Torque ripple reduction for Direct Torque Control of voltage source inverter fed Induction motor drive Rajasekaran.P1, V.Jawahar Senthilkumar2. 1 Research Scholar, Jawaharlal Nehru Technological University Hyderabad-85 and Associate Professor,Department of EEE, Aarupadai Veedu Institute of Technology,Paiyanoor-603104. 2Asst.Professor, Department of ECE, College of Engineering, Guindy, Anna University, Chennai-25 Corresponding Author e-mail: kingsekaran@gmail.com ABSTRACT: This paper presents analysis of recently used direct torque control (DTC) techniques for voltage source inverter-fed induction motors to overcome torque ripple reduction in motor steady state operation. In classical Direct Torque Control (DTC), the torque and stator …show more content…
One of the approaches is to increase the number of voltage vectors applied in a sampling period, using some sorts of pulse width modulation (PWM). Among the various techniques, a simpler one is to use two voltage vectors: a nonzero one, applied for a portion of the sampling period, and the null vector for the rest. The duty ratio must be calculated each sample period, and by varying it between its intense values, it is possible to apply more voltage levels to the motor, according to the desired torque variation. In [5], an analytical online algorithm calculates the optimum duty ratio each sampling period, by using a torque ripple minimization condition, which is based on ripple equations. However, this algorithm requires high computational effort and additional motor parameters to be known. In [6] the duty ratio value is provided by a new fuzzy logic module, whose inputs are the stator flux position, the electromagnetic torque and an input defining the motor operating point, given by the speed and the torque values. This algorithm involves expert knowledge and needs the rotor speed This paper proposes a simple solution for reducing the torque ripple in classical Direct Torque Control, while preserving the good dynamic and structural simplicity of this scheme. The proposed method consists in the modulation of the nonzero voltage vector duration …show more content…
The instantaneous values of the stator flux and torque are calculated from stator variable by using a closed loop estimator [1]. Stator flux and torque can be controlled directly and independently by properly selecting the inverter switching configuration. Figure 1.Basic direct torque control Scheme for AC motor Drives III.CLASSICAL DIRECT TORQUE CONTROL SCHEME In a symmetrical three phase induction machine, the instantaneous electromagnetic torque is proportional to the cross vectorial product of the stator flux linkage space vector and stator current space vector. Te=3/2ps*is (1) - stator flux linkage space vector Is – stator current space vector By considering that s-I s exp(js) (2) s- angle of the stator flux linkage space vector with respect to the direct –axis of the stator reference frame . Is=I Isexp(js) (3) In eqn Te=3/2 p I si I Is I sin(s-s)n (4) =3/2 p I s I I Isi
A divide by 4 ip op employing D ip op is shown next in Figure 4.8. The simulation plot for divide-by-4 (Figure 4.9) is shown Figure 4.8: Cascaded ip ops
These sequences would give us a pseudocount of 1 at each position called the Laplace pseudocount. fA,1 = (3+1)/(10+4) fC,1 = (3+1)/(10+4) fG,1 =
& { 2872(25$\%$)} & { 2499(22$\%$)} & { 5795(26$\%$)} & { 5100(23$\%$)}\\ $N_{\omega\to\pi^0\gamma}^{\circ}$ & { 4487(15$\%$)} & { 3590(12$\%$)} & { 1978(6$\%$)} & { 1721(5$\%$)} & { 5846(9$\%$)} & { 5145(8$\%$)} \\ \hline $BR^{measured}_{\omega\to\pi^0\gamma}$ & \textcolor{red}{ 1.07} & \textcolor{red}{ 0.78} & \textcolor{red}{ 0.52} & \textcolor{red}{ 0.43} & \textcolor{red}{ 0.73} & \textcolor{red}{ 0.61} \\ ($\%$) & \textcolor{red}{ (15$\%$)} & \textcolor{red}{ (11$\%$)} & \textcolor{red}{ (6$\%$)} & \textcolor{red}{ (5$\%$)} & \textcolor{red}{ (9$\%$)} & \textcolor{red}{ (8$\%$)} \\ \hline & \multicolumn{6}{c|} {\bf $\sigma_{dedp-sys}=\sigma^{av}_{rms}\times(1-\sigma_{fit-sys}^{rel})$ } \\ \hline \end{tabular} \caption[The standard deviation $\sigma^{av}_{rms}$ in ${N_{\omega\to\pi^0\gamma}}^{rec}$, ${N_{\omega\to\pi^0\gamma}}^{\circ}$ and $BR^{measured}_{\omega\to\pi^0\gamma}$ for the different energy-momentum conservation constraint are presented] { The standard deviation $\sigma^{av}_{rms}$ in ${N_{\omega\to\pi^0\gamma}}^{rec}$ and $BR^{measured}_{\omega\to\pi^0\gamma}$ for the different energy-momentum conservation
N=Number of turns in the coil I = Current in the coil …………………………………………………………….Equation 9.3 Where U=
V= m_c gL_c cos〖θ+m_T gL_T cosα 〗 (4) The generalized coordinates are defined as , q〖=( x ∅ α θ )〗^T (5)
The speed of DC motor can be controlled by the variable supply voltage or by changing the strength of current. Small DC motors are used in toys, tools, and appliances. Larger DC motors are used in propulsion of electric vehicles, in drives for steel rolling mills, elevator
onvergence of Adaptive Noise Canceller '); legend( 'Measured Signal ', 'Error Signal '); subplot(3,3,6); plot(t,e, 'r '); hold on; plot(t,fhb, 'b '); axis([Time-4 Time -0.5 0.5]); grid on; xlabel( 'Time [sec] '); ylabel( 'Voltage [mV] '); title( 'Steady-State Error Signal '); legend( 'Calc Fetus ', 'Ref Fetus ECG '); filt_e = filter(Hd,e); subplot(3,3,7); plot(t,fhb, 'r '); hold on; plot(t,filt_e, 'b '); axis([Time-4 Time -0.5 0.5]); grid on; xlabel( 'Time [sec] '); ylabel( 'Voltage [mV] '); title( 'Filtered signal '); legend( 'Ref Fetus ', 'Filtered Fetus '); thresh = 4*mean(abs(filt_e))*ones(size(filt_e)); peak_e = (filt_e >= thresh); edge_e = (diff([0; peak_e]) >0); subplot(3,3,8); plot(t,filt_e, 'c '); hold on; plot(t,thresh, 'r '); plot(t,peak_e, 'b '); xlabel( 'Time [sec] '); ylabel( 'Voltage [mV] '); title( 'Peak detection '); legend( 'Filtered fetus ', 'Dyna thresh ', 'Peak marker ', 'Location ', 'SouthEast '); axis([Time-4 Time -0.5 0.5]); subplot(3,3,9); plot(t,filt_e, 'r '); hold on; plot(t,edge_e, 'b '); plot(0,0, 'w '); fetus_calc = round((60/length(edge_e(16001:end))*Fs) * sum(edge_e(16001:end))); fetus_bpm = [ 'Fetus Heart Rate = ' mat2str(fetus_calc)]; xlabel( 'Time [sec] '); ylabel( 'Voltage [mV] '); title( 'Reconstructed fetus
-2 -1 -0.50 0.5 1 2 0.5 x 0 0.1 0.1 0.2 0.3 0.2 0.1 5 5 12/9 KING FAHD UNIVERSITY OF PETROLEUM AND MINERALS ACHB/CE EE315: PROBABILISTIC METHODS IN ELECTRICAL ENGINEERING b) M g ( x) x 2 0 x 0 x 2 0 0 x ( a ) b For ( ) ( ) ( ) [ ( )] ( ) ( ) For ( ) ( ) ( ) ( ) ( ) ( ) ( ) { ( ) ( ) ( ) { ∫ ( ) ( ) ∫ ( ) ( ) ( ) 4 4 4 4 13/9 KING FAHD UNIVERSITY OF PETROLEUM AND MINERALS ACHB/CE EE315: PROBABILISTIC METHODS IN ELECTRICAL ENGINEERING 2 G (x) forb x 0 x 0.5 0 x 1 (b) 2 0 x 2 0 x 4 c) Binomial, Poisson (discrete RV), Uniform, Exponential, Rayleigh (Continuous RV) 2 2 2 2 2 14/9 KING FAHD UNIVERSITY OF PETROLEUM AND MINERALS ACHB/CE EE315: PROBABILISTIC METHODS IN ELECTRICAL ENGINEERING QUESTION 3 a) [ ] ∫ ( ) ∫ ∫ ∫ ∫ ([ ] ∫ ) ( [ ] ) =
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As we go through this paper i want to prove how
4. Calculate the difference amidst theoretical, simulated and practical values. 5. Consult Hishan to probe in details about problematic components. 6.
Introduction This assessment will examine Dasani’s life from the bifocal of spiritual, cultural, physical aspect of her environment. Also in this assessment, I will use the theories we have learned about to evaluate further how they apply to Dasani’s situation. Summary of Control Theory Control Theory teaches us that we as individual’s face issues when trying to control what goes on in our physical environment.