Application of a Digital Twin Virtual Engineering Tool for Ground Vehicle Maintenance Forecasting
2022-01-0434
03/29/2022
- Event
- Content
- The integration of sensors, actuators and real time control in transportation systems enables intelligent system operation to minimize energy consumption and maximize occupant safety and vehicle reliability. The operating cycle of military ground vehicles can be on- and off-road in adverse environments which places a demand on continuous subsystem functionality to fulfill missions. On–board diagnostic systems can alert the operator of degraded operation once established fault thresholds are passed. An opportunity exists to estimate vehicle maintenance needs using model-based predicted trends and compiled information from fleet operating databases. A digital twin, created to virtually describe the dynamic behavior of a physical system using computer mathematical models, can estimate the system behavior based on current and future operating scenarios while accounting for past operating effects. In this manner, the collection of real time data of the physical vehicle can be constantly compared with the virtual counterpart to assess the likelihood of degraded operation and recommend maintenance. In this paper, a digital twin is created for an off-road tracked ground vehicle with accompanying parameter database. A modular architecture enables different design reconfigurations to be considered so that various chassis subsystems and vehicle-ground mobility interfaces can be evaluated. A robust maintenance estimation algorithm is introduced and applied to monitor the operating behavior of the vehicle(s). A prediction tool, operating in parallel with the digital twin, uses sensory signal and model–based condition indicators to estimate remaining useful system life. A case study investigates six operating scenarios in which a virtually field deployed tracked vehicle’s operation is (softly) degraded through transmission and other slippages, missing gear tooth/ broken road wheel, and missing track pads. The numerical results will demonstrate the advantages of a digital twin-based maintenance forecasting strategy for ground vehicles while establishing the path forward for fleet level predictions.
- Citation
- Eddy, C., WAGNER, A., Wagner, J., and Castanier, M., "Application of a Digital Twin Virtual Engineering Tool for Ground Vehicle Maintenance Forecasting," SAE Technical Paper 2022-01-0434, 2022, .