EV Charging Routing Using Shared Driver Preference Data
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing systems lack efficient methods for routing electric vehicles to optimal charging stations based on individual user preferences and vehicle-to-vehicle communication, leading to suboptimal charging experiences.
Innovation Solution
A system and method that utilize vehicle-to-vehicle communication and a centralized server to determine charging locations based on shared preferences, enabling vehicles to route to charging stations used by other vehicles with similar preferences, optimizing the charging process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a centralized server uses vehicle-to-vehicle communication to determine charging locations based on shared preferences, then charging efficiency and user satisfaction are improved, but system complexity and communication overhead increase
Solution Approach 1:
A centralized server acts as an intermediary between vehicles and charging stations, receiving charging requests from vehicles, determining optimal charging locations based on shared preferences, and routing vehicles to appropriate stations. This mediator approach resolves the contradiction by centralizing the complex decision-making logic in the server rather than requiring complex onboard systems in each vehicle, thereby improving charging efficiency while managing system complexity through centralized control.
2Loss of time
If vehicles are routed to charging stations used by other vehicles with similar preferences, then travel time is reduced and charging convenience is improved, but loss of information about individual vehicle needs increases
Solution Approach 1:
The system implements feedback mechanisms where vehicles communicate their charging needs, preferences, and experiences to the centralized server. The server uses this feedback information to continuously refine routing decisions, matching vehicles with charging stations that best suit their specific needs while leveraging patterns from similar vehicles. This feedback loop reduces travel time by directing vehicles to proven effective stations while preserving individual vehicle information through ongoing communication.
Solution Approach 2:
The system performs preliminary actions by pre-processing charging request information from multiple vehicles and pre-determining optimal charging locations based on aggregated preferences. When a vehicle needs charging, the routing decision is already prepared based on prior analysis of similar vehicles' needs and experiences, reducing travel time while maintaining accuracy about individual vehicle requirements through the pre-established preference profiles.
Data Source
AI summary
An example operation includes one or more of receiving, from a vehicle, a request for a charge, determining, based on one or more preferences related to the vehicle, a charging location used by another vehicle with the same preferences, and routing the vehicle to the charging location based on the determining.