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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.

In order to research the vibration and noise reduction in pure electric vehicle power-train, a comprehensive work is to simulate the power-train incentive of a high-speed pure electric vehicle, and indicates significant impact of gear mesh system on the power-train NVH performance. Therefore, it is necessary to further study the impact of meshing gear system on electric vehicle power-train vibration and noise performance and seek reasonable methods to reduce the vibration and noise. In this paper, a typical pure electric vehicle's powertrain was used to conduct vibration and noise dynamic simulation. Firstly, the power train model was established considering the gear meshing stiffness, transmission errors, bearing factors and shell flexible, then the vibration and sound radiation dynamic response of power-train was simulated. Based on the accuracy of prediction model, a gear tooth modification was carried out for vibration and noise optimization.

X-in-the-loop (XiL) framework is a new validation concept for vehicle product development, which integrates different virtual and physical components to improve the development efficiency. With XiL platform the requirements of reproducible test, optimization and validation, in which hardware, equipment and test objects are located in different places, could be realized. In the view of different location and communication form of hardware, equipment and test objects, time delay problem exists in the XiL platform, which could have a negative impact on development and validation process. In this paper, a simulation system of time delay prediction and compensation is founded with the help of BP neural network and RBF neural network. With this simulation system the effect of time delay in a vehicle dynamic model as well as tests of geographically distributed vehicle powertrain system is improved during the validation process.

Intelligent and connected vehicle (ICV) and new energy vehicle (NEV) will be two important directions of the automotive technology in the future, and the coordinated development of these two directions reflects relevantly the higher requirements put forward by nowadays society and people. Through the use of intelligent and connected technology (ICT), NEVs can exchange various traffic information data with the outside world (e.g. other running vehicles, road infrastructure, internet, etc.) in real time, which is so-called Vehicle to Everything (V2X). Based on the further analysis of the mutual traffic information, the vehicles can identify the current driving conditions and predict the future driving conditions effectively, which can realize the real time optimization of the energy management strategies (EMSs) of vehicles’ powertrain system, so as to meet the driving requirements of vehicles under different driving conditions.