4.6 Article

Implementation of a Cascade Fault Tolerant Control and Fault Diagnosis Design for a Modular Power Supply

Journal

ACTUATORS
Volume 12, Issue 3, Pages -

Publisher

MDPI
DOI: 10.3390/act12030135

Keywords

interleaved boost converter; cascade sliding mode control; bond graph; fault diagnosis; analytic redundancy relations; energy

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The main objective of this research was to develop reliable and intelligent power sources for the future. To achieve this, a modular stand-alone solar energy-based DC power supply was designed and implemented. The converter topology used was a two-stage interleaved boost converter, monitored in closed loop, and the diagnosis method was based on analytic redundancy relations derived from the bond graph model.
The main objective of this research work was to develop reliable and intelligent power sources for the future. To achieve this objective, a modular stand-alone solar energy-based direct current (DC) power supply was designed and implemented. The converter topology used is a two-stage interleaved boost converter, which is monitored in closed loop. The diagnosis method is based on analytic redundancy relations (ARRs) deduced from the bond graph (BG) model, which can be used to detect the failures of power switches, sensors, and discrete components such as the output capacitor. The proposed supervision scheme including a passive fault-tolerant cascade proportional integral sliding mode control (PI-SMC) for the two-stage boost converter connected to a solar panel is suitable for real applications. Most model-based diagnosis approaches for power converters typically deal with open circuit and short circuit faults, but the proposed method offers the advantage of detecting the failures of other vital components. Practical experiments on a newly designed and constructed prototype, along with simulations under PSIM software, confirm the efficiency of the control scheme and the successful recovery of a faulty stage by manual isolation. In future work, the automation of this reconfiguration task could be based on the successful simulation results of the diagnosis method.

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