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A way to improve existing hybrid vehicles is by globally optimizing the design of their components in relation to their actual use. This paper proposes a global optimal design method for power-split hybrid electric vehicles (PS-HEVs) equipped with an electric variable transmission (EVT). A genetic algorithm is used to optimize system parameters. The process includes discrete dynamic programming (DDP) for optimal energy management. The optimization focuses on minimizing fuel consumption and the number of battery cells. Pareto fronts are depicted and compared for different drive cycles, and they show the existence of a possible tradeoff between fuel consumption and battery size. [ABSTRACT FROM AUTHOR]

Automotive engineers and researchers have proposed different topologies for series–parallel hybrid electric vehicles (SP-HEVs). The Toyota Hybrid System (THS) is the best known SP-HEV-based vehicle, but alternative solutions, such as electric variable transmission (EVT), have been also proposed. An efficient comparison between these different solutions is a key point to estimate the added value of each topology. This paper presents the application of optimal control to two series–parallel hybrid architectures for efficiency assessment purposes. The dynamic programming method is applied to the THS and to a virtual hybrid vehicle with an EVT. The way to take into account the supplementary degree of freedom provided by the decoupling of the wheels and the engine in both topologies is presented. The optimal fuel consumption is then compared on different driving cycles and brings out an overconsumption of the EVT topology. Then, a parametric study shows that inserting an appropriate gear ratio on the internal-combustion-engine (ICE) shaft can improve the EVT efficiency that becomes close to the THS efficiency. [ABSTRACT FROM PUBLISHER]