Plasma-enabled energy conversion is an important way to achieve the preparation of chemicals from renewable energy. It is also one of the most important ways to reduce fossil fuel consumption and achieve net-zero carbon emissions. However

plasma-enabled energy conversion currently faces the problems of difficulty in optimizing controllable parameters

complex parameter acquisition and unclear mechanisms. It is necessary to establish new methods to achieve a comprehensive analysis of plasma energy conversion from the three aspects of experiment

diagnosis and simulation. With the rapid development of artificial intelligence in recent years

the research on artificial neural network in plasma energy conversion has gradually received attention. Artificial intelligence methods assist in the optimization of operating parameters

plasma parameter acquisition and mechanism analysis in plasma-enabled energy conversion from the two aspects of being data-driven and physical-driven. This paper introduces the application of artificial intelligence methods in plasma energy conversion from following four aspects: conversion characteristic prediction and operating parameter optimization

diagnosis and plasma parameter acquisition

simulation and mechanism analysis

and new paradigm. Current research shows great potentials of artificial intelligence in the modeling of multi-scale complex systems of plasma

which is helpful to solve complex dynamic processes with highly nonlinear and multi-physical field interactions. The research provides a new method for the development of plasma energy conversion technology in a smarter

more efficient and more sustainable direction.