IP Library Granted Patent US 12,188,428
Granted Patent B2
US 12,188,428 · App. 16/623,264 · Granted Jan 7, 2025

Method for the model-based open-loop and closed-loop control of an internal combustion engine

Inventors: Jens Niemeyer (Friedrichshafen, DE); Andreas Flohr (Deggenhausertal, DE); Jörg Remele (Hagnau, DE)
Assignee: ROLLS-ROYCE SOLUTIONS GMBH
F02D41/38F02D41/1401F02D2041/1433F02D2200/0602
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Quick Facts
Patent No.
US 12,188,428
App. No.
16/623,264
Granted
Jan 7, 2025
Kind
B2
Abstract

A method for the model-based open-loop and closed-loop control of an internal combustion engine, in which injection system set points for activating the injection system actuator are calculated as a function of a torque setpoint via a combustion model, and gas path set points for activating the gas path actuators are calculated via a gas path model. A measure of quality is calculated by an optimizer as a function of the injection system set points and the gas path set points. The measure of quality is minimized by the optimizer by changing the injection system set points and gas path set points within a prediction horizon. By using the minimized measure of quality, the injection system set points and gas path set points are set by the optimizer as definitive for adjusting the operating point of the internal combustion engine.

Claims (6)

1. A method for model-based open-loop and closed-loop control of an internal combustion engine, comprising the steps of: calculating injection system setpoint values for actuating injection system actuators as a function of a setpoint torque by a combustion model; calculating gas path setpoint values for actuating gas path actuators by a gas path model; calculating a quality measure by an optimizer as a function of the injection system setpoint values and the gas path setpoint values, the optimizer minimizing the quality measure by changing the injection system setpoint values and gas path setpoint values within a prediction horizon; and setting the injection system setpoint values and the gas path setpoint values by the optimizer based on the minimized quality measure, as definitive for setting an operating point of the internal combustion engine, including minimizing the quality measure by the optimizer calculating a first quality measure at a first point in time, predicting a second quality measure within the prediction horizon at a second point in time, determining a difference between the first quality measure and the second quality measure, and setting, via the optimizer, the second quality measure as a minimized quality measure in which the deviation is smaller than a limiting value, wherein the optimizer directly predefines, as an injection system setpoint value, a rail pressure setpoint value for a subordinate rail pressure closed-loop control circuit.

2. The method according to claim 1 , wherein the optimizer directly predefines a start of injection and an end of injection as injection system setpoint values for actuating an injector.

3. The method according to claim 1 , wherein the optimizer indirectly predefines gas path setpoint values for subordinate gas path closed-loop control circuits.

4. A method for model-based open-loop and closed-loop control of an internal combustion engine, comprising the steps of: calculating injection system setpoint values for actuating injection system actuators as a function of a setpoint torque by a combustion model;

calculating gas path setpoint values for actuating gas path actuators by a gas path model; calculating a quality measure by an optimizer as a function of the injection system setpoint values and the gas path setpoint values, the optimizer minimizing the quality measure by changing the injection system setpoint values and gas path setpoint values within a prediction horizon; and setting the injection system setpoint values and the gas path setpoint values by the optimizer based on the minimized quality measure, as definitive for setting an operating point of the internal combustion engine, including minimizing the quality measure by the optimizer calculating a first quality measure at a first point in time, predicting a second quality measure within the prediction horizon at a second point in time, and setting, via the optimizer, the second quality measure as a minimized quality measure after running through a predefinable number of new calculations, wherein the optimizer directly predefines, as an injection system setpoint value, a rail pressure setpoint value for a subordinate rail pressure closed-loop control circuit.

5. The method according to claim 4 , wherein the optimizer directly predefines a start of injection and an end of injection as injection system setpoint values for actuating an injector.

Assignments (2)
CHANGE OF NAME Recorded Dec 13, 2021
From: MTU FRIEDRICHSHAFEN GMBH
To: ROLLS-ROYCE SOLUTIONS GMBH
Reel/Frame 058741/0679 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 17, 2019
From: NIEMEYER, JENS; FLOHR, ANDREAS; REMELE, JÖRG
To: MTU FRIEDRICHSHAFEN GMBH
Reel/Frame 051322/0735 →
Continuity (1)
Related Publication 20230258144A1 · Aug 17, 2023
References Cited (12)
US 9732688B2 · Cygan, Jr. · 2017 [cited by applicant]
US 10669962B2 · Buchholz · 2020 [cited by examiner]
US 20110172897A1 · Tsuzuki · 2011 [cited by applicant]
US 20160025020A1 · Hodzen · 2016 [cited by applicant]
US 20180216558A1 · Buchholz · 2018 [cited by applicant]
DE 102006004516B3 · 2007 [cited by applicant]
DE 102015104194A1 · 2015 [cited by applicant]
DE 102014118125B3 · 2016 [cited by applicant]
DE 102015212709A1 · 2017 [cited by applicant]
WO 2017005337A1 · 2017 [cited by applicant]
WO 2017102039A1 · 2017 [cited by applicant]
Harder Karsten et al: “A real-time nonlinear MPC scheme with emission constraints for heavy-duty diesel engines”, 2017 American Control Conference (ACC), AACC, May 24, 2017 (May 24, 2017), pp. 240-245, XP033109918. [cited by applicant]