Permanent magnet linear synchronous machine (PMLSM) has the inherent drawbacks of end effect which would cause phase winding asymmetry, viz., electromagnetic parameter asymmetry (EMPA). In order to achieve fast and precise thrust response, traditional deadbeat direct thrust control (DB-DTC) is suitable for PMLSM, however it cannot be directly applied to PMLSM since it is constructed based on symmetrical machine mathematical model. Moreover, if EMPA is considered in traditional DB-DTC strategy, it is hard to calculate the required change of load angle since the primary flux linkage should be kept constant, especially when the salient-pole effect exists. Based on this, this paper proposed a simple modified DB-DTC strategy for a salient-pole PMLSM considering EMPA. Firstly, the mathematical model with and without considering asymmetrical inductance are derived. Then the influence of EMPA on traditional deadbeat direct thrust control (DB-DTC) is fully investigated. In order to compensate the effect of EMPA, this paper proposes a simple modified DB-DTC by compensating the error in both prediction and deadbeat control processes. Finally, the prototype experiments are carried out to validate the proposed control strategy. The results show that the phase current unbalance that caused by EMPA is largely suppressed controlled with the proposed control strategy. Moreover, both good steady and transient performances can be obtained compared with traditional DB-DTC strategy. The effectiveness of the proposed control strategy is validated.

Permanent magnet linear synchronous machines (PMLSMs) have the characteristic of parameter asymmetry due to the longitudinal end effect, which introduces nonlinear, coupling, and time-varying components to the machine model and leads to additional disturbances in machine control. To obtain high precision control of PMLSM, full electrical parameters including asymmetry parameters are estimated in this article. By the erected universal model of PMLSM, it is found that the parameter asymmetry makes not only the number of estimated parameters increase but also these parameters coupled with each other. To solve the problems of rank-deficient and nonlinearity by adopting a conventional method, a novel online full electrical parameter estimation method based on high-frequency (HF) injection is proposed, which is carried out in two steps. First, the inductance and asymmetry parameters are estimated by a designed dual second-order generalized integrator based on the derived HF response of PMLSM. Second, with the obtained parameters, the resistance and flux linkage are estimated by the recursive least squares algorithm. The method's effectiveness is verified by measured parameters, and the accuracy is also compared with that of the conventional method in the prototype test platform.

The electromagnetic suspension high-speed maglev train system uses long-stator linear synchronous motors (LLSMs) as levitation and traction mechanisms. In this paper, the modeling and simulation of the traction power supply system for the maglev train are performed. The simulation models include transformers, converters, variable-length cables and LLSMs of both two sides and two ends; meanwhile, the corresponding control and segmented power supply strategies, including the two-step method and three-step method, are implemented. Based on the system model, the operational performance of the high-speed maglev power supply control system is verified, and the fault performances under open circuit and short circuit are also analyzed. The whole simulation modeling and results have important reference significance for the research of high-speed maglev technology.

The longitudinal end effect of permanent magnet linear synchronous machines induces parameter asymmetry, imparting time-varying, and nonlinear characteristics to the machine model. In parameter estimation, parameter asymmetry introduces additional estimated parameters and results in nonlinearity and coupling among the parameters. To enhance the modeling precision and estimation performance, this article proposes a full electrical parameter estimation method considering asymmetry. First, the universal asymmetric equations are formulated for modeling parameter asymmetry. After these equations are subjected to reparameterization, the linear regression formulations with model order reduction are yielded. Second, the dynamic regressor extension and mixing method is employed to achieve full parameter estimation. The quasi-steady state caused by the end effect ensures that the estimation equations incorporate sufficient excitation, thereby meeting the stability conditions without the necessity of external excitation. Finally, the comparative, disturbance, and control application experiments are carried out, which validate the effectiveness and merits of the estimation method.

In permanent magnet linear synchronous machines, the longitudinal end effect gives rise to the manifestation of asymmetric and time-varying characteristics. When employing the model-based deadbeat predictive current control (DPCC), these characteristics can lead to additional disturbances and more intricate stability analysis. To enhance control performance, this article proposes a robust DPCC tailored for time-varying asymmetric machine model. Initially, an analysis is conducted on the disturbances, focusing on those induced by parameter mismatches and their associated frequency characteristics. In order to observe and compensate for various disturbances in time-varying model, the uncertainty and disturbance estimator (UDE) is employed to design one-step prediction and deadbeat control law. Building upon this, the parameter mismatch observer is developed to suppress high-frequency tracking errors while addressing the bandwidth limitations of the UDE. The proposed method not only facilitates a rigorous and concise stability proof for time-varying asymmetric system, but also mitigates disturbances across the entire frequency spectrum. The experimental results validate the effectiveness and superiority of the proposed method.