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STABILITY ISSUES IN PEAK LIMITING CURRENT MODE CONTROLLED BUCK - - PowerPoint PPT Presentation
STABILITY ISSUES IN PEAK LIMITING CURRENT MODE CONTROLLED BUCK - - PowerPoint PPT Presentation
STABILITY ISSUES IN PEAK LIMITING CURRENT MODE CONTROLLED BUCK CONVERTER Marija Glii, Predrag Pejovi Introduction peak limiting current mode control . . . known since 1978, C. W. Deisch, Simple switching control method changes
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the circuit . . . constant current load!
+ − S D L iS vIN iC C iL iD iOUT vOUT + − vX
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the waveform, . . . DCM assumed!
iL Im d TS TS t iL = fS L 2 I2
m
vIN vOUT 1 vIN − vOUT
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decoupling, switching cell . . . also assumed, implicitly!
+ − + − S D L iS vIN iL iD vOUT vX used to draw iL, to compute iL . . . vOUT assumed constant over TS . . . implicitly!
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decoupling, averaged model . . .
+ − + − iS vIN iC C iL iD iOUT vOUT + − vL
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decoupling, averaged model simplified . . .
iC C iL iOUT vOUT + − C d vOUT d t = iL − iOUT and iL is given three slides above . . . and our story begins here . . .
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Averaging
C d vOUT d t = fS L 2 I2
m
vIN vOUT 1 vIN − vOUT − iOUT
- verline notation consistent?
d vOUT d t = 0 ⇒ fixed points two fixed points . . . (overline notation dropped) vOUT 1, 2 = vIN 2 ±
- v2
IN
4 − fS L I2
m vIN
2 iOUT and it is not a good practice to have two when you need only
- ne . . .
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an example . . .
vIN = 12 V, fS = 100 kHz, L = 36 µH, Im = 0.5 A, iOUT = 0.2 A, C = 200 µF iL = 0.45 A 12 V vOUT 1 12 V − vOUT iL = iOUT = 0.2 A fixed points: vOUT = 3 V 9 V
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fixed points . . .
1 2 3 4 5 6 7 8 9 10 11 12 vOUT [V] 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 iL, iOUT [A]
Im = 0.5 A
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detour: normalization
mX vX vIN jY fS L iY vIN τ t TS = fS t result: L d iL d t = vL ⇒ d jL d τ = mL special: vIN ⇒ 1, vOUT ⇒ M, Im ⇒ Jm, iOUT ⇒ jOUT
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fixed points, normalized
Vbase = 12 V, Ibase = 10 3 A Jm = 0.15, jOUT = 0.06 M1, 2 = 1 2 ±
- 1
4 − J2
m
2 jOUT fixed ponts: M = 1/4 3/4
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fixed points . . . normalized!
1/4 1/2 3/4 1 M 3/100 6/100 9/100 12/100 15/100 jL, jOUT
Jm = 15/100
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Linearization
C d vOUT d t = fS L 2 I2
m
vIN vOUT 1 vIN − vOUT s C vOUT = gIN vIN + gOUT vOUT + αm Im − iOUT gIN = ∂ iL ∂ vIN = − fS L I2
M
2 (VIN − VOUT )2 gOUT = ∂ iL ∂ vOUT = fS L I2
M VIN (2 VOUT − VIN)
2 V 2
OUT (VIN − VOUT )2
αm = ∂ iL ∂ Im = fS L IM VIN VOUT (VIN − VOUT )
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transfer functions . . .
- vOUT = HIN
vIN + Hm Im − HOUT iOUT HIN = gIN s C − gOUT Hm = αm s C − gOUT HOUT = 1 s C − gOUT stability: gOUT < 0, ∂ iL ∂ vOUT < 0 . . . previous slide: 2 VOUT − VIN < 0, VOUT < VIN/2
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fixed points, once again . . . what’s going on?
1 2 3 4 5 6 7 8 9 10 11 12 vOUT [V] 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 iL, iOUT [A]
Im = 0.5 A
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Discrete Time Model
+ − + − S D L iS vIN iL iD vOUT vX
◮ vOUT assumed constant over TS ◮ want to know mapping iL(0) → iL(TS)
. . . knowing Im, vIN, vOUT , fS, L . . . . . . or just Jm and M? (5 → 2)
◮ iL(n) 1 TS
n TS
(n−1) TS iL(t) dt is an auxiliary (but important!)
result
◮ normalization is useful here!!!
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normalization, three cases . . .
◮ S-on, D-off:
d jL dt = 1 − M
◮ S-off, D-on:
d jL dt = −M
◮ S-off, D-off:
d jL dt = 0 But only two parameters, Jm and M! Look for jL(n − 1) → jL(n) and jL(n)!
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three cases, again . . . case 1, no switching interval jL Jm 1 τ jL(0) jL(1)
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three cases, again . . . case 2, continuous conduction interval jL Jm 1 τ jL(0) jL(1) τ1
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three cases, again . . . case 3, discontinuous conduction interval jL Jm 1 τ jL(0) jL(1) = 0 τ1 τ1 + τ2
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analytical . . .
jL(1) (jL(0), M, Jm) = 1 − M + jL(0), if jL(0) < Jm + M − 1 1 1 − M Jm − M − M 1 − M jL(0), if Jm + M − 1 < jL(0) and jL(0) < Jm M + M − 1 0, if Jm M + M − 1 < jL(0) . . . similar for jOUT . . .
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Basins of Attraction
1 2 3 4 5 6 7 8 9 10 11 12 vOUT [V] 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 iL, iOUT [A]
Im = 0.5 A
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trajectory of vOUT . . .
10 20 30 40 50 t [ms] 2 4 6 8 10 12 vOUT [V]
vOUT(0) = 9.1 V vOUT(0) = 8.9 V
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trajectory of iL . . .
10 20 30 40 50 t [ms] 0.10 0.15 0.20 0.25 iL [A]
vOUT(0) = 9.1 V vOUT(0) = 8.9 V
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steady state waveform of iL, . . . “twin peaks”
5 10 15 20 t [µs] −0.1 0.0 0.1 0.2 0.3 0.4 0.5 iL [A]
vOUT = 10.123190 V; Im = 0.5 A; IOUT = 0.2 A
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actually happens . . .
5 10 15 20 25 30 35 40 45 50 t [µs] −0.4 −0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 iL [A]
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Limit Cycles
◮ the problem begins when the converter would enter CCM
for D > 1/2
◮ supposed limit cycle is unstable! ◮ but the converter operates in a stable limit cycle, regardless
- ur assumptions . . .
◮ . . . it happened to be period-2 DCM . . . ◮ . . . and here the mess starts . . .
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supposed . . .
1 2 3 4 5 6 7 8 9 10 11 12 vOUT [V] 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 iL, iOUT [A]
Im = 0.5 A
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actual . . .
1 2 3 4 5 6 7 8 9 10 11 12 vOUT [V] 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 iL, iOUT [A]
Im = 0.5 A
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and we have it analytical . . . in the paper! (boring)
10.0 10.5 11.0 11.5 12.0 vOUT [V] 0.0 0.1 0.2 0.3 0.4 0.5 iL [A]
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iterate over Jm . . . not in the paper!
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iterate over Jm . . . not in the paper!
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important: operating mode chart . . . not in the paper!
1/2 1 M 1/4 1/2 1 Jm period-1 CCM period-1 DCM period-n DCM period-n CCM
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iterate over Jm . . . not in the paper!
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iterate over Jm . . . not in the paper!
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DCM, period number, n = 1, not in the paper!
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DCM, period number, n = 2, not in the paper!
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DCM, period number, n = 3, not in the paper!
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DCM, period number, n = 4, not in the paper!
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DCM, period number, n = 5, not in the paper!
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DCM, period number, n = 6, not in the paper!
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DCM, period number, n = 7, not in the paper!
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DCM, period number, n = 8, not in the paper!
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DCM, period number, n = 9, not in the paper!
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DCM, period number, n = 10, not in the paper!
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period number, in color, . . . not in the paper!
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stability . . . not in the paper!
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Conclusions, 1
◮ buck converter analyzed, PLCMC applied ◮ decoupling (in reversed order):
- 1. “averaged” model, linearized later on . . .
- 2. “discrete time” model
◮ stability:
- 1. stability of the averaged model
- 2. limit cycle stability (stability of the discrete time model)
◮ limit cycle instability:
- 1. occurs in would-be CCM for D > 1/2
- 2. results in sensitive small-signal parameters
- 3. affects averaged model stability!
◮ analytical techniques, models, normalization . . .
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Conclusions, 2
◮ in the paper, case study for Jm = 0.15 ◮ analytical techniques developed, discrete time model ◮ detailed study of the discrete time model ◮ identification of modes ◮ pretty good analytical description . . . ◮ analysis of stability
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Conclusions, 3
◮ in this presentation, generalized over Jm, the remaining
degree of freedom, along with M, completeness achieved
◮ important:
- 1. occurrence of period-n modes when assumed period-1 CCM
has unstable limit cycle, for D > 1/2
- 2. both period-n CCM and period-n DCM exist
◮ charts:
- 1. chart of modes
- 2. chart of periodicity (chart of n)
- 3. chart of stability
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