Aiming at the problems of punctuality, parking accuracy, energy saving and comfort in the automatic driving of urban rail trains, this paper proposes an algorithm for generating planned speed profile based on improved genetic algorithm. This improved genetic algorithm aims to achieve multi-objective optimization of on-time, accurate parking, energy saving and comfort and improve the optimization efficiency of traditional genetic algorithms. The simulation results show that the proposed algorithm can satisfy the basic constraints of safe, punctual and accurate stopping of trains. The algorithm also reduces the operation energy consumption and improves the operation comfort.
To achieve unified fault tolerance for motor faults and inverter faults in Permanent Magnet Synchronous Motor (PMSM) drive systems, a new three-level inverter fault tolerance topology for PMSM drive system faults is proposed. This topology can carry out fault-tolerant control for as many types as possible at a relatively low hardware cost. Accordingly, a fault-tolerant control algorithm is designed based on adaptive sliding mode control to adaptively control the PMSM drive system under normal conditions and various fault conditions. Simulation and experimental results demonstrate the fault tolerance capability of this fault-tolerant topology structure and the superiority of the sliding mode control algorithm.
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