RDE Plus - Rapid Characterisation of Vehicle and Powertrain Performance and Emissions using Dynamic Design of Experiments, Digital Twin and Virtual Driving Methodologies HORIBA MIRA Limited

Format:

Book

Conference/Event

Author/Creator:

Roberts, Philip, author.

Contributor:

Bates, Luke

Headley, Aaron

Tabata, Kunio

Whelan, Steven

Conference Name:

WCX SAE World Congress Experience (2022-04-05 : Detroit & Online, Michigan, United States)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2022

Summary:

Vehicle manufacturers will need to overhaul current development methods used to guarantee emissions compliance with the introduction of more stringent emissions legislation. Climatic boundaries of temperature and altitude and in-service conformity mileage compliance will likely be extended alongside alterations to trip dynamics; this will require robust calibrations for emissions compliance. Consequently, assessing this vast array of scenarios will be impossible with physical testing of prototype vehicles and overseas climatic testing alone.To reduce reliance on physical testing for compliance, a frontloading vehicle and powertrain development programme has been established where road, chassis dynamometer, Engine-in-the-Loop (EiL) and digital twin virtual toolset methodologies are used. In the current report, this frontloading approach has been implemented utilising the EiL and digital twin virtual toolsets to predict engine performance and emissions across a multitude of environmental conditions and real-world driving scenarios using high fidelity, fully validated empirical engine performance and emissions models. These models were generated using transient training data captured from a real contemporary turbocharged diesel engine operated according to the transient test sequence created using the dynamic Design of Experiments (DoE) toolset.Engine performance and emissions were predicted for various driving and environmental scenarios across several routes by coupling empirical engine performance and emission models with the digital twin virtual vehicle, driver and scenario development toolset. This allowed the identification of unfavourable operating conditions that can result in non-compliance. By deploying this methodology, physical vehicle development testing time can be reduced by at least 70%

Notes:

Vendor supplied data

Publisher Number:

2022-01-0580

Access Restriction:

Restricted for use by site license