Scholarlink

<p>The widespread adoption of electric vehicles has faced significant challenges, primarily due to the limited availability of charging infrastructure and the slow charging times associated with electric vehicle batteries. Furthermore, due to energy difficulties and the greenhouse gas consequences of fossil fuel-based vehicles, solar energy-powered vehicles have received considerable attention from researchers. In this context, this paper presents the design and implementation of a solar photovoltaic system that employs a maximum power point tracking technique, integrated with a lead-acid battery and a DC-DC converter, to optimize the battery charging process and reduce charging time.The boost converter with a fuzzy-based control algorithm has been used to operate solar photovoltaic systems at their maximum power point. Furthermore, an equilibrium optimization based intelligent fuzzy control algorithm has been proposed for a fast battery charging to control the power delivery between solar photovoltaic and battery. The proposed methodology’s effectiveness is applied to a 2&#xa0;KW solar system integrated with 12&#xa0;V battery and their performance compared with COOT and gray wolf optimization based metaheuristic techniques. As a result, the finding shows that the equilibrium optimization based fuzzy controller for solar battery circuit is better than gray wolf optimization and COOT-based techniques in terms of power tracking, settling time and rise time.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

EO based fuzzy optimal controller for solar MPPT and battery charging circuit for EV charging application

  • 期刊论文

  • 发表日期：

    2025年1月18日

查看全文
  • Sandeep Tripathi,
  • Ashish Shrivastava,
  • K. C. Jana

摘要

The widespread adoption of electric vehicles has faced significant challenges, primarily due to the limited availability of charging infrastructure and the slow charging times associated with electric vehicle batteries. Furthermore, due to energy difficulties and the greenhouse gas consequences of fossil fuel-based vehicles, solar energy-powered vehicles have received considerable attention from researchers. In this context, this paper presents the design and implementation of a solar photovoltaic system that employs a maximum power point tracking technique, integrated with a lead-acid battery and a DC-DC converter, to optimize the battery charging process and reduce charging time.The boost converter with a fuzzy-based control algorithm has been used to operate solar photovoltaic systems at their maximum power point. Furthermore, an equilibrium optimization based intelligent fuzzy control algorithm has been proposed for a fast battery charging to control the power delivery between solar photovoltaic and battery. The proposed methodology’s effectiveness is applied to a 2 KW solar system integrated with 12 V battery and their performance compared with COOT and gray wolf optimization based metaheuristic techniques. As a result, the finding shows that the equilibrium optimization based fuzzy controller for solar battery circuit is better than gray wolf optimization and COOT-based techniques in terms of power tracking, settling time and rise time.