Abstract
Stringent emission regulations, concern over increasing air pollution, geo-political influences on oil production and unstable oil prices has made the need for electrification and powertrain efficiency improvements imperative. Performance of a Hybrid Electric Vehicle (HEV) is heavily influenced by multi-layered challenges like control strategies, component limitations, real world usage profile etc. These attributes pose a challenge in modelling & front loading of component specification. A control strategy for hybrid electric powertrain should maximize the benefit for end user on a real-world driving scenario. Emphasis on this combined with the challenges in simulation of real world driving scenario mandates extensive vehicle level trials and data analysis. In this paper we will present a methodology devised to collect and analyze data from real world trials. We will also present the design of an automated analysis tool to accelerate big data analysis. Potential parameters which is considered to influence the control strategies are discussed in this paper.