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Injection-Based Online Capacitance Monitoring With Optimal Selection of Injection Frequency in Buck Converters Xinguo Zhang, Student Member, IEEE, Kang Yue , Student Member, IEEE, Haoyu Wang , Senior Member, IEEE, Junrui Liang , Senior Member, IEEE, and Yu Liu , Senior Member, IEEE
Abstract—The aging process of aluminum electrolytic
capacitors leads to a reduction in capacitance, which affects
the safe operation of switching power converters. This article
proposes an online capacitance monitoring method of Buck
converters with high capacitance estimation accuracy. The proposed
method does not ask for specific operating condition
of the circuit, and does not need to model complex circuit
dynamics in time domain. With the measurement errors considered,
the article mathematically proves that the minimum
error of capacitance estimation can be achieved with maximum
sensitivity. Without interrupting the operation of the original
system, a small disturbance with a certain frequency is injected to
the duty cycle of the switches, to generate additional information
for capacitance estimation. To achieve optimal sensitivity for
capacitance estimation, the injection frequency is selected as
the characteristic frequency based on the transfer function for
capacitance estimation. Different candidates of transfer functions
are also compared and evaluated to achieve minimum capacitance
estimation error. Simulation and hardware experiments verify
that optimal parameter sensitivity of capacitance can be achieved
at the characteristic injection frequency, and the capacitance can
be accurately estimated based on the proposed method.
