Battery Pack Fault Diagnosis Using Cell Dispersion Analysis

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Solution Overview

Problem

Conventional battery management systems face limitations in monitoring characteristics deviations between batteries in a group, leading to reduced charge/discharge performance and increased fire risk due to software and hardware constraints.

Innovation Solution

A battery diagnosis system that uses statistical analysis of big data from battery parameters to detect faults in each battery within a group, employing a communication device, data preprocessing device, and data analysis device to determine dispersion information and identify faulty batteries.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If conventional battery management systems are used, then basic battery monitoring is achieved, but fault detection accuracy is limited due to software and hardware constraints

Engineering Contradiction:
Improvefault detection accuracyVSAvoidsystem complexity
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The system segments the battery group into individual battery units, collecting and analyzing parameters for each battery separately. This segmentation enables precise fault detection for each unit while maintaining manageable system complexity through modular data processing architecture.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The system performs preliminary data collection and preprocessing of battery parameters before analysis. By pre-processing data including normalization and feature extraction, the system prepares information in advance for more accurate fault detection without increasing real-time computational complexity.

Inventive Principle:
Principle #10Preliminary action

2Reliability

If comprehensive battery parameter monitoring is implemented, then fault detection capability is improved, but data processing load increases beyond conventional system capabilities

Engineering Contradiction:
Improvebattery safetyVSAvoiddata processing efficiency
Core Design Contradiction:
ReliabilityVSProductivity

Solution Approach 1:

The system performs preliminary data collection and preprocessing of battery parameters before analysis. By pre-processing data including normalization and feature extraction, the system prepares information in advance for more accurate fault detection without increasing real-time computational complexity.

Inventive Principle:
Principle #10Preliminary action

Solution Approach 2:

The system introduces intermediate processing layers including data normalization modules and feature extraction components that act as mediators between raw data collection and final analysis. These intermediaries reduce the complexity of raw data while preserving critical information for safety assessment.

Inventive Principle:
Principle #24Intermediary (Mediator)

3Measurement precision

If statistical analysis of big data is performed, then fault prediction accuracy is improved, but computational requirements exceed conventional system capacity

Engineering Contradiction:
Improvefault prediction accuracyVSAvoidcomputational power
Core Design Contradiction:
Measurement precisionVSPower

Solution Approach 1:

The system performs preliminary data collection and preprocessing of battery parameters before analysis. By pre-processing data including normalization and feature extraction, the system prepares information in advance for more accurate fault detection without increasing real-time computational complexity.

Inventive Principle:
Principle #10Preliminary action

Solution Approach 2:

The system applies statistical analysis selectively to the most critical battery parameters and high-risk battery units rather than performing exhaustive analysis on all data. This partial action approach achieves sufficient fault prediction accuracy while staying within computational power constraints.

Inventive Principle:
Principle #16Partial or excessive action

4Reliability

If characteristics deviation monitoring is enhanced, then battery reliability is improved, but system resource consumption increases

Engineering Contradiction:
Improvebattery group performanceVSAvoidenergy consumption
Core Design Contradiction:
ReliabilityVSLoss of energy

Solution Approach 1:

The system monitors characteristics deviation for all batteries but performs detailed analysis only when deviation exceeds predetermined thresholds or for batteries showing abnormal trends. This partial monitoring approach maintains battery group reliability while minimizing energy consumption by avoiding continuous full-scale analysis.

Inventive Principle:
Principle #16Partial or excessive action

Data Source

PatentUS12210070B2Battery diagnosis system, power system and battery diagnosis method
Publication Date: 2025.01.28 LG ENERGY SOLUTION LTD
  • US12210070B2 patent drawing
  • US12210070B2 patent drawing
  • US12210070B2 patent drawing

AI summary

Discussed is a battery diagnosis system for a battery pack including a battery group of a plurality of batteries connected in series, and a battery management system to transmit a notification signal indicating a battery parameter of each of the plurality of batteries. The battery diagnosis system includes a communication device to collect the notification signal via at least one of a wired network or a wireless network, a data preprocessing device to update big data indicating a change history of the battery parameter of each battery based on the notification signal, and a data analysis device to determine dispersion information of a data set including a plurality of characteristics values indicating the battery parameter of each of the plurality of batteries from the big data, and determine whether each battery is faulty based on the dispersion information and the plurality of characteristics values.