基于迭代动态规划的网联电动汽车经济性巡航车速优化

doi:10.3901/JME.2021.06.121

机械工程学报 ›› 2021, Vol. 57 ›› Issue (6): 121-130.doi: 10.3901/JME.2021.06.121

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基于迭代动态规划的网联电动汽车经济性巡航车速优化

董昊轩, 殷国栋, 庄伟超, 陈浩, 周毅晨, 汪?

东南大学机械工程学院南京 211189

收稿日期:2020-04-01 修回日期:2020-10-14 出版日期:2021-03-20 发布日期:2021-05-25
通讯作者: 庄伟超(通信作者),男,1990年出生,博士,讲师。主要研究方向为车辆动力学控制,智能网联汽车。E-mail:wezhuang@seu.edu.cn
作者简介:董昊轩，男，1993年出生，博士研究生。主要研究方向为智能网联汽车能量优化控制。E-mail：donghaox@foxmail.com
基金资助:
江苏省重点研发计划(BE2019004)、国家杰出青年科学基金(52025121)和国家自然科学基金(51805081，51975118)资助项目。

Economic Cruising Velocity Optimization Using Iterative Dynamic Programming of Connected Electric Vehicle

DONG Haoxuan, YIN Guodong, ZHUANG Weichao, CHEN Hao, ZHOU Yichen, WANG Yan

School of Mechanical Engineering, Southeast University, Nanjing 211189

Received:2020-04-01 Revised:2020-10-14 Online:2021-03-20 Published:2021-05-25

摘要/Abstract

摘要： 为提升网联电动汽车的能量效率，针对变坡度和变限速的交通场景，提出一种结合滚动优化与迭代动态规划(Iterative dynamic programming，IDP)的滚动距离域车速规划策略(Receding distance horizon velocity planning，RDHVP)，实现了电动汽车(Electric vehicle，EV)能量优化与动态交通约束的时空解耦，快速优化求解经济性巡航车速。依据动态交通场景变限速特性，设计了基于道路限速分段的EV能量优化问题，在距离域上实现全程优化问题分段滚动优化，以避免限速变化引起的车辆控制力大幅度波动。基于动态规划原理，设计了包含状态量/控制量边界和网格大小缩放策略的IDP算法，以快速计算获取权衡计算速度和最优性的巡航车速。采集真实道路信息，建立仿真模型，验证所设计策略的有效性。结果表明，相较于传统恒定车速巡航策略和常规动态规划方法，提出的方法能够大幅度提高EV能量效率和巡航车速优化计算速度。

关键词: 网联汽车, 经济性驾驶, 交通信息物理系统, 滚动优化, 迭代动态规划

Abstract: To improve the energy efficiency of connected electric vehicle (EV), a receding distance horizon velocity planning strategy (RDHVP) is proposed, for optimizing economic cruising velocity at dynamic traffic environment with varying slopes and velocity limitations. The RDHVP strategy uses receding optimization strategy and iterative dynamic programming (IDP) algorithm, which can decouple the spatio-temporal coupling of energy optimization and dynamic traffic constraints, to achieve energy-saving cruising velocity fast optimization. Considering varying velocity limitations, the energy-optimal control problem of EV is staged by velocity limitations. The RDHVP strategy can realize staged problem receding optimization in distance domain, to avoid sharply changed vehicle force caused by varying velocity limitations. The IDP algorithm is formulated based on the principle of dynamic programming with consideration of boundary and grid scaling strategy, which can quickly solve the optimization problem and obtain the energy-optimal cruising velocity profile. Finally, to verify the effectiveness of proposed strategy, the simulation model is formulated using collected real traffic information. The results show the RDHVP strategy improves energy efficiency and reduces computing time significantly, compared with the conventional constant speed cruising strategy and regular dynamic programming optimization method.

Key words: connected vehicle, eco-driving, transportation cyber physical systems, receding optimization, iterative dynamic programming

中图分类号:

U461

董昊轩, 殷国栋, 庄伟超, 陈浩, 周毅晨, 汪?. 基于迭代动态规划的网联电动汽车经济性巡航车速优化[J]. 机械工程学报, 2021, 57(6): 121-130.

DONG Haoxuan, YIN Guodong, ZHUANG Weichao, CHEN Hao, ZHOU Yichen, WANG Yan. Economic Cruising Velocity Optimization Using Iterative Dynamic Programming of Connected Electric Vehicle[J]. Journal of Mechanical Engineering, 2021, 57(6): 121-130.

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基于迭代动态规划的网联电动汽车经济性巡航车速优化

Economic Cruising Velocity Optimization Using Iterative Dynamic Programming of Connected Electric Vehicle

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