EV Charging Navigation Optimizing Load Distribution
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Solution Overview
Problem
The existing electric vehicle charging systems face issues such as power grid overload and long waiting times at charging stations, especially when multiple vehicles charge simultaneously, leading to inefficient use of charging capacity and prolonged charging times.
Innovation Solution
A method and device that navigate electric vehicles to charging stations based on calculating the minimum time period required to arrive, wait, and charge, utilizing a node connection matrix and traffic information to optimize routing and charging station selection, ensuring maximum charging power while maintaining grid stability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If multiple electric vehicles charge simultaneously at one charging station, then charging power is maximized, but power grid overload and power loss occur
Solution Approach 1:
The system segments the charging load by directing different electric vehicles to different charging stations based on real-time status information. The navigation system divides the charging demand across multiple stations (first charging station, second charging station, etc.) to prevent concentration of load at a single location, thereby avoiding power grid overload while maintaining efficient charging power utilization.
2Productivity
If numerous electric vehicles arrive at one charging station for charging, then charging capacity is utilized, but waiting time increases significantly
Solution Approach 1:
The system segments the vehicle flow by providing differentiated navigation routes to multiple charging stations. Vehicles are directed to less congested stations based on real-time status, distributing the demand across multiple locations. This reduces queuing and waiting time at individual stations while maintaining overall high charging capacity utilization across the network.
Solution Approach 2:
The navigation system incorporates real-time status information from charging stations (availability, queue length, charging speed) to dynamically adjust navigation recommendations. This feedback mechanism allows the system to guide vehicles to stations with optimal waiting times, continuously adapting to changing conditions to minimize overall waiting time while maintaining efficient capacity utilization.
3Loss of time
If electric vehicles use fast charging, then charging time is reduced, but power grid impact increases
Solution Approach 1:
The system applies different charging strategies to different vehicles based on their specific needs and real-time grid conditions. Fast charging is directed to vehicles with urgent needs or when grid capacity is available, while other vehicles may be directed to slower charging options. This localized optimization allows fast charging benefits to be realized without uniformly increasing power grid impact.
Solution Approach 2:
The system segments the charging demand by distributing fast charging requests across multiple charging stations rather than concentrating them at one location. This spatial segmentation allows the power grid to handle the total fast charging load more effectively by distributing the power draw across different grid connection points, reducing peak impacts while maintaining short charging times for vehicles.
Data Source
AI summary
A method and a device for navigating an electric vehicle in charging are provided. The method comprises: S1, obtaining a navigation area, wherein the navigation area comprises a plurality of charging stations; S2, receiving a charging request from an electric vehicle in the navigation area; S3, obtaining a plurality of first time periods according to the electric vehicle and the plurality of charging stations; S4, selecting a minimum first time period from the plurality of first time periods; and S5, navigating the electric vehicle to a charging station corresponding to the minimum first time period.