The stiffness of mounting system determines the vibration isolation ability of the transmitted path, which is the key factor that affects the vibration and noise of vehicle. In order to improve the vibration isolation ability of the powertrain mounting system, considering the powertrain of front wheel drive car as the research object, the vibration decoupling rate and its corresponding frequency of the powertrain mounting system are analyzed by rigid body dynamics and energy method. The correctness of the calculation program with energy method has been verified by calculated vibration decoupling rate. Based on the genetic algorithm and the fusion robustness analysis, the decoupling rate and modal frequency of the mountings in all directions are considered as the objectives; the stiffness of the three mountings is optimally designed. Through multi-excitation of three methods and vehicle test, the vibration response characteristics and the vibration noise test data of the optimization stiffness are compared and the results shown that the vibration isolation performance has been significantly improved more than 10%. An integrated design method of stiffness optimization design and vibration analysis in vehicle PMS is formed, which has theoretical and practical value, and can reduce vehicle vibration and noise.

With the development of multi‐energy technology, the electric‐heat integrated energy system has become an important research direction for multi‐energy joint supply. The dynamic characteristics and energy storage capacity of heat supply network provide potential for joint dispatching of electric heating energy system. Aiming at the problem of electric‐heat joint dispatching, this paper presents an operation optimization model of electric‐heat integrated energy system considering the virtual energy storage characteristics of heat supply network. Firstly, according to the characteristics of transmission delay and user temperature fuzzy, the virtual energy storage characteristics of heat supply network are studied, and a model of the dynamic transfer of energy in the heat system was built. Then, the operation optimization model of the electric‐heat integrated energy system is established to minimize the operation cost. In order to improve the robustness of scheduling optimization results, the Monte Carlo Simulation embedded Quantum Particle Swarm Optimization algorithm is proposed to solve the model. In order to prove the validity of the proposed model, this paper selects a park (a 36 node thermal system) in the northwest region of China as a simulation case. The results show that the operation optimization method considering the virtual energy storage of heat supply network will greatly enhance the complementary potential of the electric‐heat integrated energy system and reduce the operation cost of the system.

Smart campus is an inevitable trend in the development of digital campus construction. The internet of things and cloud computing are the key technologies in the construction of smart campus. The authors expound the concepts of smart campus and put forward overall architecture of smart campus based on the internet of things and cloud computing. They elaborate on the network foundation platform, service platform and the construction of intelligent application platform in detail. Finally, discuss the problems should be noticed in the smart campus construction.

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