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The Proton Exchange Membrane Fuel Cell (PEMFC) is the most widely used engine in fuel cell vehicles. For PEMFC, whether the supply of oxygen for cathode is adequate or not is a critical factor for its net output power and service life, and the proper control of air supply mass flow and pressure can effectively improve its system performance and efficiency. At present, fuel cells need to reduce the mass and volume and increase the power density. Therefore, it is necessary to increase the air supply pressure for PEMFC. But at the same time, many auxiliary devices are appended to the system to provide high-pressure air, such as air compressor, intercooler, and back pressure valve, which make the control of the entire air supply system very complicated. So an excellent control algorithm is needed.

The efficiency and durability of fuel cells are affected by internal water content. Therefore, the active control of humidity is of great significance for vehicle fuel cells, especially for self-humidifying fuel cell systems. To realize fuel cell internal humidity active control, it is necessary to collect the humidity information of stack in real time, so as to carry out feedback control. However, humidity sensor has the characteristics of high cost and low durability, so it is more practical to get the feedback value of humidity by using state estimation method for high-power commercial fuel cell system such as vehicle fuel cell. However, humidity estimation is often affected by other physical or chemical dynamic processes, such as oxygen transportation and response process of electrical appliances. In order to weaken the influence of other physical or chemical dynamic processes on humidity estimation, this paper proposes an adaptive sliding mode Kalman observer (ASMK) algorithm.