Battery Defect Diagnosis via Current Error Analysis
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Solution Overview
Problem
Existing methods for diagnosing malfunctions in stationary batteries used for energy storage from renewable sources, such as wind or photovoltaic, lack precision in identifying the origin of failures, making it difficult for maintenance operators to accurately diagnose and address issues, which affects the performance and safety of the battery system.
Innovation Solution
A method that calculates the error between the set current and the measured current over varying time windows to differentiate between connection failures, sensor failures, and aging-related issues, allowing for precise identification of the failure origin and targeted maintenance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a stationary battery system uses recycled Li-ion batteries from electric vehicles for energy storage, then the economic profitability is improved by extending the amortization period, but the reliability deteriorates due to aging batteries requiring special maintenance care
Solution Approach 1:
The system performs preliminary diagnosis actions by continuously monitoring battery parameters (voltage, current, temperature) and comparing expected vs. actual discharge behavior before failures occur. This allows early detection of degradation patterns in recycled batteries, enabling preventive maintenance that maintains reliability while extending usable service life.
Solution Approach 2:
The diagnostic system establishes feedback loops where battery performance data is continuously collected, analyzed against expected behavior, and used to adjust maintenance schedules and operations. This feedback mechanism ensures aging batteries operate within safe parameters while maximizing their extended service life for stationary storage applications.
2Reliability
If a failure detection system is implemented in the battery system, then the reliability is improved by detecting failures, but the ease of operation deteriorates because no clear indication is provided about the origin of failures, leaving accurate diagnosis to the maintenance operator
Solution Approach 1:
The system introduces an intelligent intermediary layer (diagnostic algorithm) that sits between the raw failure detection and the maintenance operator. This intermediary analyzes the nature of failures, determines their origin (connection, sensor, or battery aging), and presents clear diagnostic information to operators, eliminating the need for them to perform complex analysis while maintaining high reliability detection.
Solution Approach 2:
The diagnostic system performs self-service by automatically characterizing failure types and origins without human intervention. The system independently analyzes discharge mismatches, identifies whether failures stem from connections, sensors, or battery aging, and communicates results in an operator-friendly format, making the system self-diagnosing rather than operator-dependent.
3Measurement precision
If the system monitors and diagnoses battery failures in real-time, then the measurement precision is improved by identifying failure origins, but the device complexity increases due to the need for comparing set current with measured current over varying time windows
Solution Approach 1:
The diagnostic system is segmented into modular functional blocks: a monitoring module that collects voltage and current data, a calculation module that computes expected vs. actual discharge, a analysis module that characterizes failure types, and a communication module that reports results. This segmentation achieves high measurement precision for failure origin identification while keeping each module's complexity manageable and the overall system organized.
Data Source
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Figure 3a~3c
AI summary
The invention relates to a method for detecting defects in an electrical power storage system comprising at least one battery. The method comprises a step for applying an instruction for charging or discharging the battery. Said method also comprises a step for measuring the current passing through the battery during application of said instruction. Said method moreover comprises a step for calculating m x n mean errors (eTj(ti j))1≤j≤m,1≤i≤n between the measured current and the theoretical current of the instruction in m x n time intervals ([ti j, ti j + Tj ])1≤j≤m,1≤i≤n , respectively. Said method also comprises a step for calculating, for each j between 1 and m, ej =max(eTj (t i j)), where i=1,…,n. Lastly, said method comprises a step for incrementing a counter Cj if ej completely or partially exceeds a predetermined threshold. A defect is detected if Cj exceeds a predetermined threshold.