Conditioning techniques for real-world sensors

Energy harvesting

Tony Armstrong, director of product marketing for power products at Linear Technology Corp, describes powering remote wireless nodes via renewable energy sources that can be harvested efficiently, given the right harvesting, power-management, and battery-charging devices (see sidebar, “Wireless sensor networks wring more utility from real-world data”). Renewable energy is providing expanded opportunities for energy conversion and more effective use of existing energy, but it also provides an opportunity for energy-harvesting devices to help power wireless sensor networks, commonly used in building-automation and predictive-maintenance applications.

Armstrong notes that the conventional approach for energy harvesting has been through solar panels and wind generators, but emerging energy-harvesting tools enable the generation of electrical energy from a variety of ambient sources. For instance, thermoelectric generators convert heat to electricity, piezo elements convert mechanical vibration, photovoltaics convert sunlight (or any photon source), and galvanics convert energy from moisture. This makes it possible to power remote sensors, or to charge a storage device such as a capacitor or thin-film battery, enabling a microprocessor or transmitter to be powered from a remote location without a local power source.

Linear’s energy-harvesting products provide enabling solutions (Table 1). Specs vary across the line, but the company touts quiescent currents typically less than 6 μA and as low as 450 nA; start-up voltages down to 20 mV; input-voltage capability up to 34V continuous, 40V transient; the ability to handle ac inputs; multipleoutput capability and autonomous system power management; autopolarity operation; maximum-power-point control for solar inputs; the ability to harvest energy from as little as a 1°C temperature delta; and compact solution footprints.

Because solar power is variable, nearly all solar-powered devices feature rechargeable batteries. Clearly, the goal is to extract as much solar power as possible to charge these batteries quickly and to maintain their state of charge.

While solar cells are inherently inefficient devices, they do have a point of maximum output power, so operating at this point is an obvious design goal. The problem, Armstrong observes, is that the IV characteristic of maximum output power changes with illumination. A monocrystalline solar cell’s output current is proportional to light intensity, whereas its voltage at maximum power output is relatively constant. Maximum power output for a given light intensity occurs at the knee of each curve, where the cell transitions from a constant-voltage device to a constant-current device (Figure 6).

Figure 6 The typical maximum-power-point control point for a single photovoltaic cell is shown. Maximum power output for a given light intensity occurs at the knee of each curve, where the cell transitions from a constant-voltage device to a constant-current device (courtesy Linear Technology).

Therefore, a charger design that efficiently extracts power from a solar panel must be able to steer the panel’s output voltage to the point of maximum power when illumination levels cannot meet the charger’s full power requirements. Linear’s LT3652 multichemistry 2A battery charger for solar-power applications uses an input-voltage regulation loop that reduces the charge current if the input voltage falls below a programmed level set by a simple voltage-divider network. When powered by a solar panel, the input-voltage regulation loop maintains the panel at near peak output.

Integrated AFE approach

Complete sensor solutions need to address sensor drive and output requirements, sample rate, signal-path calibration, performance, sensor diagnostics, and power-consumption needs. Simplifying the cycle and reducing development time can mean a faster time to market and more designs completed per year. Most existing approaches, however, address only a few of those issues and are time-consuming and complicated to develop with discrete components.

Texas Instruments’ configurable sensor AFE (analog front-end) ICs and Webench Sensor AFE Designer are part of an integrated hardware and software development platform that lets an engineer select a sensor, design and configure the solution, and download the configuration in minutes. Engineers can evaluate the complete signal-path solution online or on the bench.

Achieving accurate pH measurements in industries such as food processing, water-quality management, and chemical processing involves dealing with design challenges that include extreme temperature variations, high output impedances, offsets, and drifts. TI says its LMP91200 configurable AFE delivers an integrated pH-sensor AFE circuit that interfaces with all available pH sensors and bridges the gap between sensor and microprocessor (Figure 7), addressing the design challenges in an integrated, small form factor.

Figure 7 The LMP91200 configurable AFE delivers an integrated pH-sensor AFE circuit that interfaces with all available pH sensors and bridges the gap between sensor and microprocessor (courtesy Texas Instruments).

TI’s LMP91050 NDIR (nondispersive infrared) gas-sensing AFE, meanwhile, supports multiple thermopile sensors for NDIR sensing, indoor-air-quality monitoring, demand-controlled ventilation, HVAC, alcohol-intake breath analysis, greenhouse-gas monitoring, and Freon detection (Figure 8).

Figure 8 The LMP91050 NDIR gas-sensing AFE supports multiple types of thermopile sensors (courtesy Texas Instruments).

1. Analog Devices, Circuit Note CN0216, “Precision Weigh ScaleDesign Using the AD7791 24-BitSigma-Delta ADC with ExternalADA4528-1 Zero-Drift Amplifiers,” pg 1.
2. Analog Devices, AD8237 data sheet, “Micropower, Zero Drift, TrueRail-to-Rail Instrumentation Amplifier,” pg 26.

Weiss cites some examples of applications enabled by WSNs:

• Vigilent provides intelligent energy management systems, based on its M3 closed-loop control technology, for data centers, telcos, and large commercial buildings. To collect the necessary temperature and humidity data throughout the data center, sensors need to be widely and densely distributed. Retrofitting the data center with communications and power cabling, however, is impractical and cost prohibitive. Vigilent uses wireless connected sensor nodes to address those concerns. In selecting Linear Technology’s Dust Networks SmartMesh solution for its product, Vigilent identified as critical success factors the need for low power consumption, high reliability, and robust security.
• Emerson Process Management helps businesses automate their production, processing, and distribution in the chemical, oil and gas, refining, pulp and paper, power, water and wastewater treatment, metals and mining, food and beverage, life sciences, and other industries. Emerson’s Smart Wireless products and solutions, based on the IEC 62591 wireless standard and incorporating Linear/Dust’s SmartMesh WirelessHART products, extend predictive intelligence into areas previously beyond physical or economic reach.
• Streetline provides smart-parking solutions to cities, garages, airports, universities, and other parking providers (Figure A) and aims to make smart cities a reality through the use of sensor-enabled mobile and Web applications. Streetline needed a wireless networking solution robust enough to function in harsh and dynamic street conditions—one that could be large and dense and that could run for years without a battery change. Streetline’s smartparking solution uses Linear/Dust’s SmartMesh technology in a wireless mesh network overlaid on streets in the Hollywood/ Los Angeles area. Wireless sensors buried in the street pavement track parkingspace availability; the information is then sent wirelessly to smartphone users.

 
Figure A Streetline Networks’ smart-parking management solution uses Linear Technology/Dust Networks’ wireless technology in a wireless mesh network overlaid on urban streets. Wireless sensors buried in the pavement gather information on parking-space availability that is sent wirelessly to smartphone users.

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