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Due to growing interest in hybrid and electric vehicles, li-ion battery modeling is receiving a lot of attention from designers and researchers. This paper presents a complete model for a li-ion battery pack. It starts from the Newman electrochemistry model to create the battery performance curves. Such information is then used for cell level battery equivalent circuit model (ECM) parameter identification. 28 cell ECMs are connected to create the module ECM. Four module ECMs are connected through a busbar model to create the pack ECM. The busbar model is a reduced order model (ROM) extracted from electromagnetic finite element analysis (FEA) results, taking into account the parasitic effects. Battery thermal performance is simulated first by computational fluid dynamics (CFD). Then, a thermal linear and time-invariant (LTI) ROM is created out of CFD solution. The thermal LTI ROM is then two-way coupled with the battery pack ECM to form a complete battery pack model.

Due to growing interest in hybrid and electric vehicles, the battery, being one of the critical components, is receiving a lot of attention from designers and researchers. Two battery-modeling approaches, though seemingly different, share the same mathematical challenge of robust non-linear curve-fitting. The two methods are battery equivalent circuit model and battery system level thermal modeling using the linear time-invariant (LTI) method. Both modeling approaches involve curve-fitting testing data or data from advanced models to identify four parameters in a circuit model consisting of two pairs of RC elements. Such curve-fitting is mathematically a non-linear least-squares (LS) problem. Standard methods like the Levenberg-Marquardt (LM) method can be used for non-linear curve-fitting, but the LM method is known to be sensitive to initial conditions.

A commonly used physics based electrochemisty model for a lithium-ion battery cell was first proposed by professor Newman in 1993. The model consists of a tightly coupled set of partial differential equations. Due to the tight coupling between the equations and the 2d implementation due to the particle modeling, and thus called pseudo-2d in literature, numerically obtaining a solution turns out to be challenging even for a lot of commercial softwares. In this paper, the VHDL-AMS language is used to solve the set of equations. VHDL-AMS allows the user to focus on the physical modeling rather than numerically solving the governing equations. In using VHDL-AMS, the user only needs to specify the governing equations after spatial discretization. A simulation environment, which supports VHDL-AMS, can then be used to solve the governing equations and also provides both pre- and post- processing tools.

Battery thermal management for high power applications such as electrical/hybrid vehicles is crucial. Modeling is an indispensable tool to help engineers design better battery cooling systems. While Computational Fluid Dynamics (CFD) has been used quite successfully for battery thermal management, CFD models can be too large and too slow for repeated transient thermal analysis especially for a battery module or pack. An accurate but much smaller battery thermal model using a state space representation is proposed. The parameters in the state space model are extracted from CFD results. The state space model is then shown to provide identical results as those from CFD under transient power inputs. While a CFD model may take hours to run depending on the size of the problem, the corresponding state space model runs in seconds.

The emergence of diverse and powerful simulation tools makes it possible to describe automotive components at several levels of abstraction. Engineers are often required to make difficult decisions about the appropriate level of model complexity to employ: whether the component needs to be described at a detailed electromagnetic level, at an intermediate circuit level, or at an abstract behavioral level. While such decisions depend on application needs, they can result in expensive design changes since incorrect simulation at any level results in prototype failure and necessary redesign. This paper describes a new multi-level modeling methodology with a detailed analysis of the tradeoffs between the accuracy of an abstraction level and the efficiency of the simulation. The procedure is illustrated using a claw-pole alternator as an example.