Li-Ion Battery Impedance Monitoring for Lithium Plating Detection
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Solution Overview
Problem
Lithium-ion batteries experience performance degradation due to mechanisms such as passivation layer growth, lithium plating, loss of active sites, and increased bulk resistance, which are not adequately addressed by existing models, posing safety concerns as they are deployed in electric power grids and transportation.
Innovation Solution
Implementing a pseudo-EIS test protocol with periodic charging current interruptions to monitor battery impedance, determining resistance values, and using machine learning to set thresholds for lithium plating and dendrite growth, triggering alerts or adjusting charging currents to prevent degradation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If lithium-ion batteries are deployed at higher rates in electric power grid and transportation, then productivity and energy storage capacity increase, but reliability and safety deteriorate due to performance degradation from passivation layer growth, lithium plating, and increased bulk resistance
Solution Approach 1:
The system performs preliminary monitoring of battery impedance characteristics and detects early signs of lithium plating and dendrite growth before they cause safety hazards. By continuously measuring impedance at different charge levels and analyzing changes in real-time, the system identifies degradation mechanisms in advance, allowing preventive actions to be taken before reliability deteriorates.
Solution Approach 2:
The system implements continuous feedback monitoring of battery impedance characteristics during charging and discharging cycles. By measuring impedance at multiple charge levels and comparing against threshold values, the system provides real-time feedback on battery health status, enabling dynamic adjustment of charging parameters to maintain safety while maximizing productivity.
2Device complexity
If standard battery models are used for monitoring, then device complexity is reduced, but measurement precision deteriorates because they cannot detect lithium plating and dendrite growth
Solution Approach 1:
The system segments the battery charging process into multiple charge levels (e.g., 10%, 30%, 50%, 70%, 90% charge levels) and performs impedance measurements at each segment. This segmentation allows detection of impedance changes specific to different charge states, enabling precise identification of lithium plating and dendrite growth that would be invisible in standard single-point measurements.
Solution Approach 2:
The system adds a new measurement dimension by implementing impedance spectroscopy measurements across multiple frequencies and charge levels, rather than relying on standard voltage-current measurements. This dimensional expansion in the measurement space enables detection of electrochemical degradation mechanisms that are invisible to conventional monitoring approaches.
3Measurement precision
If impedance measurements are performed continuously without interruptions, then real-time monitoring capability is improved, but energy consumption increases and battery performance is degraded
Solution Approach 1:
The system implements periodic impedance measurements at predetermined charge levels (e.g., every 10% charge level) rather than continuous measurements. This periodic approach maintains real-time monitoring capability by capturing impedance changes at critical points in the charging cycle while minimizing energy consumption and avoiding unnecessary disruption to battery operation.
Solution Approach 2:
The system performs partial impedance measurements by applying small AC perturbation signals superimposed on the charging current, rather than stopping charging completely for measurement. This partial action approach enables impedance characterization during normal charging operation, maintaining both monitoring capability and charging efficiency without excessive energy consumption.
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
The system provides real-time monitoring and management of lithium-ion battery performance and safety by identifying and mitigating lithium plating and dendrite growth, extending battery life and preventing potential hazards.
Implementation Method 1
monitor battery impedance, determining resistance values
Data Source
AI summary
Battery testing and monitoring by determining battery characteristics such as an increase thickness of the battery SEI layer, extent of lithium-ion plating, loss of cyclable lithium, dendrite growth (and extent), and/or other characteristics that may impact the performance and/or safety of a lithium-ion battery. The battery characteristics may be determined at perioding intervals using test data that includes voltage and current at various charging levels and state of charge, thus providing impedance profiles that can be compared to modelled and/or known thresholds of battery conditions.