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DOE OSTI2017

A Simulation Framework for Battery Cell Impact Safety Modeling Using LS-DYNA

The development process of electrified vehicles can benefit significantly from computer-aided engineering tools that predict themultiphysics response of batteries during abusive events. A coupled structural, electrical, electrochemical, and thermal model framework has been developed within the commercially available LS-DYNA software. The finite element model leverages a three-dimensional mesh structure that fully resolves the unit cell components. The mechanical solver predicts the distributed stress and strain response with failure thresholds leading to the onset of an internal short circuit. In this implementation, an arbitrary compressive strain criterion is applied locally to each unit cell. A spatially distributed equivalent circuit model provides an empirical representation of the electrochemical responsewith minimal computational complexity.The thermalmodel provides state information to index the electrical model parameters, while simultaneously accepting irreversible and reversible sources of heat generation. The spatially distributed models of the electrical and thermal dynamics allow for the localization of current density and corresponding temperature response. The ability to predict the distributed thermal response of the cell as its stored energy is completely discharged through the short circuit enables an engineering safety assessment. A parametric analysis of an exemplary model is used to demonstrate the simulation capabilities.

25 ENERGY STORAGE↗

DOE OSTI2024

BIM Interoperability Tool for Improving IFC-based Model Data Exchange Between Architectural Design and Structural Analysis for Linear Piping Components

There is a growing need in the AEC industry for the digitalization of model-based data exchange in BIM workflows. However, users continue to face difficulties exchanging data between BIM-based computer-aided design (CAD) and computer-aided engineering (CAE) software, even with the open, non-proprietary data exchange format called Industry Foundation Classes (IFC). Proposed solutions in academic research focus primarily on building systems, with comparatively little attention to piping models. Therefore, this paper introduces an interoperability tool for enabling piping model data exchange between architectural and structural analysis domains. The tool is tested using a piping model created in Autodesk Revit and shows marked improvement for IFC-based CAD-to-CAE interoperability over existing practice.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2015

Predictive Engineering Tools for Injection-Molded Long-Carbon-Fiber Thermoplastic Composites (FY 2015 Third Quarterly Report)

During the third quarter of FY 2015, the following technical progress has been made toward project milestones: 1) Magna oversaw the tool build and prepared the molding plan for the complex part of Phase II. 2) PlastiComp hosted a visit by Magna and Toyota on April 23rd to finalize the molding scope and schedule. The plan for molding trials including selection of molding parameters for both LFT and D-LFT for the U-shape complex part was established. 3) Toyota shipped the U-shape complex part tool to Magna on May 28th, 2015. 4) Plasticomp provided 30wt% LCF/PP and 30wt% LCF/PA66 compounded pellets to Magna for molding the complex part. 5) Magna performed preliminary molding trials on June 2nd, 2015 to validate wall thickness, fill profile, tool temperature and shot size requirements for the complex part. 6) Magna performed the first complex part run on June 16th and 17th, 2015 at Magna’s Composite Centre of Excellence in Concord, ON, Canada. Dale Roland of Plasticomp, and Umesh Gandhi of Toyota also attended the molding. 7) Magna discussed and finalized the plan with PNNL and the team for cutting samples from molded parts at selected locations for fiber orientation and length measurements. 8) Magna provided the computer-aided design (CAD) files of the complex parts with and without ribs to PNNL and Autodesk to build the corresponding ASMI models for injection molding simulations. Magna also provided the actual parameters used. 9) Plasticomp’s provided knowledge and experience of molding LCF materials essential to the successful molding of the parts including optimization of fill speed, tool temperatures, and plasticizing conditions for the 30wt% LCF/PP and 30wt% LCF/PA66 materials in both rib and non-rib versions. 10) Magna molded additional parts for evaluation of mechanical property testing including torsional stiffness on June 29th and 30th, 2015 at Magna’s Composite Center of Excellence. 11) Toyota began preparation for the torsion test of the specimens. Preparation of a computer-aided engineering (CAE) model to predict the performance is in progress. 12) Autodesk fixed an error in the implementation of the proper orthogonal decomposition (POD) calculation of fiber length that had caused the ASMI solution to crash and provided an updated build of ASMI containing the fix. 13)Autodesk reviewed and provided feedback for the complex part molding and measurement locations. 14) Autodesk provided support to set up the workflow for ASMI-ABAQUS® analysis, and provided a fix and workaround for a bug in the ASMI-ABAQUS® output command. 15) Autodesk helped build ASMI analysis models for the complex parts with and without ribs. 16) Autodesk worked on improving the orientation prediction accuracy in the shearing layer for 3D meshes based on comparison to measured data of the plaque moldings. 17) PNNL installed a new ASMI version received from Autodesk and performed comparative analyses to assess mid-plane versus 3D fiber length predictions using the full fiber length model and the reduced-order model (ROM) using POD. 18) PNNL presented the project scope, accomplishments, significant results and future plans to DOE and the USCAR Materials Tech Team on June 3rd, 2015. 19) PNNL discussed the cutting of samples from molded parts and finalized a plan with Magna and the team suggesting the sample size, locations and number of samples per location. 20) PNNL and Autodesk built ASMI models for the complex parts with and without ribs, and preliminary analyses of the part with ribs were conducted using the actual molding parameters received from Magna. 21) PNNL worked on a procedure to extract fiber orientation and length results from a 3D ASMI analysis to a 3D ABAQUS model. This procedure is essential to import ASMI fiber orientation and length to a 3D ABAQUS model of the part allowing future part structural analysis for weight reduction study.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Accelerating kinetic plasma simulations with machine-learning-generated initial conditions

Computational models of plasma technologies often solve for the system operating conditions by time-stepping an initial value problem to a quasi-steady solution. However, the strongly nonlinear and multi-timescale nature of plasma dynamics often necessitate millions, or even hundreds of millions, of steps to reach convergence, reducing the effectiveness of these simulations for computer-aided engineering. We consider acceleration of kinetic plasma simulations via data-driven machine-learning-generated initial conditions, which initialize the simulations close to their final quasi-steady-state, thereby reducing the number of steps to reach convergence. Three machine-learning models are developed to predict the density and ion kinetic profiles of capacitively coupled plasma discharges relevant to the microelectronics industry. The models are trained on kinetic simulations over a range of device operating frequencies and pressures. Best performance was observed when simulations were initialized with ion kinetic profiles generated by a convolutional neural network, reducing the mean number of steps to reach convergence by 17.1× when compared to initialization with a zero-dimensional global model. We also outline a workflow for continuous data-driven model improvement and simulation speedup, with the aim of generating sufficient data for full device digital twins.

Artificial neural networks↗

DOE OSTI2013

Numerical Stability and Accuracy of Temporally Coupled Multi-Physics Modules in Wind-Turbine CAE Tools

In this paper we examine the stability and accuracy of numerical algorithms for coupling time-dependent multi-physics modules relevant to computer-aided engineering (CAE) of wind turbines. This work is motivated by an in-progress major revision of FAST, the National Renewable Energy Laboratory's (NREL's) premier aero-elastic CAE simulation tool. We employ two simple examples as test systems, while algorithm descriptions are kept general. Coupled-system governing equations are framed in monolithic and partitioned representations as differential-algebraic equations. Explicit and implicit loose partition coupling is examined. In explicit coupling, partitions are advanced in time from known information. In implicit coupling, there is dependence on other-partition data at the next time step; coupling is accomplished through a predictor-corrector (PC) approach. Numerical time integration of coupled ordinary-differential equations (ODEs) is accomplished with one of three, fourth-order fixed-time-increment methods: Runge-Kutta (RK), Adams-Bashforth (AB), and Adams-Bashforth-Moulton (ABM). Through numerical experiments it is shown that explicit coupling can be dramatically less stable and less accurate than simulations performed with the monolithic system. However, PC implicit coupling restored stability and fourth-order accuracy for ABM; only second-order accuracy was achieved with RK integration. For systems without constraints, explicit time integration with AB and explicit loose coupling exhibited desired accuracy and stability.

17 WIND ENERGY↗

DOE OSTI2013

Simulation Tool to Assess Mechanical and Electrical Stresses on Wind Turbine Generators: Preprint

Wind turbine generators (WTGs) consist of many different components to convert kinetic energy of the wind into electrical energy for end users. Wind energy is accessed to provide mechanical torque for driving the shaft of the electrical generator. The conversion from wind power to mechanical power is governed by the aerodynamic conversion. The aerodynamic-electrical-conversion efficiency of a WTGis influenced by the efficiency of the blades, the gearbox, the generator, and the power converter. This paper describes the use of MATLAB/Simulink to simulate the electrical and grid-related aspects of a WTG coupled with the FAST aero-elastic wind turbine computer-aided engineering tool to simulate the aerodynamic and mechanical aspects of a WTG. The combination of the two enables studiesinvolving both electrical and mechanical aspects of a WTG. This digest includes some examples of the capabilities of the FAST and MATLAB coupling, namely the effects of electrical faults on the blade moments.

17 WIND ENERGY↗

DOE OSTI2016

A surface ice module for wind turbine dynamic response simulation using FAST

It is a fact that developing offshore wind energy has become more and more serious worldwide in recent years. Many of the promising offshore wind farm locations are in cold regions that may have ice cover during wintertime. The challenge of possible ice loads on offshore wind turbines raises the demand of modeling capacity of dynamic wind turbine response under the joint action of ice, wind, wave, and current. The simulation software FAST is an open source computer-aided engineering (CAE) package maintained by the National Renewable Energy Laboratory. In this paper, a new module of FAST for assessing the dynamic response of offshore wind turbines subjected to ice forcing is presented. In the ice module, several models are presented which involve both prescribed forcing and coupled response. For conditions in which the ice forcing is essentially decoupled from the structural response, ice forces are established from existing models for brittle and ductile ice failure. For conditions in which the ice failure and the structural response are coupled, such as lock-in conditions, a rate-dependent ice model is described, which is developed in conjunction with a new modularization framework for FAST. In this paper, analytical ice mechanics models are presented that incorporate ice floe forcing, deformation, and failure. For lower speeds, forces slowly build until the ice strength is reached and ice fails resulting in a quasi-static condition. For intermediate speeds, the ice failure can be coupled with the structural response and resulting in coinciding periods of the ice failure and the structural response. A third regime occurs at high speeds of encounter in which brittle fracturing of the ice feature occurs in a random pattern, which results in a random vibration excitation of the structure. An example wind turbine response is simulated under ice loading of each of the presented models. This module adds to FAST the capabilities for analyzing the response of wind turbines subjected to forces resulting from ice impact on the turbine support structure. The conditions considered in this module are specifically addressed in the International Organization for Standardization (ISO) standard 19906:2010 for arctic offshore structures design consideration. Special consideration of lock-in vibrations is required due to the detrimental effects of such response with regard to fatigue and foundation/soil response. Finally, the use of FAST for transient, time domain simulation with the new ice module is well suited for such analyses.

17 WIND ENERGY↗

DOE OSTI2013

Importance of Second-Order Difference-Frequency Wave-Diffraction Forces in the Validation of a Fast Semi-Submersible Floating Wind Turbine Model: Preprint

To better access the abundant offshore wind resource, efforts across the world are being undertaken to develop and improve floating offshore wind turbine technologies. A critical aspect of creating reliable, mature floating wind turbine technology is the development, verification, and validation of efficient computer-aided-engineering (CAE) tools that can be relied upon in the design process. The National Renewable Energy Laboratory (NREL) has created a comprehensive, coupled analysis CAE tool for floating wind turbines, FAST, which has been verified and utilized in numerous floating wind turbine studies. Several efforts are currently underway that leverage the extensive 1/50th-scale DeepCwind wind/wave basin model test dataset, obtained at the Maritime Research Institute Netherlands (MARIN) in 2011, to validate the floating platform functionality of FAST to complement its already validated aerodynamic and structural simulation capabilities. In this paper, further work is undertaken to continue this validation. In particular, the ability of FAST to replicate global response behaviors associated with dynamic wind forces, second-order difference-frequency wave-diffraction forces and their interaction with one another are investigated.

17 WIND ENERGY↗

DOE OSTI2013

Assessing the Importance of Nonlinearities in the Development of a Substructure Model for the Wind Turbine CAE Tool FAST: Preprint

Design and analysis of wind turbines are performed using aero-servo-elastic tools that account for the nonlinear coupling between aerodynamics, controls, and structural response. The NREL-developed computer-aided engineering (CAE) tool FAST also resolves the hydrodynamics of fixed-bottom structures and floating platforms for offshore wind applications. This paper outlines the implementation of a structural-dynamics module (SubDyn) for offshore wind turbines with space-frame substructures into the current FAST framework, and focuses on the initial assessment of the importance of structural nonlinearities. Nonlinear effects include: large displacements, axial shortening due to bending, cross-sectional transverse shear effects, etc.

17 WIND ENERGY↗

DOE OSTI2017

1:52 Scale Testing of the First US Commercial Scale Floating Wind Turbine, VolturnUS: Testing Overview and the Evolution of Scale Model Testing Methods

Over the past 6 years, the University of Maine (UMaine) has been an active contributor in research and scale-model testing of floating offshore wind turbines (FOWTs). This paper serves to share the evolution of UMaine’s scale-model testing pedigree by exploring the various test campaigns at a high level, culminating with the design validation of the VolturnUS floating platform. These model test campaigns have each provided key insights into the behavior of FOWT platforms as well as improving the ability to perform model tests of FOWTs. In 2011, the UMaine-led DeepCwind Consortium carried out 1/50-scale model tests of a generic tension leg platform (TLP), a semi-submersible (semi), and a spar-buoy (spar) floating platform at the Maritime Research Institute Netherlands (MARIN) test facility. The designs were Froude-scaled and supported a scaled version of the 5-MW National Renewable Energy Laboratory (NREL) offshore research turbine. Data from these tests has been used extensively for numerical simulation validation efforts using NREL’s computer-aided engineering software FAST and laid the foundation for UMaine’s design efforts on VolturnUS. In 2013, UMaine conducted another test campaign at MARIN using the original semi-submersible from 2011 with an improved turbine as well as a 1:50-scale model of the VolturnUS concrete semi-submersible design. The improved DeepCwind semi-submersible data is currently being utilized in the validation of a large number of other analysis codes as part of the International Energy Agency’s OC5 project. In 2015, UMaine opened its own Wind/Wave test facility, the Alfond Wind/Wave Ocean Engineering Laboratory (W2). Utilizing this new facility, UMaine tested the 1:50-scale model DeepCwind semi-submersible, repeating the tests from MARIN, to validate the experimental equipment and procedures as well as demonstrate the capability of the W2. In 2016 UMaine carried out testing of a 1:52-scale model of the 100% design of the VolturnUS with a 6-MW topside as a final design validation to support the US Department of Energy-supported, full-scale Aqua Ventus demonstration project scheduled to be connected to the grid in 2019. A newly designed 6-MW scale model turbine was used in this test and the performance-matched turbine design methodology is described. Selected results from the test campaign and preliminary numerical comparisons are discussed as well as key lessons learned from the model test campaigns are presented.

17 WIND ENERGY↗

DOE OSTI2014

Improving Energy Efficiency by Developing Components for Distributed Cooling and Heating Based on Thermal Comfort Modeling (General Motors LLC Final Project Report)

On November 3, 2009, General Motors (GM) accepted U.S. Department of Energy (DOE) Cooperative Agreement award number DE-EE0000014 from the National Energy Technology Laboratory (NETL). GM was selected to execute a three-year cost shared research and development project on Solid State Energy Conversion for Vehicular Heating, Ventilation & Air Conditioning (HVAC) and for Waste Heat Recovery. The primary objective of this project was to develop a distributed automotive HVAC system that provides thermal comfort equivalent to current state-of-the-art centralized systems while using significantly less energy. To satisfy this objective, the team identified the following goals: • Reduce by at least 30% of the “billions of gallons” the fuel used in cooling mode to maintain occupant comfort through the localized use of thermoelectric (TE) technology while maintaining occupant comfort and safety. • Develop TE HVAC components with a coefficient of performance (COP) greater than 1.3 for cooling and greater than 2.3 for heating, then integrate and test these components as part of a reliable distributed HVAC system in a conventional vehicle (an eAssist Buick Lacrosse) and an extended range electric vehicle (a Chevrolet Volt). • Update the UCB Thermal Comfort model to predict the response of vehicle occupants to localized heating and cooling based on human subject testing, and develop associated computer-aided engineering (CAE) tools to support the integration of distributed HVAC components into future vehicle designs. A secondary objective of the project was to improve the efficiency of thermoelectric generators for converting engine waste heat into electricity.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2018

Battery Safety Testing

25 ENERGY STORAGE↗

DOE OSTI2019

Ultralight Door Design, Development and Demonstration Project (Final Scientific Report)

The project objectives associated with the Ultralight Door Project were to develop a lightweight driver's side door, 42.5% lighter than a current model year high-volume baseline door, at an incremental cost not to exceed $ \$ $ 5 per pound saved, while maintaining equivalent functionality, safety, corrosion, durability and sound transmission performance of the baseline vehicle. The project approach included the selection of a door architecture, development of a key performance target matrix and incremental cost model. Several unique door structures were developed and evaluated using computer-aided engineering (CAE) and cost modeling tools. The aluminum-intensive door structure was the only design capable of meeting both the performance and cost criteria objectives. The door module, glass, interior trim, latch and electrical subsystems were functionally integrated with the aluminum door structure, enabling additional mass reduction beyond material substitution. The lightweight door design was prototyped, integrated with baseline vehicles and tested to validate equivalent functionality and performance. The project results demonstrate a mass reduction of 15.2 kg (40%) at an incremental cost of $ \$ $2.81 per pound saved, while maintaining functionality and performance of the baseline door. The environmental benefit associated with the Ultralight Door enables a 6g CO 2 eq. per kilometer environmental benefit, for a 4-door vehicle powered by a downsized fuel injected gasoline combustion engine. The project results were presented and published in the 2018 SAE International Conference proceedings and in the Journal of Life Cycle Assessment.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Battery Testing FY 2017 Annual Progress Report

Abuse tests are designed to determine the safe operating limits of HEV\PHEV energy storage devices. Testing is intended to achieve certain worst-case scenarios to yield quantitative data on cell\module\pack response, allowing for failure mode determination and guiding developers toward improved materials and designs. Standard abuse tests with defined start and end conditions are performed on all devices to provide comparison between technologies. New tests and protocols are developed and evaluated to more closely simulate real-world failure conditions. When scaling from cell to the battery level, a detailed understanding of cell interactions provides insight on safety performance. Single point failures from a cell or group of cells can be initiated by a number of triggers including internal short circuit, misuse or abuse, or component failure at the battery or system level. Propagation of a single failure event (regardless of the initiation trigger) through an entire battery, system, or vehicle is an unacceptable outcome with regards to EV battery safety. In this FY, our work has focused on evaluating the propagation of a single cell thermal runaway event through a battery using a variety of design considerations with an emphasis on passive thermal management impacts. This has been coupled with thermal modeling by NREL for these testing conditions. In addition, alternative failure initiation methods have been evaluated to provide direct comparisons of possible energy injection between modes. This data was compiled to better identify what propagation test method is appropriate given certain battery designs. Expanding the analysis of short circuit current during failure propagation has been done for EV relevant chemistries. Ongoing test development and validation to obtain these values has been achieved. While robust mechanical models for vehicles and vehicle components exist, there is a gap for mechanical modeling of EV batteries. The challenge with developing a mechanical model for a battery is the heterogeneous nature of the materials and components (polymers, metals, metal oxides, liquids). Our work will provide empirical data on the mechanical behavior of batteries under compressive load to understand how a battery may behave in a vehicle crash scenario. This work is performed in collaboration with the U.S. Council for Automotive Research (USCAR) and Computer Aided Engineering of Batteries (CAEBAT). These programs have supported the design and development of a drop tower testing apparatus to close the gap between cell/string level testing and full scale crash testing with true dynamic rate effects.

25 ENERGY STORAGE↗

DOE OSTI2015

Coupled Mechanical-Electrochemical-Thermal Modeling for Accelerated Design of EV Batteries; NREL (National Renewable Energy Laboratory)

The physical and chemical phenomena occurring in a battery are many and complex and in many different scales. Without a better knowledge of the interplay among the multi-physics occurring across the varied scales, it is very challenging and time consuming to design long-lasting, high-performing, safe, affordable large battery systems, enabling electrification of the vehicles and modernization of the grid. The National Renewable Energy Laboratory, a U.S. Department of Energy laboratory, has been developing thermal and electrochemical models for cells and battery packs. Working with software producers, carmakers, and battery developers, computer-aided engineering tools have been developed that can accelerate the electrochemical and thermal design of batteries, reducing time to develop and optimize them and thus reducing the cost of the system. In the past couple of years, we initiated a project to model the mechanical response of batteries to stress, strain, fracture, deformation, puncture, and crush and then link them to electrochemical and thermal models to predict the response of a battery. This modeling is particularly important for understanding the physics and processes that happen in a battery during a crush-inducing vehicle crash. In this paper, we provide an overview of electrochemical-thermal-mechanical models for battery system understanding and designing.

25 ENERGY STORAGE↗

DOE OSTI2015

Model-Based Design and Integration of Large Li-ion Battery Systems

This presentation introduces physics-based models of batteries and software toolsets, including those developed by the U.S. Department of Energy's (DOE) Computer-Aided Engineering for Electric-Drive Vehicle Batteries Program (CAEBAT). The presentation highlights achievements and gaps in model-based tools for materials-to-systems design, lifetime prediction and control.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2013

Gearbox and Drivetrain Models to Study Dynamic Effects of Modern Wind Turbines: Preprint

Wind turbine drivetrains consist of components that directly convert kinetic energy from the wind to electrical energy. Guaranteeing robust and reliable drivetrain designs is therefore important to minimize turbine downtime. Current drivetrain models often lack the ability to model both the impacts of electrical transients as well as wind turbulence and shear in one package. In this work, thecapability of the FAST wind turbine computer-aided engineering tool, developed by the National Renewable Energy Laboratory, is enhanced through integration of a dynamic model of the drivetrain. The dynamic drivetrain model is built using Simscape in the MATLAB/Simulink environment and incorporates detailed electrical generator models. This model can be used in the future to test advanced controlschemes to extend life of the gearbox.

17 WIND ENERGY↗

DOE OSTI2016

Battery Pack Thermal Design

This presentation describes the thermal design of battery packs at the National Renewable Energy Laboratory. A battery thermal management system essential for xEVs for both normal operation during daily driving (achieving life and performance) and off-normal operation during abuse conditions (achieving safety). The battery thermal management system needs to be optimized with the right tools for the lowest cost. Experimental tools such as NREL's isothermal battery calorimeter, thermal imaging, and heat transfer setups are needed. Thermal models and computer-aided engineering tools are useful for robust designs. During abuse conditions, designs should prevent cell-to-cell propagation in a module/pack (i.e., keep the fire small and manageable). NREL's battery ISC device can be used for evaluating the robustness of a module/pack to cell-to-cell propagation.

25 ENERGY STORAGE↗