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Data-Driven Parametric Optimization for Pre-Calibration of Internal Combustion Engine Controls

Meli, Matteo 1; Wang, Zezhou ORCID iD icon 2; Sterlepper, Stefan 1; Picerno, Mario 1; Pischinger, Stefan 1
1 Rheinisch-Westfälische Technische Hochschule Aachen (RWTH Aachen)
2 Institut für Fahrzeugsystemtechnik (FAST), Karlsruher Institut für Technologie (KIT)

Abstract:

This paper presents an efficient pre-calibration method for combustion engine controls. In particular, it focuses on the initial shaping of multiple Lookup Tables (LUTs) within LUT-based Multiple-Input Single-Output (MISO) engine control systems. The approach addresses the increasing complexity of engine software, the rising number of calibration variables, and the time pressures prevalent in automotive development. Employing a white-box Model-in-the-Loop (MiL) optimization reduces the demands on hardware reliance and optimization time compared to conventional engine calibration techniques. The white-box model enables the pre-calibration of LUTs using known system inputs, expected system outputs, and the control system model structure. To optimize the white-box control system model, LUTs are parametrized through Rational Bézier Regression (RBR), facilitating Sequential Quadratic Programming (SQP) for optimization. RBR, which includes both Rational Bézier Curve Regression (RBCR) and Rational Bézier Surface Regression (RBSR), allows for flexible and smooth shaping of 1D and 2D LUTs with a unified and few number of parameters. The pre-calibration process is further improved using historical calibration data from various vehicle variants stored in a relational database. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000181276
Veröffentlicht am 02.05.2025
Originalveröffentlichung
DOI: 10.1016/j.apenergy.2025.125893
Scopus
Zitationen: 1
Web of Science
Zitationen: 1
Dimensions
Zitationen: 1
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Fahrzeugsystemtechnik (FAST)
Publikationstyp Zeitschriftenaufsatz
Publikationsdatum 15.08.2025
Sprache Englisch
Identifikator ISSN: 0306-2619
KITopen-ID: 1000181276
Erschienen in Applied Energy
Verlag Elsevier
Band 392
Seiten Art.-Nr.: 125893
Vorab online veröffentlicht am 24.04.2025
Schlagwörter Engine control, Model-based calibration, Model-in-the-Loop, Parametric optimization, Relational database, Virtual calibration
Nachgewiesen in OpenAlex
Web of Science
Dimensions
Scopus
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