The Prediction of Performance and Emissions for Synthetic Machine Handling Cycles Utilising a Powertrain Empirical Digital Twin

<div class="section abstract"><div class="htmlview paragraph">A digital twin is a digital representation of a real physical system, product, or process that functions as its practically identical digital counterpart for tasks such as testing, integration, monitoring, and maintenance. Creating digital twins allows the ‘digital system’ or ‘digital product’ to be tested at faster-than-real-time which improves overall program efficiency and shortens the programme duration.</div><div class="htmlview paragraph">The HORIBA Intelligent Lab virtual engineering toolset was used to generate an Empirical Digital Twin (EDT) of a contemporary off-highway diesel Internal Combustion Engine (ICE) from physical testing, accounting for the effects of altitude and combustion air temperature. The EDT was subsequently used to predict engine performance and emissions for several synthetic off-highway machine cycles at sea-level and 3000m altitude. The synthetic agricultural cycles which included ploughing, seeding, spraying, fertilising, and roading were generated using a machine simulation programme created by Soluzioni Ingegneria and IPG Automotive. This combined physical testing and simulation approach to off-highway machine development and calibration is expected to support Original Equipment Manufacturers (OEMs) with In Service Monitoring (ISM) within the Stage V emissions period and supplement powertrain development for future emissions standards.</div><div class="htmlview paragraph">The off-highway simulations were conducted using semi-empirical Magic Formula (MF) tyre models which accounted for the tyre-soil elastoplastic working relationship. These models incorporated the coefficients of longitudinal traction and forward resistance on plastic soil and were developed from ASAE standards and extensive field testing with instrumented vehicles. This new off-highway simulation platform developed by Soluzioni Ingegneria and IPG Automotive allows the generation of complex off-highway scenarios which can be used to estimate loading of machine components such as hydraulics, pneumatics, and accessories and right-sizing of powertrains for given machine applications.</div></div>

Authors

Institutions

Publication Details

Journal
SAE technical papers on CD-ROM/SAE technical paper series
Published
2024-11-04
DOI
https://doi.org/10.4271/2024-01-4271
Primary Topic
Manufacturing Process and Optimization
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Prediction of Performance and Emissions for Synthetic Machine Handling Cycles Utilising a Powertrain Empirical Digital Twin

M. Pezzola, Luke Bates, Claudio Maroni, Steve Whelan et al.
SAE technical papers on CD-ROM/SAE technical paper series
Manufacturing Process and Optimization
article

The Prediction of Performance and Emissions for Synthetic Machine Handling Cycles Utilising a Powertrain Empirical Digital Twin

M. Pezzola, Luke Bates, Claudio Maroni, Steve Whelan, Phil Roberts, Elisabetta Leo, Steven Child
article en

Abstract

<div class="section abstract"><div class="htmlview paragraph">A digital twin is a digital representation of a real physical system, product, or process that functions as its practically identical digital counterpart for tasks such as testing, integration, monitoring, and maintenance. Creating digital twins allows the ‘digital system’ or ‘digital product’ to be tested at faster-than-real-time which improves overall program efficiency and shortens the programme duration.</div><div class="htmlview paragraph">The HORIBA Intelligent Lab virtual engineering toolset was used to generate an Empirical Digital Twin (EDT) of a contemporary off-highway diesel Internal Combustion Engine (ICE) from physical testing, accounting for the effects of altitude and combustion air temperature. The EDT was subsequently used to predict engine performance and emissions for several synthetic off-highway machine cycles at sea-level and 3000m altitude. The synthetic agricultural cycles which included ploughing, seeding, spraying, fertilising, and roading were generated using a machine simulation programme created by Soluzioni Ingegneria and IPG Automotive. This combined physical testing and simulation approach to off-highway machine development and calibration is expected to support Original Equipment Manufacturers (OEMs) with In Service Monitoring (ISM) within the Stage V emissions period and supplement powertrain development for future emissions standards.</div><div class="htmlview paragraph">The off-highway simulations were conducted using semi-empirical Magic Formula (MF) tyre models which accounted for the tyre-soil elastoplastic working relationship. These models incorporated the coefficients of longitudinal traction and forward resistance on plastic soil and were developed from ASAE standards and extensive field testing with instrumented vehicles. This new off-highway simulation platform developed by Soluzioni Ingegneria and IPG Automotive allows the generation of complex off-highway scenarios which can be used to estimate loading of machine components such as hydraulics, pneumatics, and accessories and right-sizing of powertrains for given machine applications.</div></div>

SAE technical papers on CD-ROM/SAE technical paper seriesVol. 1
Horiba (Japan) (JP)
Life below water
Openalex Percentile: Top 72%
Manufacturing Process and Optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.