The internal combustion engine-based transportation system is causing severe problems such as rising levels of pollution, rising petroleum prices, and the depletion of natural resources. To divide power between the engine and the battery in an effective manner, a sophisticated energy management system is required to be put into place. A power split strategy that is efficient may result in higher fuel economy and performance of Electric Vehicles (EVs). In this paper, we propose the reinforcement learning method using Deep Q learning (DQL), which is a novel Improved Swarm optimized Deep Reinforcement Learning Algorithm (IS-DRLA) designed for energy management control. To perform an update on the weights of the neural network, this method computes the use of a modified version of the swarm optimization technique. After that, the suggested IS-DRLA system goes through training and verification using high-precision realistic driving conditions, after which it is contrasted with the standard approach. The performance indices such as State of Charge (SOC) and fuel consumption and loss function are analyzed for the efficiency of the proposed method (IS-DRLA). According to the findings, the newly proposed IS-DRLA is capable of achieving a higher training pace with a lower overall fuel consumption than the conventional policy, and its fuel economy comes very close to matching that of the worldwide optimal. In addition to this, the adaptability of the suggested strategy is demonstrated by utilizing a different driving schedule.
Due to the one-of-a-kind and one-of-a-kind qualities that it possesses, graphene is an appealing soft substance that may be utilized in a variety of applications. This review focuses on two significant issues that need to be resolved to make use of the notable properties of nanostructures based on graphene: The creation of graphenebased nanostructures with various well-defined structural variations is the initial of these problems, and effectively utilizing graphene-based nanoparticles as functional nanostructures in important idea or technologies is the second of these problems. Before the distinctive qualities of graphene-based nanoparticles can be completely exploited, each of these challenges must be resolved. In this critical analysis from the chemical and nanomaterials viewpoints, we provide a quick summary of recent significant developments in the creation of graphene-based nanomaterials. In this study, we also cover the synthesis, characterization, and applications of graphene nanomaterials in the disciplines of both energy and environmental pollution rehabilitation, including solar cells, lithium-ion batteries, supercapacitors, and the adsorption and degradation of pollutants from huge quantities of the aqueous medium. There is also a discussion of the most significant challenges and opportunities in the research materials.
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