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The Case for DeepSOH: Addressing Path Dependency for Remaining Useful Life

Hamidreza Movahedi, Andrew Weng, Sravan Pannala, Jason B. Siegel, Anna G. Stefanopoulou

TL;DR

The paper argues that traditional SOH and electrode-specific SOH definitions cannot capture the path-dependent degradation driving Remaining Useful Life (RUL) in lithium-ion batteries. It introduces deepSOH, a state vector $deepSOH=[\delta_{SEI}, \delta_{pl}, C_p, C_n, LLI]^T$, to represent the internal progress of SEI growth, Li plating, and mechanical degradation, linking these to capacity and resistance. By modeling the degradation dynamics with $\dot{\mathcal{X}}=f(\mathcal{X}, I)$ and demonstrating that identical eSOH and resistance can correspond to different deepSOH and hence distinct RULs, the work shows that deepSOH is necessary for accurate RUL estimation. The authors show that incorporating irreversible expansion as an additional measurement can improve identifiability of deepSOH, providing a pathway toward more reliable second-life battery assessments and fleet-scale reliability analyses.

Abstract

The battery state of health (SOH) based on capacity fade and resistance increase is not sufficient for predicting Remaining Useful life (RUL). The electrochemical community blames the path-dependency of the battery degradation mechanisms for our inability to forecast the degradation. The control community knows that the path-dependency is addressed by full state estimation. We show that even the electrode-specific SOH (eSOH) estimation is not enough to fully define the degradation states by simulating infinite possible degradation trajectories and remaining useful lives (RUL) from a unique eSOH. We finally define the deepSOH states that capture the individual contributions of all the common degradation mechanisms, namely, SEI, plating, and mechanical fracture to the loss of lithium inventory. We show that the addition of cell expansion measurement may allow us to estimate the deepSOH and predict the remaining useful life.

The Case for DeepSOH: Addressing Path Dependency for Remaining Useful Life

TL;DR

The paper argues that traditional SOH and electrode-specific SOH definitions cannot capture the path-dependent degradation driving Remaining Useful Life (RUL) in lithium-ion batteries. It introduces deepSOH, a state vector , to represent the internal progress of SEI growth, Li plating, and mechanical degradation, linking these to capacity and resistance. By modeling the degradation dynamics with and demonstrating that identical eSOH and resistance can correspond to different deepSOH and hence distinct RULs, the work shows that deepSOH is necessary for accurate RUL estimation. The authors show that incorporating irreversible expansion as an additional measurement can improve identifiability of deepSOH, providing a pathway toward more reliable second-life battery assessments and fleet-scale reliability analyses.

Abstract

The battery state of health (SOH) based on capacity fade and resistance increase is not sufficient for predicting Remaining Useful life (RUL). The electrochemical community blames the path-dependency of the battery degradation mechanisms for our inability to forecast the degradation. The control community knows that the path-dependency is addressed by full state estimation. We show that even the electrode-specific SOH (eSOH) estimation is not enough to fully define the degradation states by simulating infinite possible degradation trajectories and remaining useful lives (RUL) from a unique eSOH. We finally define the deepSOH states that capture the individual contributions of all the common degradation mechanisms, namely, SEI, plating, and mechanical fracture to the loss of lithium inventory. We show that the addition of cell expansion measurement may allow us to estimate the deepSOH and predict the remaining useful life.
Paper Structure (16 sections, 33 equations, 3 figures)

This paper contains 16 sections, 33 equations, 3 figures.

Table of Contents

  1. Introduction
  2. Battery degradation model
  3. SEI layer growth
  4. Lithium plating
  5. Mechanical degradation
  6. Loss of lithium inventory
  7. Dynamic system
  8. deepSOH
  9. Measurements or Calculations
  10. eSOH
  11. Resistance
  12. Irreversible expansion
  13. Identifiability and simulations
  14. Measuring eSOH and resistance
  15. Additional measurements
  16. ...and 1 more sections

Figures (3)

  • Figure 1: Schematic of different SOH definitions and their relationship with the use patterns and outcome. The dashed lines are ignored by eSOH.
  • Figure 2: Possible degradation trajectories of cells with the same eSOH and resistance and different deepSOH values ($\delta_{SEI}$ and $\delta_{pl})$ in particular
  • Figure 3: Voltage profile of C/20 charge and discharge of the cells the same initial eSOH and resistance and different deepSOH ($\delta_{SEI}$ and $\delta_{pl}$) values.