In this article, a novel electric-drive-reconstructed onboard charger (EDROC) is proposed for the solar-powered electric vehicle that incorporates a six-phase machine drive. The power traction inverter and the machine are re-leveraged to implement charging operation, further minimizing the incremental mass accordingly. In particular, charging and driving operations can be simultaneously carried out via the vehicle-roof photovoltaic panels, significantly expanding EV mileage range. First, the operation scenario and the topology of the proposed EDROC are introduced. Next, the operational principle is analyzed, as well as the indispensable conditions for safe and stable operation are studied. Thereafter, control schemes are designed and elaborated in terms of the simultaneous driving and charging mode and the dc charging mode. To this end, a 2-kW laboratory prototype is conducted, and experimental results are presented to verify the steady-state and dynamic behavior of the proposed EDROC system under different operation modes.

This work presents an improved finite-control-set model predictive flux control (FCS-MPFC) for asymmetrical six-phase permanent magnet synchronous machine (ASPMSM) with a novel duty-cycle regulation strategy. Firstly, virtual vector concept is adopted to suppress harmonic currents without additional cost function and the corresponding weighting factor. Then, 12 virtual vectors with higher voltage utilization are developed. Meanwhile, for the sake of strengthening steady-state performance, a novel duty-cycle regulation strategy incorporating the well-known Lagrange multiplier method is proposed. In this strategy, the reconfigurable set of voltage vectors (SVV), which consists of an active and a null virtual vector, can be determined without second modification, hence highly mitigating additional computation burden. Furthermore, in order to realize the purpose of unified switching frequency, the SVVs are implemented in terms of regular rather than irregular PWM signal pattern. Finally, experimental results prove the effectiveness of the proposed method.

To improve the voltage utilization rate of DC bus and reduce the voltage vector tracking error, a finite-control-set modulated model predictive control (FCS-M2PC) with overmodulation capacity for permanent magnet synchronous motor (PMSM) incorporating penalty function is proposed in this paper. Firstly, three modulation regions are determined according to the combined action of dead-beat control and model predictive control (MPC). Secondly, three, two and one voltage vectors are applied to linear modulation region (LMR), overmodulation region I (OMR-I) and overmodulation region II (OMR-II), respectively, to synthesize the reference voltage vector. Thirdly, to obtain better steady-state performance in the whole modulation region, the optimal vector dwell-times can be obtained from the uniform penalty function defined by a set of mode parameters to minimize the error between the current references and the current predictions, rather than applying a single voltage vector in the conventional finite-control-set model predictive control (FCS-MPC). The effectiveness and superiority of the proposed method are validated experimentally.

Although the traditional model predictive current control (MPCC) possesses superior advantages in terms of fast response, ease of implementation, and simultaneous control of multiple objections, the MPCC for permanent magnet synchronous machines (PMSMs) has a strong sensitivity to machine parameters and is a high computational method, especially in the overmodulation region. To address the above issue, an overmodulatable parameter-free predictive current control (PFPCC) for PMSMs based on an ultralocal model (ULM) is proposed in this article. First, a sliding mode observer and a model reference adaptive system have been developed to estimate the full parameters of the ULM of PMSM. Hence, the PFPCC is free of dependency on machine parameters. Subsequently, a computationally efficient three voltage vectors (VVs) PFPCC method with the ability of overmodulation is constructed by designing a simplified VV combinations preselection strategy and a low-complex overmodulation strategy. Finally, a 2 kW electric drive platform based on XC7Z030 is designed and conducted and the steady-state, dynamic, and overmodulation experiments were carried out to demonstrate the feasibility and effectiveness of the proposed method.

In this paper, a finite-control-set model predictive virtual-flux control (FCS-MPVFC) for a three-phase Vienna rectifier is developed and implemented to achieve voltage sensorless control, which is very robust to distorted grid-side voltage operation. Firstly, by investigating the relationship between virtual-fluxes aroused from grid-side voltages and line voltages in d-q frame, the control object is directly associated with virtual-flux tracking error minimization. Secondly, the reference line virtual-flux is calculated based on the controllability of active/reactive power associated with the delay compensation and load angle. Thirdly, to enhance the steady-state performance, switching sequence rather than single switching vector is utilized during one sampling period. Furthermore, a redundant vector pre-selection is adopted to balance the neutral-point voltage. The proposed strategy is compared with the traditional finite-control-set model predictive current control (FCS-MPCC) method. Both simulated and experimental results verify the effectiveness of the proposed control algorithm.

High system parameter sensitivity and large current ripple are two key drawbacks that hinder the further development of model predictive control (MPC) for power converters and motor drives. In this paper, an improved model-free predictive current control (MFPCC) based on an ultra-local model (ULM) is proposed for permanent magnet synchronous machines (PMSMs). The proposed method is free of dependence on arbitrary motor parameters and influence rejection of DC voltage mismatch since all unknown parameters of the ULM are estimated by current data only. Besides, the optimal voltage vector problem of MPC is converted to the shortest distance problem by constructing the forced current variation domain based on the ULM. On this basis, a double-vector MFPCC is developed to suppress current ripple, thus reducing torque ripple. On the whole, the proposed method is low-computational and therefore can be deployed in low-cost digital controllers. In the end, a 2 kW experimental setup is built and experiments under different operating conditions are carried out to demonstrate the effectiveness of the proposed method.