• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2015, Vol. 51 ›› Issue (16): 11-21.doi: 10.3901/JME.2015.16.011

• 汽车非线性动力学及其在复杂机电控制中的应用 • 上一篇    下一篇

混合动力汽车非线性模型预测巡航控制

罗禹贡1, 陈涛2, 李克强1   

  1. 1.清华大学汽车安全与节能国家重点实验室 北京 100084
    2.中国汽车工程研究院股份有限公司 重庆 400039
  • 出版日期:2015-08-20 发布日期:2015-08-20
  • 基金资助:
    科技部国际科技合作计划《面向中美清洁能源合作的电动汽车前沿技术研究》(2010DFA72760)资助项目

Nonlinear Model Predictive Cruise Control of Hybrid Electric Vehicle

LUO Yugong1, CHEN Tao2, LI Keqiang1   

  1. 1.State Key Laboratory of Automotive Safety & Energy, Tsinghua University, Beijing 100084
    2.China Automotive Engineering Research Institute Co., Ltd., Chongqing 400039
  • Online:2015-08-20 Published:2015-08-20

摘要: 针对混合动力汽车巡航过程的跟踪安全性和燃油经济性的优化问题,提出基于非线性模型预测理论的混合动力汽车预测巡航控制策略。考虑发动机燃油效率及电机效率的非线性,提出离线安全与经济性协调预测优化与在线查表相结合的控制系统总体结构。基于车辆行驶距离空间域,建立具有动力学非线性、系统离散性的混合动力系统巡航控制的广义纵向动力学系统模型。以驾驶员稳定跟踪为约束,设计安全性与经济性协调的多性能指标数学量化函数。基于非线性模型预测理论,提出混合动力汽车预测巡航的多目标优化控制算法。为验证所提控制算法的有效性与综合优势,建立前向仿真平台及实车试验平台,仿真及实车结果都表明,所提出的预测巡航控制算法相比常规算法在跟踪安全性和燃油经济性方面具有较大优势。

关键词: 非线性模型预测控制, 混合动力电动汽车, 巡航控制

Abstract: Focusing on the safety and fuel economy improvement of hybrid electric vehicle(HEV)during the adaptive cruise control, a predictive HEV cruise control strategy is proposed based on nonlinear model predictive control method. Considering the nonlinearities of engine fuel efficiency and motor electricity efficiency, the control architecture combines offline predictive optimization of tracking ability and fuel efficiency, and online integration based on offline results is designed. Considering the nonlinearities and discrete characteristics of vehicle dynamics, a position based hybrid longitudinal inter-vehicle dynamics model is developed. Based on the terminal constraints of stable tracking, a coordinated cost function of tracking safety and fuel economy is formulated. Utilizing the nonlinear model predictive control method, the multi-objective optimization control algorithm is developed. To validate the comprehensive performances and advantages of proposed algorithm, both simulation and experiments are implemented. Simulation and experiment results show that, the proposed algorithm has better integrated performances of tracking ability and fuel economy compared with conventional algorithms.

Key words: cruise control, hybrid electric vehicle, nonlinear model predictive control

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