System-level Method Research Articles

Towards real-world state of health estimation: Part 2, system level method using electric vehicle field data

Accurate battery health estimation is pivotal for ensuring the safety and performance of electric vehicles (EVs). While predominant research has centered on laboratory-level single cells, the accurate estimation of battery system capacity using real-world data remains a challenge, due to the vast diversity in battery types, operating conditions, data recordings, etc. To this end, we release three large-scale field datasets of 464 EVs from three manufacturers, comprising over 1.2 million charging snippets. The EVs’ capacity and State of Health (SOH) are effectively labeled using K-means to cluster and concatenate charging snippets. A robust data-driven framework integrating a Gated Convolutional Neural Network (GCNN) for estimating battery capacity is proposed, and the results outperform other machine learning models. In addition, a fine-tuning technique is employed to further enhance model efficacy on new datasets and with limited training data. This research not only advances battery health estimations but also paves the way for broader applications in battery management systems (BMSs), offering a scalable solution to real-world challenges in battery technology.

Estimating the Prevalence of Using Suspected Counterfeit Medications in the General Population.

Counterfeit medications, sometimes referred to as "fake" or falsified drugs or pills, are drugs that are illicitly manufactured but designed to look like legitimate pharmaceuticals. Counterfeit medications are a growing public health concern. This study estimated the prevalence of self-reported use of suspected counterfeit medications by adults in the US and to assess what ingredients these individuals suspected were in the counterfeit medications. This general population survey, drawn from an online panel, was administered across 2 waves in 2022 (15 April 3 June and 9 September 21 October) to 59,041 adults aged 18 and older. Statistical calibration weighting was used to calculate estimates representative of the national adult population. An estimated 1.8% (95% CI 1.7%-1.9%) of respondents, corresponding to approximately 4.6 million adults, suspected past 12-month use of counterfeit medications. Fentanyl was the most commonly suspected ingredient in the counterfeit product (16.1%, 95% CI 12.8%-19.3%). The next most prevalent response was "I don't know" (15.0%, 95% CI 11.0%-18.9%) followed by methamphetamine (14.9%, 95% CI 11.4%-18.4%). These data show the scale of the issue in relation to other well established drug use data points in the US. System-level methods, such as drug scanning software, should be implemented to reduce the likelihood that counterfeit drugs end up in the hands of individuals.

Formal methods to comply with rules of the road in autonomous driving: State of the art and grand challenges

We provide a review of recent work on formal methods for autonomous driving. Formal methods have been traditionally used to specify and verify the behavior of computer programs and digital circuits. Enabled by abstraction techniques for dynamical systems and the availability of verification and synthesis tools for finite systems, they have been adopted by the control and robotics communities. In particular, in autonomous driving, recent research proposes formal languages such as temporal logics to specify driving behaviors ranging from safety, such as collision avoidance, to compliance with complex rules of the road. Our review focuses on formal verification, monitoring, and synthesis techniques enabling autonomous vehicles to adhere to such specifications. We only consider works about system-level methods that have an ego-centric perspective, i.e., we focus on the behavior of an autonomous vehicle in its entirety, rather than specific software code within the vehicle or traffic networks consisting of multiple vehicles. This paper also identifies the main remaining challenges.

A system-level method for hardening phase-locked loop to single-event effects

To mitigate the sensitivity of the charge pump in a traditional Phase-Locked Loop(PLL), a single-event-hardened PLL architecture with a proportional and integral path is proposed. The phase margin of the PLL is kept at 58.16° due to the rational design and the output clock frequency ranges from 0.8 to 3.2 GHz. The circuit-level simulation results reveal that the sensitive volume of the hardened PLL decreases by 80% ∼ 95%. The novel radiation-hardened PLL circuit was implemented in a 28 nm CMOS technology and irradiated with heavy ions with a linear energy transfer between 1.9 and 65.6 MeV•cm2 mg−1. The proposed radiation-hardened PLL shows one order of single-event effects hardness level higher than the conventional PLL.

An Overview of Lifetime Management of Power Electronic Converters

An expected lifetime of converters is of great importance for optimal decision-making in the planning of modern Power Electronic (PE) systems. Hence, the lifetime management of power electronic systems has attracted a lot of attention in academia and industry. This paper is a guideline for managing the lifetime of power converters. Analyzing the different kinds of failures, failure modes and their corresponding mechanisms are investigated in the first section along with the failure data needed as input parameters of the assessment. In the second section, lifetime prediction in two aspects of component-level and system level is discussed and all the possible techniques to achieve them are investigated and compared. All the steps required to predict the lifetime in the component-level including electrothermal modeling, cycle counting, lifetime model, damage accumulation, parameter estimation, and lifetime distribution are described and then system level methods consisting of reliability block diagrams, fault-tree analysis, and Markov chains are examined and compared. The last section contains the roadmap of the lifetime extension including the reliable design and condition monitoring.

Recurrent Urinary Tract Infections: Unraveling the Complicated Environment of Uncomplicated rUTIs

Urinary tract infections (UTIs) are frequent in humans, affecting the upper and lower urinary tract. Present diagnosis relies on the positive culture of uropathogenic bacteria from urine and clinical markers of inflammation of the urinary tract. The bladder is constantly challenged by adverse environmental stimuli which influence urinary tract physiology, contributing to a dysbiotic environment. Simultaneously, pathogens are primed by environmental stressors such as antibiotics, favoring recurrent UTIs (rUTIs), resulting in chronic illness. Due to different confounders for UTI onset, a greater understanding of the fundamental environmental mechanisms and microbial ecology of the human urinary tract is required. Such advancements could promote the tandem translation of bench and computational studies for precision treatments and clinical management of UTIs. Therefore, there is an urgent need to understand the ecological interactions of the human urogenital microbial communities which precede rUTIs. This review aims to outline the mechanistic aspects of rUTI ecology underlying dysbiosis between both the human microbiome and host physiology which predisposes humans to rUTIs. By assessing the applications of next generation and systems level methods, we also recommend novel approaches to elucidate the systemic consequences of rUTIs which requires an integrated approach for successful treatment. To this end, we will provide an outlook towards the so-called ‘uncomplicated environment of UTIs’, a holistic and systems view that applies ecological principles to define patient-specific UTIs. This perspective illustrates the need to withdraw from traditional reductionist perspectives in infection biology and instead, a move towards a systems-view revolving around patient-specific pathophysiology during UTIs.

Far-Term Noise Reduction Roadmap for the Midfuselage Nacelle Subsonic Transport

A noise reduction technology roadmap study is presented to determine the feasibility for the midfuselage nacelle (MFN) aircraft concept to achieve the noise goal set by NASA for the far-term timeframe, which is beyond 2035. The study starts with updating the noise prediction of the MFN configuration modeled for the timeframe between 2025 and 2035, with a prediction of 34.3 dB cumulative effective perceived noise level below the stage 4 regulation. A suite of technologies that are deemed feasible to mature for practical implementation in the far term and for which the potentials for noise reduction have been demonstrated is selected for analysis. For each technology, component noise reduction is modeled either by available experimental data or by physics-based modeling with aircraft system-level methods. The noise reduction is then applied to the corresponding component predicted by advanced aircraft noise prediction tools. It is shown that the far-term MFN aircraft has the potential to achieve a cumulative effective perceived noise level up to 40.2 dB below stage 4 if all noise reductions are fully realizable. The key technologies to achieve this low noise level are assessed by the impact of each technology on the aircraft system noise.

Impact of Family-Centered Tailoring of Pediatric T1D Self-Management Resources

Background: Experts recommend family-centered self-management approaches that address specific T1D self-management barriers for each child and family. However, no system-level method currently exists to identify and address these barriers. Objectives: To assess the impact on glycemic control and QoL for the child and parent of a family-centered approach to the delivery of diabetes self-management resources. Methods: Children 8-16 years old with T1D and their parent(s) were randomized to receive either tailored self-management resources (intervention) or usual care. Our intervention 1) identified families’ self-management barriers with a validated survey, 2) tailored self-management resources to identified barriers, and 3) delivered these resources as group sessions coordinated with diabetes visits to optimize convenience, efficiency, and sustainability. Mixed effects models with repeated measures were used to examine the intervention’s impact on A1c and parent and child QoL during the 9-month intervention period and for a year thereafter. Results: Among 363 potentially eligible families, 267 (74%) consented to participate. Randomization allocated 1families to usual care and 1to the intervention. Participants were children (8-12 years, 44%) and teens (13-16 years, 56%). Mean diabetes duration was 5.4 years (sd 3.3) and 14% had an A1c <7.5%. Most families (69%) attended at least 3 of the 4 intervention sessions. No overall intervention effect on A1c or QoL for the child or parent was shown. However, at one site, mean A1c in the year post-intervention declined by 0.059% more per month for intervention group teens than for those receiving usual care (p=0.02). At this same site, mean parent QoL increased by 0.61 points per month more during the intervention for parents of intervention group children than parents of those receiving usual care (p=0.03). Conclusions: Findings can inform healthcare organizations’ decisions about ways to best deliver diabetes self-management resources. Disclosure R.V. Fiallo-Scharer: None. V.P. Rajamanickam: None. B.A. Chewning: None. M. Palta: None. T.B. Wetterneck: None. T. Wysocki: None. E.D. Cox: None.

Surviving the Heat Wave – A presentation on thermally induced failures and reliability risks created by advancements in electronics technologies

Abstract Since the advent of surface mount technology back in the 1970's we, as an industry, have continually worked to miniaturize our products. This evolution of product design has impacted us at the semiconductor, package, circuit board and system levels. So, the question is, Why do Electronics Fail Under Thermal Cycling? At the semiconductor level, you can have issues with delamination, IC complexity, degradation mechanisms, associated ceramic capacitor wearout, and electrical overstress (EOS). At the package level issues with bond wires and stacked die add to the reliability impact. At the printed circuit board level issues with solder wearout, solder phase coarsening, PWB laminates and glass materials, plated through hole (PTH) fatigue, and the impact of potting can also affect reliability while at the system level, heat sinks and other methods of heat removal can improve the situation. What drives these issues is that we use a variety of materials e.g. semiconductors, ceramics, metals and polymers. We then bond them together with other materials like solder and adhesives. Each of these materials has a Coefficient of Thermal Expansion (CTE) that is unique and therefore expands and contracts at different rates.

Trust Filter: Runtime Hardware Trojan Detection in Behavioral MPSoCs

This work introduces a runtime system level method to detect hardware Trojan in third party behavioral intellectual properties (3PBIPs). Most of the HW Trojan detection techniques either rely on golden Trojan-free (trusted) models, which are compared to the suspected model, or source IPs with the same functionality from different vendors. In the case of BIPs, this is extremely hard, as it is a market still in its infancy. Moreover, it is very difficult to find HW Trojan at the system level as the trigger condition might be visible only when the system is fully functional. Thus, this work proposes the inclusion of a small HW Trojan detection circuit called trust filters to detect HW Trojan at runtime. With the help of cycle-accurate simulation model, it is possible to fine tune these filters so that the overall system has no performance degradation. This can be achieved by exploiting the slack time between the time that a slave returns the data to the master and the time that the master sends new data to the slave. The advantages of using C-based design are multi-fold: (i) It allows the generation of fast cycle-accurate models to measure the exact slack of each BIP mapped as a loosely coupled Hardware Accelerator (HWAcc) slave and (ii) its ability to build the complete SoC using synthesizable Application Programming Interfaces (APIs) and hence allowing the fine tuning of these trust filters. Experimental results show that our proposed architecture is very efficient leading to no performance penalties in many cases and has very small area overhead.

Applied system‐level method in calibration validation for personal navigation system in field

A system-level method to validate previous calibration results for low-precision inertial measurement unit (IMU) in personal navigation system (PNS) is proposed. Micro-electro mechanical systems inertial sensors have gained popularity in PNS because they are small, compact and inexpensive. However, the calibration results of these sensors which belong to low-grade IMU will change as time and environment change. It is significant to know whether previous calibration results are reliable for navigation after a long time. However, users have no devices such as turntable to validate calibration results precisely. Therefore, a triple two-position method without any external aiding is presented to validate the bias errors relative to previous calibration results. If the errors are less than the bias range which is a priori information calculated in previous lab test, previous calibration results are available, otherwise the calibration results is invalid. The two-position method based on the strong tracking filter, which takes velocity and azimuth errors as observations, can estimate the bias and scale factor errors of accelerometers and gyros. The experimental results show that the proposed method is effective, compared with the conventional 24-position calibration method on the turntable and the system-level multi-position method usually used for high-grade IMU.

Design, management and control of demanufacturing and remanufacturing systems

In the recent years, increasing attention has been posed towards enhancing the sustainability of manufacturing processes by reducing the consumption of resources and key materials, the energy consumption and the environmental footprint, while also increasing companies’ competitiveness in global market contexts. De- and remanufacturing includes the set of technologies/systems, tools and knowledge-based methods to recover and reuse functions and materials from industrial waste and post-consumer products, under a Circular Economy perspective. This new paradigm can potentially support the sustainability challenges in strategic manufacturing sectors, such as aeronautics, automotive, electronics, consumer goods, and mechatronics. A new generation of smart de- and remanufacturing systems showing higher levels of automation, flexibility and adaptability to changing material mixtures and values is emerging and there is a need for systematizing the existing approaches to support their operations. Such innovative de- and remanufacturing system design, management and control approaches as well as advanced technological enablers have a key role to support the Circular Economy paradigm. This paper revises system level problems, methods and tools to support this paradigm and highlights the main challenges and opportunities towards a new generation of advanced de- and remanufacturing systems.

Recording and Transferring Head Positions to the Virtual Head Using a Multicamera System and Laser Level

To fulfill the requirements of computer-aided orthognathic surgery, the authors developed a method of recording head positions in pitch and roll and tested its accuracy and reliability. A laser level was used to project a horizontal laser line onto a volunteer's face. A 3-dimensional (3D) photograph of the volunteer was taken to capture the laser line using the 3dMDface System, so the head positions could be recorded. To test the accuracy and reliability of this method, 35head positions were recorded and compared with the positions recorded by the gyroscope method (Pn for pitch and Rn for roll). A cone-beam computed tomographic (CBCT) scan was taken, during which the head position was recorded by the gyroscope (P0 and R0). CBCT data were imported into ProPlan CMF 1.3 software and a virtual head was created. To reproduce each recorded head position, each 3D photograph was superimposed onto the virtual head through surface registration, and the virtual head was rotated to make the laser line parallel to the coordinate axes in the lateral and frontal views; the rotation angles were recorded, respectively, as Pn' and Rn'. Under ideal conditions, Pn' should equal Pn - P0 and Rn' should equal Rn - R0. The accuracy was evaluated using the Bland-Altman method. Reliability was tested by intraclass correlation coefficient (ICC) analysis. The 95% limits of agreement between the rotation angles recorded by the present method (Pn',Rn') and the gyroscope method (Pn - P0, Rn - R0) were -0.598° to 1.589° for pitch and -1.156° to 1.674° for roll; such a difference was generally accepted as being accurate. The ICCs were 0.996 (0.992, 0.998) for pitch and 0.998 (0.997, 0.999) for roll. The 3dMDface System and laser level method of recording head positions was accurate and reliable.

Bridging the gap between theory and practice in LPV fault detection for flight control actuators

Two different approaches for fault detection, the geometric and the detection filter based methods, are compared in the paper from practical aspects, using the linear parameter-varying (LPV) framework. Presenting two designs allows a comparison of global, system level, and local component level fault detection methods with special emphasis on their relevance to aircraft industry. Practical engineering design decisions are highlighted via applying them to a high-fidelity commercial aircraft problem. The successive steps of the design, including fault modeling, LPV model generation, and LPV FDI filter synthesis, including implementation aspects, are discussed. Results are presented according to the industrial assessment perspectives phrased within the EU ADDSAFE project.

Medial prefrontal cortex: genes linked to bipolar disorder and schizophrenia have altered expression in the highly social maternal phenotype.

The transition to motherhood involves CNS changes that modify sociability and affective state. However, these changes also put females at risk for post-partum depression and psychosis, which impairs parenting abilities and adversely affects children. Thus, changes in expression and interactions in a core subset of genes may be critical for emergence of a healthy maternal phenotype, but inappropriate changes of the same genes could put women at risk for post-partum disorders. This study evaluated microarray gene expression changes in medial prefrontal cortex (mPFC), a region implicated in both maternal behavior and psychiatric disorders. Post-partum mice were compared to virgin controls housed with females and isolated for identical durations. Using the Modular Single-set Enrichment Test (MSET), we found that the genetic landscape of maternal mPFC bears statistical similarity to gene databases associated with schizophrenia (5 of 5 sets) and bipolar disorder (BPD, 3 of 3 sets). In contrast to previous studies of maternal lateral septum (LS) and medial preoptic area (MPOA), enrichment of autism and depression-linked genes was not significant (2 of 9 sets, 0 of 4 sets). Among genes linked to multiple disorders were fatty acid binding protein 7 (Fabp7), glutamate metabotropic receptor 3 (Grm3), platelet derived growth factor, beta polypeptide (Pdgfrb), and nuclear receptor subfamily 1, group D, member 1 (Nr1d1). RT-qPCR confirmed these gene changes as well as FMS-like tyrosine kinase 1 (Flt1) and proenkephalin (Penk). Systems-level methods revealed involvement of developmental gene networks in establishing the maternal phenotype and indirectly suggested a role for numerous microRNAs and transcription factors in mediating expression changes. Together, this study suggests that a subset of genes involved in shaping the healthy maternal brain may also be dysregulated in mental health disorders and put females at risk for post-partum psychosis with aspects of schizophrenia and BPD.

包含非线性组件的系统级电磁效应分析方法

包含非线性组件的系统级电磁效应分析方法

System-Level Simulation and Fabrication of On-Chip Fatigue Bending Test Structure for Micro-Scale Polysilicon Films

Two kind of on-chip integrated fatigue bending test structures are designed through system-level simulation method based on macromodels to measure the fracture strength and fatigue mechanical properties of polysilicon thin films. The first on-chip fatigue test structure is actuated by V-beam thermal actuator, and the other test structure actuated by electrostatic comb. The static and dynamic analysis was performed by Coventorware Architect module using self-bulid reduced order model described with the MAST hardware language and some other commercial parts from Coventorware parts library. The structural dimension parameters are determined and optimized according to system-level simulation and the computing result has shown that the self-build macromodels and the on-chip integrated test system are efficient and reliable. Two kinds of polysilicon on-chip fatigue bending test structure were fabricated with two-layer polysilicon surface micromachining process in Institute of Microelectronics, Peking University.

Switching Optimization for Class-G Audio Amplifiers with Two Power Supplies

This paper presents a system-level method to decrease the power consumption of integrated audio Class-G amplifiers for mobile phones by using the same implementation of the level detector, but by changing the parameters of the switching algorithm. This method uses an optimization based on a simplified model simulation to quickly find the best power supply switching strategy in order to decrease the losses of the internal Class-AB amplifier. Using a few relevant equations of Class-G on the electrical level and by reducing the number of calculation points, this model can dramatically reduce the calculation time to allow power consumption evaluation in realistic case conditions compared to the currently available tools. This simplified model also evaluates the audio quality reproduction thanks to a psycho-acoustic method. The model has been validated by comparing model results and practical measurements on two industrial circuits. This proposed model is used by an optimizer based on a genetic algorithm associated with a pattern search algorithm to find the best power supply switching strategy for the internal Class-AB amplifier. The optimization results improve life-time performance by saving at least 25% in power consumption for typical use-case (1mW) compared to the industrial circuit studied and without losses in audio quality.

Pulmonary vascular stiffness: measurement, modeling, and implications in normal and hypertensive pulmonary circulations.

This article introduces the concept of pulmonary vascular stiffness, discusses its increasingly recognized importance as a diagnostic marker in the evaluation of pulmonary vascular disease, and describes methods to measure and model it clinically, experimentally, and computationally. It begins with a description of systems-level methods to evaluate pulmonary vascular compliance and recent clinical efforts in applying such techniques to better predict patient outcomes in pulmonary arterial hypertension. It then progresses from the systems-level to the local level, discusses proposed methods by which upstream pulmonary vessels increase in stiffness, introduces concepts around vascular mechanics, and concludes by describing recent work incorporating advanced numerical methods to more thoroughly evaluate changes in local mechanical properties of pulmonary arteries.

Purpose-driven biomaterials research in liver-tissue engineering

Bottom-up engineering of microscale tissue ("microtissue") constructs to recapitulate partially the complex structure-function relationships of liver parenchyma has been realized through the development of sophisticated biomaterial scaffolds, liver-cell sources, and in vitro culture techniques. With regard to in vivo applications, the long-lived stem/progenitor cell constructs can improve cell engraftment, whereas the short-lived, but highly functional hepatocyte constructs stimulate host liver regeneration. With regard to in vitro applications, microtissue constructs are being adapted or custom-engineered into cell-based assays for testing acute, chronic and idiosyncratic toxicities of drugs or pathogens. Systems-level methods and computational models that represent quantitative relationships between biomaterial scaffolds, cells and microtissue constructs will further enable their rational design for optimal integration into specific biomedical applications.