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In order to solve the problem that the tractor driving index constraints cannot be obtained at the beginning of the design for the fuel cell tractor due to the unknown using mass, a parameter adaptive optimization method was proposed with the dual-axle drive fuel cell tractor as the research object. A mass closure algorithm was adopted to solve the problem that the power system was unable to accurately obtain the driving index constraints due to the unknown using mass. With the goal of improving the operating efficiency, a traversal search algorithm was used to optimize the front/rear reduction gear ratios. The mass closure algorithm, the traversal search algorithm and the genetic algorithm were integrated to form a parameter adaptive optimization method of a two-axle-driven fuel cell tractor with unknown using mass. The method can simultaneously optimize the using mass, dynamic parameters and front/rear reduction gear ratios of the fuel cell tractor. To verify the reasonableness of the method, a rule design method was developed as the comparison method, and the two methods were simulated under plowing conditions. The results showed that the using mass and equivalent hydrogen consumption of the dual-axle drive fuel cell tractor obtained by the parameter adaptive method were reduced by 14.44% and 8.41%, respectively, compared with the rule design method. The operating efficiency of the power source motor was increased by 3.28 percentage points and 5.29 percentage points, and the output power of the energy source fuel cell and power battery was reduced by 6.81% and 38.59%, respectively. The method provided a theoretical basis for the parameters design of fuel cell tractors with unknown using mass.