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A linear parameter varying (LPV) reduced order model (ROM) is used to approximate the volume-averaged temperature of battery cells in one of the modules of the battery pack with varying mass flow rate of cooling fluid using uniform heat source as inputs. The ROM runs orders of magnitude faster than the original CFD model. To reduce the time it takes to generate training data, used in building LPV ROM, a divide-and-conquer approach is introduced. This is done by dividing the battery module into a series of mid-cell and end-cell units. A mid-cell unit is composed of a cooling channel sandwiched in between two half -cells. A half-cell has half as much heat capacity as a full-cell. An end-cell unit is composed of a cooling channel sandwiched in between full-cell and a half-cell. A mass flow rate distribution look-up-table is generated from a set of steady-state simulations obtained by running the full CFD model at different inlet manifold mass flow rate samples.

The purpose of present study is to use Immersed Boundary (IB) method in flow field simulations of a simplified generic ground transportation system (GTS) at 0° yaw. The IB method is usually employed in conjunction with a body non-conforming Cartesian grid. Thus, grid generation is greatly simplified. This plays an important role in reducing the cost and time in design process. This paper demonstrates the ease of use of IB method compared to body fitted mesh method and possible use of IB method to automate the external aerodynamics simulations. Also in order to assess the accuracy, the results are compared with corresponding experimental data reported in literature.

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.

Development of quick and efficient numerical tools is key to the design of industrial machines. While Computational Fluid Dynamics (CFD) techniques based on Navier Stokes (N-S) and Lattice Boltzman methods are becoming popular, predicting aeroacoustic behavior for complex geometries remains computationally intensive for design process and iteration. The goal of this paper is to evaluate application Navier-Stokes approach coupled with Ffowcs Williams and Hawkings (FW-H), and Broad-band Noise Model (BNS) to evaluate noise levels and predict design direction for industrial applications. Steady-state RANS based approaches are used to evaluate under-hood cooling performance and fan power demand. At each design iteration, noise levels and strength of noise source are evaluated using Gutin’s and broad-band noise models, respectively along with cooling performance. Each design feature selected for the final design has lower fan power and noise level with improved cooling.

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.

This paper introduces a model-based systems and embedded software engineering, workflow for the design of control systems. The interdisciplinary approach that is presented relies on an integrated set of tools that addresses the needs of various engineering groups, including system architecture, design, and validation. For each of these groups, a set of best practices has been established and targeted tools are proposed and integrated in a unique platform, thus allowing efficient communication between the various groups. In the initial stages of system design, including functional and architectural design, a SysML-based approach is proposed. This solution is the basis to develop systems that have to obey both functional and certification standards such as ARINC 653 (IMA) and ARP 4754A. Detailed system design typically requires modeling and simulation of each individual physical component of the system by various engineering groups (mechanical, electrical, etc.).

Cylinder head design is one of the most involved disciplines in engine design. Whether designing an altogether new head or revamping an old one, several different coupled and inter-dependent technologies ranging from heat transfer, fluid flow, combustion, material non-linearity, structural and fatigue have to be accounted. Simultaneous designing of ports, jacket and combustion chamber leads to cylinder head design, which is then tested for its strength and durability. Traditionally a series of analytical, empirical, test-based and simulation based exercises are conducted to design cylinder heads. With increasing pressure on reducing cost and turnaround time, focus on moving towards a quasi-simulation based design and development of cylinder heads is gaining strength. This paper talks about how a simulation driven process for cylinder head design can be developed.

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.

The thermal behavior of a fluid-cooled battery can be modeled using computational fluid dynamics (CFD). Depending on the size and complexity of the battery module and the available computing hardware, the simulation can take days or weeks to run. This work introduces a reduced-order model that combines proper orthogonal decomposition, capturing the variation of the temperature field in the spatial domain, and linear time-invariant system techniques exploiting the linear relationship between the resulting proper orthogonal decomposition coefficients and the uniform heat source considered here as the input to the system. After completing an initial CFD run to establish the reduction, the reduced-order model runs much faster than the CFD model. This work will focus on thermal modeling of a single prismatic battery cell with one adjacent cooling channel. The extension to the multiple input multiple output case such as a battery module will be discussed in another paper.

The safety, performance, and operational life of power dense Lithium-ion batteries used in Hybrid and Electric Vehicles are dependent on the operating temperature. Modeling and simulation are essential tools used to accelerate the design process of optimal thermal management systems. However, high-fidelity 3D computational fluid dynamics (CFD) simulation of such systems is often difficult and computationally expensive. In this paper, we demonstrate a multi-part coupled system model for simulating the heating/cooling system of the traction battery at a module level. We have reduced computational time by employing reduced-order modeling (ROM) framework on separate 3D CFD models of the battery module and the cooling plate. The order of the thermal ROM has also been varied to study the trade-off between accuracy, fidelity, and complexity. The ROMs are bidirectionally coupled to an empirical battery model built from in-house test data.

With the rapid development of electric vehicles, the demands for lithium-ion batteries and advanced battery technologies are growing. Today, lithium-ion batteries mainly use liquid electrolytes, containing organic compounds such as dimethyl carbonate and ethylene carbonate as solvents for the lithium salts. However, when thermal runaway occurs, the electrolyte decomposes, venting combustible gases that could readily be ignited when mixed with air and leading to pronounced heat release from the combustion of the mixture. So far, the chemical behavior of electrolytes during thermal runaway in lithium-ion batteries is not comprehensively understood. Well-validated compact chemical kinetic mechanisms of the electrolyte components are required to describe this process in CFD simulations. In this work, submechanisms of dimethyl carbonate and ethylene carbonate were developed and adopted in the Ansys Model Fuel Library (MFL).