电池寿命分析

NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, operated by the Alliance for Sustainable Energy, LLC. 26th International Battery Seminar & Exhibit Fort Lauderdale, FL March 16-19, 2009 Kandler Smith Kandler.Smith@nrel.gov Tony Markel Tony.Markel@nrel.gov Ahmad Pesaran Ahmad.Pesaran@nrel.gov NREL/PR-540-45048 PHEV Battery Trade-Off Study and Standby Thermal Control 22National Renewable Energy Laboratory Innovation for Our Energy Future Overview • Motivation for PHEV battery trade-off analysis • Battery life model – Calendar life vs. cycle life: Complex interdependency – An empirical model capturing major degradation factors (temperature, time, # cycles, ΔDOD*, voltage) • Battery life/cost interactions – Lowest cost system that meets technical requirements – Life sensitivity to different temperatures • Battery standby thermal management – Concept – Vehicle-battery thermal interactions – Benefits of temperature management • Conclusions – Future test needs * DOD = depth of discharge 3 USABC PHEV Battery Goals Characteristics at EOL (End of Life) High Power/Energy Ratio Battery High Energy/Power Ratio Battery Reference Equivalent Electric Range miles 10 40 Peak Pulse Discharge Power - 2 Sec / 10 Sec kW 50 / 45 46 / 38 Peak Regen Pulse Power (10 sec) kW 30 25 Available Energy for CD (Charge Depleting) Mode, 10 kW Rate kWh 3.4 11.6 Available Energy for CS (Charge Sustaining) Mode kWh 0.5 0.3 Minimum Round-trip Energy Efficiency (USABC HEV Cycle) % 90 90 Cold cranking power at -30°C, 2 sec - 3 Pulses kW 7 7 CD Life / Discharge Throughput Cycles/MWh 5,000 / 17 5,000 / 58 CS HEV Cycle Life, 50 Wh Profile Cycles 300,000 300,000 Calendar Life, 35°C year 15 15 Maximum System Weight kg 60 120 Maximum System Volume Liter 40 80 Maximum Operating Voltage Vdc 400 400 Minimum Operating Voltage Vdc >0.55 x Vmax >0.55 x Vmax Maximum Self-discharge Wh/day 50 50 System Recharge Rate at 30°C kW 1.4 (120V/15A) 1.4 (120V/15A) Unassisted Operating & Charging Temperature Range °C -30 to +52 -30 to +52 Survival Temperature Range °C -46 to +66 -46 to +66 Maximum System Production Price @ 100k units/yr $ $1,700 $3,400 Requirements of End of Life Energy Storage Systems for PHEVs National Renewable Energy Laboratory Innovation for Our Energy Future 4 USABC PHEV Battery Goals Characteristics at EOL (End of Life) High Power/Energy Ratio Battery High Energy/Power Ratio Battery Reference Equivalent Electric Range miles 10 40 Peak Pulse Discharge Power - 2 Sec / 10 Sec kW 50 / 45 46 / 38 Peak Regen Pulse Power (10 sec) kW 30 25 Available Energy for CD (Charge Depleting) Mode, 10 kW Rate kWh 3.4 11.6 Available Energy for CS (Charge Sustaining) Mode kWh 0.5 0.3 Minimum Round-trip Energy Efficiency (USABC HEV Cycle) % 90 90 Cold cranking power at -30°C, 2 sec - 3 Pulses kW 7 7 CD Life / Discharge Throughput Cycles/MWh 5,000 / 17 5,000 / 58 CS HEV Cycle Life, 50 Wh Profile Cycles 300,000 300,000 Calendar Life, 35°C year 15 15 Maximum System Weight kg 60 120 Maximum System Volume Liter 40 80 Maximum Operating Voltage Vdc 400 400 Minimum Operating Voltage Vdc >0.55 x Vmax >0.55 x Vmax Maximum Self-discharge Wh/day 50 50 System Recharge Rate at 30°C kW 1.4 (120V/15A) 1.4 (120V/15A) Unassisted Operating & Charging Temperature Range °C -30 to +52 -30 to +52 Survival Temperature Range °C -46 to +66 -46 to +66 Maximum System Production Price @ 100k units/yr $ $1,700 $3,400 Requirements of End of Life Energy Storage Systems for PHEVs National Renewable Energy Laboratory Innovation for Our Energy Future Available Energy = 11.6 kWh SOC Swing = 70% Total EOL Energy = 16.6 kWh Fade over Life = 20% Total BOL Energy = 20.7 kWh Calendar Life at 35°C = 15 Years System Price = $3,400 Max Weight = 120 kg Max Volume = 80 L 5 Optimization with vehicle simulations under realistic driving cycles and environments PHEV Battery Design Optimization Design/size PHEV batteries to meet USABC technical goals/requirements at minimum cost. Source: INL, LBNL Battery Life Source: VARTA Battery Cost Battery Performance Life prediction represents greatest uncertainty. Complex dependency on t1/2, t, # cycles, T, V, ΔDOD National Renewable Energy Laboratory Innovation for Our Energy Future 66National Renewable Energy Laboratory Innovation for Our Energy Future Motivation: Minimize Battery Cost, Maximize Life How? 0) Select a high-quality, low-cost cell. 1) Size battery appropriately so as not to overstress/over-cycle, but with minimum cost and mass 1) Accelerated calendar & cycle life testing 2) Accurate life and DOD predictive models 2) Minimize time spent at high temperatures 1) Standby thermal management (vehicle parked!) 2) Active thermal management (vehicle driving) 3) Proper electrical management, control design : System design Component design/ selection 77National Renewable Energy Laboratory Innovation for Our Energy Future How Can We Predict Battery Life? Cycling Fade • Poorly understood • Typical t or N dependency • Often correlated log(# cycles) with ΔDOD or log(ΔDOD) 0 0.2 0.4 0.6 1 1.05 1.1 1.15 1.2 1.25 1.3 1.35 Time (years) R el at iv e R es is ta nc e 30 40 47.5 55 Calendar Life Study at various T (°C) Calendar (Storage) Fade • Relatively well established & understood • Typical t1/2 time dependency • Arrhenius relation describes T dependency Source: V. Battaglia (LBNL), 2008 Li fe (# c yc le s) Life (# cycles) Source: John C. Hall (Boeing), IECEC, 2006. Source: Christian Rosenkranz (JCS/Varta) EVS-20 ΔDOD Δ D O D 88National Renewable Energy Laboratory Innovation for Our Energy Future Accelerated Cycle Life Tests Are Not Always Conservative! • Li-ion – high-voltage, nonaqueous chemistry – calendar life effect important • Real-time tests necessary for proper extrapolation of accelerated results Source: John C. Hall, IECEC, 2006. (Boeing, Li batteries for a GEO Satellite) Real Time Test (1 cyc./day) Accelerated Test (4 cyc./day) ΔDOD fraction Li fe (# c yc le s) 99National Renewable Energy Laboratory Innovation for Our Energy Future Our Objectives for Battery Life Modeling Develop a power and energy degradation model that — 1. Uses both accelerated and real-time calendar and cycle life data as inputs. 2. Is mathematically consistent with all calendar and cycle life empirical data. 3. Is extendable to arbitrary usage scenarios (i.e., it is predictive). 1010National Renewable Energy Laboratory Innovation for Our Energy Future Source: J.P.Christopersen, J. Electrochem. Society, 2006. Cycling has been shown to suppress impedance growth. Effect of an unintended full discharge and charge Commercial LiCoO2 cells stored at 25oC; DC resistance measured with 1 pulse/day Impedance Growth Mechanisms: Complex Calendar and Cycling Dependency 1111National Renewable Energy Laboratory Innovation for Our Energy Future Impedance Growth Mechanisms: Complex Calendar and Cycling Dependency SEM Images: John C. Hall, IECEC, 2006. Cell stored at 0oC NCA chemistry: Different types of electrode surface film layers can grow. (1) “Electrolyte film” (2) “Solid film” Cell cycled 1 cycle/day at 80% DOD Electrolyte film* • grows during storage α t1/2 • suppressed by cycling Solid film • grows only with cycling α t or N *Often called Solid-Electrolyte Interphase (SEI) layer 12 Curve-fit at 51% ΔDOD: a1 = 1.00001e-4 Ω/day1/2 a2 = 5.70972e-7 Ω/cyc R2 = 0.9684 12National Renewable Energy Laboratory Innovation for Our Energy Future Impedance (R): Cycling at Various ΔDODs Fitting t1/2 and N Components (Note: For 1 cycle/day, N = t) 4.0 EoCV Data: John C. Hall, IECEC, 2006. • Simple model fit to cycling test data: Boeing GEO satellite application, NCA chemistry • Model includes t1/2 (~storage) and N (~cycling) component. R = a1 t1/2 + a2 N 13 Curve-fit at 51% ΔDOD: a1 = 1.00001e-4 Ω/day1/2 a2 = 5.70972e-7 Ω/cyc R2 = 0.9684 13National Renewable Energy Laboratory Innovation for Our Energy Future Impedance (R): Cycling at Various ΔDODs Fitting t1/2 and N Components (Note: For 1 cycle/day, N = t) ΔDOD a1 (Ω/day1/2) a2 (Ω/cyc) R2 68% 0.98245e-4 9.54812e-7 0.9667 51% 1.00001e-4 5.70972e-7 0.9684 34% 1.02414e-4 0.988878e-7 0.94928 17% 1.26352e-4 -7.53354e-7 0.9174 4.0 EoCV Data: John C. Hall, IECEC, 2006. • Simple model fit to cycling test data: Boeing GEO satellite application, NCA chemistry • Model includes t1/2 (~storage) and N (~cycling) component. R = a1 t1/2 + a2 N 1414National Renewable Energy Laboratory Innovation for Our Energy Future R2 = 0`.9943 R2 = 0.9836 High t1/2 resistance growth on storage is suppressed by cycling. High DOD cycling grows resistance α N. Low DOD cycling reduces resistance α N. Additional models are fit to describe a1 and a2 dependence on ΔDOD. a2 < 0 not physically realistic. An equally statistically significant fit can be obtained enforcing constraint a2 > 0. x a2 / a1 = c0 + c1 (ΔDOD) a1 = b0 + b1 (1 – ΔDOD)b2 Impedance (R): Cycling at Various ΔDODs Capturing Parameter Dependencies on ΔDOD R = a1 t1/2 + a2 N 1515National Renewable Energy Laboratory Innovation for Our Energy Future 0% ΔDOD (storage) 68% ΔDOD 51% ΔDOD 34% ΔDOD 17% ΔDOD Fit to data Extrapolated using model R = a1 t1/2 + a2 N a1 = b0 + b1 (1 – ΔDOD)b2 a2 / a1 = max[0, c0 + c1 (ΔDOD)] Distinctly different trajectories result from storage, severe cycling and mild cycling.4.0 EoCV Data: John C. Hall, IECEC, 2006. Impedance: Cycling at Various ΔDODs Example Model Projections 100% ΔDOD 16 R = a1 t1/2 + a2,t t + a2,N N a2,t = a2 (1 - αN) a2,N = a2 αN αN = 0.285, R2 = 0.9488 16National Renewable Energy Laboratory Innovation for Our Energy Future Impedance: Multiple Cycles per Day [1] Corrected data from J.C. Hall et al., 208th ECS Mtg., Oct. 16-21, Los Angeles, CA. [2] Data from J.C. Hall et. al., 4th IECEC, June 26-29, San Diego, CA. Dependence on t1/2, N model overpredicts effect of accelerated cycling. (not used) R = a1 t1/2 + a2 N Dependence on t1/2, t, N model predicts accelerated and real-time cycling much better. 1717National Renewable Energy Laboratory Innovation for Our Energy Future Impedance: Voltage and Temperature Acceleration • Increased impedance growth due to elevated voltage & temperature fit using Tafel & Arrhenius-type equations. • Dedicated lab experiments required to fully decouple voltage-ΔDOD relationship. a1 = a1,ref k1 exp(α1F/RT x V) a2 = a2,ref k2 exp(α2F/RT x V) • This work assumes values for k1 & α1. • Activation energies, Ea1 and Ea2, are taken from similar chemistry. k1 = k1,ref exp(-Ea1 x (T-1 - Tref-1) /R) k2 = k2,ref exp(-Ea2 x (T-1 - Tref-1) / R) 18National Renewable Energy Laboratory Innovation for Our Energy Future Capacity Fade: Calendar (storage) and Cycling Effects Qsites = e0 + e1 x (a2,t t + a2,N N) Q = min( QLi, Qsites ) Capacity Loss During Storage Loss of cyclable Li Capacity Loss During Cycling Isolation of active sites a1 and a2 capture temperature, ΔDOD, and voltage dependencies (previous slides). • 4 cycle/day - cycling stress significant. • 1 cycle/day - voltage stress significant. 3.7V, 20oC storage data: John C. Hall, IECEC, 2006. 1 cyc/day, 20oC data: John C. Hall, IECEC, 2006. Q = Relative Capacity QLi = d0 + d1 x (a1 t1/2) 1919National Renewable Energy Laboratory Innovation for Our Energy Future Life Model Summary (equations & coefficients) Impedance Growth Model • Temperature • Voltage • ΔDOD • Calendar Storage (t1/2 term) • Cycling (t & N terms) Capacity Fade Model • Temperature • Voltage • ΔDOD • Calendar Storage (Li loss) • Cycling (Site loss) From impedance growth model Reasonably fits available data Actual interactions of degradation mechanisms may be more complex. QLi = d0 + d1 x (a1 t1/2) Qsites = e0 + e1 x (a2,t t + a2,N N) a1 = a1,ref k1 exp(α1F/RT x V) a2 = a2,ref k2 exp(α2F/RT x V) k1 = k1,ref exp(-Ea1 x (T-1 - Tref-1) /R) k2 = k2,ref exp(-Ea2 x (T-1 - Tref-1) / R) a2,t = a2 (1 - αN) a2,N = a2 αN a1 = b0 + b1 (1 – ΔDOD)b2 a2 / a1 = max[0, c0 + c1 (ΔDOD)] Q = min( QLi, Qsites ) R = a1 t1/2 + a2,t t + a2,N N 2020National Renewable Energy Laboratory Innovation for Our Energy Future Life/Cost Trade-Offs: Approach • Life model adjusted slightly to reflect experience with present-day PHEV battery technology (NCA chemistry). • Cost model from previous work: • Manufacturing cost of a complete pack at high volume production • Requirements from USABC/DOE • Energy: 3.4 kWh PHEV10; 11.6 kWh PHEV40 • CD Cycle Life: 5000 CD cycles • Calendar Life: 15 years at 35oC • Too aggressive for present-day technology • Instead used 10 years at 30oC for analysis (next two slides) • Questions: • What ΔDOD & P/E meet life at minimum cost? • Which controls life? Calendar or cycle life? • What environmental parameters cause greatest life sensitivity? $/pack = 11.1*kW + 224.1*kWh + 4.53*BSF + 340 $3500 $2860 $2600 Detailed Model: 3 NCA $3680$42903.511.46 $3020$35104.78.46 $2660$31205.86.88 Simple Model: 1.2 $=11*kW+224 *kWh+680 Detailed Model: 3 NCM P/ENominal Energy (kWh) $3500 $2860 $2600 Detailed Model: 3 NCA $3680$42903.511.46 $3020$35104.78.46 $2660$31205.86.88 Simple Model: 1.2 $=11*kW+224 *kWh+680 Detailed Model: 3 NCM P/ENominal Energy (kWh) NCA - Nickel Cobalt Alumina; NCM- Nickel Cobalt Manganese 1. Graham, R. et al. “Comparing the Benefits and Impacts of Hybrid Electric Vehicle Options,” Electric Power Research Institute (EPRI), 2001. 2. Simpson, A., “Cost Benefit Analysis of Plug-In Hybrid Electric Vehicle Technology,” 22nd International Electric Vehicle Symposium, Yokohama, Japan, Oct. 2006. 3. “Cost Assessment for Plug-In Hybrid Vehicles,” TIAX LLC, Oct. 2007. BSF = Battery Size Factor 2121National Renewable Energy Laboratory Innovation for Our Energy Future Life/Cost Trade-Offs: Usable ΔDOD PHEV10 battery sized for 10 years at 30oC, 1 cycle/day* Largest mass Pay for energy Smallest mass Pay for power Lowest cost • Optimal P/E ratio (~15 hr-1) yields lowest cost battery • Too much P/E is preferred to too little P/E - small increase in cost - reduces mass • Expanding ΔDOD window - reduces total battery energy & mass - requires higher P/E to meet power requirements at low SOC * using 3.9 EoCV (90% SOCmax) 2222National Renewable Energy Laboratory Innovation for Our Energy Future Life/Cost Trade-Offs: Temperature Sensitivity PHEV10 battery sized for 10 years at 25oC, 30oC, & 35oC* • Temperature exposure drastically impacts system size necessary to meet goals at end of life. 25oC: 70% to 80% ΔDOD is usable 35oC: 50% to 65% ΔDOD is usable • Modifying life requirements from 10 years at 25oC to 10 years at 35oC increases battery cost by > $500. * 1 cycle/day, 3.9 EoCV (90% SOCmax) Current Li-ion technology can require 30% to 70% excess power to last 15 years. Advanced Li-Ion technologies still could require 15% to 30% excess power to last 15 years. 2323National Renewable Energy Laboratory Innovation for Our Energy Future • Assume vehicle is always parked (storage calendar life effect only). • Typical Meteorological Year (TMY) hour-by-hour geographic dataset used to provide ambient conditions. • Assume Tbattery = Tambient (Realistic? No. Solar loading on vehicle cabin & battery will cause even more power loss.) Phoenix 44oC max, 24oC avg 0oC The Case for Thermal Control of PHEV Batteries Storage at elevated temperatures responsible for significant impedance growth; most passenger vehicles are parked >90% of the time. Houston 39oC max, 20oC avg Minneapolis 37oC max, 8oC avg 10 oC 20oC 30oC Thermal control of PHEV batteries is needed even during standby. 40oC 2424National Renewable Energy Laboratory Innovation for Our Energy Future Study of PHEV Battery Standby Thermal Control • Investigate the technical and economic merits of various thermal control strategies during standby – Experiments using NREL PHEV Test Bed and other vehicles – Vehicle thermal modeling with various solar and ambient loads Qsolar Tamb T1 T2 T3 T4 Battery Environment Cabin Image: Volvo 2525National Renewable Energy Laboratory Innovation for Our Energy Future On Sunny Days, Solar Warming of Cabin Can Cause Battery Temperature to Be Much Hotter than Ambient Qsolar Tamb T1 T2 T3 T4 Battery Environment Cabin Rooftop pyranometer & RTD NREL PHEV Test Bed instrumented to correlate solar radiation & ambient temperature with battery temperature Battery Pack RTD Vehicle thermal model extracted for geographic scenario analysis 0 20 40 60 80 100 120 -20 0 20 40 60 Time (hr) Te m pe ra tu re ( ° C ) Ambient Cabin Battery 0 20 40 60 80 100 120 0 200 400 600 800 Time (hr) S ol ar R ad ia tio n (W /m 2 ) 0 20 40 60 80 100 120 -20 0 20 40 Time (hr) Te m pe ra tu re ( ° C ) Cabin above Ambient Battery above Ambient Image: Volvo 2626National Renewable Energy Laboratory Innovation for Our Energy Future Model: Solar Warming of Cabin (and its effect on battery temperature) Is Important for Predicting Battery Degradation PHEV10 – Power loss after 15 years Degradation predictions with and without effects of vehicle solar loading. Current Li-ion technology Phoenix Houston Minneapolis 2727National Renewable Energy Laboratory Innovation for Our Energy Future Eliminating Peak Battery Temperatures (e.g., battery insulation, active cooling, reducing solar load) Can Greatly Improve Battery Life