Analyzing and minimizing capacity fade through optimal model-based control: theory and experimental validation
Name
Pathak_ESCTrans_2017.pdf
Description
Published version
Size
819.95 KB
Format
Adobe PDF
Checksum (MD5)
7bee9599c0f3b6c40d916e63ad4fc622
Author(s)
Pathak, Manan
Sonawane, Dayaram
Santhanagopalan, Shriram
Braatz, Richard D
Subramanian, Venkat R.
Alternative Title
(Invited) Analyzing and minimizing capacity fade through optimal model-based control: theory and experimental validation
Date Issued
2016
Journal
ECS transactions
Publisher
The Electrochemical Society
Citation
Pathak, Manan, et al., "Analyzing and minimizing capacity fade through optimal model-based control: theory and experimental validation." ECS transactions 75 (2016): no. 23 doi 10.1149/07523.0051ECST ©2016 Author(s)
Version
Final published version
Abstract
In order to significantly expand the BEV market, and to increase the use of lithium-ion batteries in electric grids, there is a need to develop optimal charging strategies to utilize the batteries more efficiently and enable longer life. Advanced battery management systems that can calculate and implement such strategies in real time are expected to play a critical role for this purpose. This article investigates different approaches for determining model-based optimal charging profiles for batteries, and experimentally validates the gain obtained using such profiles. Optimal profiles that maximize the cycle life of the cells are implemented on 16 Ah NMC cells for 30 minutes of charge followed by 5C discharge, and the cycle life is compared to a standard 2C CC-CV charge and 5C discharge. An improvement of more than 100%in cycle life is observed experimentally, for our test conditions on this cell design. This study is the first to experimentally demonstrate that the improved extra knowledge obtained by sophisticated physics-based models results in significant improvements in battery performance when employed in a real time control algorithm. ©2016 Paper delivered at the 230th ECS Meeting/PRIME 2016, October 2, 2016-October 7, 2016, Honolulu, Hawaii
MIT Department
Massachusetts Institute of Technology. Department of Chemical Engineering
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1149/07523.0051ECST
