scholarly journals Resonant converter for Data Center and Super Computer applications

2019 ◽  
Vol 8 (3) ◽  
pp. 3873-3877

In this article proposes the load sharing performance of converters in supercomputers. A new control method is proposed for dc to dc switch controlled capacitor (SCC) - LLC converter. The switching frequency is utilized for controlling the regulation of output voltage. It can give the good frequency variation range and peak gain range compared to conventional converters. To attain load sharing the half wave switch controlled capacitor (SCC) is used to control the resonant frequency of each LLC stage. The simulation results are compared with experimental results. A 600w prototype model is developed to prove the feasibility

Author(s):  
Rakhi K ◽  
Ilango Karuppasamy ◽  
Manjula G Nair

The long established battery chargers are having many drawbacks such as prominent ripple charging current, less efficiency and bulky in size. To overcome these drawbacks of conventional battery charger, several charging circuits have been proposed and inevitability force to design a high-performance battery charger with small in size and improved efficiency. In this paper solar photovoltaic system based half-bridge series–parallel resonant converter (HBSPRC) charger is proposed for battery interface. The converter is designed to abolish low and high-frequency ripple currents and thus take full advantage of the life of secondary battery circuit. This is achieved by designing converter switches turn on at zero current and zero voltage with switching frequency greater than that of resonance frequency which leads to freewheeling diodes need not have very fast reverse-recovery characteristics. The performance of the power converters depends upon the control method adopted; in this work fuzzy logic controller is used for controlling the output voltage of HBSPRC. The fuzzy control scheme for the HBSPR converter has been designed and validated in hardware implementation of HBSPRC switching technique.  From the results, it is found that the proposed battery charging system which reduces the switching loss and voltage stress across the power switches which increases the efficiency of the converter.


2017 ◽  
Vol 53 (17) ◽  
pp. 1218-1220 ◽  
Author(s):  
Yiming Chen ◽  
Jianping Xu ◽  
Jing Cao ◽  
Leiming Lin ◽  
Hongbo Ma

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 113175-113182
Author(s):  
Tianyu Zhu ◽  
Yanchao Ji ◽  
Jianze Wang ◽  
Yiqi Liu

Electronics ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 370 ◽  
Author(s):  
Bor-Ren Lin ◽  
Chu-Xian Dai

This paper presents a inductor–inductor–capacitor (LLC) resonant converter with variable winding turns to achieve wide voltage operation (100–400 V) and realize soft switching operation over the entire load range. Resonant converters have been developed for consumer power units in computers, power servers, medical equipment, and adaptors due to the advantages of less switching loss and better circuit efficiency. The main disadvantages of the LLC resonant converter are narrow voltage range operation owing to wide switching frequency variation and limited voltage gain. For computer power supplies with hold-up time function, electric vehicle battery chargers, and for power conversion in solar panels, wide input voltage or wide output voltage operation capability is normally demanded for powered electronics. To meet these requirements, the variable winding turns are used in the presented circuit to achieve high- or low-voltage gain when Vin is at low- or high-voltage, respectively. Therefore, the wide voltage operation capability can be implemented in the presented resonant circuit. The variable winding turns are controlled by an alternating current (AC) power switch with two back-to-back metal-oxide-semiconductor field-effect transistors (MOSFETs). A 500-W prototype is implemented and test results are presented to confirm the converter performance.


2017 ◽  
Vol 26 (11) ◽  
pp. 1750175
Author(s):  
Changyuan Chang ◽  
Chao Hong ◽  
Yang Xu ◽  
Hailong Sun ◽  
Yao Chen

A constant voltage AC–DC converter based on the digital assistant technology is proposed in this paper, which has the advantage of high output precision. In this paper, a novel digital exponential wave generator is adopted in Constant Voltage (CV) mode to replace the normal triangle waveform to obtain a wider range of switching frequency, increasing the accuracy of output voltage under light load. The control chip is implemented based on NEC 1[Formula: see text][Formula: see text]m 5[Formula: see text]V/40[Formula: see text]V HVCMOS process, and a 5[Formula: see text]V/1.2[Formula: see text]A prototype has been built to verify the proposed control method. In PFM mode the deviation of output voltage is within [Formula: see text]% and the load regulation is [Formula: see text]%. Meanwhile, when the load jumps from light to heavy, the minimum output voltage could be maintained above 4.16[Formula: see text]V.


2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Yue Liu ◽  
Guojun Tan

Direct power control (DPC) of pulse width modulation (PWM) is often used to control the instantaneous power of rectifiers. The instantaneous power contains both grid voltage and current information, and its value is not affected by coordinate transformation. It is constant in steady state and reflects the DC control characteristics. However, the switching frequency of traditional DPC is not fixed, the DC voltage has static error, and the system fluctuates greatly. In this work, we introduce the concept of stator flux of the AC motor into the PWM rectifier. Combined with the space vector PWM (SVPWM) technology, we use the virtual flux estimation method to obtain the instantaneous power value, which saves the grid voltage sensor, eliminates the static difference of DC voltage. Furthermore, considering that the neural proportion integral differential (PID) control depends heavily on the initial weight coefficient of the network, we use chaos particle swarm optimization (CPSO) algorithm, which combines the basic PSO algorithm and chaos theory to optimize the initial weight coefficient of neural PID control. In the experiment, the results prove that the performance of the controller can be effectively improved.


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