Solar Charging Parking Location Recommendation System
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Solution Overview
Problem
Electric and hybrid vehicles face challenges in identifying optimal parking locations that provide maximum solar radiation exposure for charging, especially considering weather, shading, and duration of parking, which affects the efficiency and reliability of solar charging.
Innovation Solution
A computer system integrated with GPS and a database that assesses geographically proximate parking facilities based on environmental factors, weather, time, and shading to recommend parking locations with optimal sun exposure, allowing for estimated charging times and cost-effective options.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If the vehicle uses solar panels for charging, then energy autonomy is improved, but the vehicle requires specific parking locations with sun exposure which limits operational flexibility
Solution Approach 1:
The system performs preliminary assessment of parking locations for solar exposure potential before the vehicle arrives. The server evaluates geographic coordinates, surrounding structures, and historical weather data to predict charging effectiveness, allowing the vehicle to proactively select optimal parking spots that maximize solar charging while maintaining operational flexibility
Solution Approach 2:
A server acts as an intermediary between the vehicle's solar charging system and the environment. The server receives vehicle location data, processes it through algorithms that consider weather forecasts, geographic features, and parking structure characteristics, then provides recommended parking locations that balance solar exposure with operational flexibility
2Productivity
If the vehicle parks in locations with maximum sun exposure, then charging efficiency is improved, but the vehicle may park in less convenient or more expensive locations
Solution Approach 1:
The system dynamically adjusts parking location recommendations based on multiple parameters including weather forecasts, expected parking duration, vehicle energy needs, and convenience factors. The algorithm weighs these parameters to provide optimized recommendations that balance charging efficiency with parking convenience and cost-effectiveness
3Measurement precision
If the system provides detailed assessment of parking locations, then charging optimization is improved, but the system complexity increases
Solution Approach 1:
The system extracts only the most critical factors for solar charging assessment (geographic coordinates, surrounding structures, weather patterns, parking duration) and processes these through efficient algorithms. By focusing on key parameters rather than comprehensively analyzing all possible variables, the system achieves high assessment accuracy while maintaining computational efficiency and manageable system complexity
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
The system effectively directs vehicle operators to parking spots that maximize solar charging potential, ensuring efficient battery charging and providing cost-effective solutions, even when solar exposure is limited, by integrating vehicle sensors and external data with algorithms to optimize vehicle orientation and location selection.
Implementation Method 1
A plurality of solar panels 14 are located on the hood and roof to convert incident solar radiation into electrical energy
Data Source
AI summary
An automotive vehicle having at least one solar panel, a battery rechargeable by the at least one solar panel, and a computer system including one or more processors and memory storing one or more programs. The program(s) generate a list of parking locations, determine which of the one or more parking location provide sun exposure, and recommending at least one parking location to a vehicle operator.