model. This feedback mechanism allows the system to adapt to actual driving conditions and improve prediction accuracy over time while maintaining a manageable computational framework
2Measurement precision
If detailed energy consumption calculation is performed, then the range prediction accuracy is improved, but the computational time increases
Solution Approach 1:
The patent pre-calculates and stores key parameters such as vehicle mass, drag coefficient, rolling resistance coefficients, and temperature control power requirements. These pre-computed values are readily available during trip estimation, eliminating the need for time-consuming real-time calculations of these fundamental parameters while maintaining high estimation accuracy
3Measurement precision
If multiple energy loss factors are considered, then the estimation accuracy is improved, but the model complexity increases
Solution Approach 1:
The patent divides the energy consumption model into distinct segments: friction (E_friction), temperature control (E_temp), air resistance (E_air), and auxiliary systems (E_aux). Each segment has its own dedicated formula and parameter set, making the complex model easier to understand, implement, and maintain while comprehensively accounting for all major energy loss factors
Data Source
AI summary
Systems, methods, devices, and models for range estimation and analysis in battery powered vehicles are described. Energy consumption over vehicle trips is collected, to evaluate weighting factors for a weighted sum. The weighted sum is evaluated based on determined weighting factors and expected trip data, to determine an energy consumption of a trip or trips of a vehicle. Determined energy consumption for trips is used for evaluating suitability of the vehicle for performing the trips.