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.
피인용 0
초록·키워드
In recent decades, the global energy crisis and environmental contamination have escalated due to rising electricity consumption and the proliferation of fuel-dependent vehicles, which are major contributors to greenhouse gas emissions. Electric Vehicles (EVs) have emerged as a key solution to mitigate these challenges, offering a pathway to reduce both emissions and reliance on fossil fuels. This review examines the evolution and current state of electric motor control technologies, focusing on three primary techniques: Field-Oriented Control (FOC), Direct Torque Control (DTC), and Model Predictive Control (MPC). While FOC remains widely adopted due to its proven efficiency and smooth operation, recent advancements in MPC suggest potential for superior dynamic performance, albeit with increased computational complexity and time requirements. DTC, known for its simple design and rapid response, faces limitations such as torque ripple and variable switching frequency. Our analysis highlights that, although MPC offers promising advantages in control flexibility and accuracy, FOC continues to be the most practical choice for electric vehicle motor control systems due to its balance of performance, reliability, and ease of implementation. This review underscores the need for further research to optimize MPC and DTC techniques to fully realize their potential in EV applications, particularly in enhancing energy efficiency and extending component lifespan.
본문·목차
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