Energy management strategy (EMS) plays a vital role in improving the fuel economy of plug-in hybrid electric vehicle (PHEV). By virtue of excellent real-time performance, deterministic rule-based (DRB) method is widely introduced into EMS for the control of actual PHEV. However, fixed parameters are usually used as thresholds in traditional DBR control, which makes it difficult for PHEV to achieve excellent fuel economy. To solve this problem, relevant parameters need to be optimized, but the resulting time-consuming and complex process is an obstacle for practical application of this scheme. Nowadays, the emergence of technologies, such as wireless communication, remote monitoring and so on, has gave birth to the concept of cyber-physical system (CPS). It provides an opportunity to optimize parameters of DRB EMS. Motivated by this, this paper proposes a cyber physical energy optimization control design for PHEVs. Among them, DRB control is designed to allocate power tasks for the engine and electric motor (EM), according to state of the charge (SOC) of battery and demand power of vehicle. Moreover, to further improve performance of EMS, an enhanced firework algorithm (EFWA) is firstly proposed to optimize parameters of controller. Compared with original algorithm, a novel selection mechanism for non-CF is introduced in EFWA. It makes the excellent parameters could be obtained in a shorter time, which is more suitable for the complex optimization of EMS. Finally, the effectiveness of proposed EMS is verified and evaluated. The results show that it improves the fuel economy of PHEV by 10% and 12% over that using the unoptimized rule-based EMS, under the China typical urban driving cycle and real-world driving cycle, respectively.

中文翻译：

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基于增强烟花算法的插电式混合动力汽车网络物理能优化控制设计

能源管理策略（EMS）在提高插电式混合动力汽车（PHEV）的燃油经济性方面起着至关重要的作用。由于出色的实时性能，基于确定性基于规则（DRB）的方法已广泛引入EMS中以控制实际的PHEV。但是，固定参数通常在传统的DBR控制中用作阈值，这使得PHEV难以实现出色的燃油经济性。为了解决该问题，需要优化相关参数，但是由此产生的耗时且复杂的过程阻碍了该方案的实际应用。如今，诸如无线通信，远程监控等技术的出现催生了网络物理系统（CPS）的概念。它提供了优化DRB EMS参数的机会。受此启发，本文提出了一种针对插电式混合动力汽车的网络物理能量优化控制设计。其中，DRB控制旨在根据电池的充电状态（SOC）和车辆的需求功率为发动机和电动机（EM）分配动力任务。此外，为了进一步提高EMS的性能，首先提出了一种增强的烟火算法（EFWA）来优化控制器的参数。与原始算法相比，在EFWA中引入了一种新的非CF选择机制。这使得可以在更短的时间内获得优异的参数，更适合于EMS的复杂优化。最后，对所提出的EMS的有效性进行了验证和评估。结果表明，与未优化的基于规则的EMS相比，PHEV的燃油经济性提高了10％和12％，