Server Consensus Algorithm for EV Charging Energy Verification
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The existing electric vehicle charging infrastructure is cost-intensive due to the need for calibrated meters at both charging stations and vehicles, leading to discrepancies in energy measurement between them, which can result in inaccurate monetary settlements and inefficiencies.
Innovation Solution
A method utilizing a server device that operates a consensus algorithm to reconcile energy measurement data from both the charging station and the vehicle, allowing for the generation of a binding consensus value without requiring calibrated meters, and enabling continuous or interrupted charging processes based on measurement tolerances and data quality evaluation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If calibrated meters are used at both charging stations and vehicles to ensure accurate energy measurement, then measurement precision is improved, but infrastructure cost increases
Solution Approach 1:
A server device acts as an intermediary between charging stations and vehicles, receiving measurement data from both parties and operating a consensus algorithm to determine a binding energy quantity. This mediator resolves measurement discrepancies without requiring expensive calibrated meters at both ends, as the server consolidates the verification function.
Solution Approach 2:
The system uses duplicate measurement data from both station-side and vehicle-side meters as independent verification sources. By comparing these parallel measurement copies and resolving discrepancies through consensus algorithms, the system achieves reliable energy quantification without requiring both meters to be expensive calibrated types.
2Reliability
If both charging station and vehicle measure energy quantity independently with different metering circuits, then measurement reliability is improved through mutual verification, but measurement discrepancies occur leading to settlement issues
Solution Approach 1:
The server device receives measurement data from both charging stations and vehicles, processes this feedback information through consensus algorithms, and generates a binding energy quantity. This feedback loop allows the system to identify and resolve measurement discrepancies, ensuring both parties accept the final settlement value.
Solution Approach 2:
The consensus algorithm dynamically adjusts the determination of energy quantity based on the specific measurement data received from both station and vehicle. By changing the parameter determination process rather than relying on fixed meter readings, the system resolves inconsistencies and achieves agreement between parties with different measurement values.
Data Source
AI summary
A method for the verification of an electric charging process is provided, wherein electric energy is transferred by the charging process between an electrically operated motor vehicle and an electric charging station and station-side measurement data about the charging process are generated by a metering circuit of the charging station and the station-side measurement data are received by a server device from the charging station. Vehicle-side charging data about the same charging process are generated by a control circuit of the motor vehicle and the vehicle-side charging data are received by the server device from the motor vehicle and the server device operates a predetermined consensus algorithm in order to generate on the basis of the measurement data and the charging data a consensus value consistently describing the charging process for both the charging station and for the motor vehicle.