汽车工程 ›› 2021, Vol. 43 ›› Issue (5): 657-666.doi: 10.19562/j.chinasae.qcgc.2021.05.003

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基于电池寿命预测控制的履带车辆能量管理

韩立金1,2,刘辉1,2(),刘聪1,2,刘宝帅1,2,张聪1,2   

  1. 1.北京理工大学机械与车辆学院,北京 100081
    2.北京理工大学前沿技术研究院,济南 250307
  • 收稿日期:2020-11-20 出版日期:2021-05-25 发布日期:2021-05-18
  • 通讯作者: 刘辉 E-mail:lh@bit.edu.cn
  • 基金资助:
    国家自然科学基金(51775040)

Energy Management of Tracked Vehicles Based on Battery Life Prediction Control

Lijin Han1,2,Hui Liu1,2(),Cong Liu1,2,Baoshuai Liu1,2,Cong Zhang1,2   

  1. 1.School of Mechanical Engineering,Beijing Institute of Technology,Beijing 100081
    2.Institute of Advanced Technology,Beijing Institute of Technology,Jinan 250307
  • Received:2020-11-20 Online:2021-05-25 Published:2021-05-18
  • Contact: Hui Liu E-mail:lh@bit.edu.cn

摘要:

为改善串联式混合动力履带车辆在复杂行驶环境中的燃油经济性和动力性,本文中提出了一种考虑电池寿命影响的基于非线性模型预测控制的能量管理策略。首先,考虑到电池不同输出功率会对电池温度产生影响,建立电池的2阶 RC 模型、热电耦合模型和寿命模型。然后,基于电池的2阶RC模型建立了用以描述车辆前功率链未来动态的预测模型,同时考虑到电池寿命的影响,设计了一种基于非线性模型预测控制的能量管理策略。提出了一种电耗与油耗之间转换因子的计算方式,使转换因子能够自适应车辆不同的行驶工况和能量管理策略。最后,搭建了仿真及硬件在环测试平台,在3种典型工况下验证了本文中所提出的能量管理策略的有效性。

关键词: 串联式混合动力履带车辆, 电池寿命, 非线性模型预测控制, 能量管理

Abstract:

In order to improve the fuel economy and power performance of series hybrid tracked vehicles in complex driving environment, an energy management strategy based on nonlinear model predictive control (NMPC) considering the influence of battery life is proposed in this paper. Firstly, considering the influence of different output power on the battery temperature, the second?order RC model, thermoelectric coupling model and life model of the battery are established. Then, based on the second?order RC model of the battery, the prediction model is established to describe the future dynamics of the vehicle front power chain. At the same time, considering the influence of the battery life, an energy management strategy based on the nonlinear model predictive control is designed. A calculation method of conversion factor between power consumption and fuel consumption is proposed to make the conversion factor adaptive to different driving conditions and energy management strategies of the vehicle. Finally, the simulation and hardware in?loop test platform are built to verify the effectiveness of the proposed energy management strategy under three typical working conditions.

Key words: series hybrid tracked vehicles, battery life, NMPC, energy management