Michael Pecht

University of Maryland, College Park | UMD, UMCP, University of Maryland College Park · Center for Advanced Life Cycle Engineering (CALCE)

Quantum computing stands at the precipice of technological revolution, promising unprecedented computational capabilities to tackle some of humanity’s most complex problems. The field is highly collaborative and recent developments such as superconducting qubits with increased scaling, reduced error rates, and improved cryogenic infrastructure, tra...

Accurate flight regime identification is critical for enhancing aircraft efficiency and safety. Traditionally, predictive models for aircraft operation have relied on complex, black-box machine learning techniques that lack transparency. This study introduces a more interpretable approach by leveraging the New Comprehensive Modular Aero-propulsion...

Remaining useful life (RUL) prediction is a crucial aspect of the prognostics health management of lithium-ion batteries (LIBs). Owing to the influence of resampling technology, particle degradation is often observed in the particle filter-based RUL prediction of LIBs, resulting in a low prediction accuracy and large uncertainty. In this paper, a n...

The widespread use of flip-chip technology in the field of microelectronics packaging makes defect detection technology face great challenges, which requires the development of detection technology with less manual intervention, a lightweight network architecture, and high precision. Aiming at the dual-stability of the neural architecture search (N...

Prognostics and health management (PHM) is critical for enhancing equipment reliability and reducing maintenance costs, and research on intelligent PHM has made significant progress driven by big data and deep learning techniques in recent years. However, complex working conditions and high-cost data collection inherent in real-world scenarios pose...

This paper presents two methods of creating model predictive control strategies for efficient real-time control algorithms for power electronics. Two novel methods of performing nonlinear modeling are presented in this research, the first being novel Takagi-Sugeno model, which combines two linear state space models using a membership function to mo...

Solar photovoltaic (PV) systems are becoming increasingly popular because they offer a sustainable and cost-effective solution for generating electricity. PV panels are the most critical components of PV systems as they convert solar energy into electric energy. Therefore, analyzing their reliability, risk, safety, and degradation is crucial to ens...

In transportation and operation, lithium-ion batteries can be exposed to environments where the temperature exceeds 75 °C, compromising seal integrity and leading to electrolyte leakage and safety issues. Standards introduced by regulatory bodies require temperature testing, including temperature cycling tests. This study examines cylindrical batte...

Cylindrical lithium-ion batteries are widely used in consumer electronics, electric vehicles, and energy storage applications. However, safety risks due to thermal runaway-induced fire and explosions have prompted the need for safety analysis methodologies. Though cylindrical batteries often incorporate safety devices, the safety of the battery als...

In the above article [1] , the authors want to update the definition of fresh water provided in Sections II and VI based on discussions with the IEC.

A method is presented for predicting the health of turbofan engines using data and simulations from NASA. The method involves estimating engine health using k-nearest neighbors’ regression and fitting a remaining useful life model that considers engine usage. A matching pursuit algorithm identifies key parameters, while functional principal compone...

Electric vehicle (EV) battery swapping stations (BSWS) are an important aid in rapid transport electrification, especially in developing countries where per capita income is low and expensive battery prices discourage EV penetration. Consequently, a BSWS model, where the BSWS owns the battery, can help in EV penetration and rapid transport electrif...

Accurate state of health (SOH) estimation of lithium-ion batteries is essential to enhance the reliability and safety of a battery system. However, the SOH estimation accuracy based on a data-driven model is degraded by one health feature (HF) and incorrect hyper-parameters selection. This paper develops a battery SOH estimation method based on mul...

Wearable medical devices are widely used for monitoring and treatment of patients. Electrostatic discharge can render these devices unreliable and cause a temporary or permanent disturbance in their operation. In a healthcare environment, severe electrostatic discharge (ESD) can occur while a patient, lying down or sitting on a hospital bed with a...

Accurate state of charge (SOC) estimation is helpful for battery management systems to extend batteries’ lifespan and ensure the safety of batteries. However, due to the pseudo-positive definiteness of the covariance matrix and noise statistics error accumulation, the SOC estimation of lithium-ion batteries is usually inaccurate or even divergent u...

In recent years, electric vehicle safety incidents related to batteries have occurred frequently enough to question the adequacy of the current international safety standards. As the world’s leading producer of batteries for electric vehicles, China has thus formulated its own national standards, but there are questions as to the unique value of th...

Video calling is one of the most energy-intensive features in apps requiring the simultaneous operation of the mobile camera, display screen, audio speaker, and internet services. This feature impacts a smartphone battery's runtime and lifetime. This paper is the first of its kind experimental study, which quantifies the operating profile (discharg...

Parametric accelerated life testing (ALT) with the reliability quantitative (RQ) statements is offered as a reliability methodology to identify and rectify design flaws. The methodology includes: (1) BX lifetime with ALT scheme, (2) fatigue design, (3) ALTs with alterations, and (4) discernment whether the design(s) obtains targeted BX life. A quan...

With the continuous concern on the safety of battery systems, accurate and rapid assessment of battery degradation is essential for practical applications. In this paper, a transferable attention network model based on deep learning is developed to evaluate battery degradation, which can simultaneously predict state of health (SOH) and remaining us...

Fuel cell vehicles (FCVs) are among the so-called green vehicles. They offer high autonomy and fast refueling but are more expensive than other green vehicles. Several efforts are devoted to reducing costs to make FCV technology more accessible. Most research addressing the optimization of FCVs focuses on energy management, sizing of the subsystems...

The reasonable allocation of the battery energy storage system (BESS) in the distribution networks is an effective method that contributes to the renewable energy sources (RESs) connected to the power grid. However, the site and capacity of BESS optimized by the traditional genetic algorithm is usually inaccurate. In this paper, a power grid node l...

The existing transfer diagnosis methods based on entropy minimization are easy to lead to trivial solution. To solve this problem, a deep diversity maximization-based adversarial transfer diagnosis approach for rotating machinery is presented in this paper. Firstly, the deep convolution neural network is utilized as the feature encoder to learn the...

Obtaining the State of Health of lithium-ion batteries and mastering its degradation laws are crucial for the utilization of Electric Vehicles. However, the prediction of discharge capacity of lithium-ion batteries requires high accuracy, which is subject to the variation of cells and the uncertainty of operating conditions. In this work, a dischar...

Lithium-ion batteries are the ideal energy storage device for numerous portable and energy storage applications. Efficient fault diagnosis methods become urgent to address safety risks. The fault modes, fault data, fault diagnosis methods in different scenarios, i.e., laboratory, electric vehicle, energy storage system, and simulation, are reviewed...

Li-ion batteries degrade with time and usage, caused by factors like the growth of solid electrolyte interface (SEI), lithium plating, and several other irreversible electrochemical reactions. These failure mechanisms exacerbate degradation and reduce the remaining useful life (RUL). This paper highlights the importance of feature engineering and h...

Energy availability is a critical challenge for space missions, especially for those missions designed to last many decades. Space satellites have depended on various combinations of radioisotope thermoelectric generators (RGTs), solar arrays, and batteries for power. For deep space missions lasting as long as 50 + years, batteries will also be nee...

The objective of this letter is to study the prediction of the electromagnetic field and the output performance of permanent magnet eddy current devices based on a physics-informed sparse neural network (PISNN). In order to achieve this goal, a unified physical model is firstly defined according to different types of permanent magnet eddy current d...

Although deep learning has achieved remarkable results in the industry, to achieve the ultimate prediction accuracy improvement, many existing models with poor performance will be added with other modules, which will become more and more bloated. To achieve the deployment of the lightweight network in an industrial system, knowledge distillation (K...

The automotive industry’s increasing dependence on compact electronic packages requires printed circuit boards with robust microvia interconnections. With a focus on minimizing failure rates and reducing costs, automotive manufacturers require that microvia reliability have zero failures. To achieve this, the automotive industry requires identifica...

State of health (SOH) prediction is key to battery health management and safety. Health indicators (HIs) are effective and feasible to predict battery SOH. The existing approaches according to HIs focused on single-source features of HIs such as voltage, current or temperature by a single model to predict SOH. The accuracy and robustness of these a...

Recent works show that knowledge transfer is an effective strategy to solve cross-domain diagnosis problems. The existing domain adaptation methods considering both global and local distribution between domains do not make the most of the knowledge learned by deep neural network, resulting in low diagnosis accuracy. To solve this problem, a deep mu...

Recycling lithium-ion batteries (LIBs) has gained prominence in the last decade due to increasing supply chain constraints for critical materials (such as lithium and cobalt) and policy shift toward increased circularity of materials to mitigate environmental concerns. Conventional recycling methods (e.g., pyrometallurgical techniques) are suboptim...

The dependent competing failure process model has received increasing research attention in recent years due to its essential role in describing system reliability. For the δ shock model, as a main type of shock in dependent competing failure process, the system fails if the interval of time between two sequential shocks is less than a threshold δ....

The capacity of lithium-ion batteries decreases during usage (cycling) and storage (rest). After some initial charge-discharge cycling, the capacity fade rate has been observed to increase, and the capacity fade curve visibly bends, the onset of which is described as a knee point. The occurrence of the knee point above the end-of-life capacity thre...

The Jiles–Atherton model is widespread in the hysteresis description of ferromagnetic, ferroelectric, magneto strictive, and piezoelectric materials. However, the determination of model parameters is not straightforward because the model involves numerical integration and the solving of ordinary differential equations, both of which are error prone...

As fixed-wing unmanned aerial vehicles (FW-UAVs) are used for diverse civil and scientific missions, failure incidents are on the rise. Recent rapid developments in deep learning (DL) techniques offer advanced solutions for fault diagnosis of UAVs. However, most existing DL-based diagnostic models only perform well when trained on massive amounts o...

Rotating machinery fault diagnosis based on deep learning has been successfully applied in modern industrial equipment. However, many existing types of research suffer from two significant deficiencies. First, most deep neural networks are based on a single or same kind of similarity measurement method, which cannot fully exploit the data to extrac...

Image monitoring of oil wear particles is currently only applicable to microflows and is susceptible to bubble interference. This paper develops an optical oil-monitoring system that can be used for large-diameter pipes with high flow rates. A shallow and wide observation cell with an equivalent diameter of Φ5 mm is designed to allow a theoretical...

The large-scale retirement of electric vehicle traction batteries poses a huge challenge to environmental protection and resource recovery since the batteries are usually replaced well before their end of life. Direct disposal or material recycling of retired batteries does not achieve their maximum economic value. Thus, the second-life use of EV b...

This paper presents the various ways that lithium-ion batteries are being counterfeited, the problems that counterfeit batteries present, how they enter the consumer market, and the difficulties of detection. Simple external visual inspection of the battery is unreliable. As shown in the presented case study, even for the same brand batteries, thei...

The continuous occurrence of lithium-ion battery system fires in recent years has made battery system fault diagnosis a current research hotspot. For a series connected battery pack, the current of each cell is the same. Although there are differences in parameters such as internal ohmic resistance, the relative change of parameters between cells i...

Lithium-ion batteries must undergo a series of quality control tests before being approved for sale. In this study, quality control tests were carried out on two types of lithium-ion pouch batteries, here denoted as type A (with stacked electrode configuration) and type B (with a jelly-roll arrangement) to assess the effectiveness of the tests. Ele...

Lithium-ion battery diagnostics and prognostics rely on measurements of electrical impedance, capacity, and voltage to infer the internal state of the battery. Mechanical changes to the cell structure represent an additional measure of the battery’s state because these changes are related to the overall battery health. As lithium-ion batteries are...

Accurately predicting batteries’ ageing trajectory and remaining useful life is not only required to ensure safe and reliable operation of electric vehicles (EVs) but is also the fundamental step towards health-conscious use and residual value assessment of the battery. The non-linearity, wide range of operating conditions, and cell to cell variati...

This article presents a comparison between the performances of two chemistries of synthetic oil lubricants, polyalphaolefins (PAOs), and perfluoropolyethers (PFPEs) when applied on gold-plated electrical contacts operating at contact loads of 9.8 centiNewton (cN) and experiencing fretting-induced degradation. Performance assessment was done using t...

This paper proposes a novel nondestructive diagnostic method for flip chips based on an improved semi-supervised deep extreme learning machine (ISDELM) and vibration signals. First, an ultrasonic transducer is used to generate and focus ultrasounds on the surface of the flip chip to excite it, and a laser scanning vibrometer is applied to acquire t...

Analog circuits are a critical part of industrial electronics and systems. Estimates in the literature show that, even though analog circuits comprise less than 20% of all circuits, they are responsible for more than 80% of faults. Hence, analog circuit fault diagnosis and isolation can be a valuable means of ensuring the reliability of circuits. T...

Bearing fault diagnosis suffers from class imbalances and distributional discrepancies of fault data under different working conditions. The class imbalance of the fault class increases the difficulty of learning the classification boundary of the diagnostic model for the minority class. Furthermore, the diversities of feature distributions decreas...

Lithium-ion (Li-ion) batteries have increasingly been used in diverse applications. Accurate estimation of the state of health (SOH) of the Li-ion batteries is vital for all stakeholders and critical in various applications such as electric vehicles (EVs). The electrical equivalent circuit (EEC) 2-RC model is often used to model the battery operati...