Author ORCID Identifier



Date of Graduation


Document Type


Degree Type



Statler College of Engineering and Mineral Resources


Lane Department of Computer Science and Electrical Engineering

Committee Chair

Brian Woerner

Committee Member

Ali Feliachi

Committee Member

Andrew C. Nix


Advancements in battery and electric motor technology have driven the development of hybrid electric vehicles to improve fuel economy. Hybrid electric vehicles can utilize an internal combustion engine and an electric motor in many configurations, requiring the development of advanced energy management strategies for a range of component configurations. The Equivalent Consumption Minimization Strategy (ECMS) is an advanced energy management strategy that can be calculated in-vehicle in real-time operation. This energy management strategy uses an equivalence factor to equate electrical to mechanical power when performing the torque split determination between the internal combustion engine and electric motor. This equivalence factor is determined from offline vehicle simulations using a sensitivity analysis to provide optimized fuel economy results, while maintaining a target state of charge of the battery. The goal of this work is to analyze how the algorithm operates with the WVU Chevy Blazer to find an optimal equivalence factor that can maintain a strict charge sustaining window of operation for the high voltage battery, while improving the fuel economy based on dynamic programing results calculated for this vehicle architecture. Different electric motor sizes are then explored by changing the max torque and max power to analyze how the equivalence factor changes to operate the ECMS algorithm. This research mainly focused on utilizing both the UDDS drive cycle and HwFET drive cycle to determine the effectiveness of the ECMS algorithm. The results show that as the max torque and max power of the electric motor increased, the equivalence factor found for the UDDS drive cycle and the HwFET drive cycle converged to similar value. The convergence of the equivalence factor allowed the ECMS algorithm to better maintain the target state of charge of the battery while maintaining the fuel economy and improving the fuel economy for the UDDS drive cycle and HwFET drive cycle, respectively.