Journal of Jilin University(Engineering and Technology Edition) ›› 2022, Vol. 52 ›› Issue (12): 2796-2805.doi: 10.13229/j.cnki.jdxbgxb20210435

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Regenerative braking optimization strategy considering battery state of power

Xing-tao LIU1,2(),Si-yuan LIN1,Ji WU1,2(),Yao HE3,Xin-tian LIU3   

  1. 1.Department of Vehicle Engineering,Hefei University of Technology,Hefei 230009,China
    2.Anhui Intelligent Vehicle Engineering Laboratory,Hefei 230009,China
    3.Automotive Research Institute,Hefei University of Technology,Hefei 230002,China
  • Received:2021-05-17 Online:2022-12-01 Published:2022-12-08
  • Contact: Ji WU E-mail:xingtao.liu@hfut.edu.cn;wu.ji@hfut.edu.cn

Abstract:

The existing regenerative braking strategy has insufficient constraints on the battery, resulting in low energy recovery efficiency, battery overcharge, and other problems. To protect the battery and improve the regenerative braking efficiency, the state of power of the battery has been fully considered. An optimized regenerative braking strategy has been proposed using the dynamic programming algorithm to obtain the optimal solution. Under fixed working condition and NEDC working condition,Compared with the method based on the I curve, the strategy proposed improves the economy by more than 36% and the stability by more than 48% compared with the single objective method. In addition, test experiments verify the practicability of the proposed strategy.

Key words: automotive engineering, battery electric vehicle, state of power, regenerative braking, dynamic programming

CLC Number: 

  • TM91

Table 1

Parameters of battery electric vehicle"

参 数数值
满载质量/kg1580
整备质量/kg1200
轴距/mm2467
前轮距/mm1480
后轮距/mm987
质心高度/mm500
轮胎半径/mm287
迎风面积/m21.97

空气阻力系数

滚动阻力系数

0.284

0.01

Fig.1

EM efficiency map"

Table 1

Motor parameters of battery electric vehicle"

参 数数值
额定电压/V420
额定转速/(r·min?17500
最大转速/(r·min?110 000
最大工作电流/A220
峰值功率/kW80
峰值转矩/(N·m)240

Fig.2

Thevenin's model"

Fig.3

Diagram of braking force distribution"

Fig.4

Battery state of charge"

Fig.5

Recovery energy"

Fig.6

Stability coefficient"

Table 3

Comparison of the results of three strategies under fixed conditions"

策略最终的SOC/%回收能量/J稳定性系数平均数
考虑稳定性50.199202 9700.1091
单目标50.220230 8570.2123
基于I曲线50.1733148 7960.1081

Fig.7

NEDC cycle conditions"

Fig.8

Energy recovery under NEDC condition"

Table 5

Comparison of the results of three strateies under NEDC condition"

策略回收能量/J稳定性系数平均数

考虑车辆

稳定性

1 201 0080.007 189
单目标1 523 5720.018 16
基于I曲线716 8500.006 349

Fig.9

Battery recovery power under different state of charge"

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