EV Charging Circuit Quality Prediction Using Smart Meter Comparison
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Solution Overview
Problem
The increasing penetration of electric vehicles poses challenges to electrical power systems due to inadequate infrastructure capacity, leading to safety concerns and operational failures in EV charging installations, with existing solutions relying on post-failure safety measures like GFCI and overtemperature protection.
Innovation Solution
A monitoring system using smart meters and EV chargers to measure grid characteristics and estimate electrical installation quality by comparing voltage and calculating resistance, predicting potential failures through central software to prevent overheating and damage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional safety measures like GFCI and overtemperature protection are used, then safety is improved, but the system can only detect failures after they occur rather than predicting them
Solution Approach 1:
The monitoring system performs preliminary actions by continuously measuring electrical parameters (voltage, current, temperature) and comparing them against baseline values to predict failures before they occur. The system calculates resistance changes and identifies deteriorating trends in the electrical installation, enabling proactive maintenance rather than reactive response after safety devices trigger.
Solution Approach 2:
The system implements feedback by continuously monitoring electrical parameters and comparing measured values against expected ranges. When deviations are detected indicating potential failures, the system generates alerts that feed back to operators, enabling timely intervention before actual failures occur, thus improving both safety and reducing downtime.
2Reliability
If a monitoring system with smart meters and central software is implemented, then failure prediction capability is improved, but device complexity increases
Solution Approach 1:
The smart meters and EV chargers perform multiple functions: they serve as both charging equipment and monitoring devices. The same sensors and communication interfaces used for normal charging operations are leveraged to collect data for failure prediction, eliminating the need for separate dedicated monitoring hardware and reducing overall system complexity.
Solution Approach 2:
The system enables self-service by allowing EV chargers to autonomously monitor their own electrical installation conditions and report status to the central platform. The chargers themselves perform measurements and preliminary analysis, reducing the burden on central system complexity while maintaining sophisticated failure prediction capabilities.
3Measurement precision
If continuous monitoring of electrical parameters is performed, then detection precision is improved, but energy consumption increases
Solution Approach 1:
The monitoring system maintains continuous measurement of electrical parameters using the existing power measurement infrastructure already present in smart meters and EV chargers. Since these devices continuously measure voltage, current, and power for billing and control purposes, the additional monitoring function leverages existing continuous operation without significant additional energy consumption.
Solution Approach 2:
The same sensors and measurement circuits used for standard charging operations are utilized for monitoring purposes. The smart meters and charger internal meters perform dual functions of both enabling charging and detecting installation quality, avoiding the need for separate dedicated monitoring hardware that would consume additional energy.
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
Enhances EV charger reliability, safety, and efficiency by identifying deteriorating circuits before failure, reducing downtime and improving utilization rates.
Implementation Method 1
Predicting a failure is going to happen based on a deteriorated resistance in an electrical circuit. An electrical circuit that presents a higher resistance than expected can cause overheating and damage.
Data Source
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AI summary
A predictor of a quality of an electrical installation of electrical vehicle (EV) charging infrastructure is provided. The predictor comprises a monitoring system including software instructions of a central monitoring software to identify whether an electrical circuit is about to fail by connecting to a smart meter measuring the electrical circuit (voltage, current, temp, etc.), as well as a smart EV charger with an internal meter connected to the same electrical circuit. The monitoring system is configured to use the smart meter to measure grid characteristics at a central place with metering information in the smart EV charger behind the central place to estimate the quality of the electrical installation.