Un nuevo rectificador reconfigurable CMOS para recolectores de energía piezoeléctrica en dispositivos portables

Los recolectores de energía para dispositivos portables tienen una aplicación potencial en la conversión de la energía del movimiento humano en energía eléctrica para alimentar dispositivos inteligentes de monitoreo de la salud, de la industria textil, así como de relojes y lentes inteligentes. Estos recolectores de energía requieren circuitos rectificadores óptimos que maximicen sus eficiencias de carga. En este estudio se presenta el diseño de un novedoso rectificador reconfigurable metal óxido semiconductor complementario (CMOS) para recolectores de energía piezoeléctrica portables que puede aumentar sus eficiencias de carga. El rectificador diseñado se basa en la tecnología de proceso CMOS estándar de 0,18 µm considerando un patrón geométrico con un área total de silicio de . El circuito rectificador propuesto tiene dos puertas de transmisión (TG) que están compuestas por cuatro transistores rectificadores con una carga de 45 kΩ, un voltaje mínimo de entrada de 500 mV y un voltaje máximo de 3,3 V. Los resultados de las simulaciones numéricas del funcionamiento del rectificador indican una eficiencia de conversión de voltaje del 99,4 % y una eficiencia de conversión de potencia de hasta el 63,3 %. El rectificador propuesto puede utilizarse para aumentar la eficiencia de carga de los recolectores de energía piezoeléctrica portables.Wearable energy harvesters have potential application in the conversion of human-motion energy into electrical energy to power smart health-monitoring devices, the textile industry, smartwatches, and glasses. These energy harvesters require optimal rectifier circuits that maximize their charging efficiencies. In this study, we present the design of a novel complementary metal-oxide semiconductor (CMOS) reconfigurable rectifier for wearable piezoelectric energy harvesters that can increase their charging efficiencies. The designed rectifier is based on standard 0.18 µm CMOS process technology considering a geometrical pattern with a total silicon area of 54.765 µm x 86.355 µm. The proposed rectifier circuit has two transmission gates (TG) that are composed of four rectifier transistors with a charge of 45 kΩ, a minimum input voltage of 500 mV and a maximum voltage of 3.3 V. Results of numerical simulations of the rectifier performance indicate a voltage conversion efficiency of 99.4% and a power conversion efficiency up to 63.3%. The proposed rectifier can be used to increase the charging efficiency of wearable piezoelectric energy harvesters

Review of Si-Based Thin Films and Materials for Thermoelectric Energy Harvesting and Their Integration into Electronic Devices for Energy Management Systems

Energy harvesters are autonomous systems capable of capturing, processing, storing, and utilizing small amounts of free energy from the surrounding environment. Such energy harvesters typically involve three fundamental stages: a micro-generator or energy transducer, a voltage booster or power converter, and an energy storage component. In the case of harvesting mechanical vibrations from the environment, piezoelectric materials have been used as a transducer. For instance, PZT (lead zirconate titanate) is a widely used piezoelectric ceramic due to its high electromechanical coupling factor. However, the integration of PZT into silicon poses certain limitations, not only in the harvesting stage but also in embedding a power management electronics circuit. On the other hand, in thermoelectric (TE) energy harvesting, a recent approach involves using abundant, eco-friendly, and low-cost materials that are compatible with CMOS technology, such as silicon-based compound nanostructures for TE thin film devices. Thus, this review aims to present the current advancements in the fabrication and integration of Si-based thin-film devices for TE energy harvesting applications. Moreover, this paper also highlights some recent developments in electronic architectures that aim to enhance the overall efficiency of the complete energy harvesting system

Multimodal Power Management Based on Decision Tree for Internet of Wearable Things Systems

Precision medicine is now evolving to include internet-of-wearable-things (IoWT) applications. This trend requires the development of novel systems and digital signal processing algorithms to process large amounts of data in real time. However, performing continuous measurements and complex computational algorithms in IoWT systems demands more power consumption. A novel solution to this problem consists in developing energy-aware techniques based on low-power machine learning (ML) algorithms to efficiently manage energy consumption. This paper proposes a multimodal dynamic power management strategy (DPMS) based on the ML-decision tree algorithm to implement an autonomous IoWT system. The multimodal approach analyzes the supercapacitor storage level and the incoming biosignal statistics to efficiently manage the energy of the wearable device. A photoplethysmography (PPG) sensing prototype was developed to evaluate the proposed ML-DPMS programmed in a Nordic nRF52840 processor. The experimental results demonstrate an IoWT system’s low consumption of 25.74 J, and a photovoltaic solar power generation capacity of 380 mW. The proposed ML-DPMS demonstrates a battery life extension of 3.87×, i.e., 99.72 J of energy harvested, which represents the possibility to achieve at least 2.4× more data transmissions, in comparison with the widely used uniform power management approach. In addition, when the supercapacitor’s energy is compromised, the decision tree technique achieves a good energy conservation balance consuming in the same period of time 39.6% less energy than the uniform power approach