Connected Laboratories for Connected Automated Vehicles

Principal Investigator: Tulga Ersal, University of Michigan, tersal(at)
Faculty: Mingyan Liu, University of Michigan, mingyan(at)
Student: Xinyi Ge, University of Michigan
Government: Denise Rizzo, U.S. Army TARDEC
Industry: Michiel van Nieuwstadt,, Ford Motor Company

Connected Labs SchematicConnected vehicles and automated driving are two technologies poised to transform mobility. Both technologies independently promise significant potential benefits in terms of fuel economy, and when the two technologies are synergistically combined, these benefits could be even more significant.

This project will develop the core tools for an experimental platform that accurately assesses the fuel economy of multi-vehicle formations of mixed vehicle types. The project will address the gaps that currently exist in fuel economy assessment from on-road experiments and from full simulations.

First, performing a controllable and repeatable evaluation of the fuel economy of connected automated vehicle technologies is difficult in on-road experiments. Second, simulation-based evaluations are not yet accurate enough. Realistic, cost-efficient and repeatable solutions are needed to accelerate the evaluation and development of connected automated vehicles.

The overarching goal of this project is to create a connected testbed with multiple engines in the loop for realistic projections of fuel economy benefits of connected and automated vehicles in mixed traffic scenarios. Validation of key vehicle (non-engine) losses will be achieved through experiments at Mcity.

Prior work related to this project:

  • T. Ersal, M. Brudnak, A. Salvi, J. L. Stein, Z. Filipi, and H. K. Fathy, "Development and modelbased transparency analysis of an Internet-distributed hardware-in-the-loop simulation platform," Mechatronics, vol. 21, no. 1, pp. 22-29, 2011.
  • T. Ersal, M. Brudnak, J. L. Stein, and H. K. Fathy, "Statistical transparency analysis in Internetdistributed hardware-in-the-loop simulation," IEEE/ASME Transactions on Mechatronics, vol. 17, no. 2, pp. 228-238 2012.
  • T. Ersal, M. J. Brudnak, A. Salvi, Y. Kim, J. B. Siegel, and J. L. Stein, "An iterative learning control approach to improving fidelity in internet-distributed hardware-in-the-loop simulation," Journal of Dynamic Systems Measurement and Control, vol. 136, no. 6, pp. 061012-061012-8, 2014.
  • T. Ersal, R. B. Gillespie, M. Brudnak, J. L. Stein, and H. K. Fathy, "Effect of Coupling Point Selection on Distortion in Internet-distributed Hardware-in-the-Loop Simulation," International Journal of Vehicle Design, vol. 61, no. 1-4, pp. 67-85, 2013.
  • Y. Kim, A. Salvi, J. B. Siegel, Z. Filipi, A. Stefanopoulou, and T. Ersal, "Hardware-in-the-Loop Validation of a Power Management Strategy for Hybrid Powertrains," Control Engineering Practice, vol. 29, no. Special Issue: ECOSM12, pp. 277–286, 2014.
  • Y. Kim, A. Salvi, A. Stefanopoulou, and T. Ersal, "Reducing Soot Emissions in a Diesel Series Hybrid Electric Vehicle using a Power Rate Constraint Map," IEEE Transactions on Vehicular Technology, vol. 64, no. 1, pp. 2-12, 2015.