The operational requirements that batteries have to satisfy in automotive and
stationary applications are more demanding. Therefore, eective control and
management of batteries is crucial for assuring the best battery performance,
considering using the batteries in the safest and longest living way. Despite
the fact that the diagnosis and prognosis of the state of health (SoH) are
absolutely needed in practical applications, they are not yet eectively
implemented. Extensive work is still required to develop an accurate and
applicable diagnosis method.
In this PhD research, a thorough and extensive state-of-the-art study
regarding SoH estimation techniques has been performed. The literature
research highlighted the need for an accurate and implementable SoH
algorithm, as well as the requirements that the algorithm needs to fulll.
According to these demands, this PhD dissertations developed dierent SoH
estimation algorithms for two types of lithium-ion chemistries: Graphite
based anode / Nickel Manganese Cobalt Oxide cathode and Graphite based
anode / Lithium Iron Phosphate cathode type of batteries. All algorithms
can be implemented in a battery management system , and are able to detect
the SoH at cell1-, module2- and battery pack3 level. Precise and accurate
estimations are obtained through partial charges or discharges of the
batteries, with no interference with the application's functionality.
Related to the SoH estimation, the path dependency is of great importance
for the detection of degradation mechanisms. Path dependence is emerging as
a key issue for how battery cells age in dierent conditions. Even though it
is not easy to handle path dependence due to the numerous features that can
vary in a cell, a novel and precise diagnosis model has been developed during
this PhD dissertation. This online- and implementable diagnosis model was
validated with dierent experimental tests. As future work this model will
give the chance of developing thorough research regarding battery aging, SoH
prediction and even battery life extension.
Datum Prijs28 aug 2017
Toekennende instantie
  • Vrije Universiteit Brussel
BegeleiderNoshin Omar (Promotor), Joeri Van Mierlo (Promotor) & Igor Villarreal (Promotor)

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