Abstract
One of the main technological stumbling blocks in the field of environmentally friendly vehicles is related to the energy storage system. It is in this regard that car manufacturers are mobilizing to improve battery technologies and to accurately predict their behavior. The work proposed in this article deals with the advanced electrothermal modeling of a hybrid energy storage system integrating lithium-ion batteries and supercapacitors. The objective is to allow the aging aspects of the components of this system to be taken into account. The development of a model including the electrothermal behaviors makes it possible to evaluate the progressive degradation of the performance of the hybrid energy storage system. The characterization of both components constituting the hybrid system is carried out via a hybrid particle swarm-Nelder-Mead (PSO-NM) optimization algorithm using the experimental data of an urban electric vehicle. The obtained results show the good performance of the developed model and confirm the feasibility of our approach. The use of the PSO-NM optimization algorithm facilitated the identification of the parameters of the developed model with high efficiency, as the error observed is less than 3%. The advanced model associated with an adapted sizing method can be used in many cases to compare energy management strategies in electric vehicle applications.
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