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Energy Metering for Free:Augmenting Switching Regulators for Real-Time

Monitoring

Prabal Dutta†, Mark Feldmeier‡, Joseph Paradiso‡, and David Culler†

Computer Science Division†

University of California, Berkeley{prabal,culler}@cs.berkeley.edu

The Media Laboratory‡

Massachusetts Institute of Technology

{carboxyl,joep}@mit.edu

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Energy is a critical resource in this domain…

So, why don’t more publications provide empirical evidence of a change in energy usage

in situ or at scale?

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Current energy metering techniques are inadequate

cumbersome, expensive, not distributed,not scalable, not embedded

cumbersome, expensive, not distributed,not scalable, not embedded,

low resolution, low responsiveness, high quiescent power

low responsiveness, high cost, high quiescent power

DS2438ADM1191BQ2019BQ27500 [Jiang07]

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How simply can energy metering be performed?

If your platform has a PFM switching regulator…(increasingly, many do)

very simply:

iCountenergymeterdesign

• The network-wide cost of the CSMA overhearing problem• Energy division between route-through and local traffic• Energy benefits of batching or compressing data

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This simple design works surprisingly well

MAX1724

Our implementation

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Outline

• Introduction• How does it work?• How well does it work?• How much does it cost?• What are its limitations?• How could it be used?

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How does it work?

Source: Maxim Semiconductor

Cin

LxVin

VinCout

Vout

Rload

iLX

Energize

Transfer

Monitor

S1

S2

VLX

E=½Li2

PFMRegulator

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The key insight: each regulator cycle transfers a fixed amount of energy to the load

ΔE=½Li2

P=ΔE/Δt

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Outline

• Introduction• How does it work?• How well does it work?

– Range– Accuracy– Resolution– Responsiveness– Precision– Stability

• How much does it cost?• What are its limitations?• How could it be used?

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A typical mote-class system exhibits a 10000:1dynamic range in current draw (5 µA to 50 mA)

iCount offers a dynamic range exceeding 100000:1

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iCount exhibits less than ±20% errorover five decades of current draw

Common Operating Points

iCount exhibits lower error over mote operating range

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A Telos mote uses about 20 µJ per second when sleeping

iCount resolves less than 1 µJ

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A mote’s energy-consuming eventscan occur in as little as 100 µs [Jiang07]

iCount responds in less than 125 µsto sudden changes in current draw

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iCount is precise over short periods (2 sec) so one or two samples is enough to estimate the instantaneous current

All samples fall within ±2% of the median

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iCount is stable over long periods (1 week)

All samples fall within ±1% of the median

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Outline

• Introduction• How does it work?• How well does it work?• How much does it cost?

– Hardware– Software– Energy

• What are its limitations?• How could it be used?

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Hardware costs include a wireand a microcontroller counter

“wire”Counter

HydroSolar Node (v2)

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Software costs include initializing hardwareand handling load-dependent counter overflows

Control

Access (15 µs)

Overflow

Initialization

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Energy costs include switching gate capacitors and handling load-dependent counter overflows

1%

0.01%

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Outline

• Introduction• How does it work?• How well does it work?• How much does it cost?• What are its limitations?

– Efficiency– Voltage dependence– Calibration

• How could it be used?

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Regulator inefficiency can makebattery gas gauging challenging

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Input voltage dependence requires calibration(not fundamental, but an artifact of the MAX1724)

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Calibration is required eitherat manufacturing or at run-time

Calibration

Reg

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Estimating per-component current draws from the aggregate

R G B ΔE Δt

0 0 0 8241024

1 0 0 123361024

0 1 0 188061024

1 1 0 304341024

0 0 1 149401024

1 0 1 264321024

0 1 1 328041024

1 1 1 442471024

Regression

Log

X = [ones(size(R)) R G B];p = dE ./ dt;i = p / 3;a = X\i;y = [dt transpose(a)];

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Conclusion

iCount - simple, functional, research-enabling research

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Future directions and enabled research

• Hardware profiling – estimating per-subsystem power draw

• Model validation – do theory and practice agree in practice and at scale?

• Real-time current metering – measuring the instantaneous current draw

• Software energy profiling – where have all the joules gone?

• Runtime adaptation – equal-energy scheduling by the operating system

• Gas gauging – estimating remaining battery energy

• Voltage independence – ensuring a cycle delivers the same energy independent of input voltage

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Questions?

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Performance summary

Performance Metric iCount

Range 1 µA – 100 mA

Accuracy ±20%

Resolution 0.1 µJ – 0.5 µJ

Read latency 15 µs

Power overhead 1% - 0.01%

Responsiveness < 125 µs

Precision ±1.5% (over 2 secs)

Stability ±1% (over 1 week)*

* Frequency averaged over 1 second

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Current energy metering techniques are inadequate

Metric

Battery Fuel Gauge

[DS2438/ADM1191/

AC Metering[ADE7753/MCP3906]

SPOT[Jiang07]

Range 45000:1

Accuracy ±3% (0-9 µA)

Resolution < 1 µA

Read latency SPI/-

Power overhead

4-7 mA

Responsiveness

?

Precision

Stability