Adaptive Optimization Charging Strategy for LCC Resonant Capacitor Charging Power Supply

In repetitive pulse power applications, the charging capacitor time occupies most of the time in a pulse period, and important parameters such as pulse repetition rate are restricted by the charging speed of the capacitor. To accelerate the charging speed and make full use of the components’ capacity, a novel adaptive optimization charging (AOC) strategy is proposed for capacitor charging power supply (CCPS). Moreover, to improve the accuracy of the inductor-capacitor-capacitor (LCC) model, a fundamental harmonic approximation model based on continuous resonant current (CRC-FHA) is put forward. Compared with conventional FHA which uses a discontinuous transformer current
$i_{T}$
, the CRC-FHA model is established by adopting the continuous and more sinusoidal resonant current
$i_{\mathrm{ r}}$
. The analytical expressions are derived for the maximum resonant current
$I_{\max }$
, zero-voltage-switching (ZVS) boundary, and the multidimensional relationship between the output voltage, the peak value of resonant current, average output current, and switching frequency. Accordingly, the proposed AOC strategy sets the maximum resonant current boundary, the ZVS charging boundary, and the upper and lower switching frequency limits as constraints to get adaptive reference output current values in real-time to make full use of the capacity of the converter to improve the charging speed. Compared with a hybrid constant current-constant power (HCC-CP) charging profile, the proposed AOC strategy has an advantage in charging speed and soft switching range with the same maximum resonant current. Finally, the accuracy of the FHA model adopting resonant current for LCC resonant converter and the effectiveness of the AOC strategy is verified by the simulation and a 2174 W LCC resonant converter.