Abstract
Battery impedance is essential to the management of lithium-ion batteries for electric vehicles (EVs), and impedance characterization can help to monitor and predict the battery states. Many studies have been undertaken to investigate impedance characterization and the factors that influence impedance. However, few studies regarding the influence of the internal temperature gradient, which is caused by heat generation during operation, have been presented. We have comprehensively studied the influence of the internal temperature gradient on impedance characterization and the modeling of battery impedance, and have proposed a discretization model to capture battery impedance characterization considering the temperature gradient. Several experiments, including experiments with artificial temperature gradients, are designed and implemented to study the influence of the internal temperature gradient on battery impedance. Based on the experimental results, the parameters of the non-linear impedance model are obtained, and the relationship between the parameters and temperature is further established. The experimental results show that the temperature gradient will influence battery impedance and the temperature distribution can be considered to be approximately linear. The verification results indicate that the proposed discretization model has a good performance and can be used to describe the actual characterization of the battery with an internal temperature gradient.
Highlights
The world faces increasingly severe environmental problems, including the greenhouse effect and industrial pollution [1]
Safe operating conditions are hard to ensure for lithium-ion batteries (LIBs), so the battery management system (BMS) is essential when LIBs are used in vehicles [6,7]
In our experiment with artificial temperature gradients, we find that the temperature distribution can be approximately considered to be linear, so the central temperature is equal to the average temperature
Summary
The world faces increasingly severe environmental problems, including the greenhouse effect and industrial pollution [1]. It is beset by the shortage of resources, especially fossil fuel energy. To resolve these urgent problems, people consider green cars including battery electric vehicles (BEVs), fuel cell electric vehicles (FCEVs), hybrid EVs (HEVs), and so on, to be critically important [2]. To monitor and better manage LIBs in the battery pack, the pack voltage, pack current, cell voltage, cell temperature, cell impedance and so on must be detected
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