The fractional-order model is effective in simulating the battery’s dynamic behaviour. However, the real-time implementation of a fractional-order component can be complicated as the related Grünwald–Letnikov (G–L) definition involves sophisticated cumulative operations. Here, we propose to use an integer-order model with frequency-dependent parameters to approximate the fractional order model. Its implementation is described as follows: In the frequency domain, multiple third-order RC models are switched with frequency to depict the battery’s impedance spectroscopy. In the time domain, our model is transformed into a weighted summation of multiple third-order RC models, whose weighting factors are determined by the current signal’s energy in the frequency ranges of interest. The comparison between the integer order RC model, the proposed frequency-dependent RC model, and the fractional order model is carried out in both the time and frequency domain to verify the effectiveness of the proposed method. The computational effort of the proposed model can be significantly reduced by 85% compared with the fractional order model, and the modelling error is reduced by 51% compared with the conventional integer order model. Our model provides an accurate yet computationally efficient way to describe the battery’s dynamic.
|Title of host publication||The Proceedings of the 5th International Conference on Energy Storage and Intelligent Vehicles, ICEIV 2022|
|Editors||Fengchun SUN, Qingxin YANG, Erik DAHLQUIST, Rui XIONG|
|Publisher||Springer Science and Business Media Deutschland GmbH|
|Number of pages||9|
|Publication status||Published - 2023|
|Event||5th International Conference on Energy Storage and Intelligent Vehicles, ICEIV 2022 - Virtual, Online|
Duration: 3 Dec 2022 → 4 Dec 2022
|Name||Lecture Notes in Electrical Engineering|
|Conference||5th International Conference on Energy Storage and Intelligent Vehicles, ICEIV 2022|
|Period||3/12/22 → 4/12/22|
Bibliographical noteFunding Information:
This work is supported by the Guangdong scientific and technological project (2019A050516002), Guangzhou Scientific and Technological Project (202002030323), and the National Natural Science Foundation of China (51977131). The first author is an awardee of the Hong Kong RGC Postdoctoral Fellowship (PDFS2122-6S06).
© 2023, Beijing Paike Culture Commu. Co., Ltd.
- Fractional-order model
- Frequency-dependent model
- Integer-order model