Real-world investigation of a methodology for power train component sizing of hybrid electric vehicles

Hybrid electric vehicles (HEVs) have emerged as near term sustainable technologies to reduce fossil-fuel dependency. The variation in fuel economy (FE) due to the variation in driving patterns exists in hybrid electric vehicles (HEVs). Powertrain component size optimisation based on a methodology considering a range of driving patterns including different traffic conditions and driving styles simultaneously has previously demonstrated the potential to reduce variation in FE over standard legislative driving patterns. Though standard legislative driving patterns are useful for comparative study, there are evidences that legislative driving patterns are often considerably different from real-world driving. Therefore to ensure wide applicability, the methodology needed to be validated for real-world driving pattern. This paper applied the methodology for ten real world driving patterns over a predefined route consisting of urban and highway driving to investigate the applicability of the methodology in real world. The study was carried out using a series-parallel Toyota Prius HEV. A rule based supervisory control strategy was considered as the energy management. A genetic algorithm was considered as the optimisation method. The methodology demonstrated the potential to reduce variation in FE by up to 33% in real world driving