<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>1665-6423</journal-id>
<journal-title><![CDATA[Journal of applied research and technology]]></journal-title>
<abbrev-journal-title><![CDATA[J. appl. res. technol]]></abbrev-journal-title>
<issn>1665-6423</issn>
<publisher>
<publisher-name><![CDATA[Universidad Nacional Autónoma de México, Instituto de Ciencias Aplicadas y Tecnología]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S1665-64232024000600863</article-id>
<article-id pub-id-type="doi">10.22201/icat.24486736e.2024.22.6.2531</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[Deep-learning framework for state of charge (SoC) estimation of electric vehicle batteries using a Pynq board]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[V.]]></surname>
<given-names><![CDATA[Vijaya Krishna]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Pappa]]></surname>
<given-names><![CDATA[N.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Joy Vasantha Rani]]></surname>
<given-names><![CDATA[S. P.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Presidency University Department of Electronics and Communication Engineering ]]></institution>
<addr-line><![CDATA[Bangalore ]]></addr-line>
<country>India</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Anna University Department of Instrumentation Engineering ]]></institution>
<addr-line><![CDATA[Chennai ]]></addr-line>
<country>India</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,Anna University Department of Electronics Engineering ]]></institution>
<addr-line><![CDATA[Chennai ]]></addr-line>
<country>India</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>00</month>
<year>2024</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>00</month>
<year>2024</year>
</pub-date>
<volume>22</volume>
<numero>6</numero>
<fpage>863</fpage>
<lpage>872</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S1665-64232024000600863&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S1665-64232024000600863&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S1665-64232024000600863&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract In recent years, carbon emissions have increased worldwide due to the excessive use of fossil fuels. To overcome these emissions, lithium-ion (Li-ion) batteries have become a more prominent alternative. Li-ion batteries are used as the primary component of energy storage systems for sustainable energy in response to rising global carbon gases. The battery management system (BMS) in electric vehicles (EVs) is an important aspect and is indicated by two parameters called state of charge (SoC) and state of health (SoH). Of these two, the SoC value is related to energy distribution, charging and discharging of batteries. Hence, estimating the SoC value is of high importance in BMS for the optimum use of batteries. Recent trends in artificial intelligence and deep learning provides a way for new developments in algorithms for estimating the SoC. At the same time, the use of programmable devices like field programmable gate arrays (FPGAs) for data processing applications provides acceleration in time and an optimal use of hardware. Pynq boards which are Zynq dependent, and one variant of FPGAs, are capable of executing python programs directly on hardware. This paper focuses on developing different DNN architectures for estimating the SoC of a Li-ion battery of an EV with a Pynq Z2 board. From the results, it can be concluded that a hybrid model when using a PYNQ board has less MAE and RMSE with 0.52% and 0.63%, and execution time with 0.28 ms which are optimum values when compared with other models.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[Electric vehicle]]></kwd>
<kwd lng="en"><![CDATA[state of charge (SoC)]]></kwd>
<kwd lng="en"><![CDATA[deep learning]]></kwd>
<kwd lng="en"><![CDATA[battery management system]]></kwd>
<kwd lng="en"><![CDATA[Pynq]]></kwd>
</kwd-group>
</article-meta>
</front><back>
<ref-list>
<ref id="B1">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Ahmed]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
<name>
<surname><![CDATA[Zheng]]></surname>
<given-names><![CDATA[Y.]]></given-names>
</name>
<name>
<surname><![CDATA[Amine]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
<name>
<surname><![CDATA[Fathiannasab]]></surname>
<given-names><![CDATA[H.]]></given-names>
</name>
<name>
<surname><![CDATA[Chen]]></surname>
<given-names><![CDATA[Z.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[The role of artificial intelligence in the mass adoption of electric vehicles]]></article-title>
<source><![CDATA[Joule]]></source>
<year>2021</year>
<volume>5</volume>
<numero>9</numero>
<issue>9</issue>
<page-range>2296-322</page-range></nlm-citation>
</ref>
<ref id="B2">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Chatterjee]]></surname>
<given-names><![CDATA[P.]]></given-names>
</name>
<name>
<surname><![CDATA[Singh]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Singh]]></surname>
<given-names><![CDATA[R.]]></given-names>
</name>
<name>
<surname><![CDATA[Avadh]]></surname>
<given-names><![CDATA[Y. A. R.]]></given-names>
</name>
<name>
<surname><![CDATA[Kanchan]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Electric Vehicle Modeling in MATLAB and Simulink with SoC &amp;SoE Estimation of a Lithium-ion Battery]]></article-title>
<source><![CDATA[IOP Conference Series: Materials Science and Engineering]]></source>
<year>2021</year>
<volume>1116</volume>
<numero>1</numero>
<issue>1</issue>
<publisher-name><![CDATA[IOP Publishing]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B3">
<nlm-citation citation-type="">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Corradi]]></surname>
<given-names><![CDATA[G.]]></given-names>
</name>
</person-group>
<source><![CDATA[The value of python productivity: Extreme edge analytics on xilinx zynq portfolio]]></source>
<year>2018</year>
</nlm-citation>
</ref>
<ref id="B4">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Cui]]></surname>
<given-names><![CDATA[Z.]]></given-names>
</name>
<name>
<surname><![CDATA[Dai]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Sun]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Li]]></surname>
<given-names><![CDATA[D.]]></given-names>
</name>
<name>
<surname><![CDATA[Wang]]></surname>
<given-names><![CDATA[L.]]></given-names>
</name>
<name>
<surname><![CDATA[Wang]]></surname>
<given-names><![CDATA[K.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Hybrid methods using neural network and Kalman filter for the state of charge estimation of lithium&#8208;ion battery]]></article-title>
<source><![CDATA[Mathematical Problems in Engineering]]></source>
<year>2022</year>
<volume>2022</volume>
<numero>1</numero>
<issue>1</issue>
</nlm-citation>
</ref>
<ref id="B5">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Guo]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[He]]></surname>
<given-names><![CDATA[H.]]></given-names>
</name>
<name>
<surname><![CDATA[Peng]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Real-time energy management for plug-in hybrid electric vehicle based on economy driving pro system]]></article-title>
<source><![CDATA[Energy Procedia]]></source>
<year>2019</year>
<volume>158</volume>
<page-range>2689-94</page-range></nlm-citation>
</ref>
<ref id="B6">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Hassan]]></surname>
<given-names><![CDATA[M. U.]]></given-names>
</name>
<name>
<surname><![CDATA[Saha]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
<name>
<surname><![CDATA[Haque]]></surname>
<given-names><![CDATA[M. E.]]></given-names>
</name>
<name>
<surname><![CDATA[Islam]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
<name>
<surname><![CDATA[Mahmud]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
<name>
<surname><![CDATA[Mendis]]></surname>
<given-names><![CDATA[N.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[A comprehensive review of battery state of charge estimation techniques]]></article-title>
<source><![CDATA[Sustainable Energy Technologies and Assessments]]></source>
<year>2022</year>
<volume>54</volume>
</nlm-citation>
</ref>
<ref id="B7">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[He]]></surname>
<given-names><![CDATA[H.]]></given-names>
</name>
<name>
<surname><![CDATA[Wang]]></surname>
<given-names><![CDATA[Y.]]></given-names>
</name>
<name>
<surname><![CDATA[Li]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Dou]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Lian]]></surname>
<given-names><![CDATA[R.]]></given-names>
</name>
<name>
<surname><![CDATA[Li]]></surname>
<given-names><![CDATA[Y.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[An improved energy management strategy for hybrid electric vehicles integrating multistates of vehicle-traffic information]]></article-title>
<source><![CDATA[IEEE Transactions on Transportation Electrification]]></source>
<year>2021</year>
<volume>7</volume>
<numero>3</numero>
<issue>3</issue>
<page-range>1161-72</page-range></nlm-citation>
</ref>
<ref id="B8">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[How]]></surname>
<given-names><![CDATA[D. N.]]></given-names>
</name>
<name>
<surname><![CDATA[Hannan]]></surname>
<given-names><![CDATA[M. A.]]></given-names>
</name>
<name>
<surname><![CDATA[Lipu]]></surname>
<given-names><![CDATA[M. S. H.]]></given-names>
</name>
<name>
<surname><![CDATA[Sahari]]></surname>
<given-names><![CDATA[K. S.]]></given-names>
</name>
<name>
<surname><![CDATA[Ker]]></surname>
<given-names><![CDATA[P. J.]]></given-names>
</name>
<name>
<surname><![CDATA[Muttaqi]]></surname>
<given-names><![CDATA[K. M.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[State-of-charge estimation of li-ion battery in electric vehicles: A deep neural network approach]]></article-title>
<source><![CDATA[IEEE Transactions on Industry Applications]]></source>
<year>2020</year>
<volume>56</volume>
<numero>5</numero>
<issue>5</issue>
<page-range>5565-74</page-range></nlm-citation>
</ref>
<ref id="B9">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Hu]]></surname>
<given-names><![CDATA[Y.]]></given-names>
</name>
<name>
<surname><![CDATA[Li]]></surname>
<given-names><![CDATA[W.]]></given-names>
</name>
<name>
<surname><![CDATA[Xu]]></surname>
<given-names><![CDATA[K.]]></given-names>
</name>
<name>
<surname><![CDATA[Zahid]]></surname>
<given-names><![CDATA[T.]]></given-names>
</name>
<name>
<surname><![CDATA[Qin]]></surname>
<given-names><![CDATA[F.]]></given-names>
</name>
<name>
<surname><![CDATA[Li]]></surname>
<given-names><![CDATA[C.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Energy management strategy for a hybrid electric vehicle based on deep reinforcement learning]]></article-title>
<source><![CDATA[Applied Sciences]]></source>
<year>2018</year>
<volume>8</volume>
<numero>2</numero>
<issue>2</issue>
</nlm-citation>
</ref>
<ref id="B10">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Hu]]></surname>
<given-names><![CDATA[C.]]></given-names>
</name>
<name>
<surname><![CDATA[Li]]></surname>
<given-names><![CDATA[B.]]></given-names>
</name>
<name>
<surname><![CDATA[Ma]]></surname>
<given-names><![CDATA[L.]]></given-names>
</name>
<name>
<surname><![CDATA[Cheng]]></surname>
<given-names><![CDATA[F.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[State-of-charge estimation for lithium-ion batteries of electric vehicle based on sensor random error compensation]]></article-title>
<source><![CDATA[Journal of Energy Storage]]></source>
<year>2022</year>
<volume>55</volume>
</nlm-citation>
</ref>
<ref id="B11">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Kalapothas]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
<name>
<surname><![CDATA[Flamis]]></surname>
<given-names><![CDATA[G.]]></given-names>
</name>
<name>
<surname><![CDATA[Kitsos]]></surname>
<given-names><![CDATA[P.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Efficient edge-AI application deployment for FPGAs]]></article-title>
<source><![CDATA[Information]]></source>
<year>2022</year>
<volume>13</volume>
<numero>6</numero>
<issue>6</issue>
</nlm-citation>
</ref>
<ref id="B12">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Kollmeyer]]></surname>
<given-names><![CDATA[P.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Panasonic 18650pf li-ion battery data]]></article-title>
<source><![CDATA[Mendeley Data]]></source>
<year>2018</year>
<volume>1</volume>
<numero>2018</numero>
<issue>2018</issue>
<page-range>1-15</page-range></nlm-citation>
</ref>
<ref id="B13">
<nlm-citation citation-type="confpro">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Krishna]]></surname>
<given-names><![CDATA[V. V.]]></given-names>
</name>
<name>
<surname><![CDATA[Pappa]]></surname>
<given-names><![CDATA[N.]]></given-names>
</name>
<name>
<surname><![CDATA[Rani]]></surname>
<given-names><![CDATA[S. J. V.]]></given-names>
</name>
</person-group>
<source><![CDATA[Implementation of embedded soft sensor for bioreactor on Zynq processing system]]></source>
<year>2018</year>
<conf-name><![CDATA[ 2018 International conference on recent trends in electrical, control and communication (RTECC)]]></conf-name>
<conf-loc> </conf-loc>
</nlm-citation>
</ref>
<ref id="B14">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Krishna]]></surname>
<given-names><![CDATA[V. V.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Performance Optimization of CNFET-based Domino Logic circuits&#8214;]]></article-title>
<source><![CDATA[International Journal of Advanced Research in Electronics and Communication Engineering]]></source>
<year>2014</year>
<volume>3</volume>
<numero>9</numero>
<issue>9</issue>
<page-range>975-8</page-range></nlm-citation>
</ref>
<ref id="B15">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Lian]]></surname>
<given-names><![CDATA[R.]]></given-names>
</name>
<name>
<surname><![CDATA[Tan]]></surname>
<given-names><![CDATA[H.]]></given-names>
</name>
<name>
<surname><![CDATA[Peng]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Li]]></surname>
<given-names><![CDATA[Q.]]></given-names>
</name>
<name>
<surname><![CDATA[Wu]]></surname>
<given-names><![CDATA[Y.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Cross-type transfer for deep reinforcement learning based hybrid electric vehicle energy management]]></article-title>
<source><![CDATA[IEEE Transactions on Vehicular Technology]]></source>
<year>2020</year>
<volume>69</volume>
<numero>8</numero>
<issue>8</issue>
<page-range>8367-80</page-range></nlm-citation>
</ref>
<ref id="B16">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Mándi]]></surname>
<given-names><![CDATA[Á.]]></given-names>
</name>
<name>
<surname><![CDATA[Máté]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Rózsa]]></surname>
<given-names><![CDATA[D.]]></given-names>
</name>
<name>
<surname><![CDATA[Oniga]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Hardware accelerated image processing on FPGA based PYNQ-Z2 board]]></article-title>
<source><![CDATA[Carpathian journal of electronic and computer engineering]]></source>
<year>2021</year>
<volume>14</volume>
<numero>1</numero>
<issue>1</issue>
<page-range>20-3</page-range></nlm-citation>
</ref>
<ref id="B17">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Messaoud]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
<name>
<surname><![CDATA[Bouaafia]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
<name>
<surname><![CDATA[Maraoui]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
<name>
<surname><![CDATA[Ammari]]></surname>
<given-names><![CDATA[A. C.]]></given-names>
</name>
<name>
<surname><![CDATA[Khriji]]></surname>
<given-names><![CDATA[L.]]></given-names>
</name>
<name>
<surname><![CDATA[Machhout]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Deep convolutional neural networks-based Hardware-Software on-chip system for computer vision application]]></article-title>
<source><![CDATA[Computers &amp; Electrical Engineering]]></source>
<year>2022</year>
<volume>98</volume>
</nlm-citation>
</ref>
<ref id="B18">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Pisal]]></surname>
<given-names><![CDATA[P. S.]]></given-names>
</name>
<name>
<surname><![CDATA[Vidyarthi]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[An optimal control for power management in super capacitors/battery of electric vehicles using Deep Neural Network]]></article-title>
<source><![CDATA[Journal of Power Sources]]></source>
<year>2022</year>
<volume>542</volume>
</nlm-citation>
</ref>
<ref id="B19">
<nlm-citation citation-type="">
<person-group person-group-type="author">
<name>
<surname><![CDATA[dos Reis]]></surname>
<given-names><![CDATA[G.]]></given-names>
</name>
<name>
<surname><![CDATA[Strange]]></surname>
<given-names><![CDATA[C.]]></given-names>
</name>
<name>
<surname><![CDATA[Yadav]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
<name>
<surname><![CDATA[Li]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
</person-group>
<source><![CDATA[Lithium-Ion Battery Data and Where to Find It. Energy and AI]]></source>
<year>2021</year>
</nlm-citation>
</ref>
<ref id="B20">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Saady]]></surname>
<given-names><![CDATA[M. M.]]></given-names>
</name>
<name>
<surname><![CDATA[Essai]]></surname>
<given-names><![CDATA[M. H.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Hardware implementation of neural network-based engine model using FPGA]]></article-title>
<source><![CDATA[Alexandria Engineering Journal]]></source>
<year>2022</year>
<volume>61</volume>
<numero>12</numero>
<issue>12</issue>
<page-range>12039-50</page-range></nlm-citation>
</ref>
<ref id="B21">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Saidi]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
<name>
<surname><![CDATA[Othman]]></surname>
<given-names><![CDATA[S. B.]]></given-names>
</name>
<name>
<surname><![CDATA[Dhouibi]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
<name>
<surname><![CDATA[Saoud]]></surname>
<given-names><![CDATA[S. B.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[FPGA-based implementation of classification techniques: A survey]]></article-title>
<source><![CDATA[Integration]]></source>
<year>2021</year>
<volume>81</volume>
<page-range>280-99</page-range></nlm-citation>
</ref>
<ref id="B22">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Shahriar]]></surname>
<given-names><![CDATA[S. M.]]></given-names>
</name>
<name>
<surname><![CDATA[Bhuiyan]]></surname>
<given-names><![CDATA[E. A.]]></given-names>
</name>
<name>
<surname><![CDATA[Nahiduzzaman]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
<name>
<surname><![CDATA[Ahsan]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
<name>
<surname><![CDATA[Haider]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[State of charge estimation for electric vehicle battery management systems using the hybrid recurrent learning approach with explainable artificial intelligence]]></article-title>
<source><![CDATA[Energies]]></source>
<year>2022</year>
<volume>15</volume>
<numero>21</numero>
<issue>21</issue>
</nlm-citation>
</ref>
<ref id="B23">
<nlm-citation citation-type="confpro">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Shrivastava]]></surname>
<given-names><![CDATA[P.]]></given-names>
</name>
<name>
<surname><![CDATA[Soon]]></surname>
<given-names><![CDATA[T. K.]]></given-names>
</name>
<name>
<surname><![CDATA[Idris]]></surname>
<given-names><![CDATA[M. Y. B.]]></given-names>
</name>
<name>
<surname><![CDATA[Mekhilef]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
<name>
<surname><![CDATA[Adnan]]></surname>
<given-names><![CDATA[S. B. R. S.]]></given-names>
</name>
</person-group>
<source><![CDATA[Lithium-ion battery state of energy estimation using deep neural network and support vector regression]]></source>
<year>2021</year>
<conf-name><![CDATA[ 2021 IEEE 12th Energy Conversion Congress &amp; Exposition-Asia (ECCE-Asia)]]></conf-name>
<conf-loc> </conf-loc>
</nlm-citation>
</ref>
<ref id="B24">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Tian]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Xiong]]></surname>
<given-names><![CDATA[R.]]></given-names>
</name>
<name>
<surname><![CDATA[Shen]]></surname>
<given-names><![CDATA[W.]]></given-names>
</name>
<name>
<surname><![CDATA[Lu]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[State-of-charge estimation of LiFePO4 batteries in electric vehicles: A deep-learning enabled approach]]></article-title>
<source><![CDATA[Applied Energy]]></source>
<year>2021</year>
<volume>291</volume>
</nlm-citation>
</ref>
<ref id="B25">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Tian]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Xiong]]></surname>
<given-names><![CDATA[R.]]></given-names>
</name>
<name>
<surname><![CDATA[Lu]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Chen]]></surname>
<given-names><![CDATA[C.]]></given-names>
</name>
<name>
<surname><![CDATA[Shen]]></surname>
<given-names><![CDATA[W.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Battery state-of-charge estimation amid dynamic usage with physics-informed deep learning]]></article-title>
<source><![CDATA[Energy Storage Materials]]></source>
<year>2022</year>
<volume>50</volume>
<page-range>718-29</page-range></nlm-citation>
</ref>
<ref id="B26">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Vidal]]></surname>
<given-names><![CDATA[C.]]></given-names>
</name>
<name>
<surname><![CDATA[Malysz]]></surname>
<given-names><![CDATA[P.]]></given-names>
</name>
<name>
<surname><![CDATA[Kollmeyer]]></surname>
<given-names><![CDATA[P.]]></given-names>
</name>
<name>
<surname><![CDATA[Emadi]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Machine learning applied to electrified vehicle battery state of charge and state of health estimation: State-of-the-art]]></article-title>
<source><![CDATA[IEEE Access]]></source>
<year>2020</year>
<volume>8</volume>
<page-range>52796-814</page-range></nlm-citation>
</ref>
<ref id="B27">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Huynh]]></surname>
<given-names><![CDATA[T. V.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[FPGA-based Acceleration for Convolutional Neural Networks on PYNQ-Z2]]></article-title>
<source><![CDATA[International Journal of Computing and Digital Systems]]></source>
<year>2022</year>
<volume>11</volume>
<numero>1</numero>
<issue>1</issue>
<page-range>441-50</page-range></nlm-citation>
</ref>
<ref id="B28">
<nlm-citation citation-type="confpro">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Wang]]></surname>
<given-names><![CDATA[E.]]></given-names>
</name>
<name>
<surname><![CDATA[Davis]]></surname>
<given-names><![CDATA[J. J.]]></given-names>
</name>
<name>
<surname><![CDATA[Cheung]]></surname>
<given-names><![CDATA[P. Y.]]></given-names>
</name>
</person-group>
<source><![CDATA[A PYNQ-based framework for rapid CNN prototyping]]></source>
<year>2018</year>
<conf-name><![CDATA[ 2018 IEEE 26th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM)]]></conf-name>
<conf-loc> </conf-loc>
</nlm-citation>
</ref>
<ref id="B29">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Wu]]></surname>
<given-names><![CDATA[C.]]></given-names>
</name>
<name>
<surname><![CDATA[Fresse]]></surname>
<given-names><![CDATA[V.]]></given-names>
</name>
<name>
<surname><![CDATA[Suffran]]></surname>
<given-names><![CDATA[B.]]></given-names>
</name>
<name>
<surname><![CDATA[Konik]]></surname>
<given-names><![CDATA[H.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Accelerating DNNs from local to virtualized FPGA in the Cloud: A survey of trends]]></article-title>
<source><![CDATA[Journal of Systems Architecture]]></source>
<year>2021</year>
<volume>119</volume>
</nlm-citation>
</ref>
<ref id="B30">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Yamamoto]]></surname>
<given-names><![CDATA[K.]]></given-names>
</name>
<name>
<surname><![CDATA[Kawahara]]></surname>
<given-names><![CDATA[T.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Scalable fully coupled annealing processing system and multi-chip FPGA implementation]]></article-title>
<source><![CDATA[Microprocessors and Microsystems]]></source>
<year>2022</year>
<volume>95</volume>
</nlm-citation>
</ref>
<ref id="B31">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Zhang]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Jiao]]></surname>
<given-names><![CDATA[X.]]></given-names>
</name>
<name>
<surname><![CDATA[Yang]]></surname>
<given-names><![CDATA[C.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[A double&#8208;deep Q&#8208;network&#8208;based energy management strategy for hybrid electric vehicles under variable driving cycles]]></article-title>
<source><![CDATA[Energy Technology]]></source>
<year>2021</year>
<volume>9</volume>
<numero>2</numero>
<issue>2</issue>
</nlm-citation>
</ref>
<ref id="B32">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Zhang]]></surname>
<given-names><![CDATA[X.]]></given-names>
</name>
<name>
<surname><![CDATA[Wang]]></surname>
<given-names><![CDATA[Y.]]></given-names>
</name>
<name>
<surname><![CDATA[Yang]]></surname>
<given-names><![CDATA[D.]]></given-names>
</name>
<name>
<surname><![CDATA[Chen]]></surname>
<given-names><![CDATA[Z.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Behavior data of battery and battery pack SOC estimation under different working conditions]]></article-title>
<source><![CDATA[Data in brief]]></source>
<year>2016</year>
<volume>9</volume>
<page-range>737-40</page-range></nlm-citation>
</ref>
<ref id="B33">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Zhang]]></surname>
<given-names><![CDATA[D.]]></given-names>
</name>
<name>
<surname><![CDATA[Zhong]]></surname>
<given-names><![CDATA[C.]]></given-names>
</name>
<name>
<surname><![CDATA[Xu]]></surname>
<given-names><![CDATA[P.]]></given-names>
</name>
<name>
<surname><![CDATA[Tian]]></surname>
<given-names><![CDATA[Y.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Deep learning in the state of charge estimation for li-ion batteries of electric vehicles: A review]]></article-title>
<source><![CDATA[Machines]]></source>
<year>2022</year>
<volume>10</volume>
<numero>10</numero>
<issue>10</issue>
</nlm-citation>
</ref>
</ref-list>
</back>
</article>
