In this paper, a new vibration reduction control of the switched reluctance machine (SRM) is proposed that takes into consideration the undesirable effects of the torque ripple. The control approach aims to reduce the variation of the sum of radial forces while optimizing the control parameters of the machine to achieve the torque ripple minimization. Thus, a reference current adapter is used in order to handle the trade-off between the vibration reduction and the torque ripple reduction. It produces an auto-tuning reference current that limits the variation of the torque and the total radial force. The effectiveness of the proposed control strategy is proved by simulation and experimental results. Comparisons with conventional control methods investigating vibrations, noise and torque ripple are provided, which show the advantages of the control approach based on an auto-tuning reference current.

This paper presents the control of a Switched Reluctance Generator (SRG) for low voltage DC grid with the objective of efficiency maximizing. Analysis of the energy conversion, including electrical machine losses (Joule, magnetic, mechanical) and power converter losses (switching and conduction), has shown that there is an optimal combination of control variables (turn-on and conduction angles, phase current reference), which maximizes the drive efficiency. The control variables are derived from a Finite Element Analysis and parametric optimization algorithm for all of the operating points in the torque-speed plane and stored in lookup tables. The performances are evaluated with intensive numerical simulations and experimental tests with a 8/6 SRG feeding a DC resistive load for different rotational speeds. The results show good performances of the output DC voltage control with low ripples, even in the presence of speed and load variations. Thanks to the optimization, simulation results show that beyond 1500 rpm, drive efficiency is higher than $60\%$ and almost reaches $70\%$ at nominal speed. The experimental results show that, for light loads and beyond rated speed, the drive efficiency lies in the range between $60\%$ and $80\%$ .

In this paper, the intermittent control is proposed for switched reluctance machine drive to both increase the efficiency and decrease the cost of the traction system for low-cost electric vehicles. With the purpose of maintaining the average machine torque required by the load, the intermittent control imposes a higher phase torque during a shorter time. The simulation and experimental results achieved with two different switched reluctance machines show that the intermittent control increases the system efficiency by reducing the converter losses and the core losses. Additionally, the intermittent has three different strategies solving different criteria of an automotive application: efficiency, machine vibration and torque pulsation. It can also be easily applied for any switched reluctance machines using average-torque-control-based methods.

This paper presents a hardware/software implementation for the vibration reduction control of a switched reluctance machine (SRM). A mixed partitioning-based architecture is proposed to make full use of both microprocessor and Field-Programmable Gate Array (FPGA) resources. The aim of the proposed controller is to control directly the radial forces in the stator teeth allowing a significant vibration reduction compared to regular controller applied to SRM. However, if the control is software-only implemented, it suffers from performance degradation due to the high execution time required by this implementation solution. For this reason, the control system implementation is partitioned. The speed control is implemented using a microprocessor, while the current control and direct force control are implemented in FPGA. This solution provides high dynamic response especially needed to control the radial force and the currents. The effectiveness of the hybrid implementation is verified by experimental results.

Due to their inherent advantages such as low cost, robustness and wide speed range, switched reluctance machines (SRMs) have attracted great attention in electrical vehicles. However, the vibration and noise problems of SRMs limit their application in the automotive industry because of the negative impact on driver and passengers’ comfort. In this paper, a new control method is proposed to improve the vibratory and acoustic behavior of SRMs. Two additional control blocks —direct force control (DFC) and reference current adapter (RCA)—are introduced to the conventional control method (average torque control (ATC)) of SRM. DFC is adopted to control the radial force in the teeth of the stator, since the dynamic of the radial force has a large impact on the vibratory performance. RCA is proposed to handle the trade-off between the DFC and ATC. It produces an auto-tuning current reference to update the reference current automatically depending on the control requirement. The effectiveness of the proposed control strategy is verified by experimental results under both steady and transient condition. The results show that the proposed method improves the acoustic performance of the SRM and maintains the dynamic response of it, which proves the potential of the proposed control strategy.

The switched reluctance generator (SRG) has intrinsic spatial and magnetic nonlinearities, making it challenging to design an output voltage controller with accurate tracking performance. This article proposes a linearization technique to improve the voltage control of SRG. A linearization block, which describes the nonlinear relation between SRG's phase current reference and averaged output current under various speed conditions, is added in the control loop. The linearization block's analytical expression is derived according to the electromechanical conversion principle of SRG. The experimental results show that, thanks to the linearization, the settling time is divided by more than two during transients, compared with the classical methods that ignore the nonlinearities. The performance of the voltage tracking is also significantly improved: the mean absolute error for load or voltage change is improved by more than 60% and 30%, respectively.