Design and Testing for longer battery life in Android and other Mobile Devices & Applications

1. Design and Testing for longer battery life
in Android Devices & Applications
Moe Tanabian

2. Batteries in Mobile Devices – Why are they important?
Battery life: second most important purchase decision factor for tablets
Cost of the device 65%
Battery Life 51%
Operating System(Apple iOS, Android, Windows) 40%
Compatibility with other eq. you own 32%
Cost/Contract flexibility of 3G service 32%
Large screen size (i.e. the size of an iPad) 31%
Positive reviews (e.g. other users, CNET) 31%
Weight 28%
How it looks , feels 26%
Number of available apps 23%
The brand of manufacturer 22%
Manufacturer’s tech support 21%
Number of ports (e.g. USB, headphone jack, etc.) 19%
Ability to play Adobe Flash content 19%
Accessories available 16%
Has camera(s) 15%
Ability to watch HD video 13%
Has slide-out keyboard 13%
Ability to hold in one hand 12%
Based on 3,835 US online customers who would consider buying a tablet
(multiple responses accepted, Source: North American Technologies, Customer Technology Survey 01/2011
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3. Outline
What influences Battery Life?
Objective power consumption measurement
Predictive methods to measure power consumption
Areas to optimize power consumption
Setting up a power measurement lab
Hands-on Demo
3

4. The 3 influencing elements on Battery Life – The Battery, The Hardware, and The
Software
BATTERY HARDWARE SOFTWARE
1 2 3
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5. The Battery
1
Source: http://www.ifixit.com/ 5

6. Batteries in Mobile Devices – Evaluating batteries
When we describe a battery and how appropriate it is for a particular
device and application, we use three metrics to define the battery:
n Energy density (Power per weight unit, e.g. mA hour per Pound)
n Number of charging cycles the battery can take
n Charge rate
n Discharge rate
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7. Batteries in Mobile Devices – Battery Chemistry
There are three types of batteries that are extensively in use today, and
each provides certain strengths and weaknesses for different type of
devices:
n Nickel Cadmium (NiCd):
Strength: mature battery technology, has been around for long.
Weakness: low energy density (Wh/Kg).
Application: long battery life, high discharge rate and price economy are priority.
n Nickel Metal Hybrid (NiMH):
Strength: more advanced Nickel based battery technology,
compared to NiCd has higher energy density
Weakness: shorter cycle life
Application: Larger portable devices, Military
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8. Batteries in Mobile Devices – Battery Chemistry
n Lithium Ion (Li-ion):
Strength: The newest and fastest growing battery technology.
Li-ion batteries are smaller and lighter (higher energy density)
Weakness: they are more expensive
Application: the main type of battery used in mobile devices and handsets today
- Li-ion battery with steady current within its dominated C can provide 700 charge
Lithium Ion Polymer (Li-ion Polymer):
A lower version of Li-ion battery with smaller profile and more simplified packaging. It
has the same energy density as Li-ion batteries.
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9. Batteries in Mobile Devices – Battery Chemistry comparison chart
NiCd NiMH Li-ion Li-ion polymer
Gravimetric Energy
45-80 60-120 110-160 100-130
Density(Wh/kg)
Internal Resistance 100 to 2001 200 to 3001 150 to 2501 200 to 3001
(includes peripheral
6V pack 6V pack 7.2V pack 7.2V pack
circuits) in m Ω
Cycle Life (to 80% of initial
15002 300 to 5002,3 500 to 10003 300 to 500
capacity)
Fast Charge Time 1h typical 2-4h 2-4h 2-4h
Overcharge Tolerance moderate low very low low
Self-discharge /
20%4 30%4 10%5 ~10%5
Month (room tem perature)
Cell Voltage (nom inal) 1.25V 6 1.25V 6 3.6V 3.6V
Load Current
- peak 20C 5C >2C >2C
- best result 1C 0.5C or low er 1C or low er 1C or low er
Operating -40 to -20 to -20 to 0 to
Temperature (discharge
only)
60°C 60°C 60°C 60°C
Maintenance Requirement 30 to 60 days 60 to 90 days not req. not req.
Commercial use since 1950 1990 1991 1999
Source: Batteries in a portable world by Isidor Buchmann
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10. Batteries in Mobile Devices – Discharge profiles of NiCd and NiMH batteries
Source: Batteries in a portable world by Isidor Buchmann
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11. Batteries in Mobile Devices – Discharge characteristics of Li-ion battery
Source: Batteries in a portable world by Isidor Buchmann
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12. Batteries in Mobile Devices – An electric model for a battery
Ri
Voc
Cl Rl
Voc: open circuit voltage
Battery
Ri : internal resistance
Cl : load capacitance
Rl : load resistance
Source: Batteries in a portable world by Isidor Buchmann
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13. Batteries in Mobile Devices – Smart Battery packs
Smart battery pack should be able to
report:
- Battery’s State of Charge (SoC)
- State of Health
- Battery’s chemistry
They come in different complexities:
- Single Wire Bus Terminal
- SMBus based on a bi-directional two wire
I2C data communication
Source: Batteries in a portable world by Isidor Buchmann
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14. The Hardware
2
Source: http://www.ifixit.com/ 14

15. Power consumption measurement approaches – component, device level
n In this method, the device power consumption is the aggregate of measured
power consumption of each subsystem
Component level
n This method is more accurate, and the results are more reproducible; it is
often used by device OEMs
n It take more effort and it is more expensive
n Detailed device HW and SW documentation is needed
n The power is measured at the aggregate point of battery connection in this
Device (Application) method; power consumption is measured for different device use cases
level n This method is easier, and more practical for most cases; it is widely used by
network operators
n Since the results may vary from run to run, it is necessary to repeat the test
runs to achieve statistical significance and stability
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16. Power consumption measurement approaches – component level
Power is measured at every important component: RF, Processors, Mem, Screen (An LTE device)
RF Frontend
Wi-Fi,
for other Audio Magnetic
RF Bluetooth
globally Codec sensor
supported Transceiver Transceivers
bands
(*assumed 10 GPS Accelerometer Gyroscope
bands) Receiver
10* X Power
Amp Bank
10 X LPF Baseband Application
Bank Processor Memory
FDD/TDD LTE
1X / EVDO (Flash, RAM)
HSPA(+)
RF
Transceiver
PowerAmp
MDM 96XX
LTE
DC-HSPA, Graphics
LPF Bank Display
DOrB, EDGE Very High Power user
High Power user
Moderate Power user
For component level measurement, power is measured in relevant device main
states: Idle, Suspended and Active
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17. The Software
3
Source: http://www.ifixit.com/ 17

18. Design for power efficiency – Android Power Management
Applications Application 1 Application 2 Application 3
Wl = newWakeLock(…)
Wl.acquire()
Wl.release()
POWER MANAGER
APP Android.os.PowerManager
Android.os.Power
Framework Android.Server.PowerManagerService
Libraries LIBRARIES
/lib/hardware/power.c
(User Space)
Linux Kernel Linux Power Management
Power Manager
Source: http://www.kandroid.org/online-pdk/guide/power_management.html
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19. Android Power Manager states – Suspended, Idle, Active
n All device states written to RAM / Application processor is
idle
n Communication processor on low level activity only to
Suspended receive calls, SMS, etc
n Other components are tuned off by power manager
n A device spends significant amount of time in Idle state
A modern mobile
device can be in n Device is fully awake but no application is active
one of the three n Main power consuming components in this state are:
power consumption Idle Cellular radio, Graphics module, display and CPU
states
n At least one application is running
n Device battery consumption depends on what usage
Active scenario it is being used under (web browsing, email, voice
call, etc)
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20. Outline
What influences the battery life?
Objective power consumption measurement
Predictive methods to measure power consumption
Areas to optimize power consumption
Setting up a power measurement lab
Hands-on Demo
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21. Power consumption profiling for different subsystems – test cases
n Measurement of backlight at minimum and maximum intensity in mW
n Complete WHITE screen
Display subsystem n Complete BLACK screen
n White noise screen for benchmarking different Graphics chip sets and LCDs
n A good test: Downloading a file with random data content via HTTP
n Shielded device test to benchmark effect of signal strength on power
Network subsystem consumption and throughput - a 2mm think metal shielded box that can drop
the signal strength by 10dBm for cellular and 2dBm drop for Wi-Fi
n A benchmark that causes a good spectrum of utilization of the CPU and the
memory from highly CPU bound to highly memory bound e.g. SPEC CPU2000
CPU and RAM n A series of READ and WRITE operations for measuring power impact of
internal NAND flash and SD card. E.g. copying a file with random data
n Audio playback of a music file: e.g. a sample of 12.3MiB, for 10 minutes at
44.1 KHz MP3 file stored on internal NAND flash and SD card
Audio subsystem n Need to include cellular radio power into account since the device needs to
be ready to receive calls, SMS
n Different scenarios: device Idle, device running a GPS app, Satellite
acquisition, navigation and guidance
GPS n In smartphones, the GPS power consumption is minimal compared to other
subsystems and can be skipped
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22. Power consumption profiling for different subsystems – test cases
Test cases for Display component
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23. Measuring power consumption – multi-core devices
Multi-core devices can be more power efficient than single core devices
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24. Video call test case: a capture all test for device level benchmarking Device (Application)
level
power consumption and benchmarking of several devices
Multi-device benchmarking
For multi device benchmarking, video call
application utilizes many of important
components of a mobile device, given that:
n Hardware specifications of the devices
under test are similar
n Same application is used for video calling,
or at least call features are close or
identical such as video resolutions,
bandwidth utilization, etc
n Test conditions need to be standardized
and similar for every device to make the
results reliable and reproducible
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25. Power consumption measurement approaches – device level Device (Application)
level
Number of tests
runs required
N = t x f x nt
N : The total number of required power readings
(Rule of thumb for stable test results N >= 10K)
t : Duration of sample collection (min)
f : number of samples collected per second
nt : Number of test runs
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26. Power consumption measurement – the cloud effect Device (Application)
level
The cloud effect can hinder power consumption measurement accuracy
Issue: Cloud services can change their behavior and these changes have
significant implications on power consumption of the device: Example: when
playing a YouTube™ video, the server often adjusts the resolution based on
the client’s capabilities and the connection throughput
Issue: Many smartphone applications constantly and in an ad-hoc way
exchange data with backend servers that are not user driven or user
controllable. Example: Google Map
Solution: Re-create the use scenario in a controlled lab environment
In Android: To recreate the input sequence of actions, while running the real
cloud based test, use captured user input interactions traces: /dev/input/event*
Android kernel can re-run the sequence by reading this information
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27. Outline
What influences the battery life?
Objective power consumption measurement
Predictive methods to measure power consumption
Areas to optimize power consumption
Setting up a power measurement lab
Hands-on Demo
27

28. Predictive methods– Two Predictive methods are based on building mathematical
Power Consumption models for each major component of the device
n A formula is built to predict Device Power consumption as a function of
power consumption of each component
Models based on
real device n Through a series of measurements, power consumption factor of each
component is determined and the model is calibrated
measurements
n The model then can be used to estimate device power consumption of an
application or task based on the time periods each component is “ON”
n The Discharge behavior of the battery is determined
Models Training n Each component’s power consumption factor is determined based on its the
based on Battery % it decreases energy level of the battery for a period of time e.g. 15min –
Discharge states and the model is calibrated based on this factor
n The model then can be used to estimate device power consumption of an
application or task based on the time periods each component is “ON”
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29. Predictive methods– Model calibration based on real device measurement
1. Identify major components to be
included in the model e.g. Display
2. Identify the System Variable (SV)
Σ SV x βsv
β: System Variable factor
corresponding to each component SV: System Variable value
e.g. screen brightness intensity
3. Build the device power consumption
model as a function of all the SVs
4. In a series of measurements, isolate Current sensing
resistor
each major component and measure Battery /
Power supply
Stabilizing
Capacitor
the power consumption factor directly
5. Use the model to predict power
consumption of the different use
cases and tasks in your applications
Device
Source: Google, U. of Michigan
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30. Predictive methods– Model calibration based on battery Discharge State
∆
1. Identify major components to be
included in the model e.g. Display
2. Identify the System Variable (SV)
corresponding to each component
e.g. screen intensity
3. Build the device power consumption
model as a function of all the SVs
4. In a series of measurements, isolate (Delta E)
each major component and
determine the power consumption
factor based on the battery SoC (vi)
P x (t1-t2) = E x (SOC(V1) – SOC(V2))
5. Use the model to predict power P: AVG Power consumption in time t1-t2
consumption of the different use E: Rated battery energy capacity
SOC(Vi): Battery State of Charge at voltage Vi
cases and tasks in your applications
Source: Google, U. of Michigan
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31. Outline
What influences the battery life?
Objective power consumption measurement
Predictive methods to measure power consumption
Areas to optimize power consumption
Setting up a power measurement lab
Hands-on Demo
31

32. Design for power efficiency – GUI
Making GUI more power efficient
GUI facilitates most of the user interactions, and since it
fully utilizes the screen, it’s a major power consuming
part of the device software.
GUI provides INPUT, OUTPUT and HYBRID UI
functions.
Here are factors that design can take into consideration:
n Cognitive latency
n Perceptual capacity
n Hot keys
n User input cache
n Direct GUI power reduction
n Backlight control
n Frame buffer compression
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33. Design for power efficiency – GUI – Cognitive latency
n Reducing Cognitive Latency makes GUI more power efficient:
Cognitive n Cognitive latency is the time that the user needs to understand the
Latency number of GUI elements present on the screen.
If N is the number of element to choose, then:
(Hick-Hayman Law)
reaction time (sec) = a + b log2N (a, b constant)
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34. Design for power efficiency – GUI – Cognitive latency
A very effective way to reduce cognitive latency is decreasing the
number of options from which the user can make a selection. Split
Cognitive menu is a good example of a GUI element with low cognitive latency.
Latency
Time taken to respond (sec)
3
Number of choices on screen
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35. Design for power efficiency – GUI – Perceptual capacity
n Better visibility of the GUI elements being presented to the user
lowers required user interaction time
Perceptual
Capacity
n font type
n font size
n color,
n GUI component size
n color and optimal contrast ratio
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36. Design for power efficiency – GUI – other stuff
n Hot keys
Other stuff
n User input cache
n Direct GUI power reduction
n Backlight control
n Frame buffer compression
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37. Design for power efficiency – proper use of wakelock(), wifilock()
PowerManager pm = (PowerManager) getSystemService(Context.POWER_SERVICE);
PowerManager.WakeLock wl = pm.newWakeLoc(PowerManager.SCREEN_DIM_WAKE_LOCK, "My Tag");
wl.acquire();
..screen will stay on during this section..
wl.release();
Flag value CPU Screen Keyboard
PARTIAL_WAKE_LOCK On Off Off
SCREEN_DIM_WAKE_LOCK On DIM Off
SCREEN_BRIGHT_WAKE_LOCK On Bright Off
FULL_WAKE_LOCK On Bright Bright
ACQUIRE_CAUSES_WAKEUP Forces screen and/or KB to illuminate without waiting for user
interaction
ON_AFTER_RELEASE User activity timer will be reset. Screen, KB will stay ON a bit
longer
Source: http://developer.android.com/reference/android/os/PowerManager.html
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38. Design for power efficiency – proper use of wakelock(), wifilock()
n wakelock()
wakelock(), n Device battery life significantly affected by the use of wakelock()
wifilock()
use best practice n Do not acquire wakelock()s unless you ABSOLUTELY need
them
n When you acquire wakelock()s, use minimum level possible
n Make sure you release the lock when you’re done
n wifilock()
n When syncing with the server, use longer periods (less
frequent: 1 every hr instead of 1 every 5min)
n Release the lock when you’re done
n Example: A good justification for wifilock() is when downloading large
files
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39. Outline
What influences the battery life?
Objective power consumption measurement
Predictive methods to measure power consumption
Areas to optimize power consumption
Setting up a power measurement lab
Hands-on Demo
39

40. Setting up a power measurement lab – Lab functions
n System to sample voltage, current and power at high
Lab functions sampling frequency rates
(1000 sample per second and above)
n System to host simulated cloud services
n Equipment to measure ambient light
n Equipment to measure ambient noise
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41. Setting up a power measurement lab – Voltage, current & power measurement
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42. Setting up a power measurement lab – Voltage, current & power measurement
Monsoon Power Monitor
National Instrument
LabView Software
National Instrument
USB-4065 USB DMM
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43. Setting up a power measurement lab – Measuring ambient light, noise
Lux Meter Sound level Meter
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44. Setting up a power measurement lab – Connecting to the device
Current sensing
resistor
Battery /
Power supply
Battery adapter
Stabilizing
Capacitor
Copper Conductive adhesive
tape
44

45. Outline
What influences the battery life?
Objective power consumption measurement
Predictive methods to measure power consumption
Areas to optimize power consumption
Setting up a power measurement lab
Hands-on Demo
45

46. Thank You!
Moe Tanabian
@motanabian
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