Virtual Battery Simulation Tools for Engineering

Transcription

1 Virtual Battery Simulation Tools for Engineering Electrical and thermal modeling of lithium-ion batteries Ari Hentunen Aalto University School of Electrical Engineering, Espoo, Finland

2 Simulation Tools for Engineering Electrical and Thermal Characterization of Batteries User need Battery characterization Users Dynamic simulations of xevs Battery performance assessment at end-of-life Battery emulation at powertrain testbed Drive train developers Battery system developers Vehicle software developers Objectives SOC range of interest: 1 1 % Voltage error less than 2 % Temperature error less than 2 C Computationally lightweight Automated model extraction Experiments with a cell, module, or pack Offline time-series I U T data Evaluation of capacity and impedance at end-of-life Virtual Battery Simulation Tools for Engineering 2/17 A. Hentunen

3 Battery Model Two Submodels Inputs i b Battery current T a Ambient temperature s Q h State of health (capacity) i b s Q h s P h Electrical model s Q u oc u b P gh s P h State of health (power) Outputs s Q State of charge u b Battery voltage u oc Open-circuit voltage P gh Generated heat P dh Dissipated heat T Battery temperature T a Thermal model T P dh Virtual Battery Simulation Tools for Engineering 3/17 A. Hentunen

4 Electrical Model Equivalent Circuit Inputs Current and temperature External Prediction of usable capacity, SOC, OCV, self-discharge, and generated heat Equivalent circuit Prediction of terminal voltage Remark Resistances and capacitances are functions of the SOC, temperature, rate, current direction, and SOH R + u oc + u 1 + u R 1 u b i b u oc R R n C n C 1 Battery voltage Battery current Open-circuit voltage Ohmic resistance Dynamic resistances Dynamic capacitances + u n R n C n ib + u b Virtual Battery Simulation Tools for Engineering 4/17 A. Hentunen

5 Electrical Characterization Test 6 8 Current [A] Current [A] Current Current Exp voltage Exp temperature 35 Exp voltage Exp temperature Voltage [V] Temperature [ C] Voltage [V] Temperature [ C]

6 Exp voltage Exp current Time [min] 1 8 Model Extraction Procedure 1 4 OCV 4 Exp voltage Exp current 16 Voltage[V] Voltage [V] Voltage [V] Current [A] 1 8 Current [A] Resistance[mΩ] 3 OCV SOC [%] SOC [%] R1 R2 R + u1 + u R1 R + uoc C1 + un Rn + Cn ub ib Time [min] Capacitance[kF] 1 C1 5 C SOC [%] Experiments Parameter maps Parameterized model 1 Ari Hentunen, Teemu Lehmuspelto, and Jussi Suomela. Time-Domain Parameter Extraction Method for Thévenin Equivalent Circuit Battery Models. In: IEEE Transactions on Energy Conversion 29.3 (14), pp Virtual Battery Simulation Tools for Engineering 6/17 A. Hentunen

7 Heat Generation P gh = ( ) u oc u b ib + i b T u i b Battery current oc = P } {{ } } {{ T ph +P Sh u b Battery voltage } polarization heat u entropic heat oc Open-circuit voltage T Temperature u oc / T-mapping can be obtained from literature or from an entropy change characterization test 2 Entropic heat can be either positive or negative At charge sustaining applications entropic heat can be neglected due to zero net effect 2 K. Jalkanen, T. Aho, and K. Vuorilehto. Entropy change effects on the thermal behavior of a LiFePO4/graphite lithium-ion cell at different states of charge. In: Journal of Power Sources 243 (13), pp Virtual Battery Simulation Tools for Engineering 7/17 A. Hentunen

8 Thermal Model Equivalent Circuit Inputs Generated heat and ambient temperature Equivalent circuit Prediction of surface temperature and dissipated heat Remark Resistances and capacitances have constant values Pgh + T1 P gh T a P dh + θ1 P2 + θ2 Pn + θn Pdh R1 C1 + T2 R2 C2 Generated heat Ambient temperature + Tn Rn Cn T Battery surface temperature θn R n C n Dissipated heat Temperature rises Thermal resistances Thermal capacitances + Ta Virtual Battery Simulation Tools for Engineering 8/17 A. Hentunen

9 Thermal Characterization Test Current 6 Current Temperature Current [A] Current [A] Temperature [ C] Time [min] Equivalent-circuit parameters can be extracted from the thermal characterization test Virtual Battery Simulation Tools for Engineering 9/17 A. Hentunen

10 Aging Effect End-of-life (EOL) criteria for a battery 3 Capacity fade of %, resulting in 8 % of the original capacity Power fade of %, resulting in 8 % of the original power and 25 % increase in impedance These effects can be included into the usable capacity and equivalent circuit resistances to assess electrical and thermal performance at end-of-life conditions 3 Electric Vehicle Battery Test Procedures Manual, Revision 2. United States Advanced Battery Consortium. Southfield, MI, Virtual Battery Simulation Tools for Engineering 1/17 A. Hentunen

11 Battery Specification: Kokam SLPB Ah (NMC), 26 V Module Table : Specification of the battery. Property Unit Cell Cell Module Nominal capacity Ah Nominal voltage V Max voltage V Cut-off voltage V Charge current A Discharge current A Energy kwh Nominal temperature C Max temp. (charge) C Max temp. (discharge) C Cycle 8 % DOD Virtual Battery Simulation Tools for Engineering 11/17 A. Hentunen

12 Model Validation Thermal Characterization Test 26.5 Exp voltage Sim voltage 26.5 Exp voltage Sim voltage Voltage [V] Voltage [V] Time [min] Exp temperature Sim temperature Amb temperature Exp temperature Sim temperature Amb temperature Temperature [ C] Temperature [ C] Time [min]

13 Model Validation Constant-Current 25 C / (C/3) Current [A] Current [A] Current Current Exp Sim without entropic heat Sim with entropic heat Voltage [V] Temperature[ C] Exp voltage Sim voltage

14 Performance Assessment Real-World Duty-Cycle / 25 C Power [kw] 1 1 Power Time [s] Exp Sim without entropic heat Sim with entropic heat Temperature[ C]

15 Performance Assessment at End-of-Life Real-World Duty-Cycle 28 Exp with SOH(P&Q) = 1 % Sim with SOH(P&Q) = 1 % Sim with SOH(P&Q) = 8 % Voltage [V] Exp with SOH(P&Q) = 1 % Sim with SOH(P&Q) = 1 % Sim with SOH(P&Q) = 8 % Temperature[ C]

16 Conclusion Electrical and thermal battery model was presented and parameterized for a Li-ion battery module with NMC chemistry Automated parameter extraction from experimental I U T time-series data Cell-, module-, or pack-level experiments Electrical and thermal performance can be assessed Cooling requirement can be assessed Performance degradation due to aging can be evaluated Entropic heat generation is significant for charge depleting (CD) cycles Heat generation and dissipation must be balanced Battery module performance was evaluated for a specific duty-cyle Thermal performance was poor Cooling would be needed Model can also be used in conjunction with a battery cycler to emulate a battery in full-scale hardware-in-the-loop testing to accelerate powertrain development Virtual Battery Simulation Tools for Engineering 16/17 A. Hentunen

17 Summary Key findings of the research A systematic method for empirical electrical and thermal characterization of a battery cell, module, and pack was developed, in which also performance degradation due to aging can be evaluated. Benefits for participating companies Knowledge and methods for battery-system development and battery performance assessment. New business opportunities Battery characterization and emulation services aimed for machine manufacturers and battery-system integrators. Virtual Battery Simulation Tools for Engineering 17/17 A. Hentunen