压电能量收集接口电路的设计与仿真

为了给无线传感器网络节点提供稳定、高效且长期的能量供给,该文提出了一种基于增强型同步电荷提取电路的压电能量收集接口电路(ESECE)。利用Multisim电路仿真软件对增强型同步电荷提取电路进行仿真,并与标准压电能量收集接口电路(SHE)和同步电荷提取电路(SECE)进行对比分析。实验结果表明,在相同激励条件下,ESECE比SECE的输出功率提高了近30%,最大输出功率达到190μW,同时还保证了输出功率与负载电阻的无关性。     

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.     

Clamp-and-Forget: A self-sustainable non-invasive wireless sensor node for smart metering applications

Measuring and managing the power consumption of household appliances, as well as that of industrial machineries, is becoming more and more important to improve the distribution and usage of the electrical energy and to reduce the energy bill. We present the design of a non-invasive wireless current meter which can measure AC current up to $60A_{\mathit{RMS}}$ exploiting a small clamp-on inductive sensor. The novelty of the design is a subsystem consisting of a harvesting circuit designed to extract energy from the same current transducer used for measurements. Experiments have been conducted to validate the approach, to assess the accuracy of the sensing system and deviations due to the energy harvester, and to determine the condition which permits us to achieve the energy neutrality and thus, a self-sustainable smart meter.     

基于声强的无线传感器网络目标跟踪方法研究

为有效解决无线传感器网络对具有声音特性移动目标的跟踪问题,该文利用声音随距离的能量衰减模,并结合声强特性,给出了基于动态组管理机制的目标跟踪方法。仿真实验结果表明无线传感器网络中基于声强特性的方法,能够有效实现对移动目标跟踪,结合Kalman滤波算法提高了实验结果的跟踪精度。     

带有MPPT功能的高效率光伏电池升压转换器芯片

为了提高光伏电池的收集效率和环境适应性,提出了一种带有MPPT功能的高效率光伏电池升压转换器芯片。该电路系统包括新型四相高效电荷泵模块、扰动观察法MPPT控制电路模块、反馈控制模块、纳安级电流基准、检测电路模块等。该芯片采用0.35μm BCD工艺设计、仿真并流片。芯片尺寸为3.15 mm×2.43 mm。测试结果表明,当光伏电池输出电压大于0.5 V时,升压转换器芯片输出电压提升到3V_in,电压转换效率可达99.4%。MPPT算法使输出功率提升8.53%。当输出负载电流为297μA时,最宽输出PCE达到85.1%。该芯片实现了高效升压光伏电池输出电压的目标。     

一种基于自适应电荷泵的多源能量收集芯片

采用标准0.18 μm CMOS工艺,设计了一种可以同时高效收集压电、光电、热电、射频能量的多源能量收集芯片.该收集芯片由多种能源接口电路、可重构电荷泵和自适应控制电路等单元构成.可重构电荷泵中,通过调节电压转换倍率和开关工作频率来降低电荷再分配损耗,提高了转换效率,扩大了输入电压范围.自适应控制电路中,采用固定导通时...     

应用于能量收集的自启动DC-DC升压转换器

基于SMIC 0.18 μm CMOS工艺,设计了一种应用于能量收集的自启动DC-DC升压转换器。系统包括两级升压结构,第一级自启动模块实现亚阈值电压输入,将电压升至可供第二级主升压结构使用的电压。两级升压结构中,均采用了基于栅交叉耦合的电荷泵,对其中的电荷传输开关进行改进,克服了传统Dickson电荷泵的体效应问题,提高了电压增益和转换效率。仿真结果表明,DC-DC升压转换器能在300 mV输入下实现自启动,输出电压为1.8 V,纹波电压约为4 mV,效率达到69%。     

Distributed and Energy Efficient Self-Organization for On–Off Wireless Sensor Networks

In this paper, we utilize clustering to achieve energy efficiency for the on–off wireless sensor network, whose member nodes alternate between active and inactive states. In the proposed Distributed and Energy Efficient Self Organization (DEESO) scheme, the head election is adjusted adaptively to the remaining battery levels of local active nodes, which is a completely distributed approach compared to LEACH that relying on other routing schemes to access global information. Furthermore, we apply the Adaptive Channel Assignment (ACA) to address the on-off topology changes. Simulation results show that DEESO delivers 184% amount of data to the base station as LEACH for the same amount of energy consumption and the effective network lifetime is extended by around 50%.     

一种高效压电能量收集与管理电路

根据压电元件的特性提出一种压电能量收集与管理电路。它包括一个基于电感的并联同步开关收集电路( P-SSHI )、一个控制电路和一个DC-DC电路。该P-SSHI电路只需要两个开关,仿真的结果显示其收集的能量相比传统的AC-DC电路提高5倍以上;DC-DC电路工作在电流断续模式下(DCM),这有利于降低功耗,提高轻载效率,且仿真结果的输出电压为3.3 V,电压精度为0.02%。这种压电能量收集与管理电路能够为微功率设备提供稳压。     

一种用于模数转换器时钟管理电路的电荷泵

采用0.13μm CMOS工艺,设计了一种用于模数转换器时钟电路的电荷泵。在共源共栅充/放电流源与其偏置电路之间增加传输门,有效地抑制了电荷泵关闭时产生的漏电流。同时,采用电流源提升技术,有效地提高了电荷泵充/放电电流支路的阻抗,抑制了沟道长度调制效应的影响,提高了电荷泵的电流匹配性。仿真结果表明,在1.2 V电源电压、20μA输出电流的条件下,输出电压的变化范围为0.13～0.93 V时,该电荷泵的充/放电电流失配低于1%。     

一体式无线无源振动传感器设计

现阶段无线传感器的供电主要依靠的依然是一次电池或可充电电池,无论哪种电池,其寿命都是有限且短暂的,大量的更换及废弃势必会对生态环境造成极大的污染。由此提出一种基于振动能量采集的自供电传感器,基于电磁感应对振动能量进行采集利用;低功耗单片机利用所收集的能量对发电单元所产生的信号进行采集,作为振动传感信号。实验结果证明,该无源传感器可在2 Hz^200 Hz的振动环境下稳定的工作,所采集的信号同样与实际振动环境一致。     

Controlled sink mobility for prolonging wireless sensor networks lifetime

This paper demonstrates the advantages of using controlled mobility in wireless sensor networks (WSNs) for increasing their lifetime, i.e., the period of time the network is able to provide its intended functionalities. More specifically, for WSNs that comprise a large number of statically placed sensor nodes transmitting data to a collection point (the sink), we show that by controlling the sink movements we can obtain remarkable lifetime improvements. In order to determine sink movements, we first define a Mixed Integer Linear Programming (MILP) analytical model whose solution determines those sink routes that maximize network lifetime. Our contribution expands further by defining the first heuristics for controlled sink movements that are fully distributed and localized. Our Greedy Maximum Residual Energy (GMRE) heuristic moves the sink from its current location to a new site as if drawn toward the area where nodes have the highest residual energy. We also introduce a simple distributed mobility scheme (Random Movement or RM) according to which the sink moves uncontrolled and randomly throughout the network. The different mobility schemes are compared through extensive ns2-based simulations in networks with different nodes deployment, data routing protocols, and constraints on the sink movements. In all considered scenarios, we observe that moving the sink always increases network lifetime. In particular, our experiments show that controlling the mobility of the sink leads to remarkable improvements, which are as high as sixfold compared to having the sink statically (and optimally) placed, and as high as twofold compared to uncontrolled mobility. Stefano Basagni holds a Ph.D. in electrical engineering from the University of Texas at Dallas (December 2001) and a Ph.D. in computer science from the University of Milano, Italy (May 1998). He received his B.Sc. degree in computer science from the University of Pisa, Italy, in 1991. Since Winter 2002 he is on faculty at the Department of Electrical and Computer Engineering at Northeastern University, in Boston, MA. From August 2000 to January 2002 he was professor of computer science at the Department of Computer Science of the Erik Jonsson School of Engineering and Computer Science, The University of Texas at Dallas. Dr. Basagni’s current research interests concern research and implementation aspects of mobile networks and wireless communications systems, Bluetooth and sensor networking, definition and performance evaluation of network protocols and theoretical and practical aspects of distributed algorithms. Dr. Basagni has published over four dozens of referred technical papers and book chapters. He is also co-editor of two books. Dr. Basagni served as a guest editor of the special issue of the Journal on Special Topics in Mobile Networking and Applications (MONET) on Multipoint Communication in Wireless Mobile Networks, of the special issue on mobile ad hoc networks of the Wiley’s Interscience’s Wireless Communications & Mobile Networks journal, and of the Elsevier’s journal Algorithmica on algorithmic aspects of mobile computing and communications. Dr. Basagni serves as a member of the editorial board and of the technical program committee of ACM and IEEE journals and international conferences. He is a senior member of the ACM (including the ACM SIGMOBILE), senior member of the IEEE (Computer and Communication societies), and member of ASEE (American Society for Engineering Education). Alessio Carosi received the M.S. degree “summa cum laude” in Computer Science in 2004 from Rome University “La Sapienza.” He is currently a Ph.D. candidate in Computer Science at Rome University “La Sapienza.” His research interests include protocols for ad hoc and sensor networks, underwater systems and delay tolerant networking. Emanuel Melachrinoudis received the Ph.D. degree in industrial engineering and operations research from the University of Massachusetts, Amherst, MA. He is currently the Director of Industrial Engineering and Associate Chairman of the Department of Mechanical and Industrial Engineering at Northeastern University, Boston, MA. His research interests are in the areas of network optimization and multiple criteria optimization with applications to telecommunication networks, distribution networks, location and routing. He is a member of the Editorial Board of the International Journal of Operational Research. He has published in journals such as Management Science, Transportation Science, Networks, European Journal of Operational Research, Naval Research Logistics and IIE Transactions. Chiara Petrioli received the Laurea degree “summa cum laude” in computer science in 1993, and the Ph.D. degree in computer engineering in 1998, both from Rome University “La Sapienza,” Italy. She is currently Associate Professor with the Computer Science Department at Rome University “La Sapienza.” Her current work focuses on ad hoc and sensor networks, Delay Tolerant Networks, Personal Area Networks, Energy-conserving protocols, QoS in IP networks and Content Delivery Networks where she contributed around sixty papers published in prominent international journals and conferences. Prior to Rome University she was research associate at Politecnico di Milano and was working with the Italian Space agency (ASI) and Alenia Spazio. Dr. Petrioli was guest editor of the special issue on “Energy-conserving protocols in wireless Networks” of the ACM/Kluwer Journal on Special Topics in Mobile Networking and Applications (ACM MONET) and is associate editor of IEEE Transactions on Vehicular Technology, the ACM/Kluwer Wireless Networks journal, the Wiley InterScience Wireless Communications & Mobile Computing journal and the Elsevier Ad Hoc Networks journal. She has served in the organizing committee and technical program committee of several leading conferences in the area of networking and mobile computing including ACM Mobicom, ACM Mobihoc, IEEE ICC,IEEE Globecom. She is member of the steering committee of ACM Sensys and of the international conference on Mobile and Ubiquitous Systems: Networking and Services (Mobiquitous) and serves as member of the ACM SIGMOBILE executive committee. Dr. Petrioli was a Fulbright scholar. She is a senior member of IEEE and a member of ACM. Z. Maria Wang received her Bachelor degree in Electrical Engineering with the highest honor from Beijing Institute of Light Industry in China, her M.S. degree in Industrial Engineering/Operations Research from Dalhousie University, Canada and her Ph.D. in Industrial Engineering/Operations Research from Northeastern University, Boston. She served as a R&D Analyst for General Dynamics. Currently MS. Wang serves as an Optimization Analyst with Nomis Solutions, Inc.     

无线传感器网络能量收集技术分析

对无线传感器网络节点的能量供应及其管理技术的现状进行了讨论。分析研究了无线传感器网络节点的能量收集原理、技术与方法,认为无线传感器网络节点能量管理应从节能与供能两方面去解决。对环境中存在的各种能源的收集原理与方法进行了分析,这些能源包括太阳能、风能、声能、振动、热电以及电磁场能等。最后提出了传感器节点应该采用尽可能多的方法从环境中吸取能量,以确保传感器节点能够长期、稳定、可靠地工作。     

无线传感器网络能量收集技术分析

对无线传感器网络节点的能量供应及其管理技术的现状进行了讨论。分析研究了无线传感器网络节点的能量收集原理、技术与方法,认为无线传感器网络节点能量管理应从节能与供能两方面去解决。对环境中存在的各种能源的收集原理与方法进行了分析,这些能源包括太阳能、风能、声能、振动、热电以及电磁场能等。最后提出了传感器节点应该采用尽可能多的方法从环境中吸取能量,以确保传感器节点能够长期、稳定、可靠地工作。