Date of Award


Document Type

Open Access Dissertation

Degree Name

Doctor of Philosophy in Mechanical Engineering-Engineering Mechanics (PhD)

Administrative Home Department

Department of Mechanical Engineering-Engineering Mechanics

Advisor 1

Mahdi Shahbakhti

Committee Member 1

John E Beard

Committee Member 2

Darrell L Robinette

Committee Member 3

Mohammad Shakiba-Herfeh


Powertrain electrification including hybridizing advanced combustion engines is a viable cost-effective solution to improve fuel economy of vehicles. This will provide opportunity for narrow-range high-efficiency combustion regimes to be able to operate and consequently improve vehicle’s fuel conversion efficiency, compared to conventional hybrid electric vehicles (HEV)s. Low temperature combustion (LTC) engines offer the highest peak brake thermal efficiency reported in literature, but these engines have narrow operating range. In addition, LTC engines have ultra-low soot and nitrogen oxides (NOx) emissions, compared to conventional compression ignition and spark ignition (SI) engines. This dissertation concentrates on integrating the LTC engines (i) in series HEV and extended range electric vehicle (E-REV) architectures which decouple the engine from the drivetrain and allow the ICE to operate fully in a dedicated LTC mode, and (ii) a parallel HEV architecture to investigate optimum performance for fuel saving by utilizing electric torque assist level offered by e-motor. An electrified LTC-SI powertrain test setup is built at Michigan Technological University to develop the powertrain efficiency maps to be used in energy management control (EMC) framework.

Three different types of Energy Management Control (EMC) strategies are developed. The EMC strategies encompass thermostatic rule-based control (RBC), offline (i.e., dynamic programing (DP) and pontryagin’s minimum principal (PMP)), and online optimization (i.e., model predictive control (MPC)). The developed EMC strategies are then implemented on experimentally validated HEV powertrain model to investigate the powertrain fuel economy. A dedicated single-mode homogeneous charge compression ignition (HCCI) and reactivity controlled compression ignition (RCCI) engines are integrated with series HEV powertrain. The results show up to 17.7% and 14.2% fuel economy saving of using HCCI and RCCI, respectively in series HEV compared to modern SI engine in the similar architecture. In addition, the MPC results show that sub-optimal fuel economy is achieved by predicting the vehicle speed profile for a time horizon of 70 sec.

Furthermore, a multi-mode LTC-SI engine is integrated in both series and parallel HEVs. The developed multi-mode LTC-SI engine enables flexibility in combustion mode-switching over the driving cycle, which helps to improve the overall fuel economy. The engine operation modes include HCCI, RCCI, and SI modes. The powertrain controller is designed to enable switching among different modes, with minimum fuel penalty for transient engine operations. In the parallel HEV architecture, the results for the UDDS driving cycle show the maximum benefit of the multi-mode LTCSI engine is realized in the mild electrification level, where the LTC mode operating time increases dramatically from 5.0% in Plug-in Hybrid Electric Vehicle (PHEV) to 20.5% in mild HEV.