Cong Wang

Bio: Cong Wang is an academic researcher from Tsinghua University. The author has contributed to research in topics: Photovoltaic system & Energy harvesting. The author has an hindex of 4, co-authored 8 publications receiving 164 citations.

Storage-Less and Converter-Less Photovoltaic Energy Harvesting With Maximum Power Point Tracking for Internet of Things

Abstract: Energy harvesting from natural environment gives range of benefits for the Internet of things. Scavenging energy from photovoltaic (PV) cells is one of the most practical solutions in terms of power density among existing energy harvesting sources. PV power systems mandate the maximum power point tracking (MPPT) to scavenge the maximum possible solar energy. In general, a switching-mode power converter, an MPPT charger, controls the charging current to the energy storage element (a battery or equivalent), and the energy storage element provides power to the load device. The mismatch between the maximum power point (MPP) current and the load current is managed by the energy storage element. However, such architecture causes significant energy loss (typically over 20%) and a significant weight/volume and a high cost due to the cascaded power converters and the energy storage element. This paper pioneers a converter-less PV power system with the MPPT that directly supplies power to the load without the power converters or the energy storage element. The proposed system uses a nonvolatile microprocessor to enable an extremely fine-grain dynamic power management in a few hundred microseconds. This makes it possible to match the load current with the MPP current. We present detailed modeling, simulation, and optimization of the proposed energy harvesting system including the radio frequency transceiver. Experiments show that the proposed setup achieves an 87.1% of overall system efficiency during a day, 30.6% higher than the conventional MPPT methods in actual measurements, and thus a significantly higher duty cycle under a weak solar irradiance.

Storage-less and converter-less maximum power point tracking of photovoltaic cells for a nonvolatile microprocessor

Abstract: This paper pioneers the maximum power point tracking (MPPT) of photovoltaic (PV) cells that directly supply power to a microprocessor without an energy storage element (a battery or a large-size capacitor) nor power converters. The maximum power point tracking is conventionally performed by an MPPT charger that stores in the energy storage element, and a voltage regulator (typically a DC-DC converter) produces a proper voltage level for the microprocessor. The energy storage element is an energy buffer and makes it possible to perform MPPT of the PV cells and power management of the microprocessor independently. However, the energy storage element, MPPT charger and DC-DC converter cause seriously limited lifetime (when a typical battery is adopted), significant energy loss (typically over 20%), increased weight/volume and high cost, etc. The proposed method enables extremely fine-grain dynamic power management (DPM) in every a few hundred microseconds and performs the MPPT without using an MPPT charger and a DC-DC converter as well as an energy storage element. We achieve 84.5% of energy harvesting efficiency using the proposed setup with huge reduction in cost, weight and volume, and extended lifetime, which is not even numerically comparable with conventional MPPT methods.

A high-efficiency dual-channel photovoltaic power system for nonvolatile sensor nodes

Abstract: With the development of the internet of things, battery maintaining of trillion sensor nodes becomes prohibitive both in time and costs. Power system with energy harvesting provides a promising solution. However, conventional energy harvesting systems with storage suffer from low efficiency because of conversion loss, storage leakage and so on. Direct supply systems without an energy buffer can achieve high efficiency, but fail to satisfy quality of service due to mismatches between energy harvesting and workloads. This paper proposes a novel dual-channel photovoltaic power system which hybrids a direct power path and a conventional supercapacitor power path. A power management unit is developed to control the channels according to real time solar condition. The nonvolatile processor enables the node system to run reliably and efficiently under varying solar profiles. We develop a simulation platform with real component parameters to validate the proposed techniques. Experimental results demonstrate up to 31.87% energy efficiency improvement under same design cost against the conventional architecture.

Power System Design and Task Scheduling for Photovoltaic Energy Harvesting Based Nonvolatile Sensor Nodes

Abstract: This chapter proposes a novel high-efficiency PV power system for nonvolatile sensor nodes. It demonstrates that the storage-less and converter-less system achieves near 90 % energy efficiency by eliminating energy loss from power converters and storage devices. Furthermore, we propose a dual-channel power supply architecture to improve the quality of service when there are time mismatches between harvested energy and workload. A channel controller dynamically selects either direct channel or indirect one to maximize the energy efficiency under failure rate constraints. Both a simulation platform and a prototype are built to validate the architecture. Finally, we presented an intra-task scheduling algorithm for the storage-less and converter-less channel, which leverages neural network training based on solar profiles and task execution. Compared to the inter-task scheduling, it tracks solar variations more quickly and a much lower deadline missing rate is achieved.

Demodulation method and device of signal difference

Abstract: The invention provides a demodulation method and a device of signal difference The demodulation method comprises the steps of inputting a sampling signal, wherein the sampling signal is a plurality of sampling points of a synchronized code element and comprises a plurality of receiving chips; processing the plurality of sampling points of N receiving chips before a current receiving chip with regard to the ith sequence of a signal set, and using a result which is obtained after the processing of the sampling points as a difference reference of the current receiving chip; carrying out conjugation multiplication between the current receiving chip and each sampling point in the difference reference, and obtaining a judgment scale of the current receiving chip in ith sequence by carrying out addition operation; adding the judgment scales of n continuous chips, and obtaining a judgment scale relative to the ith sequence, wherein the n is the length of the sequence; analyzing the judgment scale according to the judgment scale relative to the ith sequence, carrying out reversed reflection according to an analyzing result and a protocol, and obtaining demodulation data , and finally outputting the demodulation data According to the demodulation method of the signal difference, error code performance can be improved, and complexity for realizing of hardware is reduced The invention further provides the demodulation device of the signal difference

An Autonomous Wireless Body Area Network Implementation Towards IoT Connected Healthcare Applications

Abstract: Internet of Things (IoT) is a new technological paradigm that can connect things from various fields through the Internet. For the IoT connected healthcare applications, the wireless body area network (WBAN) is gaining popularity as wearable devices spring into the market. This paper proposes a wearable sensor node with solar energy harvesting and Bluetooth low energy transmission that enables the implementation of an autonomous WBAN. Multiple sensor nodes can be deployed on different positions of the body to measure the subject’s body temperature distribution, heartbeat, and detect falls. A web-based smartphone application is also developed for displaying the sensor data and fall notification. To extend the lifetime of the wearable sensor node, a flexible solar energy harvester with an output-based maximum power point tracking technique is used to power the sensor node. Experimental results show that the wearable sensor node works well when powered by the solar energy harvester. The autonomous 24 h operation is achieved with the experimental results. The proposed system with solar energy harvesting demonstrates that long-term continuous medical monitoring based on WBAN is possible provided that the subject stays outside for a short period of time in a day.

Powering the internet of things

Abstract: Various industry forecasts project that, by 2020, there will be around 50 billion devices connected to the Internet of Things (IoT), helping to engineer new solutions to societal-scale problems such as healthcare, energy conservation, transportation, etc. Most of these devices will be wireless due to the expense, inconvenience, or in some cases, the sheer infeasibility of wiring them. Further, many of them will have stringent size constraints. With no cord for power and limited space for a battery, powering these devices (to achieve several months to possibly years of unattended operation) becomes a daunting challenge. This paper highlights some promising directions for addressing this challenge, focusing on three main building blocks: (a) the design of ultra-low power hardware platforms that integrate computing, sensing, storage, and wireless connectivity in a tiny form factor, (b) the development of intelligent system-level power management techniques, and (c) the use of environmental energy harvesting to make IoT devices self-powered, thus decreasing -- in some cases, even eliminating -- their dependence on batteries. We discuss these building blocks in detail and illustrate case-studies of systems that use them judiciously, including the QUBE wireless embedded platform, which exploits the characteristics of emerging non-volatile memory technologies to seamlessly and efficiently enable long-running computations in systems that experience frequent power loss (i.e., intermittently powered systems).

Ambient energy harvesting nonvolatile processors: from circuit to system

Abstract: Energy harvesting is gaining more and more attentions due to its characteristics of ultra-long operation time without maintenance. However, frequent unpredictable power failures from energy harvesters bring performance and reliability challenges to traditional processors. Nonvolatile processors are promising to solve such a problem due to their advantage of zero leakage and efficient backup and restore operations. To optimize the nonvolatile processor design, this paper proposes new metrics of nonvolatile processors to consider energy harvesting factors for the first time. Furthermore, we explore the nonvolatile processor design from circuit to system level. A prototype of energy harvesting nonvolatile processor is set up and experimental results show that the proposed performance metric meets the measured results by less than 6.27% average errors. Finally, the energy consumption of nonvolatile processor is analyzed under different benchmarks.

Towards a Green and Self-Powered Internet of Things Using Piezoelectric Energy Harvesting

Abstract: The Internet of Things (IoT) is a revolutionizing technology which aims to create an ecosystem of connected objects and embedded devices and provide ubiquitous connectivity between trillions of not only smart devices but also simple sensors and actuators. Although recent advancements in miniaturization of devices with higher computational capabilities and ultra-low power communication technologies have enabled the vast deployment of sensors and actuators everywhere, such an evolution calls for fundamental changes in hardware design, software, network architecture, data analytics, data storage, and power sources. A large portion of the IoT devices cannot be powered by batteries only anymore, as they will be installed in hard to reach areas and regular battery replacement and maintenance are infeasible. A viable solution is to scavenge and harvest energy from the environment and then provide enough energy to the devices to perform their operations. This will significantly increase the device life time and eliminate the need for the battery as an energy source. This survey aims at providing a comprehensive study on energy harvesting techniques as alternative and promising solutions to power the IoT devices. We present the main design challenges of the IoT devices in terms of energy and power and provide design considerations for a successful implementation of self-powered the IoT devices. We then specifically focus on piezoelectric energy harvesting as one of the most promising solutions to power the IoT devices and present the main challenges and research directions. We also shed lights on the hybrid energy harvesting for the IoT and security challenges of energy harvesting enabled the IoT systems.