The fast mechanical switch is the core equipment of the hybrid DC circuit breaker

which operating mechanism is mostly driven by using the electromagnetic repulsion mechanism（ERM）. Due to the motion of ERM involves multi-physics field coupling

it is difficult to optimize the design of ERM by the control variable method alone. Basis this

a multi-strategy improved particle swarm optimization algorithm is proposed and applied to the parameter optimization of the ERM. Firstly

the effect of the parameters of coil disk size

metal plate and discharge loop parameters of ERM on the fast mechanical switch are simulated and analyzed by Ansoft Maxwell

and the key optimization design parameters were determined. Then

for the defects of the basic particle swarm

combined with the reopening and opposition-based learning strategies

the multi-strategy improved particle swarm optimization algorithm was used to optimize the key parameters of ERM. Finally

the prototype was fabricated based on the optimized parameters and testing processes were carried out. The results show that the optimized switch’s breaking speed is improved while reducing the total volume and cost of the switch

which verifies the effectiveness of the optimized design. The developed fast mechanical switch will be put into use in Zhangbei ±500 k V flexible DC transmission project.