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Multi-objective tradeoff optimization of predictive adaptive cruising control for autonomous electric buses: A cyber-physical-energy system approach

机译:自主电动公交车预测自适应巡航控制的多目标权衡优化:一种网络物理 - 能源系统方法

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摘要

Recently, Cyber-Physical System (CPS) has served as a cutting-edge technology for next-generation industrial applications, and is developing rapidly and inspires many application domains. The autonomous electric bus (AEB) that integrates the communication, perception, and control within vehicle dynamics is a typical CPS. However, the energy management is ignored in the vehicle cyber-physical system. Thus, a novelty cyberphysical-energy system (CPES) approach with deep integration and interaction of the cyber system with physical system for the energy management used cruising control is imposed. Under the new CPES framework, the energy consumption and battery capacity degradation are optimized in different driving environment. Simulation results show that the tradeoff optimization control algorithm can keep battery health by optimizing motor operating mode with a slightly penalty on the energy consumption. The total system cost effective analysis shows that the battery service lifetime is improved by about 41.59% with the proposed method, and even with the slightly sacrifice of power consumption, the whole vehicle economy is improved by about 10.08%, compared with the strategy optimizing the power consumption only. Additionally, the equivalent driving distance is significantly extended up to 70.87% when compared to the case that only energy consumption is optimized. Besides, the AEB with CPES framework not only keeps the host vehicle within the safe distance with the preceding vehicle, but optimizes the motion planning as well. The results validate the feasibility and effectiveness of the CPES-based optimization framework, and demonstrate the advantages of the tradeoff optimization energy management strategy.
机译:最近,网络物理系统(CPS)曾担任下一代工业应用的尖端技术,迅速发展并激发许多应用领域。在车辆动态内集成通信,感知和控制的自主电汇总线(AEB)是典型的CP。但是,在车辆网络物理系统中忽略了能量管理。因此,施加了一种新颖的网络耳机 - 能量系统(CPE)方法,具有用于电力系统的网络系统的深度集成和与电力系统用于能量管理使用的巡航控制。在新的CPES框架下,在不同的驾驶环境中优化了能量消耗和电池容量劣化。仿真结果表明,折衷优化控制算法可以通过优化电机操作模式,在能量消耗略有惩罚,通过优化电机运行模式来保持电池运行状况。总系统成本效益分析表明,随着策略优化的策略相比,电池服务寿命率提高了大约41.59%,甚至随着功耗的略微牺牲,甚至略微牺牲了电力消耗。仅限功耗。另外,与仅优化能量消耗的情况相比,等效驱动距离显着延伸至70.87%。此外,具有CPES框架的AEB不仅将主车辆与前车辆的安全距离保持在安全距离内,而且还优化了运动规划。结果验证了基于CPES的优化框架的可行性和有效性,并展示了权衡优化能源管理策略的优势。

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