In order to analyze the influence of degree of hybridization and the number of electric motors on the climb performance of small hybrid-electric aircraft and the selection of different performance parameters in the climb stage， according to the aerodynamic model of the hybrid-electric aircraft and the system model of tandem structure， the optimization variables of the degree of hybridization， the climb speed， the angle of climb， the number of electric motors and the take-off mass are taken as the optimization variables， and the amount of fuel for the climb and the extra payload are taken as the objective functions， to establish the hybrid-electric aircraft climb performance optimization model. Multi-objective particle swarm algorithm and non-dominated sorting genetic algorithm are respectively used to optimize the solution and comparative analysis of a certain type of hybrid-electric aircraft， and the optimization results of the two algorithms are compared with the results of the foreign research， which proves the effectiveness of the optimization results. The optimization results show that the two optimization algorithms have good optimization effect on reducing the amount of climb fuel and increasing the extra payload of the aircraft. To minimize climb fuel consumption and maximize extra payload， the degree of hybridization is 0.99， the climb speed is 51 m/s， the climb angle is 7 °， and the take-off mass is between 1 830 kg and 2 200 kg.