• battery
• bms
• ecm
• lithium
• lithium ion battery
• lithium-ion

This thesis through the analysis of the results of the simulations of the Pseudo 2
Dimensional (P2D) chemical model of a lithium ion cell aims to find a relationship
between the chemical components of the cell and the electrical parameters of the
equivalent circuit model (ECM). Rechargeable lithium-ion batteries are widely used
as energy storage systems for portable devices due to their multiple advantages over
other chemicals. Li-ion batteries must be used within a Safe Operating Area (SOA)
bounded by specific temperatures, voltages and currents. More the cell is used
outside the SOA more its health will be affected, and its performance will be worse.
The Battery Management System or BMS is the device that monitor the cell and
uses protection mechanisms to prevent irreversible damages. One way to monitor
the health of the cell is to estimate online, therefore during the operating phase of
the cell, its most significant parameters such as the state of charge, the state of
health and the parameters of the ECM. ECMs are a mathematical modelling of the
cell and replicate its electrical behaviour. These models need few computational
resources to be calculated, so they are very simple to calculate online during the cell
operational phase. The problem is that the reliability in predicting the results is
poor. This is because mathematical modelling of lithium ion cells with good
predictions need more computational requirements. A widely used modelling is P2D
because it is quite accurate and its results are very similar to the experimental ones,
but it needs greater computational requirements. The purpose of this thesis is to
link to each electrical parameter of the ECM one or more parameter of the P2D
model of the cell. Then merge the simplicity of ECM simulation with the best
predictive reliability of the P2D model. By identifying online the parameters of the
ECM, during the operating phase of the cell, the parameters of the P2D model and
therefore the phenomena within the cell will also be clear. A P2D chemical model of
a lithium-ion cell developed on COMSOL was initially validated with a large data
set. Subsequently various charges and discharges were simulated by varying some
parameters of the model, in order to modify the chemists within the cell. After each
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simulation, all the results that kept track of the electrical behaviour of the model
(voltage, current, temperature, etc.) are saved. The results are then processed by a
MATLAB script that identified the parameters of an ECM with two-time constants
that replicated the electrical behaviour of the P2D chemical model. The parameters
of the ECM have been optimized to reduce the error between the electrical results
and those of the chemical model as much as possible. The data saved after the script
was run was analysed and correlations were found between the electrical parameters
of the ECM and the changed parameters in the P2D model simulations. Finally,
correlation indices were used to find the chemical components within the cell
corresponding to each parameter of the ECM. The results obtained show that each
chemical phenomenon of the cell can identify in one or more electrical parameters of
the ECM. This thesis wants to highlight that one way to keep track of the chemical
components inside the cell and therefore of its health is to simply analyse the
variations of the ECM parameters. However, further research and refinements of the
model and of the conversion algorithms are necessary to obtain more reliable results
and to extend them to any operating condition. In addition, in the P2D chemical
model with subsequent research and more targeted variations, cell aging can be
implemented with the insertion of degradations. With this, by analysing the
electrical parameters of the ECM one could make a prediction about life span of a
cell.