Lithium-ion Battery Degradation Assessment and Remaining Useful Life Estimation in Hybrid Electric Vehicle
<p class="Abstract"><em>Abstract</em>—Prognostic activity deals with prediction of the remaining useful life (RUL) of physical systems based on their actual health state and their usage conditions. RUL estimation gives operators a potent tool in decision making by quantif...
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Academy Publishing Center
2016-06-01
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| Series: | Renewable Energy and Sustainable Development |
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| Online Access: | http://apc.aast.edu/ojs/index.php/RESD/article/view/121 |
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| author | Nabil Laayouj Hicham Jamouli |
| author_facet | Nabil Laayouj Hicham Jamouli |
| author_sort | Nabil Laayouj |
| collection | DOAJ |
| description | <p class="Abstract"><em>Abstract</em>—Prognostic activity deals with prediction of the remaining useful life (RUL) of physical systems based on their actual health state and their usage conditions. RUL estimation gives operators a potent tool in decision making by quantifying how much time is left until functionality is lost. In addition, it can be used to improve the characterization of the material proprieties that govern damage propagation for the structure being monitored. RUL can be estimated by using three main approaches, namely model-based, data-driven and hybrid approaches. The prognostics methods used later in this paper are hybrid and data-driven approaches, which employ the Particle Filter in the first one and the autoregressive integrated moving average in the second. The performance of the suggested approaches is evaluated in a comparative study on data collected from lithium-ion battery of hybrid electric vehicle.</p> |
| format | Article |
| id | doaj-art-1647f98fe72548d69595426ff2e9af10 |
| institution | Kabale University |
| issn | 2356-8518 2356-8569 |
| language | English |
| publishDate | 2016-06-01 |
| publisher | Academy Publishing Center |
| record_format | Article |
| series | Renewable Energy and Sustainable Development |
| spelling | doaj-art-1647f98fe72548d69595426ff2e9af102025-08-20T03:50:06ZengAcademy Publishing CenterRenewable Energy and Sustainable Development2356-85182356-85692016-06-0121374410.21622/resd.2016.02.1.03764Lithium-ion Battery Degradation Assessment and Remaining Useful Life Estimation in Hybrid Electric VehicleNabil Laayouj0Hicham Jamouli1LGII Laboratory, National School of Applied SciencesLGII Laboratory, National School of Applied Sciences<p class="Abstract"><em>Abstract</em>—Prognostic activity deals with prediction of the remaining useful life (RUL) of physical systems based on their actual health state and their usage conditions. RUL estimation gives operators a potent tool in decision making by quantifying how much time is left until functionality is lost. In addition, it can be used to improve the characterization of the material proprieties that govern damage propagation for the structure being monitored. RUL can be estimated by using three main approaches, namely model-based, data-driven and hybrid approaches. The prognostics methods used later in this paper are hybrid and data-driven approaches, which employ the Particle Filter in the first one and the autoregressive integrated moving average in the second. The performance of the suggested approaches is evaluated in a comparative study on data collected from lithium-ion battery of hybrid electric vehicle.</p>http://apc.aast.edu/ojs/index.php/RESD/article/view/121remaining useful lifeprognosisparticle filterarima |
| spellingShingle | Nabil Laayouj Hicham Jamouli Lithium-ion Battery Degradation Assessment and Remaining Useful Life Estimation in Hybrid Electric Vehicle Renewable Energy and Sustainable Development remaining useful life prognosis particle filter arima |
| title | Lithium-ion Battery Degradation Assessment and Remaining Useful Life Estimation in Hybrid Electric Vehicle |
| title_full | Lithium-ion Battery Degradation Assessment and Remaining Useful Life Estimation in Hybrid Electric Vehicle |
| title_fullStr | Lithium-ion Battery Degradation Assessment and Remaining Useful Life Estimation in Hybrid Electric Vehicle |
| title_full_unstemmed | Lithium-ion Battery Degradation Assessment and Remaining Useful Life Estimation in Hybrid Electric Vehicle |
| title_short | Lithium-ion Battery Degradation Assessment and Remaining Useful Life Estimation in Hybrid Electric Vehicle |
| title_sort | lithium ion battery degradation assessment and remaining useful life estimation in hybrid electric vehicle |
| topic | remaining useful life prognosis particle filter arima |
| url | http://apc.aast.edu/ojs/index.php/RESD/article/view/121 |
| work_keys_str_mv | AT nabillaayouj lithiumionbatterydegradationassessmentandremainingusefullifeestimationinhybridelectricvehicle AT hichamjamouli lithiumionbatterydegradationassessmentandremainingusefullifeestimationinhybridelectricvehicle |