Travel Energy Estimation for Electric Vehicles Using Speed Models
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Solution Overview
Problem
Existing methods for estimating travel energy of electric vehicles are not accurate enough to support the efficient utilization of green power and prevent power shortages, as they do not account for real-world traffic conditions and speed changes that significantly affect energy consumption.
Innovation Solution
A travel energy estimating device that divides a route into sections based on speed change prediction points, using speed models to estimate travel energy by considering actual speed transitions such as traffic signals and turns, allowing for more precise calculations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional travel energy estimation methods are used, then the estimation process is simple, but the accuracy of travel energy estimation is insufficient
Solution Approach 1:
The route is divided into multiple sections based on speed change prediction points (such as traffic signals, intersections, and turns). Each section is modeled separately with specific speed patterns, allowing accurate energy estimation for each segment while maintaining manageable system complexity through modular processing
Solution Approach 2:
Speed models are pre-established for different route sections based on typical speed changes at prediction points. These pre-defined models capture acceleration, deceleration, and idle patterns in advance, enabling accurate energy estimation without real-time complex calculations
2Loss of energy
If green power utilization is increased, then CO2 emissions are reduced, but power shortage risk increases due to inaccurate energy estimation
Solution Approach 1:
The system provides feedback on accurate travel energy estimation to route planning and charging station selection processes. This feedback enables reliable determination of whether green power suffices for the trip, preventing power shortage while optimizing CO2 emission reduction through informed green power utilization decisions
Data Source
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AI summary
A travel energy estimating device includes: a route acquisition unit configured to acquire a route that is composed of a road link on which a target vehicle being an electric vehicle is planned to travel; a route division unit configured to divide the route into one or more sections, each section including a speed change prediction point at which a change in a travel speed of the target vehicle is expected, each section being composed of one or a plurality of road links; a speed model acquisition unit configured to acquire a speed model for each section, the speed model indicating a temporal transition of the travel speed of the target vehicle; and a travel energy estimation unit configured to estimate travel energy of the target vehicle during traveling on the route, based on the speed model acquired for each section.