基于涡激振动的微型风能采集研究

由于体积大、污染环境、需要定期更换,传统电池供能方式已不能适应当前外场工作的需求.涡激振动的微型风能采集装置将风能转换成电能,能够对无线传感节点等微型电子设备直接供电.基于经典Buck-Boost电路,提出了一种适用于涡激振动微型风能采集的能量接口电路.通过理论与仿真分析,所设计的能量接口电路存在最优占空比,及其对应的最大功率点.基于LabVIEW平台设计了控制程序,实验结果表明,所设计的电路与程序能够对占空比进行自动寻优,保持微型风能采集装置以最大功率输出.     

一种悬臂梁式MSMA振动能量采集器研究

振动能量在自然界中广泛存在,利用智能材料收集振动能量为微电子系统供电是新能源领域的发展趋势。该文利用新型智能材料磁控形状记忆合金（MSMA）的逆效应研究设计了一种基于悬臂梁式的MSMA振动能量采集器,对采集器的各部分结构进行理论分析和系统设计,并建立了振动能量采集器的结构模型。利用ANSYS软件对磁场进行有限元分析,验证了磁场回路和磁感应强度满足采集振动能量的要求。在此基础上,研制了采集器样机,并通过搭建实验平台对采集器进行实验测试,结果表明,该悬臂梁式MSMA振动能量采集器具有较宽的振动能量采集频带,输出电压可达220 mV,为振动能量的收集利用提供了参考依据。     

能量采集破解物联网发展困局

传感器作为物联网的重要组成部分,更是得到了业界的充分关注,在技术水平上取得了一定的突破,无线传感器如何获取能量?电池供电是较为传统的方法,然而电池的供电时间毕竟有限,随着传感器的数量和规模的飞速增长,给传感器更换电池太不现实,能量采集成为物联网行业需要突破的重点。     

超低电压能量收集器利用废热为无线传感器供电

测量和控制所需的超低功率无线传感器用量的激增,再加上新型能量采集技术的运用,使得由局部环境能量而非电池供电的全自主型系统出现了。     

基于抗磁悬浮的摩擦电式振动能量收集器

针对目前传统电池供电方式无法满足无线传感网络需要长期、持久工作的要求,提出了一种基于抗磁悬浮的摩擦电式振动能量收集器,通过将环境中广泛存在的能量转化为电能,实现对无线传感网络长期、稳定的供电。利用搭建的实验测试平台,研究了采集时间、激励加速度及负载电阻对输出性能的影响。实验结果表明,输出电压随着采集时间的增长出现先增大后趋于稳定的趋势;当激励加速度分别为0.2g、0.4g和0.6g时,最大输出电压分别为21.4、29.3和35.6 V,所对应的激励频率分别为19、25和28 Hz;当负载电阻约为1×10⁷Ω时,振动能量收集器的最大输出功率为123μW,与之相对应的输出电压为38 V。     

基于校园环境监测的无线传感器网络节点设计

本文针对校园环境监测的需求,设计一种基于CC2530芯片的无线传感器网络节点,节点采用太阳能模块供电,有效避免了因能量耗尽而失效的问题;传感器节点采用温湿度传感器、光强度传感器等传感器对环境中温度、湿度和光强度等进行采集,满足对环境的基本监测功能。     

压电式振动能量采集装置研究进展

压电振动能量采集装置具有结构简单,能量密度高,寿命长等优点,在无线传感器网络、嵌入式系统和MEMS等低耗能电子设备自供电方面具有广阔的应用前景。针对提高振动能量采集能力和采集效率2个目标,根据设计压电振动能量采集装置的关键技术,从压电材料、压电元件工作模态、压电振子结构、振动支撑结构和共振频率调节方法等方面对压电振动能量采集装置的国内外研究现状进行了详细论述,指出了压电振动能量采集装置的研究前景。     

振动为无线传感器供电

通过诸如802.15.(4Zigbee及其它类似的标准)等通信协议来通告测量结果的无线传感器的概念正在日趋普及。该思想的一个重要内容是:这种传感器的供电方式应该有两种,一是采用电池来供电,凭借其低功率需求和占空比来获得长久的电池使用寿命;另一种是从环境中“收获”或“回收”能量,提取其所需的功率。创业公司Perpetuum设计出了其PMG7发电机,它能够从由AC感应电动机驱动的旋转设备(泵、风扇和其它机械设备)的振动中收集能量,然后释放出来为传感器和无线收发器节点供电。Perpetuum公司的发电机是机电式的(不同于压电式,有些研究人员在回收…     

无线传感器网络中的供电新技术

无线传感器网络作为一种由大量传感器节点构成的特殊网络,主要用于数据的采集和传输,供电技术是其发展的关键技术,探讨了其中的新型电池、能量采集以及电源的智能控制技术三个方面的最新动态。     

基于端点检测的光纤振动信号识别

利用光纤分布式传感系统对入侵事件进行识别主要难点在于对入侵事件的识别准确率低,为了提高对入侵事件的识别准确率,本文提出一种基于端点检测与信号重组的光纤振动信号的识别方法.该方法首先使用基于谱质心与短时能量的端点检测算法对振动信号的振动部分进行检测,然后将检测到的振动信号进行振动信号的重组,最后使用一个多尺度卷积神经网络结合随机森林树对重组后的信号进行识别.实验证明该识别方式能快速完成对识别模型的训练,并且能有效识别在实际环境中采集的入侵振动信号,对入侵信号的识别准确率可达97.4％.     

Modeling and Optimization of a Solar Energy Harvester System for Self-Powered Wireless Sensor Networks

In this paper, we propose a methodology for optimizing a solar harvester with maximum power point tracking for self-powered wireless sensor network (WSN) nodes. We focus on maximizing the harvester's efficiency in transferring energy from the solar panel to the energy storing device. A photovoltaic panel analytical model, based on a simplified parameter extraction procedure, is adopted. This model predicts the instantaneous power collected by the panel helping the harvester design and optimization procedure. Moreover, a detailed modeling of the harvester is proposed to understand basic harvester behavior and optimize the circuit. Experimental results based on the presented design guidelines demonstrate the effectiveness of the adopted methodology. This design procedure helps in boosting efficiency, allowing to reach a maximum efficiency of 85% with discrete components. The application field of this circuit is not limited to self-powered WSN nodes; it can easily be extended in embedded portable applications to extend the battery life.     

A self-powered piezoelectric energy harvesting interface circuit with efficiency-enhanced P-SSHI rectifier

The key to self-powered technique is initiative to harvest energy from the surrounding environment.Harvesting energy from an ambient vibration source utilizing piezoelectrics emerged as a popular method.Efficient interface circuits become the main limitations of existing energy harvesting techniques.In this paper,an interface circuit for piezoelectric energy harvesting is presented.An active full bridge rectifier is adopted to improve the power efficiency by reducing the conduction loss on the rectifying path.A parallel synchronized switch harvesting on inductor (P-SSHI) technique is used to improve the power extraction capability from piezoelectric harvester,thereby trying to reach the theoretical maximum output power.An intermittent power management unit (IPMU) and an output capacitor-less low drop regulator (LDO) are also introduced.Active diodes (AD) instead of traditional passive ones are used to reduce the voltage loss over the rectifier,which results in a good power efficiency.The IPMU with hysteresis comparator ensures the interface circuit has a large transient output power by limiting the output voltage ranges from 2.2 to 2 V.The design is fabricated in a SMIC 0.18μm CMOS technology.Simulation results show that the flipping efficiency of the P-SSHI circuit is over 80％ with an off-chip inductor value of 820 μH.The output power the proposed rectifier can obtain is 44.4μW,which is 6.7× improvement compared to the maximum output power of a traditional rectifier.Both the active diodes and the P-SSHI help to improve the output power of the proposed rectifier.LDO outputs a voltage of 1.8 V with the maximum 90％ power efficiency.The proposed P-SSHI rectifier interface circuit can be self-powered without the need for additional power supply.     

Photovoltaic scavenging systems: Modeling and optimization

The interest in embedded portable systems and wireless sensor networks (WSNs) that scavenge energy from the environment has been increasing over the last years. Thanks to the progress in the design of low-power circuits, such devices consume less and less power and are promising candidates to perform continued operation by the use of renewable energy sources. The adoption of maximum power point tracking (MPPT) techniques in photovoltaic scavengers increases the energy harvesting efficiency and leads to several benefits such as the possibility to shrink the size of photovoltaic modules and energy reservoirs. Unfortunately, the optimization of this process under non-stationary light conditions is still a key design challenge and the development of a photovoltaic harvester has to be preceded by extensive simulations. We propose a detailed model of the solar cell that predicts the instantaneous power collected by the panel and improves the simulation of harvester systems. Furthermore, the paper focuses on a methodology for optimizing the design of MPPT solar harvesters for self-powered embedded systems and presents improvements in the circuit architecture with respect to our previous implementation. Experimental results show that the proposed design guidelines allow to increment global efficiency and to reduce the power consumption of the scavenger.     

Smart dual battery management system for expanding lifespan of wireless sensor node

Wireless sensor nodes have huge energy demand for their operations; they are deployed in remote locations for various applications like weather, industrial, satellite, construction, banking, and medical. Sensor nodes require continuous or uninterrupted power supply during their life cycles. When the available renewable power sources are not sufficient to run the system, the batteries are required to deliver a continuous and uninterrupted power supply. The main focus of proposed model is to design and develop a smart dual battery management system along with a hybrid energy harvesting model that can provide reliable and efficient power support to the sensor node. The problem under consideration also focuses on reducing the state of health degradation of batteries by applying a smart battery charging methodology using an ANFIS (adaptive neuro-fuzzy inference system) controller. The proposed power management system ensures and meets the expected objectives such as switching of power sources, smart battery charging methodology (constant current and constant voltage [CC-CV]), and dual battery power support using ANFIS controller. The result was obtained through the simulation and hardware prototype of the proposed system work flawlessly to meet the desired objective with partial charging and discharging of batteries for the prevention of battery degradation and also enhance the lifespan of the batteries.     

一种基于无线传感器网络的生物信息检测系统节点电源设计

针对电源系统需要为系统中微处理器、传感器、信号调理电路、无线通讯模块等提供工作电源的目的,提出一种生物信息检测系统中无线传感器网络（WSN）节点的电源设计方案。除了通过内部3.7 V锂电池,振动产生的机械能也可以用来提供能量。系统工作过程中能自动对供电方式进行选择,并完成对锂电池的充电任务。节点采用带有8051内校的CC2430无线射频芯片,通过有效的动态电源管理和唤醒休眠机制的软件设计,针对生物信息检测系统实现了一种低功耗的能量自供给的无线传感器节点电源设计。     

基于微尺度压电振动发电机的微电源设计

为弥补传感器网络传统供电存在的不足,该文设计了一种基于微尺度压电发电机的微电源,其可有效拾取周围环境中的振动能量,从而为低功耗的传感器系统提供电能。该电源由具有微尺度效应的微振动发电机与外部高效的无源峰值监测开关电路集成而得,结合Matlab仿真分析可知,其输出电压可达0.24V;无源峰值监测开关电路能保证压电片间电荷的全部输出,与具有经典接口的微电源相比其输出功率提高了3倍。     

A low power high speed MTJ based non-volatile SRAM cell for energy harvesting based IoT applications

Powering billions of devices is one of the most challenging barrier in achieving the future vision of IoT. Most of the sensor nodes for IoT based systems depend on battery as their power source and therefore fail to meet the design goals of lifetime power supply, cost, reliable sensing and transmission. Energy harvesting has the potential to supplant batteries and thus prevents frequent battery replacement. However, energy autonomous systems suffer from sudden power variations due to change in external natural sources and results in loss of data. The memory system is a main component which can improve or decrease performance dramatically. The latest versions of many computing system use chip multiprocessor (CMP) with on-chip cache memory organized as array of SRAM cell. In this paper, we outline the challenges involved with the efficient power supply causing power outage in energy autonomous/self-powered systems. Also, various techniques both at circuit level and system level are discussed which ensures reliable operation of IoT device during power failure. We review the emerging non-volatile memories and explore the possibility of integrating STT-MTJ as prospective candidate for low power solution to energy harvesting based IoT applications. An ultra-low power hybrid NV-SRAM cell is designed by integrating MTJ in the conventional 6T SRAM cell. The proposed LP8T2MTJ NV-SRAM cell is then analyzed using multiple key performance parameters including read/write energies, backup/restore energies, access times and noise margins. The proposed LP8T2MTJ cell is compared to conventional 6T SRAM counterpart indicating similar read and write performance. Also, comparison with the existing MTJ based NV-SRAM cells show 51–78% reduction in backup energy and 42–70% reduction in restore energy.     

Energy Harvesting Based Efficient Routing Scheme for Wireless Sensor Network

Wireless Sensor Network were deployed in a complex environment where the wide range of complex application is mandatory for the services. Such application includes military, agriculture, healthcare, defense, monitoring, surveillance etc. In general sensor nodes were spatially distributed and deployed in remote fashion, usually they are powered up by batteries. These battery powered sensor nodes are pruned to failure due to its power constrained nature. This led many researchers to explore energy efficient context aware routing for Wireless Sensor Networks. Hence a novel energy harvesting based efficient routing scheme is desirable to address the above stated problem. The key idea is to harvest the energy source from the deployed environment. The proposed routing scheme is tested and validated in MATLAB based simulation test bed. The experimental results shows that the proposed routing scheme is robust and meet all the requirements of routing and promising results for energy usage.     

Tissue-Adhesive Piezoelectric Soft Sensor for In Vivo Blood Pressure Monitoring During Surgical Operation

The reliable function in vivo of self-powered implantable bioelectric devices (iBEDs) requires biocompatible, seamless, effective interactions with biological tissues. Herein, an implantable tissue-adhesive piezoelectric soft sensor (TPSS), in which the piezoelectric sensor converts biomechanical signals into electrical signals, and the adhesive hydrogel (AH) strengthens this conversion by seamlessly adhering the sensor on the wet and curvilinear surface, is proposed. The optimized AH exhibits strong adhesion to various organic or inorganic surfaces, including six commonly used engineering materials and three biological tissues. As a pressure sensor, TPSS proves good in vitro electrical performance with a high output of 8.3 V, long-term stability of over 6000 cycles, and high energy power density of 186.9 µW m⁻². In a large animal experiment, TPSS seamlessly adheres to the right-side internal carotid artery of a Yorkshire pig to monitor blood pressure during a surgical operation. Compared to commercial sensors that work by inserting into tissues, TPSS does not cause any damage and can be peeled off after service. The integration of adhesive hydrogel and self-powered pressure sensors enables biocompatible, seamless, and more efficient interactions between the biological system and iBEDs, which also contributes to next-generation implantable bioelectronics with features of battery-free, intelligent, and accurate.     

Wearable Self-Powered Electrochemical Devices for Continuous Health Management

The wearable revolution is already present in society through numerous gadgets. However, the contest remains in fully deployable wearable (bio)chemical sensing. Its use is constrained by the energy consumption which is provided by miniaturized batteries, limiting the autonomy of the device. Hence, the combination of materials and engineering efforts to develop sustainable energy management is paramount in the next generation of wearable self-powered electrochemical devices (WeSPEDs). In this direction, this review highlights for the first time the incorporation of innovative energy harvesting technologies with top-notch wearable self-powered sensors and low-powered electrochemical sensors toward battery-free and self-sustainable devices for health and wellbeing management. First, current elements such as wearable designs, electrochemical sensors, energy harvesters and storage, and user interfaces that conform WeSPEDs are depicted. Importantly, the bottlenecks in the development of WeSPEDs from an analytical perspective, product side, and power needs are carefully addressed. Subsequently, energy harvesting opportunities to power wearable electrochemical sensors are discussed. Finally, key findings that will enable the next generation of wearable devices are proposed. Overall, this review aims to bring new strategies for an energy-balanced deployment of WeSPEDs for successful monitoring of (bio)chemical parameters of the body toward personalized, predictive, and importantly, preventive healthcare.