Adaptive fault-tolerant control of five-phase permanent magnet synchronous motor current using chaotic-particle swarm optimization

Both torque ripple and current harmonics are enlarged due to single-phase open-circuit fault of five-phase permanent magnet synchronous motor (FPMSM). Based on chaotic-particle swarm, an adaptive optimization fault tolerant control algorithm is proposed for the FPMSM current. First, Park and Clarke matrices are modified in coordinate transformation process. A reduced-order decoupling matrix is obtained under the open-circuit fault of FPMSM stator winding. Second, the fault-tolerant current is generated with the principle of constant magnetomotive force. Third, the current is adaptively optimized using chaotic-particle swarm algorithm. Hence, motor torque and motor current keep uniform steady state and dynamic performance with them in regular operation. Finally, numerical simulations are carried out to verify the effectiveness of the developed method.

Automated summary

This study proposes an adaptive optimization fault tolerant control algorithm for the current control of a five-phase permanent magnet synchronous motor (FPMSM) based on chaotic-particle swarm. The algorithm modifies the matrices and optimizes the current to ensure the motor's performance under fault conditions.