智能网联混合动力汽车队列模型预测分层控制*

doi:10.19562/j.chinasae.qcgc.2020.10.001

汽车工程 ›› 2020, Vol. 42 ›› Issue (10): 1293-1301.doi: 10.19562/j.chinasae.qcgc.2020.10.001

• • 下一篇

智能网联混合动力汽车队列模型预测分层控制^*

郭景华^1,2, 王班^1,2, 王靖瑶^1,2, 罗禹贡³, 李克强³

1.厦门大学航空航天学院,厦门 361005;
2.厦门大学深圳研究院,深圳 518000;
3.清华大学车辆与运载学院,北京 100084

收稿日期:2019-11-19 修回日期:2020-01-29 出版日期:2020-10-25 发布日期:2020-10-26
通讯作者: 郭景华,副教授,博士,E-mail:guojh@xmu.edu.cn。
基金资助:
* 国家重点研发计划(2016YFB0100900)、深圳市科技计划基础研究(JCYJ20180306172720364)和中央高校基本科研业务费专项资金(20720190015)资助。

Hierarchical Model Predictive Control of Intelligent and Connected Hybrid Electric Vehicles Platooning

Guo Jinghua^1,2, Wang Ban^1,2, Wang Jingyao^1,2, Luo Yugong³, Li Keqiang³

1. School of Aerospace Engineering, Xiamen University, Xiamen 361005;
2. Shenzhen Research Institute, Xiamen University, Shenzhen 518000;
3. School of Vehicle and Mobility,Tsinghua University, Beijing 100084

Received:2019-11-19 Revised:2020-01-29 Online:2020-10-25 Published:2020-10-26

摘要/Abstract

摘要： 提出了一种智能网联混合动力汽车队列的模型预测分层控制方法,有效提高了队列的安全性、燃油经济性和乘坐舒适性。首先,建立了可准确表征智能网联混合动力汽车队列行驶中多过程耦合特性的动力学模型。然后,针对智能网联混合动力汽车队列系统的非线性和混杂特征,构建了智能网联混合动力汽车队列的模型预测分层控制构架。上层控制器利用所建立的基于反馈校正的鲁棒预测模型,消除由于参数误差或车辆动态特性变化引起的模型失配现象,增强预测模型的准确性和鲁棒性,进而实现安全性、经济性和舒适性多目标协调控制和智能网联混合动力汽车队列期望加速度的在线优化;下层控制器利用队列中智能网联混合动力汽车多系统动态协调控制器,实现发动机和电机两个动力源的准确与协调控制。最后,试验结果表明:所提出的模型预测分层控制系统在提高队列中车辆的跟踪能力的同时,明显改善了车辆的燃油经济性和乘坐舒适性。

关键词: 智能网联混合动力汽车, 队列, 模型预测控制, 燃油经济性, 协同控制

Abstract: This paper presents a hierarchical model predictive control method for intelligent connected hybrid electric vehicles (ICHEVs) platooning to improve the safety, fuel economy, and riding comfort. Firstly, a dynamic model is established to accurately characterize the multi-process coupling characteristics of ICHEVs platooning. Then, a hierarchical model predictive controller (HMPC) for ICHEVs platooning is established considering the nonlinear and discrete characteristics of ICHEVs platooning. The upper layer controller builds a robust prediction model based on feedback correction to eliminate model mismatch caused by parameter errors or vehicle dynamic characteristics changes and improve the accuracy and robustness of the prediction model so as to realize the multi-objective coordinated control of safety, economy, and comfort as well as the online optimization of the expected acceleration of ICHEVs platooning. The lower layer controller utilizes the multi-system dynamic coordination controller in the ICHEVs platooning to realize accurate and coordinated control of the two power sources of the engine and motor. Finally, the test results show that the proposed hierarchical MPC system can improve the tracking capability in the platooning and significantly improve fuel economy and riding comfort of ICHEVs

Key words: intelligent and connected hybrid electric vehicles, platooning , model predictive control, fuel economy, coordinated control

郭景华, 王班, 王靖瑶, 罗禹贡, 李克强. 智能网联混合动力汽车队列模型预测分层控制^*[J]. 汽车工程, 2020, 42(10): 1293-1301.

Guo Jinghua, Wang Ban, Wang Jingyao, Luo Yugong, Li Keqiang. Hierarchical Model Predictive Control of Intelligent and Connected Hybrid Electric Vehicles Platooning[J]. Automotive Engineering, 2020, 42(10): 1293-1301.

参考文献

[1] 郭景华,李克强,罗禹贡.智能车辆运动控制研究综述[J]. 汽车安全与节能学报, 2016(7): 151-159.
GUO J H, LI K Q, LUO Y G. Review on the research of motion control for intelligent vehicles[J]. Journal of Automotive Safety and Energy, 2016(7): 151-159.
[2] VAJEDI M, AZAD N L. Ecological adaptive cruise controller for plug-in hybrid electric vehicles using nonlinear model predictive control [J]. IEEE Transactions on Intelligent Transportation Systems, 2016, 17: 113-122.
[3] QIU S, QIU L, QIAN L, et al. Hierarchical energy management control strategies for connected hybrid electric vehicles considering efficiencies feedback [J]. Simulation Modelling Practice and Theory, 2019, 90: 1-15.
[4] QIAN L J, QIU L H, ABDOLLAHI Z, et al. Fuel efficient model predictive control strategies for a group of connected vehicles incorporating vertical vibration [J]. Science China, 2017: 1732-1746.
[5] HOMCHAUDHURI B, LIN R, PISU P. Hierarchical control strategies for energy management of connected hybrid electric vehicles in urban roads [J]. Transportation Research Part C: Emerging Technologies, 2016, 62: 70-86.
[6] KAYACAN E. Multi-objective H_∞ control for string stability of cooperative adaptive cruise control systems [J]. IEEE Transactions on Intelligent Vehicles, 2017: 1-10.
[7] GUO J H, LUO Y G, LI K Q. Adaptive fuzzy sliding mode control for coordinated longitudinal and lateral motions of multiple autonomous vehicles in a platoon [J]. Science China Technological Sciences, 2017, 60 (4): 576-586.
[8] 解来卿, 罗禹贡, 李升波, 等. 分布式电驱动车辆的ACC协同控制 [J]. 汽车工程, 2018,40(6): 652-658.
XIE L Q, LUO Y G, LI S B, et al. Coordinated control for adaptive cruise control system of distributed drive electric vehicles[J]. Automotive Engineering, 2018,40(6): 652-658.
[9] MAMDOUH M, ABIDO M A. Efficient predictive torque control for induction motor drive [J]. IEEE Transactions on Industrial Electronics, 2019, 66: 6757-6767.
[10] SAKHDARI B, AZAD N L. Adaptive tube-based nonlinear MPC for economic autonomous cruise control of plug-in hybrid electric vehicles [J]. IEEE Transactions on Vehicular Technology, 2018, 67: 11390-11401.
[11] ZHENG Y, LI S E, LI K, et al. Distributed model predictive control for heterogeneous vehicle platoons under unidirectional topologies [J]. IEEE Transactions on Control Systems Technology, 2017, 25: 899-910.
[12] 余世明, 吴赛男, 何德峰. 传感器量程和行驶约束车辆队列模型预测控制 [J]. 信息与控制, 2018,47: 60-67.
YU S M, WU S N, HE D F. Model predictive control of vehicle platoons subject to constraints on limited range of sensors and driving[J]. Information and Control, 2018,47: 60-67.
[13] 李升波, 王建强, 李克强, 等. MPC实用化问题处理及在车辆ACC中的应用 [J]. 清华大学学报(自然科学版), 2010, 50: 645-648.
LI S B, WANG J Q, LI K Q, et al. Processing of MPC practical problems and its application to vehicular adaptive cruise control systems[J]. Journal of Tsinghua University (Science and Technology), 2010, 50: 645-648.
[14] YANG H, GUO M, XIA Y, et al. Trajectory tracking for wheeled mobile robots via model predictive control with softening constraints [J]. IET Control Theory & Applications, 2018, 12: 206-214.
[15] GUO J H, LUO Y G, LI K Q. Integrated adaptive dynamic surface car-following control for nonholonomic autonomous electric vehicles[J]. Science China Technology Sciences, 2017, 60(8):1221-1230.

智能网联混合动力汽车队列模型预测分层控制^*

Hierarchical Model Predictive Control of Intelligent and Connected Hybrid Electric Vehicles Platooning

PDF (PC)

赞

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

Metrics

本文评价

推荐阅读 10

[1]	梅润,褚端峰,高博麟,李克强,丛炜,陈超义. 基于云控系统的队列预测性巡航与换道决策[J]. 汽车工程, 2023, 45(8): 1299-1308.
[2]	边有钢,张田田,谢和平,秦洪懋,杨泽宇. 车辆队列抗扰抗内切协同路径跟踪控制[J]. 汽车工程, 2023, 45(8): 1320-1332.
[3]	王明,唐小林,杨凯,李国法,胡晓松. 考虑预测风险的自动驾驶车辆运动规划方法[J]. 汽车工程, 2023, 45(8): 1362-1372.
[4]	高锋,冯德福,胡秋霞. 面向NMPC运动规划系统的数值优化加速技术[J]. 汽车工程, 2023, 45(8): 1438-1447.
[5]	林程, 汪博文, 吕沛原, 宫新乐, 于潇. 面向变曲率道路的自动驾驶汽车换道博弈运动规划与协同控制研究[J]. 汽车工程, 2023, 45(7): 1099-1111.
[6]	李军, 周伟, 唐爽. 基于自适应拟合的智能车换道避障轨迹规划[J]. 汽车工程, 2023, 45(7): 1174-1183.
[7]	查云飞,吕小龙,陈慧勤,易迎春,王燕燕. 基于路面附着系数估计的车辆轨迹跟踪控制[J]. 汽车工程, 2023, 45(6): 1010-1021.
[8]	贺伊琳,马建,杨舒凯,郑威,薛启帆. 融合预瞄特性的智能电动汽车稳定性模型预测控制研究[J]. 汽车工程, 2023, 45(5): 719-734.
[9]	周兵,魏佳宝,柴天,吴晓建,王鹤. 基于最优方法的碰后辅助驾驶控制策略[J]. 汽车工程, 2023, 45(4): 561-571.
[10]	张彬,邹渊,张旭东,孙逢春,吴喆,孟逸豪. 混动履带式无人平台轨迹跟踪控制研究[J]. 汽车工程, 2023, 45(4): 579-587.
[11]	张紫微,郑玲,李以农,乔旭强,郑浩,王戡. 考虑前车运动不确定性的多目标自适应巡航控制[J]. 汽车工程, 2023, 45(3): 361-371.
[12]	李子先,潘世举,徐友春. 8轮分布式电驱动车辆AFS和DYC协同控制[J]. 汽车工程, 2023, 45(3): 409-420.
[13]	贺林,徐子昂,黄春荣,龚超,李书华,石琴. 线控转向系统转角预测滑模控制算法研究[J]. 汽车工程, 2023, 45(12): 2200-2208.
[14]	胡丹丹,尹鹏飞,牛国臣,赵金聚. 非结构化道路下离轴式拖挂车辆主动避障控制研究[J]. 汽车工程, 2023, 45(12): 2318-2329.
[15]	宋强,王冠峰,商赫,张念忠. 基于多参数控制的分布式驱动电动汽车操纵稳定性控制策略研究[J]. 汽车工程, 2023, 45(11): 2104-2112.