Design and Evaluation of Model-Based Health Monitoring Scheme for Automated Manual Transmission | Zendy

Qi Chen | Zendy; Qadeer Ahmed | Zendy; Giorgio Rizzoni | Zendy; Mingming Qiu | Zendy

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Design and Evaluation of Model-Based Health Monitoring Scheme for Automated Manual Transmission

Author(s) -

Qi Chen,

Qadeer Ahmed,

Giorgio Rizzoni,

Mingming Qiu

Publication year - 2016

Publication title -

journal of dynamic systems measurement and control

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.528

H-Index - 89

eISSN - 1528-9028

pISSN - 0022-0434

DOI - 10.1115/1.4033907

Subject(s) - fault detection and isolation , scheme (mathematics) , reliability engineering , manual transmission , fault (geology) , transmission (telecommunications) , set (abstract data type) , computer science , identification (biology) , control engineering , data mining , engineering , real time computing , artificial intelligence , mathematics , mathematical analysis , telecommunications , botany , seismology , actuator , biology , programming language , geology

Health monitoring of automated manual transmission (AMT) in modern vehicles can play a critical role to avoid its malfunctions and ensure vehicle functional safety. In order to meet this demand, this paper presents a model-based fault detection and identification (FDI) scheme for AMT. After developing the fault model of AMT, structural analysis (SA)-based fault detectability and isolability is realized with the available set of sensors, prior to design and development of residuals. The residuals are generated by employing the theory of SA, where the concepts of analytical redundant relationship (ARR) are utilized to make residuals stable and robust. Finally, the proposed FDI scheme is successfully evaluated to detect and isolate the sensor faults in EcoCAR2 AMT.

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