College of Mechanical and Electrical Engineering, Central South University of Forestry and Technology, Changsha, 410004, China
BibTex Citation Data :
@article{IJRED60463, author = {Yuxin Ge}, title = {Adaptive control of plug-in hybrid electric vehicles based on energy management strategy and dynamic programming algorithm}, journal = {International Journal of Renewable Energy Development}, volume = {13}, number = {6}, year = {2024}, keywords = {Electric vehicles; Consumption; DP algorithm; Energy management; Control; efficiency}, abstract = { This study mainly analyses the fuel consumption of plug-in hybrid vehicles during operation. A new control method for automobiles based on energy management strategy and dynamic programming algorithm is proposed. The new method plans and analyses the minimum electricity consumption, and then uses dynamic programming algorithms to analyse this parameter. The research results indicated that the vehicle state was constantly changing with the variation of SOC value during driving. The energy mobilization of the vehicle was more obvious after adding dynamic programming strategy. The efficiency of the vehicle was relatively high in driving state 1, with a minimum value of 70%, which was about 20% higher than in driving state 4. The average fuel consumption in driving state 2 was 1.8L higher than in other driving states. The overall efficiency of automobiles after incorporating dynamic programming was improved, with a shorter time to reach the lowest efficiency point compared with not incorporating dynamic programming algorithms. The highest efficiency value was 7.86% higher than that of not incorporating dynamic programming models. The new control method can reduce energy consumption and improve the energy management and control effect. The study provides a better research direction for energy management and control of hybrid electric vehicles in the future. }, pages = {1104--1114} doi = {10.61435/ijred.2024.60463}, url = {https://ijred.cbiore.id/index.php/ijred/article/view/60463} }
Refworks Citation Data :
This study mainly analyses the fuel consumption of plug-in hybrid vehicles during operation. A new control method for automobiles based on energy management strategy and dynamic programming algorithm is proposed. The new method plans and analyses the minimum electricity consumption, and then uses dynamic programming algorithms to analyse this parameter. The research results indicated that the vehicle state was constantly changing with the variation of SOC value during driving. The energy mobilization of the vehicle was more obvious after adding dynamic programming strategy. The efficiency of the vehicle was relatively high in driving state 1, with a minimum value of 70%, which was about 20% higher than in driving state 4. The average fuel consumption in driving state 2 was 1.8L higher than in other driving states. The overall efficiency of automobiles after incorporating dynamic programming was improved, with a shorter time to reach the lowest efficiency point compared with not incorporating dynamic programming algorithms. The highest efficiency value was 7.86% higher than that of not incorporating dynamic programming models. The new control method can reduce energy consumption and improve the energy management and control effect. The study provides a better research direction for energy management and control of hybrid electric vehicles in the future.
Article Metrics:
Last update:
Last update: 2024-12-10 14:16:25
This journal provides immediate open access to its content on the principle that making research freely available to the public supports a greater global exchange of knowledge. Articles are freely available to both subscribers and the wider public with permitted reuse.
All articles published Open Access will be immediately and permanently free for everyone to read and download. We are continuously working with our author communities to select the best choice of license options: Creative Commons Attribution-ShareAlike (CC BY-SA). Authors and readers can copy and redistribute the material in any medium or format, as well as remix, transform, and build upon the material for any purpose, even commercially, but they must give appropriate credit (cite to the article or content), provide a link to the license, and indicate if changes were made. If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.
International Journal of Renewable Energy Development (ISSN:2252-4940) published by CBIORE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.