Remaining Useful Life Prediction for Components of Automated Guided Vehicles

被引:0
作者
Mrugalska, Beata [1 ]
Stetter, Ralf [2 ]
机构
[1] Poznan Univ Tech, Fac Engn Management, Ul Strzelecka 11, PL-60965 Poznan, Poland
[2] Hsch Ravensburg Weingarten, Doggenriedstr, D-88250 Weingarten, Germany
来源
ADVANCES IN MANUFACTURING, PRODUCTION MANAGEMENT AND PROCESS CONTROL | 2020年 / 971卷
关键词
Remaining useful life; Prognosis; Automated guided vehicles;
D O I
10.1007/978-3-030-20494-5_39
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:420 / 429
页数:10
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