Energy management strategies for hybrid diesel vehicles by dynamic planning embedded in real-world driving emission model
The optimization of energy management strategy for hybrid vehicles is often based on engine steady performance data and the standard driving cycle conditions in the laboratory. However, these methods cannot fully capture the vehicle’s dynamic characteristics under real-world driving conditions. This...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-01-01
|
| Series: | Case Studies in Thermal Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214157X24016745 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841555746380054528 |
|---|---|
| author | Yingzhang Wang Li Zhang Yang Chen Chaokai Li Baocheng Du Jinlin Han |
| author_facet | Yingzhang Wang Li Zhang Yang Chen Chaokai Li Baocheng Du Jinlin Han |
| author_sort | Yingzhang Wang |
| collection | DOAJ |
| description | The optimization of energy management strategy for hybrid vehicles is often based on engine steady performance data and the standard driving cycle conditions in the laboratory. However, these methods cannot fully capture the vehicle’s dynamic characteristics under real-world driving conditions. This study uses a BP-Adaboost algorithm combined with a transfer learning strategy to construct a learning model of real-world driving emissions based on several real-world driving emission tests of a hybrid diesel light truck. The real-world driving emission model is then embedded into the dynamic planning algorithm using a bi-variate interpolation algorithm on the state-space plane. Accordingly, the optimal engine and motor torque control under real-world driving conditions is determined. It is found that the energy management strategies balancing the CO2 and NOx emissions for the hybrid diesel light truck can obtain a good NOx emission benefit while slightly sacrificing the CO2 emission benefit, and the trade-off consideration between energy consumption, pollutant emissions, and state-of-charge maintenance leads to a better overall social and economic benefit. |
| format | Article |
| id | doaj-art-5c25c88c52a14d2dba5c3510ad13d535 |
| institution | Kabale University |
| issn | 2214-157X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Case Studies in Thermal Engineering |
| spelling | doaj-art-5c25c88c52a14d2dba5c3510ad13d5352025-01-08T04:52:45ZengElsevierCase Studies in Thermal Engineering2214-157X2025-01-0165105643Energy management strategies for hybrid diesel vehicles by dynamic planning embedded in real-world driving emission modelYingzhang Wang0Li Zhang1Yang Chen2Chaokai Li3Baocheng Du4Jinlin Han5College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing, 400044, ChinaCollege of Mechanical and Vehicle Engineering, Chongqing University, Chongqing, 400044, China; State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing, 400044, China; Corresponding author. College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing, 400044, China.College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing, 400044, ChinaCollege of Mechanical and Vehicle Engineering, Chongqing University, Chongqing, 400044, ChinaChina Automotive Engineering Research Institute Co., Ltd, Chongqing, 401122, ChinaDepartment of Mechanical Engineering, Eindhoven University of Technology, NL-5600, Eindhoven, NetherlandsThe optimization of energy management strategy for hybrid vehicles is often based on engine steady performance data and the standard driving cycle conditions in the laboratory. However, these methods cannot fully capture the vehicle’s dynamic characteristics under real-world driving conditions. This study uses a BP-Adaboost algorithm combined with a transfer learning strategy to construct a learning model of real-world driving emissions based on several real-world driving emission tests of a hybrid diesel light truck. The real-world driving emission model is then embedded into the dynamic planning algorithm using a bi-variate interpolation algorithm on the state-space plane. Accordingly, the optimal engine and motor torque control under real-world driving conditions is determined. It is found that the energy management strategies balancing the CO2 and NOx emissions for the hybrid diesel light truck can obtain a good NOx emission benefit while slightly sacrificing the CO2 emission benefit, and the trade-off consideration between energy consumption, pollutant emissions, and state-of-charge maintenance leads to a better overall social and economic benefit.http://www.sciencedirect.com/science/article/pii/S2214157X24016745PHEVEnergy managementDynamic planningDiesel engineNOx emissionReal-world driving emissions |
| spellingShingle | Yingzhang Wang Li Zhang Yang Chen Chaokai Li Baocheng Du Jinlin Han Energy management strategies for hybrid diesel vehicles by dynamic planning embedded in real-world driving emission model Case Studies in Thermal Engineering PHEV Energy management Dynamic planning Diesel engine NOx emission Real-world driving emissions |
| title | Energy management strategies for hybrid diesel vehicles by dynamic planning embedded in real-world driving emission model |
| title_full | Energy management strategies for hybrid diesel vehicles by dynamic planning embedded in real-world driving emission model |
| title_fullStr | Energy management strategies for hybrid diesel vehicles by dynamic planning embedded in real-world driving emission model |
| title_full_unstemmed | Energy management strategies for hybrid diesel vehicles by dynamic planning embedded in real-world driving emission model |
| title_short | Energy management strategies for hybrid diesel vehicles by dynamic planning embedded in real-world driving emission model |
| title_sort | energy management strategies for hybrid diesel vehicles by dynamic planning embedded in real world driving emission model |
| topic | PHEV Energy management Dynamic planning Diesel engine NOx emission Real-world driving emissions |
| url | http://www.sciencedirect.com/science/article/pii/S2214157X24016745 |
| work_keys_str_mv | AT yingzhangwang energymanagementstrategiesforhybriddieselvehiclesbydynamicplanningembeddedinrealworlddrivingemissionmodel AT lizhang energymanagementstrategiesforhybriddieselvehiclesbydynamicplanningembeddedinrealworlddrivingemissionmodel AT yangchen energymanagementstrategiesforhybriddieselvehiclesbydynamicplanningembeddedinrealworlddrivingemissionmodel AT chaokaili energymanagementstrategiesforhybriddieselvehiclesbydynamicplanningembeddedinrealworlddrivingemissionmodel AT baochengdu energymanagementstrategiesforhybriddieselvehiclesbydynamicplanningembeddedinrealworlddrivingemissionmodel AT jinlinhan energymanagementstrategiesforhybriddieselvehiclesbydynamicplanningembeddedinrealworlddrivingemissionmodel |