Overview of research

Transcription

1 MICDE-TARDEC Faculty Workshop Overview of research Wei Lu Mechanical Engineering University of Michigan, Ann Arbor September 15,

2 Overall of Research Areas Joining of dissimilar materials, modeling of intermetallics formation (Fe/Al) with effect of temperature history, interfacial conditions, and strain states, FSW processing. Dynamic impact and fretting wear of structures and materials rod grid Calculated wear map shows wear rate as a function of the grid-to-rod gap size and the frequency of the excitation force. Dynamic impact and fretting wear 2

3 Overall of Research Areas Coupled wear and multi-mechanics modeling Approach to couple fretting wear and creep simulation, addressing the drastic different time scales of vibration (short time scale) and creep (long time scale). Coupled wear and oxide growth. Oxide layer Oxide growth + wear Wear profile 3

4 Overall of Research Areas Coupled wear, creep and fracture Modeling of hydride formation Modelling and experiments of wear of fabrics Design of wear resistant fibers and coating Hyrdride formation In-situ wear observation Multi-scale simulation 4

5 Battery Research Areas Multi-scale/Multi-physics Modeling and Simulation macroscale (finite element methods, phase field models) microscale (ab initio, classical and reactive molecular dynamics) emphasis on battery optimization, degradation analysis and management Material Characterization, Cell Fabrication, and Testing material and parameter characterization (TEM, SEM, AFM, XPS, XRD etc.) cell fabrication and diverse performance testing (cycling, EIS, thermal, dissolution, degradation, etc.) New material development (e.g. Li metal, Black Phosphorus, Si/CNT) Smart Battery Management System and Control optimization for battery system operation as well as design 5

6 capacity utilization (%) Example: Modeling of Grain Structures and Diffusion R=5 μm C-rate normalized s gb /v p Grain boundary dramatically improves capacity utilization! 6

7 radius (10-6 m) Coupled Electrochemical-Mechanical Degradation Fracture Map current density (A/m 2 ) 65% SOC Developed tools that can predict mechanical and electrochemical behaviors at the particle, cell, and pack level, so that battery performance can be predicted accurately. Developed tools to predict mechanical failure such as fracture and delamination: it can be used in battery design for more robust cells as well as guiding the cell applications to reduce related failures. Developed module-level stress analysis tool that considers cell expansion and face pressure, which can be used in pack design. 7

8 normal traction (GPa) Multi-scale Analysis opening binder 50% SOC graphite 30 chains 65% SOC 40 chains separation (Å) Atomistic Scale 1. damage initiation: maximum stress (T max ) normal : 300 Mpa, shear : 50 Mpa 2. damage evolution: fracture energy (G c ) normal : 0.45 J/m 2 shear : J/m 2 Continuum Scale 8

9 Machine Learning in Material Modeling and Discovery Ragone plots from neural network calculations and FEM simulations. Each FEM dot represents a finite element simulation. Five of the design variables are kept constant while the C-rate ch anges from 0.5 C to 3 C. 9

10 Cell & Pack Capacity, Reliability and Safety Optimizations Face pressure analysis has provided packing design criteria for better battery performance. An appropriate applied pressure can reduce capacity degradation relative to no pressure. measurement simulation electrical and test leads interior view Bitrode Controller PC Instron Controller PC constant thickness/pressure HPPC protocol Identified source of performance gain through experimentally directed modeling. Optimized pressure on cells for maximum performance boost. 10

11 T(T-T 0 ) ( C) voltage (V) Cell & Pack Capacity, Reliability and Safety Optimizations Thermal analysis provided better management strategy of large format cells considering environmental, cycling, and C-rate effects. Revealed unique local characteristics from each heat source. Identified the effect of temperature and its gradient on cell/pack performance and degradation. ambient temperature: 20 C, 5C RTD/Thermal Camera Measurement Electro- Thermal Model voltage C-rate Ambient Temperature Cycling effect ambient temperature time (s) simulation validation IR camera RTD sensors measurement 11

12 A Comprehensive Degradation Model Solvent oxidation SL o + H + (or SL + ) + e EC + e (graphite) EC EC + EC O 2 CO CH 2 2 O 2 CO + C 2 H 4 EC + EC + e (graphite) O 2 CO CH 2 2 O 2 CO + C 2 H 4 O 2 CO CH 2 2 O 2 CO + 2Li + Li + O 2 CO CH 2 2 O 2 CO Li + side Side reaction rates limited by the SEI layer: i e i Anode side * side Cathode Coupling of electrochemical, chemical, mechanical, thermal, and transport processes X. Lin, J. Park, L. Liu, Y. Lee, A.M. Sastry and W. Lu, A comprehensive capacity fade model and analysis for Li-ion batteries, Journal of the Electrochemical Society, 160, A1701-A1710,

13 Application: SOC Swing Window SOC swing window has provided useful information on battery health state, and suggested optimal charge/discharge strategy evolving with aging of the battery. 13

14 Application: Battery Health Optimization Balanced health and energy density design can significantly reduce the reserved capacity, and thereby reduce the battery cost and weight. Set energy density requirement Keep the power density requirement Conduct battery health optimization 60% 20% Parameters Symbol average Cathode particle radius Cathode thickness Cathode porosity Cathode conductivity Anode particle radius 1. power density requirement: 2200 W/kg 2. energy density requirement : 86 W hr/kg optimized for health rp_pos [mm] L_pos [mm] Epsl_pos Ks_pos [S/m] After rp_neg [mm] optimization, battery degradation is reduced 3 times. Anode thickness L_neg [mm] Anode porosity epsl_neg Mass ratio mass_ratio degradation 60% 20% 14

15 Application: Smart Battery Management System Physics-based model electrochemical, chemical, mechanical, thermal, and transport processes equivalent circuit-based mimic Current control system Future control system Heat generation/flow, lithium plating, manganese dissolution, gas generation, SEI layer growth Reduced-order highfidelity versions of these models, suitable for controls 15