Modeling and Integrated Optimization of Power Split and Exhaust Thermal Management on Diesel Hybrid Electric Vehicles
To simultaneously achieve high fuel efficiency and low emissions in a diesel hybrid electric vehicle (DHEV), it is necessary to optimize not only power split but also exhaust thermal management for emission aftertreatment systems. However, how to coordinate the power split and the exhaust thermal ma...
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oai:doaj.org-article:242743418f064989aa3d32ecb2bd02602021-11-25T17:26:07ZModeling and Integrated Optimization of Power Split and Exhaust Thermal Management on Diesel Hybrid Electric Vehicles10.3390/en142275051996-1073https://doaj.org/article/242743418f064989aa3d32ecb2bd02602021-11-01T00:00:00Zhttps://www.mdpi.com/1996-1073/14/22/7505https://doaj.org/toc/1996-1073To simultaneously achieve high fuel efficiency and low emissions in a diesel hybrid electric vehicle (DHEV), it is necessary to optimize not only power split but also exhaust thermal management for emission aftertreatment systems. However, how to coordinate the power split and the exhaust thermal management to balance fuel economy improvement and emissions reduction remains a formidable challenge. In this paper, a hierarchical model predictive control (MPC) framework is proposed to coordinate the power split and the exhaust thermal management. The method consists of two parts: a fuel and thermal optimized controller (FTOC) combining the rule-based and the optimization-based methods for power split simultaneously considering fuel consumption and exhaust temperature, and a fuel post-injection thermal controller (FPTC) for exhaust thermal management with a separate fuel injection system added to the exhaust pipe. Additionally, preview information about the road grade is introduced to improve the power split by a fuel and thermal on slope forecast optimized controller (FTSFOC). Simulation results show that the hierarchical method (FTOC + FPTC) can reach the optimal exhaust temperature nearly 40 s earlier, and its total fuel consumption is also reduced by 8.9%, as compared to the sequential method under a world light test cycle (WLTC) driving cycle. Moreover, the total fuel consumption of the FTSFOC is reduced by 5.2%, as compared to the fuel and thermal on sensor-information optimized controller (FTSOC) working with real-time road grade information.Jinghua ZhaoYunfeng HuFangxi XieXiaoping LiYao SunHongyu SunXun GongMDPI AGarticlediesel hybrid electric vehicle (DHEV)power splitexhaust thermal managementnonlinear model predictive control (NMPC)TechnologyTENEnergies, Vol 14, Iss 7505, p 7505 (2021) |
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diesel hybrid electric vehicle (DHEV) power split exhaust thermal management nonlinear model predictive control (NMPC) Technology T |
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diesel hybrid electric vehicle (DHEV) power split exhaust thermal management nonlinear model predictive control (NMPC) Technology T Jinghua Zhao Yunfeng Hu Fangxi Xie Xiaoping Li Yao Sun Hongyu Sun Xun Gong Modeling and Integrated Optimization of Power Split and Exhaust Thermal Management on Diesel Hybrid Electric Vehicles |
description |
To simultaneously achieve high fuel efficiency and low emissions in a diesel hybrid electric vehicle (DHEV), it is necessary to optimize not only power split but also exhaust thermal management for emission aftertreatment systems. However, how to coordinate the power split and the exhaust thermal management to balance fuel economy improvement and emissions reduction remains a formidable challenge. In this paper, a hierarchical model predictive control (MPC) framework is proposed to coordinate the power split and the exhaust thermal management. The method consists of two parts: a fuel and thermal optimized controller (FTOC) combining the rule-based and the optimization-based methods for power split simultaneously considering fuel consumption and exhaust temperature, and a fuel post-injection thermal controller (FPTC) for exhaust thermal management with a separate fuel injection system added to the exhaust pipe. Additionally, preview information about the road grade is introduced to improve the power split by a fuel and thermal on slope forecast optimized controller (FTSFOC). Simulation results show that the hierarchical method (FTOC + FPTC) can reach the optimal exhaust temperature nearly 40 s earlier, and its total fuel consumption is also reduced by 8.9%, as compared to the sequential method under a world light test cycle (WLTC) driving cycle. Moreover, the total fuel consumption of the FTSFOC is reduced by 5.2%, as compared to the fuel and thermal on sensor-information optimized controller (FTSOC) working with real-time road grade information. |
format |
article |
author |
Jinghua Zhao Yunfeng Hu Fangxi Xie Xiaoping Li Yao Sun Hongyu Sun Xun Gong |
author_facet |
Jinghua Zhao Yunfeng Hu Fangxi Xie Xiaoping Li Yao Sun Hongyu Sun Xun Gong |
author_sort |
Jinghua Zhao |
title |
Modeling and Integrated Optimization of Power Split and Exhaust Thermal Management on Diesel Hybrid Electric Vehicles |
title_short |
Modeling and Integrated Optimization of Power Split and Exhaust Thermal Management on Diesel Hybrid Electric Vehicles |
title_full |
Modeling and Integrated Optimization of Power Split and Exhaust Thermal Management on Diesel Hybrid Electric Vehicles |
title_fullStr |
Modeling and Integrated Optimization of Power Split and Exhaust Thermal Management on Diesel Hybrid Electric Vehicles |
title_full_unstemmed |
Modeling and Integrated Optimization of Power Split and Exhaust Thermal Management on Diesel Hybrid Electric Vehicles |
title_sort |
modeling and integrated optimization of power split and exhaust thermal management on diesel hybrid electric vehicles |
publisher |
MDPI AG |
publishDate |
2021 |
url |
https://doaj.org/article/242743418f064989aa3d32ecb2bd0260 |
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