Electrochemical Model-Based State of Charge and Capacity Estimation for a Composite Electrode Lithium-Ion Battery

—Increased demand for hybrid and electric vehicles has motivated research to improve onboard state of charge and state of health estimation. In particular, batteries with composite electrodes have become popular for automotive applications due to their ability to balance energy density, power density, and cost by adjusting the amount of each material within the electrode. State of health estimation algorithms that do not use electrochemical based models may have more difficulty maintaining an accurate battery model as the cell ages under varying degradation modes, such as lithium consumption at the solid-electrolyte interface or active material dissolution. Furthermore, efforts to validate electrochemical model-based state estimation algorithms with experimental aging data are limited, particularly for composite electrode cells. In this paper we first present a reduced order electrochemical model for a composite LiMn2O4-LiNi1/3Mn1/3Co1/3O2 (LMO-NMC) electrode battery that predicts ...

• Type: Journal
• Year: 2016
• Where: TCST
• Authors: Alexander Bartlett, James Marcicki, Simona Onori, Giorgio Rizzoni, Xiao Guang Yang, Ted Miller
• Keywords: TCST 2016