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

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 the implementation of timely maintenance strategies. This proactive approach not only enhances battery operational efficiency but also extends their lifespan, leading to cost savings and improved safety. The paper explores the use of 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 is conducted, examining the creation of 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 the manufacturing process. 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.