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Energy Management Strategy Based on Model Prediction Control for Hybrid Batteries/ Supercapacitors Electrical Vehicle

机译:基于模型预测控制的混合动力电池/超级电容器电动汽车能源管理策略

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摘要

In this paper, an energy management strategy (EMS) for hybrid batteries and supercapacitor (SCs) electric vehicles (HBSEV) is considered for extending the batteries lifespan and lifting the power performance of HBSEV. In detail, firstly, vehicle dynamics model and hybrid energy storage source (HESS) models including batteries and SCs are adapted and simplified as fundamental of model prediction control (MPC) approach. Secondly, the EMS of HBSEV is designed for reducing batteries power variation and maintaining SCs SOC in a proper value based on MPC method combining adaptive method. That can enhance batteries lifespan and power performance. Finally, simulation results based on the proposed EMS are given, which show batteries lifespan and power performance for HBSEV are improved obviously compared with a real time average (RTA) strategy. Meanwhile, the SOC of batteries and SCs are maintained in a proper range.
机译:本文考虑了混合动力电池和超级电容器(SCs)电动汽车(HBSEV)的能源管理策略(EMS),以延长电池寿命并提高HBSEV的动力性能。详细地,首先,将包括电池和SC的车辆动力学模型和混合能量存储源(HESS)模型作为模型预测控制(MPC)方法的基础进行调整和简化。其次,基于MPC方法结合自适应方法,将HBSEV的EMS设计为减少电池功率变化并将SCs SOC保持在适当的值。这样可以延长电池寿命和电源性能。最后,给出了基于所提出的EMS的仿真结果,结果表明,与实时平均(RTA)策略相比,HBSEV的电池寿命和功率性能都有明显提高。同时,电池和SC的SOC保持在适当的范围内。

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