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The energy storage system (ESS), as well as its efficient management, represents a key factor for the success of electric vehicles. Due to well-known technological constraints in ESSs, there has been a growing interest in combining various types of energy sources with complementary features. Among the many possible combinations, our interest here lies in the hybridization of batteries and supercapacitors (SCs) with an active parallel arrangement, i.e., the sources are connected to the direct current (dc) bus through two bidirectional dc-dc converters (step-up). Based on this ESS topology, a robust dc-link controller is employed to regulate the dc-bus voltage and track the SCs current in spite of uncertainties in the system. For this purpose, we start by showing that the converters' uncertainty, e.g., the powertrain load, can be modeled as a convex polytope. The dc-link controller is then posed as a robust linear-quadratic regulator problem and, by exploring the convex polytope, converted in a linear matrix inequalities framework, which can efficiently be solved by numerical means. Finally, the operation envelope of the controller is extended by scheduling the gains according to the energy sources' voltages, which is an important feature to cope with the voltage variations in the SCs. To analyze the performance of the control architecture, a reduced-scale prototype was built. The experimental results show that, compared with the nonrobust and non-gain-scheduled controllers, the proposed dc-link controller offers better transient response and robustness to disturbances. Furthermore, the global performance of the controller is evaluated during certain driving cycles.