EV Charging Route Planning With Dynamic Station Reservation
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Solution Overview
Problem
Conventional methods for electric vehicle routing fail to consider uncertainty in waiting time, charging time, driving preference, driving habits, and vehicle state of charge, leading to inefficient route planning and sparse charging station availability along optimal traffic routes.
Innovation Solution
A dynamic route planning system integrated with an infotainment system, navigation system, battery management system, and processor that receives user preferences and road conditions to determine optimal routes with charging stations, updating routes based on power consumption and charging station availability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If conventional map application route planning is used to ensure better traffic route, then travel time is reduced, but charging station availability becomes sparse
Solution Approach 1:
The system dynamically adjusts the routing strategy based on the vehicle's state of charge and charging preferences. When battery level is low or charging preference is high, the system prioritizes routes with charging stations even if they are longer, whereas when battery is sufficient, it selects the shortest route regardless of charging station availability.
Solution Approach 2:
The system changes the routing parameters (weight of distance vs. weight of charging station proximity) based on the vehicle's current state. The cost function dynamically adjusts these parameters according to state of charge levels and user-defined charging preferences, transforming the static routing problem into a dynamic one that adapts to real-time conditions.
2Reliability
If frequent charging is required due to limited battery power, then energy supply reliability is improved, but travel time increases
Solution Approach 1:
The system performs preliminary identification of charging stations along the planned route and pre-calculates optimal charging points based on the vehicle's current battery state and destination. This allows the vehicle to proactively plan charging stops rather than reacting when battery is depleted, optimizing the balance between energy reliability and travel time.
3Measurement precision
If user has to manually research charging stations before trip, then charging station selection accuracy is improved, but preparation time increases
Solution Approach 1:
The system automatically performs the research and selection of charging stations by integrating with mapping applications and charging station databases. It autonomously identifies suitable charging stations along the route, evaluates their availability and characteristics, and presents optimized recommendations to the user, eliminating the need for manual research while maintaining high selection accuracy.
Data Source
AI summary
Embodiments relate to a dynamic routing system, comprising a memory that stores computer executable components, and a processor that executes the computer executable components stored in the memory, wherein the computer executable components comprise a first receiving component that receives information of a trip comprising a destination and departure information, and an optimal routing component that determines an optimal routing based on current conditions, user preferences for charging stations, primary user's driving habits, battery's state of health, financial impact, and availability of charging stations at the time of receiving the trip information. At the time of trip set up, the system can make reservations for charging at the charging station requiring a reservation. During the trip, if the system requires a change to the reservation, the system establishes communication with the charging station and adjusts the reservation.