  Advanced battery management systems rely on mathematical models to guarantee
optimal functioning of Lithium-ion batteries. The Pseudo-Two Dimensional (P2D)
model is a very detailed electrochemical model suitable for simulations. On the
other side, its complexity prevents its usage in control and state estimation.
Therefore, it is more appropriate the use of simplified electrochemical models
such as the Single Particle Model with electrolyte dynamics (SPMe), which
exhibits good adherence to real data when suitably calibrated. This work
focuses on a Fisher-based optimal experimental design for identifying the SPMe
parameters. The proposed approach relies on a nonlinear optimization to
minimize the covariance parameters matrix. At first, the parameters are
estimated by considering the SPMe as the real plant. Subsequently, a more
realistic scenario is considered where the P2D model is used to reproduce a
real battery behavior. Results show the effectiveness of the optimal
experimental design when compared to standard strategies.
