Szczegóły publikacji
Opis bibliograficzny
Monitoring and health prognosis of Lithium-Ion battery system / Piotr GÓRNY, Piotr MRÓZ, Tadeusz UHL // W: EWSHM 2016 [Dokument elektroniczny] : 8th European Workshop on Structural Health Monitoring : 5–8 July 2016, Spain, Bilbao. — Wersja do Windows. — Dane tekstowe. — [Spain : s. n.], [2016]. — e-ISBN: 978-151082793-6. — S. 1–9. — Wymagania systemowe: Adobe Reader. — Tryb dostępu: https://goo.gl/2w6qdy [2016-11-24]. — Bibliogr. s. 8–9, Abstr.
Autorzy (3)
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 102279 |
|---|---|
| Data dodania do BaDAP | 2016-12-21 |
| Rok publikacji | 2016 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Konferencja | 8th European Workshop on Structural Health Monitoring |
Abstract
This work discusses new approach to Lithium-Ion battery health monitoring and lifetime prediction dedicated to use in off-grid application. First part of a study contains results of testing single cell in contest to notice the degradation effect. To simulate work-conditions LabView program was written with association of hardware for control of experimental rig.The biggest issue of testing lifetime of lithium-ion cells is highly time-consuming process because measurements deploy a numerous charge/discharge cycles. Large number of cycles results in noticeable degradation thus to accelerate this process and increase the amount of performed cycle higher than nominal current magnitude is applied. But it is important to emphasize that tests in manufacturer nominal conditions should be performed as a reference to the future results. Current and voltage characteristics allow measuring internal resistance of the cell during the test. On the other hand temperature changes receive the thermal response and heat emitted in common of temperature increasing. The idea of assessment of State of Health (SOH) is based on model-Assisted approach to diagnostics. In this idea the simulation results are compared with experimental results at each cycle of battery charging and discharging and correlation between model and experiments are tested. Updated model is used for prediction of rest of battery safe life. To predict battery life the main factors that influence battery ageing are discussed and included into battery model applied for prediction. This thesis is part of the work, which aims to deploy simulation of the battery ageing mechanism to achieve lifetime prediction and ensure usage of full lithium-ion batteries potential. Applied Ageing factors based on theoretical model ensure nonlinear dependence of ageing on parameters such as temperature of operation, discharge rate and depth of discharge. Implemented algorithm can be fitted to a particular battery pack and provide a cycle life prediction including state of charge (SOC) and SOH monitoring. Last part of the paper presents meta-model formulation that is a possibility of battery state of health algorithm implementation into BMS. Memory and computing requirements are significantly limited compared to the MATLAB Simulation model. Use of Meta-model ensures the practical use of conducted research in real application.
