Fusion Research of Trajectory Tracking Energy-saving Control of Unmanned Hybrid Vehicles

被引：1
作者：
Liu J. [1 ]
Feng G. [1 ]
Zhang J. [1 ]
Yang K. [1 ]
机构：
[1] College of Vehicle and Traffic Engineering, Henan University of Science and Technology, Henan, Luoyang
来源：
Zhongguo Jixie Gongcheng/China Mechanical Engineering | 2024年 / 35卷 / 04期
关键词：
dynamic programming; hybrid power; model predictive control; trajectory tracking energy-saving control; unmanned vehicle;
D O I：
10.3969/j.issn.1004-132X.2024.04.011
中图分类号：
学科分类号：
摘要：
In order to further improve unmanned hybrid vehicles trajectory tracking accuracy and energy consumption economy, this paper proposed a trajectory tracking energy-saving control fusion strategy. Firstly, the vehicle kinematics model was established, and the trajectory tracking control of the vehicle was carried out by using the model predictive control strategy. Then, with velocity as the interactive variable, a three-stage dynamic programming energy-saving control strategy was proposed. In this way, the optimal economic function was optimized online to reduce the total cost of energy consumption of the vehicles. Finally, the independent pure pursuit trajectory tracking algorithm and the power following energy-saving control were selected for comparison strategies. The results show that the proposed trajectory tracking energy-saving control fusion strategy improves the trajectory tracking effectvieness and reduces the total cost of vehicle energy consumption. The trajectory tracking errors are reduced 70.47%. The total cost of energy consumption decreases 4.52% and 25.10% in pure electric drive mode and hybrid drive mode, respectively. © 2024 Chinese Mechanical Engineering Society. All rights reserved.
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页码：678 / 690
页数：12
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