Numerous opportunities exist for ultra-low-power (ULP) energy-harvesting technologies and related power-management ICs and energy storage. The challenge in analyzing this market boils down to the sheer number of potential applications and the requirements of each market, many of which overlap with portable applications. Any “roadmap to commercialization” has to consider not only pricing, but also the technology performance metrics that must be matched to appropriate application segments.
Energy harvesting has an “edge” over batteries, which are often needed in large quantities and then have to be replaced. But before energy-harvesting devices can be widely deployed, a case must be made for them as a power source alternative to energystorage- based solutions. Darnell Group’s report on “Energy Harvesting, Micro Batteries & Power Management ICs: Market Forces and Demand Characteristics”(www.darnell.com/eh) identifies six “critical success factors” that could open opportunities for energy harvesting:
• Applications: The “early adopters” of energy harvesting are building automation systems,
particularly lighting control. Emerging opportunities include automated meter reading, medical
applications, military/aerospace applications, tire-pressure sensing, and RFID.
• Standards/architectures: Nearly half of the wireless sensing network nodes deployed in 2007 were based on IEEE 802.15.4, which includes WirelessHART, ISA100, and ZigBee. Although several proprietary technologies have been deployed, the race is boiling down to industrial versus consumer/commercial standards. Energy efficiency regulations will also drive adoption, particularly where there are tax incentives involved. The U.S. Energy Policy Act of 2005, for example, contains an “Energy-efficient Commercial Building Deduction.” Most wireless sensor network energy-harvesting architectures have been “custom” solutions to meet very specific applications. In the next few years, expect the arrival of standard architectures based on the increasingly focused standards mentioned above. These will have power implications, particularly the utilization of power in the system.
• Power costs: Wireless sensor nodes (WSNs) have different “power costs” based on function. Energy harvesting is touted as a solution only for applications that use very, very small amounts of power intermittently. If looking at a single function, this is true. But energy harvesting is a “system solution,” so the entire WSN system needs to be considered when computing the overall power cost. Sleep mode accounts for over 98% of system time, so the actual average “worst-case” power cost is about 400 µW. It could be as low as 10 µW. This system power cost range is closer to what energy harvesting can deliver.
• Installation costs: Most wireless networks being deployed augment an existing wired network. The commercial readiness of thin-film battery technologies now makes it possible for battery backup along with energy-harvesting solutions, without the size, maintenance, and replacement issues of traditional batteries. Neither battery-based solutions nor energyharvesting solutions are significant contributors to the cost of an overall wireless-sensor-network system. The value has to be based on the relative cost of using traditional battery solutions versus an energy-harvesting solution, at installation. A comparison of three companies’ solutions showed a cost reduction of anywhere from 10% to 90%.
• Process technologies and price decline: As they are replaced by newer process technologies, older CMOS processes can enable emerging technologies when they “come down the food chain.” With die sizes shrinking each generation, the cost is cut in half every four to eight years. Thus, energy harvesting could become more cost-effective than existing solutions.
• Materials: Optimizing energy-harvesting performance via advanced materials is a major focus of both researchers and companies developing energy-harvesting technologies. Such materials will drive down costs either due to improved performance at acceptable cost increases; suitability to microfabrication; easy integration into standard complementary CMOS technologies; or increasing service life.
Linnea Brush, senior research analyst at the Darnell Group, holds a BA from California State Polytechnic University, Pomona. She has over 15 years of experience as a research analyst, technical writer, and editor.