Abstract

Heavy equipment driving conditions require a balance of terrain and soil interaction, driver comfort and durability of the machine. A complex requirement for testing scenarios when integrating variants of powertrain and chassis combinations with ever-shortening development cycles. Prototype powertrain and chassis variants may not physically exists during the development cycle, therefore subsystem optimization and validation cannot be done physically. Bringing the development into the lab allows year-round testing with simulation and physical test-cells to calibrate and optimized the design. The hardware-in-loop process can apply accurate loads to components for Heavy Equipment machinery. Digital twins of the tractor are reused from the existing engineering models. These models are used to create the loading conditions in the real-time powertrain dyno environment. Validating HIL allows application of this process too many levels of tractors, saving time and test effort in the field[KD(SS3PM1] . The John Deere transmission controller testing has physics based model and real transmission hardware. The test cell includes the internal combustion engine and transmission connected to dynos. Shift test repeatability is guaranteed in this environment. Starting with existing multibody simulation models and exporting to real-time integrating environments, there will be further discussion about how real field test signals compare to the simulated field test-cell environment. For example; shift up, shift down, skip shift and shuttle shift. Also next steps for process improvement will be discussed. Key enabler for HIL success is the reuse of John Deere’s existing 3D models for real-time applications on hardware available in the market. 3D models advance the level of load and frequency range over historical simplified reduced DOF models. This expands the accuracy of the models over broad number of scenarios. Reuse of existing models decreases risk and uncertainty of the models within the engineering organization and saves the time to develop and maintain multiple models of the same mechanism.