Our Research Projects

Extreme Fast Charging (“XFC”) for Plug-in Electric Vehicles

Subhashish Bhattacharya
01/01/2020 - 07/31/2022

Extreme fast charging (“XFC”) for plug-in electric vehicles: Medium Voltage XFC AC-DC Power Electronic converter System:
The schematic of three-phase medium voltage extreme fast charging AC-DC power electronic conversion system (XFC-ACDC) is shown in Fig. 1. The XFC-ACDC unit consists of three phase-modules whose input AC terminals are connected in Y-connection and their DC outputs are connected in parallel. The inputs of XFC-ACDC is connected to a 10 kV (Line-Line) three-phase MVAC grid and the output connected to a 1000 V DC bus across which various charging vehicles and equipment are integrated. Each phase-module of XFC-ACDC consists of a cascaded H-bridge converter and multiple dual active bridge converters (DABs). 1.7 kV SiC switches will be used for implementing the CHB and DAB converters. The voltages across the DC link capacitors of CHB will be maintained at 1.2 kV. The DABs will be regulated to maintain a voltage of 1000 V at their outputs.

FPGA Hardware Accelerator for Real Time Security, CAEML Core Project

Paul D. Franzon, Aydin Aysu
01/01/2020 - 12/31/2020

Build malware detector for detecting ransomware attacks in real time.

Si2 Power and Reliability Standards Development

William R. Davis
01/01/2020 - 05/15/2020

This effort will develop standards in collaboration with the Silicon Integration Initiative (Si2), including the Universal Power Model (UPM) and Compact Modeling Coalition (CMC) Open Model Interface (OMI) for Reliability Simulation. In addition, this effort will develop parallel computing methods for integrated circuit design databases.

Caterpillar BCP – Personnel and Object Avoidance System, ECE Sr Design Project Fall 2019-Spring 2020

Bobby Leonard Compton
08/21/2019 - 05/31/2020

A system to detect personnel and objects that is intended to be applied to industrial moving equipment

Accurate Modeling of Indoor Environments Using a LiDAR for Efficient mmWave Network Planning and Understanding mmWave Propagation Channel Characteristics

Ismail Guvenc
02/05/2020 - 03/31/2020

There is ample literature on channel models and network planning for sub-6 GHz frequencies. However, since the channel propagation characteristics at millimeter-wave (mmWave) bands are significantly different from that of the sub-6 GHz bands, for reliable results, designated solutions are needed for mmWave systems. The major challenge with the mmWave frequencies is the high loss rates in terms of both free-space path loss and penetration losses. Therefore, while planning the mmWave network, it is utmost important to model the environment accurately, i.e., dimensions of the rooms, furniture, objects, material types, etc. In this project, we will use a LiDAR sensor for 3D mapping of indoor environments and transfer the created maps to Wireless InSite software to find the optimal base station (BS) locations that maximize the coverage rate. We will also generate binary occupancy maps from the LiDAR maps and use them along with the analytical channel models in machine learning algorithms to automate the mmWave BS placement. Indoor maps created with the LiDAR sensor will also provide the opportunity for a fair comparison between the channel measurements from the ray-tracing simulations and the measurements from the real-life experiments conducted with our NI-based channel sounder.

Photovoltaic Analysis and Response Support (PARS) Platform for Solar Situational Awareness and Resiliency Services

Ning Lu, Mesut E. Baran, & Srdjan Miodrag Lukic
11/01/2019 - 10/31/2022

In this project, we will develop a Photovoltaic Analysis and Response Support (PARS) platform for improving solar situation awareness and providing resiliency services. The team will focus on developing new operation modes for solar energy systems and a PV+DER situation awareness tool to enable accurate estimation and predication of PV and DER operation conditions in both normal operation conditions and in emergency operation when there is a wide spread outage caused by natural disasters or coordinated cyber attacks. Real-time dynamic studies will be conducted to compute system operation conditions for different operation options. This tool will be run on real-time simulation platform so that optimal restoration plans can be developed in real-time using operation modes enabled by Tasks 1 and parameters derived in Task 2. The team will model transmission, distribution, and all the way down to each DER and inverter units at utility scale PV farms on a multi-core OPAL-RT real-time simulation platform.

Systems-level measurements of biophysical parameters in the Dorsal/NF-kappaB pathway

Gregory T Reeves, Cranos Williams
07/01/2019 - 06/30/2022

In the past decade and a half, our understanding of developmental biology has been revolutionized by real-time, live experimental approaches, which have acquired vast quantitative data sets and challenged established views of tissue patterning. It is now understood that gene expression does not simply rely on a steady state level of morphogen signaling, and thus, simple, intuitive descriptions of tissue patterning are no longer sufficient. To continue at the forefront of research, there must be a synergism of quantitative, real-time experiments, together with predictive computational models that synthesize the wealth of data into a coherent mathematical framework. However, it has been shown that such systems biology models have “sloppy parameters,” meaning there is a large ensemble of diverse parameter sets that each fit the noisy biological data sufficiently. This greatly reduces the predictive power of the models.
Therefore, the overall objective of this proposal is to perform detailed measurements of local biophysical parameters and global morphogen gradient properties to build and constrain a predictive, computational model of the Dorsal/NF-κB gradient in the early Drosophila embryo. During this stage, NF-kappaB signaling directs the formation of muscle, skin and neurons. Furthermore, the NF-kappaB pathway is highly conserved (i.e., the same) in all animals from flies to humans, making the lessons learned about NF-kappaB signaling in fruit flies directly relevant to human cancer research.
The central hypothesis is that such measurements, acting as model constraints, will greatly increase the model’s predictive power. Our hypothesis is based on our preliminary data and previous modeling experience of this pathway. Given that we also have experience in detailed measurements of this pathway, our lab has the capacity to perform this work. Only a few labs worldwide have combined both quantitative, real-time measurements with mechanistic models in the same system, which makes our lab nearly unique.
The expected outcomes of the work will be a more detailed understanding of the NF-κB module at the local and global level, as well as a model that can generate testable predictions. We expect these outcomes to have an important positive impact, because they will advance not only our understanding of the dynamics of Dorsal gradient formation, but the general field of biological modeling. Testing our central hypothesis will show whether models necessarily contain “sloppy parameters,” or may lead to discovering additional aspects that can improve the model. The proposed research will also our general knowledge of the NF-κB signaling module that can be found in animals from Cnidarians to humans.

Developing a Combined System Model and Simulation Process for Integrated Planning and Operations across Transmission and Distribution Systems, CAPER Enhancement Project

David Lee Lubkeman, Ning Lu
11/01/2019 - 12/31/2020

In this project, the team will investigate the ability of performing steady state analysis of distributed energy resources (DER) at both the distribution and transmission levels with a combined model. Currently this analysis is often performed by Duke Energy using Siemens PTI’s PSS®E on the transmission level and using Eaton CYMDIST on the distribution level. The team will evaluate the ability to perform a unified DER analysis involving various types of T&D interconnections and potential interactions using a single simulation software tool(s) for analysis and planning of multiple network types. Given the increasing levels of DER devices seen at the distribution level, it is no longer feasible to perform only a distribution feeder-level analysis. Given the new ride-through and other requirements in the updated IEEE 1547 standard set, it will be necessary to evaluate the impact of transmission-level events to DER interconnections at the distribution-level to evaluate potential loss of DER generation. Also, the increased level of distribution DERs back-feeding into transmission is now impacting transmission-level operation and protection. Analyzing higher-penetration levels of DERs necessitates the need for an integrated analysis using a combined T & D model.

Developing a Path Forward for the Integration of the Coordinated Real-time Sub-Transmission Volt-Var Control Tool (CReST-VCT) into Energy Management Systems (EMS)

Ning Lu
01/06/2020 - 09/30/2020

DOE EERE SETO has been funding PNNL and North Carolina State University (NCSU) to develop a Coordinated Real-time Sub-Transmission Volt-Var Control Tool (CReST-VCT) to optimize the use of reactive power control devices to stabilize voltage fluctuations caused by intermittent solar photovoltaic (PV) outputs. CReST-VCT offers an innovative optimization approach for Volt/Var co-optimization of sub-transmission and distribution systems . This tool will remove a major roadblock to the increased use of distributed PV while maintain reliability of distribution and sub-transmission networks.
In this proposed project, PNNL and NCSU (tool developers) will work with ABB, a major commercial vendor of energy management systems (EMS) and distribution management systems (DMS), to develop a path forward for the integration of the CReST-VCT into the ABB EMS. We will identify issues related to communications requirements, interoperability, and compliance with revised IEEE 1547. Stakeholder outreach will be a key to commercialize the algorithms, models, and patents that have been developed in the SETO-funded project. We will survey utilities to understand their needs. We will talk to smart inverter vendors to understand what they can offer. Finally, we will develop a white paper on the recommended path forward for CReST-VCT commercialization.
CReST-VCT is built by PNNL based on algorithms that can coordinate the control logics of the existing grid reactive power compensation devices, from the sub-transmission system down to the distribution system, in addition to required VAr support from distributed PVs . At the distribution level, NCSU has developed a Voltage Sensitivity Matrix (VSM)-based optimal dispatch algorithm to coordinate customer-owned DERs with utility-owned devices for meeting the real and reactive power control objectives . An overview of CReST-VCT distribution Volt/Var optimization is shown in Figure 1. This tool will achieve one of EERE SETO’s systems integration (SI) goals by enabling increased use of distributed PV. The proposed tool achieves the OE Resilient distribution system (RDS) technology area goal of providing resilient grid services through management of all assets across the distribution power system.
The ultimate goal of this project is for PNNL and NSU to build a clear plan for integrating CReST-VCT into the ABB EMS/DMS systems and proposing this integration effort as a future Topic 2 TCF effort.

Wearable Cerebral Oximetry

Alper Yusuf Bozkurt
08/09/2019 - 02/09/2021

Low burden and vigilant physiological monitoring of service members in the operational environment would provide better individual awareness and more actionable information for better planning by military decision makers. NIRSense proposes a wearable cerebral oximeter to directly monitor neural activity by measuring state changes in oxygenation of blood in the wearer’s prefrontal cortex.

Amorphous and Nanocomposite Magnets for High Efficiency, High Speed Motor Designs

Subhashish Bhattacharya
03/01/2017 - 09/30/2020

Amorphous and Nanocomposite Magnets for High Efficiency, High Speed Motor Designs
Electric motors use soft and/or hard ferromagnets to produce or direct spatiotemporally varying magnetic flux. World Bank reports [1] the US consumed ~4 trillion kW-h of electricity in 2009 with ~30% consumed by motors. New materials can reduce losses (~58%) between the rotor and stator with a 1% improved motor efficiency results in saving ~12 billion kW-h. Rare earth (RE) permanent magnet (PM) motors are popular but soft magnetic materials (SMMs) provide the greatest potential for energy savings [2-4]. Supply constraints on RE elements (China controls ~ 80%), cause concerns which led NATO to classify them as critical elements [5-6]. We will demonstrate RE-free 5 kW motors with 4% increased efficiency using metal amorphous nanocomposite (MANC) SMMs. A 200 W power loss, portioned equally, will need power reductions of: a) controller: 50 W; (b) copper loss: 50 W; (c) iron loss: 50 W; (d) windage, 50 W.
MANCs are a transformational technology to increase efficiency and limit RE use in high speed electric motors (HSEMs). Hybrid motors employ a REPM rotor and high induction SMM stator. New SMMs replacing laminated FeSi in stators can reduce motor size [3-4]. CMU MANC SMMs [7] have inductions comparable to Si-steels and resistivities [8] to enable high switching f’s necessary for high torques to allow motor size and weight reduction. We will investigate MANC motors targeting 1-10 kHz frequencies in stator geometries for HSEMs. Materials development builds on Fe-Co [9], Co-rich [10] and Ni-rich [11] MANCs with high inductions, low losses, strain induced anisotropy and excellent mechanical and high-T magnetic properties. MANC SMMs investigated in high-f ARPA-E power transformation applications resulted in a T2M plan to penetrate motor markets. MANCs have (1) low direct-current (dc) hysteresis losses; (2) thinner laminations offering lower ac eddy-current losses. Lower iron losses than Si steel sheets, allow MANC motors to operate at higher rotational speeds. PPMT (Parallel Path Magnetic Technology) topology motors with Co-base MANCs, as compared to Si steel, allowed a high-speed design reducing machine size (~70 %), and RE hard magnet volume (~83 %).

Indoor Ray Tracing and Base Station Placement Optimization for mmWave Systems, BWAC Core Project

Ismail Guvenc
10/01/2019 - 09/30/2020

Smart deployment of base stations (BSs) can help reduce the infrastructure costs while keeping the service quality at a desired minimum. The BS placement problem has been studied extensively for sub-6 GHz frequencies for both indoor and outdoor environments. However, the frequencies below 6 GHz are highly occupied, which makes frequencies at millimeter-wave (mmWave) bands attractive due to the vast amount of unused spectrum available for the fifth generation (5G) network. Besides, channel propagation characteristics of the mmWave band are significantly different from that of the sub-6 GHz band. mmWaves, due to using higher frequencies ranging from 30 to 300 GHz, are more vulnerable to blocking, and hence the presence of line-of-sight (LoS) links is more desired. Moreover, a typical mmWave link suffers an orders-of-magnitude larger path loss than a traditional sub-6 GHz link. Therefore, the mmWave network planning is more dependent on the layout of the environments. mmWave infrastructure also needs to be densely deployed to overcome the path loss and blockage problems, and to increase the LoS probability. This necessity may lead to many other problems, such as serious interference. The goal of this research is to understand the differences of network coverage in different bands for various indoor settings and to automate the mmWave BS placement with the aim of achieving high coverage with a minimum number of BSs.

Health Analytics Tooling: Retrieval, Assessment Decision and Trending

Hamid Krim
06/01/2018 - 11/30/2019

With a focus on Diabetes in Phase 1, we propose the development of a comprehensive tool which will systematically and seamlessly navigate across the various hybrid data accessible through UNC Medical Records, with a health assessment enabling capability as well as various possible trends. More specifically, we plan on fully exploiting the tools of machine learning and bring them to bear on each step of the data analysis and exploitation. In close consultation with the health specialists, we will develop a mapping mechanism of qualitative data to the quantitative space, thus homogenizing the data. In addition, we plan to design a “Decision Tree” (DT) adapted to our homogenized data. We will exploit the characteristic computational efficiency of tree structures to comb through each patient’s data to yield a quantifiable assessment of interest (e.g. patient is cured as a result of treatment, follow up visits, prescription follow up, and cross validated with State Vital Records). Note that the proposed DT-based analyses not only play a key role in the analysis of trends across populations of patients, but also can also be used to conduct other global statistical analyses (e.g. probabilistically determine a permanent cure conditioned on a life style).
Our plan is to have a Personal Computer-based menu-driven tool with a comprehensive set of options, including visualizations, to carry through a thorough exploration of data; the planned interactive operation will necessitate some attention to identifying and solving all computational bottlenecks in this process.

Data Analytics Using Advanced Meeting Data

Mesut E. Baran, Ning Lu
01/01/2020 - 12/31/2020

With new technologies such as AMI, utilities now have an abundance of data, however, they are doing very little with this data. Because of this situation, we will collaborate with our sponsor ElectriCities to investigate and develop applications for data analytics for utility operations and customers programs.

Development of Low-Power Electronics for ASSIST’s Self-Powered Adaptive Platform

Yaoyao Jia
09/01/2019 - 08/31/2020

In Year 8, this project mainly focuses on developing low-power electronics using commercial off-the-shelf (COTS) components for ASSIST’s Self-Powered Adaptive Platform (SAP). Two versions of SAP hardware prototypes will be developed in this project. More specifically, the major work regarding the development of the SAP hardware prototype will be developing the low-power circuit boards for ECG sensing, firmware programming the microcontroller unit (MCU) to enable the BLE data transmission and implement finite state control algorithms, and integrating the SAP hardware prototype into the current form factor (smart shirt). The main challenging of developing the SAP hardware prototype is how to reduce its power consumption to the target of

Quantifying Cost-of-Service Impacts of Distributed Generation

Wenyuan Tang, Mesut E. Baran
01/01/2020 - 12/31/2020

This project will focus on investigating the impact of distributed generation (DG) on a utility distribution system from the cost-of-service perspective and developing a methodology to quantify those costs. The NCSU team will closely collaborate with the related groups in Duke Energy to determine which impacts can be reasonably quantified, present the developed methodology to the Public Staff and other stakeholders, and potentially file expert testimony in a general rate case. This project is primarily an engineering study, providing inputs to the rates department in Duke Energy, which will handle the rate design (i.e., how those costs should be allocated to DG).

Rugged WBG Devices and Advanced Electric Machines for High Power Density Automotive Electric Drives

John Victor Veliadis, Iqbal Husain, & Subhashish Bhattacharya
04/01/2019 - 03/31/2024

The objective of the project is to research, develop, and test GaN technology equipped lightweight electric motors for use in vehicle applications

Hanesbrand-ECE Sr Design Fall 2019-Spring 2020: NeverLost AutoAdjustable Kids Hoodie

Bobby Leonard Compton
08/29/2019 - 05/31/2020

A hoodie for kids that automatically adjust tension as well as provide a neverlost find feature through wireless networks to caregiver(s)/parent(s) mobile devices.

PowerAmerica: Task BP4-5.14: Wide Bandgap Power Converter Design Space Exploration

Srdjan Miodrag Lukic, Daniel D Stancil, & John F. Muth
12/01/2014 - 06/30/2020

Power America Task 5.14 BP4 Wide Bandgap Power Converter Design Space Exploration

The goal of this effort is to develop an open-source tool that integrates the concept of design space exploration into all aspects of the power converter design and construction to enable efficient trade-off
of design parameters using a library of previously engineered components. This open-source, reusable, tool suite will allow for engineers at all levels of their career to get exposed to the trade-offs inherent in
power electronics converter design, and to explore the benefits in performance that introduction of WBG components provide at the system level. The hands-on learning experience allows students to perform advanced multi-objective optimization at an early stage in the educational process. In research, this tool will facilitate technology benchmarking and will allow designers to answer “what-if” questions and roadmap technology performance and targets at the component and converter level.

Potentiometric Detection of Neuropeptides for Non-Invasive Monitoring of Stress

Spyridon Pavlidis
09/01/2019 - 08/31/2020

The objective of this proposal is to demonstrate the detection of neuropeptide Y (NPY), a biomarker for stress found in human sweat, using gold-based potentiometric sensors that are compatible with ASSIST’s Health and Environmental Tracker (HET) 2.0 biochemical sensor architecture.