Abstract

In order to further improve fuel economy and control system stability of hybrid electric vehicle (HEV), the ant colony algorithm (ACO) is used to optimize the control strategy. Firstly, the logic threshold control strategy is combined with the traditional equivalent fuel consumption minimization strategy (ECMS). On this basis, the ant colony algorithm is used to optimize the charge and discharge equivalent factors of the improved energy management strategy. This research mainly seeks optimization under UDDS conditions, and finally simulates on the ADVISOR platform. In the final simulation results, the improved equivalent fuel consumption minimization strategy based on ant colony algorithm (ACO-ECMS) has higher fuel economy and emission control than the traditional equivalent fuel consumption minimization strategy.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.