Battery Cooling for Electrified Vehicles Gaetan Damblanc Product Manager

Transcription

1 Battery Cooling for Electrified Vehicles Gaetan Damblanc Product Manager Unestricted Siemens AG 2017 Realize innovation.

2 Agenda Industry challenges A wide length scale solution Battery pack cooling simulations Conclusion Page 2

3 Car industry mutation Source: Nextgreencar.com Page 3

4 Today s industry challenges One of the key elements of automotive electrification is Electric Storage Technology. Multiple cell chemistries are available. Choice is a trade-off according to the application According to the targeted applications, many technical issues exist : Cell selection depending on the usage Sizing of the battery pack Thermal management of the pack Lifetime, impact of aging on system performances Page 4

5 Siemens Battery Modelling Expertise Wide Length Scale Solution Micro-structure Electrochemistry Virtually test SEM produced electrode geometry Conduct design studies on new concepts Virtual Cell Design and Test Detailed geometrical representation coupled to performance model to build cell digital twin Battery pack design Flow, thermal & Electrochemistry analysis of complex power systems Study detailed spatial effects at cell, module & pack level Overall System Design LMS Amesim Interface Module & Pack 3D analyses with complex power train system models Page 5

6 CAE for li-ion battery packs Regulating the operating temperature of a battery pack is essential because it affects: The performance (power and capacity) Charge acceptance (during regenerative braking) Life span Safety Vehicle operating and maintenance expenses. CAE and particularly CFD can be used to design and size suitable cooling systems to ensure: Uniform temperature across cells and modules Maintain pack temperature in safety range Analyse cooling system efficiency Ensure minimum parasitic weight Main input How much heat the pack/cells are generating? Page 6

7 One goal Two approaches Traditional approach Cell/Pack heat Q is applied uniformly on cell or pack geometry Cell/Pack heat is applied as a function of time or temperature Cell/Pack heat generation cannot be affected by cooling system which in turns cannot affect the cell/pack performance STAR-CCM+ BSM approach The Electrochemical cell performance model is coupled to the CFD solver Current field is distributed on the current collector through Poisson s equation Computes 3D distribution of Voltage, SOC, or Heat Internal cell temperature, but also external environmental conditions affects interactively the cell performance model Q +Tab Q 11 Q 12 Q 21 Q ij Q -Tab Q nm Page 7

8 Single cell example between traditional and BSM approach 4C Discharge 100% SOC to 0% SOC 4 C 8 C Page 8

9 Design exploration on a battery module Simulate a battery module thermal performance Using pouch cell previously characterised in Battery Design Studio Build-up a module with: Full cell design (Electrode Stack, Tabs) Casing Electrical insulation pad Cell Connectors Cooling system Analyse pack behaviour under a drive cycle Cell Pouch Cell NMC/LMO- Graphite Module Cell Assembly Nominal Voltage Battery Module Specifications Nominal Capacity Energy Dimensions Cooling Width and Liquid - Length are Ethylene variables Glycol Height: 25 cm C2H6O2 14S2P 50V 30Ahr 1.5kWhr Electrical Insultation Multi-purpose Silicon Sponge Rubber Page 9

10 BSM complete workflow BDS STAR-CCM+ BSM CHARACTERISE SHARE BUILD MODULE Cell Design Models Share cell data 3D cell 3D module TBM file ANALYSE Dedicated Post-Proc COMPUTE Electro/Thermal simulation MESH Automated Page 10

11 Design exploration on a battery module Cell characterisation Create a digital twin: Cell geometry and dimensions are extracted through x-ray images or dissection These geometrical data are then input in BDS Typically for large pack CFD simulation, the cell performance is computed with an Eq Circuit Model These models are simple to configure and require simple test data called Pulse Power Characterisation test HPPC TEST Page 11

12 Design exploration on a battery module Page 12

13 Design exploration on a battery module Temperature field at the end of a 600s drive cycle simulation Page 13

14 Design exploration on a battery module Page 14

15 Design exploration on a battery module Page 15

16 Design exploration on a battery module Module weight is 22 kg including the cooling plates, heat fins, pads, and casing Page 16

17 Design exploration on a battery module Objective - Optimize the battery module design to minimise the module weight Design Exploration Inputs: Cooling system geometry Design Exploration Objectives: Single Objective: Minimise Module weight Constraints: Temperature difference in module <= 3 o C Pressure drops in channels < Pa Page 17

18 Multiple Design Exploration BDS STAR-CCM+ BSM STAR-CCM+ BSM BUILD MODULE CHARACTERISE MESH 3D cell SHARE 3D module Cell Design Models Share cell data 3D cell Automated Electro/Thermal simulation COMPUTE BUILD MODULEANALYSE 3D module Dedicated Post-Proc TBM file ANALYSE Dedicated Post-Proc DESIGN COMPUTE EXPLORATION Electro/Thermal simulation Automates the CAD generation, BSM preprocessing, solving and post-processing MESH Automated HEEDS MDO Discover Better Design, Faster Page 18

19 Design exploration on a battery module Feasible Designs Infeasible Designs Page 19

20 Design exploration on a battery module - Results BASELINE DESIGN IMPROVED DESIGN 35% weight reduction 30% improvement in temperature uniformity Page 20

21 STAR-CCM+ BSM Amesim Co-simulation Amesim Integrate detailed 3D analysis in 1D system simulation Focus on the design of the battery module while integrating it in a full xev drive line Apply realistic drive cycle to the 3D module with realistic power demand and coolant conditions profiles STAR- CCM+ BSM Page 21

22 Summary STAR-CCM+ BSM provides the modelling capabilities to simulate the complex coupled interaction between the cell s electrochemical performance and the thermal environment. The design of the battery pack and the ability to dissipate heat is key to ensure a uniform temperature distribution while having the lightest parasitic weight due to the cooling system. The ability to automate the simulation set-up and computations brings a significant gain in productivity Module thermal management system design exploration within a week Choice of a set of feasible designs Page 22