Section-Based EV Charging Planning for Faster Long-Distance Travel
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Solution Overview
Problem
Electric vehicle charging times are prolonged due to battery charging curves and state of charge (SOC) variations, especially when traveling long distances, as charging speed decreases with increased SOC, leading to increased travel time to reach a destination.
Innovation Solution
A method and apparatus for determining optimal charging stations and charging times along a driving path by using a charging plan model that considers vehicle speed, travel time, and battery SOC, incorporating environmental factors like road gradient and speed limits, to minimize overall travel time, including charging time, through a navigation device and smart charging planner.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If charging is performed for each charging station along the driving path, then the battery state of charge is maintained, but the total travel time is increased due to decreased charging speed at higher SOC levels
Solution Approach 1:
The system performs preliminary calculation of the optimal charging plan before departure by dividing the driving path into multiple sections and using a charging plan model to determine the best charging stations and charging amounts in advance. This preliminary action identifies the optimal charging strategy that minimizes total travel time while ensuring the battery SOC is maintained at appropriate levels throughout the journey, avoiding the need for reactive charging decisions that would increase travel time.
2Productivity
If charging amount is increased to reach destination faster, then travel time is reduced, but charging speed decreases due to battery protection characteristics
Solution Approach 1:
The system divides the driving path into multiple sections and determines optimal charging strategies for each section separately. By segmenting the journey, the system can plan charging amounts that are optimized for each specific section rather than attempting to charge excessive amounts at a single station, which would trigger battery protection mechanisms and reduce charging speed. This segmentation allows the system to maintain higher average charging speeds while still achieving the goal of minimizing total travel time.
3Reliability
If multiple charging stations are used along the driving path, then the battery SOC is maintained, but the complexity of charging planning increases
Solution Approach 1:
The system replaces complex manual charging planning with an automated computational model. The charging plan model, which includes an objective function and multiple constraints, automatically calculates the optimal charging strategy by processing driving path information, battery characteristics, and charging station data. This mechanical substitution of manual planning with automated computation significantly reduces the perceived complexity for the user while maintaining reliable battery SOC management across multiple charging stations.
Data Source
AI summary
A method of planning to charge an electric vehicle includes: determining a driving path based on a destination; dividing a prediction range on the driving path into a plurality of sections; obtaining driving environment information of the driving path; and applying the driving environment information to a charging plan model for each of the plurality of sections using and establishing a charging plan on the driving path by collectively calculating to find a minimized solution of the charging plan model for the plurality of sections. The charging plan model includes an objective function of travel time and battery state of charge (SOC). The objective function is defined based on a first model according to a longitudinal motion equation of the vehicle, a second model for the travel time, and a third model for the battery SOC.