In fuel cell vehicles, the output voltage of the fuel cell source is typically much lower than the voltage required by the DC bus and also this output voltage drops significantly as the output current increases. In order to match the output voltage of the fuel cell source to the DC bus voltage, a new DC-DC boost converter with a wide input range and high voltage gain is proposed to act as the required power interface, which reduces voltage stress across the power devices and operates with an acceptable conversion efficiency. A prototype rated at 300W/400V has been developed and the maximum efficiency of the proposed converter was measured as 95.01% at 300W. Experimental results are presented to validate the effectiveness of the proposed converter.

The performance of a standard model predictive controller (MPC) is directly related to its predictive model. If there are unmodeled periodic disturbances in the actual system, MPC will be difficult to suppress the disturbances, thus causing fluctuations of system output. To solve this problem, this paper proposes an improved MPC named predictive-integral-resonant control (PIRC). Compared with the standard MPC, the proposed PIRC could enhance the suppression ability for disturbances by embedding the internal model composing of the integral and resonant loop. Furthermore, this paper applies the proposed PIRC to PMSM drives, and proposes the PMSM control strategy based on the cascaded PIRC, which could suppress periodic disturbances caused by the dead time effects, current sampling errors, and so on. The experimental results show that the PIRC can suppress periodic disturbances in the drive system, thus ensuring good current and speed performance. Meanwhile, the PIRC could maintain the excellent dynamic performance as the standard MPC.

Duty cycle model predictive torque control (Duty-MPTC) only uses zero vector as the second vector to form vector combinations, which restricts its torque control performance. This paper proposes a modified double vectors model predictive torque control (DVMPTC) by reasonably selecting active vector instead of zero vector. By analyzing the regulation of torque and flux of permanent magnet synchronous motor (PMSM), the torque and flux difference parameters are obtained, and then a second vector selection table is established to determine the best vector combination for torque ripple suppression. And based on the torque and flux difference parameters, the duty cycle calculation method is proposed to reduce the calculation burden of the control system. In order to verify the effectiveness of the proposed method, experiments with a 6-kW PMSM are carried out. Compared to Duty-MPTC, the proposed DVMPTC method can significantly reduce the torque ripples with good dynamic performance and relatively low average switching frequency.

In the motor drive system fed by multilevel inverter, the problems such as the complexity of reference voltage synthesis, high common mode voltage (CMV), and high switching loss are usually the obstacles to the practical application. In order to reduce the computational complexity and improve the performance of permanent magnet synchronous motor (PMSM), a novel space vector pulsewidth modulation scheme, which is practical and independent of level number is proposed for PMSM vector control. First, the space vector plane is redivided, and the coordinates of the nearest three vectors and their duty cycles can be obtained directly by determining the location of reference vector, which simplifies the calculation and does not need any iterative algorithm. Then, the optimal switching state and switching sequence are selected online so as to ensure the minimum switching loss under the premise of minimum CMV. This article provides an original method and new idea for motor drive system fed by multilevel inverter. Finally, the practicability and validity of the proposed method are verified by simulation and experiment.

The fast and stable current inner loop in the permanent-magnet synchronous motor (PMSM) control system is the key factor that ensures the torque control performance of the motor. The deadbeat model predictive control strategy can achieve fast dynamic response, but it depended on the accurate mathematical model of the motor. When the model parameter in the predictive controller has mismatched with real system, the static error or oscillations will occur in the steady state. Therefore, a novel current predictive control based on the fuzzy algorithm is proposed in this paper. The novel control strategy contained a predictive controller, a proportional-integral (PI) compensation link, a magnetic flux observer, and a fuzzy controller. According to the operation state of the motor and the model parameter mismatch of the controller, the fuzzy algorithm can adjust the effect of compensation link by weight coefficient in real time. The dynamic performance of the proposed method is guaranteed compared with the traditional deadbeat predictive current control based on the space vector pulsewidth modulation (SVPWM). When the model parameter mismatch of controller is occurred, the weight of the PI compensation link is enhanced, and the static error or oscillation of the motor system can be eliminated.

In the control of permanent magnet synchronous motors, the active disturbance rejection control (ADRC) has attracted considerable attention due to its intrinsic ability for disturbance rejection. However, the existing ADRC methods have the problem of coupling the reference tracking performance and disturbance suppression performance. To simultaneously improve the current control's dynamic response speed and steady-state control accuracy, a two-degree-of-freedom ADRC current control method based on the improved extended state observer (IESO) is proposed in this article. First, the designed IESO cancels the error correction term in the observed current update law to realize the complete decoupling of the reference tracking performance and disturbance suppression performance. Under the decoupling structure, the observed disturbance update law of the IESO is designed as a proportional-integral-repetitive control structure to suppress periodic and aperiodic disturbances. Then, the system stability is proved by analyzing the distribution of characteristic roots, and a two-step parameter tuning guideline of the IESO is provided. The proposed method realizes the complete decoupling of the reference tracking performance and disturbance suppression performance, reducing the complexity of the controller parameter selection and facilitating the realization of the high-performance current control. Finally, the effectiveness of the proposed method is validated by experimental results.