并联式混合动力汽车转矩实时分配控制策略研究

吴静波; 李明明; 郭志军; 卢耀真

doi:10.13433/j.cnki.1003-8728.20200301

并联式混合动力汽车转矩实时分配控制策略研究

doi: 10.13433/j.cnki.1003-8728.20200301

1.
河南省汽车节能与新能源重点实验室, 河南洛阳 471000
2.
河南科技大学车辆与交通工程学院, 河南洛阳 471000

基金项目:

河南省科技攻关项目基金 182102210046

详细信息

作者简介:
吴静波(1979-), 讲师, 博士, 研究方向为新能源汽车整车及电驱动系统控制, wubocn2005@163.com

中图分类号: U469.72
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- 被引次数: 0
出版历程
- 收稿日期: 2020-06-22
- 刊出日期: 2022-01-01

A Parallel Hybrid Vehicle Torque Real-time Distribution Control Strategy

1.
Key Laboratory for Automotive Energy Saving and New Energy in Henan Province, Luoyang 471000, He′nan, China
2.
School of Vehicle and Transportation Engineering, Henan University of Science and Technology, Luoyang 471000, He′nan, China

摘要

摘要: 为提高并联式混合动力汽车的整体效率, 确保发动机工作在高效区的同时, 动力电池不会因过度放电对使用寿命造成损害, 对并联式混合动力汽车转矩实时分配控制策略展开研究。以全球轻型车测试规程(WLTP)为循环工况, 采用马尔科夫链模型预测车辆在未来时域内的需求转矩, 以未来时域内电机目标转矩占总需求转矩的百分比和电池SOC值作为输入, 以转矩分配因子作为输出, 建立模糊控制器, 利用自适应模拟退火算法对模糊控制器的输出值进行离线优化, 通过动态调节优化后的转矩分配因子实现需求转矩的合理分配, 确保电池SOC值波动在设定的上下限内。在MATLAB和Cruise仿真平台中, 对本文提出的控制策略进行联合仿真, 并与逻辑门限值控制策略进行对比分析, 结果表明: 相比于逻辑门限值控制策略, 转矩实时分配控制策略不仅保证发动机在高效区工作, 而且电池SOC值的波动范围也保持在与初始值上下的3%以内, 有效的改善了动力电池的使用寿命。
- 混合动力汽车 /
- 转矩分配因子 /
- 马尔科夫链模型 /
- 动态调节
Abstract: In order to improve the overall efficiency of a parallel hybrid vehicle and to ensure that its engine works in the efficient zone so that the power battery will not cause excessive discharge damage to its service life, the parallel hybrid vehicle torque real-time distribution control strategy is studied. With the global light vehicle test procedure as cycle condition, the Markov chain model is used to predict the demand torque of the hybrid vehicle in the future time domain. Wiwh the percentage of the total demand torque to motor target torque and the battery SOC value in the future time domain as input and the torque distribution factor as output, the fuzzy controller is established, the output value of the fuzzy controller is optimized offline with the adaptive analog annealing algorithm, and the torque demand of the fuzzy controller is optimized through dynamical optimization to ensure that the battery SOC value fluctuates within the set upper and lower limits. With the MATLAB and the Cruise simulation platform, the simulation and comparison with the logic threshold control strategy show that the torque real-time distribution control strategy not only ensures that the engine operates in the efficient zone but also keeps the fluctuation range of the battery SOC value within 3% of the initial value, effectively improving the life of the power battery.
- hybrid vehicle /
- torque distribution factor /
- Markov chain model /
- dynamic regulation

HTML全文

图 1 并联式混合动力系统结构示意图

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图 2 发动机燃油消耗图

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图 3 电机效率特性图

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图 4 单体电池充放电内阻和电压随SOC的变化关系

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图 5 马尔科夫转移概率矩阵

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图 6 基于模糊逻辑控制器对需求转矩进行分配的整体流程图

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图 7 电机目标转矩占总需求转矩的百分比的隶属度函数

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图 8 电池SOC的隶属度函数

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图 9 自适应模拟退火算法优化转矩分配因子的流程图

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图 10 并联式混合动力汽车转矩实时分配的控制策略示意图

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图 11 目标车速与实际车速的跟随情况

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图 12 WLTP工况下发动机转矩

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图 13 WLTP工况下驱动电机转矩

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图 14 WLTP工况下SOC变化曲

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图 15 动力电池的充放电电流

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图 16 WLTP工况下发动机工作点

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图 17 WLTP工况下驱动电机的工作点

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图 18 两种能量管理策略下的燃油消耗曲线

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表 1 整车与零部件参数

参数名称	参数值
发动机最大转矩/(N·m)	341
发动机最大功率/kW	65.5
电机最大功率/kW	135
电机最大转矩/(N·m)	130
电池容量/(A·h)	90
电池电压/V	320
DCT速比	3.909, 2.105, 1.387, 1.023, 0.813, 0.673
整车质量/kg	1559
风阻系数C_D	0.7
初始SOC	0.6

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表 2 模糊逻辑控制规则

	NL₂	NS₂	O₂	PS₂	PL₂
NL₁	0.95	0.9	0.85	0.8	0
NS₁	1.0	1.0	0.90	0.85	0.75
O₁	1.05	1.05	0.95	0.95	0.85
PS₁	1.15	1.1	1.0	1.05	0.95
PL₁	1.25	1.15	1.05	1.1	1.0

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参考文献(15)

[1]	张渊博, 王伟达, 项昌乐, 等. 基于模型预测控制的混合动力汽车模式切换中的转矩协调控制策略[J]. 汽车工程, 2018, 40(9): 1040-1047 https://www.cnki.com.cn/Article/CJFDTOTAL-QCGC201809006.htm ZHANG Y B, WANG W D, XIANG C L, et al. A model predictive control-based torque coordinated control strategy for hybrid electric vehicle during mode shifting[J]. Automotive Engineering, 2018, 40(9): 1040-1047 (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-QCGC201809006.htm
[2]	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, 911 https://www.cnki.com.cn/Article/CJFDTOTAL-QCGC201808001.htm XIE S B, LIU T, LI H L, et al. A study on predictive energy management strategy for a plug-in hybrid electric bus based on Markov chain[J]. Automotive Engineering, 2018, 40(8): 871-877, 911 (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-QCGC201808001.htm
[3]	BORHAN H A, VAHIDI A, PHILLIPS A M, et al. Predictive energy management of a power-split hybrid electric vehicle[C]//2009 American Control Conference. St. Louis, MO, USA: IEEE, 2009: 3970-3976
[4]	MENG D W, ZHANG Y, ZHOU M L, et al. Intelligent fuzzy energy management research for a uniaxial parallel hybrid electric vehicle[J]. Computers & Electrical Engineering, 2017, 58: 447-464
[5]	HUANG Y J, WANG H, KHAJEPOUR A, et al. Model predictive control power management strategies for HEVs: A review[J]. Journal of Power Sources, 2017, 341: 91-106 doi: 10.1016/j.jpowsour.2016.11.106
[6]	QIAO Y, SONG Y Z, HUANG K S. A novel control algorithm design for hybrid electric vehicles considering energy consumption and emission performance[J]. Energies, 2019, 12(14): 2698 doi: 10.3390/en12142698
[7]	钱立军, 荆红娟, 邱利宏. 基于随机模型预测控制的四驱混合动力汽车能量管理[J]. 中国机械工程, 2018, 29(11): 1342-1348 doi: 10.3969/j.issn.1004-132X.2018.11.014 QIAN L J, JING H J, QIU L H. Energy management of a 4WD HEV based on SMPC[J]. China Mechanical Engineering, 2018, 29(11): 1342-1348 (in Chinese) doi: 10.3969/j.issn.1004-132X.2018.11.014
[8]	JOŠEVSKI M, ABEL D, MONTI A. Performance study of deterministic and uncertainty-aware predictive energy management strategies for real-world driving cycles[C]//2019 18th European Control Conference (ECC). Naples, Italy: IEEE, 2019
[9]	王钦普, 杜思宇, 李亮, 等. 基于粒子群算法的插电式混合动力客车实时策略[J]. 机械工程学报, 2017, 53(4): 77-84 https://www.cnki.com.cn/Article/CJFDTOTAL-JXXB201704012.htm WANG Q P, DU S Y, LI L, et al. Real-time energy management strategy for plug-in hybrid electric bus on particle swarm optimization algorithm[J]. Journal of Mechanical Engineering, 2017, 53(4): 77-84 (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JXXB201704012.htm
[10]	林歆悠, 冯其高, 张少博. 等效因子离散全局优化的等效燃油瞬时消耗最小策略能量管理策略[J]. 机械工程学报, 2016, 52(20): 102-110 https://www.cnki.com.cn/Article/CJFDTOTAL-JXXB201620014.htm LIN X Y, FENG Q G, ZHANG S B. Global optimal discrete equivalent factor of equivalent fuel consumption minimization strategy based energy management strategy for a series-parallel plug-in hybrid electric vehicle[J]. Journal of Mechanical Engineering, 2016, 52(20): 102-110 (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JXXB201620014.htm
[11]	赵韩, 吴迪. 基于随机模型预测控制的并联式混合动力汽车控制策略研究[J]. 汽车工程, 2014, 36(11): 1289-1294 https://www.cnki.com.cn/Article/CJFDTOTAL-QCGC201411001.htm ZHAO H, WU D. A research on the control strategy of a parallel HEV based on stochastic model predictive control[J]. Automotive Engineering, 2014, 36(11): 1289-1294 (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-QCGC201411001.htm
[12]	黄硕, 李亮, 杨超, 等. 基于规则修正的同轴并联混合动力客车瞬时优化能量分配策略[J]. 机械工程学报, 2014, 50(20): 113-121 https://www.cnki.com.cn/Article/CJFDTOTAL-JXXB201420017.htm HUANG S, LI L, YANG C, et al. Rule correction-based instantaneous optimal energy management strategy for single-shaft parallel hybrid electric bus[J]. Journal of Mechanical Engineering, 2014, 50(20): 113-121 (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JXXB201420017.htm
[13]	李萍, 朱晓璐, 焦晓红. 基于智能优化规则的并联混合动力汽车能量管理策略[J]. 燕山大学学报, 2019, 43(6): 546-553 https://www.cnki.com.cn/Article/CJFDTOTAL-DBZX201906010.htm LI P, ZHU X L, JIAO X H. Parallel hybrid electric vehicle energy management strategy based on intelligent optimization rules[J]. Journal of Yanshan University, 2019, 43(6): 546-553 (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-DBZX201906010.htm
[14]	HMIDI M E, SALEM I B, EL AMRAOUI L. An efficient method for energy management optimization control: Minimizing fuel consumption for hybrid vehicle applications[J]. Transactions of the Institute of Measurement and Control, 2019, 42(1): 69-80
[15]	刘辉, 李训明, 王伟达, 等. 基于最优功率分配因子的插电式混合动力汽车实时能量管理策略研究[J]. 机械工程学报, 2019, 55(4): 91-101 https://www.cnki.com.cn/Article/CJFDTOTAL-JXXB201904012.htm LIU H, LI X M, WANG W D, et al. Optimal power allocation factor based real time energy management strategy for a plug-in hybrid electric vehicle[J]. Journal of Mechanical Engineering, 2019, 55(4): 91-101 (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JXXB201904012.htm