能源管理
解算器
计算机科学
最优控制
伪谱最优控制
燃料效率
数学优化
能源消耗
非线性规划
动态规划
控制理论(社会学)
电动汽车
高斯伪谱法
能量(信号处理)
伪谱法
非线性系统
汽车工程
功率(物理)
工程类
控制(管理)
算法
数学
人工智能
数学分析
物理
傅里叶分析
电气工程
统计
傅里叶变换
量子力学
作者
Jinlong Wu,Yuan Zou,Xudong Zhang,Guangze Du,Guodong Du,Runnan Zou
出处
期刊:IEEE Transactions on Transportation Electrification
日期:2020-06-01
卷期号:6 (2): 703-716
被引量:20
标识
DOI:10.1109/tte.2020.2973577
摘要
This article proposes a hierarchical energy management strategy (EMS) for hybrid electric tracked vehicle (HETV) considering the two tracks velocity planning based on pseudospectral method (PM). Constrained by the reference path known a priori, the upper layer of the hierarchical EMS finds the optimal velocity of the two tracks, in which the two motor torques are chosen as the control variable to minimize an objective function, trading off the energy consumption, and path tracking accuracy. Based on the obtained optimal velocity profile, the lower layer distributes the power demand to the engine-generator and the battery to minimize the energy consumption. The hierarchical EMS is designed to minimize energy consumption while ensuring the premise of the vehicle path tracking performance. Both layers adopt the PM which transforms the optimal control problem (OCP) into nonlinear programming (NLP) problem, and the Sparse Nonlinear OPTimizer (SNOPT) solver is used. Simulation results show that the fuel economy of the PM outperforms that of dynamic programming (DP). Compared with DP, the hierarchical EMS can save fuel consumption by 3.92% with a significantly reduced computation burden. Finally, field experiments show that the proposed method improves fuel economy by 14.85% compared with the rule-based EMS without velocity optimal planning.
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