| The primary objective of this dissertation is to present a new method of modeling the charging and discharging processes of lithium-ion batteries, investigate their effectiveness and explore their applications. The primary contributions of this research work include development of adaptive time series models for modeling the charging and discharging processes of individual lithium-ion cells, extension of the above concepts to multi-cell lithium-ion batteries, and development of a new scheme for predicting the state of health of lithium-ion batteries.;The battery charge/discharge time series model introduced here consists of a group of piecewise linear time-invariant models, whose parameters are adapted online over time. Thus, the combined overall model is capable of modeling a nonlinear time-varying process, such as a li-ion battery charging/discharging process, quite well. Such models are appealing, because the piecewise linear nature of such models can account for the nonlinear characteristics of a battery. Also, the time-adaptive nature of such models account for the time-varying voltage-current characteristics of a battery quite well. To validate the theory, modeling results for both simulated test data and experimental data gathered from a high-power automotive-grade Li-ion cell are presented.;The above modeling concept is then extended to model the charging and discharging processes of multi-cell lithium-ion batteries. To validate the theory, modeling results for simulated test data are presented.;Finally, as an application of the proposed modeling strategy, a new scheme for estimating the state of health of lithium-ion batteries is presented. To validate the theory, modeling results for simulated test data are presented.;The results obtained from our simulation and experimental studies demonstrate the effectiveness of the proposed modeling strategy and indicate the potential usefulness of such models for a battery management system. |
