This thesis investigates the optimization of lithium-ion battery electrode parameters and the utilization of advanced simulation techniques to enhance battery performance. Layered lithium nickel-manganese-cobalt oxide (NMC) and lithium iron phosphate (LFP) are the two most widely used cathode materials for lithium-ion batteries. Battery performance is controlled not only by the intrinsic properties of the active materials (e.g. NMC, LFP) but also the porous electrode structure at the battery cell level. This thesis deals with cell-level battery modeling and is structured in three comprehensive chapters. The first chapter discusses the application of high-efficiency computational tools for simulating lithium-ion batteries with NMC cathodes. It emphasizes the adoption of the Pseudo-Two-Dimensional (P2D) model and computational approaches to expedite parameter optimization, which is crucial for improving battery performance. The second chapter critically evaluates four modeling techniques for LFP cathode batteries, with a focus on their capability to accurately fit experimental data regarding the lithium diffusivity coefficient. The efficacy and precision of the selected models are thoroughly assessed. The final chapter explores the incorporation of phase-transition-induced stress in the model for LFP, analyzing how various model parameters influence the battery’s discharge curve and the reaction distribution. It includes a discussion on the current gaps in comprehensive analyses of phase transition materials and highlights the need for better computational models to simulate the stress effect during battery charge / discharge.