 Subjects -> ELECTRONICS (Total: 207 journals)
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- Hybrid neuroelectronics: towards a solution-centric way of thinking about
complex problems in neurostimulation tools
Authors: Sofia Drakopoulou, Francesc Varkevisser, Linta Sohail, Masoumeh Aqamolaei, Tiago L. Costa, George D. Spyropoulos
Abstract: Responsive neuromodulation is increasingly being used to treat patients with neuropsychiatric diseases. Yet, inefficient bridges between traditional and new materials and technological innovations impede advancements in neurostimulation tools. Signaling in the brain is accomplished predominantly by ion flux rather than the movement of electrons. However, the status quo for the acquisition of neural signals is using materials, such as noble metals, that can only interact with electrons. As a result, ions accumulate at the biotic/abiotic interface, creating a double-layer capacitance that increases impedance and negatively impacts the efficiency of neural interrogation. Alternative materials, such as conducting polymers, allow ion penetration in the matrix, creating a volumetric capacitor (two orders of magnitude larger than an area-dependent capacitor) that lowers the impedance and increases the spatiotemporal resolution of the recording/stimulation. On the other hand, the increased development and integration capabilities of CMOS-based back-end electronics have enabled the creation of increasingly powerful and energy-efficient microchips. These include stimulation and recording systems-on-a-chip (SoCs) with up to tens of thousands of channels, fully integrated circuitry for stimulation, signal conditioning, digitation, wireless power and data telemetry, and on-chip signal processing. Here, we aim to compile information on the best component for each building block and try to strengthen the vision that bridges the gap among various materials and technologies in an effort to advance neurostimulation tools and promote a solution-centric way of considering their complex problems.
PubDate: 2023-09-12T00:00:00Z
- Topology synthesis of integrated active power decoupling converters using
asymmetrical H-bridge circuits
Authors: Yonglu Liu, Yiqi Zuo, Liang Yuan
Abstract: Aiming to handle the inherent double-line frequency ripple power in single-phase power systems, a lot of active power decoupling (APD) topologies have been developed. In this paper, a general method is introduced to synthesize APD topologies. The main construction idea is to insert a rectifier/inverter into asymmetrical H-bridge circuits (AHCs) or replace the switch/diode in the AHCs with a rectifier/inverter. This approach not only reveals the formation process of existing APD topologies but also deduces new APD topologies. Finally, an experimental case study has been carried out to illustrate the feasibility and effectiveness of the proposed topology synthesis method.
PubDate: 2023-09-08T00:00:00Z
- Lifetime prediction and reliability analysis for aluminum electrolytic
capacitors in EV charging module based on mission profiles
Authors: Hongpeng Liu, Jiahui Qiu, Wei Zhang, Mengyuan Zhang, Zhenlan Dou, Liangliang Chen
Abstract: The charging modules of Electric vehicles (EVs) always run in a complex and variable state. As the weakness in the reliable operation of charging modules, the accurate lifetime prediction of aluminum electrolytic capacitors (Al-caps) is important for the later maintenance and reliability design. The hotspot temperature calculation method and lifetime model limit the accuracy of aluminum electrolytic capacitors lifetime prediction methods, which cannot meet the increasing requirements for reliability. In order to solve the problems above, this paper has proposed a hotspot temperature calculation method based on the ripple current with frequency characteristics and the cooling conditions on the heat generation and thermal conductivity of the capacitors. Furthermore, the lifetime model under reference voltage has been constructed with 3D surface fitting toolbox, which describes the trends of capacitor lifetime with ambient temperature and hotspot temperature under the constant voltage condition. Considering the variation of voltage, the multiple lifetime model of capacitor is established with a voltage correction coefficient. With the proposed method, it can be realized about the real-time lifetime prediction of capacitors under multiple operating profiles such as ripple current, thermal dissipation conditions, ambient temperature and operating voltage. Finally, the effectiveness of the proposed method is verified with the annual profiles of a 30 kW EV charging module.
PubDate: 2023-08-16T00:00:00Z
- Impact of inverter-based resources on transmission line relaying -part II:
power swing protection
Authors: Amin Jalilian, Duane A. Robinson
Abstract: The power swing characteristic of transmission lines (TLs) can be affected by the large-scale integration of inverter-based resources (IBRs), resulting in the maloperation of the legacy power swing blocking (PSB) and out-of-step tripping (OST) functions. This paper presents a brief review of power swing phenomena and the impact on power swing protection functions. In this regard, the impact of IBR integration of type-III, and type-IV wind turbine generation (WTG) on legacy power swing protection functions has been scrutinized. To do so, the performance of impedance-based PSB and OST functions during the IBR integration has been investigated via comprehensive simulation studies. The results show that under a system contingency and high IBR penetration, depending on the IBR technology, the system experiences frequency oscillations and swinging impedance trajectories which are different from those from synchronous generators, such that the reliable operation of the legacy PSB and OST functions can be jeopardized. Moreover, during power swing phenomena, the simulation results have found that the security of distance protection cannot be guaranteed and the fault ride-through requirements cannot be maintained when a high share of IBRs have been integrated.
PubDate: 2023-08-10T00:00:00Z
- Ear canal pressure sensor for food intake detection
Authors: Delwar Hossain, Tonmoy Ghosh, Masudul Haider Imtiaz, Edward Sazonov
Abstract: Introduction: This paper presents a novel Ear Canal Pressure Sensor (ECPS) for objective detection of food intake, chew counting, and food image capture in both controlled and free-living conditions. The contribution of this study is threefold: 1) Development and validation of a novel wearable sensor that uses changes in ear canal pressure and the device’s acceleration as an indicator of food intake, 2) A method to identify chewing segments and count the number of chews in each eating episode, and 3) Facilitation of egocentric image capture only during eating by triggering camera from sensor detection thus reducing power consumption, privacy concerns, as well as storage and computational cost.Methods: To validate the device, data were collected from 10 volunteers in a controlled environment and three volunteers in a free-living environment. During the controlled activities, each participant wore the device for approximately 1 h, and during the free living for approximately 12 h. The food intake of the participants was not restricted in any way in both part of the experiment. Subject-independent Support Vector Machine classifiers were trained to identify periods of food intake from the features of both the pressure sensor and accelerometer, and features only from the pressure sensor.Results: Results from leave-one-out cross-validation showed an average 5 sec-epoch classification F-score of 87.6% using only pressure sensor features and 88.6% using features from both pressure sensor and accelerometer in the controlled environment. For the free-living environment, both classifiers accurately detected all eating episodes. The wearable sensor achieves 95.5% accuracy in counting the number of chews with respect to manual annotation from the videos of the eating episodes using a pressure sensor classifier in the controlled environment.Discussion: The manual review of the images found that only 3.7% of captured images belonged to the detected eating episodes, suggesting that sensor-triggered camera capture may facilitate reducing the number of captured images and power consumption of the sensor.
PubDate: 2023-07-18T00:00:00Z
- Straightforward data transfer in a blockwise dataflow for an analog
RRAM-based CIM system
Authors: Yuyi Liu, Bin Gao, Peng Yao, Qi Liu, Qingtian Zhang, Dong Wu, Jianshi Tang, He Qian, Huaqiang Wu
Abstract: Analog resistive random-access memory (RRAM)-based computation-in-memory (CIM) technology is promising for constructing artificial intelligence (AI) with high energy efficiency and excellent scalability. However, the large overhead of analog-to-digital converters (ADCs) is a key limitation. In this work, we propose a novel LINKAGE architecture that eliminates PE-level ADCs and leverages an analog data transfer module to implement inter-array data processing. A blockwise dataflow is further proposed to accelerate convolutional neural networks (CNNs) to speed up compute-intensive layers and solve the unbalanced pipeline problem. To obtain accurate and reliable benchmark results, key component modules, such as straightforward link (SFL) modules and Tile-level ADCs, are designed in standard 28 nm CMOS technology. The evaluation shows that LINKAGE outperforms the conventional ADC/DAC-based architecture with a 2.07×∼11.22× improvement in throughput, 2.45×∼7.00× in energy efficiency, and 22%–51% reduction in the area overhead while maintaining accuracy. Our LINKAGE architecture can achieve 22.9∼24.4 TOPS/W energy efficiency (4b-IN/4b-W) and 1.82 ∼4.53 TOPS throughput with the blockwise method. This work demonstrates a new method for significantly improving the energy efficiency of CIM chips, which can be applied to general CNNs/FCNNs.
PubDate: 2023-04-17T00:00:00Z
- Design of a wireless charging system in DC microgrids with accurate output
regulation and optimal efficiency
Authors: Chenchen Li, Kaiyuan Wang, Yuan Mao
Abstract: This paper presents a general circuit and control design method for wireless power transfer (WPT) systems in DC microgrids to achieve optimal power transfer efficiency, while maintain accurate output voltage regulation. An auxiliary inductor is added at the transmitter resonator to form a current sink to ensure zero voltage switching (ZVS) of the primary-side full-bridge inverter with even extreme-light load conditions. Besides, an adaptive proportional-integral (PI) controller is adopted to track the output voltage references by regulating the phase shift angle of the phase shift control for the full-bridge inverter. The coefficients of the adaptive proportional-integral controller are determined by the inductor of the auxiliary inductor. Both simulation and experimental results have validated the effectiveness of the proposed circuit and control design in achieving optimal efficiency and output voltage regulation for wireless power transfer systems in DC microgrids with source and load variations.
PubDate: 2023-03-17T00:00:00Z
- Optimal dispatch of integrated energy systems considering integrated
demand response and stepped carbon trading
Authors: Xianglei Ye, Zhenya Ji, Jinxing Xu, Xiaofeng Liu
Abstract: The integrated energy system is an effective way to achieve carbon neutrality. To further exploit the carbon reduction potentials of IESs, an optimal dispatch strategy that considers integrated demand response and stepped carbon trading is proposed. First, an integrated demand response (IDR) pricing approach is proposed based on the characteristics of different load types. Classify multi-energy loads into curtailable and substitutable loads, and incentivize both loads through a price elasticity matrix and low-price energy in the same period. Then, to better incentivize IESs to reduce carbon emissions, a stepped pricing mechanism was introduced in the carbon price. Finally, an optimal dispatch model is developed with an objective function that minimizes the sum of energy purchase cost, carbon trading cost, and operation and maintenance (O&M) cost. Considering the high-dimensional and non-linear characteristics of the model, an improved differential evolution (DE) algorithm is introduced in this paper. In addition, this paper also analyzes the effects of the stepped carbon trading parameters on the optimal dispatching results of the system in terms of carbon trading base price, carbon emission interval length, and carbon price growth rate. Compared to the case of adopting a single IDR model or a single stepped carbon trading, carbon emissions from the IESs decreased by 6.28% and 3.24%, respectively, while total operating costs decreased by 1.24% and 0.92%, The results show that the model proposed in this paper has good environmental and economic benefits, and the reasonable setting of stepped carbon trading parameters can effectively promote the low-carbon development of IESs.
PubDate: 2023-02-23T00:00:00Z
- Research on optimal coil configuration scheme of insulator relay WPT
system
Authors: Wei Wang, Mingrong Duan, Zhenwei Zeng, Huai Liu, Zhenya Ji
Abstract: This paper presents the optimized structure of the multi-relay coils insulator of WPT system. With the rapid development of the smart grid, on-line monitoring devices in the transmission tower have been widely used. However, the power supply problem has become an important bottleneck in the development of transmission tower intelligent sensing technology. Hence, the multi-relay coils wireless power transfer technology has been proposed to supply for the tower monitoring equipment in this paper. Compared with traditional multi-relay coils, the effects of the number, arrangement position and turns of relay coils on the performance of WPT system are further explored. The simulation results show that the operation performance of WPT can be significantly improved by optimizing the coil arrangement position and turns. Moreover, there are multiple configuration schemes that the design indexes of the system could be achieved. The experiment results show that in the 110 kV high-voltage transmission with the insulator length of 1.015 m, the transmitting power and efficiency of the WPT system could be increased to 1.81 W and 60.11% respectively by parameters optimization, which ensures the continuous and stable work of the monitoring equipment.
PubDate: 2023-01-26T00:00:00Z
- CoFHE: Software and hardware Co-design for FHE-based machine learning as a
service
Authors: Mengxin Zheng, Lei Ju, Lei Jiang
Abstract: Introduction: Privacy concerns arise whenever sensitive data is outsourced to untrusted Machine Learning as a Service (MLaaS) platforms. Fully Homomorphic Encryption (FHE) emerges one of the most promising solutions to implementing privacy-preserving MLaaS. But prior FHE-based MLaaS faces challenges from both software and hardware perspectives. First, FHE can be implemented by various schemes including BGV, BFV, and CKKS, which are good at different FHE operations, e.g., additions, multiplications, and rotations. Different neural network architectures require different numbers of FHE operations, thereby preferring different FHE schemes. However, state-of-the-art MLaaS just naïvely chooses one FHE scheme to build FHE-based neural networks without considering other FHE schemes. Second, state-of-the-art MLaaS uses power-hungry hardware accelerators to process FHE-based inferences. Typically, prior high-performance FHE accelerators consume >160 Watt, due to their huge capacity (e.g., 512 MB) on-chip SRAM scratchpad memories.Methods: In this paper, we propose a software and hardware co-designed FHE-based MLaaS framework, CoFHE. From the software perspective, we propose an FHE compiler to select the best FHE scheme for a network architecture. We also build a low-power and high-density NAND-SPIN and SRAM hybrid scratchpad memory system for FHE hardware accelerators.Results: On average, under the same security and accuracy constraints, on average, CoFHE accelerates various FHE-based inferences by 18%, and reduces the energy consumption of various FHE-based inferences by 26%.Discussion: CoFHE greatly improves the latency and energy efficiency of FHE-based MLaaS.
PubDate: 2023-01-12T00:00:00Z
- Analytic circuit model for thermal drying behavior of electronic inks
Authors: Gabriel Maroli, Santiago Boyeras, Hernan Giannetta, Sebastian Pazos, Joel Gak, Alejandro Raúl Oliva, María Alicia Volpe, Pedro Marcelo Julian, Felix Palumbo
Abstract: Understanding the sintering process of conductive inks is a fundamental step in the development of sensors. The intrinsic properties (such as thermal conductivity, resistivity, thermal coefficient, among others) of the printed devices do not correspond to those of the bulk materials. In the field of biosensors porosity plays a predominant role, since it defines the difference between the geometric area of the working electrode and its electrochemical surface area. The analysis reported so far in the literature on the sintering of inks are based on their DC characterization. In this work, the shape and distribution of the nanoparticles that make up the silver ink have been studied employing a transmission electron microscopy. Images of the printed traces have been obtained through a scanning electron microscope at different sintering times, allowing to observe how the material decreases its porosity over time. These structural changes were supported through electrical measurements of the change in the trace impedance as a function of drying time. The resistivity and thermal coefficient of the printed tracks were analyzed and compared with the values of bulk silver. Finally, this work proposes an analytical circuit model of the drying behavior of the ink based on AC characterization at different frequencies. The characterization considers an initial time when the spheric nanoparticles are still surrounded by the capping agent until the conductive trace is obtained. This model can estimate the characteristics that the printed devices would have, whether they are used as biosensors (porous material) or as interconnections (compact material) in printed electronics.
PubDate: 2023-01-06T00:00:00Z
- Breakdown-limited endurance in HZO FeFETs: Mechanism and improvement under
bipolar stress
Authors: Kasidit Toprasertpong, Mitsuru Takenaka, Shinichi Takagi
Abstract: Breakdown is one of main failure mechanisms that limit write endurance of ferroelectric devices using hafnium oxide-based ferroelectric materials. In this study, we investigate the gate current and breakdown characteristics of Hf0.5Zr0.5O2/Si ferroelectric field-effect transistors (FeFETs) by using carrier separation measurements to analyze electron and hole leakage currents during time-dependent dielectric breakdown (TDDB) tests. Rapidly increasing substrate hole currents and stress-induced leakage current (SILC)-like electron currents can be observed before the breakdown of the ferroelectric gate insulator of FeFETs. This apparent degradation under voltage stress is recovered and the time-to-breakdown is significantly improved by interrupting the TDDB test with gate voltage pulses with the opposite polarity, suggesting that defect redistribution, rather than defect generation, is responsible for the trigger of hard breakdown.
PubDate: 2022-12-21T00:00:00Z
- XMA2: A crossbar-aware multi-task adaption framework via 2-tier masks
Authors: Fan Zhang, Li Yang, Jian Meng, Jae-sun Seo, Yu Cao, Deliang Fan
Abstract: Recently, ReRAM crossbar-based deep neural network (DNN) accelerator has been widely investigated. However, most prior works focus on single-task inference due to the high energy consumption of weight reprogramming and ReRAM cells’ low endurance issue. Adapting the ReRAM crossbar-based DNN accelerator for multiple tasks has not been fully explored. In this study, we propose XMA2, a novel crossbar-aware learning method with a 2-tier masking technique to efficiently adapt a DNN backbone model deployed in the ReRAM crossbar for new task learning. During the XMA2-based multi-task adaption (MTA), the tier-1 ReRAM crossbar-based processing-element- (PE-) wise mask is first learned to identify the most critical PEs to be reprogrammed for essential new features of the new task. Subsequently, the tier-2 crossbar column-wise mask is applied within the rest of the weight-frozen PEs to learn a hardware-friendly and column-wise scaling factor for new task learning without modifying the weight values. With such crossbar-aware design innovations, we could implement the required masking operation in an existing crossbar-based convolution engine with minimal hardware/memory overhead to adapt to a new task. The extensive experimental results show that compared with other state-of-the-art multiple-task adaption methods, XMA2 achieves the highest accuracy on all popular multi-task learning datasets.
PubDate: 2022-12-20T00:00:00Z
- A review and analysis of current-mode biosensing front-end ICs for
nanopore-based DNA sequencing
Authors: Xu Liu, Qiumeng Fan, Zhijie Chen, Peiyuan Wan, Wei Mao, Hao Yu
Abstract: Bio-sensors connect the biological world with electronic devices, widely used in biomedical applications. The combination of microelectronic and medical technologies makes biomedical diagnosis more rapid, accurate, and efficient. In this article, the current-mode biosensing front-end integrated circuits (ICs) for nanopore-based DNA sequencing are reviewed and analyzed, aiming to present their operation theories, advantages, limitations, and performances including gain, bandwidth, noise, and power consumption. Because biological information and external interference are contained in extremely weak sensing current, usually at the pA or nA level, it is challenging to accurately detect and restore the desired signals. Based on the requirements of DNA sequencing, this paper shows three circuit topologies of biosensing front-end, namely, discrete-time, continuous-time, and current-to-frequency conversion types. This paper also makes an introduction to the current-mode sensor array for DNA sequencing. To better review and evaluate the research of the state-of-the-art, the most relevant published works are summarized and compared. The review and analysis would help the researchers be familiar with the requirements, constraints, and methods for current-mode biosensing front-end IC designs for nanopore-based DNA sequencing.
PubDate: 2022-11-29T00:00:00Z
- Kinetic energy harvesting based sensing and IoT systems: A review
Authors: Zijie Chen, Fei Gao, Junrui Liang
Abstract: The rapid advance of the Internet of Things (IoT) has attracted growing interest in academia and industry toward pervasive sensing and everlasting IoT. As the IoT nodes exponentially increase, replacing and recharging their batteries proves an incredible waste of labor and resources. Kinetic energy harvesting (KEH), converting the wasted ambient kinetic energy into usable electrical energy, is an emerging research field where various working mechanisms and designs have been developed for improved performance. Leveraging the KEH technologies, many motion-powered sensors, where changes in the external environment are directly converted into corresponding self-generated electrical signals, are developed and prove promising for multiple self-sensing applications. Furthermore, some recent studies focus on utilizing the generated energy to power a whole IoT sensing system. These systems comprehensively consider the mechanical, electrical, and cyber parts, which lead a further step to truly self-sustaining and maintenance-free IoT systems. Here, this review starts with a brief introduction of KEH from the ambient environment and human motion. Furthermore, the cutting-edge KEH-based sensors are reviewed in detail. Subsequently, divided into two aspects, KEH-based battery-free sensing systems toward IoT are highlighted. Moreover, there are remarks in every chapter for summarizing. The concept of self-powered sensing is clarified, and advanced studies of KEH-based sensing in different fields are introduced. It is expected that this review can provide valuable references for future pervasive sensing and ubiquitous IoT.
PubDate: 2022-10-06T00:00:00Z
- Influence analysis of metal foreign objects on the wireless power
transmission system
Authors: Jiacheng Li, Yijie Huang
Abstract: The wireless power transmission (WPT) system through magnetic field coupling for energy transmission may have foreign objects in the transmission channel in the practical application process, which brings hidden dangers to the WPT system. In this article, a WPT system without and with foreign objects is constructed. The influence of foreign objects on self-inductance and mutual-inductance of coupling coils is studied from the aspects of foreign object height, radius, transmission distance, and coil turns. Then, by constructing the circuit topology of the series structure, the influence of foreign objects on the transmission efficiency and the phase difference between voltage and current of the system is studied, and finally the influence law of metal foreign objects on the performance of the WPT system is summarized.
PubDate: 2022-10-03T00:00:00Z
- Reliability of pulse photoplethysmography sensors: Coverage using
different setups and body locations
Authors: Pablo Armañac-Julián, Spyridon Kontaxis, Andrius Rapalis, Vaidotas Marozas, Pablo Laguna, Raquel Bailón, Eduardo Gil, Jesús Lázaro
Abstract: Pulse photoplethysmography (PPG) is a simple and economical technique for obtaining cardiovascular information. In fact, PPG has become a very popular technology among wearable devices. However, the PPG signal is well-known to be very vulnerable to artifacts, and a good quality signal cannot be expected for most of the time in daily life. The percentage of time that a given measurement can be estimated (e.g., pulse rate) is denoted coverage (C), and it is highly dependent on the subject activity and on the configuration of the sensor, location, and stability of contact. This work aims to quantify the coverage of PPG sensors, using the simultaneously recorded electrocardiogram as a reference, with the PPG recorded at different places in the body and under different stress conditions. While many previous works analyzed the feasibility of PPG as a surrogate for heart rate variability analysis, there exists no previous work studying coverage to derive other cardiovascular indices. We report the coverage not only for estimating pulse rate (PR) but also for estimating pulse arrival time (PAT) and pulse amplitude variability (PAV). Three different datasets are analyzed for this purpose, consisting of a tilt-table test, an acute emotional stress test, and a heat stress test. The datasets include 19, 120, and 51 subjects, respectively, with PPG at the finger and at the forehead for the first two datasets and at the earlobe, in addition, for the latter. C ranges from 70% to 90% for estimating PR. Regarding the estimation of PAT, C ranges from 50% to 90%, and this is very dependent on the PPG sensor location, PPG quality, and the fiducial point (FP) chosen for the delineation of PPG. In fact, the delineation of the FP is critical in time for estimating derived series such as PAT due to the small dynamic range of these series. For the estimation of PAV, the C rates are between 70% and 90%. In general, lower C rates have been obtained for the PPG at the forehead. No difference in C has been observed between using PPG at the finger or at the earlobe. Then, the benefits of using either will depend on the application. However, different C rates are obtained using the same PPG signal, depending on the FP chosen for delineation. Lower C is reported when using the apex point of the PPG instead of the maximum flow velocity or the basal point, with a difference from 1% to even 10%. For further studies, each setup should first be analyzed and validated, taking the results and guidelines presented in this work into account, to study the feasibility of its recording devices with respect to each specific application.
PubDate: 2022-09-29T00:00:00Z
- Energy-efficient neural network design using memristive MAC unit
Authors: Shengqi Yu, Thanasin Bunnam, Sirichai Triamlumlerd, Manoch Pracha, Fei Xia, Rishad Shafik, Alex Yakovlev
Abstract: Artificial intelligence applications implemented with neural networks require extensive arithmetic capabilities through multiply-accumulate (MAC) units. Traditional designs based on voltage-mode circuits feature complex logic chains for such purposes as carry processing. Additionally, as a separate memory block is used (e.g., in a von Neumann architecture), data movements incur on-chip communication bottlenecks. Furthermore, conventional multipliers have both operands encoded in the same physical quantity, which is either low cost to update or low cost to hold, but not both. This may be significant for low-energy edge operations. In this paper, we propose and present a mixed-signal multiply-accumulate unit design with in-memory computing to improve both latency and energy. This design is based on a single-bit multiplication cell consisting of a number of memristors and a single transistor switch (1TxM), arranged in a crossbar structure implementing the long-multiplication algorithm. The key innovation is that one of the operands is encoded in easy to update voltage and the other is encoded in non-volatile memristor conductance. This targets operations such as machine learning which feature asymmetric requirements for operand updates. Ohm’s Law and KCL take care of the multiplication in analog. When implemented as part of a NN, the MAC unit incorporates a current to digital stage to produce multi-bit voltage-mode output, in the same format as the input. The computation latency consists of memory writing and result encoding operations, with the Ohm’s Law and KCL operations contributing negligible delay. When compared with other memristor-based multipliers, the proposed work shows an order of magnitude of latency improvement in 4-bit implementations partly because of the Ohm’s Law and KCL time savings and partly because of the short writing operations for the frequently updated operand represented by voltages. In addition, the energy consumption per multiplication cycle of the proposed work is shown to improve by 74%–99% in corner cases. To investigate the usefulness of this MAC design in machine learning applications, its input/output relationships is characterized using multi-layer perceptrons to classify the well-known hand-writing digit dataset MNIST. This case study implements a quantization-aware training and includes the non-ideal effect of our MAC unit to allow the NN to learn and preserve its high accuracy. The simulation results show the NN using the proposed MAC unit yields an accuracy of 93%, which is only 1% lower than its baseline.
PubDate: 2022-09-26T00:00:00Z
- Biodegradable polymeric materials for flexible and degradable electronics
Authors: Zhiqiang Zhai, Xiaosong Du, Yin Long, Heng Zheng
Abstract: Biodegradable electronics have great potential to reduce the environmental footprint of electronic devices and to avoid secondary removal of implantable health monitors and therapeutic electronics. Benefiting from the intensive innovation on biodegradable nanomaterials, current transient electronics can realize full components’ degradability. However, design of materials with tissue-comparable flexibility, desired dielectric properties, suitable biocompatibility and programmable biodegradability will always be a challenge to explore the subtle trade-offs between these parameters. In this review, we firstly discuss the general chemical structure and degradation behavior of polymeric biodegradable materials that have been widely studied for various applications. Then, specific properties of different degradable polymer materials such as biocompatibility, biodegradability, and flexibility were compared and evaluated for real-life applications. Complex biodegradable electronics and related strategies with enhanced functionality aimed for different components including substrates, insulators, conductors and semiconductors in complex biodegradable electronics are further researched and discussed. Finally, typical applications of biodegradable electronics in sensing, therapeutic drug delivery, energy storage and integrated electronic systems are highlighted. This paper critically reviews the significant progress made in the field and highlights the future prospects.
PubDate: 2022-09-06T00:00:00Z
- Maximum efficiency control and predictive-speed controller design for
interior permanent magnet synchronous motor drive systems
Authors: Tian-Hua Liu, Yu-Hang Zhuang
Abstract: Improving the efficiency of home appliances is an important area of research these days, especially for global warming and climate change. To achieve this goal, in this paper, a new method to improve the maximum efficiency control of an interior permanent magnet synchronous motor (IPMSM) drive system, which includes an IPMSM and an inverter, is investigated. By suitably controlling the d-axis current, the IPMSM drive system can quickly reach its maximum efficiency. A steepest ascent method is used to obviously reduce the searching steps of the maximum efficiency tracking control for an IPMSM. According to experimental results, by using the traditional fixed step method, 14 steps are required to reach the maximum efficiency operating point. By using the proposed steepest ascent method, however, only 4 steps are needed to reach the maximum efficiency operating point. In addition, according to the experimental results, during the transient dynamics, the predictive controller obtains faster responses and 2% lower overshoot than the PI controller. Moreover, during adding external load, the predictive controller has only a 10 r/min speed drop and 0.1 s recover time; however, the PI controller has a 40 r/min speed drop and 0.3 s recover time. Experimental results can validate theoretical analysis. Several measured results show when compared to the fix-step searching method with a PI controller, the proposed methods provide quicker searching maximum efficiency ability, quicker and better dynamic transient responses, and lower speed drop when an external load is added.
PubDate: 2022-09-01T00:00:00Z
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