Battery Modeling: A Versatile Tool to Design Advanced Battery Management Systems

Abstract

Fundamental physical and (electro) chemical principles of rechargeable battery operation form the basis of the electronic network models developed for Nickel-based aqueous battery systems, including Nickel Metal Hydride (NiMH), and non-aqueous battery systems, such as the well-known Li-ion. Refined equivalent network circuits for both systems represent the main contribution of this paper. These electronic network models describe the behavior of batteries during normal operation and during over (dis) charging in the case of the aqueous battery systems. This makes it possible to visualize the various reaction pathways, including convention and pulse (dis) charge behavior and for example, the self-discharge performance.

Explaining key properties of lithiation in TiO2 -anatase Li-ion battery electrodes using phase-field modeling

“…The nonequilibrium conditions in complete electrodes will lead to * m.wagemaker@tudelft.nl macroscopic gradients in diffusing species, and the associated potential gradients can change phase-transition kinetics, as has been demonstrated for LiFePO 4 [11]. Even when a model is obtained which reasonably describes the processes, it often involves a number of unknown physical parameters, which require fitting to experimental data.…”

“…This is computationally feasible because the phase-interface is taken implicitly into account [9], making it unnecessary to evaluate the phase transition kinetics in every position in an electrode particle. Using phase-field models for LiFePO 4 the observed decreasing miscibility and spinodal gap in nanoparticles [15] has been explained [13,16], the observed transition from a first-order phase transition to a solid solution reaction at high overpotentials [17,18] has been predicted, and the transition from particle by particle to a concurrent mechanism was predicted [11] consistent with observations [19]. Recently, a three-dimensional phase-field model has been presented for LiFePO 4 [16], and crack formation and the effects this causes have also been incorporated [20].…”

“…Using phase-field models for LiFePO 4 the observed decreasing miscibility and spinodal gap in nanoparticles [15] has been explained [13,16], the observed transition from a first-order phase transition to a solid solution reaction at high overpotentials [17,18] has been predicted, and the transition from particle by particle to a concurrent mechanism was predicted [11] consistent with observations [19]. Recently, a three-dimensional phase-field model has been presented for LiFePO 4 [16], and crack formation and the effects this causes have also been incorporated [20]. The phase-field method has also been used to describe the lithiation of graphite electrodes [21,22], requiring the introduction of two first-order phase-transformations, which is relatively straight forward in a phase-field model, resulting in good agreement with experiments [21].…”

Structural Identifiability of Equivalent Circuit Models for Li-Ion Batteries

“…Given a model of the general form (17)- (19) that satisfies the ORC, this approach generates the corresponding input/output map for the system. This approach requires calculating the Lie derivatives of the observation function, defined in Equation (25). These are used as inputs into the univariate polynomial or Groebner bases algorithms in Maple, producing the input/output relationship for the model.…”

“…As discussed previously, Unidentifiable parameters (i.e., parameters that cannot be uniquely identified) can take an infinite number of numerical values, rendering any numerical estimate obtained from parameter estimation meaningless. Despite the implications, LIB models containing in excess of 19 resistors and 30 capacitors can be found in the literature with no consideration for structural identifiability [25]. In this ECM, diffusion and migration were represented by a complex ladder network.…”