The MC Method Ryan Harty and Steve Mathison Honda R&D Americas, - PowerPoint PPT Presentation

An Advanced Fueling Algorithm The MC Method Ryan Harty and Steve Mathison Honda R&D Americas, Inc

2 Outline Need for Advanced Fueling Algorithm What An Advanced Algorithm Should Be… MC Method Development Determining Tank Specific MC From Test Data Applying MC Method Testing MC Method at Powertech Summary and Conclusions

3 Outline Need for Advanced Fueling Algorithm What An Advanced Algorithm Should Be… MC Method Development Determining Tank Specific MC From Test Data Applying MC Method Testing MC Method at Powertech Summary and Conclusions

4 Need for an advanced fueling algorithm A fueling standard should work well for all tank systems, in all conditions, for any station configuration, in all ambient conditions, all the time.  Guarantee safe fueling in all conditions  Guarantee fast fueling in a wide range of conditions Real customers using real stations need great station performance

5 Need for an advanced fueling algorithm Station Operating Many Envelope Current No Cooling Some Precooling Temperature Stations and Current Fueling Forklift Bus Stations Standard Stations (No Precooling) Advanced Algorithm 0C Most of the Precooled -20C Stations in US Today Some of the Future -40C Stations in the US Tomorrow 25MPa 35MPa 50MPa 70MPa Fill Pressure

6 Need for an advanced fueling algorithm Station Operating Many Envelope Current SAE J2601 No Cooling Some Type D35 Precooling Temperature Stations and Current Fueling Forklift CAFCP Bus Stations Standard Stations Rev6.1 (No Precooling) Advanced Algorithm SAE J2601 0C Type C35 No Standard Most of the Precooled -20C SAE J2601 SAE J2601 Stations in US Today Type B35 Type B70 No Standard SAE J2601 SAE J2601 Some of the Future -40C Type A35 Type A70 Stations in the US Tomorrow 25MPa 35MPa 50MPa 70MPa Fill Pressure Do the existing fill protocols always give good fueling performance to the maximum capability of the tank system?

7 Need for an advanced fueling algorithm Station Operating Envelope SAE J2601 No Cooling Type D35 Precooling Temperature Current Fueling CAFCP Standard Rev6.1 Advanced Algorithm Advanced Algorithm SAE J2601 0C Type C35 Target: Safe, -20C SAE J2601 SAE J2601 High Quality, Type B35 Type B70 Fast Fills at SAE J2601 SAE J2601 All Stations -40C Type A35 Type A70 25MPa 35MPa 50MPa 70MPa Fill Pressure Maximize the possible performance at all conditions.

8 Outline Need for Advanced Fueling Algorithm What An Advanced Algorithm Should Be… MC Method Development Determining Tank Specific MC From Test Data Applying MC Method Testing MC Method at Powertech Summary and Conclusions

9 An advanced fueling algorithm… -should be based on the actual conditions of a hydrogen station  enthalpy of delivered hydrogen (any condition) -should be applicable for all initial fill temperature, pressure  internal energy in the tank (any condition) -should be based on the actual capabilities of a tank system  actual volume, NWP  real thermodynamic characteristics  hot soak, cold soak based on test results and conditions expected by the OEM and the Station -should make use of available technology to communicate these parameters to the station.  ID-Fill? IRDA? RFID? etc

10 An advanced fueling algorithm… Photo courtesy of Air Products and Chemicals Inc Knowable by the Vehicle: Knowable by the Station: -NWP -Ambient Temperature -Tank Volume -Initial Tank Pressure -Max Hot Soak Temp -Enthalpy of Fill -Max Cold Soak Temp -Precooler Output -Tank Thermodynamics -Starting Pressure -Other? -Ending Pressure

11 An advanced fueling algorithm… Data Toss (Static Communication – RFID, Barcode, HVAS, ID-Fill, etc. Not integrated to ECU) Photo courtesy of Air Products and Chemicals Inc Knowable by the Vehicle: Knowable by the Station: -NWP -Ambient Temperature -Tank Volume -Initial Tank Pressure -Max Hot Soak Temp -Enthalpy of Fill -Max Cold Soak Temp -Precooler Output -Tank Thermodynamics -Starting Pressure -Other? -Ending Pressure

12 Outline Need for Advanced Fueling Algorithm What An Advanced Algorithm Should Be… MC Method Development Determining Tank Specific MC From Test Data Applying MC Method Testing MC Method at Powertech Summary and Conclusions

13 MC Method Development A control volume analysis yields several insights.    m h m u Q Only source ( T , P ) ( T , P ) i i cv cv  ?   of energy m h ( m u m u ) Q  ( T , P ) ( T , P ) ( T , P )   i i 2 2 1 1    m u m h Q ( , ) ( , )  T P T P 1 1 i i u 2 m 2 Since internal energy, u, is a state property, if we know the density, and the h i =enthalpy at the inlet (at T,P,dm) pressure, for any given m 1 =initial mass of hydrogen in the control volume amount of heat transfer, Q, u 1 =initial internal energy in the control volume m 2 =final mass of hydrogen in the control volume we can directly calculate u 2 =final internal energy in the control volume the temperature. Q=heat transferred across the control volume boundary Model based on Inlet Enthalpy and Internal Energy

14 MC Method Development A control volume analysis yields several insights.    m h m u Q 0 Only source ( T , P ) ( T , P ) i i cv cv 0 0    of energy m h ( m u m u ) Q  ( T , P ) ( T , P ) ( T , P )   i i 2 2 1 1    m u m h Q 0 ( , ) ( , )  T P T P 1 1 i i u 2 m 2 Density, T adiabatic If we study the case of Q=0, the adiabatic condition, then u 2 =u adiabatic , and since u is a h i =enthalpy at the inlet (at T,P,dm) state property, for a given m 1 =initial mass of hydrogen in the control volume density and pressure we u 1 =initial internal energy in the control volume m 2 =final mass of hydrogen in the control volume can directly calculate the u 2 =final internal energy in the control volume adiabatic temperature. Q=heat transferred across the control volume boundary   m u ( m m ) h Density=target density at end-of-fill ( , ) ( , ) T P T P i  1 1 2 1 1 1 u ( T , P ) T adiabatic =adiabatic temperature if no heat was Adiabatic m 2 transferred T adiabatic depends only on station enthalpy and initial tank conditions (Temp, Press).

15 MC Method Development Now let heat transfer occur again, and let the tank hydrogen in the tank cool to     ? ( ) some final state, T final . Q m C T T 2 v adiabatic final X Density, T adiabatic to T final Density is constant as the tank cools. The heat transfer can be m 2 =final mass of hydrogen in the control volume described as: Q=heat transferred across the control volume boundary Density=target density at end-of-fill   Q m C ( T T ) 1 T adiabatic =adiabatic temperature if no heat was transferred 2 v adiabatic final T final =end of fill temperature C v =specific heat capacity of hydrogen at constant volume

16 MC Method Development Use of T adiabatic to Calculate Q: Fill from 2MPa T vs Time for 35MPa Type 3 Fill at 25C start at 25C using 160 T Adiabatic no precooling 140 Tank Temp (C), Pressure (MPa)     ? Q m C ( T T ) 120 2 v adiabatic final T Final (3min) 100 The total heat 80 T Final (30min) transfer from the 60 hydrogen can be 40 End of Fill Time = 3min described by T 20 T Adiabatic T adiabatic to T final 0 0 600 1200 1800 2400 3000 3600 Time (s) T adiabatic is maximum possible temperature in the tank.

17 MC Method Development Q The temperature distribution inside the liner is very T H2Inside complex. T CFRPOuter T LinerWall T LinerW/CFRP m 2 Individual layer T Environment mass, specific heat capacity of liner, tank valve Q Environment assy, carbon fiber, epoxy, etc Actual Tank Model 1D or 2D Heat Transfer Temp Distribution Complex Time Domain All Time Q Environment Need to solve Heat Capacitance Each material M, C

18 MC Method Development Q The temperature distribution inside the liner is very T H2Inside complex. T CFRPOuter Simplify T LinerWall T LinerW/CFRP m 2 Individual layer T Environment mass, specific heat capacity of liner, tank valve Q Environment assy, carbon fiber, epoxy, etc Actual Tank Model Model 1D or 2D Heat Transfer Lumped Heat Capacitance Temp Distribution Complex Time Domain All Time Q Environment Need to solve Heat Capacitance Each material M, C

19 MC Method Development Characteristic Volume Q The temperature Q (Mathematical entity – Not distribution inside actual mass or volume) the liner is very T H2Inside T H2Inside complex. T CFRPOuter Simplify T T LinerWall =T final = Characteristic Volume T LinerW/CFRP m 2 M cv m 2 T Environment Individual layer T Environment Combined mass mass, specific heat capacity of and specific heat =0 liner, tank valve Q Environment capacity = MC assy, carbon Q Environment fiber, epoxy, etc Adiabatic Actual Tank Model Boundary Model 1D or 2D Heat Transfer Lumped Heat Capacitance Temp Distribution Complex T=T H2Inside Time Domain All Time 3 min + D t (final condition) Q Environment Need to solve 0 Heat Capacitance Each material M, C Combined MC