Analysis and Implementation of the Crowbar Clamping Circuit for Surge Voltage Reduction in the DC Solid-State Circuit Breakeropen access
- Authors
- Sok, Phanit; Song, Sung-Geun; Kang, Feel-Soon
- Issue Date
- Oct-2024
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Keywords
- Voltage control; Integrated circuit modeling; Surge protection; Varistors; SPICE; Snubbers; Clamps; Mathematical models; Crowbar clamping circuit; curve fit function; metal oxide varistor (MOV); overvoltage suppression; snubber circuit; solid-state circuit breaker (SSCB); surge voltage
- Citation
- IEEE Access, v.12, pp 149018 - 149031
- Pages
- 14
- Indexed
- SCIE
SCOPUS
- Journal Title
- IEEE Access
- Volume
- 12
- Start Page
- 149018
- End Page
- 149031
- URI
- https://scholarworks.gnu.ac.kr/handle/sw.gnu/74648
- DOI
- 10.1109/ACCESS.2024.3476123
- ISSN
- 2169-3536
2169-3536
- Abstract
- The DC Solid-State Circuit Breaker (SSCB) is usually used to prevent damage to sensitive equipment and ensure system stability by rapidly interrupting fault currents and improving safety. However, the surge voltage, driven by high switching speeds and the stray inductance of Metal Oxide Varistors (MOVs), can easily damage semiconductor switches in DC SSCB. Due to this reason, this paper presents a method for effectively suppressing surge voltage and addressing this problem. The surge voltage suppression method analyzed and simulated in this paper involves using a crowbar clamping circuit, which divides the overvoltage protection into three MOVs. This approach employs lower DC-rated voltages and a maximum clamping voltage achieved by double MOVs in series with a thyristor, and this configuration optimizes surge voltage protection. It is facilitated by a voltage divider circuit composed of two resistors. A higher-rated single MOV is also used for energy absorption from the stray inductance. After theoretical analysis, it is verified by computer-aided simulations and small-scale experiments. A significant challenge in DC SSCB is simulating the behavior with several types of MOV with the highly non-linear model of MOV. The equivalent non-linear model of the MOV used in this paper for simulation is determined through the curve fit function using the algorithm for optimization.
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