Abstract: To solve the problem that the parameters of the model of proton exchange membrane fuel cell（PEMFC）are difficult to determine,a novel joint optimization algorithm is proposed in this paper,integrating the Harris hawks optimizer（HHO）and firefly algorithm（FA）. The HHO-FA algorithm is employed to tackle the parameter identification problem of PEMFC. To enhance the modeling accuracy of PEMFC,HHO-FA retains global exploitation with high search efficiency and accuracy in HHO. The local exploitation is combined with the FA with the characteristics of group optimization. At the same time,the conversion factor responsible for switching between global exploration and local exploitation is optimized,and the inertia weight factor is added to optimize the algorithm structure.Sample data is obtained using Thermolib,a commercial simulation toolbox based on fuel cells. The performance of HHO-FA for PEMFC parameter identification is evaluated against particle swarm optimization（PSO）,HHO algorithm,ant colony optimization（ACO）and FA algorithm. The simulation results show that,compared with PSO,HHO,ACO and FA,HHO-FA has the highest identification accuracy and convergence efficiency,which confirms the outstanding performance of the proposed HHO-FA algorithm in PEMFC parameter identification.