A Total Li-Ion Battery Simulation Solution

Lewis Collins, Director of Software Development ANSYS Convergence Regional Conference Santa Clara, CA April 21, 2015 1

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Collins / Convergence

Apr 2015

Advantages

Engaged in electrochemical systems R&D for >15 years • Primarily batteries and fuel cells

Industry Solutions Value-Added Services Global Support

Unequalled Depth Unparalleled Breadth Comprehensive Multiphysics Engineered Scalability Adaptive Architecture SDPD Vision Company Strength Independence

Confidence from usage in dozens of industries, hundreds of applications, thousands of organizations 2

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Apr 2015

Ongoing Collaborations Scale-Bridging Models for Electrochemical Power Sources • U.S. Office of Naval Research, 2005• ANSYS, NRL, universities • Metrology and resolved modeling of electrodes • Upscaling methods for cell, pack, and system

Computer-Aided Engineering of Electric Drive Vehicle Batteries (CAEBAT) • U.S. DoE Vehicle Technologies Office, 2011• ANSYS, GM, ESim, NREL, universities • Improve CAE tools for battery cells and packs (usability, validation, interoperability)

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Apr 2015

Battery Considerations in Electronics In mobile devices, battery is connected with key design issues Power management (battery-to-chip)

Pressure on noise margins Signal and power integrity

Thermal Electromagnetic interference (EMI)

Hardware/software integration 4

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Apr 2015

Demand Trend for Mobile Power Battery has become a limiting factor Driving ultra-low power design methodologies

(for a specified form factor)

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Battery is Key to Vehicle Electrification EV Everywhere Grand Challenge goal: make plug-in electric vehicles as affordable and convenient as today’s gasoline-powered vehicles by 2022

Image credit: “FY 2013 Annual Progress Report”, Energy Storage R&D, Vehicle Technologies Office, U.S. Department of Energy 6

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Engineering Challenges Cost Performance (power and energy density) Durability and service life (in disparate environments) Safety (tolerance to abusive conditions)

Thermal

Complex multi-scale, multi-physics system

Electrical

Fluid

Rapidly evolving materials and design concepts Chemical

Existing software tools not “tuned” for batteries

Molecular

Particle

Electrode

Cell

Need to account for interconnection 7

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Apr 2015

Pack

System

Methods Toolkit Electrochemistry sub-models Homogenization (over particles, electrode layers)

Field simulation Electrode  cell  module scales e.g. CFD: fluid, thermal, chemical, electrical

Cosimulation

Extraction

System simulation Module  pack  vehicle scales Lumped-parameter models, controls

Instantiation

Reduced-order models (ROM) Small number of (linear or nonlinear) state eqns

Expansion

dx  Ax  Bu dt y  Cx  Du

Multidisciplinary design optimization 8

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Model-Based Systems Engineering Requirements and Specifications

Functional

System Validation

Allocations System Functional & Architectural Design

Sub-System Integ. & Verification

Sub-System Design

Detailed Architecture Architecture

Component Integration & Verification

Mechanical Electrical Software

Detailed Design & Optimization

Simplorer

Fluent

Maxwell 9

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Mechanical

Balancing Speed and Resolution New techniques can reduce cost while preserving a sufficiently accurate approximation of the responses of interest “Selective use” of CFD, tailored to the unique objectives cost (log scale)

Field Simulation (e.g., CFD) (orders of magnitude)

With ROM, cosimulation System Simulation Spreadsheet/ Handbook Calcs fidelity 10

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Apr 2015

Cell Model: Field Simulation Geometry: built-in parametric templates • Inputs available in Workbench Parameter Manager and DesignXplorer

Meshing: also templated, based on best practices

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Apr 2015

Custom Geometry is Easily Handled Traditional approach supports maximum design creativity • SpaceClaim, DesignModeler, or CAD Interfaces • Assumption: lithium transport is perpendicular to local electrode plane

Image credits: www.apple.com/macbook/design

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Apr 2015

Electro-Chemical-Thermal Simulation Battery Module a standard feature of Fluent Single or multiple cells

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Apr 2015

Multiscale Approach No need to resolve individual electrode layers with the mesh User-defined scalars represent electrical potentials F+ , FChemical species are not explicit solution variables • Sub-grid model may track lithium ion concentration R1

R2

C1

C2

 

Rs

I (t )



V (t )

Vocv ( soc )

q, j

I (t )



Φ- , Φ+ , T Φ-

Φ+

Ref: G-H Kim et al, “Multi-Domain Modeling of Lithium-Ion Batteries Encompassing Multi-Physics in Varied length Scales” J. Electrochem. Soc. 158(8) A955-A969 (2011). 14

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Apr 2015

Cell Model: Productivity Aids “Single-point” (0-D) analysis option, from the same interface

Auto-merge separately-created cell and adjacent-structure models Auto-fit properties from test data file • e.g. from calorimeter testing

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Apr 2015

Cell Model Validation Logical step for system simulation • Verification of material properties, electrochemistry models, stoichiometry assumptions, etc.

Representative results from CAEBAT project:

HPPC @ 25 degC, 30% DOD

Images on this slide courtesy of General Motors LLC 16

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Apr 2015

System Simulation Templates and Scripts Goal: automate workflow while preserving tool generality Exploit periodicity or symmetry when possible Unit-Model Template • Reusable building-block

Script

• Define based on thermal and electrical connectivity

• Reusable procedure for a specific pack architecture

• One-time manual creation using standard Simplorer components

• Automate connections, layout, post-solution statistics • One-time optional programming task using highly-accessible Python language

• Store to User Library

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Automotive Examples Application

PHEV

BEV

15 Ah pouch

3 Ah cylindrical

288

7104

8 x (12S3P)

16 x (6S74P)

Cooling configuration (cells/channel)

Totally parallel, 2

Series within module, 444

Unit definition (# cells)

6

2

Cell type # cells Electrical configuration

Image credits Left: General Motors LLC Right: Ricardo Strategic Consulting 18

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Apr 2015

System Hierarchy Starts with a Single Cell Applicable to both rectangular and cylindrical types • Form-factor effects incorporated into lumped coefficients Electrical • Equivalent-circuit model • Coulomb-counter  (SOC = state of charge)

Two-way Coupling

Thermal • Includes adjacent part of fluid cooling channel

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Apr 2015

Drag-and-drop components

Unit Model (Domain Decomposition) Created once and stored to Simplorer library file (Shapes and layout for reference, not part of model)

+

–

c1

f

c2

c3

f

c4

c5

f

+

c1

c6

– – Electrical 20

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– Thermal Apr 2015

– Hydraulic

f

c2

Module Model Exploit periodicity, instancing templated models from library

Group (row)

2P Unit 2S3P Unit

2S3P Unit

... (6x)

2S3P Unit

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... (37x)

2S3P Unit

– Electrical 21

2P Unit

Collins / Convergence

– Thermal Apr 2015

– Hydraulic

2P Unit

2P Unit

Pack Model Ready for coupling with BMS or full-vehicle models

Outer Case

AMBIENT

12S3P Module

12S3P Module

... (8x)

Thermal Mgmt System

12S3P Module

12S3P Module

6S74P Module

LOAD

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6S74P Module

... (16x)

LOAD

– Electrical 22

Outer Case

AMBIENT

Collins / Convergence

– Thermal Apr 2015

– Hydraulic

Thermal Mgmt System

6S74P Module

6S74P Module

Process Automation Script-generated form • Enter 3 integers • Select unit from library

Click on any instance To drill into hierarchy

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Apr 2015

Validation GM prototype 24-cell module • LG 24-Ah pouch cells (LMO/NCA cathode) • Steady-state liquid cooling • 32 thermocouples Progressive model comparison: • “Brute force” CFD model • Lumped-parameter system model – Some inputs guided by CFD results

• CFD-derived ROM Progressive case complexity: • Symmetric pulse charge/discharge • Simulated drive-cycle load profile 24

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Apr 2015

Typical Comparison: Middle Cell Cooling fin

Top View

Foam spacer

Measurement

No data

No data

CFD Prediction

Coolant out

High-frequency ±3.5C pulse charge/discharge @50% SOC Maximum difference between simulation and measurement < 1 C 25

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Apr 2015

Coolant in

Typical Comparison: System Model Volume-average cell temperature versus time – Simplorer prediction – averaged measurements (other colors = individual measured locations on cell)

1 C

60 minutes (5 x US06 drive cycle + cooled rest, SOC 0.9-0.2) 26

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Apr 2015

Typical Comparison: ROM versus CFD Excellent thermal replication of cells in ordinary operation ROM execution several orders of magnitude faster than CFD

Ref: X. Hu and S. Stanton, “A Complete Li-Ion Battery Simulation Model,“ SAE 2014-01-1842 27

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Apr 2015

Thermal Stress Temperatures transfer to Mechanical for analysis at any scale

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Apr 2015

Plug-In Hybrid Software Plug-and-play concept: several interfaces to support native, in-house, and third-party tool integration • E.g., user-defined function (UDF) for custom electrochemistry models • Other Tools can include micromechanics, cell-design apps, system simulators, battery cost models, …

UDF

Fluent Battery Model

Mechanical

ANSYS Workbench

Simplorer Other Tools 29

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Apr 2015

CAD

Functional Mockup Interface (FMI) Maintained by the non-profit Modelica Association Supports simulation model exchange and tool coupling, including hardware-in-the-loop (HiL) Functional Mockup Unit (FMU) = portable package containing • Interface description (XML schema) • Model functionality (C code – source or binary) Supported by ANSYS Simplorer, SCADE (and >60 other tools) Tool

FMU

Solver

Model

Master

Slave FMI Wrapper

Model Solver

Ref: T. Blochwitz, et.al., “The Functional Mockup Interface for Tool independent Exchange of Simulation Models”, Modelica Association, Proceedings of the 2011 Modelica Conference, modelica.org 30

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Apr 2015

Improving Battery Safety ANSYS is working with experts on simulation of abuse scenarios Common geometry

(image courtesy MIT)

Extensions for abuse kinetics Structural Simulation

Electro-Chemical-Thermal Damage translation

Quarter-symmetric indentation (image courtesy NREL)

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Apr 2015

Current and temperature after internal short

Design Optimization Using Workbench Parameter Manager and DesignXplorer, parametric studies can explore battery trade-offs • Robust design, service life and safety improvements, …

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Apr 2015

Battery Management Systems Battery requires complex control system for • Cell SOC balancing (maximize lithium utilization) • Charging protocols and dynamic power-limiting (maximize battery life) • Safety isolation and cell protection • Integration with power electronics and other systems Image courtesy of General Motors LLC

A model-based development environment for embedded software

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Apr 2015

Supporting Materials Innovation Next frontier for simulation: efficient coupling with materials-science and -processing (ICME) • Closing the loop on the real-world chain of dependencies  • Example issues: – Optimal particle size, morphology, binder/conductor mixture, etc. – New cathode / anode / electrolyte materials, beyond lithium-ion, etc.

• ANSYS collaborates with molecular-modeling software leaders

Atomistic

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Particles

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Electrodes

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Cell

Apr 2015

Pack

Vehicle

Reconstructing Microstructure Geometry To create a representative volume element (RVE) model

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Apr 2015

Resolved Electrode Approach RVE considers more-fundamental physics while limiting cost

(Image courtesy R. Kee, Colorado School of Mines) 36

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Apr 2015

Summary Advanced batteries present a challenging application for the ANSYS vision of Simulation-Driven Product Development Key gaps involve domain interfaces and transitions • Multiscale methods for electrode  battery  system • Cyber-physical (software  hardware) system optimization • Materials & manufacturing process  in-service performance ANSYS is addressing these challenges using several technologies, to support battery innovation

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Chevrolet Bolt - image courtesy of General Motors LLC

Apr 2015

Acknowledgments ANSYS contributors: Erik Ferguson, Xiao Hu, Genong Li, Shaoping Li, Sandeep Sovani, Dimitri Tselepidakis This material is based in part upon work supported by the Alliance for Sustainable Energy LLC, Management and Operating Contractor for the National Renewable Energy Laboratory, under Award Number ZCI-1-40497-01, and by the Office of Naval Research, under Award Number N00014-05-1-0339. This presentation includes an account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. 38

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Apr 2015