Integrated Assessment of Battery Degradation and Advanced Characterizations in Renewable–Hydrogen Hybrid Architectures

Abstract

Lithium-ion batteries are widely used in electric mobility, renewable energy integration, portable electronics, and renewable–hydrogen hybrid energy systems. Despite significant advances in battery materials and design, long-term degradation remains a major challenge that affects system reliability, efficiency, and economic viability. In renewable–hydrogen hybrid architectures, battery degradation influences not only energy storage performance but also hydrogen production stability, electrolyzer operation, fuel cell utilization, and overall system efficiency. Major degradation mechanisms include solid electrolyte interphase (SEI) growth, electrolyte decomposition, lithium inventory loss, transition-metal dissolution, particle cracking, and structural phase transformations. This review provides a comprehensive assessment of degradation mechanisms affecting lithium-ion battery components and their implications for renewable–hydrogen hybrid systems. Advanced characterization techniques, including in situ and operando X-ray diffraction, electron microscopy, spectroscopy, electrochemical impedance spectroscopy, cyclic voltammetry, and differential capacity analysis, are examined for their ability to reveal chemical, structural, and morphological changes during battery operation. Particular emphasis is placed on the effects of dynamic load variations, partial state-of-charge cycling, temperature fluctuations, and intermittent renewable energy inputs that accelerate degradation in hybrid systems. The review further discusses mitigation strategies such as surface engineering, electrolyte optimization, material doping, thermal management, intelligent energy management systems, predictive maintenance, and machine learning-based prognostics. Key challenges associated with battery–hydrogen integration, including efficiency trade-offs, component ageing, hydrogen production stability, and lifecycle costs, are critically analysed. The adaptability of hybrid systems under varying operating conditions is also explored, highlighting the importance of degradation-aware control strategies, digital twins, and real-time diagnostics. Finally, future research directions are identified, including multiscale characterization, physics-informed machine learning, techno-economic optimization, and life-synergy modelling. These approaches are essential for developing reliable, adaptive, and cost-effective renewable–hydrogen hybrid energy systems capable of supporting long-term decarbonization objectives.