2024年5月26日发(作者：圭令怡)
Battery-Driven Dynamic
Power Management
Luca Benini
Università di Bologna
Giuliano Castelli
Alberto Macii
Riccardo Scarsi
Politecnico di Torino
Battery lifetime extension is a primary design
objective for portable systems. We introduce the
concept of battery-driven dynamic power
management, which strives to enhance lifetime by
automatically adapting discharge rate and current
profiles to battery charge state.
T
HEACTIVITYOFSEVERALCOMPONENTS
in
a computing system is event-driven. For example,
the activity of display servers, communication
interfaces, and user interface functions is triggered
by external events, and it is often interleaved with
long, idle periods. An intuitive way to reduce
average power dissipated by the whole system
consists of shutting down resources during peri-
ods of inactivity. In other words, one can adopt a
dynamic power management (DPM) policy that
dictates how and when various components
should be shut down according to a system’s
workload. Workload-driven DPM can be very
effective, thanks to sophisticated policies, based
on complex computational models (such as
Markov chains) proposed in the recent literature.
1
We observe, however, that minimum aver-
age power is not always the objective when
designing battery-operated, mobile applica-
tions. Rather, what really matters for this kind
of system is ensuring long battery lifetime.
Average power reduction and battery lifetime
March–April 2001
extension may be numerically far apart.
2
This
implies that optimizations for minimum aver-
age power may not be equally effective in
extending battery lifetime, and vice versa. Our
work moves from the assumption that taking
battery’s charge state into account while man-
aging the system helps in maximizing the time
of operation of portable devices.
We describe several DPM policies specifical-
ly tailored to battery lifetime maximization. In
particular, we introduce a class of closed-loop
policies, whose decision rules used to control the
system operation state are based on the obser-
vation of a battery’s output voltage (which is relat-
ed, nonlinearly, with the charge state). This is in
contrast with open-loop solutions that reach deci-
sions about component shutdown indepen-
dently from battery voltage measurement.
Open-loop policies are normally simpler, but
less effective, than closed-loop ones; they rep-
resent a viable option when cost constraints
prevent the use of a voltage sensor on the bat-
tery terminals. On the other hand, the distin-
guishing feature of closed-loop policies is that
they control system operation based on the
observation of both system workload and bat-
tery output voltage. As a consequence, they can
dynamically adapt a component’s shutdown
scheme to the actual battery charge state.
Battery properties
From the system designer’s point of view, the
physical properties of interest in a battery are out-
put voltage and battery capacity. In an ideal bat-
tery, the voltage is constant over a complete
0740-7475/01/$10.00 ©2001 IEEE
53
54
Power Management by Battery
1.4
1.3
)
r
h
1.2
×
p
s
1.1
m
A
(
1.0
y
t
i
c
a
0.9
p
a
C
0.8
0.7
Usable
Nominal
0.6
0.01
0.1
1
Load current Amps
Figure 1. Capacity variation as a function of load
current.
4.0
Constant
Intermittent
3.8
3.3
)
V
(
e
3.6
g
a
t
l
V
o
3.4
3.2
3.0
01,0001,2001,4001,6001,800
Elapsed time of discharge (s)
Figure 2. Continuous compared with intermittent
discharge.
discharge cycle, and it drops to zero when the bat-
tery is fully discharged. In practice, however, volt-
age decreases as the time of discharge increases.
As a matter of fact, a battery is considered exhaust-
ed when its output voltage falls below a given volt-
age threshold (such as 80% of the nominal
voltage). This behavior motivates the adoption of
DC-DC converters for voltage stabilization when
batteries are used to power up digital systems.
Beside this, two additional factors differen-
tiate real batteries from ideal power supplies
that are at the basis of the battery-based DPM
technique:
s
the effective capacity of a battery depends
on the discharge current, and
s
a battery can recover some of its deliverable
charge when it is given some rest.
We illustrate these two effects through exper-
imental evidence, rather than by rigorous con-
struction and derivation of mathematical
models representing electrochemical phenom-
ena. Readers may refer to the vast, specialized
literature for more information.
3
The data we present have been obtained
through event-driven simulation of the system-
level, discrete-time model of a lithium-ion bat-
tery.
2
Such a model guarantees an average error
in estimated lifetime of 0.52% with respect to a
circuit-level, continuous-time model.
4,5
The lat-
ter, in their turn, have proven to be within 15%
from measured data under a large variety of
loading conditions.
Capacity versus discharge current
At higher currents, a battery is less efficient
in converting its chemically stored energy into
available electrical energy. This fact is pictori-
ally shown in the diagram of Figure 1, where the
capacity of the battery is plotted as a function of
the average current load. The plot is relative to a
battery of nominal capacitance of 1.35 Amp/hr
(solid line). We observe that, for increasing load
currents, the battery capacity progressively devi-
ates from the nominal value (dashed line).
Charge recovery
A battery can recover some of its deliverable
charge if discharge periods are interleaved with
rest periods (periods in which no current is
drawn). This is shown in Figure 2, where the
output voltage of the battery is plotted under
two discharge profiles: a constant current load
(solid line) and an intermittent current load
(dashed line).
Both the constant current and the intermit-
tent current, while on, have the same discharge
rate. In addition, the off time of the intermittent
discharge is not shown in the plot. Then the x-
axis represents the actual elapsed time of dis-
charge, and it is proportional to the actual
usable capacity of the battery. Note that, in the
plot, the constant line at 3.3 V represents the
voltage level under which the battery is regard-
ed as exhausted.
IEEE Design & Test of Computers
2024年5月26日发(作者：圭令怡)
Battery-Driven Dynamic
Power Management
Luca Benini
Università di Bologna
Giuliano Castelli
Alberto Macii
Riccardo Scarsi
Politecnico di Torino
Battery lifetime extension is a primary design
objective for portable systems. We introduce the
concept of battery-driven dynamic power
management, which strives to enhance lifetime by
automatically adapting discharge rate and current
profiles to battery charge state.
T
HEACTIVITYOFSEVERALCOMPONENTS
in
a computing system is event-driven. For example,
the activity of display servers, communication
interfaces, and user interface functions is triggered
by external events, and it is often interleaved with
long, idle periods. An intuitive way to reduce
average power dissipated by the whole system
consists of shutting down resources during peri-
ods of inactivity. In other words, one can adopt a
dynamic power management (DPM) policy that
dictates how and when various components
should be shut down according to a system’s
workload. Workload-driven DPM can be very
effective, thanks to sophisticated policies, based
on complex computational models (such as
Markov chains) proposed in the recent literature.
1
We observe, however, that minimum aver-
age power is not always the objective when
designing battery-operated, mobile applica-
tions. Rather, what really matters for this kind
of system is ensuring long battery lifetime.
Average power reduction and battery lifetime
March–April 2001
extension may be numerically far apart.
2
This
implies that optimizations for minimum aver-
age power may not be equally effective in
extending battery lifetime, and vice versa. Our
work moves from the assumption that taking
battery’s charge state into account while man-
aging the system helps in maximizing the time
of operation of portable devices.
We describe several DPM policies specifical-
ly tailored to battery lifetime maximization. In
particular, we introduce a class of closed-loop
policies, whose decision rules used to control the
system operation state are based on the obser-
vation of a battery’s output voltage (which is relat-
ed, nonlinearly, with the charge state). This is in
contrast with open-loop solutions that reach deci-
sions about component shutdown indepen-
dently from battery voltage measurement.
Open-loop policies are normally simpler, but
less effective, than closed-loop ones; they rep-
resent a viable option when cost constraints
prevent the use of a voltage sensor on the bat-
tery terminals. On the other hand, the distin-
guishing feature of closed-loop policies is that
they control system operation based on the
observation of both system workload and bat-
tery output voltage. As a consequence, they can
dynamically adapt a component’s shutdown
scheme to the actual battery charge state.
Battery properties
From the system designer’s point of view, the
physical properties of interest in a battery are out-
put voltage and battery capacity. In an ideal bat-
tery, the voltage is constant over a complete
0740-7475/01/$10.00 ©2001 IEEE
53
54
Power Management by Battery
1.4
1.3
)
r
h
1.2
×
p
s
1.1
m
A
(
1.0
y
t
i
c
a
0.9
p
a
C
0.8
0.7
Usable
Nominal
0.6
0.01
0.1
1
Load current Amps
Figure 1. Capacity variation as a function of load
current.
4.0
Constant
Intermittent
3.8
3.3
)
V
(
e
3.6
g
a
t
l
V
o
3.4
3.2
3.0
01,0001,2001,4001,6001,800
Elapsed time of discharge (s)
Figure 2. Continuous compared with intermittent
discharge.
discharge cycle, and it drops to zero when the bat-
tery is fully discharged. In practice, however, volt-
age decreases as the time of discharge increases.
As a matter of fact, a battery is considered exhaust-
ed when its output voltage falls below a given volt-
age threshold (such as 80% of the nominal
voltage). This behavior motivates the adoption of
DC-DC converters for voltage stabilization when
batteries are used to power up digital systems.
Beside this, two additional factors differen-
tiate real batteries from ideal power supplies
that are at the basis of the battery-based DPM
technique:
s
the effective capacity of a battery depends
on the discharge current, and
s
a battery can recover some of its deliverable
charge when it is given some rest.
We illustrate these two effects through exper-
imental evidence, rather than by rigorous con-
struction and derivation of mathematical
models representing electrochemical phenom-
ena. Readers may refer to the vast, specialized
literature for more information.
3
The data we present have been obtained
through event-driven simulation of the system-
level, discrete-time model of a lithium-ion bat-
tery.
2
Such a model guarantees an average error
in estimated lifetime of 0.52% with respect to a
circuit-level, continuous-time model.
4,5
The lat-
ter, in their turn, have proven to be within 15%
from measured data under a large variety of
loading conditions.
Capacity versus discharge current
At higher currents, a battery is less efficient
in converting its chemically stored energy into
available electrical energy. This fact is pictori-
ally shown in the diagram of Figure 1, where the
capacity of the battery is plotted as a function of
the average current load. The plot is relative to a
battery of nominal capacitance of 1.35 Amp/hr
(solid line). We observe that, for increasing load
currents, the battery capacity progressively devi-
ates from the nominal value (dashed line).
Charge recovery
A battery can recover some of its deliverable
charge if discharge periods are interleaved with
rest periods (periods in which no current is
drawn). This is shown in Figure 2, where the
output voltage of the battery is plotted under
two discharge profiles: a constant current load
(solid line) and an intermittent current load
(dashed line).
Both the constant current and the intermit-
tent current, while on, have the same discharge
rate. In addition, the off time of the intermittent
discharge is not shown in the plot. Then the x-
axis represents the actual elapsed time of dis-
charge, and it is proportional to the actual
usable capacity of the battery. Note that, in the
plot, the constant line at 3.3 V represents the
voltage level under which the battery is regard-
ed as exhausted.
IEEE Design & Test of Computers