IEEE

Data-Driven Fault Diagnosis of Lithium-Ion Battery Overdischarge in Electric Vehicles

Abstract: The overdischarge can significantly degrade a lithium-ion (Li-ion) battery's lifetime. Therefore, it is important to detect the overdischarge and prevent severe damage of the Li-ion battery.
IEEE

Safety-Critical Control With Control Barrier Function Based on Disturbance Observer

Abstract: In this article, we investigate the continuous and sampled-data safety-critical control problems with control barrier functions in the presence of time-varying disturbances. To this end, a ...
IEEE

Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey

Abstract: Deep learning is at the heart of the current rise of artificial intelligence. In the field of computer vision, it has become the workhorse for applications ranging from self-driving cars to ...
IEEE

Horus—A Fully Digital Polarimetric Phased Array Radar for Next-Generation Weather Observations

Abstract: Weather radars have become indispensable to meteorologists and the general public for both understanding and awareness of high-impact weather events and as part of the operational warning ...
IEEE

Federated Learning for Wireless Communications: Motivation, Opportunities, and Challenges

Abstract: There is a growing interest in the wireless communications community to complement the traditional model-driven design approaches with data-driven machine learning (ML)-based solutions.
IEEE

An Integrated Multitasking Intelligent Bearing Fault Diagnosis Scheme Based on Representation Learning Under Imbalanced Sample Condition

Abstract: Accurate bearing fault diagnosis is of great significance of the safety and reliability of rotary mechanical system. In practice, the sample proportion between faulty data and healthy data ...
IEEE

A Variational Bayesian-Based Unscented Kalman Filter With Both Adaptivity and Robustness

Abstract: This paper proposes a modified unscented Kalman filter (UKF) with both adaptivity and robustness. In the proposed filter, the adaptivity is achieved by estimating the time-varying ...
IEEE

1789-2015 - IEEE Recommended Practices for Modulating Current in High-Brightness LEDs for Mitigating Health Risks to Viewers

Abstract: This document includes a definition of the concept of modulation frequencies for light-emitting diodes (LEDs), a discussion on their applications to LED lighting, a description of LED ...
IEEE

DC Fault Protection Algorithms of MMC-HVDC Grids: Fault Analysis, Methodologies, Experimental Validations, and Future Trends

Abstract: To protect the converters and minimize the power transmission interruption during dc line faults, it is necessary to detect the faults at ultra high speed for the modular multilevel ...
IEEE

Improving Renewable Energy Forecasting With a Grid of Numerical Weather Predictions

Abstract: In the last two decades, renewable energy forecasting progressed toward the development of advanced physical and statistical algorithms aiming at improving point and probabilistic forecast ...
IEEE

Deep Learning for Household Load Forecasting—A Novel Pooling Deep RNN

Abstract: The key challenge for household load forecasting lies in the high volatility and uncertainty of load profiles. Traditional methods tend to avoid such uncertainty by load aggregation (to ...
IEEE

Improved Deadbeat Predictive Current Control of PMSM Drives With Repetitive Control-Based Disturbance Correction Observer

Abstract: In order to achieve high robustness and high-precision current control, this article proposes a disturbance correction observer based on repetitive control (RDCO) for deadbeat predictive ...