This article represents modified model reference adaptive system (MRAS) method for speed sensorless control of interior permanent magnet synchronous motor (IPMSM), which can estimate rotor speed and position information. To suppress the adverse effect of parameter variation on control performance, the stator resistance and the permanent magnet flux linkage are estimated and continuously updated in reference and adjustable model. Then, proportional-integral (PI) controller parameters of speed adaptive law obtained by MRAS are optimized by gray wolf optimization (GWO) algorithm. To get the smallest possible speed following error and reference current error, the objective function is designed with discretized rotor speed error and current error as variables. The simulation results show the better performance of rotor speed estimation is obtained with GWO algorithm.

This article presents an optimal direct torque control (DTC) strategy with variable flux for a switched reluctance motor using the improved linear active disturbance rejection control (LADRC) plus the hybrid optimization algorithm (HOA). First, the constant flux amplitude is substituted by the variable flux DTC (VF-DTC) to reduce the torque ripple. Then, the LADRC with the improved extended state observer applied in speed controller is utilized instead of the conventional PI control to improve the speed of the observer, antidisturbance ability, and robustness. Moreover, the HOA is employed to search for the optimal control parameters and acquire satisfactory dynamic performances. Finally, the optimal VF-DTC system is implemented on a 12/8 SRM. Simulation and experimental results are carried out to compare the performances of the conventional DTC, the VF-DTC with LADRC, the VF-DTC with PI using HOA, and the proposed optimal VF-DTC using HOA. The results show that the proposed control method has a faster speed response, superior antidisturbance ability, and lower torque ripples.

Due to the increasing demand for high-speed motors with high stability, bearingless motors have attracted much attention. Bearingless permanent magnet synchronous motors (BPMSMs) are a kind of motor, which uses suspension force to eliminate the motor bearings. This article proposes a five-phase BPMSM with 10 slots and 8 poles. Based on the principle of suspension force of BPMSM, an analytical expression of the suspension force is derived for the proposed BPMSM. To improve the suspension stability and torque, an optimization method consisting of a response surface model and a multiobjective optimization algorithm is employed. Not only the geometric parameters but also the winding distribution are considered in the optimization process. Finally, the effectiveness and superiority of the optimal design are verified by experiment.

The fuel economy of hybrid electric vehicles is very closely associated with the energy management strategy (EMS). In this paper, a practicality-oriented adaptive EMS for a parallel hybrid electric bus is presented, which combines the adaptive neuro-fuzzy inference system (ANFIS) and equivalent consumption minimization strategy (ECMS). Considering the regular and fixed route of the city bus, the optimal control trajectories can be attained by the dynamic programming in advance. Using the rolling optimization method, a group of optimal equivalent factors is extracted from aforementioned control trajectories and used as the training samples. Then, a trained ANFIS model that produces the optimal equivalent factor online is constructed, showcasing striking superiority in self-learning and inference. By applying the derived equivalent factor in the framework of the ECMS, an adaptive energy management controller is available to achieve desirable power distribution online. Finally, the simulation and hardware in the loop (HIL) tests are used to validate effectiveness and feasibility of the controller. The results demonstrate that, compared with other strategies, the fuel economy with the proposed strategy can be effectively improved.

Switched reluctance motors (SRMs) have attracted much attention in industry due to the advantages of low cost, robust structure, high fault tolerance and high torque density. However, several disadvantages like high torque ripples and coil temperatures hinder their industrialization for some applications requiring high dynamic performance, like electric vehicles (EVs). In this paper, a multiobjective and multiphysics design optimization method considering both thermal and electromagnetic performance is presented for a 12/10 SRM. First, the topology of the SRM is introduced and the optimal parameters are defined. Then, the electromagnetic finite element model (FEM) is introduced and the 3D transient lumped-parameter thermal model (TLPTM), considering both axial and radial heat transfer for the SRM, is proposed. Second, the objectives and constraints of the optimization are determined. To improve the optimization efficiency, the sequential subspace optimization strategy is employed to find the optimal solution of this high-dimensional design optimization problem. Finally, to validate the effectiveness of the proposed method, both simulation and experimental results are given and discussed. Compared with the initial design, the optimal solution exhibits lower temperature, higher torque, lower torque ripple and less loss.

This paper proposes a model predictive current control (MPCC) compensation method based on virtual voltage vectors for single-phase open-circuit faults of an asymmetric six-phase permanent magnet synchronous hub motor (PMHSM). The proposed strategy adopts the normal vector space to decompose the transformation matrix without reconfiguring the controller topology. By analyzing the difference between the open-circuit phase voltage and the state of health, the disturbance term of the prediction vector in the α-β and x-y subspaces is obtained. 64 voltage vectors are obtained from the switching states of the 6-phase two-level inverter, and then these 64 voltage vectors are appropriately compensated and synthesized into 24 new virtual voltage vectors. The new virtual vectors avoid the adjustment of the MPCC weighting factors and the synthesized virtual vectors can suppress current harmonics. Finally, the experimental results show the effective performance of the method before and after the fault-tolerant operation.