EV Charge Point Positioning for Solar-Aware Vehicle Organization
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Solution Overview
Problem
There is no optimal way to organize electric vehicles at charging points to maximize charging efficiency, considering variations in charging capabilities and solar panel usage.
Innovation Solution
A method and system that analyzes charging capability and solar panel information of vehicles, along with map and point of interest data, to recommend optimal charging positions, taking into account direct sunlight exposure and charging profiles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If electric vehicles are organized at charging points without optimization, then any vehicle can be charged, but charging efficiency is not maximized and solar panel utilization is suboptimal
Solution Approach 1:
The system performs preliminary analysis of vehicle charging capabilities, solar panel configurations, and parking space characteristics before assigning charging positions. By pre-processing this information and creating an optimization algorithm that evaluates multiple factors simultaneously, the system determines optimal vehicle-to-space assignments in advance, maximizing charging efficiency without requiring complex real-time adjustments during charging operations.
2Use of energy by moving object
If vehicles are positioned to maximize solar exposure, then solar charging efficiency improves, but some vehicles may not access optimal charge points
Solution Approach 1:
The system applies different optimization criteria to different vehicles based on their specific characteristics. Vehicles equipped with solar panels are assigned to parking spaces with optimal solar exposure and minimal shadow interference, while vehicles without solar panels are assigned to spaces with access to electrical charge points. This localized optimization approach ensures that each vehicle receives the most appropriate positioning for its specific capabilities, simultaneously maximizing solar energy utilization and maintaining charge point accessibility for all vehicles.
3Loss of energy
If charging positions are optimized for solar exposure, then solar panel charging improves, but charging time varies significantly among vehicles
Solution Approach 1:
The system changes multiple parameters simultaneously to optimize charging outcomes: it considers vehicle battery capacity, charging rate requirements, solar panel area and efficiency, parking space solar exposure, and shadow patterns throughout the day. By adjusting these parameters together in an optimization algorithm, the system assigns vehicles to charging positions that balance solar charging efficiency with overall charging time requirements, reducing excessive variation in charging times while maximizing solar energy utilization.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances charging efficiency by optimizing vehicle positioning to utilize solar power effectively and minimize shadow interference, thereby reducing charging time.
Implementation Method 1
The solar panel on the vehicle may charge a battery of the vehicle
Data Source
AI summary
Systems and methods for electric vehicle organization are provided. For example, a method for electric vehicle organization includes receiving charging capability information of one or more vehicles. The method also includes receiving information corresponding to charging profiles of the one or more vehicles. The method also includes determining charge point data in a given area associated with the one or more vehicles. The method also includes determining map object data and point of interest data in the given area. The method also includes generating a recommendation for an optimal charge position within the given area for a vehicle of the one or more vehicles based on a charging capability information of the vehicle, a charge profile of the vehicle, the determined charge point data in the given area, and the determined map object data and the point of interest data.