﻿ 一种动态规划算法模型预测控制在混合动力汽车控制策略中的应用 Application of a Dynamic Programming Algorithm Model Predictive Control in Hybrid Electric Vehicle Control Strategy

Dynamical Systems and Control
Vol. 07  No. 04 ( 2018 ), Article ID: 26945 , 5 pages
10.12677/DSC.2018.74032

Application of a Dynamic Programming Algorithm Model Predictive Control in Hybrid Electric Vehicle Control Strategy

Qiong Wang, Xiaokan Wang

Henan Mechanical and Electrical Vocational College, Xinzheng Henan

Received: Sep. 1st, 2018; accepted: Sep. 19th, 2018; published: Sep. 26th, 2018

ABSTRACT

Good control strategy of hybrid electric vehicles can not only meet the power demand of vehicles, but also effectively save fuel and reduce emissions. In this paper, the construction of model predictive control (MPC) in hybrid electric vehicle (HEV) is proposed. The solving process and the use of reference trajectory are discussed for the application of MPC based on dynamic programming algorithm. The simulation results show that the control method can effectively reduce fuel consumption when the torque of engine and motor is reasonably distributed, and the effectiveness of the control strategy is verified.

Keywords:Battery Charging State, Model Predictive Control, Dynamic Programming Algorithm, Optimization

1. 绪论

2. 基于模型预测控制的混合动力汽车优化控制函数的设计

${J}_{k}=\underset{k}{\overset{k+p}{\sum }}L\left(x\left(t\right),u\left(t\right)\right)=\underset{k}{\overset{k+p}{\sum }}f\left(t\right)$ (1)

3. 基于动态规划在混合电动汽车模型预测控制的应用

3.1. 动态规划在模型预测控制的求解

${J}_{k}^{\ast }\left(SOC\left(k\right)\right)=\underset{u\left(k\right)}{\mathrm{min}}\left[L\left(SOC\left(k\right),u\left(k\right)\right)+{J}_{k+1}^{\ast }\left(SOC\left(k+1\right)\right)\right]$ (2)

3.2. SOC参考轨迹及使用

Figure 1. Power demand diagram under cyclic condition

$SO{C}_{r}\left(k\right)=SO{C}_{0}-\frac{k}{s}\left(SO{C}_{0}-SO{C}_{f}\right)$ (3)

$SO{C}_{0}=SO{C}_{i}-0.01$ (4)

${J}_{k}=\underset{k}{\overset{k+p}{\sum }}\left(f\left(t\right)+h\left(SOC\left(t+\text{1}\right)\right)\right)$ (5)

$h\left(SOC\left(t\right)\right)=\left\{\begin{array}{l}0,SOC\left(t\right)\ge SO{C}_{r}\left(t\right)\\ \alpha {\left(SOC\left(t\right)-SO{C}_{r}\left(t\right)\right)}^{2},SOC\left(t\right) (6)

4. 结论

Figure 2. SOC curve of storage battery

Application of a Dynamic Programming Algorithm Model Predictive Control in Hybrid Electric Vehicle Control Strategy[J]. 动力系统与控制, 2018, 07(04): 282-286. https://doi.org/10.12677/DSC.2018.74032

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