| In recent years, due to the increasingly serious energy crisis and environment issues, the Electric Vehicle (EV) has been becoming an excellent candidate to alleviate and even solve these problems. However, the dynamic performance and driving mileage can't meet the market requirements because the Hybrid Energy Storage System (HESS) technology is far to be mature and applicable. Therefore, a novel routine to prepare the graphene supercapacitor and new method to conduct the state-of-charge (SOC) estimation of energy storage devices in EV HESS are proposed in this paper.Firstly, the supercapacitor energy storage and working principles are introduced, and then a microwave-assisted routine to synthesize nitrogen-doped graphene. The physical and electrical characterization results show the obtained material presents outstanding internal surface area, cycling stability and energy density. The capacitance density is 208.17F/g and 157.31F/g under the current density of 0.5A/g and 5A/g. After 5000 cycles at the current of 0.5A/g, the capacitance density is kept 98.56% and the ESR is 0.32?.Secondly, on the basis of the working principles of the energy storage devices in HESS, two equivalent models are established, respectively. Furthermore, the model parameter identification is carried out in Recursive Least Square (RLS) and Kalman Filtering methods, and the ultimate SOC estimation is conducted in Unscented Kalman Filtering (UKF) method.Finally, the experiment platform is established, adopting NI PCI 6221 Acquisition Card to collect voltage and current data, employing Lab VIEW and Matlab to conduct the following data processing. The experiment result shows the errors of supercapacitor and battery SOC estimation are limited in the ranges of [-0.94%,0.34%] and [-1.16%,0.85%], and the 2RC model is the best choice for lithium battery. The accurate experiment result demonstrates the effectiveness of estimation system and could provide precise SOC information for control strategy. |
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