The invention, which belongs to the battery state estimation field, relates to a particle-swarm-optimization-based battery state estimation method. A particle swarm is initialized and a state estimator is initialized; for each particle in the particle swarm, state posteriori estimation is obtained and the precision levels of the obtained state posteriori estimation are compared to obtain state estimation, state priori estimation of a next sampling point is obtained by the state posteriori estimation; and then according to the precision of the state posteriori estimation, evolution of the particle swarm is carried out. When a battery state estimation is carried out, battery parameter estimation information is obtained based on particle optimization; and when a battery model has a plurality of local optimal points, compared with the local optimization method, the particle-swarm-optimization-based battery state estimation method enables optimal estimation of the battery model to be obtained easily, so that battery state estimation obtained by state filtering becomes accurate.