Hybrid Electric Vehicle Torque Split Algorithm for Reduction of Engine Torque Transient

The increased concern over energy efficiency and emissions in recent years has led to the deployment of cleaner alternatives for vehicle powertrains, including electrified vehicles. Electrified vehicles have shown promise in increasing fuel economy as well as reducing emissions. As part of the increased push for electrification, various technologies aiding in the deployment of electrified vehicles have been studied. One such important technology is the hybrid electric vehicle torque-split algorithm. Research on these algorithms has largely focused on improving the ability of a hybrid electric vehicle to reduce emissions and energy consumption. In this thesis the development of a hybrid torque split algorithm that proposes a method for reducing engine torque transients over a base power-loss minimization cost function algorithm is presented and compared for the reduction of engine torque transients. Engine torque transients can increase HC and CO emissions, as well as potentially increase fuel consumption, so the developed algorithms were also compared in terms of fuel economy and emissions. The correlation of engine torque transients to emissions and fuel consumption was also assessed. From model-in-the-loop testing an 8.25% decrease of engine torque transients was found over the base power-loss minimization cost function algorithm. From vehicle-in-the-loop testing a 14.6% reduction of engine torque transients was measured, with a 4.84% reduction approximated to be attributable to the difference in algorithms alone, over the base power-loss minimization cost function algorithm. A moderate positive correlation was shown to exist between CO emissions and the engine torque transients, and a 10.4% reduction in CO was found while testing the algorithm against the base power-loss minimization cost function algorithm.