Torque Sharing Function Research Articles

Enhancing SRM Performance through Multi-Platform Optimization and FPGA-Based Real-Time Simulation

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.

An Online Torque Sharing Function Method Based on Region Division for Reducing Torque Ripple and Copper Losses of Switched Reluctance Motors

An Online Torque Sharing Function Method Based on Region Division for Reducing Torque Ripple and Copper Losses of Switched Reluctance Motors

Current Profiling Control for Torque Ripple Reduction in the Generating Mode of Operation of a Switched Reluctance Motor Drive

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.

Model Predictive Control of Switched Reluctance Machines With Online Torque Sharing Function Based on Optimal Flux-Linkage Curve

Model Predictive Control of Switched Reluctance Machines With Online Torque Sharing Function Based on Optimal Flux-Linkage Curve

A New Torque Control Approach for Torque Ripple Minimisation in Switched Reluctance Drives

The switched reluctance motor (SRM) has many merits, such as robustness, a simple construction, low cost, and no permanent magnets. However, its deployment in servo applications is restrained due to acoustic noise and torque ripple (TR). This paper presents a new torque control approach for TR reduction in switched reluctance drives. The approach is based on the maximum utilisation of the available dc-link voltage, hence extending the zero torque-ripple speed range. The approach is suitable for an SRM with any number of phases and stator/rotor poles. Soft switching control is deployed, which reduces switching losses. At any instant (regardless of the number of phases being conducted simultaneously), only one phase current is controlled. The well-established torque-sharing function concept is adapted and generalised to cater for more than two phases conducting simultaneously. MATLAB/Simulink confirmation simulations are based on the widely studied four-phase 8/6, 4 kW, 1500 rpm SRM.

Torque fault compensation in electric vehicle switched reluctance motor drives: A jellyfish search optimization method

AbstractIn this paper, an enhanced indirect instantaneous‐torque‐control is proposed based on the torque sharing function approach of switched reluctance motor drives for electric vehicles by employing the jelly fish search. The major goal is to attain vehicle desires that include minimal torque ripple, maximum torque per ampere (MTPA), and huge performance and extend speed limit. First, a simplest analytic design is developed a determine more proficient turn‐on angle for the torque product. Second, an altered torque sharing function (TSF) is used for compensating the faults of torque tracking. The proposed technique is calculated to represent an accurate switched reluctance motor and its magnetized features. They have worked to create the machine model and execute the necessary transmits. The torque fault is evaluated and compensated inside the torque sharing function. The adapting TSF is compensates for the torque fault with receiving the phase because it is the minimal flux rate connecting variation. Finally, the jellyfish search technique is accepted to determine the optimal control parameters. The proposed strategies are done in MATLAB and its performance is contrasted with different existing strategies. According to the simulation result, the proposed strategy‐based accuracy is 94.2% at 50 iteration and 80% at 100th iteration which is higher than the existing methods. From this analyses, it proved that the proposed technique gives superior performance to existing one.

Fuzzy Super-Twisting Sliding Mode Controller for Switched Reluctance Wind Power Generator in Low-Voltage DC Microgrid Applications

There is limited research focused on achieving optimal torque control performance of Switched Reluctance Generators (SRGs). The majority of existing studies tend to favor voltage or power control strategies. However, a significant drawback of SRGs is their susceptibility to high torque ripple. In power generation systems, torque ripple implicates fluctuations in the generated power of the generator. Moreover, high torque ripple can lead to mechanical vibrations and noise in the powertrain, impacting the overall system performance. In this paper, a Torque Sharing Function (TSF) with Indirect Instantaneous Torque Control (IITC) for SRG applied to Wind Energy Conversion Systems (WECS) is proposed to minimize torque ripple. The proposed method adjusts the shared reference torque function between the phases based on instantaneous torque, rather than the existing TSF methods formulated with a mathematical expression. Additionally, this paper introduces an innovative speed control scheme for SRG drive using a Fuzzy Super-Twisting Sliding Mode Command (FSTSMC) method. Notably robust against parameter uncertainties and payload disturbances, the proposed scheme ensures finite-time convergence even in the presence of external disturbances, while effectively reducing chattering. To assess the effectiveness of the proposed methods, comprehensive comparisons are made with traditional control techniques, including Proportional–Integral (PI), Integral Sliding Mode Control (ISMC), and Super-Twisting Sliding Mode Control (STSMC). The simulation results, obtained using MATLAB®/SIMULINK® under various speeds and mechanical torque conditions, demonstrate the superior performance and robustness of the proposed approaches. This study presents a thorough experimental analysis of a 250 W four-phase 8/6 SRG. The generator was connected to a DC resistive load, and the analysis focuses on assessing its performance and operational characteristics across different rotational speeds. The primary objective is to validate and confirm the efficacy of the SRG under varying conditions.

Advanced Torque Sharing Function Strategy With Sliding Mode Control for Switched Reluctance Motors

In this paper, an improved torque sharing function control (TSF) using sliding mode control (SMC) is proposed for switched reluctance motor (SRM). First, as for TSF control strategy, due to low increase rate of inductance in the commutation interval, the latter phase is compensated with torque error for torque ripple reduction. Second, SMC is applied in design of speed controller and disturbance observer for better comprehensive performance. Regarding speed controller, the novel sliding mode reaching law is proposed to further suppress the torque ripple and accelerate approaching speed. With respect to the disturbance observer, a modified super-twisting algorithm is employed to enhance the anti-interference ability. Finally, the simulation and experiments are carried out, which verify that the proposed control method behaves better in aspects of the dynamic response and torque ripple suppression, and anti-interference ability.

Model Predictive Torque Control of Switched Reluctance Machines with Torque Sharing Function and PWM Control Signals Based on Linear Polynomial Fitting

Model Predictive Torque Control of Switched Reluctance Machines with Torque Sharing Function and PWM Control Signals Based on Linear Polynomial Fitting

Indirect Instantaneous Torque Control for Switched Reluctance Motor Based on Improved Torque Sharing Function

Indirect Instantaneous Torque Control for Switched Reluctance Motor Based on Improved Torque Sharing Function

Optimal Torque Sharing Function Control for Switched Reluctance Motors Based on Active Disturbance Rejection Controller

In this article, an optimal torque sharing function (TSF) control method incorporated with improved linear active disturbance rejection control (LADRC) and modified coyote optimization algorithm (MCOA) is introduced and applied in switched reluctance motors (SRMs). First, the piecewise TSF is employed to reduce the torque ripple, which exhibits little effects on the rate of current change and the current peak value. The improved linear extended state observer with the variable gain in speed controller using LADRC is designed to guarantee better antidisturbance ability and torque ripple reduction simultaneously. Then, the MCOA is introduced to automatically tune the parameters including the turn- <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">on</small> angle, conduction angle, and coefficients for better comprehensive performances. Finally, comparisons among the conventional TSF with LADRC, the piecewise TSF with LADRC, and the proposed TSF with improved LADRC are conducted both in the simulations and experiments. The results indicate that the proposed method behaves best in aspects of torque ripple suppression and anti-interference ability among the three methods.

Online Current Spikes Suppression Strategy Research of Switched Reluctance Motors Based on Hybrid Torque Sharing Function

In this paper, an online compensation predictive control method based on hybrid torque sharing function (HTSF) is proposed to reduce current spikes in the torque sharing control of switched reluctance motor (SRM). First, predictive control is introduced to the torque sharing function (TSF) and a new cost function is designed with Laplace multiplier method by predicting the current and torque of the next cycle of SRM. Then the optimal current control amount is carried out. Second, the ratio of the torque error to the desired torque and its derivative are compensated online to the current phase at the beginning of the commutation overlap period to accurately track the torque, and the torque distribution is optimized by a HTSF at the end of the phase change to further reduce the current spikes and suppress the torque ripple. Finally, the experiment on 8/6 four‐phase SRM is achieved to verify the feasibility and effectiveness of the proposed control strategy, and the results show that the current spikes and the torque ripple are reduced by 25% and 14.5% respectively. Therefore, compared with traditional TSF control, this method can effectively reduce the SRM torque ripple and excessive current spikes. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

Instantaneous torque error compensation based online torque sharing function for Switched reluctance Machines

An online torque sharing function (TSF) with instantaneous torque error compensation method for switched reluctance machines is proposed to maintain a minimized ripple operation. The proposed method adjusts the shared torque between the phases based on instantaneous torque error different than the existing TSF methods formulated with a mathematical expression. The objective of this approach is to benefit from the outgoing phase torque as it has slow current dynamics due to the high inductance. Also, the incoming phase is turned on as soon as it can generate positive torque. During this process, the total torque is estimated instantaneously using lookup tables, and a correction current is calculated and injected into the incoming phase reference current as the inductance is low and current dynamics are fast. This way, the torque ripple is reduced for a wide speed range. Compared to the conventional linear, sinusoidal, exponential, and cubic TSFs, better torque ripple performance is obtained.

Influence of the Rotor Geometry on Efficiency and Torque Ripple of Switched Reluctance Motor Controlled by Optimized Torque Sharing Functions

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.

Improved indirect instantaneous torque control based torque sharing function approach of SRM drives in EVs using hybrid technique

This manuscript proposes an improved indirect instantaneous torque control (IITC) based torque sharing function (TSF) method of switched reluctance motor (SRM) drives in electric vehicles (EVs) using a hybrid system. The proposed hybrid techniques are joint performance of both Reptile Search Algorithm (RSA) and Honey Badger Algorithm (HBA), hence it is named as Enhanced RSA (ERSA) method. Here, an IITC method of SRMs for EVs is utilized. It achieves the requirements of the vehicle, like minimum torque ripple, improved speed range, high effectiveness, and maximal torque per ampere (MTPA). To precisely specify the switched reluctance motor and its magnetic features are measured by the proposed method. The modified Torque sharing function compensates the torque error along with incoming phase, which contains the minimal rate of change of flux linkage. Finally, the ERSA method is implemented to define the best control parameters. Then, the proposed ERSA system is performed on the MATLAB platform and the performance is compared to different existing systems. The MSE for case 1 and case 2 using proposed system attains 0.01093 and 0.01095. The voltage deviation for case 1 and case 2 using proposed system reaches 5 and 5. The power factor for case 1 and case 2 reaches a value of 50 and 40 using the proposed system.

An Online Torque Sharing Function Method Involving Current Dynamics for Switched Reluctance Motor Drives

This article proposes an online torque sharing function (TSF) method for torque ripple reduction in switched reluctance machines (SRMs). The proposed TSF takes the current dynamics and induced electromotive force (EMF) into account by establishing a new online current profile generation technique. First, a primary phase current reference derived from the torque reference is applied to the SRM. Then, the decaying phase current after the turn-off angle is sampled and it is used to update the current reference. A new online optimization strategy is performed to shape the current reference during the operation of the machine. Due to the proposed current profile generation technique, the optimization process is decoupled to independently minimize the torque ripple by optimizing the turn-on angle and minimizing copper losses by optimizing the turn-off angle. Compared to the conventional TSFs and existing optimization-based TSFs, the proposed TSF achieves accurate torque control, improved torque–speed capability, reduced torque ripple, and better current tracking performance. Simulations and experiments are performed on a three-phase 12/8 SRM under various operating conditions to validate the proposed online TSF method.

Quantification of Noise Benefits in Torque Control Strategies of SRM Drives

Torque Sharing Function (TSF) based control is a well-established method for the reduction of torque ripple in Switched Reluctance Motor (SRM) drives. There have not been much investigations carried out in the literature on the noise benefits of TSF based control and on the impact of the commutation angles of TSF definition on the acoustic noise in SRM. In this paper, the advantages of TSF based control in noise reduction of SRM are investigated in detail. A new TSF profile, which is characterized by a slower variation of the radial force and hence reduced vibration on the stator, is introduced. Further, the effects of variation of turn-on and overlap angles of TSF definition on the vibration and torque ripple in a closed loop control are analysed in detail, using simulations and experimental methods. Based on the analysis and experimental studies, a new strategy for the selection of turn-on and overlap angles of TSF definition has been developed for achieving reduced acoustic noise, in addition to low torque ripple. Simulation and experimental results are presented to demonstrate the effectiveness of the proposed TSF definition and angle selection strategy.

Torque Ripple Reduction for a 12/8 Switched Reluctance Motor Based on a Novel Sliding Mode Control Strategy

A hybrid control strategy based on torque sharing function (TSF) and sliding mode control is proposed for switched reluctance motor (SRM), which can obtain smaller torque ripple and higher dynamic response speed. The conventional cosine-type TSF strategy can effectively reduce the torque ripple of the SRM at low speed, but there will be insufficient torque tracking at high speed. In order to improve the torque ripple suppression capability of TSF at high speed, a new sliding mode controller (NSMC) is designed, which can achieve smaller torque ripple and faster system response speed and improve system robustness. The final experimental results confirm the effectiveness of the control method.

Torque Ripple Suppression of Switched Reluctance Motor with Reference Torque Online Correction

High torque ripple dramatically affects the switched reluctance motor (SRM) application. To reduce the torque ripple, a reference torque neural network (RTNN) is proposed to adjust the reference torque online. Firstly, the RTNN is built on the torque sharing function (TSF) method. Furthermore, the RTNN is designed as a single-input and -output network. As the periodic relationship between the torque ripple and the rotor angle, the rotor angle constitutes the central node parameter of the implicit function in RTNN. Therefore, one-step adjustment of the RTNN can perform well at restraining reference torque. Lastly, the torque error is used to adjust the parameters of RTNN to reduce the torque ripple. In the MATLAB environment, through the simulation comparison with fuzzy torque and PD current compensation method, the effectiveness of RTNN at torque ripple suppression is proven with different loads and speeds.

An Improved Hybrid Control Scheme of a Switched Reluctance Motor for Torque Ripple Reduction

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.