This paper proposes a new finite control set model predictive control (FCS-MPC) strategy that simultaneously evaluates two targeting control objectives (TCOs) including speed and currents in a single cost function, achieving high-performance single-closed-loop control structure. Besides, aiming at the calculation delay problem of the MPC controllers, a novel calculation delay compensation method by predicting the current variation within the delay time is proposed. In this paper, an improved machine model that is specially designed for the multi-objective FCS-MPC operation is illustrated at first. Then, a new cost function which can evaluate the tracking performance of speed and d-axis current and steady-state performance of q-axis current is developed. Compared to the conventional FCS-MPC approaches, extra speed controllers are not needed so that the proposed control topology becomes simpler. Then, in order to tune the weighting factors for the speed and currents in the cost function, an efficient handling strategy containing two implementation procedures, state variable normalization (SVN) and balance of state sensitivity to voltage alteration, is developed. Finally, a brand-new computation delay estimation and compensation technique based on dual sampling within a switching period is proposed to reduce the current and torque ripples during control process. Comparative simulation and experiments are conducted on a three-phase 1.5kW PMSM drive system.

This letter proposes a novel sliding mode (SM) disturbance observer-based technique to diagnose demagnetization fault of interior permanent magnet (IPM) motors with stator parameter mismatch impacts eliminated. First, the IPM motor model incorporating the disturbances caused by the PM demagnetization and stator parameter mismatch is established. Then, an SM disturbance observer is constructed to identify the overall disturbance caused by all parameters, with its stability discussed by using the Lyapunov function. Third, a current-analysis-based method is developed to extract the disturbance only caused by flux linkage mismatch from the overall disturbance. Third, the extracted disturbance is adopted to calculate the real flux linkage, achieving demagnetization fault judgment and demagnetization degree calculation. Finally, experiment is conducted on two IPM motors to validate the proposed flux linkage estimation and fault diagnosis methods.

A position sensorless control of interior permanent synchronous motor (IPMSM) equipped with LC sinusoidal filter based on the full-order sliding mode observer (FOSMO) and feedforward quadrature phase-locked loop (FQPLL) is proposed in this article. The FOSMO is designed to estimate stator currents, stator voltages, and extended back electromotive forces of IPMSM. To enhance the rapidity of the convergence and accuracy of the estimation of the FOSMO, an adaptive gain matrix is designed by adopting equivalent control theory and Lyapunov stability theory. In order to suppress the dc deviation in the position estimation error under acceleration or deceleration operations, a robust and anti-interference feedforward loop without differentiator and motor parameters is added to the conventional quadrature phase-locked loop. The parameter design method of the proposed FQPLL is studied by analysis of the frequency characteristics. The experimental results verify the effectiveness of the proposed strategy.

Finite-position-set phase-locked loop (FPS-PLL) is a research hotspot in the sensorless control of permanent magnet synchronous motor (PMSM) due to its excellent dynamic response and no parameters tuning, but it takes the high computational burden and may suffer from a rotor position error of 180°. To solve the above problems, a double-cost-function FPS-PLL (DCF-FPS-PLL) is proposed in this article, where two different cost functions are defined to decide the iteration direction and guarantee the convergence of the Newton iteration method. The estimation accuracy of the rotor position is theoretically 4.73e-6 rad for the DCF-FPS-PLL without considering the error caused by the observer while only three iterations are needed, which reduces the large amount of computation without sacrificing the accuracy. The experimental results verify the advantages of the DCF-FPS-PLL.

There is little review work concerning the safety of electric vehicles (EVs) in the crash conditions, leading to the fact that many people, even including those who have been studying EVs for many years, are not familiar with the relevant injury hazards and the corresponding prevention measures. To solve the problem, this article reviews several safety-related aspects of EVs in crash conditions. First, the injuries, including the reasons and forms behind them, that the occupants are going to suffer are introduced. Meanwhile, both the international and national regulations and their provisions concerning injury hazards prevention are discussed. Finally, the up-to-date technologies that are adopted to prevent the different injuries are illustrated. Through this article, the scholars in academia and researchers in the industry can gain a sufficient grasp of current/future development about the EV safety issues in the crash conditions, and meanwhile, the end-users or potential end-users (EUs/PEUs) can gain easy-to-understand knowledge in this area.

Identifying the air-gap flux is a prerequisite for realizing the decoupling control between the air-gap flux and torque in an electrically excited synchronous motor (EESM) vector control system. For the nonlinear problem of EESM, the frequency response function method is introduced to analyze the air-gap flux voltage and current models' sensitivity to the motor parameters in this article. A dynamic air-gap current model for EESM based on the equivalent reaction inductance is proposed to solve the parameter dynamic-variant problem caused by the nonlinear magnetic distribution of the EESM. Meanwhile, the comparative analysis of effectiveness caused by linear and nonlinear flux identification errors in the hybrid air-gap flux model of vector control system is carried out. The effectiveness of the nonlinear dynamic model has been verified by simulation and experimental results, which shows its excellent control performance.