An integrated approach for real-time model-based state-of-charge estimation of lithium-ion batteries

Lithium-ion batteries have been widely adopted in electric vehicles (EVs), and accurate state of charge (SOC) estimation is of paramount importance for the EV battery management system. Though a number of methods have been proposed, the SOC estimation for Lithium-ion batteries, such as LiFePo4 battery, however, faces two key challenges: the flat open circuit voltage (OCV) vs SOC relationship for some SOC ranges and the hysteresis effect. To address these problems, an integrated approach for real-time model-based SOC estimation of Lithium-ion batteries is proposed in this paper. Firstly, an auto-regression model is adopted to reproduce the battery terminal behaviour, combined with a non-linear complementary model to capture the hysteresis effect. The model parameters, including linear parameters and non-linear parameters, are optimized off-line using a hybrid optimization method that combines a meta-heuristic method (i.e., the teaching learning based optimization method) and the least square method. Secondly, using the trained model, two real-time model-based SOC estimation methods are presented, one based on the real-time battery OCV regression model achieved through weighted recursive least square method, and the other based on the state estimation using the extended Kalman filter method (EKF). To tackle the problem caused by the flat OCV-vs-SOC segments when the OCV-based SOC estimation method is adopted, a method combining the coulombic counting and the OCV-based method is proposed. Finally, modelling results and SOC estimation results are presented and analysed using the data collected from LiFePo4 battery cell. The results confirmed the effectiveness of the proposed approach, in particular the joint-EKF method.

Iso-Quality of Service: Fairly Ranking Servers for Real-Time Data Analytics

We present a mathematically rigorous Quality-of-Service (QoS) metric which relates the achievable quality of service metric (QoS) for a real-time analytics service to the server energy cost of offering the service. Using a new iso-QoS evaluation methodology, we scale server resources to meet QoS targets and directly rank the servers in terms of their energy-efficiency and by extension cost of ownership. Our metric and method are platform-independent and enable fair comparison of datacenter compute servers with significant architectural diversity, including micro-servers. We deploy our metric and methodology to compare three servers running financial option pricing workloads on real-life market data. We find that server ranking is sensitive to data inputs and desired QoS level and that although scale-out micro-servers can be up to two times more energy-efficient than conventional heavyweight servers for the same target QoS, they are still six times less energy efficient than high-performance computational accelerators.

Methods and Metrics for Fair Server Assessment under Real-Time Financial Workloads

We present a rigorous methodology and new metrics for fair comparison of server and microserver platforms. Deploying our methodology and metrics, we compare a microserver with ARM cores against two servers with ×86 cores running the same real-time financial analytics workload. We define workload-specific but platform-independent performance metrics for platform comparison, targeting both datacenter operators and end users. Our methodology establishes that a server based on the Xeon Phi co-processor delivers the highest performance and energy efficiency. However, by scaling out energy-efficient microservers, we achieve competitive or better energy efficiency than a power-equivalent server with two Sandy Bridge sockets, despite the microserver's slower cores. Using a new iso-QoS metric, we find that the ARM microserver scales enough to meet market throughput demand, that is, a 100% QoS in terms of timely option pricing, with as little as 55% of the energy consumed by the Sandy Bridge server.

Characterization of a reference material for BCR-ABL (M-BCR) mRNA quantitation by real-time amplification assays:towards new standards for gene expression measurements

Monitoring of BCR-ABL transcripts has become established practice in the management of chronic myeloid leukemia. However, nucleic acid amplification techniques are prone to variations which limit the reliability of real-time quantitative PCR (RQ-PCR) for clinical decision making, highlighting the need for standardization of assays and reporting of minimal residual disease (MRD) data. We evaluated a lyophilized preparation of a leukemic cell line (K562) as a potential quality control reagent. This was found to be relatively stable, yielding comparable respective levels of ABL, GUS and BCR-ABL transcripts as determined by RQ-PCR before and after accelerated degradation experiments as well as following 5 years storage at -20 degrees C. Vials of freeze-dried cells were sent at ambient temperature to 22 laboratories on four continents, with RQ-PCR analyses detecting BCR-ABL transcripts at levels comparable to those observed in primary patient samples. Our results suggest that freeze-dried cells can be used as quality control reagents with a range of analytical instrumentations and could enable the development of urgently needed international standards simulating clinically relevant levels of MRD.

Geotechnical monitoring using a combination of LIDAR, real-time dGPS, and electrical tomography to assess geotechnical risk of a coastal landslide.

The Antrim Coast Road stretching from the seaport of Larne in the East of Northern Ireland has a well-deserved reputation for being one of the most spectacular roads in Europe (Day, 2006). However the problematic geology; Jurassic Lias Clay and Triassic Mudstone overlain by Cretaceous Limestone and Tertiary Basalt, and environmental variables result in frequent instances of slope instability manifested in both shallow debris flows and occasional massive rotational movements, creating a geotechnical risk to this highway. This paper describes how a variety of techniques are being used to both assess instability and monitor movement of these active slopes near one site at Straidkilly Point, Glenarm. An in-depth understanding of the geology was obtained via boreholes, resistivity surveys and laboratory testing. Environmental variables recorded by an on-site weather station were correlated with measured pore water pressure and soil moisture infiltration data. Terrestrial LiDAR (TLS), with surveys carried out on a bi-monthly basis allowed for the generation of Digital Elevation Models (DEMs) of difference, highlighting areas of recent movement, accumulation and depletion. Morphology parameters were generated from the DEMs and include slope, curvature and multiple measures of roughness. Changes in the structure of the slope coupled with morphological parameters were characterised and linked to progressive failures from the temporal monitoring. In addition to TLS monitoring, Aerial LiDAR datasets were used for the spatio-morphological characterisation of the slope on a macro scale. A Differential Global Positioning System (dGPS) was also deployed on site to provide a real-time warning system for gross movements, which were also correlated with environmental conditions. Frequent electrical resistivity tomography (ERT) surveys were also implemented to provide a better understanding of long-term changes in soil moisture and help to define the complex geology. The paper describes how the data obtained via a diverse range of methods has been combined to facilitate a more informed management regime of geotechnical risk by the Northern Ireland Roads Service.

High Performance Real-time Pre-Processing for Fixed-Complexity Sphere Decoder

Pre-processing (PP) of received symbol vector and channel matrices is an essential pre-requisite operation for Sphere Decoder (SD)-based detection of Multiple-Input Multiple-Output (MIMO) wireless systems. PP is a highly complex operation, but relative to the total SD workload it represents a relatively small fraction of the overall computational cost of detecting an OFDM MIMO frame in standards such as 802.11n. Despite this, real-time PP architectures are highly inefficient, dominating the resource cost of real-time SD architectures. This paper resolves this issue. By reorganising the ordering and QR decomposition sub operations of PP, we describe a Field Programmable Gate Array (FPGA)-based PP architecture for the Fixed Complexity Sphere Decoder (FSD) applied to 4 × 4 802.11n MIMO which reduces resource cost by 50% as compared to state-of-the-art solutions whilst maintaining real-time performance.

Real-Time Channel Model Selection Using Windowed Received Signal Strength Measurements

This paper investigates the potential for using the windowed variance of the received signal strength to select from a set of predetermined channel models for a wireless ranging or localization system. An 868 MHz based measurement system was used to characterize the received signal strength (RSS) of the off-body link formed between two wireless nodes attached to either side of a human thorax and six base stations situated in the local surroundings.

Real-time estimation of battery internal temperature based on a simplified thermoelectric model

Li-ion batteries have been widely used in the EVs, and the battery thermal management is a key but challenging part of the battery management system. For EV batteries, only the battery surface temperature can be measured in real-time. However, it is the battery internal temperature that directly affects the battery performance, and large temperature difference may exist between surface and internal temperatures, especially in high power demand applications. In this paper, an online battery internal temperature estimation method is proposed based on a novel simplified thermoelectric model. The battery thermal behaviour is first described by a simplified thermal model, and battery electrical behaviour by an electric model. Then, these two models are interrelated to capture the interactions between battery thermal and electrical behaviours, thus offer a comprehensive description of the battery behaviour that is useful for battery management. Finally, based on the developed model, the battery internal temperature is estimated using an extended Kalman filter. The experimental results confirm the efficacy of the proposed method, and it can be used for online internal temperature estimation which is a key indicator for better real-time battery thermal management.

Electron-phonon thermalization in a scalable method for real-time quantum dynamics

We present a quantum simulation method that follows the dynamics of out-of-equilibrium many-body systems of electrons and oscillators in real time. Its cost is linear in the number of oscillators and it can probe time scales from attoseconds to hundreds of picoseconds. Contrary to Ehrenfest dynamics, it can thermalize starting from a variety of initial conditions, including electronic population inversion. While an electronic temperature can be defined in terms of a nonequilibrium entropy, a Fermi-Dirac distribution in general emerges only after thermalization. These results can be used to construct a kinetic model of electron-phonon equilibration based on the explicit quantum dynamics.

Dielectrics in a time-dependent electric field: a real-time approach based on density-polarization functional theory

In the presence of a (time-dependent) macroscopic electric field the electron dynamics of dielectrics cannot be described by the time-dependent density only. We present a real-time formalism that has the density and the macroscopic polarization P as key quantities. We show that a simple local function of P already captures long-range correlation in linear and nonlinear optical response functions. Specifically, after detailing the numerical implementation, we examine the optical absorption, the second- and third-harmonic generation of bulk Si, GaAs, AlAs and CdTe at different level of approximation. We highlight links with ultranonlocal exchange-correlation functional approximations proposed within linear response time-dependent density functional theory framework.

Real-Time Multiple Event Detection and Classification Using Moving Window PCA

This paper proposes a method for the detection and classification of multiple events in an electrical power system in real-time, namely; islanding, high frequency events (loss of load) and low frequency events (loss of generation). This method is based on principal component analysis of frequency measurements and employs a moving window approach to combat the time-varying nature of power systems, thereby increasing overall situational awareness of the power system. Numerical case studies using both real data, collected from the UK power system, and simulated case studies, constructed using DigSilent PowerFactory, for islanding events, as well as both loss of load and generation dip events, are used to demonstrate the reliability of the proposed method.

NanoStreams: Codesigned Microservers for Edge Analytics in Real Time

NanoStreams explores the design, implementation,and system software stack of micro-servers aimed at processingdata in-situ and in real time. These micro-servers can serve theemerging Edge computing ecosystem, namely the provisioningof advanced computational, storage, and networking capabilitynear data sources to achieve both low latency event processingand high throughput analytical processing, before consideringoff-loading some of this processing to high-capacity datacentres.NanoStreams explores a scale-out micro-server architecture thatcan achieve equivalent QoS to that of conventional rack-mountedservers for high-capacity datacentres, but with dramaticallyreduced form factors and power consumption. To this end,NanoStreams introduces novel solutions in programmable & con-figurable hardware accelerators, as well as the system softwarestack used to access, share, and program those accelerators.Our NanoStreams micro-server prototype has demonstrated 5.5×higher energy-efficiency than a standard Xeon Server. Simulationsof the microserver’s memory system extended to leveragehybrid DDR/NVM main memory indicated 5× higher energyefficiencythan a conventional DDR-based system. 

Satellite DNA as a target for TaqMan real-time PCR detection of the pinewood nematode, Bursaphelenchus xylophilus

The pinewood nematode (PWN), Bursaphelenchus xylophilus , is a major pathogen of conifers, which impacts on forest health, natural ecosystem stability and international trade. As a consequence, it has been listed as a quarantine organism in Europe. A real-time PCR approach based on TaqMan chemistry was developed to detect this organism. Specific probe and primers were designed based on the sequence of the Msp I satellite DNA family previously characterized in the genome of the nematode. The method proved to be specific in tests with target DNA from PWN isolates from worldwide origin. From a practical point of view, detection limit was 1 pg of target DNA or one individual nematode. In addition, PWN genomic DNA or single individuals were positively detected in mixed samples in which B. xylophilius was associated with the closely related non-pathogenic species B. mucronatus , up to the limit of 0.01% or 1% of the mixture, respectively. The real-time PCR assay was also used in conjunction with a simple DNA extraction method to detect PWN directly in artificially infested wood samples. These results demonstrate the potential of this assay to provide rapid, accurate and sensitive molecular identification of the PWN in relation to pest risk assessment in the field and quarantine regulation.

Enhanced ethernet switching technology for adaptive hard real-time applications: Tecnologia de comutação ethernet melhorada para aplicações adaptativas e críticas de tempo-real

Os Sistemas Embarcados Distribuídos (SEDs) estão, hoje em dia, muito difundidos em vastas áreas, desde a automação industrial, a automóveis, aviões, até à distribuição de energia e protecção do meio ambiente. Estes sistemas são, essencialmente, caracterizados pela integração distribuída de aplicações embarcadas, autónomas mas cooperantes, explorando potenciais vantagens em termos de modularidade, facilidade de manutenção, custos de instalação, tolerância a falhas, entre outros. Contudo, o ambiente operacional onde se inserem estes tipos de sistemas pode impor restrições temporais rigorosas, exigindo que o sistema de comunicação subjacente consiga transmitir mensagens com garantias temporais. Contudo, os SEDs apresentam uma crescente complexidade, uma vez que integram subsistemas cada vez mais heterogéneos, quer ao nível do tráfego gerado, quer dos seus requisitos temporais. Em particular, estes subsistemas operam de forma esporádica, isto é, suportam mudanças operacionais de acordo com estímulos exteriores. Estes subsistemas também se reconfiguram dinamicamente de acordo com a actualização dos seus requisitos e, ainda, têm lidar com um número variável de solicitações de outros subsistemas. Assim sendo, o nível de utilização de recursos pode variar e, desta forma, as políticas de alocação estática tornam-se muito ineficientes. Consequentemente, é necessário um sistema de comunicação capaz de suportar com eficácia reconfigurações e adaptações dinâmicas. A tecnologia Ethernet comutada tem vindo a emergir como uma solução sólida para fornecer comunicações de tempo-real no âmbito dos SEDs, como comprovado pelo número de protocolos de tempo-real que foram desenvolvidos na última década. No entanto, nenhum dos protocolos existentes reúne as características necessárias para fornecer uma eficiente utilização da largura de banda e, simultaneamente, para respeitar os requisitos impostos pelos SEDs. Nomeadamente, a capacidade para controlar e policiar tráfego de forma robusta, conjugada com suporte à reconfiguração e adaptação dinâmica, não comprometendo as garantias de tempo-real. Esta dissertação defende a tese de que, pelo melhoramento dos comutadores Ethernet para disponibilizarem mecanismos de reconfiguração e isolamento de tráfego, é possível suportar aplicações de tempo-real críticas, que são adaptáveis ao ambiente onde estão inseridas.Em particular, é mostrado que as técnicas de projecto, baseadas em componentes e apoiadas no escalonamento hierárquico de servidores de tráfego, podem ser integradas nos comutadores Ethernet para alcançar as propriedades desejadas. Como suporte, é fornecida, também, uma solução para instanciar uma hierarquia reconfigurável de servidores de tráfego dentro do comutador, bem como a análise adequada ao modelo de escalonamento. Esta última fornece um limite superior para o tempo de resposta que os pacotes podem sofrer dentro dos servidores de tráfego, com base unicamente no conhecimento de um dado servidor e na hierarquia actual, isto é, sem o conhecimento das especifidades do tráfego dentro dos outros servidores. Finalmente, no âmbito do projecto HaRTES foi construído um protótipo do comutador Ethernet, o qual é baseado no paradigma “Flexible Time-Triggered”, que permite uma junção flexível de uma fase síncrona para o tráfego controlado pelo comutador e uma fase assíncrona que implementa a estrutura hierárquica de servidores referidos anteriormente. Além disso, as várias experiências práticas realizadas permitiram validar as propriedades desejadas e, consequentemente, a tese que fundamenta esta dissertação.