Experimental Verification of Fault Identification for Overactuated System With a Scaled-Down Electric Vehicle

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The experimental verification of the optimal input design method for fault identification is performed using a scaled-down overactuated electric vehicle. In the previous study, online fault identification was achieved by utilizing all the characteristics of an overactuated system (Park and Park, 2016). The perturbation input signal for the actuator fault identification can be applied to the faulty actuators to suppress most of the control performance loss. The scaled-down vehicle contains four independent driving motors and four independent wheel steering motors to model an extremely overactuated system. The lateral velocity and yaw rate are estimated using the state observer to realize feedback control, and the cornering stiffness is determined based on the estimated values. Experimental verification is performed using steady state cornering maneuvers with sudden actuator faults. The experiments with the scaled-down vehicle support the performance of the optimal input design method. When sensor noise and modeling uncertainties exist, the results from our method were much more precise than the results obtained using the conventional white noise perturbation input signal.
Publisher
KOREAN SOC AUTOMOTIVE ENGINEERS-KSAE
Issue Date
2020-08
Language
English
Article Type
Article
Citation

INTERNATIONAL JOURNAL OF AUTOMOTIVE TECHNOLOGY, v.21, no.4, pp.1037 - 1045

ISSN
1229-9138
DOI
10.1007/s12239-020-0098-4
URI
http://hdl.handle.net/10203/275625
Appears in Collection
ME-Journal Papers(저널논문)
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