主办:陕西省汽车工程学会
ISSN 1671-7988  CN 61-1394/TH
创刊:1976年

汽车实用技术 ›› 2023, Vol. 48 ›› Issue (24): 1-4.DOI: 10.16638/j.cnki.1671-7988.2023.024.001

• 新能源汽车 •    

考虑电池寿命的插电式混合动力客车的 能量管理策略

戚泽恩,王多辉,栾怡萱   

  1. 长安大学 汽车学院
  • 出版日期:2023-12-30 发布日期:2023-12-30
  • 通讯作者: 戚泽恩
  • 作者简介:戚泽恩(1998-),男,硕士研究生,研究方向为新能源汽车能量管理策略与控制算法,E-mail:qze2024@ 163.com。

Consider the Battery Life of the Plug-in Hybrid Electric Bus Energy Management Strategy

QI Zeen, WANG Duohui, LUAN Yixuan   

  1. School of Automobile, Chang'an University
  • Online:2023-12-30 Published:2023-12-30
  • Contact: QI Zeen

摘要: 文章基于电池寿命模型,针对插电式混合动力客车,旨在建立一种考虑电池老化成本 的能量管理策略,以进一步提高车辆的经济性能。首先构建了插电式混合动力客车的动力系 统后向仿真模型,然后构建了基于实验数据来计算电池容量衰减的电池寿命半经验模型。其 次以能耗成本和电池老化成本为指标建立目标函数,最后基于模型预测控制的框架,制定了 考虑电池寿命的能量管理策略。仿真结果表明,该策略通过优化动力电池输出功率与电子控 制单元开启次数,延缓了电池的衰老速率,降低了电池的老化成本,其经济性相较于不考虑 电池老化的能量管理策略,约提升 1.51%,具有一定的实用意义。

关键词: 插电式混合动力客车;能量管理;模型预测控制;电池寿命

Abstract: Based on the battery life model, this paper aims to establish an energy management strategy considering the cost of battery aging for plug-in hybrid electric buses to further improve the economic performance of vehicles. Firstly, the backward simulation model of the power system of the plug-in hybrid electric bus is constructed, and then the semi-empirical model of battery life based on the experimental data to calculate the attenuation of battery capacity is constructed. Secondly, the objective function of energy consumption cost and battery aging cost is established, and the energy management strategy considering battery life is developed based on the framework of model predictive control at last. The simulation results show that this strategy can delay the aging rate of the battery and reduce the aging cost of the battery by optimizing the output power of the battery and the number of turning on of the electronic control unit. Compared with the energy management strategy without considering the aging of the battery, its economy is improved by about 1.51%, which has certain practical significance.

Key words: Plug-in hybrid electric bus; Energy management; Model predictive control; Battery life