To obtain characteristic parameters and fault influence law required for fault diagnosis of the train air supply system, and address the problems that some fault modes cannot be injected or the injection is destructive, the structure composition, working principle and fault modes are explained. The equivalent fault model design method and the equivalent fault injection process are proposed. Based on the equivalent fault injection test, the influence laws of five typical fault modes at different failure levels were studied and the causes of the faults are analyzed. The research results show that the equivalent fault injection test could reproduce the three typical fault phenomena of insufficient air supply, high oil temperature and compressor not loading without causing damage to the air supply system. The influence laws and characteristic parameters of different fault modes are different. When the air intake filter is severely blocked, the total air pressure is less than 740 kPa, resulting in insufficient air supply. When the temperature control valve is severely stuck, the maximum fuel injection temperature and the compressor head exhaust temperature are increased by about 20℃ and 17℃ compared with the normal values, and the maximum cooling oil flow is decreased by about 14 L/ min. The cooling effect is reduced due to the accumulation of dust in the cooler, and the maximum drop is about 3℃ when the ambient temperature values are 20℃ , 35℃ , and 50℃ , respectively. When the oil is seriously leaking, the fuel injection flow is about 19 L/ min higher than the normal value, and the compressor head exhaust temperature could reach up to 105℃ , resulting in high oil temperature. When the opening degree of the unloading solenoid valve is from 25% ~ 100% , the total air pressure is only 690 kPa, resulting in insufficient air supply. When the opening degree is 0, the air compressor could not restart after the first normal operation and shutdown, causing the compressor not loading. The research results provide a reference for the design of fault diagnosis algorithm based on multi - sensor data such as temperature and pressure and sensor layout of intelligent air supply systems.