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Robust air-to-fuel ratio and boost pressure controller design for EGR and VGT systems using QFT method Inseok Park Advised by prof. Myoungho Sunwoo November,

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Presentation on theme: "Robust air-to-fuel ratio and boost pressure controller design for EGR and VGT systems using QFT method Inseok Park Advised by prof. Myoungho Sunwoo November,"— Presentation transcript:

1 Robust air-to-fuel ratio and boost pressure controller design for EGR and VGT systems using QFT method Inseok Park Advised by prof. Myoungho Sunwoo November, 2012 Department of Automotive Engineering, Hanyang university

2 - 2 - ACE Lab, All rights reserved Introduction Part I. Robust feedback design Control loops design using QFT method Decoupler design Part II. Model-based feed-forward design Mean-value engine model Feedforward design using model inversion technique Conclusions Contents

3 - 3 - ACE Lab, All rights reserved Increasing complexity of clean diesel engine control system Background DPF EGR EGR EURO-5 EURO-6 and Further EURO-4 NOx [g/km] PM [g/km] EURO-3 (2000) EURO-6 (2014) EURO-5 (2009) EURO-4 (2005) EURO Complexity EGR SCR DPF LNT

4 - 4 - ACE Lab, All rights reserved Exhaust gas recirculation (EGR) Background u EGR W EGR

5 - 5 - ACE Lab, All rights reserved Exhaust gas recirculation (EGR) Background NOx reduction - Combustion temperature - Oxygen availability Excessive EGR - NOx vs. PM tradeoff - Combustion instability Fresh charge Burned gas

6 - 6 - ACE Lab, All rights reserved Variable geometry turbocharger (VGT) Background u VGT P int

7 - 7 - ACE Lab, All rights reserved Variable geometry turbocharger (VGT) Background Power increase - Fresh charge - Fuel mass Slow response - Smoke limit function - Limitation of drivability Fresh charge Fuel mass

8 - 8 - ACE Lab, All rights reserved Difficulties in EGR and VGT control problems Background Two feedback loops between exhaust and intake manifolds Mass flow path (Pressure ratio, effective valve area) Power path (T/C dynamics)

9 - 9 - ACE Lab, All rights reserved EGR rate* Direct measurement / unmeasurable Accuracy & reliability problems of estimator Mass air flow rate measured from HFM sensor Indirect measurement / measurable (on-board sensor) Drift problems / poor SNR* Air-to-fuel ratio Indirect measurement / measurable (on-board sensor) Robust to HFM, Injector drift Good SNR* Related works - Performance variables for EGR *EGR rate = W egr / (W comp + W egr ), SNR: signal to noise ratio

10 ACE Lab, All rights reserved Model-based controller design (Sliding mode, Hinf, …) Limited access of on-line calibration Model-predictive approach High computational loads / unknown future disturbance Limited access of on-line calibration Soft-computing approach (Artificial neural-network) High computational loads / Limited access of on-line calibration Related works - Control approach There is still a large gap between theory and industry applications Use Gain-scheduled PID structure How to design PID gains ? How to compensate non-linearity and cross-coupling effect?

11 ACE Lab, All rights reserved Proposition of design methodology for robust air-to-fuel ratio and boost pressure controller of EGR and VGT system Problem formulation Performance variables: Air-to-fuel ratio(AFR exh ), Boost pressure (P int ) Controller structure: Gain-scheduled PID structure Approaches Uncertainty problems: Quantitative feedback theory Cross-coupled problems: Static forward path decoupler Non-linearity compensation: Model-based feedforward design Research objectives

12 ACE Lab, All rights reserved Part I. Robust feedback design - Control loops design using QFT method - Forward path decoupler design

13 ACE Lab, All rights reserved Multi-input multi-output control problem Problem formulation Scope In-house developed controller Smart actuator

14 ACE Lab, All rights reserved Linear approximation of non-linear system Potentially large uncertainty Robustness problem Problem statement (1) Stationary measurements of G 11, G 1750 rpm, 20 mg/str

15 ACE Lab, All rights reserved Linear approximation of non-linear system Potentially large uncertainty Robustness problem Problem statement (2) P int set-point LUTAFR exh set-point LUT

16 ACE Lab, All rights reserved Linear approximation of non-linear system Potentially large uncertainty Robustness problem Problem statement (3) Static gain contour of G 11 (s), G rpm, 20 mg/str

17 ACE Lab, All rights reserved Large parameter uncertainty problem Design of two SISO control loops using QFT, independently Cross-coupled dynamics problem Design of forward path static decoupler Target engine operating points Design overview Sample design point (1750 rpm, 20 mg/str) N e and W f trajectories of NEDC

18 ACE Lab, All rights reserved Design framework for robust controller design Parametric uncertainty mapped on Nichols chart Bounds of controller requirements on Nichols chart Quantitative feedback theory Structure parameter uncertainty Template on Nichols chart

19 ACE Lab, All rights reserved Two DOF controller structure Compensator, Prefilter Straight-forward design process Quantitative feedback theory

20 ACE Lab, All rights reserved Plant model: 1 st order plus time-delay (FOPTD) Measurement conditions for parameter identification Parameter identification Input variablesStationary conditionDynamic condition u EGR 70 ~ 100 (grid size: 5) [%, close] 24 Step patterns u VGT 70 ~ 95 (grid size:5) [%, close] 24 Step patterns

21 ACE Lab, All rights reserved Stationary measurements results Parameter identification

22 ACE Lab, All rights reserved Stationary measurements results Parameter identification

23 ACE Lab, All rights reserved Identification results at sample design operating point Parameter identification Plant Model ParameterValue rangeNominal value G 11 (s) K ~ ~ T d ~ G 12 (s) K ~ ~ T d ~ G 21 (s) K ~ ~ T d ~ G 22 (s) K ~ ~ T d ~ st Loop design using QFT method 2 nd Loop design using QFT method u EGR linearization range: 70 ~ 95 [%,close] u VGT linearization range: 75 ~ 95 [%, close]

24 ACE Lab, All rights reserved Point-wise frequency response analysis Step1: Frequency vector Power spectrum analysis of AFR during NEDC experiment

25 ACE Lab, All rights reserved Robust stability specification Peak response of complementary sensitivity function(T) for all freq. Step2: Desired controller specifications (1) M p = 1.1 (GM = 5.61 dB, PM = 54 deg)* *Maximum peak criteria

26 ACE Lab, All rights reserved Robust stability bound on Nichols chart Step2: Desired controller specifications (1) *Maximum peak criteria

27 ACE Lab, All rights reserved Robust reference tracking specification Design of acceptable time responses models Step2: Desired controller specifications (2)

28 ACE Lab, All rights reserved Robust reference tracking specification Upper bound model: %OS (10%), Tr (0.7 sec), Min Td (0.13 sec) Lower bound model: Ts (3.5 sec), Max Td (0.25 sec) Step2: Desired controller specifications (2)

29 ACE Lab, All rights reserved Robust reference tracking bounds on Nichols chart Step2: Desired controller specifications (2) Higher than solid lines Lower than dashed lines

30 ACE Lab, All rights reserved Composite bounds and nominal plant responses Step3: Loop shaping Nominal plant, G 11,0 (s)

31 ACE Lab, All rights reserved Off-line tuning of PID gains using bounds on Nichols chart Step3: Loop shaping Nominal plant, G 11,0 (s) Nominal Loop function, L 11,0 (s) = G 11,0 (s)C 1 (s)

32 ACE Lab, All rights reserved Off-line tuning of PID gains using bounds on Nichols chart Step3: Loop shaping Nominal Loop function, L 11,0 (s) = G 11,0 (s)C 1 (s) GM: dB PM: deg Nominal plant, G 11,0 (s)

33 ACE Lab, All rights reserved Design tradeoff between performance and robustness Step3: Loop shaping GM: 7.86 dB PM: deg Nominal Loop function, L 11,0 (s) = G 11,0 (s)C 1 (s) (High gain case)

34 ACE Lab, All rights reserved Fragility analysis within parameter uncertainty Step3: Loop shaping

35 ACE Lab, All rights reserved F 1 (s) design with min/max closed-loop responses in bode plot Step4: Prefilter design Bode plot of T 1 (s) CL response w/o prefilter Tracking bounds CL resp. with prefilter

36 ACE Lab, All rights reserved F1(s) design with min/max closed-loop response in bode plot Step4: Prefilter design Step responses within parameter uncertainty region Tracking bounds

37 ACE Lab, All rights reserved Frequency vector Desired controller specifications Robust stability (Same as 1 st loop) –Complementary sensitivity functions peak response M p : 1.1 –GM: 5.61db, PM: 54 deg Robust reference tracking (Slower than 1 st loop) –Upper bound: %OS (6%), Tr (0.95 sec) –Lower bound: Ts (5.8 sec) 2 nd Loop design (1)

38 ACE Lab, All rights reserved Loop shaping results: 2 nd Loop design (2) C 2 (s)s Loop shaping resultsC 2 (s)s Fragility analysis

39 ACE Lab, All rights reserved Prefilter design results 2 nd Loop design (3) Bode plot of T 2 (s) with F 2 (s) Step responses within parameter uncertainty region

40 ACE Lab, All rights reserved Part I. Robust feedback design - Control loops design using QFT method - Forward path decoupler design

41 ACE Lab, All rights reserved Static gain contour at N e = 1750 rpm, W f = 20 mg/str Measurements of cross-coupling characteristics *RNGA: Relative Normalized Gain Array

42 ACE Lab, All rights reserved RNGA* analysis result at sample design point Poor input-output paring condition RNGA analysis of entire operating points Measurements of cross-coupling characteristics *RNGA: Relative Normalized Gain Array

43 ACE Lab, All rights reserved Forward path static decoupler Attenuation of the off-diagonal gains using static gain inversion Decoupling interactions, approximately Decoupler design Control input scaling parameters

44 ACE Lab, All rights reserved Repetition of proposed design steps for 15 operating points Implementation results LUT-based set-point generator and feed-forward controller Prefilters: (F 1, F 2 ) Gain scheduled PID controllers (C 1, C 2 ) Gain scheduled decouplers (W 11, W 12, W 21, W 22 ) Implementation

45 ACE Lab, All rights reserved Experimental results

46 ACE Lab, All rights reserved Target plant: Mass produced R2.2 Liter diesel engine Experimental setup Engine test cell Common rail & Fuel injection (MeUn*, PCV*, piezo injector) Exhaust air path (VGT & EGR) Intake air path (VSA* & ACV*) MeUn*: Metering unit PCV*: Pressure control valve RPS*: Rail pressure sensor VSA*: Variable swirl actuator ACV*: Air control valve

47 ACE Lab, All rights reserved Test environment configuration Experimental setup

48 ACE Lab, All rights reserved Implementation environment Engine management system (EMS) platform Experimental setup Hardware platform - Production type 32-bit microcontroller (MPC5554) - Target engine compatible I/O configuration Software platform - Standardized architecture (AUTOSAR-Lite) - Model-based SW development (Simulink)

49 ACE Lab, All rights reserved AFR exh step responses at N e = 1750 rpm, W f = 20 mg/str Three fixed VGT positions Experimental results – SISO case Tracking bound models

50 ACE Lab, All rights reserved AFR exh step responses at N e = 1750 rpm, W f = 20 mg/str Experimental results – MIMO case (1)

51 ACE Lab, All rights reserved P int step responses at N e = 1750 rpm, W f = 20 mg/str Experimental results (2)

52 ACE Lab, All rights reserved AFR exh step responses of entire operating points Experimental results (3)

53 ACE Lab, All rights reserved P int step responses of entire operating points Experimental results (4)

54 ACE Lab, All rights reserved Transient responses Experimental results (4)

55 ACE Lab, All rights reserved Transient responses Performance limitation due to the phase lag of the EGR valve controller Experimental results (5) 1750 rpm case

56 ACE Lab, All rights reserved Part II. Model-based feed-forward design

57 ACE Lab, All rights reserved Why the feed-forward controller is required? Limited bandwidth of feedback controlled system due to slow, time-delay dynamics of EGR and VGT system Compensating non-linear behavior Problems in designing feed-forward controller for EGR and VGT system Conventional: Look-up table based feed-forward design –LUTs are obtained from steady state experiments –In transient, each actuator FF control input is generated without the considerations of physical interactions Proposed: Model-based feed-forward design –Physical model-based feedforward controller –In transient, physically acceptable EGR valve and VGT vane trajectories are generated Overview

58 ACE Lab, All rights reserved Structure of model-based feed-forward controller Overview Desired values Measured values Estimated values

59 ACE Lab, All rights reserved MVEM of AFR exh path MVEM modeling (1) In-Cylinder mass balance model Energy balance of intake manifold EGR Poppet valve model

60 ACE Lab, All rights reserved MVEM of P int path MVEM modeling (2) Mass balance of exhaust manifold Compressor power model Turbine power model VGT vane valve model

61 ACE Lab, All rights reserved Modeling region (225 operating points) N e [rpm]: 1500, 1750, 2000 W f [mg/str]: 15, 20, 25 u VGT [%,close]: 82.5 ~ 95 u EGR [%,close]: Nominal value ±5,10 % Steady state evaluation (1)

62 ACE Lab, All rights reserved Evaluation results of EGR path Steady state evaluation (2) ± 5%

63 ACE Lab, All rights reserved Evaluation results of VGT path Steady state evaluation (3) ± 5%

64 ACE Lab, All rights reserved Feedback controller: small PID gains without decoupler P int step response at N e = 1750 rpm, W f = 20mg/str (1) KpKiKd QFT design MBD-FF case10.40 KpKiKd QFT design MBD-FF case AFR exh control loop P int control loop

65 ACE Lab, All rights reserved EGR path P int step response at N e = 1750 rpm, W f = 20mg/str (2) W egr W comp W ie P int / P exh A egr

66 ACE Lab, All rights reserved VGT path P int step response at N e = 1750 rpm, W f = 20mg/str (3) P exh Pwr comp W ie +W f W egr W turb

67 ACE Lab, All rights reserved Test condition N e : 1750 rpm, W f : mg/str Transient responses (1)

68 ACE Lab, All rights reserved LUT- FF + PID w/o decoupler vs. MBD-FF + PID w/o decoupler Transient responses (2)

69 ACE Lab, All rights reserved LUT- FF + PID w/o decoupler vs. MBD-FF + PID w/o decoupler Transient responses (2)

70 ACE Lab, All rights reserved Conclusions

71 ACE Lab, All rights reserved In this dissertation, two kinds of controller design method for the EGR and VGT systems are proposed Approach 1. Robust MIMO feedback controller QFT design of two SISO control loops with regard to the parameter uncertainty Mitigation of cross-coupled dynamics of the two loops by using forward path decoupler Approach 2. Model-based feedforward controller Mean value modeling of the air-path systems Feedforward design using model inversion technique Summary

72 ACE Lab, All rights reserved EGR and VGT system analysis Control-oriented modeling and identification Potentially large uncertainty and cross-coupled dynamics are quantitatively evaluated A good degree of physical insight is presented QFT-based MIMO controller design method Robust PID controller off-line tuning using QFT method Static feedforward design Fast initial design without extensive calibration Considerably calibration work can be reduced Model-based feed-forward controller Non-linear EGR and VGT system modeling EGR and VGT feedforward design Solution for NL, MIMO control systems (e.g. LP-EGR or Two stage T/C) Contributions

73 ACE Lab, All rights reserved Thank you

74 ACE Lab, All rights reserved Best practices for successful handling of EMS* complexities Background EMS*: engine management system Control algorithm - Approach (Mathematical model-based approach for control / estimation / fault-diagnosis / calibration) - Advanced application (Combustion control using cylinder pressure sensor) Software engineering - Standardized architecture (AUTOSAR) - Model-based SW design (Simulink) EMS

75 ACE Lab, All rights reserved Control system design Control process and controller design approach Set point governor Physical state controller Actuator controller Physical set value Actuator set value Control signal Operating condition Approach Optimization problem Approach MIMO problem Nonlinear problem Slow and delayed system Approach Nonlinear problem Dead band / stiction problem Fast system

76 ACE Lab, All rights reserved Complexities of passenger car diesel engines Engine position -Crank, Cam Temperature -Coolant, fuel -Intake air -Exhaust gas, … etc. -Accel. pedal -Mass air flow -Lambda -SOC, Vbatt, … Pressure -Common rail -Intake manifold -DPF difference, … CFI system -MeUn, PCV -Injector1,2,3,4 Air system -EGR valve -VGT vane -Throttle valve -Variable swirl -EGR Cooler Bypass etc. -Glow plug -LSU heater -Alternator -EFP, …. Sensors (20 EA) Actuators (15 EA)

77 ACE Lab, All rights reserved Common rail and injection system Complexities of passenger car diesel engines Fuel tank HP-pump LP-pump MeUn* MeUn*: Metering unit PCV*: Pressure control valve RPS*: Rail pressure sensor PCV* RPS* Common rail Piezo-injectors

78 ACE Lab, All rights reserved

79 ACE Lab, All rights reserved Deterioration Problems of HFM sensor (1)

80 ACE Lab, All rights reserved Poor SNR Problems of HFM sensor (2)

81 ACE Lab, All rights reserved Performance variables for EGR control EGR rate* –Ideal variable / unmeasurable state Mass air flow rate –Indirect measurement of EGR mass flow rate / typical variable –HFM sensors drift problem / poor SNR* Air-to-fuel ratio of exhaust gas as a performance variable for EGR control problem Background *EGR rate = W egr / (W comp + W egr ), SNR: signal to noise ratio W comp +W f (fresh chared mixture) W egr (EGR gas) W rg (residual gas) - Mass balance equation of in-cylinder

82 ACE Lab, All rights reserved Advantages of AFR exh Robust to HFM sensor and Injector drifts Relatively good SNR Background Closing EGR valve Air-to-fuel ratio versus EGR various engine operating points

83 ACE Lab, All rights reserved

84 ACE Lab, All rights reserved AFRexh vs. EGR rate (225 points)

85 ACE Lab, All rights reserved AFRexh vs. Wcomp (225 points)

86 ACE Lab, All rights reserved VGT vane closing case Considerable cross-coupling characteristics

87 ACE Lab, All rights reserved EGR vane closing case Considerable cross-coupling characteristics

88 ACE Lab, All rights reserved QFT

89 ACE Lab, All rights reserved Step4: Bounds calculations Parameter uncertainty space Template on Nichols chart Parameter uncertainty and templates in Nichols chart

90 ACE Lab, All rights reserved Nichols chart Open-loop and close-loop response are concurrently displayed Fundamentals of Quantitative feedback theory Low freq. High freq.

91 ACE Lab, All rights reserved Plant model definition Model structure: First-order plus time-delay model (FOPTD) Three parameters: Static gain, time constant, time-delay Lumped actuator dynamics (EGR valve) Plant model

92 ACE Lab, All rights reserved Nichols chart

93 ACE Lab, All rights reserved Maximum peak criteria Robust stability

94 ACE Lab, All rights reserved Pseudo-continuous time augmented plant model AFR control design: Implementation issues

95 ACE Lab, All rights reserved Ref He, M.-J., et al. (2009). "RNGA based control system configuration for multivariable processes." Journal of Process Control 19(6): Interaction measurement Steady-state and transient characteristics are considered Simple for field engineers Relative normalized gain array

96 ACE Lab, All rights reserved Straight forward manner of design process Plant parameter identification / controller specification Bounds calculation Loop shaping / Prefilter design Advantages Guarantee of robustness within structured parameter uncertainty Design tradeoffs are highly transparent between stability, performance, plant uncertainty, disturbance level, the number of controller order, and others Easy & simple theoretical background Short summary of QFT method

97 ACE Lab, All rights reserved Gain-scheduled PID and W controller Implementation LUT-based set-point generators LUT-based FF controller F1 F2 C1 C2 WG

98 ACE Lab, All rights reserved Modeling

99 ACE Lab, All rights reserved Air-to-fuel ratio feedforward path In-cylinder AFR inverse model Intake manifold energy balance inverse model EGR popet valve inverse model

100 ACE Lab, All rights reserved Air-to-fuel ratio feedforward path In-cylinder AFR inverse model Intake manifold energy balance inverse model EGR popet valve inverse model

101 ACE Lab, All rights reserved Air-to-fuel ratio feedforward path In-cylinder AFR inverse model Intake manifold energy balance inverse model EGR popet valve inverse model

102 ACE Lab, All rights reserved Boost pressure feedforward path Compressor power inverse model Exhaust manifold mass conservation inverse model Turbine power inverse model VGT vane inverse model

103 ACE Lab, All rights reserved Boost pressure feedforward path Compressor power inverse model Exhaust manifold mass conservation inverse model Turbine power inverse model VGT vane inverse model

104 ACE Lab, All rights reserved Boost pressure feedforward path Compressor power inverse model Exhaust manifold mass conservation inverse model Turbine power inverse model VGT vane inverse model

105 ACE Lab, All rights reserved Boost pressure feedforward path Compressor power inverse model Exhaust manifold mass conservation inverse model Turbine power inverse model VGT vane inverse model

106 ACE Lab, All rights reserved Limitation of this study Robust anti windup controller design using QFT Robust stability in the case of actuator saturation (Stiff control, unreachable set-point) Decoupler mismatching problem in transient Optimizing loop shaping Problems to be considered Multi equilibrium points of EGR and VGT system –Same set-point different steady state actuator positions Sing-inversion problem of VGT system –In the case of High EGR condition, G12, G22 sign of static gain Challenging works

107 ACE Lab, All rights reserved Integrating other devices using CANape Compact RIO Lambda meter gateway ES636 DFM-3100 AVL439 Opacity Pressure Temperature UniNOx INDICOM Intercooler controller Fuel meter gateway CAN1(500k bps) CAN2(250k bps) CAN3(500k bps) IMEP SOC, MFB PC (CANape, CANoe) VN1630 Intake/Exha ust O2, A/F, Lambda NOx I/C DS temp Fuel rate VX1000 EMS

108 ACE Lab, All rights reserved DAQ measuring variables In-cylinder pressure EGR cooler downstream Pressure Temperature Intake manifold downstream Pressure Temperature Intake manifold Lambda Intake manifold upstream Temperature Intercooler downstream Pressure Temperature Exhaust manifold upstream Temperature Engine out emission NOx PM Turbine downstream Pressure Temperature Compressor upstream Pressure Temperature Compressor downstream Pressure Temperature Exhaust manifold Pressure Temperature Exhaust manifold Lambda

109 ACE Lab, All rights reserved Integrating other devices using CANape Elec. interface Comm. line Analog signals SCI CAN Ch1 CAN Ch2 EthernetNEXUS CAN Analog, PWM signals Press. and temp. cRIO VN1630 CANape ECUVX1000 ES636Gateway 1 IcCtl UniNOx Elec. Vlv, Temp sensor MEXA1600Gateway 2 Cylinder Pressure INDICOM SCI Analog signals R1DAQ_Ch1_CAN500 R1DAQ_Ch2_CAN250 CAN Ch3 R1DAQ_Ch3_CAN500 Opacimeter 439 Analog signal DFM-3100Gateway 3 SCI Battery sensor LIN Ch1 R1DAQ_Ch1_LINXXX(TBD)


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