An 18 nA, 87% Efficient Solar, Vibration and RF Energy-Harvesting Power Management System With a Single Shared Inductor

Chowdary, Gajendranath; Singh, Arun Kumar; Chatterjee, Shouri

doi:10.1109/jssc.2016.2585304

Cited by 96 publications

(47 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Finally, one important design aspect is that the total power consumption of the PMU circuitry should be negligible when compared to the power delivered to the load (particularly during standby mode). This imposes design constraints for a PMU to operate in the regime of a few microwatts or even nanowatts [17][18][19]. This in itself is also a very challenging design goal.…”

Section: Iot End-node Architecture and Power Management Unitsmentioning

confidence: 99%

“…The oscillator (one for each source) continues the MPPT operation, and the comparator is powered down to save power. With this strategy, power can be harvested even at the nanowatts level [19].…”

Section: Shared-inductor Dc-dc Convertersmentioning

confidence: 99%

“…Fast comparators are then needed to maintain good MPPT tracking accuracy, and they come with higher power consumption. In [19] this problem is solved by using a shared comparator for all input sources, and then tuning an oscillator to mimic the output of the comparator. The oscillator (one for each source) continues the MPPT operation, and the comparator is powered down to save power.…”

Section: Shared-inductor Dc-dc Convertersmentioning

confidence: 99%

See 2 more Smart Citations

Multiple Input Energy Harvesting Systems for Autonomous IoT End-Nodes

Estrada-López

Abuellil

Zeng

et al. 2018

JLPEA

View full text Add to dashboard Cite

Abstract:The Internet-of-Things (IoT) paradigm is under constant development and is being enabled by the latest research work from both industrial and academic communities. Among the many contributions in such diverse areas as sensor manufacturing, network protocols, and wireless communications, energy harvesting techniques stand out as a key enabling technology for the realization of batteryless IoT end-node systems. In this paper, we give an overview of the recent developments in circuit design for ultra-low power management units (PMUs), focusing mainly in the architectures and techniques required for energy harvesting from multiple heterogeneous sources. The paper starts by discussing a general structure for IoT end-nodes and the main characteristics of PMUs for energy harvesting. Then, an overview is given of different published works for multisource power harvesting, observing their main advantages and disadvantages and comparing their performance. Finally, some open areas of research in multisource harvesting are observed and relevant conclusions are given.

show abstract

Section: Iot End-node Architecture and Power Management Unitsmentioning

confidence: 99%

Section: Shared-inductor Dc-dc Convertersmentioning

confidence: 99%

Section: Shared-inductor Dc-dc Convertersmentioning

confidence: 99%

See 1 more Smart Citation

Multiple Input Energy Harvesting Systems for Autonomous IoT End-Nodes

Estrada-López

Abuellil

Zeng

et al. 2018

JLPEA

View full text Add to dashboard Cite

show abstract

“…The management circuit in the circuit is mainly responsible for managing the charging and discharging of the lithium batteries, but cannot carry on the MPPT to the solar energy, and has not realized the full use of energy [1]. Compared with Prometheus system, C. Park and some scholars designed AmbiMax, which makes use of the method of maximum power point tracking to store the solar panel output energy in the capacitor, and the system also collects wind power for the charging of the super capacitors [2,3]. However, due to the large capacity of the selected super capacitors, the leakage phenomenon of the super capacitors is also very serious, and the system does not deal with the leakage of super capacitors very well.…”

Section: Literature Reviewmentioning

confidence: 99%

Design of Solar Power Management Circuit Based on Wireless Sensor Network

Jianying

2017

Int. J. Onl. Eng.

View full text Add to dashboard Cite

Abstract-To explore the design of solar power management circuit, the fuzzy logic control algorithm based on MPPT, which has fast control speed and good environment robustness, is adopted as the control algorithm. In addition, the MPPT solar battery charge and discharge power management circuit is designed and successfully applied in the on-line measurement projects of dielectric loss of wireless sensor network in Jilin Province LG Electronics Company. The results show that the charging efficiency of solar battery charge and discharge power management circuit can reach above 80%, and the current of static power management circuit is less than 1mA. In different light intensities, the dynamic power management is intelligently carried out. At last, it is concluded that the stability and reliability of circuit are quite high.Keywords-Wireless sensor, power management, circuit design IntroductionIn the research on solar power supply, the control algorithms of MPPT in the past are divided into the following three categories: indirect control method based on parameter selection, direct control method based on sampled data, and intelligent control method based on modern control theory. Among them, the algorithm based on parameter selection is comparatively simple, but it cannot adapt to the influence of environment change on the parameters of solar panel. The control method based on sampled data is dynamic, which makes the maximum power point tracking according to environmental conditions, but the tracking is too slow. The MPPT algorithm based on the modern control theory makes up for the shortcomings of the above two algorithms, and it can achieve better maximum power point tracking. Compared with the previous two algorithms, this algorithm is more complex. Fuzzy logic control algorithm has the characteristics of fast control speed, good environment robustness and simple algorithm realization. As a result, it is chosen as the control algorithm for further study.

show abstract

“…Given that the energy required by a sensor node can be relatively constant for a specific application, it is necessary to capture the energy from energy harvesters at their maximum power point (MPP) to ensure that the harvested energy is able to meet the energy demand either immediately or after accumulation of energy within a reasonable timeframe. To date, a few methods that can find the MPP of energy harvesters have been reported, for example, hill-climbing method [1], [2] and fractional opencircuit voltage (FOCV) method [3], [4].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Maximum Power Point Finding Using Direct V _OC/2 Tracking Method With Microwatt Power Consumption for Energy Harvesting

Chew

Zhu

2018

IEEE Trans. Power Electron.

View full text Add to dashboard Cite

Abstract-Maximum power transfer occurs in many energy harvesters at their half open-circuit voltage (V OC /2).A novel implementation method of maximum power point finding based on the V OC /2 method is presented by exploiting the capacitor charging voltage across a smoothing capacitor connected in parallel with the energy harvester. The presented technique has a specifically designed high-pass filter which has a peak output voltage that corresponds to the V OC /2 of the energy harvester. The control circuit filters and differentiates the voltage across the smoothing capacitor to directly determine the timing of reaching the V OC /2 of the energy harvester without having to find the V OC first, and is fully implemented using discrete analog components without the need of a programmable controller, leading to low power consumption of the method. In this paper, the control circuit is used in conjunction with a full wave diode bridge rectifier and a dc-dc converter to harvest energy from a piezoelectric energy harvester (PEH) as the studied case. The PEH was subjected to various strain levels at low frequencies from 2 to 10 Hz. Experimental results show that the implemented circuit is adaptive to various vibration amplitudes and frequencies and has a maximum power point finding efficiency of up to 98.28% with power consumption as low as 5.16 µW.

show abstract

An 18 nA, 87% Efficient Solar, Vibration and RF Energy-Harvesting Power Management System With a Single Shared Inductor

Cited by 96 publications

References 22 publications

Multiple Input Energy Harvesting Systems for Autonomous IoT End-Nodes

Multiple Input Energy Harvesting Systems for Autonomous IoT End-Nodes

Design of Solar Power Management Circuit Based on Wireless Sensor Network

Adaptive Maximum Power Point Finding Using Direct V _OC/2 Tracking Method With Microwatt Power Consumption for Energy Harvesting

Contact Info

Product

Resources

About

An 18 nA, 87% Efficient Solar, Vibration and RF Energy-Harvesting Power Management System With a Single Shared Inductor

Cited by 96 publications

References 22 publications

Multiple Input Energy Harvesting Systems for Autonomous IoT End-Nodes

Multiple Input Energy Harvesting Systems for Autonomous IoT End-Nodes

Design of Solar Power Management Circuit Based on Wireless Sensor Network

Adaptive Maximum Power Point Finding Using Direct V OC/2 Tracking Method With Microwatt Power Consumption for Energy Harvesting

Contact Info

Product

Resources

About

Adaptive Maximum Power Point Finding Using Direct V _OC/2 Tracking Method With Microwatt Power Consumption for Energy Harvesting