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<p>As electric vehicles and renewable energy systems become more widespread, there is an increasing need for DC–DC converters that can provide higher voltage gain, better efficiency, and improved reliability. This paper presents a comprehensive review of the latest advancements in enhanced gain DC–DC converter technologies. It covers a range of topologies including interleaved, coupled-inductor, switched-capacitor, multiport, and resonant converters, each suited for different application requirements. The review also explores the role of emerging semiconductor materials such as silicon carbide (SiC) and gallium nitride (GaN), as well as the integration of modern control strategies like model predictive control (MPC), fuzzy logic, and sliding mode control. Artificial intelligence (AI) and digital twin technologies are also discussed as tools for improving real-time performance and predictive maintenance. Through comparative studies and application-specific recommendations, this paper identifies key research gaps and future directions that could enhance scalability, cost-effectiveness, and thermal performance in power conversion systems for EVs and renewable energy.</p>

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State-of-the-art DC–DC converters for electric mobility and renewable integration: trends, challenges, and future directions

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年12月26日

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  • B. Nagi Reddy,
  • B. Jyothi,
  • Gundala Srinivasa Rao,
  • N. Janaki,
  • P. Swathi,
  • Sareddy Venkata Rami Reddy

摘要

As electric vehicles and renewable energy systems become more widespread, there is an increasing need for DC–DC converters that can provide higher voltage gain, better efficiency, and improved reliability. This paper presents a comprehensive review of the latest advancements in enhanced gain DC–DC converter technologies. It covers a range of topologies including interleaved, coupled-inductor, switched-capacitor, multiport, and resonant converters, each suited for different application requirements. The review also explores the role of emerging semiconductor materials such as silicon carbide (SiC) and gallium nitride (GaN), as well as the integration of modern control strategies like model predictive control (MPC), fuzzy logic, and sliding mode control. Artificial intelligence (AI) and digital twin technologies are also discussed as tools for improving real-time performance and predictive maintenance. Through comparative studies and application-specific recommendations, this paper identifies key research gaps and future directions that could enhance scalability, cost-effectiveness, and thermal performance in power conversion systems for EVs and renewable energy.