IoT-Integrated Gas Sensing for Battery Management Systems in Electric Vehicles: A Review on Progress, Challenges, and Future Research
DOI:
https://doi.org/10.33736/jaspe.13432.2026Keywords:
Battery management system, Gas sensor, Thermal runaway, Electric vehicle, IoT, Machine learning, Lithium-ion battery, Early warning system, Edge computing, Sensor fusionAbstract
The rapid electrification of road transport has placed battery management systems (BMS) at a critical interface between operational performance and safety. Lithium-ion batteries (LIBs) used in electric vehicles (EVs) are susceptible to catastrophic failure modes, particularly thermal runaway, accompanied by the emission of toxic and flammable gases such as carbon monoxide (CO), hydrogen fluoride (HF), hydrogen (H2), methane (CH4), and volatile organic compounds (VOCs). The early detection of these gases through integrated sensing strategies offers an important pathway for preventing fires, explosions, and loss of life. This review critically examines the convergence of Internet of Things (IoT) technologies with advanced gas-sensing modalities to build intelligent, proactive BMS architectures. We systematically reviewed the electrochemical mechanisms of gas generation in lithium-ion cells under abuse and degradation conditions, classified gas sensor technologies applicable to EV battery packs, including metal oxide semiconductors, electrochemical sensors, optical sensors, and nanomaterial-based platforms, and analyzed their integration with IoT frameworks, encompassing IoT hardware, edge computing, and machine learning algorithms. Comparative tables synthesize the sensing performance, deployment suitability, and intelligent processing pipelines of these platforms. Prominent challenges, including sensor cross-sensitivity, packaging constraints, data latency, cybersecurity, and regulatory gaps, have been identified. This review concludes by mapping emerging research directions, such as multi-gas sensor fusion, large language model-assisted diagnostics, digital twin integration, and solid-state battery-compatible sensing, providing a roadmap for fail-safe, self-aware EV battery systems.
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