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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.

Demands for higher power engines have led to higher pressures in fuel injectors. Internal nozzle flow plays a critical role in the near nozzle flow and subsequent spray pattern. The internal flow becomes more difficult to model when the injector pressure and internal shape make it more prone to cavitation. Two Bosch injectors, proposed for experimental and computational studies under the Engine Combustion Network (namely “Spray C” and “Spray D”) are modeled in the computational fluid dynamics code ANSYS Fluent. Both injectors operate with n-dodecane as fuel at 150 MPa inlet pressures. The computational model includes cavitation effects to characterize any cavitating regions. Including compressibility of both liquid and vapor is found to be critical. Also, due to high velocity gradients and stresses in the nozzle, turbulent viscous energy dissipation is considered along with pressure work resulting from significant pressure changes in the injector.

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.

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.

A methodology has been implemented to calculate local turbulent flame speeds for spark ignition engines accurately and on-the-fly in 3-D CFD modeling. The approach dynamically captures fuel effects, based on detailed chemistry calculations of laminar flame speeds. Accurately modeling flame propagation is critical to predicting heat release rates and emissions. Fuels used in spark ignition engines are increasingly complex, which necessitates the use of multi-component fuels or fuel surrogates for predictive simulation. Flame speeds of the individual components in these multi-component fuels may vary substantially, making it difficult to define flame speed values, especially for stratified mixtures. In addition to fuel effects, a wide range of local conditions of temperature, pressure, equivalence ratio and EGR are expected in spark ignition engines.

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.

Computational Fluid Dynamics (CFD) is widely used in vehicle aerodynamics development today, but typically used to study one vehicle shape at a time. In order to be used for aerodynamic shape exploration and optimization the CFD simulation process has to be able to study a large set of design alternatives (vehicle shape variants) within the short period of time typically available in the overall aerodynamics development process. This paper reports the development and testing of a process, referred to as the 50:50:50 Method, which is developed to study a large set of design alternatives in a highly automated way, while ensuring that each design alternative is simulated with a high fidelity CFD simulation.

A CFD simulation methodology is presented to evaluate the ice that sheds from rotating components. The shedding detection is handled by coupling the ice accretion and stress analysis solvers to periodically check for the propagation of crack fronts and possible detachment. A novel approach for crack propagation is highlighted where no change in mesh topology is required. The entire computation from flow to impingement, ice accretion and crack analysis only requires a single mesh. The accretion and stress module are validated individually with published data. The analysis is extended to demonstrate potential shedding scenarios on three complex industrially-relevant 3D cases: a helicopter blade, an engine fan blade and a turboprop propeller. The largest shed fragment will be analyzed in the context of FOD damage to neighboring aircraft/component surfaces.

With advances in computing power and Computational Fluid Dynamics (CFD) algorithms, the complexity of CutCell based simulation models has significantly increased. In this study three dimensional numerical simulations were created for steady incompressible flow around airfoil shape. The NACA-0012 airfoil was used for this study. Boundary layer thickness, mesh expansion ratio, and mesh density variation parameters were investigated. Drag and lift coefficients were compared to experimental data. Use of the CutCell method results in a good agreement between CFD results and experimental data.

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.

Thorough design exploration is essential for improving vehicle performance in various aspects such as aerodynamic drag. Shape optimization algorithms in combination with computational tools such as Computational Fluid Dynamics (CFD) play an important role in design exploration. The present work describes a Free-Form Deformation (FFD) approach implemented within a general purpose CFD code for parameterization and modification of the aerodynamic shape of real-life vehicle models. Various vehicle shape parameters are constructed and utilized to change the shape of a vehicle using a mesh morphing technique based on the FFD algorithm. Based on input and output parameters, a design of experiments (DOE) matrix is created. CFD simulations are run and a response surface is constructed to study the sensitivity of the output parameter (aerodynamic drag) to variations in each input parameter.

One of the best tools to explore complicated in-cylinder physics is computational fluid dynamics (CFD). In order to assess the accuracy and reliability of the CFD simulations, it is critical to perform validation studies over different engine operating conditions. Simulation-based design of SI engines requires predictive capabilities, where results do not need to be tuned for each operating condition. This requires the models adopted to simulate their respective engine physics to be reliable under a broad range of conditions. A detailed set of experimental data was obtained to validate the CFD predictions of SI engine combustion.

Gasoline Direct Injection (GDI) is a key technology in the automotive industry for improving fuel economy and performance of gasoline internal combustion engines. GDI engine performance and emission characteristics are mainly determined by the complex interaction of in-cylinder flow, mixture formation and subsequent combustion processes. In a GDI engine, mixture formation depends on spray characteristics. Spray evolution and mixture formation is critical to GDI engine operation. In this work, a multi-component surrogate fuel blend was used to represent the chemical and physical properties of the gasoline employed in the experimental engine tests. Multi-component spray models were also validated in this study against experimental spray injection measurements in a chamber. The spray-chamber data include spray-penetration lengths, transient spray velocities and droplet Sauter mean diameter (SMD) at different axial and radial distances from the spray tip, obtained using a PDPA system.

Computational Fluid Dynamics (CFD) is heavily used in automotive HVAC industry in order to reduce the time and cost in design, optimization, and development of different components [2]. Correct prediction of the aerodynamic characteristics of an HVAC blower is crucial in development of the accurate CFD models for the whole HVAC system. CFD models are extensively used in the optimization of both thermal and airflow characteristics of automotive HVAC [3, 4 and 5]. In this study we have performed CFD simulations for different blower operating conditions in order to assess the CFD results in prediction of the aerodynamic performance in an automotive HVAC forward curved (FC) centrifugal blower. The realizable k-ε turbulence model was used on the Reynolds Averaged Navier-Stokes approach to model complex flow field properly.

Increased energy costs make optimal aerodynamic design even more critical today as even small improvements in aerodynamic performance can result in significant savings in fuel costs. Energy conscious industries like transportation (aviation and ground based) are particularly affected. There have been a number of different optimization methods, some of which require geometrically parameterized models. For non-parameterized models (as it is the case often in reality where models and shapes are very complex). Shape optimization and adjoin solvers are some of the latest approaches. In our study we are focusing on generating best practices and investigating different strategies of employing the commercially available shape optimizer tool from ANSYS'CFD solver Fluent. The shape optimizer is based on a polynomial mesh-morphing algorithm. The simple case of a low speed, airfoil/flap combination is used as a case study with the objective being the lift to drag ratio.

Carbon-neutral (CN) fuels will be part of the solution to reducing global warming effects of the transportation sector, along with electrification. CN fuels such as hydrogen, ammonia, biofuels, and e-fuels can play a primary role in some segments (aviation, shipping, heavy-duty road vehicles) and a secondary role in others (light-duty road vehicles). The composition and properties of these fuels vary substantially from existing fossil fuels. Fuel effects on performance and emissions are complex, especially when these fuels are blended with fossil fuels. Predictively modeling the combustion of these fuels in engine and combustor CFD simulations requires accurate representation of the fuel blends. We discuss a methodology for matching the targeted fuel properties of specific CN fuels, using a blend of surrogate fuel components, to form a fuel model that can accurately capture fuel effects in an engine simulation.

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).

In-flight icing significantly influences the design of large passenger aircraft. Relevant aspects include sizing of the main aerodynamic surfaces, provision of anti-icing systems, and setting of operational restrictions. Empennages of large passenger aircraft are particularly affected due to the small leading edge radius, and the requirement to generate considerable lift for round out and flare, following an extended period of descent often in icing conditions. This paper describes a CFD-based investigation of the effects of sweep on the aerodynamic performance of a novel forward-swept horizontal stabilizer concept in icing conditions. The concept features an unconventional forward sweep, combined with a high lift leading edge extension (LEX) located within a fuselage induced droplet shadow zone, providing passive protection from icing.

Aromatics constitute a significant portion of refinery fuels. Characterizing the impact of various aromatic components on combustion and emissions facilitates formulation of surrogate fuels for engine simulations. The impact of blending aromatics in fuel surrogates is usually nonlinear for ignition characteristics responsible for knocking in spark engines and for combustion phasing in diesel engines. In this work, we have characterized the behavior of nine aromatics components under engine-relevant conditions. A self-consistent and validated detailed kinetics mechanism has been developed for gasoline and diesel surrogates that contains toluene, ethylbenzene, n-propylbenzene, n-butylbenzene, isomers of xylene, 1,2,4-trimethylbenzene, and 1-methylnaphthalene. Numerical experiments using 0-D and 1-D models have been performed to study the relative behavior of these aromatics for different reacting conditions.

A full-automated CFD mesh generation technique has been developed and implemented for 3-D aircraft icing simulations to permit robust 45-minute ice accretion simulations in support of icing certification campaigns. The changes in the shape of the aircraft surfaces due to accreting ice and their effects on the air and droplet flow are accounted for in a quasi-steady manner by subdividing the total icing time into sequential steps of shorter duration, updating the computational grid at each step. This “multi-shot” ice accretion approach requires robust and accurate grid re-meshing for it to be embedded in engineering design and analysis workflows. ANSYS FENSAP-ICE has been coupled to Fluent Meshing to take advantage of generic and highly automated surface displacement and mesh wrapping tools. A wide spectrum of geometries is supported, ranging from full-size aircraft to air data probes, turbomachinery components, rotors and propellers.