EV Wireless Charging Routing via Segmented Roadway Control
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Solution Overview
Problem
Existing wireless charging technologies for electric vehicles are inefficient in managing varying battery capacities and charge levels across different routes, particularly failing to account for fluctuations in traffic flow and load variations on roadways.
Innovation Solution
A control system that includes a processor and computer-readable medium for tracking and routing rechargeable electric vehicles to optimal charging segments, balancing load by considering vehicle information, grid energy availability, and traffic patterns, and enabling bidirectional energy flow to optimize charging efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If wireless charging is implemented on roadways, then electric vehicles can be charged during motion, but load balancing across charging segments becomes difficult to manage
Solution Approach 1:
The roadway charging system is divided into multiple discrete charging segments along the transportation network. Each segment can be independently controlled and monitored, allowing the system to manage charging loads in distributed portions rather than as a monolithic system. This segmentation enables targeted load balancing strategies for each segment while maintaining overall system efficiency.
Solution Approach 2:
The system dynamically routes electric vehicles to optimal charging segments based on real-time conditions including traffic flow, grid energy availability, and vehicle battery status. This dynamic routing adapts to changing conditions to balance load across segments, preventing any single segment from becoming overloaded while ensuring vehicles receive charging when and where needed.
2Productivity
If vehicles are routed to specific charging segments, then load balancing is improved, but traffic congestion may increase due to routing decisions
Solution Approach 1:
The system changes multiple parameters simultaneously when routing vehicles: selecting charging segments based on current load conditions, determining optimal times for charging based on grid availability, and coordinating routing decisions to minimize impact on traffic flow. By adjusting these parameters in concert, the system achieves load balancing while maintaining acceptable travel times.
Solution Approach 2:
The system continuously monitors traffic conditions, charging segment utilization, and vehicle locations, using this feedback to adjust routing decisions in real-time. When routing vehicles to charging segments would cause congestion, the system receives feedback about traffic conditions and modifies its routing recommendations to avoid creating bottlenecks, thus balancing load management with traffic flow maintenance.
3Ease of operation
If charging segments are distributed along roadways, then charging accessibility is improved, but managing variable load across segments becomes complex
Solution Approach 1:
The control system performs multiple functions through a unified platform: it tracks vehicle locations, analyzes battery status, monitors grid energy availability, manages traffic coordination, and routes vehicles to appropriate charging segments. This multi-functional approach consolidates what would otherwise be separate complex systems into a single coordinated platform, making the distributed charging network manageable despite its complexity.
Solution Approach 2:
The control system acts as an intermediary between the distributed charging segments, the power grid, and the electric vehicles. It receives information from vehicles and the grid, processes this information according to load balancing objectives, and sends routing instructions to vehicles while coordinating with charging segments. This intermediary role simplifies the management of distributed segments by centralizing the decision-making logic.
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
This solution allows for efficient and uniform distribution of electric vehicle charging, reducing traffic congestion, improving user satisfaction, and enabling more effective power grid operation by adapting to varying load conditions and traffic patterns.
Implementation Method 1
a wire carrying an electric current produces a magnetic field around the wire (Ampere's Law)
Implementation Method 2
a coil intersecting a magnetic field produces a voltage in that coil (Faraday's Law)
Implementation Method 3
a coil intersecting a magnetic field produces a voltage in that coil (Faraday's Law)
Implementation Method 4
electromagnetic power transfer between electrical circuits across an air gap can be achieved using magnetic field coupling at resonance (Tesla's Law)
Data Source
AI summary
A control system for a rechargeable vehicle control system, comprises: a processor and a computer readable medium, in communication with the processor, that comprises processor executable instructions. The processor executable instructions comprise: a vehicle tracker that identifies rechargeable electric vehicles currently using a transportation network and tracks a last known position in the transportation network of each rechargeable electric vehicle and a vehicle router that directs the rechargeable electric vehicles to one of plural charging segments located along the transportation routes in the transportation network to receive a charge, thereby load balancing the rechargeable electric vehicles over the plurality of charging segments.