Correction: Improved torque ripple minimization of SynRM with optimal multi-frequency harmonic current tracking

This study discusses the evolution of the local minimum to global minimum torque ripples of the direct torque control of induction motor drives. This study will show that the previous minimum torque ripple design is not the global minimum but a local minimum root-mean-square (RMS) torque ripple. To show this, the study finds the optimal initial torque error, which makes the global minimum torque ripple, and then the related global minimum RMS torque ripple. Moreover, after finding the optimal initial torque error and its related global minimum RMS torque ripple, this study derives the evolution of the initial torque ripple error, under the local minimum RMS torque ripple control strategy. Furthermore, this study also proves that under the local minimum RMS torque ripple control strategy, the local minimum torque ripple will converge to the global minimum value.

An inductance model-based sensorless control strategy with torque ripple and acoustic noise minimization for switched reluctance machines is proposed. In order to simultaneously reduce the torque ripple and acoustic noise, a specific-shaped current waveform that is needed and obtained from a torque-sharing function (TSF) is used in this paper. With the inductance model-based sensorless control strategy and the specific-shaped current modulation, the any rotor position within the entire electrical angle can be calculated by the bisection algorithm so that a specific current profiling can be obtained and therefore torque ripple and acoustic noise minimization can be achieved. The traditional trapezoid-shaped current modulation is compared with the specific current profiling in term of torque ripple. A 2 kW 12/8 SRM sensorless drive is modelled using the PSIM software. The simulated results indicate that the new sensorless control strategy is effective in reducing torque ripple. A hardware prototype of 2 kW converter with TMS320F28335 is also constructed and tested. The experimental results indicate that the new sensorless control strategy is effective in rotor position estimation.

Due to the existence of cogging torque, magnet flux harmonics and inverter dead time, permanent magnet synchronous motor (PMSM) has torque ripple during operation, which limits its application in high-precision situations. Stator current optimization is an easy-to-apply and accurate torque ripple suppression approach. However, existing methods fail to consider the effect of magenet flux phase angle on optimal current calculation. In this paper, a torque ripple minimization method considering harmonic magnet flux phase is presented, which uses torque waveform of an electric angular period as the optimization object. By deducing the electromagnetic torque model considering harmonic magnet flux, the torque is expressed as a dense sequence. Based on this, the objective function including torque ripple and losses minimization is constructed and optimized by genetic algorithm (GA) to obtain the optimal harmonic current. Experiment results show that the proposed approach can calculate the optimal harmonic current accurately and suppress the torque ripple effectively.

This paper proposed an open-circuit fault-tolerant control method for dual three-phase permanent magnet synchronous motor (DTPPMSM), which takes the back electromotive force (back EMF) harmonics into consideration and can achieve the minimum torque ripple. From the perspective of machine ontology and electromagnetic power, this paper analyzed the influence of back EMF harmonics on torque ripple. On this basis, by adjusting the phase of currents, specific order torque ripple components which can offset each other can be generated by the back EMF fundamental wave and harmonics, thus suppressing the specific order torque ripple of the whole motor. Furthermore, not limited to specific order torque ripple, the method can also be used to obtain the minimum overall torque ripple under open-circuit operation. Finite element analysis (FEA) and prototype experiment are employed to verify the proposed method.

Hydraulic motors generate torque ripple, periodic fluctuations in output torque, adversely affecting performance for many applications. Traditional efforts to mitigate torque ripple have mainly addressed kinematic aspects by altering structural motor parameters, leaving dynamic torque ripple, influenced by fluid compressibility, less explored. This study introduces a novel approach to minimize torque ripple across different operating conditions in a Variable Displacement Linkage Motor (VDLM) by optimizing piston trajectory. Torque ripple was controlled by creating a custom piston trajectory defined by control points of a B-spline and tuning motor valve timing. The research employed kinematic and cylinder models to simulate the motion of the cam-linkage mechanism of the VDLM and the pressure dynamics in the piston chambers. The torque output and ripple of the motor were predicted through a simulation, and the motion of the pistons was optimized to minimize ripple. The VDLM torque ripple was reduced below 5% for a targeted corner condition and remained under 12% for other operating conditions, including fractional displacements of the motor. The optimized trajectory was compared to a baseline sinusoidal path, showing a simultaneous reduction in torque ripple at different operating conditions. Furthermore, the simulation results show good agreement when compared to experimental data obtained from a VDLM prototype constructed with an optimal piston trajectory. These results highlight the effectiveness of piston trajectory optimization in improving hydraulic motor performance, offering substantial benefits for applications requiring smooth output torque.

In this paper, a single inductor-single sensor based photovoltaic optimizer with an optimal current point tracking strategy is proposed. With only one inductor, one sensor and one MPPT unit, this optimizer can not only make all submodules output their individual maximum powers, but also utilize the least components compared with current solutions, greatly reducing the size and cost of photovoltaic optimizer and increasing the integration level. The effectiveness of the proposed solution is verified by both simulation and experiments.

PurposeThe paper aims to provide an adaptive neural network controller for permanent magnet synchronous motor (PMSM) under direct torque control (DTC) algorithm to minimize the torque ripple and EMI noise.Design/methodology/approachThe design methodology is based on vector control used for electrical machines. MATLAB simulations supported with experimental study under C++ are used.FindingsThe simulated and experimental results show that considerable torque ripple as well as current ripple and EMI noise reduction can be achieved by utilizing adaptive neural switching algorithm to fire the inverter supplying the PMSM.Research limitations/implicationsThis research is limited to PMSM, however the research can be extended to include other AC motors as well. In addition, the following points can be studied: the effects of harmonics in control signals on the torque ripple can be analyzed; the actual mathematical relation between the torque and flux ripple can be studied to set the flux and torque bands width in reasonable value; different neural network algorithms can be applied to the system to solve the similar problems.Practical implicationsBased on existing DTC control system, it is only required to change the software switching algorithm, to provide smooth torque, given that the switching frequency of the inverter module is more than or equal to 15 MHz and the system is supplied with timers. In addition a relatively higher DC voltage may be required to achieve higher speed compared with the traditional DTC.Originality/valueIn this paper, the stator flux position, and errors due to deviations from reference values of the torque and stator flux are used to select two active vectors while at the same time the absolute value of the torque error and the stator flux position are used neural network structure to adapt the switching of the inverter in order to control the applied average voltage level in such a way as to minimize the torque ripple, so instead of fixed time table structure, a neural network controller is used to calculate the switching time for the selected vectors and no PI controller is used as the case in the traditional space vector modulation. This work is directed to motor drive system designers who seek highly smooth torque performance with EMI noise reduction.

This paper gives a concise review on mathematical modeling of brushless direct current (BLDC) motor, the challenges on BLDC motor, torque ripple reduction techniques, condition for minimum commutation torque ripple, and different control strategies for torque ripple reduction in sensor and sensorless BLDC motor. This review also discusses the comparison between sensor and sensorless BLDC drives, merits of sensorless BLDC drive, and outcomes of different torque ripple reduction techniques. It also gives an idea to select better control strategy for specific BLDC drive applications. The best-suited control strategies have the advantages such as high efficiency, minimum torque ripple over the entire speed range, less switching loss, simple modulation scheme, improvement in DC voltage utilization, smooth and noiseless operation, and regulation in the speed of BLDC motor. The MATLAB simulation tool is used to verify the results of few topologies.KeywordsSensor BLDCSensorless BLDCTorque rippleCuk converterLine–line flux linkage

This paper presents an adaptive filter based torque ripple minimization (TRM) of a fuzzy logic controller (FLC) for speed control of an interior permanent magnet synchronous motor (BPMSM) drive. A simple and effective first order digital infinite impulse response (HR) filter is utilized to reduce the torque ripple introduced by the FLC. The gain of the filter is adapted online based on the magnitude of the torque ripple. The optimal position of the filter in the complete drive is also determined for effective TRM. The various sources of torque pulsations in a practical electric machine drive are described. The main cause of the torque ripple in an FLC is also explained A simulation model for closed vector control of an FLC based IPMSM drive incorporating the proposed TRM technique is developed in Matlab/Simulink. The effectiveness of the proposed technique is investigated extensively in simulation at different operating conditions. It is found that the performance of the FLC based IPMSM drive is improved significantly with the proposed TRM technique.

Direct torque control (DTC) schemes can produce quick and robust responses, but heir major problem is the high torque and flux ripple, especially when operation conditions result in low speed. This paper proposes a new control strategy. On the basis of conventional direct torque control, a flux and torque ripple minimum controller is introduced in the strategy in order to decrease flux and torque ripple. Simulation results justify the validity of the proposed method to reduce the motor torque and flux ripple

The balanced commutator method of computing the reference currents for current tracking feedback is presented. For a given switch reluctance (SR) motor, the commutator reduces the peaks and the rate of change of the reference currents. This allows accurate current tracking, and therefore minimum torque ripple, over a wider range of operating speeds. Reference current waveshapes for two different SR motors, and the resulting torque ripples, are compared

This paper presents the application of the cuckoo search (CS) algorithm in attempts to the minimization of the commutation torque ripple in the brushless DC motor (BLDC). The optimization algorithm was created based on the cuckoo’s reproductive behavior. The lumped-parameters mathematical model of the BLDC motor was developed. The values of self-inductances, mutual inductances, and back-electromotive force waveforms applied in the mathematical model were calculated by the use of the finite element method. The optimization algorithm was developed in Python 3.8. The CS algorithm was coupled with the static penalty function. During the optimization process, the shape of the voltage supplying the stator windings was determined to minimize the commutation torque ripple. Selected results of computer simulation are presented and discussed.

Among all control methods for induction motor drives, Direct Torque Control (DTC) seems to be particularly interesting being independent of machine rotor parameters and requiring no speed or position sensors. The DTC scheme is characterized by the absence of PI regulators, coordinate transformations, current regulators and PWM signals generators. In spite of its simplicity, DTC allows a good torque control in steady state and transient operating conditions to be obtained. However, the presence of hysterics controllers for flux and torque could determine torque and current ripple and variable switching frequency operation for the voltage source inverter. This paper is aimed to analyze DTC principles, and the problems related to its implementation, especially the torque ripple and the possible improvements to reduce this torque ripple by using a proposed fuzzy based duty cycle controller. The effectiveness of the duty ratio method was verified by simulation using Matlab/Simulink software package. The results are compared with that of the traditional DTC models.

Among all control methods for induction motor drives, Direct Torque Control (DTC) seems to be particularly interesting being independent of machine rotor parameters and requiring no speed or position sensors. The DTC scheme is characterized by the absence of PI regulators, coordinate transformations, current regulators and PWM signals generators. In spite of its simplicity, DTC allows a good torque control in steady state and transient operating conditions to be obtained. However, the presence of hysterics controllers for flux and torque could determine torque and current ripple and variable switching frequency operation for the voltage source inverter. This paper is aimed to analyze DTC principles, and the problems related to its implementation, especially the torque ripple and the possible improvements to reduce this torque ripple by using a proposed fuzzy based duty cycle controller. The effectiveness of the duty ratio method was verified by simulation using Matlab/Simulink software package. The results are compared with that of the traditional DTC models.

Torque ripple modeling and minimization for interior permanent magnet synchronous machines (IPMSMs) requires accurate information of the inductances, which vary nonlinearly due to magnetic saturation. However, existing approaches fail to consider the magnetic saturation and, thus, their performance are limited under different load conditions. Therefore, this paper improves the torque ripple model by considering magnetic saturation, and employs this model for the optimal current design to improve the performance of torque ripple minimization for IPMSMs under different load conditions. At first, numerical studies are performed to analyze and understand how magnetic saturation affects the torque ripples in IPMSMs. Then, a novel torque ripple model for IPMSMs is developed, in which the inductance term is replaced by exploring the machine electrical model. This improved torque ripple model is computationally efficient and it can provide fast and accurate torque ripple prediction. Based on this model, a genetic algorithm (GA)-based optimal stator current design approach is proposed to minimize the torque ripple in IPMSMs. The proposed GA-based approach can adaptively optimize the stator current under different load conditions, which can guarantee the robust performance of torque ripple minimization under different saturation levels. The proposed approach is validated through an experimental test on a laboratory IPMSM drive system.