摩擦材料的性能是影响机械设备工作可靠性的重要因素，研究摩擦材料对改善制动系统的制动效能具有重要意义。从制动摩擦材料的分类与制备、摩擦磨损性能与机理以及性能预测三个方面，对制动摩擦材料的研究与发展现状进行了调研。首先，介绍了制动摩擦材料包括金属基、半金属基、非金属基三种类型，阐述了各种摩擦材料常用的制备方法及应用领域；其次，分析了制动压力、制动速度等工况对摩擦磨损性能的影响规律及其作用原理，简述了常见的磨损形式，并结合无石棉闸瓦的 SEM 微观形貌，重点探讨了粘着磨损、磨粒磨损、切削磨损、疲劳磨损与热磨损各自的产生机理及其主要影响因素。此外，归纳了摩擦材料性能的预测与分析方法，并以 BP 神经网络为例介绍了人工智能技术在摩擦学性能预测中的应用。最后，指出了陶瓷摩擦材料与功能性摩擦材料是未来摩擦材料的发展方向。

Tribological properties of friction materials have significant influences on the working reliability of mechanical equipment, hence studies on friction materials are greatly beneficial to the improvement of braking efficiency of braking systems. Investigations into the research and development status of brake friction materials were carried out in three aspects: classification and preparation methods, frictional wear resistance and mechanism as well as performance prediction. At first, it was introduced that brake friction materials included metallic, semi-metallic and non-metallic friction materials based on the type of matrix material. Typical preparation methods and application fields of each friction material were presented. Secondly, the influencing laws of braking conditions such as braking pressure and velocity on frictional wear resistance and their function mechanisms were analyzed. Then common wear forms like adhesive wear, abrasive wear, cutting wear, fatigue wear and thermal wear were introduced. The formation mechanism of each wear form and correponding influencing factors were analyzed in detail according to SEM microtopography of non-asbestos brake shoes. In addition, several performance and analysis methods for predicting friction materials performance were concluded. The application of BP neural network was taken as an example to introduce application of artificial intelligence technology to tribology performance prediction. Ultimately, it was pointed out that ceramic and functional friction materials were the developmental trend of friction materials in the future.