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Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines Gregory M. Shaver Dynamic Design Lab May 6 th, 2005 Department.

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Presentation on theme: "Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines Gregory M. Shaver Dynamic Design Lab May 6 th, 2005 Department."— Presentation transcript:

1 Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines Gregory M. Shaver Dynamic Design Lab May 6 th, 2005 Department of Mechanical Engineering Stanford University

2 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 2 Outline What is residual-affected HCCI? What are its benefits? Hurdles to practically implementing HCCI Lack of combustion trigger Cyclic coupling Dynamic modeling of HCCI Making HCCI practical with feedback control Conclusions and future work

3 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 3 What is Residual-Affected HCCI? Residual-Affected Homogeneous Charge Compression Ignition Advanced combustion strategy for piston engines Combustion due to uniform auto-ignition using compression alone Hot exhaust gases reinducted using Variable Valve Actuation (VVA) Main benefits 1. Increased efficiency compared to SI 2. Modest compression ratios 3. Drastic reduction in NO x emissions (i.e. smog)

4 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 4 HCCI with Variable Valve Actuation

5 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 5 HCCI with Variable Valve Actuation Reactants (fuel & air) & previously exhausted gases (residual) inducted

6 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 6 HCCI with Variable Valve Actuation Reactants (fuel & air) & previously exhausted gases (residual) inducted Compression of mixture

7 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 7 HCCI with Variable Valve Actuation Reactants (fuel & air) & previously exhausted gases (residual) inducted Compression of mixture causes auto-ignition uniform, fast & uncontrolled

8 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 8 HCCI with Variable Valve Actuation Reactants (fuel & air) & previously exhausted gases (residual) inducted Compression of mixture causes auto-ignition uniform, fast & uncontrolled Useful work from expansion

9 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 9 HCCI with Variable Valve Actuation Reactants (fuel & air) & previously exhausted gases (residual) inducted Compression of mixture causes auto-ignition uniform, fast & uncontrolled Useful work from expansion Hot combustion products exhausted

10 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 10 HCCI with Variable Valve Actuation Reactants (fuel & air) & previously exhausted gases (residual) inducted Compression of mixture causes auto-ignition uniform, fast & uncontrolled Useful work from expansion Hot combustion products exhausted, portion reinducted

11 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 11 HCCI with Variable Valve Actuation Valve motions from VVA determine: inducted gas composition amount of compression

12 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 12 HCCI with Variable Valve Actuation

13 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 13 HCCI with Variable Valve Actuation Sudden rise in pressure combustion initiation

14 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 14 HCCI with Variable Valve Actuation Sudden rise in pressure combustion initiation Work output:

15 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 15 HCCI with VVA -Challenges Goal: achieve desired combustion timing & work output Challenges No direct initiator of combustion Cycle-to-cycle coupling through exhaust gas Significantly complicate transient load operation

16 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 16 HCCI with VVA -Challenges Goal: achieve desired combustion timing & work output Challenges No direct initiator of combustion Cycle-to-cycle coupling through exhaust gas Significantly complicate transient load operation To date – HCCI impractical!!

17 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 17 Research Goals Make HCCI practical through closed-loop control Stabilize process & control work output Modeling Objective: Simple physical models that capture behavior most relevant for control Cyclic coupling Combustion timing In-cylinder pressure evolution (work output) Control Objective - Control of: Combustion timing – make combustion sure happens! Work output – the key output of the engine efficiency & reduced emissions come as result of process

18 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 18 Previous Work – Simulation Modeling Ogink and Golovitchev 2002, Babajimopoulos et al Multi-zone modeling of HCCI Kong et al Multi-dimensional CFD models using detailed chemistry Many others Complex flow and chemical kinetics models Capture general steady state behavior Ignore cycle-to-cycle coupling Exhibit long run times - ~12 hours per engine cycle

19 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 19 Contributions – Simulation Modeling Developed a simulation model of residual-affected HCCI that: Captures the cyclic coupling Predicts behavior during steady state & transients Captures ignition via kinetics with a simple, intuitive model runtimes: ~ 15 seconds per engine cycle (amenable to use as a control testbed)

20 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 20 Previous Work - Control Agrell et al. 2003, Haraldsson et al. 2003, Bengtsson et al. 2004, Olsson et al Various approaches to control combustion timing or work output In all cases: controller hand-tuned or synthesized from black-box models

21 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 21 Contributions - Control Physics-based control model of HCCI The first physics-based approach to control of HCCI Generalizable Enables use of control engineering tools: Theoretical control design Stability analysis Control strategies for: Combustion timing Peak pressure or work output

22 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 22 Outline - Modeling Strategies Simulation model Gain some intuition of the process What are key features? What are relevant control inputs & outputs? Control model Need a slightly simpler physical description for synthesis The launching point for developing control strategies …..making HCCI practical!!

23 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 23 Experimental Apparatus Single cylinder engine With VVA Fuel used: Propane Compression ratio Variable: Engine speed Fixed: 1800 rpm In-cylinder pressure transducer Combustion timing Peak pressure Work output

24 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines st law analysis of cylinder and exhaust manifold HCCI Simulation Model

25 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines st law analysis of cylinder and exhaust manifold Steady state 1D compressible flow relations HCCI Simulation Model

26 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines st law analysis of cylinder and exhaust manifold Steady state 1D compressible flow relations Heat transfer In-cylinder (modified Woschni) Ref: Chang et al Exhaust manifold HCCI Simulation Model

27 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines st law analysis of cylinder and exhaust manifold Steady state 1D compressible flow relations Heat transfer In-cylinder (modified Woschni) Ref: Chang et al Exhaust manifold Combustion model Wiebe function What do we use as a combustion trigger? HCCI Simulation Model

28 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines st law analysis of cylinder and exhaust manifold Steady state 1D compressible flow relations Heat transfer In-cylinder (modified Woschni) Ref: Chang et al Exhaust manifold Combustion model Wiebe function What do we use as a combustion trigger? Resulting Model – 9 nonlinear ODEs HCCI Simulation Model

29 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 29 Temperature Threshold Assume HCCI occurs at a threshold temperature A fit at one temperature…

30 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 30 Temperature Threshold Assume HCCI occurs at a threshold temperature Fit at one temperature… doesn’t hold at others! Increasing residual

31 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 31 What Happened? Simulation model: earlier timing for increasing residual More residual means mixture temperature Higher temperature leads to early timing Experiments show more constant timing Is some physical effect missing? Yes! Concentration of reactants More residual means lower reactant concentration

32 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 32 Integrated Arrhenius Rate Equation Simple model for start of combustion Integrated Arrhenius rate Constant threshold, a, b and E a from published experiments Contributions from temperature & reactant concentration captured

33 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 33 Integrated Arrhenius Rate Set threshold at one operating point…

34 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 34 Set threshold at one operating point… …and pressure, timing & work output at all points is captured Increasing residual Integrated Arrhenius Rate

35 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 35 Integrated Arrhenius Rate Note: can vary composition without much change in timing Increasing residual

36 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 36 Steady state behavior with propane captured What about transients? Changes in load Can the model capture these? Simulation Model: Can it be extended?

37 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 37 Simulation Model: Transients 1 st operating point has higher steady state temperature than 2 nd The elevated exhaust temperature advances combustion process during transition As exhaust temperature decreases, behavior reaches new steady state Experiment

38 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 38 Simulation Model: Transients Simple model captures the coupling and ignition behavior during transition Simulation Experiment

39 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 39 Results from Simulation modeling Aspects most relevant for control captured with simple simulation model: Cyclic coupling & combustion timing In-cylinder pressure evolution Approach can handle: Steady-state behavior Transients A valuable virtual testbed for control

40 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 40 Motivation for Control Model Simulation model has a lot of benefits Still, too complex for synthesizing control strategies Motivates a simpler dynamic model 1. Enabled through additional physical assumptions 2. Discretizing the process (induction, compression, etc.) 3. Linking processes

41 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 41 Control Model Assumptions Assumptions: Induction: atmospheric pressure Isentropic compression & expansion HCCI is fast: constant volume combustion In-cylinder heat transfer:% of combustion energy

42 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 42 Control Model Assumptions

43 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 43 A Simple Control Model

44 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 44 A Simple Control Model Step through process to develop model of dynamics

45 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 45 A Simple Control Model Step through process to develop model of dynamics dynamics

46 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 46 Peak Pressure Dynamics The peak pressure dynamics takes the form: Fairly complex nonlinear dynamic model

47 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 47 Peak Pressure Dynamics The peak pressure dynamics takes the form: Fairly complex nonlinear dynamic model Can see dependence on: Control inputs

48 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 48 Peak Pressure Dynamics The peak pressure dynamics takes the form: Fairly complex nonlinear dynamic model Can see dependence on: Control inputs Cyclic coupling

49 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 49 Peak Pressure Dynamics The peak pressure dynamics takes the form: Fairly complex nonlinear dynamic model Can see dependence on: Control inputs Cyclic coupling Combustion timing

50 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 50 Peak Pressure Dynamics The peak pressure dynamics takes the form: Fairly complex nonlinear dynamic model Can see dependence on: Control inputs Cyclic coupling Combustion timing How do we model initiation of combustion,  comb 

51 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 51 Combustion Timing Dynamics Recall the integrated Arrhenius rate model:

52 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 52 Combustion Timing Dynamics Recall the integrated Arrhenius rate model: Integrand takes on largest value at TDC

53 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 53 Combustion Timing Dynamics Recall the integrated Arrhenius rate model: Integrand takes on largest value at TDC Simplify: begin integration at TDC with values at TDC

54 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 54 Combustion Timing Dynamics Recall the integrated Arrhenius rate model: Integrand takes on largest value at TDC Simplify: begin integration at TDC with values at TDC

55 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 55 Combustion Timing Dynamics Recall the integrated Arrhenius rate model: Integrand takes on largest value at TDC Simplify: begin integration at TDC with values at TDC

56 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 56 Combustion Timing Dynamics Recall the integrated Arrhenius rate model: Integrand takes on largest value at TDC Simplify: begin integration at TDC with values at TDC Algebraic expression exists for each variable

57 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 57 Combustion Timing Dynamics Recall the integrated Arrhenius rate model: Integrand takes on largest value at TDC Simplify: begin integration at TDC with values at TDC Algebraic expression exists for each variable

58 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 58 Control Model Peak pressure and combustion timing dynamics together give: A nonlinear 2-state, dynamic, discrete system model

59 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 59 Control Model Validation Control model captures Steady state & transient Peak pressure Combustion Timing Captures Cyclic coupling Ignition via kinetics

60 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 60 Control Modeling Summary HCCI is difficult to control: Cyclic coupling No direct combustion trigger Control model captures these phenomena!! Simple model tells us how dynamics are affected by control inputs Is a launching point for: Synthesizing control strategies Assessing system stability Generalizable

61 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 61 Outline of Control Implementations From control model 1. Peak-pressure control at constant combustion timing 2. Work output control at constant combustion timing 3. Simultaneous peak pressure and combustion timing control Many other approaches possible

62 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 62 Peak Pressure Control w/ Constant timing Fix final valve closure Vary composition to control peak pressure A “static” approach to controlling timing A large number of control approaches can be utilized

63 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 63 Peak Pressure Control w/ Constant timing Linear Controller Synthesis A common control approach is to linearize the system model Linearizing about an operating point yields: Simple linear control laws can be synthesized where:

64 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 64 Peak Pressure Control w/ Constant timing In closed-loop: Controller synthesized from linearized version of model Is controller stable in closed-loop with nonlinear model?

65 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 65 Peak Pressure Control w/ Constant timing Nonlinear Stability Analysis Using: Lyapunov stability theory Convex optimization Shows: Simple linear controller stabilizes entire operating regime

66 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 66 Peak Pressure Control w/ Constant timing Experimental Implementation Accurate control of peak pressure Mean tracking Fluctuation reduction Increases robustness Little change in phase What about direct control of work output (IMEP)?

67 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 67 Experimental Work Output Control Rapid mean tracking & fluctuation reduction We can control work output, while keeping timing roughly constant

68 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 68 Experimental Work Output Control Positive and negative load transients What about simultaneous control of combustion timing and work output?

69 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 69 Combustion Timing & Work Output Control Add other control input: final valve closure Significant control knob for combustion timing Simple approach Separate linear controllers for peak pressure and timing

70 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 70 Decoupled Peak Pressure and Phase Control Maintain cycle-to-cycle peak pressure controller, vary phase more slowly

71 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 71 Approach works Simultaneous control of timing and peak pressure Experiments with Decoupled Control

72 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 72 Comments on Control Experiments Simple physics-based controllers works well Implementation is straightforward Mean tracking & fluctuation reduction of peak pressure work output Combustion timing fairly constant Independent control of peak pressure & combustion timing Many others possible

73 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 73 Conclusion HCCI has a promising future as a cleaner, more efficient strategy Hurdle: controlling the process No combustion initiator & cycle-to-cycle coupling The good news: HCCI is amenable to model-based control Key behaviors captured in both simulation and control models Simulation & control models capture: Steady-state Transients Physics-based control of: Peak pressure Work output Combustion timing

74 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 74 Future Work Study different control approaches Control of multi-cylinder HCCI engines Results to date with single-cylinder engines Cylinder-to-cylinder dynamics now play a key role! Change the world!

75 Dynamic Design Lab.Stanford University Physics-based Modeling and Control of Homogeneous Charge Compression Ignition (HCCI) Engines - 75 Acknowledgments Chris Gerdes The Dynamic Design Lab Partners in crime: Matt Roelle & Nikhil Ravi A great sponsor – Robert Bosch Corporation Jean-Pierre Hathout, Jasim Ahmed, Aleks Kojic & Sungbae Park The defense Committee Chris Edwards, Sanjay Lall, Matt Franchek & Steve Rock Stanford University


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