A novel energy management strategy for connected plug-in hybrid electric vehicle using periodic event-triggered mechanism

In the networked environment, it is of prospective significance to design an energy management strategy that improves the vehicle's energy-saving performance and reduces the occupation of communication and computing resources. In this paper, a novel energy management strategy using periodic event-triggered mechanism (PETM) for connected plug-in hybrid electric vehicle (C-PHEV) is proposed. Firstly, the tabu search algorithm is adopted to optimize control parameters combined with the latest driving information. In order to reduce redundant optimization operations, a trigger period that can guarantee ideal control performance is derived. And the cloud monitoring platform monitors the status information of C-PHEV in real time, judging whether the trigger condition of PETM is satisfied. Subsequently, the tabu list is updated every time the optimization process is triggered to speed up the search for the optimal solution. Finally, the comparison is carried out under real-world driving condition. The results indicate that PETM strategy elevates the fuel economy of C-PHEV by 11.191% over rule-based strategy. In the case of comparable fuel economy, the optimization time of PETM strategy saves 97% compared with that of continuous trigger optimization strategy, which fully verifies the superiority of the comprehensive performance of the proposed strategy.