With the rapid growth of the new energy vehicle sector, plug-in hybrid electric buses (PHEBs) have become an important part of public transportation. This research proposes a model predictive control (MPC) strategy for PHEB in the car-following scenarios based on driving style detection, which comprehensively examines fuel economy and safety. The approach begins by defining and computing a set of driving style indicators, which are used to classify driver behavior and dynamically adjust the equivalent factor (EF) in the equivalent consumption minimization strategy (ECMS). Then, a total cost function is formulated, which includes the cost of safety and fuel consumption. This method considers the two costs together to obtain the optimal cost function. Furthermore, the proposed energy management strategy (EMS) is tested under two standard operating conditions UDDS and CLTC, and compared with the conventional ECMS. Simulation results illustrate that with sufficient safe following distances, this method is effective in reducing overall energy use by 8.96% for aggressive drivers and slightly less for conservative drivers. Hardware-in-the-loop (HIL) test results confirm that the achieved fuel economy is commensurate with theoretical expectations.
Wang et al. (Fri,) studied this question.