基于新型优化神经网络的光伏电动汽车系统鲁棒安全云监测

IF 6 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Ain Shams Engineering Journal Pub Date : 2025-05-07 DOI:10.1016/j.asej.2025.103443

Saranya R.B. , K. Ramesh

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引用次数: 0

摘要

这项研究通过基于光伏（PV）的电动汽车（ev）解决了交通运输的可持续电气化问题，并得到了安全的基于云的监控系统的支持。实时电动汽车诊断、电池分析和光伏系统数据通过物联网设备收集，并通过改进的Diffie-Hellman （IDH）和Twofish加密（TE）技术安全地传输到云端。一种新的基于小龙虾优化算法（COA）的深度前馈神经网络（DFFNN）识别出最优路由路径，最大限度地降低成本、延迟和能耗。为了提高PV性能，实现了高增益二次升压变换器（HGQBC），以最小的输入纹波实现96.29%的效率，而改进的增量电导（IC）最大功率点跟踪（MPPT）以0.1 s的响应时间确保99.61%的跟踪效率。MATLAB仿真和实验室原型验证了系统的有效性，展示了优越的分组传输率，低能耗和快速响应时间，使该方法成为基于pv的EV优化的强大解决方案。

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Robust and secure cloud-based monitoring of PV based electric vehicle system using novel optimized neural network

This research addresses the sustainable electrification of transportation through Photovoltaic (PV)-based Electric Vehicles (EVs), supported by a secure, cloud-based monitoring system. Real-time EV diagnostics, battery analytics, and PV system data are collected using IoT devices and transmitted securely via an Improved Diffie-Hellman (IDH) and Twofish Encryption (TE) technique to the cloud. A novel Crayfish Optimization Algorithm (COA)-based Deep Feed Forward Neural Network (DFFNN) identifies optimal routing paths, minimizing cost, delay, and energy consumption. For enhancing PV performance, a High Gain Quadratic Boost Converter (HGQBC) is implemented achieving 96.29 % efficiency with minimal input ripple, while an Improved Incremental Conductance (IC) Maximum Power Point Tracking (MPPT) ensures 99.61 % tracking efficiency with a 0.1 s response time. MATLAB simulations and laboratory prototypes validate the system’s efficacy, showcasing superior packet delivery ratios, low energy use, and fast response times, making this approach a robust solution for PV-based EV optimization.

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来源期刊

Ain Shams Engineering Journal Engineering-General Engineering

CiteScore

10.80

自引率

13.30%

发文量

441

审稿时长

49 weeks

期刊介绍： in Shams Engineering Journal is an international journal devoted to publication of peer reviewed original high-quality research papers and review papers in both traditional topics and those of emerging science and technology. Areas of both theoretical and fundamental interest as well as those concerning industrial applications, emerging instrumental techniques and those which have some practical application to an aspect of human endeavor, such as the preservation of the environment, health, waste disposal are welcome. The overall focus is on original and rigorous scientific research results which have generic significance. Ain Shams Engineering Journal focuses upon aspects of mechanical engineering, electrical engineering, civil engineering, chemical engineering, petroleum engineering, environmental engineering, architectural and urban planning engineering. Papers in which knowledge from other disciplines is integrated with engineering are especially welcome like nanotechnology, material sciences, and computational methods as well as applied basic sciences: engineering mathematics, physics and chemistry.