Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

Novel Low-Complexity Model Development for Li-ion Cells Using Online Impedance Measurement

Abhijit Kulkarni, Ahsan Nadeem, Roberta Di Fonso, Yusheng Zheng, Remus Teodorescu

TL;DR

This paper tackles online, low-complexity ECM parameter identification for Li-ion cells within BMS to support accurate SoC/SoH estimation and digital-twin functionality. It introduces a method that uses only three discrete impedance measurements at frequencies $\omega_{low}$, $\omega_{mid}$, and $\omega_{high}$ to derive all ECM parameters ($R_0$, $R_1$, $C_1$, $A_w$) for the Randles circuit with closed-form algebraic expressions. The approach relies on simple filters and avoids optimization or Fourier-based post-processing, enabling implementation on low-power microcontrollers; it is validated on large prismatic and small cylindrical cells, achieving RMSEs generally below $3\%$ across varied SoC, temperature, and aging. Experimental validation with offline EIS data and online pulsed-current impedance measurements demonstrates robustness to geometry and aging and confirms practical viability for BMS protection, diagnostics, and digital-twin integration in automotive applications.

Abstract

Modeling of Li-ion cells is used in battery management systems (BMS) to determine key states such as state-of-charge (SoC), state-of-health (SoH), etc. Accurate models are also useful in developing a cell-level digital-twin that can be used for protection and diagnostics in the BMS. In this paper, a low-complexity model development is proposed based on the equivalent circuit model (ECM) of the Li-ion cells. The proposed approach uses online impedance measurement at discrete frequencies to derive the ECM that matches closely with the results from the electro-impedance spectroscopy (EIS). The proposed method is suitable to be implemented in a microcontroller with low-computational power, typically used in BMS. Practical design guidelines are proposed to ensure fast and accurate model development. Using the proposed method to enhance the functions of a typical automotive BMS is described. Experimental validation is performed using large prismatic cells and small-capacity cylindrical cells. Root-mean-square error (RMSE) of less than 3\% is observed for a wide variation of operating conditions.

Novel Low-Complexity Model Development for Li-ion Cells Using Online Impedance Measurement

TL;DR

This paper tackles online, low-complexity ECM parameter identification for Li-ion cells within BMS to support accurate SoC/SoH estimation and digital-twin functionality. It introduces a method that uses only three discrete impedance measurements at frequencies , , and to derive all ECM parameters (, , , ) for the Randles circuit with closed-form algebraic expressions. The approach relies on simple filters and avoids optimization or Fourier-based post-processing, enabling implementation on low-power microcontrollers; it is validated on large prismatic and small cylindrical cells, achieving RMSEs generally below across varied SoC, temperature, and aging. Experimental validation with offline EIS data and online pulsed-current impedance measurements demonstrates robustness to geometry and aging and confirms practical viability for BMS protection, diagnostics, and digital-twin integration in automotive applications.

Abstract

Modeling of Li-ion cells is used in battery management systems (BMS) to determine key states such as state-of-charge (SoC), state-of-health (SoH), etc. Accurate models are also useful in developing a cell-level digital-twin that can be used for protection and diagnostics in the BMS. In this paper, a low-complexity model development is proposed based on the equivalent circuit model (ECM) of the Li-ion cells. The proposed approach uses online impedance measurement at discrete frequencies to derive the ECM that matches closely with the results from the electro-impedance spectroscopy (EIS). The proposed method is suitable to be implemented in a microcontroller with low-computational power, typically used in BMS. Practical design guidelines are proposed to ensure fast and accurate model development. Using the proposed method to enhance the functions of a typical automotive BMS is described. Experimental validation is performed using large prismatic cells and small-capacity cylindrical cells. Root-mean-square error (RMSE) of less than 3\% is observed for a wide variation of operating conditions.
Paper Structure (14 sections, 12 equations, 17 figures, 2 tables)

This paper contains 14 sections, 12 equations, 17 figures, 2 tables.

Table of Contents

  1. Introduction
  2. Overview of the Equivalent Circuit Model of Li-ion Cells
  3. Variation of ECM parameters with battery states
  4. Review of the existing methods to obtain ECM parameters
  5. Proposed Model Development Using Discrete Impedance Values
  6. Frequency selection approach
  7. Using Proposed Method with Online Impedance Measurement
  8. Filter design
  9. Applying the proposed method in BMS
  10. Experimental Validation
  11. Validating the proposed ECM parameter identification approach
  12. Validating the method on batteries with different capacity/geometry
  13. Validating the online impedance evaluation approach
  14. Conclusion

Figures (17)

  • Figure 1: Popular equivalent circuit models used in Li-ion cells.
  • Figure 2: Nyquist plot of a 50Ah Li ion cell at 50% SoC and at a temperature of $25^oC$.
  • Figure 3: Illustrating the impact of SoC and Temperature on the battery impedance using Nyquist plots.
  • Figure 4: Discrete frequencies marked on a generic Nyquist plot to obtain the ECM parameters analytically.
  • Figure 5: Impact of frequency selection on the model accuracy.
  • ...and 12 more figures