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Switched reluctance motors (SRMs) offer several advantages, including a magnet- and winding-free rotor, high mechanical strength, and exceptional output efficiency. However, the doubly salient pole structure and high-frequency switching power supply result in significant torque ripple and electromagnetic noise, which limit the application in the field of new energy vehicles. To address these issues, this paper proposes a direct instantaneous torque control (DITC) strategy based on an optimal switching angle torque sharing function (TSF). Firstly, an improved cosine TSF is designed to reasonably distribute the total reference torque among the phases, stabilizing the synthesized torque of SRM during the commutation interval. Subsequently, an improved artificial bee colony (ABC) algorithm is used to obtain the optimal switching angle data at various speeds, integrating these data into the torque distribution module to derive the optimal switching angle model. Finally, the effectiveness of the proposed control strategy is validated through simulations of an 8/6-pole SRM. Simulation results demonstrate that the proposed control strategy effectively suppresses torque ripple during commutation and reduces the peak current at the beginning of phase commutation. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Zhengzhou University: Engineering Science is the property of Editorial Office of Journal of Zhengzhou University: Engineering Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The traditional torque sharing function (TSF) strategy can lead to large torque ripple and copper consumption in switched reluctance motors (SRMs) due to the limitation of the voltage in the phase change interval. In this paper, an improvement scheme is proposed to address this problem. First, a segmented non-linear correction TSF (SN-TSF) is proposed. Then with the torque ripple and copper consumption of the SRM as optimization objectives, the proposed SN-TSF values are optimized using the velocity control particle swarm optimization (VCPSO) algorithm based on the particle velocity–boundary relationship. The optimal parameters are used to obtain the optimal SN-TSF curves with different loading torques and speeds. Experimental results show that the proposed SN-TSF strategy reduces the torque ripple by 40.17% and 66.5%, and the peak phase currents by 5.058 A and 5.371 A under two different operating conditions, which demonstrates the effectiveness of this strategy. [ABSTRACT FROM AUTHOR]

Aiming at the problems of large torque ripple in permanent magnet-assisted switched reluctance motor (PMa-SRM) under conventional voltage pulse width modulation (PWM) method. A torque sharing function (TSF) control strategy with interval segmented zero-voltage modulation is proposed in this paper. Firstly, the zero voltage is decentralized by optimizing the PWM modulation method. Secondly, the control interval is divided and a segmented TSF based on hyperbolic tangent function transformation is proposed tailored to the torque characteristics. Then, the PWM variable duty cycle control is carried out according to the inductance characteristics. In the single-phase conduction region (SpC), the optimal duty cycle is predicted by using the deadbeat predictive control (DPC); in the two-phase exchange region (TpE), the duty cycle function is designed for each interval, and the duty cycles of the incoming and outgoing phases are obtained online through the torque error. Finally, simulations and experimental verification of the 6/20 PMa-SRM prototype confirm that the proposed control strategy to have good performance in torque ripple suppression.

The benefits of utilizing Switched Reluctance Motor (SRM) drives in traction applications can be realized fully by improving the electromagnetic performance of the machine in the generating mode of operation. This is because the generating capability of an SRM drive could be utilized for regenerative braking and also for the machine to generate power for the vehicle while the engine is in operation. In this paper, a current profiling-based control strategy is proposed to reduce the torque ripple in an SRM drive in the generating mode. The reference current profile is determined using a multi-step computation method to minimize torque ripple and maximize the average torque. The reference current profile is derived based on the reference torque command by utilizing the torque–current–angle look up table. The flux linkage characteristics of the SRM are considered when deriving the phase reference current profile. Then, the performance of the proposed profiling method, analytical linear and cubic torque sharing functions (TSFs), and the average torque optimization scheme are compared using simulation results. Finally, an experimental correlation is performed to validate the efficacy of the proposed control scheme. [ABSTRACT FROM AUTHOR]

In this paper, a new torque sharing function control strategy is proposed to reduce the torque ripple. The traditional torque ripple methods, such as exponential and linear torque allocation strategies, the torque generation capacity of each phase and the power limitation of the power converter is not taken into account, in this paper, the communication region is divided into three intervals by establishing a new partitioning standard. According to the re-established reference function of torque generation, the torque deviation caused by phase current tracking error is compensated according to the torque generation capacity. Both optimization of torque ripple suppression and copper loss minimization are taken into consideration in this paper. To verify the validity and performances of the proposed TSF methods, simulations and experiments have been implemented in a 12/8 structure Switched Reluctance Motor prototype. This method can be applied to other switched reluctance motors with different topologies. Result shows lower current tracking error and better performance of torque ripple minimization compared with the conventional two-interval compensation method. [ABSTRACT FROM AUTHOR]

This paper proposes a multi-platform algorithm methodology in order to define firing angles of torque sharing functions (TSFs) for the indirect torque control of switched reluctance motors (SRM) through a hardware-in-the-loop (HIL) system. This proposal is used to achieve optimal levels of torque ripple and losses with accuracy and reliability, while taking advantage of real-time simulation. The analysis is performed assuming steady-state conditions of speed and torque reference for levels below the base speed, aiming to obtain firing angles ensuring optimal tracking performance. A novel methodology is proposed by using a grid search algorithm that handles the communication between Python, Code Composer, and the Typhoon HIL device. For that, an experimental data FPGA-based model with 500~ns of simulation time step is used to ensure highly accurate dynamic responses of current and electromagnetic torque. Moreover, controller-HIL (C-HIL) is used to have a safe and high fidelity testing environment, allowing rapid testing before transitioning to an experimental test bench. The simulation results are experimentally validated, demonstrating that the proposed strategy is effective and ensures optimal performance, taking into account peripheral systems of A/D, signal conditioning, PWM, and sensor emulation.

Switched reluctance motors (SRMs) offer several advantages, including a magnet- and winding-free rotor, high mechanical strength, and exceptional output efficiency. However, the doubly salient pole structure and high-frequency switching power supply result in significant torque ripple and electromagnetic noise, which limit the application in the field of new energy vehicles. To address these issues, this paper proposes a direct instantaneous torque control (DITC) strategy based on an optimal switching angle torque sharing function (TSF). Firstly, an improved cosine TSF is designed to reasonably distribute the total reference torque among the phases, stabilizing the synthesized torque of SRM during the commutation interval. Subsequently, an improved artificial bee colony (ABC) algorithm is used to obtain the optimal switching angle data at various speeds, integrating these data into the torque distribution module to derive the optimal switching angle model. Finally, the effectiveness of the proposed control strategy is validated through simulations of an 8/6-pole SRM. Simulation results demonstrate that the proposed control strategy effectively suppresses torque ripple during commutation and reduces the peak current at the beginning of phase commutation.

Copyright of Electric Machines & Control / Dianji Yu Kongzhi Xuebao is the property of Electric Machines & Control and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Switched reluctance motors (SRMs) have recently gained notable interest in industrial applications. Yet, their inherent torque ripple poses a significant impediment, limiting the adoption of SRM in high-performance applications. Instantaneous Torque Control (ITC) based on conventional Torque Sharing Function (TSF) is considered a promising technique for torque ripple reduction of SRMs at low speeds. However, the back electromotive force is increased with speed escalation, reducing torque tracking ability to its reference in the ITC based on conventional TSF, especially in the demagnetizing period. The high inductance value in this period opposes phase-current decaying, generating considerable torque ripple, making the ITC unsuitable at medium and high speeds. This paper proposes the indirect ITC based on an improved TSF to address the torque ripple over extended speed for SRM drive. The improved TSF relies on predicting the outgoing phase torque in the demagnetizing period and compensating for the difference between the predicting and reference torque in the next excitation phase by reshaping the incoming phase torque, minimizing the torque ripple. Moreover, simple analytical formulas are used to regulate the control angles to gain further improvements and extended speed. An accurate nonlinear motor model is created based on static magnetic characteristics estimated by the finite element analysis. Several simulated results are conducted to evaluate the effectiveness of the proposed controller. The proposed method offers higher torque ripple mitigation with the speed increase, decreasing the torque ripple by 10% to 45%. Furthermore, the proposed control reduces copper losses and enhances efficiency and torque/current ratio.

In this paper, a new torque sharing function control strategy is proposed to reduce the torque ripple. The traditional torque ripple methods, such as exponential and linear torque allocation strategies, the torque generation capacity of each phase and the power limitation of the power converter is not taken into account, in this paper, the communication region is divided into three intervals by establishing a new partitioning standard. According to the re-established reference function of torque generation, the torque deviation caused by phase current tracking error is compensated according to the torque generation capacity. Both optimization of torque ripple suppression and copper loss minimization are taken into consideration in this paper. To verify the validity and performances of the proposed TSF methods, simulations and experiments have been implemented in a 12/8 structure Switched Reluctance Motor prototype. This method can be applied to other switched reluctance motors with different topologies. Result shows lower current tracking error and better performance of torque ripple minimization compared with the conventional two-interval compensation method.

Copyright of Electric Machines & Control / Dianji Yu Kongzhi Xuebao is the property of Electric Machines & Control and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Switched reluctance motor (SRM) drive has outstanding features like robust construction, double saliency, fault tolerance capability, and heat withstanding capability. Despite these, torque ripple is an intrinsic characteristic of SRM because of double salient geometry, air gap length, and switching sequence of motor phase currents, making it unsuitable for slick torque and high dynamic performances applications. This paper discusses the novel Torque Sharing Function (TSF) implementation and the flower pollination algorithm-based intelligent controller to minimize the torque ripples in Switched Reluctance Motor (SRM). TSF values depend on commutation angles during turn on, turn off, and overlapping angles. The proposed TSF and flower pollination algorithm evaluates the performance parameters using the machine model and controls the torque ripples for a wide range of speeds. Additionally, optimal results are obtained using three TSFs functions with valuable guidance provided for TSF selection. The proposed TSF with flower pollination algorithm-based intelligent controller finds its suitability for online evaluation of optimal turn on, turn off, and overlapping angles. The performance of the proposed method has effectively reduced the torque ripple in SRM than the Differential Evolution (DE) algorithm. [ABSTRACT FROM AUTHOR]

This paper presents a novel indirect predictive control method to reduce the torque ripple of switched reluctance motor drive in electric vehicle (EV) application. The proposed indirect predictive torque control algorithm includes two parts: torque inverse model and robust predictive current controller. The torque inverse model adopts the form of adding torque error compensator to the simple linear model to realize the accurate mapping from torque to current, which avoids the complex calculation of the traditional torque inverse model. Then the predictive current controller is designed to traverse all candidate switching states and use the switching state of minimizing the cost function as the optimal output. Further, the modeling error, parameter variations and sampling error are equivalent to a total disturbance, which are compensated by the developed disturbance observer to improve the robustness of the predictive control. The proposed predictive control scheme indirectly realizes the instantaneous torque control through the accurate tracking of current, which is easy to implement, and is suitable for driving electric vehicles. Simulation experiments are performed to verify the effectiveness of the proposed predictive control algorithm.

This paper proposes a unified control method based on an improved grey wolf optimization algorithm to improve the performance of the switched reluctance motors (SRMs) to cope with various operating conditions. Compared with the single control mode of traditional SRMs, an SRM with 12/10 poles is called a multimode switched reluctance motor, which can be used not only as a six-phase motor but also as a three-phase motor. The control method proposed is based on a 12/10 pole SRMs. In the TSRM mode, an improved torque sharing function with parameters is utilized to reduce torque ripple and widen the speed range. In the SSRM mode, the linear active disturbance rejection control (LADRC) method is used to increase the anti-interference ability of the system. For the switching modes, an improved gray wolf optimization algorithm is designed to ensure smooth switching. The global optimal solution is obtained by introducing the coyote group to avoid falling into the local optimal solution. Finally, the experimental results prove the effectiveness of the control method. • The 12/10 SRM is used as a TSRM mode and a SSRM mode. And a unified control method is proposed. • The proposed method uses an improved TSF and the LADRC method in different modes and they can switch smoothly. • In TSRM mode, an improved TSF with tunable parameter is proposed to reduce the torque in a wide speed range. • An improved grey wolf packs optimization algorithm for introducing coyote packs is designed. • The proposed method can reduce torque ripple within 23.5% in the rated speed range. [ABSTRACT FROM AUTHOR]

In this paper, we presents an improved hybrid control scheme based on model predictive torque control using linear active disturbance rejection control (LADRC) for the torque drive system of a 12/14 bearingless switched reluctance motor. The proposed approach can considerably reduce the torque ripple and enhance the anti-disturbance ability. First, a modified piecewise torque sharing function (TSF) is applied to reduce the torque ripple in the commutation interval. Second, model predictive control is introduced to further reduce the torque ripple caused by the hysteresis control. The selection of the optimal weighting factor is avoided, as the current value corresponding to different positions of each phase is determined by the TSF; thus, the cost function can be simplified. Then, a speed controller is designed by an enhanced LADRC for improved tracking performance and anti-disturbance ability, whereby a proportional gain of observation error and a time-varying function are investigated in extended-state observer. Finally, experiments are carried out to verify the effectiveness of the hybrid control scheme by comparison with cosine TSF function and conventional LADRC. [ABSTRACT FROM AUTHOR]

In this work, three control techniques of minimization of torque ripple in SRM are proposed and compared to the classical control technic names as Hysteresis control proposed in [1]. The principle of these methods is based on the Torque Sharing Function (TSF) fixing the reference torque in each phase. In the literature review, the classical method used in the reduction of torque ripples in SRM is the TSF-Hysteresis Controller (TSF-H). The first proposed method is the TSF-Predictive control (TSF-P), here the objective is to find the voltage to be applied to the machine minimizing the error of the current through a prediction algorithm on the supply current. The second proposed method is the sliding mode control (TSF-SMC-PSO) whose parameters are optimized by the particle swarm algorithm (PSO). Finally, the third proposed method is the sliding mode controller whose parameters are optimized by fuzzy logic controller (TSF-SMFC). The finite element method (FEM) through the magnetic field calculation software FEMM was used to calculate the flux and torque in static system and to take into account magnetic saturation circuit of the SRM. The results obtained show that the TSF-SMC-PSO control methods have better performance compared to the other proposed methods mentioned above. [ABSTRACT FROM AUTHOR]

Torque sharing function (TSF)-based switched reluctance motor (SRM) control is an effective approach to minimize torque ripple and maximize efficiency. This study investigated the influence of the rotor geometry to overcome the inherent torque and current tracking error of used TSFs. Parameters of the TSF were optimized according to several objectives. A finite element method simulation model of the motor was built and verified to evaluate the objective functions. The optimization result is a set of functions that calculate optimal values of the start angle and overlap angle of the sinusoidal TSF for every operating point of the motor. Different objectives, including efficiency and a torque ripple, lead to different functions for calculating start and overlap angles. The research showed that if efficiency is the most important objective, it is possible to determine a suitable rotor pole geometry. For other criteria, the choice of rotor geometry is not so clear-cut and requires consideration of the SRM operating modes.

Copyright of Electric Machines & Control / Dianji Yu Kongzhi Xuebao is the property of Electric Machines & Control and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Electric Machines & Control / Dianji Yu Kongzhi Xuebao is the property of Electric Machines & Control and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This article presents a method to reduce the torque ripple in an 8/6 four-phase switched reluctance motor (SRM). The proposed scheme introduces a nonlinear modulating factor dependent on the rotor position and magnitude of the phase currents. This factor manipulates the currents in two adjacent phases during commutation and reduces the torque ripple effectively. Unlike the conventionally available torque-sharing functions, the proposed method instantaneously modulates every phase current obtained mathematically based on the other phase current in order to maintain the net torque constant. The proposed method requires minimal offline analysis and offers maximum possible torque with a minimal ripple. The method is simple and easy to implement due to a low computational burden. The proposed algorithm is implemented using MATLAB/Simulink software and is also validated experimentally on a 0.6-hp 8/6 SRM using a field-programmable-gate-arrays-based hardware setup developed in the laboratory. Typical results are presented and compared with the existing techniques. A torque ripple of $\approx 8\%$ has been achieved. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Zhengzhou University: Engineering Science is the property of Editorial Office of Journal of Zhengzhou University: Engineering Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper, a novel control method based on model predictive control (MPC) and torque sharing function (TSF) is addressed to minimize the torque ripple of switched reluctance motor (SRM). Firstly, an accurate SRM model is established based on flux‐linkage characteristic curves obtained from the locked rotor test, which can predict the future operation state of the SRM drive system. Secondly, an improved TSF curve is proposed, and genetic algorithm is used to optimize TSF parameters to reduce torque ripple in commutation region. Besides, the MPC is integrated into the TSF control framework to replace the traditional hysteresis controller, and establishes a new TSF‐based model predicted torque control (MPTC) method, which avoids the frequency conversion problem caused by torque or current hysteresis controller. Further, a sector division scheme is addressed to decrease the number of candidate voltage states, whereby the computation of the controller in each sampling period is effectively reduced. Finally, in order to verify the correctness of the MPTC method, it is compared with the traditional direct instantaneous torque control (DITC). Both simulations and experiments on a three‐phase 12/8 pole SRM have confirmed that MPTC scheme can not only decreases torque ripple and stator copper losses, but also has higher efficiency than DITC. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

In this paper, we presents an improved hybrid control scheme based on model predictive torque control using linear active disturbance rejection control (LADRC) for the torque drive system of a 12/14 bearingless switched reluctance motor. The proposed approach can considerably reduce the torque ripple and enhance the anti-disturbance ability. First, a modified piecewise torque sharing function (TSF) is applied to reduce the torque ripple in the commutation interval. Second, model predictive control is introduced to further reduce the torque ripple caused by the hysteresis control. The selection of the optimal weighting factor is avoided, as the current value corresponding to different positions of each phase is determined by the TSF; thus, the cost function can be simplified. Then, a speed controller is designed by an enhanced LADRC for improved tracking performance and anti-disturbance ability, whereby a proportional gain of observation error and a time-varying function are investigated in extended-state observer. Finally, experiments are carried out to verify the effectiveness of the hybrid control scheme by comparison with cosine TSF function and conventional LADRC.

This paper presents a Torque Sharing Function (TSF) control of Switched Reluctance Machines (SRMs) with different current sensor placements to reconstruct the phase currents. TSF requires precise phase current information to ensure accurate torque control. Two proposed methods with different chopping transistors or a new PWM implementation require four or two current sensors to replace the current sensors on each phase regardless of the phase number. For both approaches, the actual phase current can be easily extracted during the single phase conducting region. However, how to separate the incoming and outgoing phase current values during the commutation region is the difficult issue to deal with. In order to derive these two adjacent currents, the explanations and comparisons of two proposed methods are described. Their effectiveness is verified by experimental results on a four-phase 8/6 SRM. Finally, the approach with a new PWM implementation is selected, which requires only two current sensors for reducing the number of sensors. The control system can be more compact and cheaper.

This paper presents a new and improved Torque Sharing Function (TSF) to minimize torque ripple of Switched Reluctance Motor (SRM). This approach combined of three steps. At first step, Genetic Algorithm has been used to define the best Turn-on and Turn-off angel of phase current. At second step, a fuzzy logic controller system has been designed as a new TSF. Finally, at the last step, Particle Swarm Optimization (PSO) has been used to optimize Fuzzy membership function. The two main merits of this approach are that the proposed control algorithm can be used in wide speed ranges and also three-step-design and optimization makes this approach enable to perfectly results in smooth torque. The effectiveness of this approach has been verified through a simulation of four phase 8/6 SRM in Matlab/Simulink. Obtained result from simulation shown that the produced torque was high quality and its ripple was one-third of fuzzy TSF. This proposed method is very powerful to adapt itself for various kind of SRMs with different parameters.

Abstract—This article presents a novel torque ripple minimization approach based on the genetic algorithm (GA) for the switched reluctance motor (SRM) drives. The fitness function of the GA is designed on the basis of two main optimization criteria. The first optimization criteria; three objectives are defined to optimize commutation angles minimizing torque ripple and copper loss. The second optimization criteria; an objective is defined to eliminate the negative torque which decreases the average torque in SRM drives. The achievement of all objectives depends on the adjusting appropriate the commutation angles of the torque sharing functions (TSF) during the commutation period. All of conventional TSFs are dependent on three different commutation angles, namely turn-on, turn-off, and overlapping. Due to the nonlinear phase inductances of SRM, the delay of current rising and falling time are not unity in overlapping commutation region. To overcome the separation of the incoming and outgoing phase currents during the commutation region, rise angle, and fall angle are used instead of overlapping angle. GA is used to optimize the commutation angles of conventional (sinusoidal) TSF and improved (sinusoidal) TSF. At the same time, the elimination negative torque effects on torque ripple, average torque, and copper loss is investigated. [ABSTRACT FROM AUTHOR]

Large torque and voltage ripple are inherent drawbacks of doubly salient generators. This paper first introduces torque sharing function (TSF) into the application of a dual-channel three-phase 12/8 poles doubly salient permanent magnet generator (DSPMG) to reduce torque and voltage ripple. Based on the principle of copper losses minimization, a new TSF is proposed through theoretical analysis and numerical computation. The proposed TSF is compared to conventional TSFs according to three evaluation criteria. In order to achieve satisfying and consistent steady state and dynamic performances over the whole operation range, gain scheduling PI controller is adopted to overcome the highly nonlinear characteristic of the DSPMG. Besides, with compensators of back-EMF, cogging torque and losses adopted as feed-forward, a dual closed-loop generation control system is detailed designed. Both simulation and experimental results verify the effectiveness of the proposed control system and the copper losses minimization TSF in reducing torque and voltage ripple. [ABSTRACT FROM AUTHOR]

This paper introduces an optimal control model strategy to minimize system loss and meantime to maintain low torque ripple for a can-shielded switched reluctance machine (SRM). The system loss consists of semiconductor loss from power converter, as well as loss from the machine which not only includes traditional iron and copper losses, but also the characteristic ohmic can loss and friction loss due to the use of can shields. In particular, the can loss is calculated by Poynting’s theorem of magnetic energy conversion using a model of concentric layer structure. Loss of semiconductors considers temperature rise effect by an electro-thermal coupling approach. The effectiveness is verified on a 3-phase 20 kW 12/8 canned SRM. [ABSTRACT FROM AUTHOR]

Copyright of Electric Machines & Control / Dianji Yu Kongzhi Xuebao is the property of Electric Machines & Control and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The switched reluctance machine against its several merits such as simplicity, robustness, less cost manufacturing and large speed still suffers from its undesirable torque ripple and acoustic noise. Compared to different candidates of hybrid and electric vehicle engine, the frequency of use of SRM in traction drives is improved with the different optimizing torque oscillation solutions. Most of studies used the generic or specific model of switched reluctance machine in the Simulink library (6/4,8/6 and 10/8). Despite, a new non linear model simply implemented in Simulink tool using a static finite element analysis a previous study is used in this work. Hence, a 12/8 non linear SRM drive system is simulated using MATLAB toolbox tested with an intelligent controller (FLC) in order to minimize the torque ripple of an oriented starter-alternator application of a hybrid vehicle. [ABSTRACT FROM AUTHOR]

In this paper, an extended-speed low-ripple torque control of switched reluctance motor (SRM) drives using torque sharing function (TSF) is proposed. Two operational modes are defined for the online TSF during commutation: In Mode I, absolute value of rate of change of flux linkage (ARCFL) of incoming phase is higher than outgoing phase; in Mode II, ARCFL of outgoing phase is higher than incoming phase. In order to compensate the torque error produced by imperfect tracking of phase current, a proportional and integral compensator with torque error is added to the torque reference of outgoing phase in Mode I and incoming phase in Mode II. Therefore, the total torque is determined by the phase with lower ARCFL rather than the phase with higher ARCFL as in conventional TSFs. The maximum torque-ripple-free speed of the proposed TSF is increased to more than ten times as the best case in conventional TSFs. Finally, the proposed TSF is verified by both simulations and experiments with a 2.3 kW, 6000 rpm, three-phase 12/8 SRM operating in both linear magnetic and saturated magnetic regions. Results show that the proposed TSF has higher average torque, and much lower torque ripples compared to conventional TSFs. [ABSTRACT FROM AUTHOR]