- 1 -Niš, Serbia, November 11 th - 14 th, 2010 Projekt ISSNBS DAAD Deutscher Akademischer Austausch Dienst German Academic Exchange Service NEW HYBRID.

- 1 -Niš, Serbia, November 11th- 14th, 2010

Projekt „ISSNBS“DAADDeutscher Akademischer Austausch DienstGerman Academic Exchange Service

NEW HYBRID MODEL FOR EFFICIENCY NEW HYBRID MODEL FOR EFFICIENCY OPTIMIZATIONOPTIMIZATION OF INDUCTION MOTOR DRIVES OF INDUCTION MOTOR DRIVES

Presented by: Branko BlanuPresented by: Branko Blanušša a University of Banja Luka, Faculty of Electrical Engineering

E-mail: [email protected]

Branko D. Blanuša, Petar R. Matić, Branko L.Dokić



Main goal:

Define optimal control strategy for a given operating conditions so the drive operates with minimal energy consumption.



Content

1. Introduction

2. Power loss modelling

3. Hybrid model for efficiency optimization

4. Simulation results

5. Conclusion



Results of applied algorithms for efficiency optimization highly depends from the size of drive (Fig.1) and operating conditions, especially load torque and speed (Fig. 2)

Fig. 1 Rated motor efficiences for ABB motors (catalog data) and typical converter efficiency.



Fig 2. Measured standard motor efficiences with both rated flux and efficiency optimized control at rated mechanical speed (2.2 kW rated power).



Important conclusions

1. It is possible to minimize power losses by variation of magnetizing flux in the machine, so the balance between cooper and iron losses are obtained.

2. Best results in efficiency optimization of induction motor drives can be achieved for a light loads.



According to the literture, there are three strategies dealingwith the problem of efficiency optimization of the inductionmotor drive

1. Simple State Control - SSC ,2. Loss Model Control - LMC and 3. Search Control- SC.



The first strategy (SSC) is based on the control of one of the variables in the drive. This strategy is simple, but gives good results only for a narrow set of operation conditions. Also, it is sensitive to parameter changes in the drive due to temperature changes and magnetic circuit saturation.

O p tim a ls ta te

re fe ren ceC o n tro l C o n v e rte r

f

V I.M .

C o n tro l s ta tev a riab le

(m easu red o r e s tim a ted )

e

s

f r

Fig. 3. Control diagram for the simple state efficiency optimization strategy.



For LMC methods, a power loss model is used for optimal drive control. These algorithms are fast because the optimal control is calculated directly from the loss model. But, power loss modeling and calculation of the optimal operating conditions can be very complex. This strategy is also sensitive to parameter variations in the drive.

C o n v erte r

f

V I .M .

e

s

f r,refE ffic ien cy

o p tim iza tio nco n tro l

f rD riv e lo ssm o d e l

Fig. 4. Block diagram for the model based control strategy.



In the search strategy, the on-line procedure for efficiency optimization is carried out. The optimization variable, stator or rotor flux, increases or decreases step by step until the measured input power is at a minimum. This strategy has an important advantage over others: it is insensitive to parameter changes.

C o n tro l C o n v e rte r

f

V I.M .

e

s

frP o w er lo ssca lcu la tio n

f r,re f

P -in P o u tP =

P

r

r,m in

Fig. 5. Block diagram of search control strategy.



Hybrid methods

Hybrid method combines good characteristics of two optimization strategies Search Control and Loss model control.

During transient process LMC is used, so fast flux changes and good dynamic performances are kept. SC is used for efficiency optimization in a steady state of drive. Hybrid method obtains fast convergence to optimal flux and negligible sensitivity to parameter changes.



Power loss modelling

FeCumot

invmottot

PPP

PPP

The overall power loss in electrical drive consists of converter loss and motor losses, while motor power loss can be divided in copper and iron loss:

Overall flux-dependent losses are usually given by:

222qdinvsinvinv iiRiRP



Loss model of drive is developed in d-q rotational system in such way that that rotor side variables do not depend on leakage inductances while the effect of leakage inductances is incorporated into other variables.

jwrLm’im

Rs Ls’(p+jwe)

Lm’(p+jwe)Rm

R’r

if

Vs

ir

im

is

Fig.6. Space vector model of induction motor drive.

,

'

''

''

mr

remme

m

mm

rfms

mmessesss

iR

jpLijp

R

Li

iiii

iLjpiLjpRiv

www

ww



+

-

Vsd

isd imdLs’weisq Rs

Lm’

+

-

Ls’weisd

wrLm’imd

isq

Rs

RmRr’

if

Vsq

ir

Fig. 7. Steady state model of IM in a rotor flux oriented reference frame, d-axis equivalent circuit, q-axis equivalent circuit.

mdr

mslmd

m

merqfsq

mdsd

mdmrmdmslsdsesqssq

sqsesdssd

iR

Li

R

Liii

ii

iLiLiLiRv

iLiRv

'

''

'''

'

ww

www

w



,22sqbsdatot iRiRP

Total power losses

'2' / rmmrsinva RRLRRR w

'

'

rm

rmsinvb RR

RRRRR

,

2

3

2

3 '2

sqsdekv

sqsdmsqsdr

mem

iik

iiPLiiL

LPT

.2/3 'mekv PLk

22

22

sdekv

embsdatot

ik

TRiRP

42

2*

32

2

022

ekv

em

a

bsdLMC

sdekv

embsda

sd

tot

k

T

R

Ri

ik

TRiR

i

P



Search controller

S C A L IN GFA C T O RC A L C U L AT IO N

F U Z Z Y IN F E R E N C E

z -1z -1z -1

isq*

w r

P in(k )

Pin (k -1 )

Pin(k )Pin(p .u )

P Ig g

id s* (p .u ) id s*

id s* (p .u )L

sdi *

Fig.8. SC efficiency optimization controller



Fig. 10. Overall proposed block diagram of efficiency optimization controller in IMD.



Simulation results

0 2 4 6 8 10 12 14 16-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

time (s)

speed reference

load torque

Fig. 11. Load torque and speed reference.



0 2 4 6 8 10 12 14 16-1

-0.5

0

0.5

1

1.5

2

time (s)

magnetization curremt p.u.

mechanical speed p.u.

torque reference p.u

Fig.12. Magnetization current, mechanical speed and electromagnetic torque.



4.4 4.6 4.8 5 5.2 5.4 5.6 5.8 6 6.2 6.4-1

-0.5

0

0.5

1

1.5

time (s)

magnetization curremt p.u.

mechanical speed p.u.

torque reference p.u

Fig.13. Magnetization current, mechanical speed and electromagnetic torque.



0 2 4 6 8 10 12 14 160

20

40

60

80

100

120

140

160

180

time (s)

Pow

er lo

ss (

W)

hybrid method

nominal flux

Fig.14. Graph of power loss for nominal flux and applied hybrid method.



0 2 4 6 8 10 12 14 160

20

40

60

80

100

120

140

160

180

time (s)

Pow

er lo

ss (

W)

hybrid method

LMC method

Fig.15. Graph of power loss for LMC method and hybrid method.



4.5 5 5.5 6 6.5 7

142.5

143

143.5

144

144.5

time (s)

Pow

er lo

ss (

W)

hybrid method

LMC method

Fig.16. Graph of power loss for LMC method and hybrid method.



Conclusion

If load torque has a value close to nominal or higher, magnetizing flux is also nominal regardless of whether an algorithm for efficiency optimization is applied or not. For a light load hybrid method for efficiency optimization gives significiant power loss reduction (figs. 14,15 and 16). Also, it shows good dynamic performances (figs. 12 and 13) and negligible sensitivity to parameter changes.



Thank you

- 1 -Niš, Serbia, November 11 th - 14 th, 2010 Projekt ISSNBS DAAD Deutscher Akademischer Austausch Dienst German Academic Exchange Service NEW HYBRID.

Documents

motor power loss

optimal drive control

loss model control lmc

optimal control strategy

model based control

overall power loss

doki slide

conclusion slide