Offering better fuel economy and lower emissions than conventional vehicles, plug–in hybrid electric vehicles (PHEVs) are promising near–term options for high efficiency, 'sustainable' transportation. It has recently been found that these efficiency benefits can be further improved with access to upcoming trip and driving conditions. This study is organised into two parts: in part I, upcoming trip data is used to find the optimal SOC trajectory of our PHEV model that will help minimise the total cost of electricity and fossil fuel. In part II, the optimum SOC trajectory is applied within the real–time controller to optimally distribute propulsion power between two energy sources. Autonomie was used to develop and implement a high fidelity PHEV model. The optimal SOC trajectory which has been found by real–time optimisation technique is in close agreement with the global optimum solution of Dynamic Programming. Moreover, the real–time technique is much less computationally expensive.
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Vajedi et al. (2014) studied this question.