EV Charger Rate Validation for Maintenance and Overbilling Detection
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Solution Overview
Problem
Conventional electric vehicle charging systems often provide unreliable charger information, leading to inconvenient charging experiences and potential over-billing due to sub-optimal or malfunctioning charging stations.
Innovation Solution
A vehicle charger optimization system that connects vehicles with charging stations, crowdsources real-time charging rates, and compares them to projected rates to detect maintenance needs and over-billing, providing accurate information to users and managing entities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional charging systems provide charger information to users, then users can plan trips and identify chargers, but the information may be unreliable and lead to sub-optimal charging experiences
Solution Approach 1:
The system implements a feedback mechanism where actual charging rates are collected from vehicles that charged at specific stations, then compared against projected charging rates. This feedback loop enables the system to identify discrepancies and provide accurate real-time information to users, resolving the reliability issue by continuously validating charger performance data.
Solution Approach 2:
The system introduces an intermediary layer between the charging stations and users - a centralized platform that collects, validates, and processes charging rate information. This intermediary filters out unreliable data and provides verified charging performance information to users, solving the problem of information accuracy without requiring direct user-access to raw charger data.
2Ease of operation
If users rely on projected charging rates from charging stations, then charging planning is simplified, but users may be subject to over-billing due to discrepancies between projected and actual rates
Solution Approach 1:
The system performs preliminary validation of charging rates by collecting actual charging data from previous vehicles at each station before providing information to new users. This advance verification ensures that users receive accurate charging rate information for trip planning, maintaining ease of operation while preventing over-billing through pre-validated data.
Solution Approach 2:
The system continuously monitors actual charging rates and compares them against projected rates, providing real-time feedback on charging station performance. This feedback mechanism allows users to make informed decisions based on verified data while maintaining the simplicity of using projected rates for planning, as the system automatically adjusts for discrepancies.
3Device complexity
If charging stations operate without monitoring, then system complexity is reduced, but maintenance needs go undetected and charging performance deteriorates
Solution Approach 1:
The system implements self-service monitoring where charging stations automatically report their operational data and charging rates to the centralized platform. This self-reporting mechanism enables automatic detection of maintenance needs and performance issues without requiring complex external monitoring infrastructure, resolving the contradiction between system simplicity and reliable operation detection.
Data Source
AI summary
A vehicle charger optimization system is disclosed. The system may include a transceiver configured to receive charging information from a vehicle. The charging information may include a real-time charging rate at which the vehicle may be getting charged using a charger. The system may further include a memory configured to store a projected charging rate associated with the charger. The system may further include a processor configured to obtain the projected charging rate and the real-time charging rate and calculate a first difference between the projected charging rate and the real-time charging rate. The processor may determine that the first difference is greater than a first predefined threshold, and perform a predetermined action based on a determination that the first difference is greater than the first predefined threshold. The predefined action may include transmitting a maintenance flag to a server or a third-party entity that manages the charger.