Time: 1:30 pm - 2:30 pm
Location: 409 Dougherty Engineering Building
Optimizing Modern Automotive Systems Through Model-Based Control: A Physics-Based Approach
The initiative to curtail greenhouse gas emissions has spurred great interest among automotive companies to expand their portfolios with new vehicle technologies, such as hybrid and electric vehicles, as well as adopting new engine technologies. The optimal and robust utilization and increased safety of such modern automotive systems can be obtained through advance model-based control and optimization strategies. Recent trends in automotive control research have pointed out the inherent necessity to ‘bring in more physics’ into such control design phase. The use of physics-based models to predict system and component behavior can substantially increase performance of such complex engineering systems and create a platform to develop robust control strategies.
Recent modeling and estimation developments with respect to Sustainable Transport Systems at CU-ICAR have been achieved on Lithium-ion battery systems. The adoption of physics-based models (in the forms of partialdifferential equations) can enhance the development and utilization of such systems for online on-board diagnosis and robust health-monitoring, within an embedded control framework. However, there are still issues and challenges that need to be addressed to further develop the field.