2014 Texas Instruments Motor Control Training Series. -V th. Dave Wilson

Transcription

1 204 Texas Instruments Motor Control Training Series V th

2 Speed Sensorless FOC P Commanded Rotor Speed Commanded i d = 0 Commanded i q (torque) P I P V d V q Reverse ClarkePark Transform θ d V a V b V c PMSM TI Dave s Control Center Rotor Speed I I i d i q Forward ClarkePark Transform i a i b i c Phase C Current Calculation Observer θ d θ d Shaft position sensors are VERY expensive ($,500 in some cases). Many applications cannot afford the cost of a shaft sensor.

3 Model Based Filtering Noise Process Measurement Error feedback Mathematical Model of Process Estimate

4 Tracking Filters y n yn yn yn yn yˆ( n) yˆ( n ) y n y n ^ y correction y ^ correction β α yn errorn y n Z Z y n Integrator Integrator y n Better tracking is obtained when α and β are high Better filtering is obtained when α and β are low

5 The Tracking Filter Unmasked! The tracking filter is revealed to be a simple 2 nd order IIR filter as shown below. Accumulator X(n) Y(n) Delay Delay X(n) 2 Y(n) Delay Y(n)

6 Cascaded Representation This form of the filter reveals the derivatives of the tracked variable. β α Measured Position Error Z Z Integrator Integrator Estimated Position Estimated Velocity Estimated Acceleration

7 Parameter Estimation with Observers By providing an additional feedforward input, the tracking filter can make better output estimates. It then takes the form of an OBSERVER. Can be designed to have zero (or near zero) estimation lag. β α Source: Motion Controller Employs DSP Technology, Robert van der Kruk and John Scannell, Phillips Centre for Manufacturing Technology, PCIM September, 988 Model of H(z) Integrator Integrator Observers are used to observe a quantity which is difficult to measure by mathematically modeling the system. Observers literally recreate the desired signal mathematically (great noise decoupling). The guess is corrected by comparison with an observable signal.

8 Servo Performance with Velocity Directly from Encoder vs. Observer

9 Sensorless Sinusoidal PMSM Control L s Rs Lls Lm applied voltage k E syn Assuming no saliency, stationary frame equations are: v v R s i i L s d dt i i k E syn sin e cos e Rotor with surfacemount magnets Nonsalient design (magnetically round)) Back EMF component

10 Stationary Frame Back EMF Observer V in R s Ls i emf V in Back EMF Observer ^ R s Low Pass Filter i ^ i PI emf emf V in V in t emf t i t e R s t t emf R s Low Pass Filter i

11 BackEMF Observer Performance Rs 0.46Ω Ls.365 mh 20 VAC 60 Hz One of three phases of Baldor PMSM motor i emf??? Back EMF Observer V in ^ R s Low Pass Filter i ^ i PI EMF estimate 20 V 20V 00V 80V 60V V(bemf) V(voltage_input) Observer simulation Observer sampling frequency = 0 KHz 40V 20V 0V 20V 40V BackEMF Estimated BackEMF 60V 80V 00V 20 V 20V 0ms 5ms 0ms 5ms 20ms 25ms 0 25ms

12 Stationary Frame State Observer for a NonSalient Machine v v Dave s Motor Control Center Texas Instruments i sls R s Back EMF α ( v, emf,, i ) P I R s sl s i K sin PMSM Motor (2phase representation) K cos s L P F s n n sls R s Back EMF β P I K cos sin K 2

13 Sliding Mode EMF Observer I α V α /L s ^ I α I α error SGN Kslide Z α R s /L s Z α LPF EMF α A Position and Velocity Sensorless Control of Brushless DC Motors Using an Adaptive Sliding Observer, Takeshi Furuashi, Somboon Sangwongwanich, Shigeru Okuma, 990 IEEE Proceedings, /90/0088, pp

14 Low Speed Saliency Tracking Observer High Frequency Current Measurement i q VmZ 2 Z Z hf d Demodulator L P F High Frequency Voltage Injection (about 500 Hz) q sin 2 err P I regulator results in steady state value servoing to zero P I Z q Z d s n L P F n θ err Disadvantages: 2Z Only works on motors with a strong saliency signal. Saliency graph shifts when the motor is loaded. Works at low speeds, but falls apart at high speeds.

15 ACIM Sensorless Control Note: Still in stationary frame qds Vqds Rs Iqds dt Stationary Frame Synchronous Frame Source: ZeroSpeed Tacholess I.M. Torque Control: Simply a Matter of Stator Voltage Integration, by K.D.Hurst, T.G.Habetler, G. Griva F. Profumo, IEEE paper, 997

16 ACIM Stator Flux Referenced FOC Torque 3 4 P es i es ds qs λqds Vqds Rs Iqds dt (easily measured)! However, Daxis stator current no longer independently controls flux (i.e., the axes are now COUPLED).

17 DTC: A Peek under the Hood Vector Selector Flux Error Hysteretic Band increase decrease Texas Instruments Dave s Motor Control Center Torque Error Hysteretic Band increase decrease SVM T em p Im 2 conj s is s Commanded Torque Torque Calculator Commanded Flux s s Stator Flux Calculator s s s v s Rs i s dt