Study on the Rule-based Control Strategy for PHEV According to Two-state Dynamic Programming Algorithm

Wei Hanbing; Zhu Ning

doi:10.16578/j.issn.1004.2539.2018.02.002

您当前的位置：

首页 >

文章列表页 >

Study on the Rule-based Control Strategy for PHEV According to Two-state Dynamic Programming Algorithm

更新时间：2022-10-20

- Study on the Rule-based Control Strategy for PHEV According to Two-state Dynamic Programming Algorithm
- Vol. 42, Issue 2, Pages: 6-13(2018)
- 作者机构：
  
  1. 重庆交通大学机电与车辆工程学院
- 作者简介：
- 基金信息：
- DOI：10.16578/j.issn.1004.2539.2018.02.002
  CLC：
扫描看全文
[1]隗寒冰,朱宁.基于双状态动态规划算法的PHEV规则控制策略研究[J].机械传动,2018,42(02):6-13+35.

Wei Hanbing, Zhu Ning. Study on the Rule-based Control Strategy for PHEV According to Two-state Dynamic Programming Algorithm. [J]. 42(2):6-13(2018)
[1]隗寒冰,朱宁.基于双状态动态规划算法的PHEV规则控制策略研究[J].机械传动,2018,42(02):6-13+35. DOI： 10.16578/j.issn.1004.2539.2018.02.002.

Wei Hanbing, Zhu Ning. Study on the Rule-based Control Strategy for PHEV According to Two-state Dynamic Programming Algorithm. [J]. 42(2):6-13(2018) DOI： 10.16578/j.issn.1004.2539.2018.02.002.

摘要

以插电式柴电混合动力汽车（Diesel Engine Hybrid Plug-in Electric Vehicle,PHEV）燃油经济性和排放性能综合优化为研究目标,依托MATLAB/Simulink仿真平台建立包含柴油机选择性催化还原反应器（Selective Catalytic Reduction,SCR）后处理系统在内的整车动力学模型。在此基础上,建立了燃油消耗量和SCR出口NOx排放量多目标优化函数,以电池SOC和SCR温度分别作为动力系统和排气后处理系统的可观测状态变量,利用双状态动态规划算法求解控制系统全局优化问题,得到最优控制规律。从双状态动态规划算法结果的基础上拟合实时控制策略,并与基于规则的逻辑门限控制策略进行比较。结果表明,优化后的控制策略在燃油经济性和排放性能上均有所提升,油耗和NO,x,分别降低1.9%和9.3%。

Abstract

Comprehensive optimization of fuel economy and emissions of diesel engine hybrid plug-in electric vehicle has been investigated. A vehicle dynamic model considering Selective Catalytic Reduction（ SCR） aftertreatment system is established on MATLAB/Simulink simulation platform. A multi-objective optimization function with fuel consumption and SCR outlet’s NOxemission is developed by adopting two states dynamic programming algorithm to solve global optimization problem. Specifically,the battery SOC and SCR temperature is designated as two states respectively which reflect the powertrain system and aftertreatment system dynamics. Based on the optimized results,a rule-based control strategy which is applicable for real-time control is deduced. Compared with CS-CD control strategy,the simulation result shows the fuel economy and NO,x, emission both is decreased by 1. 9% and 9. 3%.

关键词

插电式柴电混合动力汽车排气后处理SCR动态规划

Keywords

Diesel engine hybrid plug-in electric vehicleExhaust aftertreatmentSCRDynamic programming

references

Views

126

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Model-based Optimal Gearshift Strategy Design for Pure Electric Bus AMT

Study on Energy Management Strategy for Hybrid Heavy-duty Truck based on Dynamic Programming

Analysis of Power Coupling Device with Dual Planetary Gear Set based on Dynamic Programming

Related Author

No data

Related Institution

College of Automobile Marketing， Changchun Automobile Industry Institute

College of Mechanical and Electrical Engineering， Northeast Forestry University

Hubei Key Laboratory of Advanced Technology for Automotive Components， Wuhan University of Technology

Hubei Collaborative Innovation Center for Automotive Components Technology， Wuhan University of Technology

Hubei Research Center for New Energy & Intelligent Connected Vehicle， Wuhan University of Technology

⁰