Autonomous Vehicle Battery State-of-Charge Prognostics Enhanced Mission Planning



Published Nov 1, 2020
Bin Zhang Liang Tang Jonathan DeCastro Michael Roemer Kai Goebel


Most mission planning algorithms are designed for healthy systems. When faults occur in a system, it is advantageous to optimize the mission plan by taking the system health condition into consideration. In this paper, a mission planning scheme is proposed to integrate real-time prognostics in a receding horizon path planning framework to accommodate the system fault. In this scheme, the state-of-charge of a battery is monitored and predicted by a particle-filtering based prognostic algorithm. The predicted state-of-charge and remaining useful life of the battery are used in the mission planning to minimize mission failure risk. A series of experiments are presented on a robotic platform, which is powered by a Lithium-ion battery, to demonstrate and verify the proposed scheme.

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diagnosis, prognosis, fault-tolerant control, reconfigurable control, PHM

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