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A Tanks-in-Series Approach to Estimate Parameters for Lithium-Ion Battery Models

Journal Article · · Journal of the Electrochemical Society
 [1];  [1];  [2];  [3];  [3];  [4];  [1]
  1. Univ. of Texas, Austin, TX (United States)
  2. Univ. of Washington, Seattle, WA (United States)
  3. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
  4. Indian Inst. of Technology Bombay, Maharashtra (India)
+ Show Author Affiliations

Advanced Battery Management Systems (BMS) play a vital role in monitoring, predicting, and controlling the performance of lithium-ion batteries. BMS employing sophisticated electrochemical models can help increase battery cycle life and minimize charging time. However, in order to realize the full potential of electrochemical model-based BMS, it is critical to ensure accurate predictions and proper model parameterization. The accuracy of the predictions of an electrochemical model is dependent on the accuracy of its parameters, the values of which might change with battery cycling and aging. Parameter estimation for an electrochemical model is generally challenging due to the nonlinear nature and computational complexity of the model equations. To this end, this work utilizes the recently proposed Tanks-in-Series model for Li-ion batteries (J.Electrochem. Soc., 167, 013534 (2020)) to perform parameter estimation. The Tanks-in-Series approach allows for substantially faster parameter estimation compared to the original pseudo two-dimensional (p2D) model. The objective of this work is thus to demonstrate the gain in computational efficiency from the Tanks-in-Series approach. A sensitivity analysis of model parameters is also performed to benchmark the fidelity of the Tanks-in-Series model.

Research Organization:
Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
Sponsoring Organization:
USDOE Office of Electricity Delivery and Energy Reliability (OE); USDOE National Nuclear Security Administration (NNSA)
Grant/Contract Number:
NA0003525
OSTI ID:
1872016
Report Number(s):
SAND2022-6046J; 706317
Journal Information:
Journal of the Electrochemical Society, Journal Name: Journal of the Electrochemical Society Journal Issue: 5 Vol. 169; ISSN 0013-4651
Publisher:
IOP PublishingCopyright Statement
Country of Publication:
United States
Language:
English

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