Efficient energy management for a plug-in hybrid electric vehicle considering motor current alert mechanism

Plug-in hybrid electric vehicle (PHEV), due to its energy cleanliness and sustainability, has gained plenty of research in cleaner production. Energy management strategy (EMS) can govern the energy flow and reduce fossil fuels wasting. Most PHEVs prefer their motors working prolonged time to pursue better fuel-saving performance, and the overcurrent protection (OCP) would easily occur due to the motor taking additional demand power, and it would be a challenge to develop self-examination of EMS and ensure the efficient energy distribution. Thus, this paper proposes an efficient energy management for a PHEV considering motor current alert (MCA) mech-anism. First, an MCA mechanism is originally established for PHEV to prevent large motor currents that persist for a long time, which improves the current sensitivity of EMS. Second, a multi-step Markov chain is used to predict future velocities and a new clustering method for Markov states is designed, which improves the grid clustering method. Third, the cooperative game theory (CGT) of the energy optimization problem is formulated, and its calculation process is implemented by model predictive control (MPC) method. This CGT-MPC can optimize both group profit and personal profit. Finally, the proposed strategy is validated against other baseline strategies in both simulation and bench test. Comparison results show that the proposed strategy can reduce the frequency and duration of large motor current occurrences by 71% under complex driving conditions, while at most reducing the fuel consumption by 10.28% and electricity consumption bias within 1%.