Sampled-data flux estimation in induction machines

Zell, C.; Medvedev, Alexander

doi:10.1109/cca.1996.559086

Cited by 4 publications

(5 citation statements)

References 4 publications

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“…However, the coefficients for the two models are different. For a fair comparison, the timeinvariant coefficients in the high-SF flux observer (17) have been used as base values and placed in the center in Fig. 3.…”

Section: Flux Observer Comparisonmentioning

confidence: 99%

“…The solution is developed in the synchronous reference frame and evaluated on a V /F induction motor drive by simulation. The solutions provided in [17] require no assumption of constant voltage over each discrete step but need input voltage known in advance (e.g., sinusoidal voltage). Thus, it is not suitable for fast dynamic applications fed by a pulsewidth-modulation (PWM) voltage source.…”

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confidence: 99%

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A Low-Switching-Frequency Flux Observer and Torque Model of Deadbeat–Direct Torque and Flux Control on Induction Machine Drives

Wang

Tobayashi

Lorenz

2015

IEEE Trans. on Ind. Applicat.

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This paper presents a digital implementation of deadbeat-direct torque and flux control (DB-DTFC) for induction machines at low switching frequencies (SFs). For high SFs, existing discrete-time flux observers and Volt-second-based inverse torque models used for DB-DTFC achieve acceptable flux estimation accuracy and fast torque response. However, the flux estimate is less accurate when the SF is reduced and the DB-DTFC performance degrades. This paper develops a more suitable flux observer and Volt-second-based inverse torque model that minimizes flux estimation error and improves torque control for DB-DTFC. Simulation and experimental results are provided to evaluate the performance of the proposed observer and torque model at very low SFs. Consequently, digital implementation of low-SF DB-DTFC on high-power induction machines is feasible. Index Terms-Deadbeat-direct torque and flux control (DB-DTFC), flux observer, low-switching-frequency (SF) operation.NOMENCLATURE ( ) s Stationary reference frame. ( ) r Rotor reference frame. ( ∧ ) Estimation quantity. ( ) * Reference quantity. ( · ) Time derivative operator. ( ) s Quantity on the stator side. ( ) r Quantity on the rotor side. ( ) qdx Complex vector quantity. (k) Quantity at the kth sampling time. (s) Quantity in the Laplace domain. s Laplace operator. v qds Stator voltage complex vector. i qds Stator current complex vector. i qdr Rotor current complex vector. λ qds Stator flux linkage complex vector. i qdr Rotor flux linkage complex vector. R s Stator resistance. R r Rotor resistance. L m Magnetizing inductance. L ls Stator leakage inductance. L lr Rotor leakage inductance. σ = 1 − (L m L m /L s L r ) Total leakage factor. τ r = R r /L r Rotor time constant. ω r Electrical angular velocity of rotor. ω br = (R r /L r ) − jω r Rotor break frequency. T e Electromagnetic torque. T s Sampling time.

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Section: Flux Observer Comparisonmentioning

confidence: 99%

mentioning

confidence: 99%

A Low-Switching-Frequency Flux Observer and Torque Model of Deadbeat–Direct Torque and Flux Control on Induction Machine Drives

Wang

Tobayashi

Lorenz

2015

IEEE Trans. on Ind. Applicat.

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“…By assuming the change of rotor speed over one switching period is negligible, the Laplace transforms are applied to (3) and (8), which results in the Laplace transformed differential equations, as shown in (9) and (10), for stator flux and current respectively. The initial conditions should also be included.…”

Section: B the Full Order Flux Observermentioning

confidence: 99%

“…solution for each switching interval. Discrete time flux observers have been developed in [7][8][9], using discretization of continuous state equations. With more mathematical focus and less physical insight, they are not straightforward for implementation and estimation accuracy evaluations.…”

Section: Introductionmentioning

confidence: 99%

Deadbeat-direct torque and flux control on low switching frequency induction machine drives using the enhanced flux observer and torque model

Wang

Tobayashi

Lorenz

2013

2013 IEEE Energy Conversion Congress and Exposition

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This paper presents a digital implementation of deadbeat-direct torque and flux control (DB-DTFC) for induction machines at low switching frequencies. For high switching frequencies, existing discrete time flux observers and Volt-sec.-based inverse torque models used for DB-DTFC achieve acceptable flux estimation accuracy and fast torque response. However, the flux estimate is less accurate when switching frequency is reduced and DB-DTFC performance degrades. This paper develops a more suitable flux observer and Volt-sec.-based inverse torque model that minimizes flux estimation error and improves torque control for DB-DTFC. Simulation and experimental results are provided to evaluate the performance of the proposed observer and torque model at very low switching frequencies. Consequently, digital implementation of low switching frequency DB-DTFC on high power induction machines is feasible.

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“…In the augmented system the new stateū c with initial value e θ is equivalent to the original input signalū c . The augmented model may be used in an observer to estimate the input signal instead of measuring it and thus eliminating redundant sensors [9]. The augmented model iṡ…”

Section: Transition Matrix and Current Envelopementioning

confidence: 99%

Estimation of induction machine parameters at start-up using current envelope

Stocks

Medvedev

Conference Record of the 2002 IEEE Industry Applications Conference. 37th IAS Annual Meeting (Cat. No.02CH37344)

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A new method for estimation of electrical parameters in Induction Machines (IM) is presented. Evaluation of the parameters is performed by considering the envelope of the stator currents under motor start-up, thus avoiding the high sampling rates necessary for logging the actual currents. The use of start-up data makes the method attractive in the IM control and monitoring applications where the parameter estimates can be used for adjusting the control law or evaluating the motor condition. It is also demonstrated that the use of a simplified decoupled dynamic model of the IM in the estimation algorithm does not significantly worsen the quality of the obtained parameter estimates. Both simulations and experiments show fast convergence of the suggested algorithm. 1163 0-7803-7420-7/02/$17.00 © 2002 IEEE

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Sampled-data flux estimation in induction machines

Cited by 4 publications

References 4 publications

A Low-Switching-Frequency Flux Observer and Torque Model of Deadbeat–Direct Torque and Flux Control on Induction Machine Drives

A Low-Switching-Frequency Flux Observer and Torque Model of Deadbeat–Direct Torque and Flux Control on Induction Machine Drives

Deadbeat-direct torque and flux control on low switching frequency induction machine drives using the enhanced flux observer and torque model

Estimation of induction machine parameters at start-up using current envelope

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