This paper introduces a parameter estimation technique for power electronic inverter-based systems. Specific attention is given to the real-time parameter estimation of dc-ac switched-mode power converters; Nevertheless, the proposed method can be applied to many alternative applications where efficient and accurate parameter estimation is required. The proposed scheme is computationally efficient, based on a Kalman filter algorithm, and uses an infinite impulse response adaptive filter as the plant model. The system identification scheme reduces the complexity of computation of existing typical adaptive algorithms. Importantly, the proposed approach can also identify the parameters fast and accurately, thus providing an efficient hardware solution that is suitable for real-time applications. In doing so, the uncertainties of VSIs can be identified by estimated parameters changes. The analysis of simulation and verification based on experimental data from a prototype flexible dc-ac converter is presented. Results clearly demonstrate that the estimated parameters of the dc-ac converter are a high match to the real experimental system. The scheme can be directly employed on adaptive and self-tuning digital controllers to improve control performance of a wide range of renewable energy applications.

Switched reluctance motors (SRMs) are highly regarded for their robustness and simplicity; however, they frequently encounter challenges associated with high torque ripple, significantly impacting their overall performance and efficiency. This paper presents a novel power converter specifically engineered to mitigate this issue by substantially reducing torque ripple in SRMs. The proposed converter incorporates a strategically positioned capacitor to enhance negative voltage discharge during the demagnetisation phase, effectively curtailing negative torque generation. Comparative analysis with the Asymmetric Half-Bridge Converter (AHBC) under lower voltage conditions revealed a slightly elevated torque ripple in the proposed converter’s performance. However, at 250V, it demonstrated a notable 10% reduction in torque ripple, with further enhancements of up to 79% observed at 400V. The results of the experiments mirror the results of the simulations, indicating the performance of the converter in enhancing SRM performance and efficiency. This development represents a significant advancement over traditional converter designs, presenting a compelling solution for the wider adoption of SRM technology.

This paper introduces a novel, compact, and adaptable power converter topology tailored for three-phase Switched Reluctance Motors (SRMs). The proposed converter utilizes five switches, five diodes, and two capacitors, the latter specifically incorporated to alleviate voltage spikes and lessen stress imposed on the lower leg switch. This topology can be categorized as a q+2 configuration, where ‘q’ represents the phase count of the SRM. Engineered with automotive applications in mind, the converter offers salient advantages over the conventional Asymmetric Half Bridge Converter (AHBC), including reduced torque ripple, enhanced demagnetization rates, and improved torque to current ratio. The converter is crafted using Silicon Carbide (SiC) MOSFET power transistors and SiC diodes, and its performance is validated using PLECS simulation software. The inherent flexibility and scalability of the proposed converter make it a viable and efficient solution for a broad spectrum of SRM applications.

Isolated DC/DC modular multilevel converters (MMC) consisting of two MMCs isolated by a transformer are one of the converter topologies being considered used for DC/DC conversion in HVDC transmission. Two level modulation can be used to obtain different voltage levels by inserting/bypassing a specific number of sub-modules (SM) in the converter circuit. However, it does not take into account the SM's voltage when elevation factors need to be readjusted, which results in either higher or lower output voltage than the reference. This paper proposes a finite control set model predictive control (FCS-MPC) for output voltage regulation to the reference value. A cost function comprising the output voltages is defined and a mathematical equation is formed to calculate the one step ahead value of output voltage. The number of SMs which minimize the cost function is applied to the converter circuit. Voltage balancing amongst the sub-module cells has been achieved by using a sorting algorithm. The performance of the proposed control strategy is evaluated and verified.

Periodic speed errors can occur in permanent magnet linear synchronous machines for two reasons: 1) a periodic reference signal; 2) cogging force and friction. For reducing such periodic errors, iterative learning control or repetitive control approaches, used in conjunction with more common control actions, can be strongly effective. However, the design of the stability filter, robustness filter and other parameters for a traditional repetitive controller can be a complex task and may need to be adjusted when the frequency of such periodic error varies. Existing solutions tend to develop more adaptive tuning methods for repetitive controller to enhance the whole control system. This paper shows that the performance of a traditional speed loop can be enhanced with a repetitive controller without complicating the tuning of the repetitive controller. Consequently, a position-based repetitive control combined with deadbeat current control method is proposed. Simulation results show that the proposed method is effective for reducing speed ripple at difference frequencies without necessarily adjusting its parameters.

The paper presents a new implementation of direct flux and current vector control of an induction motor drive using the techniques of model predictive control. The advantages offered by predictive control are used to enhance the dynamics of direct flux vector control. To minimize the problems of variable switching frequency inherent to finite control set predictive control, an alternative approach using pulse width modulation is studied for command execution as occurs in the so-called modulated model predictive control. A comparison between finite control set and modulated model predictive control is presented and the results are also compared with the control implementation through traditional proportional-integral regulators to highlight the advantages and drawbacks of predictive control based strategies. Apart from a greater harmonic content in stator currents, the predictive control can offers control dynamics comparable with proportional-integral control while maintaining immunity against machine parameter variations and excluding the need for controller tuning.

From the structure point of view, a repetitive controller (RC) is considerably similar to a disturbance observer. By adding a correction term to the traditional RC and considering the disturbances as states, the repetitive controller can be designed in the same way as a disturbance observer. This paper presents therefore a new simple way of tuning a repetitive controller. Simulations show that, when compared with the traditional RC, the proposed RC configuration can achieve greater stability margin. As opposed to the traditional plug-in RC, the new RC structure studied in this paper is also shown to be robust against variations in the inner loop delays if it is used in a cascaded configuration. The immunity to plant parameter variations is another added benefit of the proposed controller.

In this paper, a fault assessment of a multiphase permanent magnet generator designed for `more electric engine' aeronautic applications is presented. The distribution of various electrical faults occurring in three-phase machines that is available in the literature helped the authors to identify the most probable fault types. The six-phase machine under observation is tested under these faults both in Finite Element Analysis (FEA) as well as experimentally. In the experimental analysis, the generator supplies a resistive load through rectifier bridges when faults are introduced at its terminals. For a variety of fault situations, the measured machine response is compared with the finite element results in order to validate the accuracy of the implemented FEA model. The comparison show an extremely good match between simulated and measured results, without the need of particular fine-tuning of the model.