Journal of Low Power Electronics and Applications

19 pages, 9685 KB

Open AccessArticle

Dynamics of a Neuromorphic Circuit Incorporating a Second-Order Locally Active Memristor and Its Parameter Estimation

by Shivakumar Rajagopal, Viet-Thanh Pham, Fatemeh Parastesh, Karthikeyan Rajagopal and Sajad Jafari

J. Low Power Electron. Appl. 2025, 15(4), 62; https://doi.org/10.3390/jlpea15040062 - 13 Oct 2025

Neuromorphic circuits emulate the brain’s massively parallel, energy-efficient, and robust information processing by reproducing the behavior of neurons and synapses in dense networks. Memristive technologies have emerged as key enablers of such systems, offering compact and low-power implementations. In particular, locally active memristors [...] Read more.

Neuromorphic circuits emulate the brain’s massively parallel, energy-efficient, and robust information processing by reproducing the behavior of neurons and synapses in dense networks. Memristive technologies have emerged as key enablers of such systems, offering compact and low-power implementations. In particular, locally active memristors (LAMs), with their ability to amplify small perturbations within a locally active domain to generate action potential-like responses, provide powerful building blocks for neuromorphic circuits and offer new perspectives on the mechanisms underlying neuronal firing dynamics. This paper introduces a novel second-order locally active memristor (LAM) governed by two coupled state variables, enabling richer nonlinear dynamics compared to conventional first-order devices. Even when the capacitances controlling the states are equal, the device retains two independent memory states, which broaden the design space for hysteresis tuning and allow flexible modulation of the current–voltage response. The second-order LAM is then integrated into a FitzHugh–Nagumo neuron circuit. The proposed circuit exhibits oscillatory firing behavior under specific parameter regimes and is further investigated under both DC and AC external stimulation. A comprehensive analysis of its equilibrium points is provided, followed by bifurcation diagrams and Lyapunov exponent spectra for key system parameters, revealing distinct regions of periodic, chaotic, and quasi-periodic dynamics. Representative time-domain patterns corresponding to these regimes are also presented, highlighting the circuit’s ability to reproduce a rich variety of neuronal firing behaviors. Finally, two unknown system parameters are estimated using the Aquila Optimization algorithm, with a cost function based on the system’s return map. Simulation results confirm the algorithm’s efficiency in parameter estimation. Full article

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15 pages, 1662 KB

Open AccessArticle

Adaptive Hybrid Switched-Capacitor Cell Balancing for 4-Cell Li-Ion Battery Pack with a Study of Pulse-Frequency Modulation Control

by Wu Cong Lim, Liter Siek and Eng Leong Tan

J. Low Power Electron. Appl. 2025, 15(4), 61; https://doi.org/10.3390/jlpea15040061 - 1 Oct 2025

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Abstract

Battery cell balancing is crucial in series-connected lithium-ion packs to maximize usable capacity, ensure safe operation, and prolong cycle life. This paper presents a comprehensive study and a novel adaptive duty-cycled hybrid balancing system that combines passive bleed resistors and an active switched-capacitor [...] Read more.

Battery cell balancing is crucial in series-connected lithium-ion packs to maximize usable capacity, ensure safe operation, and prolong cycle life. This paper presents a comprehensive study and a novel adaptive duty-cycled hybrid balancing system that combines passive bleed resistors and an active switched-capacitor (SC) balancer, specifically designed for a 4-cell series-connected battery pack. This work also explored open circuit voltage (OCV)-driven adaptive pulse-frequency modulation (PFM) active balancing to achieve higher efficiency and better balancing speed based on different system requirements. Finally, this paper compares passive, active (SC-based), and adaptive duty-cycled hybrid balancing strategies in detail, including theoretical modeling of energy transfer and efficiency for each method. Simulation showed that the adaptive hybrid balancer speeds state-of-charge (SoC) equalization by 16.24% compared to active-only balancing while maintaining an efficiency of 97.71% with minimal thermal stress. The simulation result also showed that adaptive active balancing was able to achieve a high efficiency of 99.86% and provided an additional design degree of freedom for different applications. The results indicate that the adaptive hybrid balancer offered an excellent trade-off between balancing speed, efficiency, and implementation simplicity for 4-cell Li-ion packs, making it highly suitable for applications such as high-voltage portable chargers. Full article

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26 pages, 2759 KB

Open AccessReview

MCU Intelligent Upgrades: An Overview of AI-Enabled Low-Power Technologies

by Tong Zhang, Bosen Huang, Xiewen Liu, Jiaqi Fan, Junbo Li, Zhao Yue and Yanfang Wang

J. Low Power Electron. Appl. 2025, 15(4), 60; https://doi.org/10.3390/jlpea15040060 - 1 Oct 2025

Viewed by 373

Abstract

Microcontroller units (MCUs) serve as the core components of embedded systems. In the era of smart IoT, embedded devices are increasingly deployed on mobile platforms, leading to a growing demand for low-power consumption. As a result, low-power technology for MCUs has become increasingly [...] Read more.

Microcontroller units (MCUs) serve as the core components of embedded systems. In the era of smart IoT, embedded devices are increasingly deployed on mobile platforms, leading to a growing demand for low-power consumption. As a result, low-power technology for MCUs has become increasingly critical. This paper systematically reviews the development history and current technical challenges of MCU low-power technology. It then focuses on analyzing system-level low-power optimization pathways for integrating MCUs with artificial intelligence (AI) technology, including lightweight AI algorithm design, model pruning, AI acceleration hardware (NPU, GPU), and heterogeneous computing architectures. It further elaborates on how AI technology empowers MCUs to achieve comprehensive low power consumption from four dimensions: task scheduling, power management, inference engine optimization, and communication and data processing. Through practical application cases in multiple fields such as smart home, healthcare, industrial automation, and smart agriculture, it verifies the significant advantages of MCUs combined with AI in performance improvement and power consumption optimization. Finally, this paper focuses on the key challenges that still need to be addressed in the intelligent upgrade of future MCU low power consumption and proposes in-depth research directions in areas such as the balance between lightweight model accuracy and robustness, the consistency and stability of edge-side collaborative computing, and the reliability and power consumption control of the sensor-storage-computing integrated architecture, providing clear guidance and prospects for future research. Full article

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3 pages, 161 KB

Open AccessEditorial

Ultra-Low-Power ICs for the Internet of Things (2nd Edition)

by Orazio Aiello

J. Low Power Electron. Appl. 2025, 15(4), 59; https://doi.org/10.3390/jlpea15040059 - 1 Oct 2025

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Abstract

After the success of the first edition [...] Full article

(This article belongs to the Special Issue Ultra-Low-Power ICs for the Internet of Things (2nd Edition))

14 pages, 3756 KB

Open AccessArticle

Active Quasi-Circulator Based on Wilkinson Power Divider for Low-Power Wireless Communication Systems

by Kaijun Song, Xinsheng Chen and Zongrui He

J. Low Power Electron. Appl. 2025, 15(4), 58; https://doi.org/10.3390/jlpea15040058 - 1 Oct 2025

Viewed by 177

Abstract

This paper presents a microstrip active quasi-circulator designed for low-power wireless communication systems. The circuit consists of a second-order Wilkinson power divider and two power amplifiers with high gain and ultra-low noise characteristics. By leveraging the unidirectional transmission characteristics of the transistors and [...] Read more.

This paper presents a microstrip active quasi-circulator designed for low-power wireless communication systems. The circuit consists of a second-order Wilkinson power divider and two power amplifiers with high gain and ultra-low noise characteristics. By leveraging the unidirectional transmission characteristics of the transistors and the isolation provided by resistors within the power divider, the interference between the transmitter (TX) and receiver (RX) is effectively suppressed. Additionally, thanks to the dual-amplifier architecture, no extra power amplification circuitry is required, thereby reducing the overall complexity and power consumption of the communication system. The detailed design procedure of the proposed quasi-circulator is presented. The measurement results show that, within the frequency range of 4.75 GHz to 6.11 GHz, the isolation between the TX and RX ports exceeds 20 dB, the return loss at each port is greater than 10 dB, and the transmission gains from the TX port to the antenna and from the antenna to the RX port are 3.1–8.7 dB and 2.7–4.0 dB, respectively, demonstrating a relative bandwidth of 25%. Full article

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28 pages, 7493 KB

Open AccessArticle

Research on Frequency Characteristic Fitting of LLC Switching-Mode Power Supply Under All Operating Conditions Based on FT-WOA-MLP

by Jiale Guo, Rongsheng Han, Zibo Yang, Guoqing An, Rui Li and Long Zhang

J. Low Power Electron. Appl. 2025, 15(4), 57; https://doi.org/10.3390/jlpea15040057 - 28 Sep 2025

Viewed by 267

Abstract

The frequency characteristics of the switching-mode power supply (SMPS) control loop under all operating conditions are crucial for performance evaluation and defect detection. Traditional methods, relyingon experiments under preset conditions, struggle to achieve comprehensive evaluation. This study proposes a frequency characteristic fitting method [...] Read more.

The frequency characteristics of the switching-mode power supply (SMPS) control loop under all operating conditions are crucial for performance evaluation and defect detection. Traditional methods, relyingon experiments under preset conditions, struggle to achieve comprehensive evaluation. This study proposes a frequency characteristic fitting method for all operating conditions based on FT-WOA-MLP. A discrete-point dataset covering all conditions of an LLC SMPS was obtained using the small-signal perturbation method, including input voltage, output current, injection frequency, and corresponding amplitude- and phase-frequency characteristics. The multilayer perceptron (MLP) model was trained on the training set covering all operating conditions, with the whale optimization algorithm (WOA) used to optimize the learning rate, and fine tuning (FT) applied to further enhance accuracy. Independent test set validation showed that, for amplitude-frequency characteristics, the mean absolute error (MAE) was 2.0995, the mean absolute percentage error (MAPE) was 0.0974, the root mean square error (RMSE) was 4.0474, and the coefficient of determination (R²) reached 0.92; for phase-frequency characteristics, the MAE was 3.502, the MAPE was 0.0956, the RMSE was 10.5192, and the R² reached 0.94. The method accurately fits frequency characteristics under all conditions, supporting defect identification and performance optimization. Full article

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18 pages, 2888 KB

Open AccessArticle

Data Analysis of Electrical Impedance Spectroscopy-Based Biosensors Using Artificial Neural Networks for Resource Constrained Devices

by Marco Grossi and Martin Omaña

J. Low Power Electron. Appl. 2025, 15(4), 56; https://doi.org/10.3390/jlpea15040056 - 26 Sep 2025

Viewed by 399

Abstract

Portable and wearable sensors have gained attention in recent years to perform measurements in many different applications. Sensors based on Electrical Impedance Spectroscopy (EIS) are particularly promising, because they can make accurate measurements with minimum perturbation to the sample under test. Electrochemical biosensors [...] Read more.

Portable and wearable sensors have gained attention in recent years to perform measurements in many different applications. Sensors based on Electrical Impedance Spectroscopy (EIS) are particularly promising, because they can make accurate measurements with minimum perturbation to the sample under test. Electrochemical biosensors are devices that use electrochemical techniques to measure a target analyte. In the case of electrochemical biosensors based on EIS, the measured impedance spectrum is fitted to that of an equivalent electrical circuit, whose component values are then used to estimate the concentration of the target analyte. Fitting EIS data is usually carried out by sophisticated algorithms running on a PC. In this paper, we have evaluated the feasibility to perform EIS data fitting using simple Artificial Neural Networks (ANNs) that can be run on resource constrained microcontrollers, which are typically used for portable and wearable sensors. We considered a typical case of an impedance spectrum in the range 0.1 Hz–10 kHz, modeled by using the simplified Randles equivalent circuit. Our analyses have shown that simple ANNs can be a low power alternative to perform EIS data fitting on low-cost microcontrollers with a memory occupation in the order of kilo bytes and a measurement accuracy between 1% and 3%. Full article

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37 pages, 14177 KB

Open AccessReview

Wake-Up Receivers: A Review of Architectures Analysis, Design Techniques, Theories and Frontiers

by Suhao Chen, Xiaopeng Yu and Xiongchun Huang

J. Low Power Electron. Appl. 2025, 15(4), 55; https://doi.org/10.3390/jlpea15040055 - 23 Sep 2025

Viewed by 555

Abstract

The rapid growth of the Internet of Things (IoT) has driven the need for ultra-low-power wireless communication systems. Wake-up receivers (WuRXs) have emerged as a key technology to enable energy-efficient, near-always-on operation for IoT devices. This review explores the state of the art [...] Read more.

The rapid growth of the Internet of Things (IoT) has driven the need for ultra-low-power wireless communication systems. Wake-up receivers (WuRXs) have emerged as a key technology to enable energy-efficient, near-always-on operation for IoT devices. This review explores the state of the art in WuRXs design, focusing on low-power architectures, key trade-offs, and recent advancements. We discuss the challenges in achieving low power consumption while maintaining sensitivity, power consumption, and interference resilience. The review highlights the evolution from radio frequency (RF) envelope detection architectures to more complex heterodyne and subthreshold designs and concludes with future directions for WuRXs research. Full article

(This article belongs to the Topic Advanced Integrated Circuit Design and Application)

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J. Low Power Electron. Appl., Volume 15, Issue 4 (December 2025) – 8 articles

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