Proportional-Type Sensor Fault Diagnosis Algorithm for DC/DC Boost Converters Based on Disturbance Observer

Kyunghwan Choi, Kyung-Soo Kim and Seok-Kyoon Kim
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Kyunghwan Choi: Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology, Daejeon 291, Korea
Kyung-Soo Kim: Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology, Daejeon 291, Korea
Seok-Kyoon Kim: Department of Creative Convergence Engineering, Hanbat National University, Daejeon 341-58, Korea

Energies, 2019, vol. 12, issue 8, 1-14

Abstract: This study seeks an advanced sensor fault diagnosis algorithm for DC/DC boost converters governed by nonlinear dynamics with parameter and load uncertainties. The proposed algorithm is designed with a combination of proportional-type state observer and disturbance observer (DOB) without integral actions. The convergence, performance recovery and offset-free properties of the proposed algorithm are derived by analyzing the estimation error dynamics. An optimization process to assign the optimal feedback gain for the state observer is also provided. Finally, a fault diagnosis criteria is introduced to identify the location and type of sensor faults online using normalized residuals. The experimental results verify the effectiveness of the suggested technique under variable operating conditions and three types of sensor faults using a prototype 3 kW DC/DC boost converter.

Keywords: DC/DC boost converter; nonlinear dynamics; parameter variation; fault diagnosis; convergence analysis (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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