Engineering topics

Nagpure, Shrikant C.

Publications and source records attributed to Nagpure, Shrikant C..

2 records

DOE OSTI2020

Cell degradation quantification—a performance metric-based approach

A safe and reliable battery operation needs effective diagnostic tools. A quantitative failure analysis (FA) to enable cell qualification and quantify its effectiveness for reliable and safe operation of rechargeable Li batteries (RLB) is shown here. The method can identify and quantify potential failure based on the state of charge (SOC) under any operating conditions. A precise and accurate electrochemical analytic diagnosis (eCAD) of 14 rechargeable Li || NMC622 cells of the same build are used as an example. The FA by eCAD can quantitatively decipher good, bad and ugly cells in cycle aging. The cell qualification is based on thermodynamic SOC, not experimental conditions. The method provides a quantitative failure mode and effect analysis (FMEA) to reveal diverse “dead Li” formation that affects the reversibility of the Li anode and charge retention in the cell. This cell qualification method highlights the potential to improve cell quality for safe operation, with strong implications for early fault detection, FA, risk mitigation, state estimation and life prediction for reliable and safe RLB operations

25 ENERGY STORAGE↗

DOE OSTI2020

A Quantitative Failure Analysis on Capacity Fade in Rechargeable Lithium Metal Cells

Rechargeable lithium battery (RLB) technology is transforming portable devices, vehicle electrification, and grid modernization. To make RLB durable, reliable and safe, conducting failure mode and effect analysis (FMEA) to identify failure mechanism under the operating conditions is very desirable. However, this ability is often overlooked or even lacking. The failure analysis (FA) is often conducted by laboratory testing and postmortem analysis, and the knowledge typically empirical. Here we present a quantitative approach for FMEA that can reveal how failure modes and effects reduce the capacity of a RLB. This approach is based on the state of the battery for FMEA, contrary to the conventional approach based on operating or testing conditions. The key aspect of this FMEA method is to convert the experimental results to a state-of-charge (SOC)-based analytic methodology. Such a conversion can separate the thermodynamic and kinetic attributes of capacity fade based on compositional correspondence in the electrode, so the loss and the decreased utilization of the active materials can be determined respectively.

25 ENERGY STORAGE↗