Practice presentation 25


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  • Introduction : consists of definition and background of the problems Objective : the goal of the research Problem definitions : define the problems Modeling : Propulsion system model Solution : How to solve the problems Result: Simulation result Recomendations
  • Fuel cell based vehicle -Energy converter -Convert chemical to electricity -Clean - zero emission - the product is only water and heat However, Not beneficial in term of fuel consumption –performance Therefore The electrical storage should be hybridized with the fuel cell Recuperate the braking energy – the fuel consumption is reduced Transient demand is compensated by the electrical storage
  • A design level stages In this study definition Configuring the rated power or maximum capacity for propulsion system of the vehicle which is in our case is fuel cell, battery and supercapacitor.
  • The vehicle under study is Hytruck - Which is prototype vehicle for a truck based on the fuel cell - which is still under going research -Produced in netherlands -The benefit to study : a varian of a hytruck based on the type -Driving cycle -Je05 and CSC -driving condition –urban traffic environment -heavy vehicle
  • IN PRINCIPAL -- The propulsion system in Hybrid Power train FC system : FC stack ( series of fuel cell ) - can not work Alone - Auxilliaries Battery Supercapacitor A motor (Not mentioned) : electricity to mechanics DC/DC converter : to raise the voltage level Inverter : Signal conditoner from motor to DC/bus
  • I define again the sizing objective in the math term now ! 3 degree of freedom problems ! Which maximum power of stack, maximum power battery, maximum power of Scap  Fuel consumption APPARENTLY : This problem is coupled to EMS problems, because In each size , the predefined cycle demand should be fullfilled by Component sources HOW to Regulate The power from each component source is defined in EMS Problems
  • EMS ! Objective How we regulate the control input for stack = u1 The control input for battery =u2 The control input for supercapacitor = u3 Such as it should produce the minimum fuel consumption The solutions should be also within the constraints ! The power balance should be met State of energy should be conserved Inequality constraints from the Supercapacitor: Physical constraints of Scap
  • The variables described in the EMS is described in schematic level of the propulsion system We can see only the fuel cell power has a unidirection flow to deliver the power or to charge on the battery/scap while at the same time other power trains such battery and supercapacitor can have charge/discharging mechanism
  • To realize The EMS – We need a model The model for the battery and supercapacitor is based on the power losses Model The model in the fuel cell Fuel consumption rate against the power drawn at the output of the stack, The model is derived from the fit relation of the polariation curve from the reference stack Why ? Fit relation
  • The power in the vehicle Is the power derived to overcome the air resistence, the friction and the acceleration /decceleration from speed profiles Inverter and motor are modeled as average values So it used defined the power demand that should be met in the dc bus
  • Brute force Is a techniek to check all the feasible answers. Given the feasible ranges of power train sizes and The result from the EMS are collected and selected to find the maximum sizes which result in minimum fuel consumption
  • The sizing Offline Design Level EMS offline EMS problems Dynamic problems = constraints Benchmark
  • The solution in fmincon is solved in numeric method Determines the initial values, the minimum is found when both the gradient of the constraints and cost function are co-linear Which is described in local minimum condition And the hessian matrices approaches small
  • This is an illustration of numeric approach of static optimization As we can see in the diagram , the estimation of solution is provided at complete cycle at each iterations So the dynamic is already included Another advantage using the method is The convergence is speed up by manipulating the lagrange multiplier SINCE in every step size, THE SEARCHING OF control signal u is not fixed
  • This is the initial size of stack size, battery size and supercapacitor size at the start of simulation The variation is limited to the maximum mass of Vehicle
  • EMS Minimum Fuel consumption Optimal control signal Power balance is met Energy is conserved The inequality constraints are holds
  • Analize based on the fuel consumption sensivity It is observed when the two components at the optimal and one components are changing Unlike the stack size and supercapacitor size variation
  • The optimal battery size is Found at the minimum !
  • Based on summarized table here that Deviation in battery energy is small 1% compared to its capacity Stresses the battery to be removed
  • Supercapacitor compensates the power more Even if The power losses of the supercapacitor is larger due to the higher size Still the supercapacitor has lower internal losses
  • Now the battery is removed and it is true that the fuel consumption is reduced to
  • It is interesting as well to compare the result in term of spectral distribution Supercapacitor dominates the power in high frequency range Battery and the stack in low range high frequency It is directly seen that removing battery reduce the gain of the stack about 10 dB which can be interpreted as the effort to charge on the battery Therefore the fuel consumption is reduced.
  • Practice presentation 25

    1. 1. The Sizing For Fuel Cell Stack, Battery and Supercapacitor of FCHEV Truck Iin Lidiya Zafina Supervised by Ir. Edwin Tazelaar Dr. P.A. Veenhuizen Collaboration Project Master of Control System Engineering - Applied Research Laboratory Automotive Department HAN University of Applied Science
    2. 2. <ul><li>Introduction </li></ul><ul><li>Objective </li></ul><ul><li>Problems Definitions </li></ul><ul><li>Modeling </li></ul><ul><li>Solutions </li></ul><ul><li>Result and Discussion </li></ul><ul><li>Conclusion </li></ul><ul><li>Recommendation </li></ul><ul><li>Introduction </li></ul><ul><li>Objective </li></ul><ul><li>Problems Definitions </li></ul><ul><li>Modeling </li></ul><ul><li>Solutions </li></ul><ul><li>Result and Discussion </li></ul><ul><li>Conclusion </li></ul><ul><li>Recommendation </li></ul>
    3. 6. Hytruck prototype Hytruck Specification kg kg kg m 2 - - - 4600 1740 7500 200 4.4 0.7 0.015 m v _ em m v _ payload m v_max m rot A f c d c r Empty mass Payload Max gross vehicle weight Equivalent rotating mass Frontal area Drag coefficient Rolling resistance Unit Value Variable Vehicle
    4. 9. <ul><li>Equality constraints </li></ul><ul><li>P FCn - P aux +P batn +P scap_term - P demand =0 </li></ul><ul><li>SOE bat (0)= SOE bat (end ) </li></ul><ul><li>SOE scap (0)= SOE scap (end) </li></ul>Inequality constraints
    5. 10. DC/ DC DC/DC DC/ AC Pw P bat_term P batn Pdemand P EM P FCn P aux M left P FC = u 1 .P FC_max M right P FC P scap_term P s_scap = u 3 .P scap_max P s_bat = u 2 .P bat_max Fuel Cell System P s_scap losses Supercapacitor Ideal storage P s_bat losses Ideal storage Battery
    6. 11. V oc_ba t = f (SOC) Fuel consumption Battery model Supercapacitor model V oc_scap = f (E _scap ) R int_scap P s_scap P scap_term R int_bat = f (SOC) P s_bat P bat_term
    7. 12. Vehicle model Inverter and motor are modeled as average values
    8. 13. Range of sizes P FC_ max1, P FC_ max2, P FC _maxi,,. P bat_ max1, P bat max2,. P bat maxt j,.... P scap max1, P scap max2, P scap_max k,…. EMS P demand Driving cycle P FC__max i, P bat_maxj ,P scap_max k Vehicle Model J opt P FC_max i, P bat_maxj , P scap_maxk ………………………… ... Store the result Find the Optimal sizing
    9. 14. Sizing Offline activity Energy management strategy Offline method <ul><li>Dynamic problems </li></ul><ul><li>Cost function </li></ul><ul><li>Constraints </li></ul><ul><li>Global minimum </li></ul><ul><li>as Benchmark </li></ul>Pseudo static optimization as DP approach Dynamic Programming (DP)
    10. 15. J(u)=0 G(u)=0 u 1 u m+1 u 0 u 0 u*
    11. 16. Initial approximation J(u) ,Gu), J u (u), G u (u) H uu Iter ≤ max iter du ,dλ, Evaluate initial function J(u) ,G(u), J u (u), G u (u) , ,, du Evaluate function maipulated u and λ end Vehicle + Propulsion model Driving cycle i-th u 0 u ,λ
    12. 18. EMS result
    13. 19. 188 – 246 116 – 145 Supercapacitor 25 25 Battery 55 - 66 45 - 55 Fuel cell stack Optimal size [kW] Je05 Cycle Optimal size [ kW] CSC cycle Component Source
    14. 21. <ul><li>The energy content is not an issue of hybridization </li></ul><ul><li>Energy deviation is small </li></ul><ul><li>Supercapacitor Compensate energy deviation to its maximum capacity </li></ul>3.3-3.9 3.2-3.7 kW 115 99 Peak demand kW 16.6 13.8 Average demand Kg/100 km 4.13 4.11 Fuel Consumption kWh 1.63 - 1.80 0.87 - 0.95 Total Energy Content kW kWh kWh 188 - 232 [1.13 -1.29] [1.13 -1.29] 116 – 145 [0.64 - 0.73] [0.64 - 0.73] Supercapacitor power Supercapacitor capacity Supercapacitor used capacity kW kWh kWh 25 [25] [0.50 - 0.52] 25 [25] [0.21 - 0.22] Battery power Battery capacity Battery used capacity kW 55 - 66 45 – 55 Stack size Unit Je05 cycle CSC cycle
    15. 22. Hybridization is sized by its power handling Not by energy content ! Supercapacitor compensates more ! kW kWh kWh 188 - 232 [1.13 -1.29] [1.13 -1.29] 116 – 145 [0.64 - 0.73] [0.64 - 0.73] Supercapacitor power Supercapacitor capacity Supercapacitor used capacity kW kWh kWh 25 [25] [0.50 - 0.52] 25 [25] [0.21 - 0.22] Battery power Battery capacity Battery used capacity Unit Je05 cycle CSC cycle increased continually 100 Battery reduced 510 Supercapacitor Impacts of the increment size to the fuel consumption trends Power rate [W/Kg] The component source
    16. 23. - 3.9 3.7 kW 113.5 97 Peak demand kW 16.2 13.55 Average demand kg/100 km 4.0 3.9 Fuel Consumption kW kWh kWh 203 1.29 1.29 174 0.97 0.97 Supercapacitor Capacity Capacity used kW 63 52 Stack size Unit Je05 cycle CSC cycle 3.3-3.9 3.2-3.7 kW 115 99 Peak demand kW 16.6 13.8 Average demand kg/100 km 4.13 4.11 Fuel Consumption kWh 1.63 - 1.80 0.87 - 0.95 Total Energy Content kW kWh kWh 188 - 232 [1.13 -1.29] [1.13 -1.29] 116 – 145 [0.64 - 0.73] [0.64 - 0.73] Supercapacitor power Supercapacitor capacity Supercapacitor used capacity kW kWh kWh 25 [25] [0.50 - 0.52] 25 [25] [0.21 - 0.22] Battery power Battery capacity Battery used capacity kW 55 - 66 45 – 55 Stack size Unit Je05 cycle CSC cycle
    17. 24. (a).FC stack –battery-supercapacitor (b). FC stack - supercapacitor
    18. 25. <ul><li>The optimal sizes and minimum fuel consumption has been summarized in the table. </li></ul><ul><li>The result from fuel sensitivity against component sizes show that by reducing the battery size, the fuel consumption is continuously reduced. In addition, from the size trends, the optimal size for the battery is found at the minimum size, 25 kW. Therefore, the fuel cell stack with supercapacitor is configured to observe the possibility of less fuel consumption. The result shows that the fuel consumption is reduced to 3.99 kg/100 km for CSC cycle and 4.03 kg/100 km for Je05 cycle which is reduced about 2 % from the optimal size with FC stack , battery and supercapacitor . The optimal stack size is 52 kW for CSC cycle with supercapacitor size 174 kW and stack 63 KW with supercapacitor 203 kW for Je05 cycle. </li></ul>
    19. 26. <ul><li>The on line EMS implementation should be implemented. </li></ul><ul><li>Equivalent Consumption Minimization Strategy, ECMS. The EMS strategy manipulating the equivalent electricity to fuel consumption cost </li></ul><ul><li>On line using the feedback battery model </li></ul><ul><li>predicting the future of the driving cycle using driving cycle generator. </li></ul>
    20. 27. Thank you