Driving patterns have great impact on fuel economy or power split control decisions of PHEV (Plug-in Hybrid Electric Vehicle) energy management. In this paper, a statistical approach was used to analyze real world velocity profiles to gather traffic information such as average speed, speed limits, segment length, etc. A Markov chain model was developed to make use of such information for generation of random velocity profiles that are representative of real world driving scenarios. The velocity profiles generated using the Markov chain models are used to calculate vehicle fuel economy by means of a validated through the road parallel PHEV model and ECMS (Equivalent Consumption Minimization Strategy) control strategy. The end goal of the research is to find mathematical, statistical or heuristic relationships between road events and the performance of PHEV energy management.
The role of ITS in PHEV performance improvement
MARANO, VINCENZO;
2011-01-01
Abstract
Driving patterns have great impact on fuel economy or power split control decisions of PHEV (Plug-in Hybrid Electric Vehicle) energy management. In this paper, a statistical approach was used to analyze real world velocity profiles to gather traffic information such as average speed, speed limits, segment length, etc. A Markov chain model was developed to make use of such information for generation of random velocity profiles that are representative of real world driving scenarios. The velocity profiles generated using the Markov chain models are used to calculate vehicle fuel economy by means of a validated through the road parallel PHEV model and ECMS (Equivalent Consumption Minimization Strategy) control strategy. The end goal of the research is to find mathematical, statistical or heuristic relationships between road events and the performance of PHEV energy management.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
