Cloud-Based Monitoring of Lithium-Ion Battery Management Systems for Health Estimation in Manufacturing Industries

<div class="section abstract"><div class="htmlview paragraph">The increasing reliance on lithium-ion batteries in manufacturing necessitates advanced monitoring techniques to ensure their longevity and reliability. Cloud technology offers a solution by enabling real-time data collection, analysis, and accessibility, facilitating thorough monitoring and predictive maintenance. Digital twin technology, creating a virtual replica of the physical battery system, provides a platform for simulating real-world conditions and predicting potential issues before they arise. By integrating sensor data and historical usage patterns, the digital twin model can accurately predict battery degradation, aiding in timely maintenance strategies. This proactive approach enhances battery operational efficiency and extends lifespan, leading to cost savings and improved safety. The paper explores using cloud-based monitoring systems to enhance the health estimation and management of lithium-ion batteries. A comprehensive feasibility study on adopting battery digital twin technology for electric two-wheeler and three-wheeler manufacturers examines creating a digital twin model for batteries and validating corresponding tests. Furthermore, the research discusses the technical challenges and solutions associated with implementing digital twin technology in manufacturing. Key metrics such as state of charge (SoC) and state of health (SoH) are analyzed to showcase the effectiveness of the digital twin model in real-world applications.</div></div>