The advent of BS6 coupled with RDE emission norms has increased the development efforts and costs due to the shear amount of testing and validation on real engines and vehicles which are necessitated by these stringent norms.Front-loading of tasks by moving actual vehicle and engine tasks on to virtual setup, will reduce the development efforts and costs significantly. This front-loading of tasks on to a LABCAR would need real time and highly accurate plant models, tools to parameterize these plant models and accurate data driven models to predict dynamic parameters like emissions.In this collaborative work between Maruti Suzuki India Ltd and ETAS India, ETAS VVTB and ICE plant models were parameterized with the data generated on engine test with ASCMO Global DoE test plan by using ASCMO MOCA. The ASCMO Global test plan also ensures the coverage of data points across the entire engine operating space. These plants models were optimized to an accuracy level of more than 95%. The optimized plant model parameters are integrated on ETAS LABCAR and necessary fine tuning is carried out on the LABCAR.The results show, for MIDC cycle the accuracy of simulation torque and airflow results are greater than 95% and fuel consumption simulation has an error less than 6%. Accuracy levels of ASCMO dynamic emission models also have good accuracy levels.


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    Title :

    Front-Loading: Virtual Validation and Calibration on LABCAR


    Additional title:

    Sae Technical Papers


    Contributors:

    Conference:

    Symposium on International Automotive Technology ; 2024



    Publication date :

    2024-01-16




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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