A fully integrated autonomous power management system with high power capacity and novel MPPT for thermoelectric energy harvesters in IoT/wearable applications

This paper reports a fully integrated autonomous power management system for thermoelectric energy harvesting with application in batteryless IoT/Wearable devices. The novel maximum power point tracking (MPPT) algorithm does not require open circuit voltage measurement. The proposed system delivers 0.5 mA current with 1 V regulated output based on simulations, which is the highest output current for a fully integrated converter reported in the literature for ultra-low voltage applications, to the best knowledge of the authors. Regulated 1 V output can be achieved for load range >2 k Omega, and input voltage range >140 mV. The circuit has been implemented in UMC-180nm standard CMOS technology and simulated

Анализ методов борьбы с парафиновыми отложениями на месторождениях Западной Сибири

В данной работе рассмотрели проблему парафиновых отложений в систематической и всеобъемлющей форме. В результате исследования были подробно рассмотрены причины образования парафиновых отложений, а также методы борьбы и предупреждение парафиновых отложений.In this paper, we have considered the problem of paraffin deposits in a systematic and comprehensive form. As a result of the study, the reasons for the formation of paraffin deposits, as well as methods for controlling and preventing paraffin deposits, were considered in detail

Oral Cells-On-Chip: Design, Modeling and Experimental Results

Recent advances in periodontal studies have attracted the attention of researchers to the relation between oral cells and gum diseases, which is a real threat to overall human health. Among various microfabrication technologies, Complementary Metal Oxide Semiconductors (CMOSs) enable the development of low-cost integrated sensors and circuits for rapid and accurate assessment of living cells that can be employed for the early detection and control of periodontal diseases. This paper presents a CMOS capacitive sensing platform that can be considered as an alternative for the analysis of salivatory cells such as oral neutrophils. This platform consists of two sensing electrodes connected to a read-out capacitive circuitry designed and fabricated on the same chip using Austria Mikro Systeme (AMS) 0.35 µm CMOS process. A graphical user interface (GUI) was also developed to interact with the capacitive read-out system and the computer to monitor the capacitance changes due to the presence of saliva cells on top of the chip. Thanks to the wide input dynamic range (IDR) of more than 400 femto farad (fF) and high resolution of 416 atto farad (aF), the experimental and simulation results demonstrate the functionality and applicability of the proposed sensor for monitoring cells in a small volume of 1 µL saliva samples. As per these results, the hydrophilic adhesion of oral cells on the chip varies the capacitance of interdigitated electrodes (IDEs). These capacitance changes then give an assessment of the oral cells existing in the sample. In this paper, the simulation and experimental results set a new stage for emerging sensing platforms for testing oral samples

Gi̇yi̇lebi̇li̇r ve IoT uygulamalarında termoelektri̇k enerji̇ hasatı i̇çi̇n tamamen özerk arayüz devresi̇

IoT and wearable electronics are building blocks of the current and future monitoring technologies with numerous applications such as environmental monitoring, precision agriculture, healthcare, transportation and logistics, and smart buildings. Powering the IoT smart nodes is costly due to the existence of billions of these nodes in the technology roadmaps, and is not environmental friendly due to the use of chemical batteries with toxic substances. Eliminating batteries is therefore highly desirable. Fully integrated solutions with sufficient output power capacity for batteryless IoT applications are rarely targeted in the literature. In this thesis, a novel fully autonomous interface circuit for energy harvesting from thermoelectric devices is introduced, which provides considerably increased output power with maximum power point tracking capability at 1 V regulated voltage level. The circuit is composed of a DC-DC converter based on charge pump and LC-tank oscillator with a digital MPPT block, and an LDO regulator. A novel MPPT algorithm is proposed that refrains from disconnecting the circuit form the TEG, and is compatible with varying input and load conditions. Based on the measurement results, the circuit start-up voltage is as low as 170 mV. The output power attains 500 µW, which is the state of the art in the literature for a fully integrated design, and thus meets the real time demand of IoT nodes for sensing, signal processing and wireless data transmission in duty cycle mode and some GHz range. The peak efficiency based on post-layout simulations is 36%, which reduces to 20% due to fabrication mismatches. The discrepancies between simulations and measurements are fully characterized as part of the research, and are modeled to enable design improvements in the future. The MPPT algorithm reaches up to 98% accuracy when the internal resistance of the thermoelectric generator is between 30 Ω to 100 Ω, which is a typical range for a number of tiny TEGs in series.IoT ve giyilebilir elektronik cihazlar, çevresel izleme, hassas tarım, sağlık, ulaşım ve lojistik, ve akıllı binalar gibi sayısız uygulama ile mevcut ve gelecekteki izleme teknolojilerinin yapı taşlarıdır. IoT akıllı düğümlerine güç vermek, teknoloji yol haritalarında bu düğümlerin milyarlarca olmasına bağlı olarak maliyetlidir ve zehirli maddeler içeren kimyasal bataryaların kullanılmasından dolayı çevre dostu değildir. Bataryaları ortadan kaldırmak bu nedenle çok arzu edilir. Bataryasız IoT uygulamaları için tamamen entegre, yüksek çıkış gücü üreten çözümler literatürde nadiren ele alınmıştır. Bu tezde, termoelektrik cihazlardan enerji hasadı için maksimum güç noktası takip (MGNT) özelliği ile 1 V regüle voltaj ve önemli ölçüde artırılmış çıkış gücü sağlayan yeni ve tam otonom bir arayüz devresi önerilmiştir. Devre, şarj pompası ve LC-tank osilatöre dayalı bir DA-DA dönüştürücü ile bir dijital MGNT bloğu ve bir doğrusal regülatörden (LDO) oluşur. Devrenin termoelektrik jeneratör (TEJ) ile bağlantısını kesmeden çalışan, değişken giriş ve yük koşullaıyla uyumlu uyumlu yeni bir MGNT algoritması önerilmiştir. Ölçüm sonuçlarına göre devre başlatma voltajı 170 mV’a kadar inmektedir. Çıkış gücü tam entegre bir çip için literatürde en gelişmiş teknoloji olan 500 µW seviyesine kadar çıkmakta, ölçüm, sinyal işleme ve görev döngüsü modunda ve bazı GHz aralıklarında kablosuz veri iletimi için gerekli olan gerçek zamanlı güç talebini karşılayabilmektedir. Yonga yerleşim sonrası simülasyonlara dayanan en yüksek verimlilik %36'dır; fabrikasyon uyumsuzlukları dolayıslıyla bu değer ölçümde %20'ye düşmektedir. Bu uyumsuzluklar gelecekteki tasarım geliştirmelerini mümkün kılmak için ölçümle karakterize edilmiş ve modellenmiştir. MGNT algoritması, TEJ iç direnci 30 Ω ila 100 Ω arasında olduğunda % 98'e kadar doğruluk oranına ulaşabilmektedir. Bu direnç aralığı, seri bağlanmış bir dizi küçük TEJ için tipiktir.M.S. - Master of Scienc

AI for dynamic packet size optimization of batteryless IoT nodes: a case study for wireless body area sensor networks

Packet size optimization, with the purpose of minimizing the wireless packet transmission energy consumption, is crucial for the energy efficiency of the Internet of Things nodes. Meanwhile, energy scavenging from ambient energy sources has gained a significant attraction to avoid battery issues as the number of nodes increasingly grows. Packet size optimization algorithms have so far been proposed for battery-powered networks that have limited total energy with continuous power availability to prolong their lifetime. On the other hand, batteryless networks based on energy harvesting offer unlimited total energy with the interruption in availability. This is due to changing ambient conditions or the required time for harvesting and storing in small capacitors. Packet size optimization of batteryless networks has not been addressed so far. In this paper, an AI-based packet size optimization algorithm is proposed for batteryless networks that consider the amount of harvested energy at each node. Therefore, packet size is optimized dynamically for each round of data transmission. The proposed method is then evaluated via numerical simulations for a heterogenous wireless body area sensor network as a case study, considering 1-hop, cooperative, and 2-hop communication networks. Cooperative topology yields optimum energy efficiency for highly dynamic sensors, such as ECG, while 2-hop has shown to be optimum for the same type of sensors in battery-powered networks. Also, for sensors with slower dynamics such as body temperature, 1-hop turns out to be optimum in networks solely dependent on energy scavenging while cooperative topology is optimum for battery-powered networks. The algorithm applies to any heterogeneous fully batteryless networks to dynamically optimize packet size at each transmission instance

A Multidisciplinary Approach toward CMOS Capacitive Sensor Array for Droplet Analysis

This paper introduces an innovative method for the analysis of alcohol–water droplets on a CMOS capacitive sensor, leveraging the controlled thermal behavior of the droplets. Using this sensing method, the capacitive sensor measures the total time of evaporation (ToE), which can be influenced by the droplet volume, temperature, and chemical composition. We explored this sensing method by introducing binary mixtures of water and ethanol or methanol across a range of concentrations (0–100%, with 10% increments). The experimental results indicate that while the capacitive sensor is effective in measuring both the total ToE and dielectric properties, a higher dynamic range and resolution are observed in the former. Additionally, an array of sensing electrodes successfully monitors the droplet–sensor surface interaction. However practical considerations such as the creation of parasitic capacitance due to mismatch, arise from the large sensing area in the proposed capacitive sensors and other similar devices. In this paper, we discuss this non-ideality and propose a solution. Also, this paper showcases the benefits of utilizing a CMOS capacitive sensing method for accurately measuring ToE

Fully Integrated 98mV Start Up DC-DC Converter for Energy Harvesting in Batteryless IoT/Wearable Devices

Energy harvesting is an important pillar for large scale exploitation of IoT smart nodes and wearable devices. To this end, DC-DC converters with ultra-low start-up voltage, full integration and high efficiency in a wide input voltage range are required. In this paper a novel one-input, two-output DC-DC converter circuit is introduced. Low-power output provides 0.8-3.5 V with maximum load current of 3.5 mu A starting up from 98 mV input. High-power output is turned on by an ultra-low-power voltage detector when input voltage reaches 150 mV, to provide 0.8-2.4 V with maximum load current of 200 mu A. The circuit has been implemented in UMC 180-nm CMOS technology. Maximum simulated system efficiency is 34% at 0.2 V input. Low-power output meets the real time power demand of sensing, data processing and data storage blocks of IoT/Wearable devices, while high-power output provides sufficient power for data transmission, enabling batteryless operation

Fully Integrated Autonomous Interface With Maximum Power Point Tracking for Energy Harvesting TEGs With High Power Capacity

In this article, a novel fully autonomous and integrated power management interface circuit is introduced for energy harvesting using thermoelectric generators (TEGs) to supply power to Internet of Thing nodes. The circuit consists of a self-starting dc & x2013;dc converter based on a dual-phase charge pump with LC-tank oscillator, a digital MPPT unit, and a 1-V LDO regulator. The novel maximum power point tracking (MPPT) algorithm avoids open-circuit state, and accommodates varying input power and ultra-low voltage conditions. Validation data from the fabricated test-chip in 180 & x00A0;nm standard CMOS technology indicates the circuit start-up voltage is as low as 170 mV. The maximum output power capacity is 0.5 mW, which is the highest noted in the literature for a fully integrated solution. The high output power at low cost is achieved with a peak system efficiency of 30 & x0025;. The relatively low efficiency is expected, since the focus of the design is high power capacity at low cost. The MPPT algorithm reaches 98 & x0025; maximum accuracy for a source output resistance of 40 & x2126;, which is typical for wearable TEG modules

Fully Integrated Ultra-Low Voltage DC-DC Converter with Voltage Quadrupling LC Tank Oscillator for Energy Harvesting Applications

This paper presents a novel fully integrated ultra-low voltage DC-DC converter and its multi-stage architecture. DC-DC converter frequency has been analytically derived using model analysis and validated in Cadence environment. The proposed voltage quadrupling LC tank oscillator eliminates the buffer circuits utilized in the traditional DC-DC converter, hence improves the performance metrics such as efficiency and output power capacity. The circuit was designed in 180nm standard CMOS process and was simulated to self-start and boost 70 mV to deliver 1.4 V to a 1 M Omega load. The minimum start-up voltage of the DC-DC converter is 60 mV. The optimized 2-stage DC-DC converter can yield 1.1 V output and 560 mu W load power with 43% peak efficiency at 0.2 V input. The 3-stage and 4-stage can deliver 1524 mu W and 1193 mu W load power, 1.64 V and 2.18 V output voltage with 40% and 34% peak efficiency respectively at 0.2 V input

A novel calibration-free fully integrated CMOS capacitive sensor for life science applications

CMOS capacitive sensors for label-free monitoring of biological/chemical reactions are typically prone to inaccuracies due to the parasitic elements and mismatch rooted in the CMOS fabrication process as well as real-time changes inside the sample solution. The former can usually be compensated by employing differential circuits and static calibration of the sensor before the experiment. On the other hand, changes in the sample solution such as sedimentation of non-target molecules or change in the conductivity of solution can significantly alter the operating point and result in inaccurate sensor readings that might require recalibration of the sensor during the experiment. In this paper, we present a CMOS capacitive sensor that is calibration-free via the creation of time-resolved three-dimensional (3D) surface electrochemical profiles. These 3D profiles uncover the variations of both target and unwanted parasitic capacitances. The sensor includes on-chip interdigitated electrodes (IDEs), a wide input dynamic range (IDR) differential capacitance-to-current converter, a digitally programable reference capacitor, and an oscillator-based analog-to-digital converter (ADC), and is implemented using 0.35 m AMS CMOS process. The IDR covers a change in capacitance as small as 1 fF up to 1.27 pF with a minimum detectable change of 0.416 fF