Abstract
This paper presents an approach to prediction of the Remaining Useful Life (RUL) for components of Automated Guided Vehicles (AGV). The focus is paid on the batteries which are a crucial element of these systems and influence the possible operation times considerably. For batteries, two aspects are taken into consideration, if the remaining useful life should be predicted: the State of Charge (SOC) and the State of Health (SOH). Both aspects include non-linearity and are influenced by many factors such as temperature and discharging velocity. To solve such problem a new estimator of SOC and SOH was developed. The proposed approach was applied for Health-Aware Model Predictive Control (H-A MPC) of two cooperate AGV.
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Mrugalska, B., Stetter, R. (2020). Remaining Useful Life Prediction for Components of Automated Guided Vehicles. In: Karwowski, W., Trzcielinski, S., Mrugalska, B. (eds) Advances in Manufacturing, Production Management and Process Control. AHFE 2019. Advances in Intelligent Systems and Computing, vol 971. Springer, Cham. https://doi.org/10.1007/978-3-030-20494-5_39
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DOI: https://doi.org/10.1007/978-3-030-20494-5_39
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