考虑电池电-热-放电深度的并联PHEV能量管理策略研究

doi:10.19562/j.chinasae.qcgc.2021.06.001

Abstract

Abstract:

Considering the influence of battery aging in the design of energy management strategy of plug?in hybrid electric vehicles （PHEVs） is of great significance for improving the vehicle economy. An energy management strategy is proposed for parallel PHEVs equipped with automatic mechanical transmission while considering triple coupled factors of electric?thermal?depth?of?discharge which influence battery aging， and model predictive control （MPC） is used to achieve real?time co?optimization of gear?shifting and torque distribution. Firstly， the optimal depth of battery discharge over the entire trip is identified based on historical speed profiles and battery aging dynamics. Secondly， with the optimal depth?of?discharge， the battery discharge planning and reference SOC in the preview horizon are established where the Pontryagin minimum principle （PMP） is leveraged to solve the co?optimization problem. Then， it is compared with the MPC without considering battery aging， one?dimensional MPC （1D?MPC） where a scheduled gear?shifting policy is used， and MPC with the dynamic programming based optimization method. The results show that the following ：（1） Optimizing the gear?shifting for parallel PHEVs can effectively reduce the battery aging cost；（2） Compared with the one?dimensional model predictive control strategy （1D?MPC） with regular shift strategy， the two?dimensional model predictive control strategy （2D?MPC） with simultaneous optimization of gear selection and torque distribution is conducive to reduce the battery core temperature and aging cost；（3） Compared with the rule?based CD?CS strategy， the proposed 2D?MPC method can reduce the total cost （the sum of energy consumption cost and battery aging cost） by 28.2 %.

Key words: parallel plug?in hybrid electric vehicle, energy management, battery aging, model predictive control, depth?of?discharge

Shaobo Xie,Kangkang Zhang,Qiankun Zhang,Huiran Luo. Study on Energy Management Strategy for Parallel Plug⁃in Hybrid Electric Vehicles Considering Battery Electric⁃Thermal⁃Depth⁃of⁃Discharge[J].Automotive Engineering, 2021, 43(6): 791-798.

Figures/Tables 20

References 15

1	解少博，刘通，李会灵，等. 基于马尔科夫链的并联PHEB预测型能量管理策略研究［J］. 汽车工程， 2018， 40（8）： 871-877.
	XIE S B. LIU T， LI H L，et al. A study on predictive energy management strategy for a piug⁃in hybrid electric bus based on markov chain ［J］.Automotive Engineering， 2018，40（8）：871-877.
2	LIN C C， PENG H， GRIZZLE J W， et al. Power management strategy for a parallel hybrid electric truck［J］. IEEE Transactions on Control Systems Technology2003， 11 （6）： 839-849.
3	KIM N， CHA S W， PENG H. Optimal control of hybrid electric vehicles based on Pontryagin's minimum principle［J］. IEEE Transactions on Control Systems and Technology， 2011， 19（5）： 1279-1287.
4	SERRAO L， ONORI S， RIZZONI G. ECMS as a realization of Pontryagin's minimum principle for HEV control［C］. American Control Conference （ACC）， 2009： 3964-3969.
5	LI L， YOU S， YANG C， et al. Driving⁃behavior⁃aware stochastic model predictive control for plug⁃in hybrid electric buses［J］. Applied Energy， 2016， 162： 868-879.
6	XIE S， HU X， QI S， et al. Model predictive energy management for plug⁃in hybrid electric vehicles considering optimal battery depth of discharge［J］. Energy， 2019， 173： 667-678.
7	BLOOM I， COLE B W， SOHN J J， et al. An accelerated calendar and cycle life study of Li-ion cells［J］. Journal of Power Sources， 2001， 101（2）： 238-247.
8	EBBESEN S， ELBERT P， GUZZELLA L. Battery state⁃of⁃health perceptive energy management for hybrid electric vehicles［J］. IEEE Transactions on Vehicular Technology， 2012， 61（7）： 2893-2900.
9	PADOVANI T M， DEBERT M， COLIN G， et al. Optimal energy management strategy including battery health through thermal management for hybrid vehicles［J］. IFAC Proceedings Volumes， 2013， 46（21）： 384-389.
10	LIU T， ZOU Y， LIU D. Energy management for battery electric vehicle with automated mechanical transmission［J］. International Journal of Vehicle Design， 2015， 70（1）： 98-112.
11	DU R， HU X， XIE S， et al. Battery aging⁃and temperature⁃aware predictive energy management for hybrid electric vehicles［J］. Journal of Power Sources， 2020， 473： 228568.
12	PEREZ H E， HU X， DEY S， et al. Optimal charging of Li⁃ion batteries with coupled electro⁃thermal⁃aging dynamics［J］. IEEE Transactions on Vehicular Technology， 2017， 66（9）： 7761-7770.
13	WANG J， LIU P， HICKS⁃GAMER J， et al. Cycle⁃life model for graphite⁃LiFePO4 cells［J］. Journal of Power Sources， 2011， 196（8）： 3942-3948.
14	SERRAO L， ONORI S， SCIARRETTA A， et al. Optimal energy management of hybrid electric vehicles including battery aging［C］. Proceedings of the 2011 American Control Conference. IEEE， 2011： 2125-2130.
15	XIE S， HU X， XIN Z， et al. Pontryagin’s minimum principle based model predictive control of energy management for a plug⁃in hybrid electric bus［J］. Applied Energy， 2019， 236： 893-905.

[1]	SHEN Zhe, WANG Yi-Gang, YANG Zhi-Gang, LI Fang-Xu. [J]. , 2016, 38(12): 1440 -1445 .
[2]	ZENG Bi-Qiang, GAO Ji-Dong, PENG Wei, SUN Zhen-Dong. [J]. , 2016, 38(12): 1446 -1451 .
[3]	LIU Hui, WANG Xiao-Jie, XIANG Chang-Le. [J]. , 2016, 38(12): 1483 -1487 .
[4]	CHEN Wu-Wei, DENG Shu-Chao, HUANG He, XIE You-Hao. [J]. , 2016, 38(12): 1488 -1493 .
[5]	PENG Qian-Lei, GUI Liang-Jin, FAN Zi-Jie. [J]. , 2016, 38(12): 1500 -1507 .
[6]	DONG Zhu-Rong, ZHANG Xin, HU Song-Hua, QIU Hao. [J]. , 2017, 39(1): 79 -85 .
[7]	SHI Hai-Min, YU Xiao-Li, LU Guo-Dong, HUANG Yu-Qi, LIU Zhen-Tao, HUANG Rui. [J]. , 2017, 39(1): 102 -106 .
[8]	QIN Chao-Ju, YANG Zhen-Zhong, ZHANG Wei-Zheng, SONG Li-Ye, YUAN Yan-Peng. [J]. , 2017, 39(2): 133 -137 .
[9]	ZHANG Guan-Jun, ZHAO Xin-Feng, CAO Li-Bo. [J]. , 2017, 39(2): 150 -158 .
[10]	CAO Li-Bo, HU Yuan, YAN Ling-Bo, PENG Yu, SHI Xiang-南. [J]. , 2017, 39(2): 174 -180 .

项目	参数	数值
整车	整备质量/kg	16 000
整车	主减速器速比	6.2
5-挡 AMT	传动比	6.9/3.83/2.32/1.49/1
电池	容量/（A·h）	100
电池	电压/V	537.6

速度谱	FC/L	EC/（kW·h）	BAC/CNY	总费用/CNY	ΔT/K	ODOD
No.1	7.52	24.36	17.72	80.23	1.21	0.448 8
No.2	7.12	24.95	17.68	78.35	1.56	0.459 8
No.3	7.74	23.28	17.36	80.23	1.27	0.428 6
No.4	7.10	25.08	17.13	77.79	1.39	0.462 1

方法	FC/L	EC/ （kW·h）	BAC/ CNY	总费用/CNY	ΔT/K	最终 SOC	计算时间/s
CD?CS	9.70	31.93	35.93	116.99	6.92	0.309 6	19
DP?w/o	6.00	32.28	20.95	81.10	2.63	0.302 8	13 324
PMP?w/o	5.96	32.44	21.01	81.08	2.66	0.300 1	70
PMP?w	7.65	24.32	17.36	80.59	1.48	0.451 8	56
1D?MPC?w/o	6.56	33.19	21.76	85.86	3.02	0.305 6	119
1D?MPC?w	8.24	25.24	18.27	85.58	1.96	0.456 3	121
2D?MPC?w/o	6.65	32.68	20.44	84.63	2.59	0.303 3	131
2D?MPC?w	8.28	24.58	17.05	84.06	1.57	0.454 0	135

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[8]	Bin Zhang,Yuan Zou,Xudong Zhang,Fengchun Sun,Zhe Wu,Yihao Meng. Research on Trajectory Tracking Control of Hybrid Tracked Unmanned Platform [J]. Automotive Engineering, 2023, 45(4): 579-587.
[9]	Ziwei Zhang,Ling Zheng,Yinong Li,Xuqiang Qiao,Hao Zheng,Kan Wang. A Multi-objective Adaptive Cruise Control Strategy for Autonomous Vehicle Considering Uncertain Movements of Preceding Vehicle [J]. Automotive Engineering, 2023, 45(3): 361-371.
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Study on Energy Management Strategy for Parallel Plug⁃in Hybrid Electric Vehicles Considering Battery Electric⁃Thermal⁃Depth⁃of⁃Discharge

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