phase - Power Electronics

While clutch and gearbox assemblies in washing
machines have been replaced with belt-driven
induction motors with tachometer feedback,
digital-control algorithms will enable direct drive
from sensorless permanent-magnet motors.
Washing controls have used power inverters
to control motor speeds for years. Variable-speed
control enables a signifi cant
simplifi cation of the mechanical system by
replacing a clutch and gearbox with a belt
drive. Washers in North American commonly use a threephase
induction motor with tachometer feedback. The drive
typically uses slip torque control during the washing cycle
and fi eld weakening for high-speed spinning. Compared
to drives that do not provide fi eld weakening, this simple
mechanical system enables a higher spin speed that extracts
more water from the clothes, which reduces the energy the
dryer consumes.
To gain further energy savings, appliance engineers are
now introducing laundry algorithms that minimize the hot
water that the washing cycle consumes. However, the new
algorithms require a higher dynamic response from the drive
train so manufacturers seek to replace the belt-drive system
with direct-drive permanent-magnet (PM) motors.
Compared to a three-phase induction motor, a direct-
By Aengus Murray, Director iMOTION Products,
Energy Savings Product Group, International
Rectifi er, El Segundo, Calif.
drive PM motor uses a larger number of motor poles to
generate higher torque at lower speeds for the same power
input. The ratio of the drum speed to the motor electrical
frequency remains almost the same, but instead of stepping
down the motor speed using, for example, a 10-to-1 pulley
ratio, increasing the motor-pole count by a factor of 10
achieves the same effect.
Induction motors require a relatively large number of
slots per pole and a small air gap that makes it diffi cult to
build motors with high pole counts. PM motors provide
much more construction fl exibility and are the best choice
for the direct drive. Fig. 1 shows a direct-drive motor with
an external rotor that connects directly to the washer drum.
Concentrated stator windings make it possible to design the
motor with a “pancake” construction that easily fi ts into the
washing machine’s available space.
Though PM ac motors provide advantages over induction
motors for washer applications, one critical issue to
solve is rotor position sensing. Transformer action generates
the rotor fi eld in the induction motor, so the fi eld is always
Power Electronics Technology June 2006 14
www.powerelectronics.com

Fig. 1. The compact profi le of the stator windings (left) and rotor (right) permit a “pancake” form factor well suited for washing-machine
applications.
Field
weakening
Target
velocity Velocity
controller
Rotor velocity ()
Torque
demand
synchronous to the stator current. However, the motor-drive
circuit must measure the rotor position in the PM machine
to synchronize the stator current with the rotor fi eld. Given
the rotor position, it is possible to drive the PM ac motor
effi ciently because the drive circuit can align the stator current
to the optimum angle relative to the rotor fi eld.
In the direct-drive motor shown in Fig. 1, Hall Effect
sensors detect the rotor-magnet position. However, designs
that eliminate these sensors alleviate the reliability issues
that result from mounting the sensor electronics assembly
within the motor housing.
One popular sensorless algorithm measures the rotorfl
ux position based on the stator winding’s back EMF. This
algorithm is suitable when driving the PM motor in six-step
mode with rectangular winding currents. The algorithm
is easy to implement but produces high torque ripple because
of delays in current commutation due to the winding
inductance.
One of the major drawbacks of this scheme is that the
torque ripple causes unacceptably high acoustic-noise levels
I D *
I D
I Q *
I Q
I D
controller
I Q
controller
Rotating
reference
frame
stator
voltages
V D
V Q
I D
I Q
Rotating
reference frame
stator currents
e j
Forward
rotation
in the direct-drive motor, as the rotor acts like a loud speaker.
Another important problem with the back-EMF-sensing
algorithm is that it does not allow high-speed fi eld weakening,
which is required for high-speed spinning.
Sensorless Control
A sensorless control algorithm can use motor-windingcurrent
measurements to indirectly determine the rotor-fl ux
position. This algorithm allows for sinusoidal currents to
drive the motor. These sinusoidal waveforms produce low
torque ripple, which minimizes the acoustic noise. The
control method also easily provides for fi eld-weakening
operation for high-speed spinning.
Typically, sensorless control algorithms determine the
rotor-fl ux position based on the winding’s back EMF—an
indirect measurement that derives from the motor circuit
model. The advantage of this approach is that it is applicable
when sinusoidal-current waveforms drive the motor, which
produce smooth, glitch-free torque.
The control diagram in Fig. 2 describes the field-
www.powerelectronics.com 15
Power Electronics Technology June 2006
V
V
Rotor angle ()
e -j
Reverse
rotation
I
I
2 - to - 3
Clark
Rotor-flux
estimation
algorithm
3 - to - 2
Clark -1
Applied
stator ac
voltages
V U
V V
V W
I U
I V
I W
Measured
stator ac
currents
Permanent magnet
synchronous motor
Fig. 2. The permanent magnet synchronous motor (PMSM) fi eld-oriented-control algorithm transforms the stator’s three-phase ac currents
into a rotating reference frame that tracks the rotor’s position.
U
V
W

V
I
V
I
WASHER DRIVES
R x cos( R ) + L S x I = (V – I x R S )dt
R x sin( R ) + L S x I = (V – I x R S )dt
Flux
estimator
R x sin( R )
R x cos( R )
oriented-control (FOC) algorithm for the permanent magnet
synchronous motor (PMSM). A feature of this algorithm
is that it transforms the three-phase ac currents in the stator
windings into a rotating reference frame where they appear as
two dc-current components representing the stator current’s
torque and fl ux components.
The reference transformations occur in two stages. The
fi rst stage calculates the equivalent stator currents in a twophase
machine model. The second performs a vector rotation
to calculate the stator currents’ effect in a reference frame
synchronous with the rotor shaft.
The two-phase stator-current model forms the basis for
the rotor-fl ux-estimation algorithm, which is defi ned as:
v R i L di α d
v α = R S ×
i α
α + L S
S +
+ ( R R )
dt dt
θ ( ) θ
R R θ ( R R ) θ ( − Ψ R ×
× cos( R ) )
)
diβ
d
v = R × i + L × + − Ψ × sin( θ )
β S β S R R
dt
e -j
Estimated
angle
dt
( ),
Rotor
velocity
()
Rotor
angle
()
where R is the rotor fl ux.
As shown in Fig. 3, the inputs are the stator voltages
(v α and v β ) that the drive system provides and the statorcurrent
measurements (i α and i β ). Calculations for the winding
voltage’s back-EMF components use the stator-current
measurements as input. Integration of the back-EMF components
produces two rotor-fl ux components that are sine
and cosine functions of the rotor angle.
The second stage in the rotor-angle estimator is a phaselocked
loop that forces the sine and cosine of the angle
estimate to track the sine and cosine rotor-fl ux functions,
PI
Phase-locked loop
Fig. 3. Two-phase stator-current models form the basis of the rotor-fl uxestimation
algorithm.
AC
input
EMI
filter
Communication
Isolation
System
I/O
Power
supply
1 s
M
C
U
8-bit
300-Vdc bus
Digital control IC
RAM
M
C
E
16-bit
PWM
ADC
respectively. This approach has the advantage of delivering
both rotor-angle and velocity estimates, and is independent
of the rotor-fl ux magnitude.
The controller performs the current-control loop calculations
within the rotating reference frame and compensates
for the winding resistance, inductance and back-EMF magnitude.
The input to the torque current loop comes from
the outer velocity-control loop that compensates for the
mechanical load’s dynamics. The fi eld-weakening controller
sets the fl ux-current loop input to zero at low speeds to
maximize the output torque.
At the motor’s base speed, the back EMF due to the PM
fl ux reaches the dc bus voltage. At this speed, drives without
fi eld weakening would be unable to further increase the motor
speed because, with the back EMF equal to the dc bus
voltage, there is no excess voltage available with which to
drive additional current.
However, the fi eld-weakening controller can provide a
negative input to buck a fraction of the PM fl ux that couples
to the winding. This allows the fi eld-weakening controller to
set motor speeds beyond the base speed. The advantage of
the sensorless FOC implementation is that it delivers smooth
torque with good dynamic control—without the use of any
position sensors.
Algorithm Implementation
The hardware platform for the washing-machine controller
consists of a digital control IC and an integrated power
module, as appears in the application circuit in Fig. 4. An
embedded 16-bit motion-control engine (MCE) implements
the sensorless control algorithm that performs all of the
control calculations using hardware macro blocks.
There is an independent 8-bit microcontroller for the
application software that communicates with the MCE
using shared memory. The MCE connects directly to the
motor-control peripherals that interface to the inverter
power module that drives the motor.
The PWM unit calculates the duty-cycle timing of the
power transistors to control the voltage applied to each
phase of the motor while the analog-to-digital converter
(ADC) samples the motor currents fl owing in the dc-link
shunt resistor.
DC bus
voltage
Integrated power module
Fig. 4. The main electronic components of the washing-machine controller are the digital control IC and the integrated
power module.
The high-voltage
IC (HVIC),
gate-drive circuit
interfaces
b e t ween t h e
3.3-V logic-level
outputs of the
digital control
IC and the power
transistors.
The HVIC also
includes inverter-protection
features such
Power Electronics Technology June 2006 16
www.powerelectronics.com
HVIC
gate
drive
PM
motor

WASHER DRIVES
as overcurrent
shutdown that
also use feedbackinformation
from the
dc-link shunt.
The digital
implementation
of the FOC
algorithm that
appears in Fig.
5 has the same
basic structure
as that in
Fig. 2, with an
outer velocity
loop and two
inner current
loops for controlling
the
motor torque
Target
speed
Closed-loop speed control Sensorless field-oriented control
Ramp
Velocity loop Limit
Torque loop
–
PI
IQ +
–
PI
and fl ux. The other control functions include the rotor-angle
estimation, fi eld weakening for high-speed operation and
the phase-current reconstruction block. Practical imple-
CKE-PET mentations ad need 5-06 additional 5/10/06 functions 1:03 PM such Page as those 1
that the
startup-sequencer and fault-detection blocks provide.
+
VD VQ ID REF
Field
weakening
REF
+
= 0 below
base speed
Estimated speed
Startup
sequencer
–
Each control-loop compensator has a proportional-plusintegral
(PI) block with a limiting function at its output. The
output of the velocity loop, which is the reference input to
the torque loop, is limited so that the controller does not
drive too much current into the motor. The controller limits
the current-loop outputs to a voltage range that the power
inverter can deliver. An output from each limit block halts
the integration upon reaching the limit, to prevent unwanted
integrator windup while the controller is saturated.
The vector-rotation block (e j ) transforms the currentloop
outputs to ac quantities in the stator-reference frame.
The two-phase stator-reference voltages directly feed the
space-vector PWM block that controls the voltages to the
motor since the modulation algorithm has an embedded
two- to three-phase transformation.
The most diffi cult part of the rotor-angle-estimator
implementation is in the low-speed range. The fl ux-estimator
algorithm’s integrators have a low frequency cutoff
to avoid saturation due to dc offsets. At start up, the back
EMF is zero and so the motor must start without position
feedback.
The fi rst stage of the startup algorithm parks the rotor
in known position by driving dc currents into the stator
windings. In the second stage, the rotor fl ux estimator is in
open-loop mode, and the estimator’s angular velocity output
signal increases at a constant rate. In this mode the torquereference
current (I QREF ) is a constant value to deliver a torque
that will accelerate the motor at the rate equal to the angular
velocity output of the rotor-fl ux estimator.
If the motor torque is greater than that which the system
requires to match the estimator acceleration, the rotor will
advance in phase and move out of optimum alignment.
However, since the motor torque function is a cosine function
of this alignment, the rotor angle advances until the
motor torque exactly matches the target value.
Power Electronics Technology June 2006 18
www.powerelectronics.com
Flux loop
PI
I Q
I D
Limit
Limit
V D
Estimated angle
Rotor-flux
estimator
e -j
V Q
I
I
e j
3 - to - 2
Clark -1
Carrier frequency
V Space
6
V vector
PWM
I U
I V
I W
Fault
detection
Phasecurrent
reconstruction
Current
sample
timing
Threephase
inverter
gate-drive
signals
Fault
DC bus
current
(measured
by shunt
resistor)
Fig. 5. The digital implementation of the fi eld-oriented-control algorithm has one outer velocity-control loop and two inner
current loops for torque and fl ux control.
CKE manufactures
a wide range of
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(MOVs) for your unique
requirements. r
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Lucernemines, PA 15754
(724) 479-3533 (724) 479-3537 FAX
e-mail: info@cke.com www.cke.com

WASHER DRIVES
At 5% of the rated velocity, by which point a measurable
level of back EMF develops, the estimator switches into the
closed-loop mode. The feedback loops are then controlled
by the estimated angle and estimated speed signals from the
rotor-fl ux estimator.
Implementation Issues
Designers must face several practical considerations when
implementing the control algorithm in fi xed-point hardware.
The most important decision is the selection of control-variable
scaling, which must allow a good dynamic signal range
while avoiding calculation overfl ow. The resolution of the
digital-to-analog interface circuits could defi ne the controlvariable
scaling, but this does not ensure numerical stability
of the control-loop functions. Fixed control-variable scaling
simplifi es the design of the control-loop functions with the
minor additional complexity of the feedback-gain scaling.
Since velocity is a user input, its scaling requires the
highest resolution. To defi ne the velocity scaling for a 16bit
platform, the maximum operating drive speed is set to
equal +16383(~2 14 ), which allows 1 bit of headroom in case
of overshoot.
The velocity value that the rotor-angle estimator calculates
is the change in rotor-angle count in every control-loop
cycle. The scaling of this value depends on the loop sample
rate, the number of motor poles and the maximum rotor-
angle count. The feedback-gain scaling is then the ratio
of 16384 to the angle-estimator output at the maximum
operating speed.
Similarly, the current-variable scaling is defi ned by setting
the name-plate-rated motor current equal to +4095 (~2 12 )
counts. This allows suffi cient headroom for the current
controller to operate the motor in short-term overload. The
gain of the current-feedback circuits depends on the current-sense
resistor values, the buffer amplifi ers’ gains, and
the ADC’s input range and resolution. The current-sense
resistor is also useful for protection.
The value selected should trip the power inverter before
the motor current reaches its demagnetization limit. The
buffer amplifi er’s gain defi nes the operating range of current-control
loop since the ADC will saturate when the input
signal is out of range. The resolution of the vector-rotation
block, which requires all inputs to be in the 11-bit-plus sign
range, sets the voltage scaling in the case of this hardware
implementation.
The actual voltage scaling is a function of the maximum
voltage count and the dc-bus voltage. However, the dc-bus
voltage can change with either input ac voltage or the load,
and so a bus-voltage measurement contributes to the scaling
calculation.
Control Algorithm Tuning
The fi nal stage in the control algorithm design is in the
calculation of the feedback-gain parameters. The process
usually involves an element of trial and error, but there are
design tools that provide close-to-optimum values. Pole-zero
placement is a well-known technique that works well with
systems such as the current-control loop, whose parameters
are given to easy measurement.
The system model of the current controller in Fig. 6 illustrates
the technique. Gain elements, which the selection of
voltage and current scaling defi ne, model the PWM-inverter
and current-feedback circuits. A continuous-time-domain
Power Electronics Technology June 2006 20
www.powerelectronics.com
I* +
–
K L P
Stage 1: = for pole-zero cancellation
K R I
A x B x KI Stage 2: C = to set closed-loop bandwidth ( ) C R
Stage 3:
(
K P s + K I
s
T SAMPLE)
2
Proportional-plusintegral
controller
scaling factor for K I to calculate
gain in the digital algorithm
PWM inverter
V (counts) V (volts) 1
A
R + sL
I (counts) I (amps)
B
Motor winding
(dynamic)
Current feedback
Fig. 6. Current-loop tuning using pole-zero cancellation is executed in
three stages.

IRMCF3341- Reference design
8051
running MCE
interface
software
Shared
memory
8051
memory
Motion
control
engine
(MCE)
PWM
and
ADC
AC input
Rectifier
IRAM
JTAG UART
8051 tools
MCE Tools
WASHER DRIVES
PM
motor
Fig. 7. Design tools for the washing-machine design platform include
a spreadsheet for calculating controller constants based on motor
parameters and system specifi cations. A second tool, MCEDesigner,
transmits the constants to the embedded microcontroller.
model simplifi es the fi gure, but a sampled-data model only
requires some additional scaling of the integrator-gain
parameter.
As shown in Fig. 6, the PI-controller gains are calculated
in three stages. First, to reduce the order of the loop, select the
ratio of the PI compensator gains so that its zero cancels the
pole in the motor-winding model. Next, select the integral
gain so that the closed-loop bandwidth matches the target
specifi cations. Finally, scale the integral-gain parameter by
half of the sample period to calculate the gain in the digital
implementation.
The calculation of gain parameters for the current loop is
straightforward, but the next section describes some of the
tools for tuning the velocity loop when driving the type of
complex load found in washing-machine applications.
Simplifying Drive Commissioning
The washing-machine design platform includes a digital
IC with the control algorithm already embedded (Fig. 7).
The MCE implements the algorithm in hardware based
on parameters and variables that the shared-memory area
stores. One of the available design tools is a spreadsheet that
calculates the controller constants that match the motor
parameters and system specifi cations.
The second tool is MCEDesigner, which transmits the
controller constants from a PC to an interface program
running on the embedded 8051 microcontroller. The 8051
copies the parameters to the block of shared memory before
the MCE starts running the motor.
Another important function of the 8051 interface software
is to capture trace data from the MCE, which gives the
user access to all the control-system variables. MCEDesigner
also generates speed profi les that allow users to evaluate drive
performance in the washer application. The combination
of an embedded motor control algorithm and easy-to-use
evaluation tools simplifi es the evaluation of direct-drive
motors for washer applications. PETech
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November 14 to 17, 2006
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