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Power limit estimation of a lithium-ion battery pack can be employed by a battery management system (BMS) to balance a variety of operational considerations, including optimization of pulse capability while avoiding damage and minimizing aging. Consideration of cell-to-cell performance variability of lithium-ion batteries is critical to correct estimation of the battery pack power limit as well as proper sizing of the individual cells in the battery. Further, understanding of cell variability is necessary to protect the cell and other system components (e.g., fuse and contactor, from over-current damage). In this work, we present the use of an equivalent circuit model for estimation of the power limit of lithium-ion battery packs by considering the individual cell variability under current or voltage constraints. We compare the power limit estimation by using individual cell characteristics compared to the estimate found using only max/min values of cell characteristics.

The microhybrid electric vehicle (MHEV) has increasingly received attention since it holds promise for significant increases in fuel economy vs. traditional gasoline vehicles at a lower price point than hybrid vehicles. Passive parallel connection of the traditional 12V lead acid battery and a high power lithium ion battery has been identified as a potential architecture that will facilitate fuel economy improvements with minimal changes to the electrical network. Enabling a passive dual-battery connection requires a design match between the two batteries, including characteristics such as battery size and resistance, so that the performance can be optimized. In this work we have developed a hybrid model that couples electrochemical model of lithium ion battery (NMC-Graphite as an example) and an equivalent circuit model of lead acid battery in order to study the behavior of 12V dual-battery microhybrid architectures.

Competitive engineering of battery packs for vehicle applications requires a careful alignment of function against vehicle manufacturer requirements. Traditional battery engineering practices focus on flow down of requirements from the top-level system requirements through to low-level components, meeting or exceeding each requirement at every level. This process can easily produce an over-engineered, cost-uncompetitive product. By integrating the key limiting factors of battery performance, we can directly compare battery capability to requirements. Here, we consider a power-oriented microhybrid battery system using coupled thermal and electrochemical modeling. We demonstrate that using dynamic resistance acquired from drive cycle characteristics can reduce the total size of the pack compared to typical static, fixed-duration resistance values.