Abstract
Understanding battery characteristic behaviors is indispensable in designing and managing large-scale battery-based energy storage systems in high-power applications. This paper presents a practical-based characterization method to model the ohmic series resistance of lithium-ion batteries under life-cycle consideration. Aging cells were prepared in a controlled environment, and the testing information was automatically characterized using a developed computer-based battery test system. An experimental methodology based on the cycling of pulse tests is applied for modeling the ohmic series resistance. Several aspects of the testing parameters during the cycling operations, such as the characteristic changes of the ohmic series resistance, amplitudes of the periodic test current, cell capacity, state of charge, and the rate of change of the resistance increment, are also investigated and analyzed so as to fulfill the resistance model. The accuracy of the proposed model is verified by comparing the testing information, showing a satisfactory result.
Highlights
Nowadays, lithium-ion batteries (LIBs) are promising energy storage devices being used in many applications, such as portable devices, personal electric vehicles, public transportation, and renewable energy storage and grid supporting systems
We focus on the modeling of the ohmic series resistance (OSR) of the lithium-ion battery to understand the resistance characteristic behaviors on the changing of life cycles
When compared to the cell at the beginning of life at 50% state of charge (SOC), the OSRs of the highest testing cycle as 2400 cycles increased by 18.38% and 15.08% during the charge and discharge, respectively
Summary
Lithium-ion batteries (LIBs) are promising energy storage devices being used in many applications, such as portable devices, personal electric vehicles, public transportation, and renewable energy storage and grid supporting systems. In high-power and high-voltage applications with smart grid technologies, a battery-based energy storage system (BESS) is an important part to maintain the grid stability and flexibility of the system. One is the direct current (DC) pulse test, which is generally used for the simple parameter identification of LIBs. The other is an electrochemical impedance spectroscopy (EIS), which is a complicated alternating current (AC) impedance-based measurement in the frequency domain [2,3]. Rahimi-Eichi et al [4] applied a piecewise linear approximation technique and the DC pulse method with a one-time constant EECM to estimate the online parameters and state of charge (SOC) of the LIB. Rahmoun et al [5] demonstrated the methodology to determine the battery SOC
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