Monitoring and health prognosis of Lithium-Ion battery system
PBN-AR
Instytucja
Wydział Inżynierii Mechanicznej i Robotyki (Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie)
Książka
Tytuł książki
EWSHM 2016 [Dokument elektroniczny]. 8th European Workshop on Structural Health Monitoring : 5–8 July 2016, Spain, Bilbao
Data publikacji
2016
ISBN
978-151082793-6
Wydawca
s.n.
Publikacja
Główny język publikacji
EN
Tytuł rozdziału
Monitoring and health prognosis of Lithium-Ion battery system
Rok publikacji
2016
Strony (od-do)
2756--2764
Numer rozdziału
Link do pełnego tekstu
Identyfikator DOI
Liczba arkuszy
0.64
Hasło encyklopedyczne
Autorzy
(liczba autorów: 3)
Słowa kluczowe
EN
lifetime management
Lithium-Ion battery
battery ageing mechanism
state of health monitoring
battery degradation monitoring
Konferencja
Indeksowana w Scopus
tak
Indeksowana w Web of Science Core Collection
nie
Liczba cytowań z Web of Science Core Collection
Nazwa konferencji (skrócona)
EWSHM 2016
Nazwa konferencji
8th European Workshop on Structural Health Monitoring
Początek konferencji
2016-07-05
Koniec konferencji
2016-07-08
Lokalizacja konferencji
Bilbao
Kraj konferencji
ES
Lista innych baz czasopism i abstraktów w których była indeksowana
Streszczenia
Język
EN
Treść
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.
Cechy publikacji
chapter-in-a-book
peer-reviewed
Inne
System-identifier
idp:102279