* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Download Brian Otis - Techniq..
Variable-frequency drive wikipedia , lookup
History of electric power transmission wikipedia , lookup
Voltage optimisation wikipedia , lookup
Standby power wikipedia , lookup
Spectral density wikipedia , lookup
Electrification wikipedia , lookup
Electric power system wikipedia , lookup
Mains electricity wikipedia , lookup
Audio power wikipedia , lookup
Utility frequency wikipedia , lookup
Power over Ethernet wikipedia , lookup
Alternating current wikipedia , lookup
Power electronics wikipedia , lookup
Rectiverter wikipedia , lookup
Switched-mode power supply wikipedia , lookup
Opto-isolator wikipedia , lookup
Life-cycle greenhouse-gas emissions of energy sources wikipedia , lookup
Distributed generation wikipedia , lookup
Resonant inductive coupling wikipedia , lookup
Techniques for miniaturization of circuits and systems for wireless sensing Brian Otis Wireless Sensing Lab Seattle, WA, USA [email protected] • Vision • Existing technologies • How do we get there? – – – Circuit techniques Energy harvesting techniques Integration techniques Vision: autonomous sensing • Miniaturized devices (a few mm3) • Extremely inexpensive • Frequent radio contact with peers and with basestation • Periodic sensing of environmental parameters (temperature, light, pressure, acceleration etc.) • Flexible deployment in wide variety of biological, manufacturing, or environmental monitoring applications Vision: autonomous sensing • Miniaturized devices (a few mm3) • Extremely inexpensive • Frequent radio contact with peers and with basestation • Periodic sensing of environmental parameters (temperature, light, pressure, acceleration etc.)miniaturization of Critical challenges: - RF Link • Flexible deploymentclock in wide variety of - Reference generation biological, manufacturing, - Power sources or environmental monitoring applications RF Link: existing designs won’t work – why? 1.They are too large. Traditional architectures require multiple off-chip components, high die area, and a large quartz crystal resonator. 2.They consume too much power. Bluetooth & Zigbee (the “low power” standards) consume > 20mW. This eliminates the possibility of energy harvesting. 3. They require high-end processes and high transistor counts. What about RFID? • Case study: Hitachi m-chip • (150x150x7.5)mm3 (168e-6 mm3) • Si Density r=2330kg/m3 mass of one chip = 0.393 mg (small) • Millions of die/wafer • < $0.10 US (cheap) • Interrogator output power: 0.3W • Range: 450mm (limited capabilities) M. Usami et. al, ISSCC 2006 Case Study: Hitachi RFID chip Power harvesting Frequency reference harvesting (100kHz clock) • Power is extracted from incoming RF energy • External antenna (few cm) • Ideal for embedding in secure documentation M. Usami et. al, ISSCC 2006 RFID Interrogators Power dissipation >1W Cost >$100 US Provides two critical functions that are currently impossible to generate on-chip: 1. Accurate quartz-based frequency reference 2. Power source RFID summary 1. RFID chips can be made extremely small and cheap 2. These are radios that harvest their power from an incoming RF signal. RF power falls off quadratically (at best) with distance, resulting in high interrogator power and very short range. 3. There is little energy available for sensing or computation. 4. They cannot form peer-to-peer networks. Research Goal Self-contained wireless sensing systems that can be fabricated exclusively with thin-film processing techniques. This should include: Peer-to-peer Wireless links Computation/Data Storage Chemical/biological Sensors Electrical Sensor Interfaces Energy/Power Source Three steps to autonomy 1. Generate accurate frequency reference locally 2. Generate power locally 3. Develop circuit design techniques for reducing computing/sensing/communication power consumption RF MEMS: path to ultra-small radios? On-Chip Inductors (Q ~10) MEMS Resonators (Q~1000) 100mm ~300mm • MEMS resonators have significantly higher Q than on-chip inductors • Possibility for elimination of quartz resonators • MEMS sensing capabilities System proof-of-concept Can we design an entire low-power radio link using MEMS resonators as a frequency reference? Case Study: 2GHz transceiver for wireless sensors Goal: Use matching RF MEMS resonators on the transmit and receive paths to define carrier frequency 1mm3, 2GHz super-regenerative transceiver 1mm BAW CMOS 2mm • No external components (inductors, crystals, capacitors) • 0.13um CMOS Total Rx: 380uW Range: 30m Datarate: 50kbps • Operates above transistor fT B. Otis et al., IEEE ISSCC 2005 Three steps to autonomy 1. Generate accurate frequency reference locally 2. Generate power locally 3. Develop circuit design techniques for reducing computing/sensing/communication power consumption Energy Harvesting antenna Extracting energy from the environment to power the electronics reduces maintenance costs and increases capabilities PV cell Bottom line: -Approximately 100uW/cm3 available (but efficiency decreases as volume shrinks) -Power consumption of electronics determines wireless sensor volume and capabilities Thermoelectric energy harvesting Why thermoelectric? • Large, stable temperature gradients often exist in ubiquitous sensing applications • Monolithic, solid state, possible to integrate with circuitry How does it work? • Converts thermal gradient to electric potential via Seebeck effect • Thermocouples connected in series as a thermopile increases voltage (and resistance) • Radioisotope powered TEGs widely used in space missions Work-in-progress: • SOI-based mTEG • p,n silicon thermoelements • Floating membrane increases thermal isolation Three steps to autonomy 1. Generate accurate frequency reference locally 2. Generate power locally 3. Develop circuit design techniques for reducing computing/sensing/communication power consumption -> example: sensor ID generation Inexpensive, low power sensor identification 10101111 00110101 0111001 • • • • Wireless sensor network addressing Object identification for Radio Frequency ID (RFID) tags Wafer and process tracking of individual chips for failure analysis Tracking for implantable electronics devices Can we extract a unique digital fingerprint from process variations? ID Generating Circuit Requirements • ID circuit must generate a digital output • ID code must be repeatable and reliable over supply, temperature, aging and thermal noise • The ID code length and stability must allow positive unique identification of each die • Low power consumption, no calibration Proposed Idea: positive feedback ID generation B A voltage (V) • Each ID cell: cross-coupled gates used to amplify transistor mismatch A B time(s) – Evaluation period Node A and B will split due to transistor mismatch – Readout period Digital-level output will be obtained directly at ID node Chip Implementation • 128 ID generators – 140nW @ 1V • Technology: 0.13mm CMOS • Provides stable fingerprint with extremely high probability of correct chip identification Su, Holleman, Otis, IEEE ISSCC 2007 Conclusions 1. Wireless sensor scaling is constrained by energy source, antenna dimensions, and frequency reference 2. Self-contained wireless sensors less than 1mm3 are on the horizon 3. Future chips will include circuitry, EM elements, MEMS structures, sensors, and power generation 4. Interdisciplinary collaboration is critical to focus our efforts on relevant sensing problems 500um