The increasingly serious environmental pollution and the shortage of social energy have promoted the rapid development of fuel cell vehicles. The major factor which limits the commercialization of fuel cell vehicles is durability. Accurately estimating the state and parameters of a fuel cell is critical to extending the life of the fuel cell. To address this challenge, we extended a proton exchange membrane fuel cell (PEMFC) lumped parameter model and incorporated new algorithms that are essential to estimate the health of the fuel cell in a range-extended fuel cell car. The unscented Kalman filter (UKF) algorithm has been used to estimate the ohmic internal resistance of the fuel cell in real time. By using the unscented transformation (UT) method, the linearization of the nonlinear state equation is avoided, and the filtering accuracy is improved without increasing the complexity of the system. By comparing simulation and experimental results, the feasibility and accuracy of the algorithm in this paper are further verified. This method has high estimation accuracy and is suitable for an embedded system. The research of this method is an important basis for improving the control strategy of fuel cell vehicles. Reasonable use of fuel cells can extend battery life, and this method is of great significance to the commercialization of fuel cell vehicles.

Energy management control strategy is one of the key technologies in the development of extended-range fuel cell vehicles. During the use of vehicles, fuel cell performance will decline, which limits the power output of the stack and the life of the stack. In order to control the power output of the fuel cell more reasonably, in this paper, the lumped parameter model of fuel cell is built based on Matlab/Simulink, and the vehicle model is built by AVL/Cruise simulation software. Combined with the fuel cell health state (SOH: State of Health) estimation method, the vehicle demand power and the state of charge (SOC: State of Charge) value of the power battery are used as input, and an energy management control strategy architecture based on the performance degradation of the fuel cell is designed. The simulation results show that the designed energy management can improve dynamic performance, and avoid frequent start and stop of the fuel cell, prolong the service life of the fuel cell, and further improve the economy of the vehicle.