Training Datasets of Exhaust Temperature Model (ETM) and Three-Way Catalyst Control Lambda Set Point (TWCC) Model for Black-Box Modeling

These are the two training datasets for the Exhaust Temperature Model (ETM) and the Three-Way Catalyst Control Lambda Set Point (TWCC) Model, used in Black-Box Modeling, such as through Neural Networks. The datasets for each black box model are stored in XLSX files. Each dataset file contains ECU channel inputs, related Map parameters, and output. The ECU channel inputs and Map parameters are collected with Sobol methods. The output is generated by Hardware-in-the-Loop (HiL) corresponding to the related ECU channel inputs and Map parameters. The ETM model has four effective Maps, hence there are 32 corresponding shape-based algorithm parameters. Its output is the exhaust temperature. Its ECU channel inputs are as follows: CH_1: Intake valve cut-off condition CH_2: Thrust cut-off condition CH_3: Cylinder equalization control work cycle injection enabled CH_4: Ignition angle efficiency CH_5: Relative level of reduction CH_6: Lean engine lambda for cylinders on exhaust bank with lambda split CH_7: Rich engine lambda for cylinders on exhaust bank with lambda split CH_8: Exhaust gas mass flow CH_9: Engine speed CH_10: Relative air filling CH_11: Material temperature CH_12: Engine temperature The TWCC model has one Map, hence there are 8 corresponding shape-based algorithm parameters. Its output is lambda set point. Its ECU channel inputs are as follows: CH_1: Exhaust mass flow CH_2: Trigger bit for inhibiting the purge CH_3: Trigger bit for a rich mixture CH_4: Trigger bit for empty catalyst CH_5: Trigger bit for catalyst reset CH_6: Oxygen storage level CH_7: Desired air-fuel ratio