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Research Papers: Internal Combustion Engines

Decentralized Feedback Control of Pumping Losses and NOx Emissions in Diesel Engines

[+] Author and Article Information
Rasoul Salehi

Powertrain Control Laboratory,
Department of Mechanical Engineering,
University of Michigan,
Ann Arbor, MI 48109
e-mail: rsalehi@umich.edu

Jason Martz, Anna Stefanopoulou

Powertrain Control Laboratory,
Department of Mechanical Engineering,
University of Michigan,
Ann Arbor, MI 48109

Bruce Vernham, Lakshmidhar Uppalapati, Bantwal Prashant Baliga

ISUZU Technical Center of America,
Plymouth, MI 48170

1Corresponding author.

Contributed by the IC Engine Division of ASME for publication in the JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER. Manuscript received March 1, 2018; final manuscript received March 31, 2018; published online June 25, 2018. Editor: David Wisler.

J. Eng. Gas Turbines Power 140(10), 102810 (Jun 25, 2018) (9 pages) Paper No: GTP-18-1108; doi: 10.1115/1.4040008 History: Received March 01, 2018; Revised March 31, 2018

A novel decentralized control architecture is developed based on a feedback from the pressure difference across the engine which is responsible for the pumping losses and the exhaust gas recirculation (EGR) flow in diesel engines. The controller is supplemented with another feedback loop based on NOx emissions measurement. Aiming for simple design and tuning, the two control loops are designed and discussed: one manipulates the variable geometry turbine (VGT) actuator and the other manipulates the EGR valve. An experimentally validated mean-value diesel engine model is used to analyze the best pairing of actuators and set points. Emphasis is given to the robustness of this pairing based on gain changes across the entire operating region, since swapping the pairing needs to be avoided. The VGT loop is designed to achieve fast cylinder air charge increase in response to a rapid pedal tip-in by a feedforward term based on the real-time derivative of the desired boost pressure. The EGR loop relies on a feedback measurement from a NOx sensor and a real-time estimation of cylinder oxygen ratio, χcyl. The engine model is used for evaluating the designed controllers over the federal test procedure (FTP) for heavy duty (HD) vehicles. Results indicate that the control system meets all targets, namely fast air charge and χcyl control during torque transients, robust NOx control during steady-state operation, and controlled pumping losses in all conditions.

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References

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Figures

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Fig. 5

Schematic of the 5.2 L diesel engine

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Fig. 4

(a) Sign change in DC gains for the channel VGT to χcyl and (b) positive RGA matrix element γ11 over most of the engine map

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Fig. 3

Outputs variation in a VGT sweep indicating linearity in VGT → ΔP channel up to VGT = 60. The VGT position shows the percentage of opening.

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Fig. 2

(a) DC gains ratio from VGT channel and (b) ratio of VGT change in response to variations in Pb and ΔP

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Fig. 1

ΔP and χcyl control architecture

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Fig. 12

Extension of the original control system to include direct feedback from NOx sensor and compensation from desired Pb

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Fig. 6

Validation of the major engine component models

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Fig. 7

Verification of the dynamic charge path model during the FTP HD drive cycle

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Fig. 8

Validation of the static NOx model

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Fig. 9

Bode plots of T(s) and S(s) for ΔP and χcyl control loops at [2000 rpm, 265 N·m]

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Fig. 10

Response of the designed χcyl—ΔP controller (darker) and χcyl—ΔP with ΔP compensation controller (lighter) to a fuel step at [2000 rpm, 265 N·m]

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Fig. 11

Bode plots of normalized ΔP and Pb in response to the VGT input

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Fig. 13

The effect of set point compensation on the normalized boost pressure frequency response

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Fig. 14

Comparison of the original ΔP control with boost pressure controller and ΔP+ compensator (simulation results)

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Fig. 15

Sensitivity of different controllers to set points: (a) operation with nominal set points and (b) operation with 10% error in set points

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Fig. 16

Canceling χcyl uncertainty and reducing transient NOx by χcyl—NOx cascade control (simulation results)

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