Automotive Innovation ›› 2023, Vol. 6 ›› Issue (1): 62-75.doi: 10.1007/s42154-022-00204-1

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Energy Management Optimization Based on Aging Adaptive Functional State Model of Battery for Internal Combustion Engine Vehicles

Weiwei Kong1 · Tianmao Cai1 · Yugong Luo2 · Xiaomin Lian2 · Fachao Jiang1
  

  1. 1. College of Engineering, China Agricultural University, Beijing 100083, China
    2. School of Vehicle and Mobility, Tsinghua University, Beijing 100084, China
  • 出版日期:2023-03-06 发布日期:2023-03-06

Energy Management Optimization Based on Aging Adaptive Functional State Model of Battery for Internal Combustion Engine Vehicles

Weiwei Kong1 · Tianmao Cai1 · Yugong Luo2 · Xiaomin Lian2 · Fachao Jiang1   

  1. 1. College of Engineering, China Agricultural University, Beijing 100083, China
    2. School of Vehicle and Mobility, Tsinghua University, Beijing 100084, China
  • Online:2023-03-06 Published:2023-03-06

摘要: This paper presents an energy management optimization system based on an adaptive functional state model of battery aging for internal combustion engine vehicles (ICEVs). First, the functional characteristics of batteries in ICEVs are investigated. Then, an adaptive functional state model is proposed to represent battery aging throughout the entire battery service life. A battery protection scheme is developed, including over-discharge and graded over-current protection to improve battery safety. A model-based energy management strategy is synthesized to comprehensively optimize fuel economy, battery life preservation, and vehicle performance. The performance of the proposed scheme was examined under comprehensive test scenarios based on field and bench tests. The results show that the proposed energy management algorithm can effectively improve fuel economy.

Abstract: This paper presents an energy management optimization system based on an adaptive functional state model of battery aging for internal combustion engine vehicles (ICEVs). First, the functional characteristics of batteries in ICEVs are investigated. Then, an adaptive functional state model is proposed to represent battery aging throughout the entire battery service life. A battery protection scheme is developed, including over-discharge and graded over-current protection to improve battery safety. A model-based energy management strategy is synthesized to comprehensively optimize fuel economy, battery life preservation, and vehicle performance. The performance of the proposed scheme was examined under comprehensive test scenarios based on field and bench tests. The results show that the proposed energy management algorithm can effectively improve fuel economy.