Artificial intelligence driven hydrogen and battery technologies – A review

Abstract

The world has recognized the importance of renewable energy and is moving towards a rapid transition to renewable energy and energy efficiency. Advances in electrolysis and cost reductions, as well as the availability of renewable energy sources, have paved the way for the creation of green hydrogen, a completely carbon-free fuel, making it a real contender to revolutionize the energy market. The recent incorporation of artificial intelligence into the energy sector has provided a major breakthrough for the industry. Artificial intelligence algorithms and models such as artificial neural networks, machine learning, support vector regression, and fuzzy logic models can greatly contribute to improving hydrogen energy production, storage, and transportation. They play an important role in predicting various parameters, safety protocols and management of hydrogen production. Furthermore, advances in artificial intelligence are expected to bring huge state-of-the-art technologies and tools for hydrogen and battery technology that could help solve the current energy-oriented crises and problems. This review provides insight into the feasibility of state-of-the-art artificial intelligence for hydrogen and battery technology. The primary focus is to demonstrate the contribution of various AI techniques, its algorithms and models in hydrogen energy industry, as well as smart battery manufacturing, and optimization. Meanwhile, AI models integrated into battery technology play a key role in material discovery, battery design, improved battery manufacturing, diagnostic tools, and optimal battery management systems for smart batteries. With improved performance and longer life, these smart batteries will be integrated into modern robotics, electric vehicles, aerospace and other fields.