Optimized energy management control for the Toyota Hybrid System using dynamic programming on a predicted route with short computation time

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dc.contributor.author Mansour, C.
dc.contributor.author Clodic, D.
dc.date.accessioned 2016-02-04T07:21:57Z
dc.date.available 2016-02-04T07:21:57Z
dc.date.copyright 2012
dc.date.issued 2016-02-16
dc.identifier.issn 1229-9138 en_US
dc.identifier.uri http://hdl.handle.net/10725/3001
dc.description.abstract Among the general problematic of the HEV power trains, the most critical point is the determination of the power-split ratio between the mechanical and the electrical paths, known as the energy management strategy (EMS). Many EMS are proposed in the literature, and can be grouped in two categories: the local optimization EMS and the global optimization EMS. The local optimization category corresponds to the EMS based on human expertise and the knowledge of the power train components efficiency maps. Thus, the local optimization EMS manages the power train operations by referring to predefined rules. The drawback of such strategies is that it brings an instantaneous fuel consumption optimization, and does not fully optimize the fuel consumption over the whole trip. Therefore, additional fuel savings are still possible. This paper presents an overall optimized predictive EMS for the Toyota Hybrid System (THS-II) power train of the Prius. The proposed EMS is based on Dynamic Programming (DP), where the prior knowledge of the route is required in order to predetermine the power-split ratio and optimize the fuel consumption for the whole predicted route. The DP EMS proposed for the THS-II power train is designed with a very short computation time, intended to be implemented in real-time applications. The potential of this DP-controller in reducing fuel consumption on regulatory cycles are computed and compared to a rule-based controller and to the Prius published fuel consumption results. Finally, the fuel reduction enhancements of the DP-controller are computed for real road tests achieved on a MY06 Prius in Ile-de-France, by comparing to the associated observed consumption measurements. en_US
dc.language.iso en en_US
dc.title Optimized energy management control for the Toyota Hybrid System using dynamic programming on a predicted route with short computation time en_US
dc.type Article en_US
dc.description.version Published en_US
dc.author.school SOE en_US
dc.author.idnumber 201001655 en_US
dc.author.woa N/A en_US
dc.author.department Industrial & Mechanical Engineering en_US
dc.description.embargo N/A en_US
dc.relation.journal International Journal of Automotive Technology en_US
dc.journal.volume 13 en_US
dc.journal.issue 2 en_US
dc.article.pages 309-324 en_US
dc.keywords Dynamic programming en_US
dc.keywords Energy consumption savings en_US
dc.keywords Energy management strategy en_US
dc.keywords Hybrid power-split power train en_US
dc.keywords Predictive control en_US
dc.keywords Rule-based control strategy en_US
dc.keywords Road Test measurements en_US
dc.identifier.doi http://dx.doi.org/10.1007/s12239-012-0029-0 en_US
dc.identifier.ctation Mansour, C., & Clodic, D. (2012). Optimized energy management control for the Toyota hybrid system using dynamic programming on a predicted route with short computation time. International Journal of Automotive Technology, 13(2), 309-324. en_US
dc.author.email charbel.mansour@lau.edu.lb
dc.identifier.url http://link.springer.com/article/10.1007/s12239-012-0029-0

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