智能网联电动汽车经济性巡航速度规划

doi:10.19562/j.chinasae.qcgc.2022.04.016

Abstract

Abstract:

On the premise of sufficiently utilizing intelligent traffic environment information， an economical cruising speed planning method based on approximate dynamic programming in rolling distance domain is proposed in this paper， to enable vehicle achieve economic cruise on roads with different slopes， effectively extending the driving range of electric vehicles. Firstly， according to the dynamic traffic environment， the segmented rolling form based on distance domain is designed， and the mapping relationship between vehicle speed and road slope is established. Then， the approximate dynamic programming algorithm with asynchronous parallel network is adopted to rapidly calculate the economic cruising speed with concurrent considerations of safety and traffic efficiency. Finally， a hardware-in-the-loop simulation platform for intelligent connected vehicle is built to verify the method proposed. The results indicate that compared with traditional constant-speed cruise strategy， the proposed method effectively reduces the energy consumption and extends the driving range of vehicle without increasing its travel time.

Key words: network connected EV, economic driving, approximate dynamic programming, energy management

Zhe Zhang,Haitao Ding,Niaona Zhang,Konghui Guo. Economic Cruising Speed Planning of Intelligent Network Connected Electric Vehicle[J].Automotive Engineering, 2022, 44(4): 609-616.

Figures/Tables 15

基于距离域近似动态规划方法流程

1）根据前方道路信息及本车信息，设计分段距离域基本离散距离等信息。

2）车辆状态初始化；动作网络、评价全局网络及子网络权值、学习率及子系统更新时间等参数初始化；设定最小误差 $T c$ 及 $T a$ ；设定每次迭代次数。

3）由式（10）计算控制动作估计值 $u ? (k)$ 。

4）根据式（8）和状态方程计算回报值 $r (k)$ 和下一状态 $x ? (k + 1)$ 。

5）由式（13）计算全局评价网络值 $J ? (k)$ 和根据 $x ? (k + 1)$ 计算 $J ? (k + 1)$ 。

6）计算评价网络误差，子网络达到更新时间上传更新权值，根据式（18）更新全局评价网络误差。

7）更新最优值函数并求解近似最优解。

8）计算动作网络误差，根据式（12）更新动作网络。

9）如果 $e c < T c$ 并 $e a < T a$ 或达到最大迭代步，完成训练，输出动作值 $u (k)$ ，否则执行第3步。

10）根据输出 $u (k)$ 和 $x (k)$ 获得 $x (k + 1)$ ；循环更新状态。

References 21

1	郭露露，高炳钊，陈虹. 汽车经济性行驶优化［J］. 中国科学：信息科学，2016（5）：11.
	GUO Lulu， GAO Bingzhao， CHEN Hong. Optimal eco-driving control of vehicles［J］. Scientia Sinica Informationis， 2016（5）：11.
2	TIE S F， TAN C W. A review of energy sources and energy management system in electric vehicles［J］. Renewable & Sustainable Energy Reviews，2013， 20（4）： 82-102.
3	李升波，徐少兵，王文军，等. 汽车经济性驾驶技术及应用概述［J］. 汽车安全与节能学报， 2014， 5（2）： 121-131.
	LI Shengbo， XU Shaobing， WANG Wenjun， et al. Overview of ecological driving technology and application for ground vehicles［J］. Automotive Safety and Energy， 2014， 5（2）： 121-131.
4	XU S B， LI S B， CHENG B. Optimization for economical cruising strategy of continuously variable transmission vehicle using pseudo-spectral method［J］. Control Theory & Applications， 2014.
5	杨宁康，韩立金，刘辉，等.基于效率优化的混合动力车辆强化学习能量管理策略研究［J］.汽车工程，2021，43（7）： 1046-1056.
	YANG Ningkang， HAN Lijin， LIU Hui， et al. Research on efficiency optimization based energy management strategy for a hybrid electric vehicle with reinforcement learning［J］.Automotive Engineering， 2021，43（7）： 1046-1056.
6	李克强，陈涛，罗禹贡，等. 智能环境友好型车辆——概念、体系结构及工程实现［J］. 汽车工程， 2010，30（9）： 743-748.
	LI Keqiang， CHEN Tao， LUO Yugong， et al. Environmentally friendly intelligent vehicle： concept， architecture and implementation［J］. Automotive Engineering， 2010，30（9）： 743-748.
7	HANNAN M A， AZIDIN F A， MOHAMED A. Hybrid electric vehicles and their challenges： a review［J］. Renew Sustain Energy Rev， 2014， 29 ： 135–150.
8	付锐，张雅丽，袁伟.生态驾驶研究现状及展望［J］.中国公路学报，2019， 32（3）： 1-12.
	FU Rui， ZHANG Yali， YUAN Wei. Progress and prospect in research on eco-driving［J］. China Journal of Highway Transport， 2019， 32（3）： 1-12.
9	KAMAL M A S， MUKAI M， MURATA J， et al. Ecological vehicle control on roads with up-down slopes［J］. IEEE Transactions on Intelligent Transportation Systems， 2011， 12（3）： 783-794.
10	LI S E， PENG H， LI K， et al. Minimum fuel control strategy in automated car-following scenarios［J］. IEEE Transactions on Vehicular Technology， 2012， 61（3）： 998-1007.
11	XU S， LI S E， ZHANG X， et al. Fuel-optimal cruising strategy for road vehicles with step-gear mechanical transmission［J］. IEEE Transactions on Intelligent Transportation Systems， 2015， 16（6）： 3496-3507.
12	SAERENS B， BULCK E. Calculation of the minimum-fuel driving control based on Pontryagin's maximum principle［J］. Transportation Research Part D ：Transport & Environment， 2013， 24：89-97.
13	ZHUANG W C， QU Linghu， XU Shaobing， et al. Integrated energy-oriented cruising control of electric vehicle on highway with varying slopes considering battery aging［J］. Science China（Technological Sciences）， 2020，1（63），155-165.
14	HELLSTRO M E， IVARSSON M，ASLUND J， et al. Look-ahead control for heavy trucks to minimize trip time and fuel consumption［J］. IFAC Proceedings Volumes， 2007， 40（10）： 439-446.
15	DING Feng， JIN Hui. On the optimal speed profile for eco-driving on curved roads［J］. IEEE Transactions on Intelligent Transportation Systems， 2018， 19 （12）：1-11.
16	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， 2015， 17（1）： 113-122.
17	BAKIBILLAH A， KAMAL M， TAN C， et al. Fuzzy-tuned model predictive control for dynamic eco-driving on hilly roads［J］. Applied Soft Computing， 2020， 99.
18	GUO L， GAO B， YING G， et al. Optimal energy management for hevs in eco-driving applications using bi-level MPC［J］. IEEE Transactions on Intelligent Transportation Systems， 2017， 18（8）： 2153-2162.
19	GUO L， CHEN H， LIU Q， et al. A computationally efficient and hierarchical control strategy for velocity optimization of on-road vehicles［J］. IEEE Transactions on Systems， Man， and Cybernetics： Systems， 2019，1（49）：1-11.
20	HUANG Zhi， ZHONG Zhihua. A study on active handling stability control for electric vehicle with individual wheel driving［J］. Automotive Engineering，2005， 27（5）： 565-569.
21	CHEN H， GUO L， DING H， et al. Real-time predictive cruise control for eco-driving taking into account traffic constraints［J］. IEEE Transactions on Intelligent Transportation Systems， 2018， 20（3）：1-11.

车辆参数	数值
汽车质量/kg	1 700
迎风面积/m²	2.08
空气阻力系数	0.35
空气密度/（kg·m^-3）	1.205
车轮半径/m	0.33

控制方法	运行时间
ACC巡航	179.99 s
本文方法	179.45 s

[1]	Jinxia Liu,Zhihao Liang,Qiang Wang,Mingxing Wen. Research on the Equivalent Fuel Consumption Minimizing Energy Management Strategy of Through-the-Road Vehicle [J]. Automotive Engineering, 2023, 45(2): 285-292.
[2]	Chunyang Qi,Chuanxue Song,Shixin Song,Liqiang Jin,Da Wang,Feng Xiao. Research on Energy Management Strategy for Hybrid Electric Vehicles Based on Inverse Reinforcement Learning [J]. Automotive Engineering, 2023, 45(10): 1954-1964.
[3]	Shaobo Xie,Pengcheng Qu,Jiacheng Li,Huiqing Wang,Kun Lang. Study on Coordinated Control of Speed Planning and Energy Management for Connected Hybrid Electric Truck in Vehicle Following Scene [J]. Automotive Engineering, 2022, 44(8): 1136-1143.
[4]	Xiaodong Wei,Bo Liu,Jianghao Leng,Xingyu Zhou,Chao Sun,Fengchun Sun. Research on Eco-driving of Fuel Cell Vehicles via Convex Optimization [J]. Automotive Engineering, 2022, 44(6): 851-858.
[5]	Yong Chen,Changyin Wei,Xiaoyu Li,Yanlin Li,Caixia Liu,Xiaozhe Lin. Research on Fuzzy Energy Management Strategy for Extended-Range Electric Vehicles with Driving Condition Identification [J]. Automotive Engineering, 2022, 44(4): 514-524.
[6]	Ximing Cheng,Wei Hu,Jun Zhai,Ronghua Luo,Pan Zhang,Ye Xu. Study on the Efficiency of Low-voltage Electric System in Battery Electric Vehicles [J]. Automotive Engineering, 2022, 44(4): 601-608.
[7]	Junqiu Li,Jiwei Liu,Chaofeng Zhu. Research on Energy Management of Hybrid Electric Vehicle Based on Time-Varying Chassis Configuration [J]. Automotive Engineering, 2022, 44(12): 1866-1876.
[8]	Ningkang Yang,Lijin Han,Hui Liu,Xin Zhang. Research on Efficiency Optimization Based Energy Management Strategy for a Hybrid Electric Vehicle with Reinforcement Learning [J]. Automotive Engineering, 2021, 43(7): 1046-1056.
[9]	Shaobo Xie,Huiran Luo,Qiankun Zhang,Kangkang Zhang. Research on Multiple Objective Coordinated Control of Speed Planning for Intelligent Connected Hybrid Electric Vehicles [J]. Automotive Engineering, 2021, 43(7): 953-961.
[10]	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.
[11]	Lijin Han,Hui Liu,Cong Liu,Baoshuai Liu,Cong Zhang. Energy Management of Tracked Vehicles Based on Battery Life Prediction Control [J]. Automotive Engineering, 2021, 43(5): 657-666.
[12]	Jie Hu,Ming Wang,Di Liu,Fuwu Yan,Kai Cao. Optimization of Control Strategy for Hybrid Power System Based on Traffic Information [J]. Automotive Engineering, 2021, 43(5): 675-682.
[13]	Hao Zhang,Qinhao Fan,Wei Wang,Jin Huang,Zhi Wang. Reinforcement Learning Based Energy Management Strategy for Hybrid Electric Vehicles Using Multi⁃mode Combustion [J]. Automotive Engineering, 2021, 43(5): 683-691.
[14]	Long Chen,Zhixing Chen,Xing Xu,Feng Wang,Yingfeng Cai,Tao Zhang. Energy Management Strategy of Plug⁃in Hybrid Electric Vehicle with Engine Start and Stop Optimization [J]. Automotive Engineering, 2021, 43(3): 313-322.
[15]	Ruiliang Zhang,Zhun Chen,Senhai Liu,Zhengwu Fan. Adaptive Energy Management Strategy for High Power Hydrogen Fuel Cell Heavy-duty Truck Based on Low Pass Filter [J]. Automotive Engineering, 2021, 43(11): 1693-1701.

Economic Cruising Speed Planning of Intelligent Network Connected Electric Vehicle

RichHTML

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 15

References 21

Related Articles 15

Metrics

Comments

Recommended 10