模型预测控制
数学优化
能源管理
计算机科学
启发式
电动汽车
时间范围
动态规划
正多边形
凸优化
电池(电)
整数规划
功率(物理)
能量(信号处理)
整数(计算机科学)
控制(管理)
数学
几何学
程序设计语言
人工智能
物理
统计
量子力学
作者
Fei Ju,Nikolce Murgovski,Weichao Zhuang,Xiaosong Hu,Ziyou Song,Liangmo Wang
出处
期刊:Energy
[Elsevier]
日期:2023-01-01
卷期号:263: 125971-125971
被引量:11
标识
DOI:10.1016/j.energy.2022.125971
摘要
This paper studies energy management (EM) of a power-split hybrid electric vehicle (HEV) equipped with planetary gear sets. We first formulate a mixed-integer global optimal control problem that includes a binary switching variable. Convex modeling, including the fuel model for a compound energy conversion unit, is then presented to reformulate the mixed-integer EM as a two-step program. For optimizing the engine switching and battery power decisions in the first step, we employ the alternating direction method of multipliers (ADMM) algorithm where the solution of the convex relaxation is used to initialize the non-convex problem. On the standard driving cycle, simulation results indicate that the ADMM based EM method saves 7.63% fuel compared to a heuristic method, and shows 99% optimality compared to a dynamic programming method, while saving three orders of magnitude in computing time. An ADMM combined model predictive control (ADMM-MPC) method is also developed that is suitable for receding horizon control scenarios. The ADMM-MPC method shows 5.28% fuel saving when implemented using a prediction horizon of 15 samples. Meanwhile, the mean computing time for MPC updates is 3.53 ms. Our results demonstrate that the proposed ADMM is capable of real-time control.
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