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International audienceAmong 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

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International audienceThe hybridization of the conventional thermal vehicles nowadays constitutes a paramount importance for car manufacturers, facing the challenge of minimizing the consumption of the road transport. Although hybrid power train technologies did not converge towards a single solution, series/parallel power trains with power-split electromechanical transmissions prove to be the most promising hybrid technology. In fact, these power trains show maximum power train overall efficiency and maximum fuel reduction in almost all driving conditions compared to the conventional and other hybrid power trains. This paper addresses the model and design of the electro-mechanical configuration of one of the most effective HEV power trains: case study of the 2nd generation Prius. It presents the simulation work of the overall operation of the Toyota Hybrid System (THS-II) of the Prius, and explores not only its power-split eCVT innovative transmission system but also its overall supervision controller for energy management. The kinematic and dynamic behaviors of the THS-II power train are explained based on the power-split aspect of its transmission through a planetary gear train. Then, the possible regular driving functionalities that result from its eCVT operation and the energy flow within its power train are outlined. A feed-forward dynamic model of the studied power train is next proposed, supervised by a rule-based engineering intuition controller. The energy consumption of the THS-II proposed model has been validated by comparing simulation results to published results on European, American and Japanese regulatory driving cycles