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A high-fidelity battery model capable of accurately predicting battery performance is required for proper design and operation of battery-powered systems. However, the existing battery models have at least one of the following drawbacks: 1) requiring intensive computation due to high complexity, 2) not applicable for electrical circuit design and simulation, and 3) not capable of accurately capturing the State of Charge (SOC) and predicting runtime of the battery due to neglecting the nonlinear capacity effects. This thesis proposes a novel hybrid battery model, which takes the advantages of an electrical circuit battery model to accurately predicting the dynamic circuit characteristics of the battery, and an analytical battery model to capturing the nonlinear capacity effects for accurate SOC tracking and runtime prediction of the battery. The proposed battery model is validated by simulation and experimental studies for single-cell and multicell polymer lithium-ion batteries as well as for a lead-acid battery. The proposed model is applicable to other types and sizes of electrochemical battery cells, such as Nikel Cadmium (NiCd) and Nikel Metal Hydride (NiMH). The proposed battery model is computationally effective for simulation, design, and real-time management of battery-powered systems.
Adviser: Wei Qiao