Exploiting driving history for optimising the Energy Management in plug-in Hybrid Electric Vehicles

This paper proposes an Energy Management Strategy (EMS) for a plug-in parallel Hybrid Electric Vehicle (pHEV) with the goal of minimising fuel consumption while fulfilling constraint on terminal battery State-of-Charge (SoC). The proposed strategy assumes that route was previously covered several times by vehicle, in order to extract information about feasible operating conditions driving cycle. Note this situation is usual commuting and daily trips. In sense, history vehicle speeds positions are used build space-dependent transition probability matrices latter cycle estimation means Markov-Chain approach. Once estimated, torque-split problem hybrid powertrain addressed using Equivalent Consumption Minimisation (ECMS), where associated boundary value finding weighting factor between cost drives SoC desired level at end estimated solved applied system. Finally, make up error, ECMS recurrently. For sake clarity, initially developed analysed modelling environment. Then tests engine-in-the-loop basis done validation. show potential strategy, results presented trade-off terminal-SoC four different methods: optimal power-split requires priori knowledge benchmarking, online fixed (average speed profile obtained from previous trips route), method, i.e. dynamic finally rule-based charge depleting sustaining strategy. demonstrate outperforms rest applicable methods.