Abstract
The distribution of alumina concentration is important for optimal cell operations in the aluminium smelting process. However, continuous real-time measurement of alumina concentration is generally infeasible due to the hostile environment in the cell. As such a soft sensor is often needed to estimate the alumina concentration from readily available measurements (e.g., cell voltage and line current). However, these approaches often suffer from poor estimation accuracy when the model error increases (e.g., during the anode effect). To address these problems, this work develops a robust Kalman filter to estimate the spatial alumina concentration using voltage measurements and individual anode current data. The proposed method utilises a Huber function to deal with model errors, resulting in more robust estimations. The effectiveness of this approach is validated through experimental data, demonstrating its potential for improving spatial alumina concentration estimation in the aluminium smelting process.
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Acknowledgements
The authors wish to acknowledge the financial support from ARC Research Hub for Integrated Energy Storage Solutions, and Emirates Global Aluminium Jebel Ali Operations for their technical support, especially from the Technology Development and Transfer team and Operations team.
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Ma, L. et al. (2024). Estimation of the Spatial Alumina Concentration of an Aluminium Smelting Cell Using a Huber Function-Based Kalman Filter. In: Wagstaff, S. (eds) Light Metals 2024. TMS 2024. The Minerals, Metals & Materials Series. Springer, Cham. https://doi.org/10.1007/978-3-031-50308-5_59
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DOI: https://doi.org/10.1007/978-3-031-50308-5_59
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