ABSTRACT
Heat transfer is necessary for various emerging technologies, including information technology, biotechnology, nanotechnology, and low-carbon energy use. AI applications in heat transfer research are gaining traction and are being used to speed up basic research and practical progress in heat and mass transfer. Combustion is used in most energy generation systems, such as power generators and combustion engines, to convert the chemical energy stored in fossil fuels into work, turning into more usable and transportable forms, such as electricity. Combustion knowledge and technologies have been consistently updated to address the growing issues of fossil fuel depletion, energy security, environmental pollution, and climate change. Artificial intelligence (AI) cutting-edge technologies have emerged 28as valuable tools in various fields. Artificial intelligence (AI) applications in combustion research are gaining traction and are being used to speed up product development toward more environmentally friendly and efficient combustion systems. Solar, wind, hydro, biomass, geothermal, and other renewable energy sources are critical for creating a clean and sustainable future. These renewables are often intermittent, unpredictable, and poorly distributed physically and temporally; so directly incorporating them would significantly disrupt power networks. As a result, developing efficient and reliable energy storage technology is critical to effectively adopting renewable energy. Despite tremendous advancements in advanced energy storage technology (AEST) in the last decade, particularly for large-scale energy storage, intelligent and efficient energy storage systems are in demand more than ever. Vast amounts of data about the performance and life of energy storage devices are becoming available, thanks to the advent of the Internet of Things (IoT). Big data and advances in artificial intelligence (AI) present significant potential for optimizing and increasing AEST performance and durability and inventing game-changing solutions. The primary goal of this chapter is to provide a platform for presenting the most recent breakthroughs in the use of artificial intelligence in energy storage systems, particularly large-scale energy storage systems.
