面向高速工况的混合动力卡车预见性节能算法

doi:10.13229/j.cnki.jdxbgxb.20221388

摘要/Abstract

摘要：

重型卡车长途货物运输过程中，车辆主要行驶工况为车速小范围波动的高速巡航工况。为进一步提升车辆在该工况下的节油率，以P2构型单轴并联式混合动力卡车为研究对象，提出了以发动机燃油消耗量最小为目标的预见性节能算法。基于车辆前方道路坡度变化，考虑车速变化与动力部件能量分配对车辆油耗的影响，将车速与电池SOC作为系统状态变量，用动态规划算法确定针对当前行驶道路的全局最优未来车速轨迹及能量分配规则。经对比验证，本文算法得出的车速规划及能量分配结果合理，且采用预见性节能算法的混动卡车相较定速巡航（CCS）下采用动态规划算法的混动卡车及预见性巡航控制（PCC）下的纯燃油卡车节油率分别为3.19%和6.26%。

关键词: 车辆工程, 混合动力卡车, 预见性节能算法, 车速规划, 能量管理策略

Abstract:

In the process of long-distance cargo transportation of heavy truck， the main driving condition of the vehicle is the high-speed cruising condition with little change in speed range. In order to further improve the fuel saving rate of the vehicle under this condition， a predictive energy saving algorithm with the objective of minimizing engine fuel consumption is proposed， which takes the P2 configuration single-axle parallel hybrid truck as the research object. Based on the change of road slope in front of the vehicle， considering the influence of speed change and energy distribution on fuel consumption， the vehicle speed and battery SOC are regarded as system state variables， and the global optimal future vehicle speed trajectory and energy distribution rules for the current road are determined by dynamic programming algorithm. It has been verified that the speed planning and energy distribution results obtained by the predictive energy saving algorithm are reasonable， and the fuel saving rates of hybrid truck with predictive energy saving algorithm are 3.19% and 6.26%， respectively compared with hybrid truck using dynamic programming algorithm under cruise control system （CCS） and pure fuel truck under predictive cruise control （PCC）.

Key words: vehicle engineering, hybrid electric truck, predictive energy saving algorithm, vehicle speed planning, energy management strategy

中图分类号:

U461.8

王玉海,李晓之,李兴坤. 面向高速工况的混合动力卡车预见性节能算法[J]. 吉林大学学报(工学版), 2024, 54(8): 2121-2129.

Yu-hai WANG,Xiao-zhi LI,Xing-kun LI. Predictive energy saving algorithm for hybrid electric truck under high-speed condition[J]. Journal of Jilin University(Engineering and Technology Edition), 2024, 54(8): 2121-2129.

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参考文献 16

1	洪金龙, 高炳钊, 董世营, 等. 智能网联汽车节能优化关键问题与研究进展[J]. 中国公路学报, 2021, 34(11): 306-334.
	Hong Jin-long, Gao Bing-zhao, Dong Shi-ying, et al. Key problems and research progress of energy saving optimization for intelligent connected vehicles[J]. China Journal of Highway and Transport, 2021, 34(11): 306-334.
2	景远, 焦晓红. 基于交通信息和模型预测控制的混合动力汽车能量管理策略综述[J]. 燕山大学学报, 2019, 43(4): 319-330.
	Jing Yuan, Jiao Xiao-hong. A review of energy management strategies for hybrid electric vehicles based on traffic information and model predictive control[J]. Journal of Yanshan University, 2019, 43(4): 319-330.
3	武小花, 余忠伟, 朱张玲, 等. 燃料电池公交车模糊能量管理策略[J].吉林大学学报: 工学版, 2022, 52(9): 2077-2084.
	Wu Xiao-hua, Yu Zhong-wei, Zhu Zhang-ling, et al. Fuzzy energy management strategy of fuel cell buses[J]. Journal of Jilin University(Engineering and Technology Edition), 2022, 52(9): 2077-2084.
4	王哲, 谢怡, 臧鹏飞, 等. 基于极小值原理的燃料电池客车能量管理策略[J]. 吉林大学学报: 工学版, 2020, 50(1): 36-43.
	Wang Zhe, Xie Yi, Zang Peng-fei, et al. Energy management strategy of fuel cell bus based on pontryagin's minimum principle[J]. Journal of Jilin University(Engineering and Technology Edition), 2020, 50(1): 36-43.
5	巴特, 高印寒, 王庆年, 等. 基于动态规划算法的并联混合动力客车控制策略优化[J]. 汽车工程, 2015, 37(12): 1359-1365.
	Ba Te, Gao Yin-han, Wang Qing-nian, et al. Control strategy optimization for a parallel hybrid electric bus based on dynamic programming algorithm[J]. Automotive Engineering, 2015, 37(12): 1359-1365.
6	Yang Y L, Pei H X, Hu X S, et al. Fuel economy optimization of power split hybrid vehicles: a rapid dynamic programming approach[J]. Energy, 2019, 166: 929-938.
7	江冬冬, 李道飞, 俞小莉. 基于混杂模型预测控制的混合动力车辆能量管理[J]. 吉林大学学报: 工学版, 2020, 50(4): 1217-1226.
	Jiang Dong-dong, Li Dao-fei, Yu Xiao-li. Energy management of HEV based on hybrid model predictive control[J]. Journal of Jilin University(Engineering and Technology Edition), 2020, 50(4): 1217-1226.
8	宋大凤, 云千芮, 杨南南, 等. 行星式混合动力客车的模型预测动态协调控制[J]. 哈尔滨工业大学学报, 2019, 51(1): 150-156.
	Song Da-feng, Yun Qian-rui, Yang Nan-nan, et al. Model predictive dynamic coordinated control of planetary hybrid electric bus[J]. Journal of Harbin Institute of Technology, 2019, 51(1): 150-156.
9	Sciarretta A, Giovanni D, Ojeda L. Optimal ecodriving control: energy-efficient driving of road vehicles as an optimal control problem[J]. IEEE Control Systems, 2015, 35(5): 71-90.
10	王建强, 俞倩雯, 李升波, 等. 基于道路坡度实时信息的经济车速优化方法[J]. 汽车安全与节能学报, 2014, 5(3): 257-262.
	Wang Jian-qiang, Yu Qian-wen, Li Sheng-bo, et al. Eco speed optimization based on real-time information of road gradient[J]. Journal of Automotive Safety and Energy, 2014, 5(3): 257-262.
11	王玉海, 李兴坤, 张鹏雷, 等. 基于ADAS地图的载货车预见巡航实时优化算法[J]. 汽车工程, 2020, 42(10): 1335-1339.
	Wang Yu-hai, Li Xing-kun, Zhang Peng-lei, et al. Real-time optimization algorithm for truck predictive cruise based on ADAS map[J]. Automotive Engineering, 2020, 42(10):1335-1339.
12	Chu H Q, Guo L L, Gao B Z, et al. Predictive cruise control using high-definition map and real vehicle implementation[J]. IEEE Transactions on Vehicular Technology, 2018, 67(12):11377-11389.
13	鞠飞, 庄伟超, 王良模, 等. 混合动力汽车经济型巡航的车速规划策略[J]. 浙江大学学报: 工学版, 2021, 55(8): 1538-1547.
	Ju Fei, Zhuang Wei-chao, Wang Liang-mo, et al. Velocity planning strategy for economic cruise of hybrid electric vehicles[J]. Journal of Zhejiang University (Engineering Science), 2021, 55(8): 1538-1547.
14	Zeng X R, Wang J M. A parallel hybrid electric vehicle energy management strategy using stochastic model predictive control with road grade preview[J]. IEEE Transactions on Control Systems Technology, 2015, 23(6): 2416-2423.
15	Deng J P, Re L G, Joes S. Predictive hybrid powertrain energy management with asynchronous cloud update[J]. IFAC-PapersOnLine, 2020, 53(2):14123 -14128.
16	付雪青, 王宝森, 杨建军, 等. 基于双状态动态规划混动汽车坡道生态驾驶策略[J]. 汽车安全与节能学报, 2021, 12(3): 373-379.
	Fu Xue-qing, Wang Bao-sen, Yang Jian-jun, et al. Eco-driving strategy at ramp road for hybrid electric vehicles based on two-state dynamic programming[J]. Journal of Automotive Safety and Energy, 2021, 12(3): 373-379.

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对比项	路段编号	行驶里程 /km	平均车速 /（km·h^-1）	总油耗 /L	百公里油耗 /［L·（100 km）^-1］
仿真计算	1	16.00	86.6	5.26	32.88
实车实验	1	16.00	86.6	5.3	33.13
仿真计算	2	17.10	81.7	5.52	32.28
实车实验	2	17.10	81.7	5.5	32.16

对比项	路段编号	行驶里程/km	平均车速 /（km·h^-1）	电池SOC 初值/%	电池SOC 终值/%	总油耗 /L	百公里油耗/ ［L·（100 km）^-1］
预见性节能算法	1	19.15	79.8	50	50	5.88	30.70
混动车CCS	1	19.15	80.1	50	50	6.05	31.59
燃油车PCC	1	19.15	80.4	-	-	6.25	32.64
预见性节能算法	2	20.00	79.7	50	50	6.23	31.15
混动车CCS	2	20.00	80.1	50	50	6.46	32.30
燃油车PCC	2	20.00	80.2	-	-	6.67	33.35