SENSORLESS FIELD ORIENTED CONTROL OF BRUSHLESS ...

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CHAPTER 6 - Sensorless Techniques It is evident that control of a brushless PM motor requires knowledge of the shaft position. For six-step 120° commutation, only six pulses per electrical revolution are required (hence three Hall-effect sensors are often used); for 180° commutation, position feedback of higher resolution is required (such as that provided by an encoder or resolver). This chapter discusses techniques that can be used to replace a physical shaft position sensor by indirectly determining the shaft position. Hence, in BPMS motor control, sensorless refers to the lack of a position sensor; voltage and/or current sensors are still required. First, a brief overview of techniques is presented. Then the general structure of a sensorless FOC system is described and an open-loop estimation scheme is presented. Then the closed-loop topology (a Luenberger observer) is discussed further. Overview of Techniques As with BPMS motor types, PWM methods, and direct torque control schemes, there are a very large number of sensorless techniques reported in the literature. As before, there are many different approaches to classifying the sensorless methods. In this report the top-level distinction is between the techniques applicable when using a 120° inverter and those applicable when using either a 120° or a 180° inverter. In the 120° inverter there is a 60° period per half-cycle when both switches in a phase leg are <strong>OF</strong>F. This gives a chance at monitoring the terminal voltage to detect the zero-crossing of the bEMF. These techniques are usually based on voltage measurement but not always. There are a number of ways to accomplish the task in practice. There are also a large number of practical issues that must be dealt with to ensure successful operation; the issues differ between methods and not all methods are applicable to all motors. For a given motor and drive, use of a sensorless control scheme may limit operation to an operating region that is only a subset of the capability of the same motor and drive under sensored control. All 120° voltage measurement techniques fail at low speed, some may fail with increasing speed or load, and none can achievable appreciable commutation advance unless a neutral connection is used in sensing. As discussed in Appendix 238
D, some of the 120° methods are applicable when using a 180° inverter, but these require a neutral connection which is not available on standard motors. In contrast to the 120° inverter, a 180° inverter drives each phase high or low at all times thus there is no possibility of using the direct bEMF sensing techniques applicable with 120° inverters. Instead, an estimator of some sort must be used to determine rotor position. Many of these methods are applicable to 120° inverters as well (but as mentioned, the converse is not true). The estimation methods could be divided into two categories. The first consists of those that estimate variables (such as rotor-stator flux linkage, bEMF) based on principle (first-order) effects. The second consists of those that estimate variables based on second-order or parasitic effects. These include tracking inductance variation due to saliency (a second-order effect) or due to saturation (which is normally a parasitic effect but it can be intentionally exploited) [87, pp.167-176]. The latter methods are specialized to particular machine topologies; many require a salient machine but some are applicable to rotors with surface-mounted magnets. In addition, some of them exploit features that require analysis deeper than that presented in this report, including a detailed treatment of the leakage flux path and the consideration of the effects of slotting and tooth saturation. Some techniques require very accurate values of machine parameters. Finally, a variety of techniques require a high-frequency signal to be injected into the stator voltage commands to excite the variance they track (this requires a deeper understanding of the inverter) and the chosen frequency and magnitude can be critical to performance [168], [169], [170], [171]. Several methods require special techniques to remove ambiguity in position sensing. For these reasons, only the estimators of “normal” principle quantities will be discussed further. (As with all other areas of BPMS motor control, the sensorless literature is flooded with techniques that use artificial intelligence [87], [60], [61]. As before, many of these warrant their own field of study and are not mentioned here.) Reviews of sensorless operation of AC motors have been published ([172], [167], [166]) as well as general articles reviewing AC motor control which include sections summarizing sensorless operation ([93], [102]). Many references address AC motors as a whole, thus care is required in discerning which general group of motors and inverters a technique is applicable to (induction or BPMS, nonsalient BPMS or salient BPMS, 120° or 180° inverters); this is very difficult to do when techniques for induction and BPMS motors are reviewed simultaneously. 239
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SENSORLESS FIELD ORIENTED CONTROL O
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Table of Contents List of Figures..
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CHAPTER 5 - Field Oriented Control
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List of Figures Figure 2.1 - Radial
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Figure 3.29 - Arbitrary space vecto
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Figure 4.44 - ZS components of some
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Figure C.13 - Single-turn full-pitc
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List of Symbols Symbol Meaning Unit
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Abbreviations ACIM AC induction mot
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Superscripts * commanded value ref
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CHAPTER 1 - Introduction Historical
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vector theory to model a machine, w
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publications and magazines, and Int
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elationship between SVM and other P
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CHAPTER 2 - Fundamentals of Electri
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Preliminaries In reading the litera
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Taxonomy of Motors There is any num
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characteristics (the DC load curren
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torque component, sturdily construc
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Figure 2.7 - Cross sections of some
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draw the line between the solenoida
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These texts generally attribute the
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N B A B Y x(t) (2.6) The induc
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extended to the rotational case lat
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present analysis). When this is tru
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Figure 2.16 - Components of total f
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As aforementioned a spatial analysi
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clear the meaning, but the reader i
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Figure 2.20 - Elementary brushless
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called the per-phase torque functio
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Expressing bEMF in terms of the bEM
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Equation (2.44) is the component of
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d R( r) ke( r) kt( r) sin( r) (2.
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General Electromechanical Models Th
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Figure 2.28 - Phase-variable simula
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Trapezoidal and Sinusoidal BPMS Mot
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Figure 2.29 - Back-EMF and drive cu
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Figure 2.31 - Back-EMF and drive cu
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3 KT Ke 2 (sinusoidal) K 2 K (tra
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control scheme must keep sinusoidal
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with misconceptions. The primary is
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Part I - Sinusoidal BPMS Motors wit
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grounded-neutral wye or delta conne
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N e f A ( ) i 2 N e f B ( ) i 2
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Figure 3.7 - Developed view at zero
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Figure 3.9 - Developed view showing
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Although Equations (3.6) or (3.7) a
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direction. The contributions always
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sinusoidal electrical variable will
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Figure 3.14 - Cross section of two
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3 N e (3.6): f ( , t) I p cos(
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In the previous chapter the per-pha
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peak value is represented as an upp
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Figure 3.21 - Time relationship bet
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another and thus could be placed in
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more widely understood theory (such
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other methods, although it has clos
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The SV as a Vector The first facet
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j0 j0 j0 aˆ 1 0 1 bˆ j e e e
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j j ee 1 cos( ) (3.45) 2 3 j t x
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Notice that the amplitude of the MM
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Figure 3.27 - Equivalent MMF produc
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Ne 1 jj f , t i e i * e 2 2
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distribution that is cosinusoidal i
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3 Ne j t f Ie p 2 2 . This
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j set θ to anything. Taking the re
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epresent any physically-distributed
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lumped-parameter model in this repo
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x kCx (3.75) abc The set of varia
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phase variable axes; three axes in
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The component MMFs act away from th
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common choice is to force the power
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As an example, find the SV that cor
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the same magnitude, the projection
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Figure 3.32 - Arbitrary SV referenc
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universal and the choice of convent
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stator’s perspective and at R fr
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The potential discrepancy (p.108) w
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x cos( r) sin( r) xd x sin(
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It must be emphasized that we have
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in relative time like an oscillogra
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Part III - SV Theory Applied to Sin
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In Equation (3.135) Z has elements
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to use SV theory. It may be helpful
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Figure 3.42 - Coupling between d- a
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R R d R R v Ri Li j Li dt s
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current does not influence the valu
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d v Ri L i e dt d v Ri L i e
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Figure 3.47 - Simulation diagram fo
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e je ), and (2) it was demonstrate
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Overview of Voltage Source Inverter
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In addition to measuring voltages w
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then there would be periods during
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Figure 4.9 - Gating and POLE voltag
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Figure 4.11 - Ideal voltage wavefor
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inverter is called sine-triangle co
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and it offers the fastest dynamic r
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Figure 4.18 - Fundamental gain and
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In the literature this is called th
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voltage will be below (above) the b
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Figure 4.24 - Instantaneous phase-A
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Figure 4.26 - Base SVs showing the
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Figure 4.27 - Transformed voltage w
Page 207 and 208: also correspond to six-step squarew
Page 209 and 210: was fed to the SVM inverter as a SV
Page 211 and 212: Figure 4.31 - Temporal limit of inv
Page 213 and 214: Figure 4.34 - SVM overmodulation re
Page 215 and 216: Checking sextant s 23 again for thi
Page 217 and 218: SVM Implementation The block diagra
Page 219 and 220: has been made of using THI in the S
Page 221 and 222: different triplen signal would be i
Page 223 and 224: Similarly, when the modulation inde
Page 225 and 226: Summary and Conclusion The two-leve
Page 227 and 228: CHAPTER 5 - Field Oriented Control
Page 229 and 230: torque production; this is called d
Page 231 and 232: Figure 5.3 - Torque control of sinu
Page 233 and 234: obviously a change in perspective.
Page 235 and 236: Figure 5.9 - Comparison of referenc
Page 237 and 238: variables to the stationary referen
Page 239 and 240: Figure 5.13 - Torque control of sin
Page 241 and 242: To analyze a salient machine one mu
Page 243 and 244: Figure 5.16 - Torque functions: (a)
Page 245 and 246: Figure 5.19 - Buried permanent magn
Page 247 and 248: Figure 5.21 - Flux weakening in the
Page 249 and 250: appears that this is very much rela
Page 251 and 252: Stationary and Synchronous Regulato
Page 253 and 254: stationary regulator had. For compl
Page 255 and 256: This coupling can be mitigated by m
Page 257: educes to two independent circuits,
Page 261 and 262: d d v Ri Ls i R dt dt The r
Page 263 and 264: section a state-space model for the
Page 265 and 266: Figure 6.6 - Full state feedback (o
Page 267 and 268: State-Space Model of BPMS Motor A s
Page 269 and 270: Figure 6.9 - FOC block diagram. The
Page 271 and 272: loop). A second way to implement th
Page 273 and 274: knowing the rotor position from ini
Page 275 and 276: [11] E. Clarke, Circuit analysis of
Page 277 and 278: Control Systems, Linear Analysis [4
Page 279 and 280: [77] J.M.D. Murphy, F.G. Turnbull,
Page 281 and 282: Machine Modeling, Analysis [103] J.
Page 283 and 284: THI, SVM, SPWM [127] J.A. Houldswor
Page 285 and 286: Wisconsin-Madison. [Online]. Availa
Page 287 and 288: Angle Tracking [175] D. Morgan, “
Page 289 and 290: Appendix A - Elementary Electromagn
Page 291 and 292: L i (A.8) S SS S SR S SS SR (A.9
Page 293 and 294: First the self-flux-linkage of an i
Page 295 and 296: vAN R iA LM iA eA d v R i
Page 297 and 298: Figure B.3 - One-half of the flux p
Page 299 and 300: Equations (B.27) and (B.28) are for
Page 301 and 302: Fundamental Relationships Figure C.
Page 303 and 304: Figure C.3 - Sinusoidal winding den
Page 305 and 306: manufactured compared to the steppe
Page 307 and 308: phase winding of Figure C.4 will ha
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Distributed N Fp i 2 (C.5) Figu
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alanced machine only odd harmonics
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sinusoidal windings with a sinusoid
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0, and since the direction of inte
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That the rotor-stator flux linkage
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Figure C.17 - Summary of rotor-stat
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Figure C.19 - Amplitudes of harmoni
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triangle with an amplitude whose nu
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Returning to Figure C.18 it is clea
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torque will describe the torque pro
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However, Equation (D.2) is incorrec
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the same order as the PS set (arran
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Implications of the ZS Component Th
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Figure D.6 - Neutral voltage of loa
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3v 3e 3v v v v v v v 3v AM BM CM A
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components of source voltage sum to
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Equation (D.25) and instantaneous q
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If a ZS component could possibly be
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xA X1cos( t) X3cos(3 t) X5cos(5 t)
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Figure D.11 - 3-D base vectors of 1
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the Clarke transform is used. Howev
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Appendix E - Park Transforms This a
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Appendix F - Useful Mathematical Re
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335
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