This paper designs a novel Nonlinear Robust Fractional-Order Control (NRFOC) for Battery/Superconducting Magnetic Energy Storage (SMES) Hybrid Energy Storage Systems (BSM-HESS) used in Electric Vehicles (EVs). It can track the change of load demand quickly and accurately. First, Rule-Based Strategy (RBS) is adopted to assign the optimal power demand. Then the combined effect of nonlinearities, parameter uncertainties and unmodeled dynamics of BSM-HESS are aggregated into a perturbation, which is rapidly estimated by a High Gain Perturbation Observer (HGPO). The perturbation is fully compensated online by NRFOC. NRFOC does not require an accurate system model. It only needs to measure the battery current and DC bus voltage. Finally, three case studies, including heavy load condition, light load condition and parameter uncertainty, are carried out. Simulation results verify the effectiveness and robustness of NRFOC. This work is supported by National Natural Science Foundation of China (No. 61963020).