인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
This article presents an innovative asymmetric multilevel inverter (MLI) topology that outperforms conventional counterparts. The introduced topology presents a breakthrough in implementing power electronics control by maximizing specific levels while minimizing switching components. A cutting-edge control scheme for optimal operation of the cascaded half-bridge MLI is presented. The ant lion optimization (ALO) algorithm was implemented to optimize the switching control to reduce the total harmonic distortion (THD) and improve power quality. For verification, the performance and effectiveness of the ALO technique are assessed by comparing its results to those obtained using the simplified sinusoidal pulse width modulation (SSPWM) technique, genetic algorithm (GA), and particle swarm optimization (PSO) in existing literature. Simulation results verified the efficacy of ALO in finding the optimal parameters. The suggested method showcases a remarkable reduction in the THD compared to SSPWM. The quality of the resulting waveform was enhanced, and both filter size and cost were significantly reduced. To meet stringent IEEE standards, an LC filter has been designed with minimal size and proper requirements. Experimental results validation of the suggested scheme, using a dSPACE R&D controller board unequivocally, confirmed its robustness and effectiveness. This groundbreaking study not only introduces a superior asymmetric MLI topology but also validates its exceptional performance through comprehensive analysis and experimentation. The experimental waveforms showed good matching with the simulation outcomes. The findings hold immense promise for advancing the field of power system control and revolutionizing the designing and implementation of efficient and cost-effective inverter systems.
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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