Welcome to Journal of Automotive Safety and Energy,

Journal of Automotive Safety and Energy ›› 2022, Vol. 13 ›› Issue (3): 580-589.DOI: 10.3969/j.issn.1674-8484.2022.03.020

• Automotive Energy Efficiency and Environment Protection • Previous Articles    

Joint estimation algorithm of SOC-SOP for lithium-ion battery pack in new energy vehicles

XIE Yi1(), JIANG Disheng1, ZHANG Yangjun2, LI Wei1, YANG Rui3, QIAN Yuping2   

  1. 1. College of Mechanical and Vehicular Engineering, Chongqing University, Chongqing 400044, China
    2. State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China
    3. School of Energy and Power Engineering, Chongqing University, Chongqing 400044, China
  • Received:2021-11-30 Revised:2022-06-11 Online:2022-09-30 Published:2022-10-04

Abstract:

The parallel-connected submodule in the serial-parallel connected battery pack was considered as the single battery unit to accurately estimate the state of the lithium-ion battery pack of a new energy vehicle, and the first-order resistance-capacitance model was applied to modelling the battery pack. The adaptive extended Karlman filter (AEKF) and the algorithm with multiple constrains were used for the state of charge- state of power (SOC-SOP) estimation algorithm for the battery pack. Based on the accurate estimation of SOC and multiple-constrain algorithm, SOC-SOP joint estimation algorithm precisely predicted the maximum current through the battery pack and realized the accurate SOP estimation. The results show that the maximum absolute error of the state of charge (SOC) estimate after convergence is only 2.7% under the simulated cyclic highway fuel economy test (HWFET); the state of power (SOP) estimate result is the same as that obtained in the Japanese Electric Vehicle Standard (JEVS) experimental test and the average relative error is less than 3.5%.

Key words: electric vehicle, lithium-ion battery pack, adaptive extended Kalman filtering (AEKF), state of charge(SOC), state of power(SOP)

CLC Number: