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ZigBeeTM Alliance | Wireless Control That Simply WorksEmbedded and Adaptive Computing Group
Hande, Nov 2005
Energy Harvesting Methodologies for Wireless Sensor Nodes
Dinesh BhatiaAssociate Professor
Abhiman HandeResearch Associate
Erik Jonsson School of EngineeringNovember 23, 2005
ZigBeeTM Alliance | Wireless Control That Simply WorksEmbedded and Adaptive Computing Group
Hande, Nov 2005
Outline
Present power requirements in PANs Necessity for alternate sources of energy Available alternative energy sources Energy harvesting issues Energy storage issues Power management strategies Research at UTD’s EACG
ZigBeeTM Alliance | Wireless Control That Simply WorksEmbedded and Adaptive Computing Group
Hande, Nov 2005
Technology Trends
Relative improvements in laptop computing technology from 1990–2003.
ZigBeeTM Alliance | Wireless Control That Simply WorksEmbedded and Adaptive Computing Group
Hande, Nov 2005
Feasible Sources of Energy
Photovoltaic solar cells Amorphous Crystalline
Vibrations Piezoelectric Capacitive Inductive
Radio-Frequency (RF) Thermoelectric conversion Human power Wind/air flow Pressure variations
Harvesting technology Power density
Solar cells (outdoors at noon) 15 mW/cm2
Piezoelectric (shoe inserts) 330 μW/cm3
Vibration (small microwave oven) 116 μW/cm3
Thermoelectric (10oC gradient) 40 μW/cm3
Acoustic noise (100dB) 960 nW/cm3
Power densities of energy harvesting technologies
ZigBeeTM Alliance | Wireless Control That Simply WorksEmbedded and Adaptive Computing Group
Hande, Nov 2005
Feasible Devices for Energy Storage
Batteries Li-ion NiCD NiMH
Ultracapacitors Maxwell Samsung NEC
Micro-fuel cells Micro-heat engines Radioactive power sources Maxwell 5V 2F 2.7 mAhr ultracapacitor
VoltaFlex thin film rechargeable lithium batteries
ZigBeeTM Alliance | Wireless Control That Simply WorksEmbedded and Adaptive Computing Group
Hande, Nov 2005
Energy Harvesting for Wireless Sensor Nodes
VCC
Raw data
Packetized samples
MicrocontrollerA/D converter
Sensors Program and data flash memory
RF communication link
Energy harvesting and energy storage
Energy source
Antenna
Block diagram of an energy harvesting wireless sensing node with data logging and bidirectional RF communications capabilities
ZigBeeTM Alliance | Wireless Control That Simply WorksEmbedded and Adaptive Computing Group
Hande, Nov 2005
Solar Cell Characteristics
10-20 % efficiency outdoors <1% efficiency indoors Needs power management scheme Maximum power point might need tracking
V-I characteristics of a Solar World 4-4.0-100 solar panel
ZigBeeTM Alliance | Wireless Control That Simply WorksEmbedded and Adaptive Computing Group
Hande, Nov 2005
Solar Cell Efficiencies Under Different Light Conditions
ZigBeeTM Alliance | Wireless Control That Simply WorksEmbedded and Adaptive Computing Group
Hande, Nov 2005
Vibrations to Electricity
ZigBeeTM Alliance | Wireless Control That Simply WorksEmbedded and Adaptive Computing Group
Hande, Nov 2005
Comparison of Vibrations to Electricity Methods
Scavenging the power from commonly occurring vibrations for use by low power wireless systems is both feasible and attractive for certain applications.
Piezoelectric converters appear to be the most attractive for meso-scale devices with a maximum demonstrated power density of approximately 200 μW/cm3 vs. 100 μW/cm3 for capacitive MEMS devices.
Electromagnetic converters provide maximum voltage of 0.1 volts
ZigBeeTM Alliance | Wireless Control That Simply WorksEmbedded and Adaptive Computing Group
Hande, Nov 2005
Piezo Converter Set-up
Piezoelectric converter with rectifier and DC-DC converter
ZigBeeTM Alliance | Wireless Control That Simply WorksEmbedded and Adaptive Computing Group
Hande, Nov 2005
Power Management
Charge energy storage devices Route stored energy to sensor node Monitor available energy level Low power buck/boost converter required
VCC to system
Ultracapacitors Batteries
Power ManagementOptional rectification
Solar panels / piezoelectric
element
Dual energy storage mechanism for a wireless sensor node
ZigBeeTM Alliance | Wireless Control That Simply WorksEmbedded and Adaptive Computing Group
Hande, Nov 2005
Research at UTD’s EACG
CrossbowTM MICAz motes 2.4GHz, IEEE 802.15.4 compliant ZigBeeTM transceiver. Mesh networking protocol Potential applications include temperature and light monitoring in
remote locations, measuring tire pressure, monitoring acceleration in automobiles, medical applications, etc.
MICAz mote MICA2 motes
ZigBeeTM Alliance | Wireless Control That Simply WorksEmbedded and Adaptive Computing Group
Hande, Nov 2005
Battery Life Estimation for a MICAz Mote
Processor Currents Example duty cycle Full operation 8 mA 1 %
Sleep mode 8 A 99 % Radio Currents Example duty cycle
Receive mode 8 mA 0.75 % Transmit mode 12 mA 0.25 %
Sleep mode 2 A 99 % Logger Memory Currents Example duty cycle
Write operation 15 mA 0 % Read operation 4 mA 0 %
Sleep mode 2 A 100 % Sensor Board Currents Example duty cycle
Full operation 5 mA 1 % Sleep mode 5 A 99 %
Computed mAhr used each hour Processor 0.0879
Radio 0.0920 Logger Memory 0.0020
Sensor Board 0.0550 Total mAhr used 0.2369
Computed battery life vs. battery size Battery Capacity (mAhr) Battery Life (months)
250 1.45 1000 5.78 3000 17.35
Battery life estimation for a MICAz mote operating at 1% duty cycle
ZigBeeTM Alliance | Wireless Control That Simply WorksEmbedded and Adaptive Computing Group
Hande, Nov 2005
Research Challenges
Set-ups for both solar and vibrational energy Dual energy storage scheme Power management Low power buck converter design
Task 1: Develop designs for energy scavenging prototypes
Task 2: Develop an appropriate power management scheme
Task 3: Identify appropriate components for procurement
Task 4: Implement the prototype designs
Task 5: Testing and modifications
SP SU FA2006 (Y1)
SP SU FA2007 (Y2)
SP SU FA
2008 (Y3)Indicates publications
Tentative research timeline
ZigBeeTM Alliance | Wireless Control That Simply WorksEmbedded and Adaptive Computing Group
Hande, Nov 2005
Conclusions
Acceptable power sources remain perhaps the most challenging technical hurdle to the widespread deployment of wireless sensor networks.
While significant progress has been made in many areas including indoor photovoltaic systems, micro-fuel cells, thermoelectrics, micro-heat engines, and vibration-to-electricity conversion, much more research and new approaches need to be pursued.
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