Abstract
At present, compared with lithium ion batteries, the accuracy of detection, modeling and state of charge (SOC) estimation still need to be improved in aluminum air battery management system. First, the relation curve between open circuit voltage and SOC is calibrated by discharging experiments under different rates. Then, an equivalent circuit parameter identification method by recursive least square method with forgetting factor is presented to identify the model parameters. Finally, with real-time parameter identification of the second order RC battery equivalent circuit model of battery, the real-time variation of open circuit voltage (OCV) value is obtained. A piecewise SOC estimation method combining the online open circuit voltage method and the ampere-hour integral method is proposed, and the SOC estimation error is no bigger than 0.05. The research result shows that this method is not only feasible, but also can effectively judge whether the aluminum air battery becomes invalid or not.
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Acknowledgments
This research is supported by the Zhejiang Provincial public welfare Foundation (LGG19E070004), China.
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Cai, H., Cheng, S., Wang, Y., Zhang, S., Liu, W. (2020). Study on the Modeling and Online SOC Estimation of the Aluminum Air Battery. In: Fei, M., Li, K., Yang, Z., Niu, Q., Li, X. (eds) Recent Featured Applications of Artificial Intelligence Methods. LSMS 2020 and ICSEE 2020 Workshops. LSMS ICSEE 2020 2020. Communications in Computer and Information Science, vol 1303. Springer, Singapore. https://doi.org/10.1007/978-981-33-6378-6_9
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DOI: https://doi.org/10.1007/978-981-33-6378-6_9
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