Co-Simulation of a Powertrain Digital Twin with Off-Highway Machine Simulations for the Prediction of Performance and Emissions for Real-World Machine Handling Cycles

A digital twin is a digital representation of a planned or 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 faster-than-real-time improving overall efficiency and reducing time of a programme. The HORIBA Intelligent Lab virtual engineering toolset was used produce an empirically based digital twin of a contemporary off-highway diesel Internal Combustion Engine (ICE). These empirical models were then coupled with simulations developed by AgriSI and IPG CarMaker to predict performance and emissions for real-world machine handling cycles of off-highway machines such as ploughing, planting, weeding, and fertilising. To supplement the prediction of performance and emissions attributes across many off-highway handling cycles, thanks to the implementation of ASAE standards and extensive field tests with dedicated instrumented vehicles, it has been possible to identify the tire-soil elastoplastic relationship, integrating it into semi-empirical MF-tyre models suitable for real-time simulation, adequately populating the coefficients of longitudinal traction and forward resistance on plastic soil. This new virtual platform developed by AgriSI and in co-simulation with IPG CarMaker and IPG TruckMaker allows for 24/7 X-in-the-Loop (XiL) simulations under particularly challenging conditions, suitable for reliably estimating the loads on machine components for the proper sizing of contemporary liquid fuelled ICEs and/or new hybrid or electric powertrains.