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Developing a Real-Time Heavy-Duty Engine Model Build Using GT-SUITE’s Fast Running Model (FRM) Builder and Running on Virtual Test Bed A CASE STUDY PUBLISHED BY AUTOMOTIVE RESEARCH ASSOCIATION OF INDIA (ARAI) AND GAMMA TECHNOLOGIES

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Developing a Real-Time Heavy-Duty Engine Model Build Using GT-SUITE’s Fast Running Model (FRM) Builder and Running on Virtual Test Bed A CASE STUDY PUBLISHED BY AUTOMOTIVE RESEARCH ASSOCIATION OF INDIA (ARAI) AND GAMMA TECHNOLOGIES

BS VI norms, which are stringent on

emissions, require improved performance.

As a result, the number of labels to be

calibrated increases and with increased

complexity due to aftertreatment and

diagnostics.

In addition to this, RDE requirements call for

extended range calibration. All these

requirements lead to calibration efforts on

engine / chassis dyno as well as on vehicle.

Upcoming Stage IV and CPCB 4+ norms in

off-road and genet categories respectively

also bring similar calibration challenges.

Therefore, calibration using a virtual test bed

becomes essential to frontload the activities

as shown in Figure 1.

Figure 1 BSVI calibration efforts

Key Aspects of Calibration with Virtual Test Bed (VTB):

• Calibration not dependent on

weather, location and prototype

availability

• Improved calibration quality with high

reproducibility and good

extrapolation capability

• Concept definition, calibration

robustness investigation

• Minimized usage of expensive test

facilities

• Reduced number of prototypes

resulting in faster time to market

Virtual Calibration Lab at ARAI:

The virtual calibration lab setup at ARAI as

shown in Figure 2 is equipped with PUMA,

an open test bed controller with a CAMEO

DOE tool integrated to dSPACE’s

SCALEXIO system. The calibration

environment is exactly the same as a real

calibration test bed. The heart of the virtual

calibration is the plant model and therefore it

is very important to get the required fidelity in

the shortest time depending on the purpose

of activities as shown in Table 1. Here the

Level 1 modeling approach using GT’s Fast

Running Model (FRM) builder tool is

explored for six-cylinder heavy duty

application. The objective is:

• Assess FRM builder approach for

engine calibration

• Achieve reasonable accuracy with

minimum efforts using FRM builder,

when limited test data is available

• Convert to Real Time model and run

on VTB

• Run steady state and transient cycle

Figure 2 ARAI Virtual Test Bed system

Table 1 Plant model fidelity level

Plant model development using GT-SUITE FRM builder tool:

The FRM builder tool provides the ability to

select engine configuration. After filling the

required details, the Mean Value engine

model is automatically generated with all

default settings. Changes are made in inputs

such as TC maps, speed range, fueling, and

EGR to match the existing six-cylinder

engine configuration as shown in figure 3.

Combustion and emission parameters are

tuned quickly with limited steady state data

and different parameters such as torque,

BSFC, in-cylinder pressures, MFB 50, turbo

speed, manifold pressures, and

temperatures. Emissions limited to NO were

compared to check the accuracy of the

model and were found to be satisfactory. The

results are shown in figure 4 for the Level 1

model. The required real time factor is

achieved on the fast running model after

some simplifications in the model.

Figure 3 Engine plant model built using FRM builder

Figure 4 Comparison of simulation vs test results for Level 1 Model

VTB integration of RT FRM model:

The next step is to run the RT plant model on

the VTB system. The load drawer metering

unit, which consists of actuators such as

injectors, is prepared and integrated with a

RT plant model. Inputs required for engine

plant models such as fueling are taken from

the ECU in the real-time domain. The ECU

exchanges signals with the virtual engine

through soft sensors and with actual

hardware such as injectors through electrical

signals. The VTB setup of the load drawer

along with ECU and RT plant model is shown

in figure 5.

Figure 5 VTB setup for Level 1 RT FRM Model

The steady state and transient operating

points are run on VTB at standard ambient

conditions and compared with test data. The

results shown in figures 6,7, and 8 show very

good accuracy at steady as well as at

transient conditions. Considering the limited

test data, time, and efforts put into calibrating

the model the results are very encouraging

and prove the usefulness of an FRM

approach for level 1 activities.

The VTB is now ready for carrying out

calibration at steady state and transient

points at standard ambient conditions.

“The GT-SUITE FRM

builder approach took very

little effort and time to

reach good accuracy at

steady as well as at

transient conditions”

-Hitesh Chaudhari

Figure 6 Steady state results at standard conditions

Figure 7 Transient results at standard conditions

Figure 7 Transient results at standard conditions

Figure 8 NO prediction at transient cycle

Summary:

The engine plant model built using GT’s FRM

builder approach showed very good fidelity

and real time capability. These results show

the usefulness of an FRM approach for

concept investigation, function development

etc. The summary of the work is as follows:

• The FRM builder approach took very

little effort and time to reach required

accuracy level

• The plant model built with limited test

data has shown very good correlation

with experimental data at steady

state & transient level

• The FRM model showed real time

compliance and therefore is useful for

calibration using a VTB approach

This approach has shown huge potential in

reduction of calibration efforts, ease of

calibration, screening of various hardware

options, and fast calibration of engine

derivatives for various applications.

Depending upon the plant model fidelity the

usage of VTB can be listed as follows:

Authors

Mr Hitesh B Chaudhari, Manager, PTE, ARAI [email protected]

Dr N. H Walke, Deputy Director, PTE, ARAI [email protected]

About ARAI

Automotive Research Association of India (ARAI), established in 1966, is the leading automotive R&D organization of the country set up by the Automotive Industry with the Government of India. ARAI is an autonomous body affiliated to the Ministry of Heavy Industries and Public Enterprises, Government of India. The Department of Scientific and Industrial Research, Ministry of Science and Technology, Government of India, has recognized ARAI as a Scientific and Industrial Research Organization (SIRO). Further, ARAI is a prime Testing and Certification Agency notified by Government of India under Rule 126 of Central Motor Vehicle Rules, 1989. Powertrain Engineering Department (PTE) at ARAI is a state of art R&D centre for engine and transmission development. PTE is engaged in research, design, development and evaluation of all types of IC engines, such as diesel, gasoline, LPG, CNG, HCNG, Hydrogen, Ethanol, Bio-Diesel, Dual-Fuel & Hybrid systems. PTE is engaged in design engines from concept to prototype to production support for various applications like HGV, LCV, utility vehicles, tractor, genset, 2 and 3 wheelers. PTE is equipped with capabilities to develop BS VI/ Stage IV/ Stage V solutions and hybrid vehicle systems More Information at https://araiindia.com/home

About Gamma Technologies

Gamma Technologies is the developer of GT-SUITE, the leading 0D/1D/3D multi-physics CAE system simulation software. GT-SUITE supplies a comprehensive set of component libraries which simulate the physics of fluid flow, thermal, mechanical, electrical, magnetic, chemistry, and controls. From those libraries, one can build accurate models of almost any engineering system, including vehicles, engines, drivelines, transmissions, general powertrains and mechanical systems, hydraulics, lubrication and friction, thermal management, cooling, chemistry, aftertreatment and much more. More Information at: https://www.gtisoft.com/ Gamma Technologies

Contact Information by Territory: https://www.gtisoft.com/about-gt/contact-by-territory/