Humidity estimation of vehicle proton exchange membrane fuel cell under variable operating temperature based on adaptive sliding mode observation

Active humidity control of vehicle fuel cell requires real-time and accurate estimation of actual humidity. However, the vehicle operation conditions change rapidly, which makes the accuracy of transient estimation become the difficulty of estimation algorithm with operation condition deviation. In order to solve this problem, an adaptive sliding mode estimation algorithm based on dimensionless modelling method is designed. The experiment on a real 80 kW commercial fuel cell system proves that compared with the classical sliding mode observation algorithm, the adaptive scheme can reduce the absolute estimation error of humidity by about 5% on average, and the absolute estimation error can be reduced by 17% in some transients.