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An optimal control strategy design for plug-in hybrid electric vehicles based on internet of vehicles

机译:基于车辆的插入式混合动力电动车辆的最优控制策略设计

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This paper presents an approach to the design of an optimal control strategy for plug-in hybrid electric vehicles (PHEVs) incorporating Internet of Vehicles (IoVs). The optimal strategy is designed and implemented by employing a mobile edge computing (MEC) based framework for IoVs. The thresholds in the optimal strategy can be instantaneously optimized by chaotic particle swarm optimization with sequential quadratic programming (CPSO-SQP) in the mobile edge computing units (MECUs). The vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication are adopted in IoV to collect traffic information for a CPSO-SQP based optimization and transmit the optimized control commands to vehicle from MECUs. To guarantee real-time optimal performance, the communication delay in V2V and V2I is decreased via an alternative iterative optimization algorithm (AIOA) approach. The simulation results demonstrate the superior performance of the novel optimal control strategy for PHEV with 9% improvement, compared with the original strategy.(c) 2021 Elsevier Ltd. All rights reserved.
机译:本文提出了一种方法,可以设计一种包含车辆互联网(IOV)的插入式混合动力电动车辆(PHEV)的最佳控制策略。通过使用基于移动边缘计算(MEC)的IOV框架来设计和实现最佳策略。通过在移动边缘计算单元(MECus)中的顺序二次编程(CPSO-SQP)中的混沌粒子群优化可以瞬间优化最佳策略中的阈值。在IOV中采用车辆到车辆(V2V)和基础设施(V2I)通信,以收集基于CPSO-SQP的优化的交通信息,并将优化的控制命令从MECus发送到车辆。为了保证实时最佳性能,通过替代迭代优化算法(AIOA)方法降低V2V和V2I中的通信延迟。仿真结果表明,与原始策略相比,PHEV的新颖最优控制策略的优越性表现为PHEV。(c)2021 Elsevier Ltd.保留所有权利。

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