EV Charging Wait Prediction Using Charged Vehicle Ratios
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Solution Overview
Problem
There is a demand to predict the future congestion status of charging stations for electric vehicles, as vehicles often have to wait when arriving at a charging station that is already in use.
Innovation Solution
A charging prediction system that includes vehicles, charging stations, and a server apparatus, using indices such as charged vehicle ratio and remaining traveling distance to derive predicted waiting periods by accumulating and analyzing data on vehicle charging behavior, traffic conditions, and environmental factors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If charging stations are installed at predetermined positions on traveling roads, then vehicles can access charging infrastructure, but waiting periods increase when multiple vehicles arrive simultaneously
Solution Approach 1:
The system performs preliminary actions by accumulating charging history data and deriving charged vehicle ratio statistics before vehicles arrive at charging stations. This advance preparation enables real-time prediction of waiting periods, allowing drivers to make informed decisions about which charging station to use, thereby reducing actual waiting time without requiring additional charging infrastructure
Solution Approach 2:
The system establishes a feedback loop where charging station usage data is continuously accumulated, processed to derive charged vehicle ratios, and used to predict future waiting periods. This feedback mechanism enables dynamic optimization of charging station selection based on real-time congestion predictions, resolving the contradiction between maintaining charging accessibility and minimizing waiting periods
2Measurement precision
If charging prediction is performed using charged vehicle ratio, then waiting time prediction accuracy improves, but data accumulation and processing complexity increase
Solution Approach 1:
The system transforms complex multi-dimensional charging behavior data into a simplified parameter - the charged vehicle ratio. By changing the data representation from raw charging records to a normalized ratio parameter, the system achieves accurate waiting time prediction while reducing processing complexity. The charged vehicle ratio serves as a compact statistical measure that captures essential charging station utilization patterns
Solution Approach 2:
The charged vehicle ratio acts as an intermediary parameter between raw charging data and waiting time prediction. Instead of directly processing complex charging records to predict waiting times, the system uses the charged vehicle ratio as a mediating statistic that simplifies the relationship between historical charging behavior and future congestion levels, thereby reducing overall system complexity
Data Source
AI summary
A charging prediction system includes vehicles, a charging station, and a control device including one or more processors and one or more memories. The one or more processors are configured to execute a process. The process includes accumulating, in a storage device, record data that is actual data on a charged vehicle ratio for a first remaining traveling distance of each of the vehicles traveling along a specific traveling road. The process includes deriving, based on the record data, a predicted value of the charged vehicle ratio for each vehicle in a predetermined group including ones of the vehicles currently traveling along the specific traveling road. The process includes deriving a predicted waiting period that is a predicted value of a waiting period to a start of charging at the charging station based on the predicted values of the charged vehicle ratios.