POWER OPTIMIZATION OF HETEROGENEOUS imec 2011 microtech2011 mems-based system solutions and...
Transcript of POWER OPTIMIZATION OF HETEROGENEOUS imec 2011 microtech2011 mems-based system solutions and...
© IMEC 2011
MICROTECH2011 MEMS-BASED SYSTEM SOLUTIONS AND INTEGRATION APPROACHES
POWER OPTIMIZATION
OF HETEROGENEOUS AND MEMS-BASED
SYSTEMS
”CONSUME MORE TO CONSUME LESS”
CHRIS VAN HOOF
DIRECTOR INTEGRATED SYSTEMS
© IMEC 2011
OVERVIEW
Introduction / motivation from imec perspective
Drivers for System Optimization
3 Optimization Examples
▸ The Self-Powered Health Patch ▸ The iTire – a new TPMS paradigm ▸ The eNose – a Future Smartphone Add-on
Conclusions
© IMEC 2011
IMEC
imec Belgium
imec The Netherlands
imec Taiwan
imec office Japan
imec office US imec China
Independent R&D center performing leading research in nanoelectronics
© IMEC 2011
IMEC: TECHNOLOGY IS KEY ONE OF THE WORLD’S MOST ADVANCED IC R&D FACILITIES
© IMEC 2011
imec aims to shape the future.
With our global research partners, we will lead the development of nano-enabled solutions that
allow people to have a better life in a sustainable society.
© IMEC 2011
and it must be a SUSTAINABLE FUTURE
Busy lifestyle Aging society Global warming Unlimited mobile access Mobility Energy shortage
and SUSTAINABILITY
implies ENERGY AWARENESS
© IMEC 2011
OVERVIEW
Introduction
Drivers for System Optimization
3 Optimization Examples
▸ The Self-Powered Health Patch ▸ The iTire – A new TPMS paradigm ▸ The eNose as Future Smartphone Add-on
Conclusion - Disruptive
© IMEC 2011
3 DRIVERS FOR SYSTEM OPTIMIZATION
1 2 3 Power Functionality Size
0
100
Gen 4
Gen 3
Gen 2
Gen 1
COST ?
© IMEC 2011
TRADITIONAL SYSTEM OPTIMIZATION
Manageable System Optimization
“EVERYBODY PAYS (SAVES)”
0 20 40 60 80
100 120 140 160 180
GEN 1 GEN 2 GEN 3
Sensor
Analog Interface
Digital Control
Signal Processing
Power Management
Radio
Microsystem cpts
© IMEC 2011
DISRUPTIVE SYSTEM OPTIMIZATION Smart System Optimization
“CONSUME MORE TO CONSUME LESS”
0 20 40 60 80
100 120 140 160 180
GEN 1 GEN 2' GEN 3'
Sensor
Analog Interface
Digital Control
Signal Processing
Power Management
Radio
© IMEC 2011
OVERVIEW
Introduction
Drivers for System Optimization
3 Optimization Examples
▸ The Self-Powered Health Patch ▸ The iTire – A new TPMS paradigm ▸ The eNose as Future Smartphone Add-on
Conclusion - Disruptive
© IMEC 2011 12
THE SELF-POWERED HEALTH PATCH
© IMEC 2011
THE IMEC HEALTH PATCH
13
Cardiac patch with arrhythmia analysis and continuous wireless ECG signal transmission
© IMEC 2011
THE SELF-POWERED HEALTH PATCH ?
14
PV cells! TEG!
▸ BiTe based micromachined thermopiles
▸ 30uW/cm2 ! 60uW …90uW maximum
TODAY: Battery powered TOMORROW: Self Powered ?
THERMAL ENERGY
HARVESTING
© IMEC 2011
MCU 2%
Radio 50%
ADC 2%
Sensor &ROIC
7%
PM 39%
THE SELF-POWERED HEALTH PATCH ?
15
1112!W
Today’s ECG patch consumes 1.1mW
▸ In optimum operation mode ▸ Power consumption
should be reduced by 10x - 20x
© IMEC 2011
POWER DIAGNOSIS BY MODELING POWER OPTIMIZATION STRATEGY: STEP 1
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989!W !=12%"
MCU 68%
Radio 3%
ADC 2%
Sensor &ROIC
8%
PM 20%
MCU 2%
Radio 50%
ADC 2%
Sensor &ROIC
7%
PM 39%
1112!W
NO CIRCUIT CHANGE PURELY SYSTEM CHANGE
© IMEC 2011
POWER DIAGNOSIS BY MODELING POWER OPTIMIZATION STRATEGY: STEP 2
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MCU 68%
Radio 3%
ADC 2%
Sensor &ROIC
8%
PM 20%
369!W !=63%"
MCU 13%
Radio 7%
ADC 5%
Sensor & ROIC
20%
PM 55%
CIRCUIT CHANGE: REPLACE MCU (MSP430 ! CORTEX M3)
989!W
© IMEC 2011
POWER DIAGNOSIS BY MODELING POWER OPTIMIZATION STRATEGY: STEPS 3 & 4
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MCU 13%
Radio 7%
ADC 5%
Sensor & ROIC
20%
PM 55%
214!W !=42%"
MCU 12%
Radio 12%
ADC 9%
Sensor & ROIC
35%
PM 23%
174!W !=20%"
MCU 27%
Radio 15%
ADC 11%
Sensor & ROIC
21%
PM 26%
REPLACE linear
regulator
REPLACE sensor
interface (lower
voltage)
369!W
© IMEC 2011
MCU 39%
Radio 4%
ADC 1%
Sensor & ROIC
31%
PM 26%
POWER DIAGNOSIS BY MODELING POWER OPTIMIZATION STRATEGY: STEPS 5 & 6
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MCU 27%
Radio 15%
ADC 11%
Sensor & ROIC
21%
PM 26%
121!W !=30%
96!W !=21%"
MCU 32%
Radio 5%
ADC 1% Sensor
& ROIC 39%
PM 23%
REPLACE RADIO
by custom BAN radio
REPLACE MCU
by custom BIO-DSP
174!W
© IMEC 2011
THE SELF-POWERED HEALTH PATCH !
20
PV cells! TEG!
▸ BiTe based micromachined thermopiles
▸ 30uW/cm2 ! 60uW …90uW maximum
TODAY: Battery powered TOMORROW: Self Powered !
THERMAL ENERGY
HARVESTING MCU 32%
Radio 5%
ADC 1% Sensor
& ROIC 39%
PM 23%
96!W
© IMEC 2011
THE iTIRE VEHICLE AND TIRE EVOLUTION
1885
1908
1985
2015
2011
2500 BCE
2020
First pneumatic automobile tire
Tire pressure monitoring mandatory in US
Introduction of the radial tire
Intelligent Autonomous tire Systems
Fully active tires
© IMEC 2011
Board computer
TPMS Transmitter/Receiver IC
TPMS APPLICATION; PRESENT
22 imec Confidential
Pressure sensor
Acceleration sensor (opt.)
ADC
MCU (Memory, Firmware)
RF Transmitter 315/434MHz
LF
Receiver (125KHz) (Wake-up)
Power management
RF Receiver
315/434MHz
MCU
Power management 12V
3V battery LF Transmitter (Wake-up)
Regulated in US and from 2012 in Europe Ultra-low power, low-cost, reliable
EXPLORE DISRUPTIVE SYSTEM OPTIMIZATION POSSIBILITIES
© IMEC 2011
Board computer
TPMS Transmitter/Receiver IC
23 imec Confidential
Pressure sensor
Acceleration sensor
ADC
MCU (Memory, Firmware)
RF Transmitter 315/434MHz
LF
Receiver (125KHz) (Wake-up)
Power management
RF Receiver
315/434MHz
MCU
Power management 12V
3V battery LF Transmitter (Wake-up)
TPMS APPLICATION; NEW ARCHITECTURE
Energy harvester functionality/added value Energy source Wake-up; Takes the LF & accelerometers modules role Reduces capacity consumption by >50%
Harvester+ Capacitor
No need
New
DISRUPTIVE SYSTEM OPTIMIZATION (1): Re-think the TPMS architecture to fit the harvester
© IMEC 2011
CURRENT TPMS; BATTERY CAPACITY ESTIMATION FOR 10 YEARS OPERATION
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" This explains the 5-7 years battery-powered TPMS life cycle limitation***
Leakage 1%
RF 64%
MCU 14%
Power management
12%
Sensors & ADC 1%
Others 8%
T (15%)
Volt. (15%)
Rx* (94%)
Tx* (6%)
730mAh
* 4/20hours motion/parking cycle **10!A/sec for operations & 10!A/sec Memory for 3/15seconds motion/parking cycle ***500mAh battery
Pressure (58%)
Operations (50%)
Memory (50%)
ADC (12%)
© IMEC 2011
TPMS; POWER / CAPACITY ESTIMATION 10 YEARS OPERATION (WITH HARVESTER)
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" Scenario with harvester replacing the LF wake-up process
Leakage 3%
RF 7%
MCU 26% Power
management 47%
Sensors & ADC 1% Others
16%
T (15%)
Volt. (15%)
Rx* (0%)
Tx* (100%)
380mAh
* 4/20hours motion/parking cycle **10!A/sec for operations & 10!A/sec Memory for 3/15seconds motion/parking cycle ***90mAh/10 years added for harvester-battery PM2
Pressure (58%)
Operations (50%)
Memory (50%)
ADC (12%)
PM generation
(50%) PM
consumption (50%) May be even reduced to a half or less if
50% (PM + leakage) battery powered 50% harvester powered
© IMEC 2011
Intelligent tire sensor system on inner liner
i TIRE – THE FUTURE
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Pressure sensor
ADC
MCU (Memory, Firmware)
RF Transmitter 315/434MHz Power management
Super capacitor
Energy harvester functionality/added value Force sensor for improved tire state estimator Energy harvester with sufficient power generation Super capacitor as energy storage Mounted in the inner liner of the tire
Harvester
Energy source Wake-up
Force sensor
RADICAL SYSTEM OPTIMIZATION (2): Re-think the system for improved tire state estimation
© IMEC 2011
REAL iTIRE WITH ENHANCED FUNCTIONALITY A SYSTEM POWER CHALLENGE
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*Assuming 6kbps data rate
6954!W*
MCU 2%
Radio 82%
ADC 1%
Sensor &R-out
<1% PM 15%
WELL OUT OF RANGE OF BATTERY
POWERED OR HARVESTED SYSTEMS
321!W !=95%"
MCU 7%
Radio 60%
ADC 4%
Sensor &R-out
4%
PM 25%
APPROACHES HARVESTER
CAPABILITIES
© IMEC 2011
REAL iTIRE WITH ENHANCED FUNCTIONALITY MORE THAN JUST NUMBERS … ALSO FIRST HARDWARE
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First 100’s of Km test drive in June 2011 on a racetrack
Sensor on the rim and in the inner liner
MEMS harvester reliability & power
Instantaneous wireless signal and data storage (8GB)
© IMEC 2011 29
THE eNOSE AS FUTURE SMARTPHONE ADD-ON
Air quality monitoring and indoor air quality control (pollution, malodor emission, toxic gasses..)
Consumer fraud prevention (ingredient confirmation, content standards..)
Ripeness, Food contamination (spoilage, self live..)
Taste, smell characteristics (off flavors , product variety assessment..)
Pathogen identification (patient treatment selection, prognosis..)
Physiological condition (nutritional status, organ failure..)
Personnel and population security (biological and chemical weapons...)
CO2 high levels
© IMEC 2011
POWER is a challenge but not the main challenge
PERFORMANCE AND SYSTEM INTEGRATION are key challenges
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THE eNOSE AS FUTURE SMARTPHONE ADD-ON
© IMEC 2011
Nokia Scentsory Concept
Nokia EcoSensor Concept
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THE eNOSE AS FUTURE SMARTPHONE ADD-ON
AS THIS CAN BE FULLY INTEGRATED IN A FUTURE SMARTPHONE, A SELF-POWERED SOLUTION IS NOT NEEDED
POWER is a challenge but not the main challenge
PERFORMANCE AND SYSTEM INTEGRATION are key challenges
© IMEC 2011 32
THE eNOSE AS FUTURE SMARTPHONE ADD-ON
PERFORMANCE AND SYSTEM INTEGRATION are key challenges
▸ Device Integration - Monolithic MEMS integration - Hybrid MEMS integration - Very … hybrid integration
▸ Calibration challenges - Reusable MEMS sensor - Disposable MEMS sensor
▸ System Integration - Many applications need to be covered - One nose fits all vs dedicated eNoses
THE SMARTPHONE ENVIRONMENT OFFERS
UNPRECEDENTED SYSTEM OPTIONS:
- Calibration by peers
instead of in-situ - “App” style hardware
additions (micro-SD) - These are disruptive
integration options
© IMEC 2011
OVERVIEW
Introduction
Drivers for System Optimization
3 Optimization Examples
▸ The Self-Powered Health Patch ▸ The iTire – A new TPMS paradigm ▸ The eNose as Future Smartphone Add-on
Conclusion: DISRUPTIVE MEMS System Design is key – and it does involve “CONSUME MORE … TO CONSUME LESS”
© IMEC 2011