Smart IoT Frameworks for Electric Vehicle Battery Health Monitoring
Year: 2026
Type: book-chapter
Abstract: As electric vehicles (EVs) grow in popularity and become an important component of sustainable transport, there is an increased demand for intelligent battery management and monitoring systems which guarantee not only their safety and reliability, but also long service life. Traditional Battery monitoring and control systems (BMS) perform localized monitoring and usually do not have a capability of real-time data collection and analysis. Internet of Things (IoT) enables uninterrupted data collection related to the battery such as voltage, current, temperature, available battery capacity (SOC), overall battery condition (SOH), and estimated service life (RUL). Intelligent IoT systems incorporate such components as sensors, wireless communication, edge computing, cloud platforms, artificial intelligence (AI), and digital twins to develop intelligent battery health management systems. These systems can perform such tasks as failure detection, battery aging, optimization of charging and operation. This chapter will focus on the architecture, communication technologies, AI-based analytics, cloud integration, cyber security issues and practical implementations of IoT battery health monitoring systems in electric vehicles. Such emerging technologies as edge AI, federated learning, blockchain, and digital twins will also be discussed.
Institutions: AMET University, National Institute of Ocean Technology
Language: English
Subfield: Automotive Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7204086283