Fault Detection and Isolation of Automotive Air Conditioning Systems using First Principle Models

Although model-based fault detection and isolation (FDI) has become a common design tool in automotive fields, its application to automotive air conditioning (A/C) systems based upon vapor compression cycles is limited due to the lack of control-oriented models characterizing the refrigerant phase change. The emergence of moving boundary method (MBM) illuminates a promising way of assisting FDI scheme development, because common faults in automotive A/C systems, such as compressor fault, pressure transducer fault, and fouling fault, can be easily incorporated by the control-oriented model developed. Out of various observed-based FDI methods, the H ∞ filter technique, due to its robustness to model uncertainties and external disturbances, is chosen for designing FDI scheme over actuator/sensor/parameter faults. The model and the filter are connected closed-loop by an H ∞ controller gain-scheduled to meet different cooling loads. From the closed-loop analysis results, the H ∞ filter is capable of detecting and isolating actuator/sensor faults, as well as estimating parameter faults, even if external disturbances imposed on the air side of the evaporator exist.

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