Energy Source Prioritization in EV Battery Distribution Control
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Solution Overview
Problem
Existing electric vehicles lack a systematic approach to prioritize and manage the distribution of energy based on its type and source, leading to inefficiencies in utilizing renewable versus non-renewable energy sources.
Innovation Solution
An energy distribution system that utilizes an energy meta-data file to track and prioritize energy transfers based on type and source, allowing for efficient management and distribution of energy within electric vehicles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If energy distribution is managed without prioritization, then all energy sources are treated equally, but renewable energy utilization is inefficient
Solution Approach 1:
The energy distribution system segments energy sources into different priority categories (renewable vs. non-renewable) using an energy metadata file that classifies each energy unit's source type. This segmentation enables selective prioritization of renewable energy without requiring complete system redesign, resolving the contradiction by creating manageable categories that improve efficiency while limiting complexity growth.
Solution Approach 2:
The system performs preliminary classification of energy sources by storing metadata about each energy unit's origin (renewable or non-renewable) before distribution occurs. This advance categorization allows the distribution algorithm to automatically prioritize renewable energy without real-time complex analysis, improving renewable utilization while keeping the management system relatively simple through pre-computed energy characteristics.
2Loss of information
If multiple energy sources are mixed without tracking, then distribution is simple, but energy source traceability is lost
Solution Approach 1:
The system creates a digital copy (metadata file) that records the source characteristics of each energy unit without physically separating or tagging the actual energy. This metadata copying approach maintains complete traceability of energy origins while avoiding the complexity of physical tracking mechanisms, as the information replica is sufficient for distribution decisions.
Solution Approach 2:
The energy metadata file acts as an intermediary between the physical energy sources and the distribution system. Instead of directly tracking complex physical energy flows, the system uses this intermediate data structure to represent and manage energy source information, reducing the complexity of direct traceability while preserving all necessary source attribution data.
3Productivity
If green energy is prioritized in distribution, then renewable energy utilization improves, but distribution control complexity increases
Solution Approach 1:
The system changes the prioritization parameter used in energy distribution from equal treatment to source-type-based treatment. By modifying the distribution algorithm to read and act upon the energy source classification in the metadata file, the system prioritizes green energy without requiring complex real-time optimization, achieving improved renewable utilization through a relatively simple parameter-based control rule.
Data Source
AI summary
An energy distribution system includes at least a first energy storage system including a controller and at least one energy storage unit configured to store a quantity of energy. The controller includes a memory storing an energy meta-data file. The energy meta data file includes an energy type element and an energy source element.