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Energy management of a power-split plug-in hybrid electric vehicle based on genetic algorithm and quadratic programming

机译:基于遗传算法和二次规划的插电式混合动力汽车能量管理

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摘要

This paper introduces an online and intelligent energy management controller to improve the fuel economy of a power-split plug-in hybrid electric vehicle (PHEV). Based on analytic analysis between fuel-rate and battery current at different driveline power and vehicle speed, quadratic equations are applied to simulate the relationship between battery current and vehicle fuel-rate. The power threshold at which engine is turned on is optimized by genetic algorithm (GA) based on vehicle fuel-rate, battery state of charge (SOC) and driveline power demand. The optimal battery current when the engine is on is calculated using quadratic programming (QP) method. The proposed algorithm can control the battery current effectively, which makes the engine work more efficiently and thus reduce the fuel-consumption. Moreover, the controller is still applicable when the battery is unhealthy. Numerical simulations validated the feasibility of the proposed controller.
机译:本文介绍了一种在线智能能源管理控制器,以改善动力分配插电式混合动力电动汽车(PHEV)的燃油经济性。基于在不同传动系功率和车速下的燃油率和电池电流之间的分析分析,应用二次方程式来模拟电池电流与车辆燃油率之间的关系。遗传算法(GA)根据车辆的燃油费率,电池充电状态(SOC)和传动系统的功率需求,优化了发动机启动的功率阈值。使用二次编程(QP)方法计算发动机启动时的最佳电池电流。该算法可以有效地控制电池电流,使发动机工作效率更高,从而降低了燃油消耗。此外,当电池不健康时,控制器仍然适用。数值模拟验证了该控制器的可行性。

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