Event-triggered intelligent energy management strategy for plug-in hybrid electric buses based on vehicle cloud optimisation

Energy management strategy (EMS) of plug-in hybrid electric buses (PHEBs) has a very important impact on the fuel economy. Currently there is still huge room to improve the performance of EMS, regarding the optimisation and real-time application potentials. With the rapid development of intelligent transportation systems, the emerging technologies, such as telematics, remote vehicle monitoring, cloud optimisation, and so on, provide an opportunity to realize this goal. Based on this, this study proposes an event-triggered intelligent EMS for PHEBs. Taking the demand torque of PHEB and the battery's stateof- charge as the inputs, and the electric motor torque as the output, triangle and trapezoid membership functions are chosen to construct a specialised fuzzy controller to accomplish torque split task in the studied PHEB. To further improve the fuzzy controller, an enhanced genetic algorithm is proposed to optimize its membership function parameters. Furthermore, to reduce the calculated load in the vehicle cloud optimisation process, an event-triggered mechanism is introduced. Finally, the proposed strategy is verified, and results show that the proposed strategy improves the fuel economy of the studied PHEB by 19% and 22% over that using the rule-based strategy, under the real-world driving cycle and China typical urban driving cycle, respectively.