Vehicle-to-Station Energy Offload Using Route-Based Charge Planning
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Solution Overview
Problem
Current vehicle energy management systems lack efficiency in determining the actual energy needs based on destination and route conditions, leading to suboptimal energy transfer between vehicles and charging stations.
Innovation Solution
A method where a transport vehicle requests a portion of stored energy to be transferred to a charging station, which determines the actual energy needed based on the destination and route conditions, allowing for dynamic adjustment of energy transfer amounts considering factors like weather, road conditions, and vehicle condition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a transport vehicle requests a fixed portion of stored energy to be transferred to a charging station, then the energy transfer process is simple and quick, but the energy usage is inefficient because it does not account for actual route conditions
Solution Approach 1:
The energy management system dynamically adjusts the energy transfer amount based on real-time route conditions, weather, and vehicle state. The charging station receives route information and calculates the actual energy needed, transforming a static fixed-amount transfer into a dynamic condition-based transfer process
Solution Approach 2:
The system implements feedback loops where the charging station communicates with the transport vehicle to exchange route data, energy requirements, and vehicle status. This bidirectional communication enables continuous optimization of energy transfer based on actual conditions
2Use of energy by moving object
If the charging station determines the actual energy needed based on detailed route and condition data, then the energy usage is optimized, but the determination process becomes more complex and time-consuming
Solution Approach 1:
The transport vehicle provides route information and destination data to the charging station before the energy transfer process begins. This preliminary information exchange allows the charging station to pre-calculate the required energy amount, avoiding time-consuming calculations during the actual charging process
Solution Approach 2:
The system changes the parameter basis for energy determination from fixed vehicle capacity to dynamic route-specific requirements. By incorporating variables such as distance, weather conditions, road gradient, and vehicle load, the system calculates precise energy needs while maintaining efficient processing
3Reliability
If the transport vehicle transfers more energy than actually needed, then the vehicle is prepared for unexpected conditions, but unnecessary energy transfers occur leading to waste
Solution Approach 1:
The energy transfer is tailored to the specific local conditions of the upcoming route rather than applying a uniform energy amount. The charging station analyzes route-specific factors such as distance, elevation changes, weather forecasts, and traffic conditions to determine the precise energy amount needed for that particular journey segment
Solution Approach 2:
The transport vehicle autonomously provides its route information and destination data to the charging station, enabling the charging station to self-determine the appropriate energy amount without manual input. This self-service information exchange ensures accurate matching of energy supply with actual vehicle needs
Data Source
AI summary
An example operation includes one or more of initiating, by a transport, a request to provide a first portion of stored energy to a charging station, determining, by the charging station, an actual amount of energy needed by the transport, wherein the determining is based on a first destination of the transport and on data received by the charging station based on a route associated with the first destination, wherein the actual amount of energy is not the same amount as the first portion of stored energy, and depositing, by the transport, the actual amount of energy in the charging station.