CHANCE: Capacitor Charging Management Scheme in Energy Harvesting Systems

• Published in: IEEE transactions on computer-aided design of integrated circuits and systems Vol. 40; no. 3; pp. 419 - 429
• Main Authors: Hoseinghorban, Ali, Bahrami, Mohammad Reza, Ejlali, Alireza, Abam, Mohammad Ali
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.03.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Capacitors; Charging; Energy consumption; Energy harvesting; Energy harvesting system; Energy storage; Failure rates; Nonvolatile memory; Random access memory; Response time; Static random access memory; Task analysis; worst case energy consumption (WCEC)
• ISSN: 0278-0070; 1937-4151
• DOI: 10.1109/TCAD.2020.3003295

The energy efficiency of emerging nonvolatile processors equipped with FRAM-SRAM memory makes them a promising solution for energy harvesting systems. To enable correct functionality and forward progress with an unreliable power supply, the system must accumulate sufficient energy in the capacitor to execute tasks atomically, even in the worst case scenario. Due to the large gap between the average and worst case energy consumption of tasks, state-of-the-art approaches like eM-map require a large capacitor to execute tasks on the SRAM. However, the size, cost, and charging time of the capacitor are major concerns in the energy harvesting systems. In this article, we proposed CHANCE, a capacitor charging management scheme that improves the capacitor size and average response time of an energy harvesting system. CHANCE analyses the energy consumption of tasks to set an appropriate capacitor size to make a balance between capacitor charging time and failure rate for each task. The results show that CHANCE improves the response time of state-of-the-art approaches up to 68% with a five times smaller capacitor.