功率分流式混合动力矿用自卸车预测性等效燃油消耗最小控制策略研究

doi:10.3901/JME.2021.02.200

机械工程学报 ›› 2021, Vol. 57 ›› Issue (2): 200-209.doi: 10.3901/JME.2021.02.200

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功率分流式混合动力矿用自卸车预测性等效燃油消耗最小控制策略研究

周维¹, 刘鸿远¹, 徐彪¹, 张雷²

1. 湖南大学机械与运载工程学院长沙 410082;
2. 北京理工大学机械与车辆学院北京 100081

收稿日期:2020-01-28 修回日期:2020-10-22 出版日期:2021-01-20 发布日期:2021-03-15
通讯作者: 张雷(通信作者),男,1987年出生,博士,副研究员。主要研究方向为新能源汽车动力系统综合控制与优化。E-mail:lei_zhang@bit.edu.cn
作者简介:周维,男,1986年出生,博士,讲师。主要研究方向为新能源汽车动力系统综合控制与优化。E-mail:zhouweibit@hnu.edu.cn
基金资助:
国家自然科学基金（51705139）和湖南省自然科学基金（2018JJ3047）资助项目。

Predictive Equivalent Consumption Minimization Strategy for Power Split Hybrid Electric Mining Truck

ZHOU Wei¹, LIU Hongyuan¹, XU Biao¹, ZHANG Lei²

1. College of Mechanical and Vehicle Engineering, Hunan University, Changsha 410082;
2. School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081

Received:2020-01-28 Revised:2020-10-22 Online:2021-01-20 Published:2021-03-15

摘要/Abstract

摘要： 矿用自卸车运行线路固定、无交通约束，但行驶地形复杂且装载质量变化大。重载下长坡时，传统的自适应等效燃油消耗最小策略（Adaptive equivalent consumption minimization strategy，A-ECMS）可能由于电池荷电状态（State of charge，SOC）处于高位而无法最大限度地利用电制动进行能量回收。为解决该问题，针对矿山实际工况，提出一种融合坡度信息和整车质量估计的预测性ECMS策略（Predictive equivalent fuel consumption minimum strategy，P-ECMS）。结合GPS提供的地形信息实现路面坡度预测，并利用递推最小二乘法对装载后的整车质量进行在线估计；建立能量回收预估模型分别计算满载和空载时车辆下坡制动前的目标SOC值，加权平均后得到参考SOC轨迹；采用一种传统A-ECMS算法实现对参考SOC轨迹的跟踪和功率分配的瞬时优化。进行了控制器在环仿真试验，结果表明，所提出的P-ECMS算法能在车载控制器中实时运行，能适应不同的装载载荷，且燃油经济性相比传统A-ECMS最高可改善7.21%。

关键词: 矿用自卸车, 递推最小二乘法, 质量估计, 制动能量回收, 预测性ECMS

Abstract: Mining trucks have fixed operating routes and no traffic constraints, but they often operate on complex terrains and endure largely varying loads. When driving on a long downhill slope with heavy loads, traditional adaptive equivalent consumption minimization strategy(A-ECMS) cannot fully capitalize on regenerative braking since battery state of charge(SOC) may be at a high level. To solve this problem, a predictive equivalent fuel consumption minimum strategy(P-ECMS) that combines slope information prediction and vehicle mass estimation is proposed. GPS topographical data is used to realize road slope prediction, and a recursive least squares method is used to estimate the vehicle mass after loading operation. A braking energy recovery estimation model is established to predict the target SOC values before the downhill driving with full and empty loads, and the reference SOC trajectory is further obtained based on the weighted sum of these two SOC values. A traditional A-ECMS algorithm is adopted to track the reference SOC trajectory while realizing power-split optimization instantaneously. Comprehensive hardware-in-the-loop(HIL) simulations are conducted and the results show that the proposed P-ECMS algorithm is computationally efficient and can be implemented in real-time in an automotive controller and improve the fuel economy up to 7.21% compared with the traditional A-ECMS.

Key words: mining trucks, recursive least squares, vehicle mass estimation, braking energy recovery, predictive ECMS

中图分类号:

U469

周维, 刘鸿远, 徐彪, 张雷. 功率分流式混合动力矿用自卸车预测性等效燃油消耗最小控制策略研究[J]. 机械工程学报, 2021, 57(2): 200-209.

ZHOU Wei, LIU Hongyuan, XU Biao, ZHANG Lei. Predictive Equivalent Consumption Minimization Strategy for Power Split Hybrid Electric Mining Truck[J]. Journal of Mechanical Engineering, 2021, 57(2): 200-209.

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功率分流式混合动力矿用自卸车预测性等效燃油消耗最小控制策略研究

Predictive Equivalent Consumption Minimization Strategy for Power Split Hybrid Electric Mining Truck

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