Math Enabled Innovation

Math EnabledInnovationDr. Paul E. KrajewskiDirector, Vehicle Systems Research LabGM Global Research & DevelopmentJ. T. Wang, Bahram Khalighi, Yilu Zhang

AGENDAConnected LivingFuel Economy CO2– Aero– Electric Vehicles– Lightweight MaterialsPersonal SecurityFuture / Summary

CONNECTED LIVINGMobile-cellular subscriptionsapproaching 7B, the number ofpeople on the earth3B use the InternetFacebook has over 1.4 billion activeusers globally; 85% are mobile users90% of the world’s data has beencreated in the last two years –2.5 quintillion bytes of datacreated every day!

CUSTOMER EXPECTATIONSBring their digital life into their vehicleBring their vehicle into their digital life

WIRELESS CHARGINGPhone overheating in vehicle cabins using inductive wireless charging led tounacceptable phone charging performanceArm RestVertical ImplementationICS Bin

PASSIVE COOLINGPhoneAir gap for convectivecoolingPOWER ModuleArmrest Passive cooling incorporates an air-gap to facilitate the dissipation of trapped heatfrom the interface between the phone and charging surface CFD tools like Fluent were used to design bumps and spacing

ACTIVE THERMAL MANAGEMENTEvaporatorAir flow to ICS binICS BinICS Bin2 mm air gapPhone temperatureAir from the HVAC module routed to the phone to maintain it within operational temperatures.

RESULTS Significant improvement in phone charge timesduring extreme hot and cold. Increased customer acceptance and satisfactionby not compromising charging performance. Enabled GM to be the first OEM to provide anintegrated dual protocol (WPC and PMAPowermat) wireless charging system (inductive) invehicles.Phone Temperature

2025 CO2 AND FUEL ECONOMY elTailpipeCO2(g/KM)FuelEconomy(mpg)B-segment CarCompact CarChevrolet Sonic7861.1D-segment CarMid-Size CarBuick Regal8854.9E-segment CarFull-Size CarCadillac XTS10248.0C-segment TruckSmall SUVChevrolet Equinox10247.5D-segment TruckMid-Size CUVCadillac SRX11243.4FSFF TruckLarge PUChevy Silverado15033.0

ELECTRIFICATION

BATTERY THERMAL MANAGEMENT Temperature impacts battery performance and life.Li-Ion batteries in hybrid and EV vehicles undergo constant charging anddischarging.Active battery cooling is necessary to maintain the cell temperatures withinallowable temperature limits (25oC 35oC)Peak durability and reliability requires DT 5oC within the cell and across the packChevy VoltBattery pack11

BATTERY PACK DESIGNElectrochemistryHeat TransferFluid FlowMaterial PropertiesDesign

CAEBATx sep SeparatorPositiveElectrodeCurrent Collector (Al)L NegativeElectrodeCurrent Collector (Cu)-e-ecs(r)LixC6cs,erLi cecs,ercs(r)LiyCoO2ElectrolyteComputer-aided software design tools for hybrid/electric andelectric vehicle (HEV/EV) batteries to reduce cost, improveperformance and increase life.Partners GM : End user requirements,verification/validation, project management ANSYS : Software dev. and commercialization ESim : Cell level sub models, life model NREL : Technical monitorFunding provided by DOE Vehicle Technologies Program .

RESULTS Cooling design implemented on 2016 Chevy Volt Enabled more uniform temperature Lower power requirements for cooling2011 Chevy Volt2016 Chevy VoltTotal pressure drop 28.4 kPaTotal pressure drop 12.4 kPa

AERODYNAMICS

DRAG REDUCTION - CONVENTIONALMETHODParametric sensitivity Approximate a vehicle shape with manydesign parameters, such as angle, length,curvatures Calculate the sensitivity for each designvariablesN design parametersN 1 CFD Flow solutions16 Incremental. Takes too long. Doesn’t account for multipleinteractions

DRAG REDUCTION - ADJOINT METHODPrecept (Cd 0.19) CFD provides diagnostic information for drag reduction. CFD is not prescriptive on shape sensitivities nor direction of the shape change. Adjoint optimization method provides aerodynamic design information for both shapesensitivity and direction for shape improvements.

ADJOINT METHODOLOGYCFD Flow Solver All the surface mesh (x,y,z)locations are the designparameters Large number of designparameters 0.5 to 1 millionAdjoint SolverShapeChangeCalculateShape SensitivityN design parameters1 CFD Flow solution1 Adjoint solution18

ADJOINT EXAMPLE RESULTSRed: push outwardBlue: push inwardRaising the cowl area to providea smooth and continuous flowaccelerationLowering the roofline toreduce the frontal areaBoat-tailing near the rearfender for a largerpressure recoveryReduce thestagnation regionSmooth transitionnear the front fasciaCorner rounding alongthe sharp cornerRecessing the A-pillar toreduce the transversepressure gradientThe modified shape reduced the drag by 4%19

ADJOINT SUMMARY Currently using to give guidance to engineers and designers Seeing reduction in windtunnel and CFD iterations Future integration with other MDO approaches

LIGHTWEIGHT MATERIALS

MULTI-SCALE MODELING OF MATERIALS ostructuralAtomisticChemistryMg flowPhysicsElectronicPhilosophynmlog(Length scale)mmmmm

ICME:RD3GENERATION STEELSIntegrated Computational Materials EngineeringQ&PMed. Mn (10wt%)MathWorks tools used to measureretained austenite volume fraction withstrain and parse data

PERSONAL SECURITY

CRASH TEST DUMMIES

CRASH DUMMY BASED SIMULATIONCrash ModelINDIRECT INJURYMEASURES:CrashSimulationsDummy Response Head injury criterion Neck forces Chest deflection Femur load Tibia index

HUMAN-LIKE CRASH TEST/SIMULATIONTOOLSReduced Biofidelity

GLOBAL HUMAN BODY MODELS CONSORTIUMGHBMC Co-founded by GM in 2006, GHBMC is an international consortium ofautomakers & suppliers working with research institutes and governmentagencies to advance human body modeling technologies for crash simulations.MEMBERS OBJECTIVE: Toconsolidate world-wideHBM R&D effort into asingle global effortsSPONSOR MISSION: To developand maintain highfidelity FE humanbody models forcrash simulationsPARTICIPANTS

GHBMC DEVELOPMENT STATUS Developed 10 models Three more detailed pedestrian models (M50-P,F05-P, and M95-P) to be delivered in 2017F05-OM50-ODetailedM95-O F05-OS M50-OSM95-OS 6YO-PSF05-PS M50-PS M95-PSSimplifiedMathWorks tools used for crashsensing algorithm developmentUNBELTEDPASSENGERBELTEDPASSENGER

FUTURE: A HUMAN BODY MODEL BASED VEHICLEDEVELOPMENT PROCESSCrash ModelCrashSimulationsHuman Body ResponseTISSUE LEVEL INJURY ASSESSMENT: Skull fracture Brain Injury Vertebra fracture Spinal cord injury Rib fracture Major artery injury Lung injury Liver injury Pelvis fracture Femur fracture

FUTURE: INFORM FIRST RESPONDERS AND ER24

VEHICLE PROGNOSIS

MOTIVATIONEverything wears out over timeCustomer’s life is disrupted, when his/her vehicle needsrepair unexpectedlyOnStarTM Proactive Alert – A new customer care service– Alert before failure happens– Transform an emergency repair to planned maintenance– Enhance ownership experience - a delight to customers

PROGNOSTIC ALGORITHM DEVELOPMENTPhysical-model based algorithm generation: Study failure modes - FMEA Model physics of failure Generate fault signatures and failureprecursors Develop prognostics algorithm Validate concept on benches and testvehiclesLead Acid Battery(Plate Surface Scanning Electron Microscopy)Electric MotorMathWorks tools used for algorithmdevelopment and data analysis34

PROGNOSTIC ALGORITHM DEVELOPMENT1.2Fuzzy Set LongPercentage0.26 10.160.80.120.60.080.40.040.203 00.10.20.30.40.50.60.7Crank Time To 200 RPM (s)0.80.901Statistical analysis0.850.50.80.450.75Crank atio ()0.4RCrankTimeForConventionalVehicles (Second)Big-data based algorithm validation: Collect data from 1M vehicles Analyze warranty return parts Correlate algorithm outputs withengineering assessment Calibrate algorithm 01/0601/2602/1503/07Date03/2704/1605/06Time series analysis3505/2612/17Membership Grade0.24

VALIDATIONReplacement Date80RcRho 1GYRG36

LIDAR DATA

ARTIFICIAL INTELLIGENCE AND LEARNING

SUMMARY New mathematical models and methodologies are driving automotiveinnovation in a variety of areas. These approaches have reduced the time to bring innovative solutions tothe market. Themes Model Integration Collaboration The future of mobility will rely on continued breakthroughs in Model integration

IHS/CSM Segment NHTSA Segment Representative Model Tailpipe CO 2 (g/KM) Fuel Economy (mpg) B-segment Car Compact Car Chevrolet Sonic 78 61.1 D-segment Car Mid-Size Car Buick Regal 88 54.9 E-segment Car Full-Size Car Cadillac XTS 102 48.0 C-segment Truck Small SUV Chevrolet Equinox 102 47.5 D-segment Truck Mid-Size CUV Ca