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X-in-the-loop (XiL) framework is a validation concept for vehicle product development, which integrates different virtual and physical components to improve the development efficiency. In order to develop and validate an extended validation method based on XiL, Tongji University in Shanghai, China and the Karlsruhe Institute of Technology (KIT) in Karlsruhe, Germany co- performed a feasibility study about an X-in-the-distance-loop demonstration platform. The X-in-the-distance-loop demonstration platform includes a MATLAB/Simulink software platform and geographically distributed equipment (driver simulator, driving electric motor and dynamometer test stand), which are used to conduct bidirectional experiments to test communication of powertrain data between China and Germany.

Most of the existing energy management strategies for Extended-Range Electric Vehicles (E-REVs) are heuristic, which restricts coordination between the battery and the Range Extender. This paper presents an instantaneous optimization energy management strategy based on the Minimum Loss Power Algorithm (MLPA) for a fuel cell E-REV. An instantaneous loss power function of power train system is constructed by considering the charge and discharge efficiency of the battery, together with the working efficiency of the fuel cell Range Extender. The battery working mode and operating points of the fuel cell Range Extender are decided by an instantaneous optimization module (an artificial neural network) that aims to minimize the loss power function at each time step.