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Title: Inductive model development for lithium-ion batteries to predict life and performance.

Abstract

Sandia National Laboratories has been conducting studies on performance of laboratory and commercial lithium-ion and other types of electrochemical cells using inductive models [1]. The objectives of these investigations are: (1) To develop procedures and techniques to rapidly determine performance degradation rates while these cells undergo life tests; (2) To model cell voltage and capacity in order to simulate cell performance characteristics under variable load and temperature conditions; (3) To model rechargeable battery degradation under charge/discharge cycles and many other conditions. The inductive model and methodology are particularly useful when complicated cell performance behaviors are involved, which are often difficult to be interpreted from simple empirical approaches. We find that the inductive model can be used effectively: (1) To enable efficient predictions of battery life; (2) To characterize system behavior. Inductive models provide convenient tools to characterize system behavior using experimentally or analytically derived data in an efficient and robust framework. The approach does not require detailed phenomenological development. There are certain advantages unique to this approach. Among these advantages is the ability to avoid making measurements of hard to determine physical parameters or having to understand cell processes sufficiently to write mathematical functions describing their behavior. We used artificialmore » neural network for inductive modeling, along with ancillary mathematical tools to improve their accuracy. This paper summarizes efforts to use inductive tools for cell and battery modeling. Examples of numerical results will be presented. One of them is related to high power lithium-ion batteries tested under the U.S. Department of Energy Advanced Technology Development Program for hybrid vehicle applications. Sandia National Laboratories is involved in the development of accelerated life testing and thermal abuse tests to enhance the understanding of power and capacity fade issues and predict life of the battery under a nominal use condition. This paper will use power and capacity fade behaviors of a Ni-oxide-based lithium-ion battery system to illustrate how effective the inductive model can interpret the cell behavior and provide predictions of life. We will discuss the analysis of the fading behavior associated with the cell performance and explain how the model can predict cell performance.« less

Authors:
;  [1]; ; ; ;
  1. (University of Hawaii, Honolulu, HI)
Publication Date:
Research Org.:
Sandia National Laboratories
Sponsoring Org.:
USDOE
OSTI Identifier:
959095
Report Number(s):
SAND2004-3074J
TRN: US201001%%23
DOE Contract Number:  
AC04-94AL85000
Resource Type:
Journal Article
Journal Name:
Proposed for publication in the Electrochemical Society Symposium Publication.
Additional Journal Information:
Journal Name: Proposed for publication in the Electrochemical Society Symposium Publication.
Country of Publication:
United States
Language:
English
Subject:
25 ENERGY STORAGE; METAL-NONMETAL BATTERIES; LITHIUM; MATHEMATICAL MODELS; SERVICE LIFE; PERFORMANCE; FORECASTING; NICKEL OXIDES

Citation Formats

Doughty, Daniel Harvey, Liaw, Bor Yann, Case, Herbert Luedinghaus, Urbina, Angel, Jungst, Rudolph George, and Paez, Thomas Lee. Inductive model development for lithium-ion batteries to predict life and performance.. United States: N. p., 2004. Web.
Doughty, Daniel Harvey, Liaw, Bor Yann, Case, Herbert Luedinghaus, Urbina, Angel, Jungst, Rudolph George, & Paez, Thomas Lee. Inductive model development for lithium-ion batteries to predict life and performance.. United States.
Doughty, Daniel Harvey, Liaw, Bor Yann, Case, Herbert Luedinghaus, Urbina, Angel, Jungst, Rudolph George, and Paez, Thomas Lee. Tue . "Inductive model development for lithium-ion batteries to predict life and performance.". United States.
@article{osti_959095,
title = {Inductive model development for lithium-ion batteries to predict life and performance.},
author = {Doughty, Daniel Harvey and Liaw, Bor Yann and Case, Herbert Luedinghaus and Urbina, Angel and Jungst, Rudolph George and Paez, Thomas Lee},
abstractNote = {Sandia National Laboratories has been conducting studies on performance of laboratory and commercial lithium-ion and other types of electrochemical cells using inductive models [1]. The objectives of these investigations are: (1) To develop procedures and techniques to rapidly determine performance degradation rates while these cells undergo life tests; (2) To model cell voltage and capacity in order to simulate cell performance characteristics under variable load and temperature conditions; (3) To model rechargeable battery degradation under charge/discharge cycles and many other conditions. The inductive model and methodology are particularly useful when complicated cell performance behaviors are involved, which are often difficult to be interpreted from simple empirical approaches. We find that the inductive model can be used effectively: (1) To enable efficient predictions of battery life; (2) To characterize system behavior. Inductive models provide convenient tools to characterize system behavior using experimentally or analytically derived data in an efficient and robust framework. The approach does not require detailed phenomenological development. There are certain advantages unique to this approach. Among these advantages is the ability to avoid making measurements of hard to determine physical parameters or having to understand cell processes sufficiently to write mathematical functions describing their behavior. We used artificial neural network for inductive modeling, along with ancillary mathematical tools to improve their accuracy. This paper summarizes efforts to use inductive tools for cell and battery modeling. Examples of numerical results will be presented. One of them is related to high power lithium-ion batteries tested under the U.S. Department of Energy Advanced Technology Development Program for hybrid vehicle applications. Sandia National Laboratories is involved in the development of accelerated life testing and thermal abuse tests to enhance the understanding of power and capacity fade issues and predict life of the battery under a nominal use condition. This paper will use power and capacity fade behaviors of a Ni-oxide-based lithium-ion battery system to illustrate how effective the inductive model can interpret the cell behavior and provide predictions of life. We will discuss the analysis of the fading behavior associated with the cell performance and explain how the model can predict cell performance.},
doi = {},
journal = {Proposed for publication in the Electrochemical Society Symposium Publication.},
number = ,
volume = ,
place = {United States},
year = {2004},
month = {6}
}