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Mr.Sidharth Sharma
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Abstract : Hybrid Electric Vehicles (HEVs) have gained significant popularity due to their reduced environmental impact and fuel efficiency. However, the complex integration of electrical and mechanical systems in HEVs presents significant cooling challenges. A robust cooling system is essential to maintain optimal performance and extend the lifespan of powertrains and battery systems. This paper explores the development of an advanced cooling system designed specifically for HEV powertrains, leveraging modern technologies such as heat exchangers, liquid cooling, and smart thermal management systems. The proposed system uses adaptive cooling mechanisms that adjust based on real-time vehicle operating conditions to maximize efficiency and reduce energy consumption. Additionally, machine learning algorithms are integrated into the cooling system for predictive maintenance, identifying potential issues before they arise. By optimizing thermal management, the system ensures higher efficiency, improved vehicle performance, and a longer life for HEV components. This paper presents an analysis of the current cooling technologies in HEVs, identifies gaps in their functionality, and proposes a novel cooling framework that addresses these limitations, making HEVs more viable for long-term sustainability and performance.
Keyword Hybrid Electric Vehicle (HEV), Powertrain, Advanced Cooling System, Thermal Management, Predictive Maintenance, Liquid Cooling, Machine Learning, Energy Efficiency, Heat Exchanger, Smart Cooling
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