The Grand Challenge of Advanced Batteries Kev Adjemian, Ph.D. Division Director, Clean Energy & Transportation Boryann (Bor Yann) Liaw, Ph.D. Department Manager, Energy Storage & Advanced Vehicles Idaho National Laboratory March 22, 2017 IBSE 2017 meeting, Fort Lauderdale, FL, USA
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Idaho National Laboratory Research Programs Research Development Demonstration Deployment 3
Fraction of Institutions Effort & Competence National Labs Solve Unique Classes of Science and Technology Challenges Emphasis on early discovery; focus on solutions with smaller technical complexity Ideally suited for highcomplexity, multi-disciplinary, long-time horizon challenges that span the fundamental to applied R&D Market needs & competitive pressure focus R&D on near-term solutions Basic Science Understanding how the world works Basic Science To advance applications Applied Science Engineering Serial Production 4
Vehicles, Energy Storage & Infrastructure Development of Next-Generation Low Cost / Reliable Batteries: Leverage unique INL capabilities to lead Performance Science Foundation: Battery Testing Center & Advanced Vehicle Testing Growth via strong partnerships with: o DOE-EERE (USABC) o Automotive OEMs o Battery Developers Impact: Enabling / accelerating next gen low cost, durable, reliable and safe batteries Performance Science: Half-Cell to Vehicle & Pack Half-Cell / Coin Pouch / Cell Pack Battery Test Center Non-destructive Battery Evaluation Lab (NOBEL) Electric Vehicle Infrastructure Lab (EVIL) Vehicle
Performance, durability, reliability and safety in a proper perspective Risk assessment & management Policies & regulations Protocols & procedures Control, management & auditing Manuals Installation Operation System Device Environmental Factors: Mechanical Electrical Thermal Chemical Education, training & enforcement Human Factors: Duty cycle & schedule Frequency Preference Habit.. Durability Reliability Safety Catastrophic Events Abuse Tolerance
Safety relies on proper cell design and deep understanding of cell performance Materials selection & processing Electrode architecture Cell balance Manufacturing quality System control and management Preventive measures
Design-Build-Test Paradigm Forward-looking design principles Insufficient to enable failure mode and effect analysis (FMEA) Pouch / Cell Half-Cell / Coin Pack Sources: various literature documents
Engineering Approach Durability Reliability Safety FMEA Quantitative Analysis Diagnostics Prognostics
+ + + Vo Vo Vo _ R 1 + R 1 + R 1 + Load Source Load Source Load Source C (= /f c2r 2) R 2 _ C (= /f c2r 2) _ R 2 C (= /f c2r 2) _ R 2 I I I + Vo _ R 1 + Load Source C (= /f c2r 2) _ R 2 I + Vo _ R 1 + Load Source C (= /f c2r 2) _ R 2 I 4.2 4.0 3.8 3.6 3.4 3.2 3.0 100% OCV Fresh cell 60 cycle 120 cycle 180 cycle OCV Fresh cell 60 cycle 120 cycle 180 cycle 240 cycle 300 cycle 600 cycle 1200 cycle 1800 cycle 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Roadmap: Diagnostics & Prognostics to Validation Field Testing Representative usage schedule Laboratory Testing Simulation Tools Data collection Performance model Small scale tests Specific protocols Intensive High Normal Mild Benign 40 Pulses / min Driving Pulse Driving Event 0 80 Peak Power (kw) Driving Cycle Driving Cycle Profile Vehicle Usage Profile Vehicle Usage Event Pattern recognition Duty Pulse Duty Cycle Duty Cycle Profile Duty Event Usage (Pattern) Performance + Vo _ R 1 + Load ~ Source C (= /f c2r 2) _ R 2 Diagnostic model ~ ~ I ~ ~ Prognostic model ~ Cell Voltage, V Performance & life Cell count 40 35 30 25 20 15 10 SOC 5 Battery capacity Cell variability 0 0.042 0.07 0.098 0.126 0.154 0.182 Polarization resistance ( Ah) 100% 95% 90% 85% 80% 75% Cell count 0 100 200 300 400 30 25 20 15 10 5 Under-discharge Number of cycles 0 285 291 297 303 309 Capacity @ C/5 (mah) Loss of Active Material Under-charge In-depth understanding in performance simulation to achieve reliable & safe operation of battery systems
Cell Variability Origins Chemistry: Redox Couple Voltage Crystal Structure Morphology Architecture Theoretical Capacity Intrinsic (Thermodynamics) Rate capability Cycle life Electrode Processing (Kinetics) Cell Manufacturing Δ PERFORMANCE Δ Rate Capability Δ Weight Packaging Δ Capacity Cell Balance Δ Resistance Cell specific capacity Nominal capacity Polarization resistance
Cell Variability Cell design metrics capacity Cell DCR + cutoff condition = SOC EOC W = 8.89±0.15 g (±1.69%) Q 2 = 295.5±5.5 mah (±1.9%) RCV = 3.880±0.018V (±0.45%) Q 5 = 298.6±4.7 mah (±1.6%)
EOD to Capacity Int. J. Energy Res. 34 (2010) 216 231 J. Power Sources 186 (2009) 500 507 With the same test protocol and procedure, we do not really strictly control the test conditions
Capacity Ration (mah/%soc) Int. J. Energy Res. 2010; 34:216 231 Specific capacity: mah/g Loading variations: g/%soc Capacity ration: mah/%soc
Impacts from DCR on SOC Int. J. Energy Res. 2010; 34:216 231
Impacts from DCR on Capacity Int. J. Energy Res. 2010; 34:216 231
High Fidelity of Cell Model and Simulation Capacity ration DCR Int. J. Energy Res. 34 (2010) 216 231 J. Power Sources 186 (2009) 500 507
Every cell in the pack can be modeled precisely Int. J. Energy Res. 2010; 34:216 231
Cell variability in aging & capacity fading Even with the best state-of-the-art cell design and manufacturing, variability in endurance remains as an issue that impacts durability, reliability and safety Cell Count Cell Count 12 10 8 6 4 2 0 2.82 2.84 2.86 2.88 2.9 Measured C/5 Capacity (Ah) 15 10 2863.09 ± 11.35 mah (± 0.40%) 5 0 60 65 70 75 80 Measured DC Resistance (mohms) 66.30 ± 2.45 mω (± 3.7%) Normalized Capacity (%) 100 90 80 70 60 50 Commercial 2.8 Ah G LCO + NMC 18650 cells Cell 1 Cell 2 Cell 3 Cell 4 Cell 5 40 0 100 200 300 400 500 600 Cycle # 6% spread
Quantify Cell Variability over Aging 51 commercial G LCO + NMC 2.8 Ah 18650 cells Normalized Capacity (%) 100 90 80 70 60 50 40 0 100 200 300 400 500 600 Cycle # Dubarry and Liaw, Assessing Cell-To-Cell Variations in Commercial Batteries, 218 th ECS, Las Vegas, B2- #326: Battery Safety and Abuse Tolerance, 2010 M. Dubarry et al. Internat. J. Energy Res. 34 (2010) 216-231 Cell 1 Cell 2 Cell 3 Cell 4 Cell 5 6% spread Normalized Capacity (%) -Im(Z) 100 95 90 85 80 Thermodynamics Linear fade of low-rate capacity Cell 1 Cell 2 Cell 3 Cell 4 Cell 5 2% spread 75 0 100 200 300 400 500 600 Cycle # 0.04 0.02 0 Resistance build-up Initial -0.02 Cell 1 Cell 2-0.04 Cell 3 Kinetics Cell 4 Cell 5-0.06 0.04 0.06 0.08 0.1 0.12 0.14 Re(Z) Capacity Loss(%) 60 50 40 30 20 10 Kinetics LAM dene LLI Cell #1 Cell #2 Cell #3 Cell #4 Cell #5 High rate Low rate 0 0 100 200 300 400 500 600 Cycle # Performance LLI (%) LAM dene (%) Base 22.5 14 Under 25.5 (ä) 16 (ä) Over 20.5 (æ) 13 (æ) Batch 22.5 +3-2 14 +2-1 Avg ra o 1.6 1 LAM dene =f(lli)
State-of-Charge (SOC) Engineering definition (e-soc): Coulomb counting (Ah-counting) Thermodynamic definition (t-soc): Electrode
Thermodynamic definition (t-soc): Cell At equilibrium,
Pack SOC Determination
Accommodating Cell Variability and Degradation V = f(soc) curve evolution with LLI
Conclusion Grand challenges: Cell variability SOC determination Quantitative failure mode and effect analysis (FMEA) to achieve desired durability, reliability and safety Safety by Design Cause-and-consequence analysis (causality) for accurate and precise prediction and management strategy to enable reliability and safety