Theses and Dissertations


Jianwei Li

Issuing Body

Mississippi State University


Mazzola, Michael S.

Committee Member

Molen, G. Marshall

Committee Member

Xin, Ming

Committee Member

Younan, Nicolas H.

Date of Degree


Document Type

Dissertation - Open Access


Electrical Engineering

Degree Name

Doctor of Philosophy


James Worth Bagley College of Engineering


Department of Electrical and Computer Engineering


A behavioral battery modeling approach aimed at large format batteries is the topic of this dissertation. Drawing from the development of cell - level electrical analogue battery models, the comprehensive modeling approach described here shows how to scale a high fidelity battery cell model to a computationally fast battery model of large format batteries for system level design and simulation. The accurate behavioral battery model is performance - driven and tailored for stringent system simulation requirements. A novel bandwidth - based parameter extraction algorithm and advanced State of Charge (SOC) - Open Circuit Voltage (OCV) profile identification method are presented. While a real-world battery system is non-linear and time varying, a truncated representation of the system is provided by a commonly studied non-physical "electrical analogue" battery model. However, the limited bandwidth characteristic of the electrical analogue battery model is often overlooked. The reported algorithm starts by assessing a desired battery application, followed by modeling the battery according to the application bandwidth, and then estimating the model parameters using the sequential quadratic programming method. This approach recognizes and makes use of the limited bandwidth of the battery model by reconciling the bandwidth of the application into the bandwidth of the electrical analogue battery model. The model will help in vehicle concept development, and provide an analytical tool during the process of selecting the most appropriate battery during system design but before a prototype system is built. Another application is to represent the plant in realtime model-based battery management and control systems embedded in actual application controllers. This modeling approach is independent of the battery chemistry and therefore it is applicable to lithium-ion, nickel-metal-hydride (NiMH), and lead-acid batteries, among others.