ENERGY HARVESTING APPLICATION FOR INDUSTRY 4.0. Dr. CARLES FERRER CTO AEInnova

Transcription

1 ENERGY HARVESTING APPLICATION FOR INDUSTRY 4.0 Dr. CARLES FERRER CTO AEInnova

2 Introduction/Motivation Ubiquitous sensor networks Monitoring (environment, wild-life), security, health Conformal and low profile circuit topologies Low cost (manufacturing, material and maintenance) Autonomous operation Operating with high efficiency Minimize dissipated power / maximize harvested power Green networks Environmental friendly, materials and fabrication (Spent batteries pose a significant waste management concern)

3 Introduction/Motivation Power Consumption for various applications Autonomous wireless sensor networks & energy needs

4 Introduction/Motivation Battery operated WSN node vs Energy harvesting node Low-power Sensor e.g. temperature sensor, accelerometer Battery Micro- Controller Wireless Transceiver Battery-operated WSN node Ambient Energy (e.g. solar, thermal, vibration, RF) Energy Harvesting Device Energy Storage Device Low-power Sensor e.g. temperature sensor, accelerometer Micro- Controller Wireless Transceiver Self-powered WSN node

5 Introduction/Motivation Industrial sector is the biggest expected potential economic impact of IoT applications in 2015

6 Introduction/Motivation Market growth of energy harvesting technologies Source: IDTech Nov in M$

7 Energy Source The World of Energy Harvesting Sources Photovoltaic Energy Thermoelectric Energy Vibration Energy Electromagnetic Energy Depends on surface area (# PV cells) DC: 0.5V to 5V Depends on thermal difference DC: 10s of mv to 10V Variability of vibrational frequency AC: 10s of Volts Coupling & rectification AC: Varies with distance Outdoor 10 mw/cm 2 Indoor 10 µw/cm 2 Person 20 µw/cm 2 Machine 1-10 mw/cm 2 Person 4 µw/cm 2 Machine 100 µw/cm 2 GSM 0.1 µw/cm 2 WiFi 0.01 µw/cm 2 Source: IMEC Hoslt

8 Solar Energy Harvesting Photovoltaic effect (Observed by Becquerel 1839) American Society for Testing and Materials (ASTM) reference solar spectra ETR spectral irradiance distribution is modeled a black-body radiation with T= 5800 K Atmosphere absorption bands visible Principles of thermodynamics and black-body radiation allow to estimate performance limits of solar cells (Shockley-Queisser Limit 1961)

9 Solar Energy Harvesting Wafer based solar cells (150 $/m 2 efficiency 20%) Thin film solar cells (30 $/m 2 efficiency 5-10%) Third generation solar cell (high efficiency, low cost) Challenges High efficiency and low cost Integration with other circuitry Indoor conditions?

10 Solar Energy Harvesting

11 Solar Energy Harvesting Solar cell efficiency, measured under AM1.5G at T = 25 o C M.A. Green, K. Emery, Y. Hishikawa and W. Warta, Solar cell efficiency tables (version 38), Progress in Photovoltaics: Research and Applications, vol. 19, pp , May 2011

12 Solar Energy Harvesting Off-Grid Small Solar Power Systems Small field solar power for oil and gas production field and line pipes Small solar panels and enclosure systems dot the landscape, powering all kinds of small electronic monitoring devices and communications in location without grid power Solarcraft

13 Thermal Energy Harvesting Conversion of temperature differences to electrical energy Sources Waste heat from industrial plants Heating systems Automobiles, other vehicles Human body Three thermoelectric phenomena Seebeck Peltier Thomson

14 Thermal Energy Harvesting The Seebeck coefficient is much higher for semiconductor materials rather than metals and metal alloys, where it can reach magnitudes of 1mV/K Thermoelectric generators (TEGs) are formed by pairs of coupled of N-doped and P-doped semiconductor pellets connected electrically in series and placed between two thermally conductive plates.

15 Thermal Energy Harvesting Thermoelectric figure of merit: High Seebeck Coefficient (α) High Electrical Conductivity (σ) Low Thermal Conductivity (λ)

16 Power (mw) Thermal Energy Harvesting Small Thermal Power Systems Small thermoelectrical power generator system for self powered WSN nodes Small TEG devices powering all kinds of small electronic monitoring devices and communications in location without grid power AEInnova Thermal difference ( o C)

17 Kinetic/Vibration Energy Harvesting Characteristics: Conversion of mechanical movements to electrical energy Vibrations Displacements Forces or pressures Sources Traffic Human movement Heating, ventilating and AC (HVAC) Air currents Water movement

18 Kinetic/Vibration Energy Harvesting Transducer types: Electromagnetic (inductive) Faraday s law Electrostatic (capacitive) Vary the capacitance or charge of a variable capacitor Piezoelectric Piezoelectric strain d tensor relating Mechanical Stress T to Electric Displacement D

19 Kinetic/Vibration Energy Harvesting Vibration transducers modeled by mass m, attached to a frame using a spring k [*] Mechanical to electric conversion losses included in d

20 Kinetic/Vibration Energy Harvesting Require low frequency high-q resonators Application dependent:

21 Kinetic/Vibration Energy Harvesting Challenges: Self-tuning / Adaptive tuning, Wideband / Multiband

22 Kinetic/Vibration Energy Harvesting Small Vibration Power Systems Several embodiments, same principle Typically for industrial applications: high g, high f Flexous Hiper-D 79 mw, 5 37 Hz, 204 cm 3 Perpetuum PMG37 92 mw, 1 22 Hz, 522 cm 3

23 Electromagnetic Energy Harvesting Conversion of ambient low power electromagnetic sources to electrical power An Electric field of 1V/m in air corresponds to an EM power density of 0.26 µw/cm 2 Key element: Rectenna (Brown US , 1969). Application dependent. Conversion efficiency for available input power of ~ -20 dbm is 10% - 20%.

24 Electromagnetic Energy Harvesting Challenges: Compact antenna elements, arbitrary polarization, broadband, multi-band designs EM simulation to model radiating element. Nonlinear optimization to model rectenna circuit and optimize rectifier taking into account the antenna properties. Antenna in receiving mode (Norton, Thevenin equivalent, Reciprocity) Measurement campaigns necessary

25 Electromagnetic Energy Harvesting Small Electromagnetic Power Systems RF energy harvesting converts radio waves into DC Power which powers the rest of circuit elements ,2 KHz, tags small and light used on logistics and traceability 13,56 MHz, printed on flexible substrates used on logistics and traceability r= A eff 4π P total P rec MHz, dipole antena trans. 3-8 m, spec. design QI wireless charging modules 5V/1A, TX/RX, size: TX 55X35 mm 2, RX 46x36 mm 2, com. distance 2-6 mm, freq. < 200 KHzefficiency max 73%

26 Sensor Roadmap Sensors Roadmap Power reduction in IoT Current SoA in Energy Harvesting technologies (10µW-15mW) meeting demand of IoT sensors Reduce power consumption per transducer below 100nW, while meeting resolution, bandwith and measurement range constraints.

27 Microcontroller Roadmap Microcontroller Roadmap Power reduction in IoT Current SoA in Energy Harvesting technologies permit part time microcontroller activity Reduce power consumption to new ultra low power in ST 28nm IoT FD-SOI below 10mW, while meeting computing capabilities, power management, RF, security and privacy for larger periods of time

28 AEInnova s Indu-eye Self powered WSN nodes for industry 4.0 Place a sensor in any location: Remote points with thermal energy available Replace batteries as a source of power No need of: Power and communication hardness Completely autonomous by using wireless (WiFi/Bluetooth/LoRa, Sigfox or similar) Reduction by per linear meter of cable No batteries (reduction of cost of annual maintenance)

29 AEInnova s Indu-eye Self powered WSN nodes for industry 4.0 Complet solution including: Thermal battery + sensors + processor + communication + big data in only one product AEInnova Indu-eye A AEInnova Indu-eye B

30 AEInnova s Indu-eye Self powered WSN nodes for industry 4.0 Indu-Eye: High range of temperatures: Min: 15 o C over ambient temperature Max: 250 o C No use of lead technologies (SuperCaps) It can be used outside (IP67) CE and ATEX certified ROI (between 2 months and 1 year) Integration with SCADA platforms and Fiware bigdata

31 AEInnova s Indu-eye Energy Harvesting for control and monitoring in industry 4.0 Self-powered WSN installation: Data: Gas temperature: 120 o C Superficial contact Monitored equipment with WiFi/BT4.0: Parameters: T, CO 2, Humidity, atmospheric pressure Fiware big data: Alerts, predictive maintenance, mailing.

32 AEInnova s WHRU Energy Harvesting for control and monitoring in industry 4.0 Data: Gases temperature = 160 o C Inside diameter: 1.12 m Energy production: Power installed: 250Wh Monitored equipment by 4G: T, CO 2, power generated and reporting Big Data Fiware: Alerts, predictive maintenance, mailing, etc.

33 Thank you for joining us for the global reference IOT INDUSTRY EVENT