Optimizing Powertrain Simulation Models
Students on the Isuzu project will develop and optimize a Powertrain simulation model to improve the efficiency and effectiveness of Powertrain design.
The student team will support engine model based development with a combination of data driven models, 1D powertrain models, and supervised machine learning based optimization methodologies. Utilizing existing algorithm libraries, students will develop and perform statistical analysis and build data driven emission models and engine performance models to optimize both steady-state and transient operation conditions. Previous feasibility studies suggest that a supervised machine learning approach could be effective. Results will support steps towards a fully virtual vehicle simulation and development environment.