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Punit Tulpule

Email: tulpule.3@osu.edu

Office Hours:

Monday and Friday 10 a.m. - 11 a.m

Simulation Capabilities:

11+ years of experience with Matlab and Simulink

Software Proficiency:

  • GT-Power
  • AxiSuite (ExoThermia)
  • C++

Recent Research:

My research has four main themes: 1) Systems modeling, 2) Control, 3) Model Based Design and 4) prognosis of complex engineering systems

1. Systems Modeling:  Integration of component level models into a full system level model is not        trivial since the system behavior is typically more the just sum of its components.  We have expertise in modeling, calibration and integration of system models at various levels from vehicle powertrain to traffic.

2.Control: My research expertise in optimal controls are more application focused. I have been working on improving computation time for optimal control for various applications. A couple of examples of my research are: I have developed methods and tools for quick design of optimal control of linear systems.  I am involved in NEXTCAR project, and I was able to significantly improve computation time of dynamic programming such that we were able to use it in real-time.

3. Model Based Design: I got interest in Model Based Design during my PhD. I developed tools and methods for integrated control and system optimal design of dynamical systems. Some other examples are:

             1.Calibration automation of engine start controls
             2. Model based design and benchmarking of fueling control
             3. Model reduction for xIL validation and verification of transmissions

4. Prognosis: Remaining useful life prediction for complex engineering systems is a fundamentally challenging topic due to propagation of aging through components.  I worked on a project to develop methods for prognosis for battery packs of PHEVs.  Later we also established algorithms for prognosis of tires and lead-acid batteries.

Selected Publications:

Sadabadi, K. K., Ramesh, P., Tulpule, P., & Rizzoni, G. (2019). Design and calibration of a semi-empirical model for capturing dominant aging mechanisms of a PbA battery. Journal of Energy Storage, 24, 100789.

Thomas, C., Tulpule, P., & Midlam-Mohler, S. (2019). Model Order Reduction for x-In the Loop (xIL) Simulation of Automotive Transmissions (No. 2019-01-1042). SAE Technical Paper.

Olin, P., Aggoune, K., Tang, L., Confer, K., Kirwan, J., Deshpande, S. R., Gupta, S., Tulpule, P., Canova, M., Rizzoni, G. (2019). Reducing Fuel Consumption by Using Information from Connected and Automated Vehicle Modules to Optimize Propulsion System Control (No. 2019-01-1213). SAE Technical Paper.

Chang, C. Y., Tulpule, P., Rizzoni, G., Zhang, W., & Du, X. (2017). A probabilistic approach for prognosis of battery pack aging. Journal of Power Sources, 347, 57-68.

Tulpule, P., Rezaeian A., Karumanchi, A., Midlam-Mohler, S., (2017), Model Based Design and Hardware in the Loop validation: A new course development, American Control Conference, IEEE.

Tulpule, P., Chang, C. Y., & Rizzoni, G. (2016, October). Li-ion cell aging model online parameter estimation for improved prognosis. In Dynamic Systems and Control Conference (DSCC), ASME.

Hegde, B., Midlam-Mohler, S., & Tulpule, P. J. (2015, October). Thermal Model of Fuse Dynamics for Simulation Under Intermittent DC Faults. In ASME 2015 Dynamic Systems and Control Conference (pp. V002T34A008-V002T34A008). American Society of Mechanical Engineers.

Tulpule, P., & Kelkar, A. (2014). Integrated robust optimal design (irod) of header height control system for combine harvester. In 2014 American Control Conference (pp. 2699-2704). IEEE.

Tulpule, P. J., & Kelkar, A. G. (2014). Integrated Robust Optimal Design Using Bilinear Matrix Inequality Approach Via Sensitivity Minimization. Journal of Dynamic Systems, Measurement, and Control, 136(3), 031012.