Analytic discrete state-space model of LLC resonant converter

• Published in: e-Prime Vol. 9; p. 100625
• Main Authors: Rezaii, Elias Yousefi, Carvalho, Adriano
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.09.2024; Elsevier
• Subjects: Audio-susceptibility; Control-to-output; Discrete; Exact discretization; LLC; Resonant; Sampled-data model; Small-signal; State-space model; LLC; Audio-susceptibility; Sampled-data model; Small-signal; Exact discretization; Resonant; Discrete; State-space model; Control-to-output
• ISSN: 2772-6711; 2772-6711
• DOI: 10.1016/j.prime.2024.100625

•Discrete state-space model of LLC converter.•Exact estimations of cyclic steady-state trajectories of LLC converter using exact discretization method.•Obtaining small-signal model of LLC converter using sampled-data model. The LLC resonant converter has widely been used for having high-frequency soft-switching capability which could lead to high power density power electronic solutions, and higher power conversion efficiency at lower costs. However, the presence of excessive non-linearity resulting from power conversion through the resonant tank has led to a lack of accurate and reliable large-signal and small-signal models which limits the performance optimization. This paper presents a theoretical analysis of the LLC converter using the sampled-data modeling approach to accurately convert the continuous-time-variant state equations to discrete-time-invariant state equations and solve them using switching time-segmented boundary conditions to obtain the discrete large-signal model. The small-signal model is obtained by perturbation and linearization of the steady-state model in the vicinity of the cyclic equilibrium states of the converter. Theoretical analysis results are validated by simulating a 650W LLC converter in Matlab Simulink. Based on the provided results, the proposed steady-state and small-signal models can accurately predict the dynamic behavior of the LLC converter in different operational conditions.