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Aging Propagation Modeling and State-of-Health Assessment in Advanced Battery Systems

Cordoba Arenas, Andrea Carolina
http://rave.ohiolink.edu/etdc/view?acc_num=osu1385967836

Abstract Details

2013, Doctor of Philosophy, Ohio State University, Mechanical Engineering.
A crucial step towards the large-scale introduction of plug-in hybrid electric vehicles (PHEVs) in the market is to reduce the cost of their energy storage systems. One of the goals of U.S Department of Energy (DOE) Vehicle Technologies Program for hybrid electric systems is to, by 2014, reduce the production cost of Li-ion batteries by nearly 70 percent from 2009 costs. Currently, battery cycle- and calendar-life represents one of the greatest uncertainties in the total life-cycle cost of advanced energy storage devices. Batteries are inherently subject to aging. Aging is the reduction in performance, availability, reliability, and life span of a system or component. The generation of long-term predictions describing the evolution of the aging in time for the purpose of predicting the Remaining Useful Life (RUL) of a system may be understood as Prognosis. The field of battery prognosis has seen progress with respect to model based and data driven algorithms to model aging and estimate RUL of battery cells. However, in advanced battery systems, cells are interconnected and aging propagates. The aging propagation from one cell to others exhibits itself in a reduced system life. Propagation of aging has a profound effect on the accuracy of battery systems state of health (SOH) assessment and prognosis. This thesis proposes a systematic methodology for modeling the propagation of aging in advanced battery systems. The modeling approach is such that it is able to predict battery pack aging, thermal, and electrical dynamics under actual PHEV operation, and includes consideration of random variability of the cells, electrical topology and thermal management. The modeling approach is based on the interaction between dynamic system models and dynamic models of aging propagation. The system level SOH is assessed based on knowledge of individual cells SOH, electrical topology and voltage equalization approach. The proposed methodology is used to develop a computational model-based design tool that can assist in the evaluation of trade-offs between, performance, manufacturing quality, system complexity, battery management approach, and life-cycle. The tool may be used for verification and validation of control algorithms such as estimation and identification, in particular for battery management systems including health management. The proposed methodology constitutes the first steps towards an integrated system design with 'a priori' consideration of health management.
Giorgio Rizzoni (Advisor)
Simona Onori (Advisor)
Yann Guezennec (Committee Member)
Manoj Srinivasan (Committee Member)
Zhang Wei (Committee Member)
244 p.
Mechanical Engineering
Lithium-ion battery pack; PHEV vehicles; System cycle-life prognosis; Capacity and power fade; NMC-LMO cathode; Aging modeling; Cell-to-cell variations; Equivalent circuit model; Lumped-capacitance thermal model

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Citations

  • Cordoba Arenas, A. C. (2013). Aging Propagation Modeling and State-of-Health Assessment in Advanced Battery Systems [Doctoral dissertation, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1385967836

    APA Style (7th edition)

  • Cordoba Arenas, Andrea. Aging Propagation Modeling and State-of-Health Assessment in Advanced Battery Systems. 2013. Ohio State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1385967836.

    MLA Style (8th edition)

  • Cordoba Arenas, Andrea. "Aging Propagation Modeling and State-of-Health Assessment in Advanced Battery Systems." Doctoral dissertation, Ohio State University, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=osu1385967836

    Chicago Manual of Style (17th edition)

osu1385967836
685
© 2013, all rights reserved.
This open access ETD is published by The Ohio State University and OhioLINK.