Abstract: To guarantee the safe and high-efficiency running of Lithium-ion battery, it’s vitally important to make battery state estimation timelier and more accurate. The key parameters inside the battery perceived by using advanced sensing technology in situ provide abundant data and theoretical support for battery state estimation, which has great significance of battery state estimation. Taking the general battery state estimation methods: character-based methods, model-based methods and data-driven machine learning methods as references and comparisons, the principles, applications, advantages and disadvantages of advanced sensing technology including optical fiber sensing technology, electrochemical impedance spectroscopy sensing technology, mechanical strain sensing technology and acoustic sensing technology are analyzed. Finally, the future smart battery and smart battery management system is built.